Functional architecture of Escherichia coli: new insights provided by a natural decomposition approach.

PubMed

Freyre-González, Julio A; Alonso-Pavón, José A; Treviño-Quintanilla, Luis G; Collado-Vides, Julio

2008-10-27

Previous studies have used different methods in an effort to extract the modular organization of transcriptional regulatory networks. However, these approaches are not natural, as they try to cluster strongly connected genes into a module or locate known pleiotropic transcription factors in lower hierarchical layers. Here, we unravel the transcriptional regulatory network of Escherichia coli by separating it into its key elements, thus revealing its natural organization. We also present a mathematical criterion, based on the topological features of the transcriptional regulatory network, to classify the network elements into one of two possible classes: hierarchical or modular genes. We found that modular genes are clustered into physiologically correlated groups validated by a statistical analysis of the enrichment of the functional classes. Hierarchical genes encode transcription factors responsible for coordinating module responses based on general interest signals. Hierarchical elements correlate highly with the previously studied global regulators, suggesting that this could be the first mathematical method to identify global regulators. We identified a new element in transcriptional regulatory networks never described before: intermodular genes. These are structural genes that integrate, at the promoter level, signals coming from different modules, and therefore from different physiological responses. Using the concept of pleiotropy, we have reconstructed the hierarchy of the network and discuss the role of feedforward motifs in shaping the hierarchical backbone of the transcriptional regulatory network. This study sheds new light on the design principles underpinning the organization of transcriptional regulatory networks, showing a novel nonpyramidal architecture composed of independent modules globally governed by hierarchical transcription factors, whose responses are integrated by intermodular genes.

Contributions of sociodemographic factors to criminal behavior

PubMed Central

Mundia, Lawrence; Matzin, Rohani; Mahalle, Salwa; Hamid, Malai Hayati; Osman, Ratna Suriani

2016-01-01

We explored the extent to which prisoner sociodemographic variables (age, education, marital status, employment, and whether their parents were married or not) influenced offending in 64 randomly selected Brunei inmates, comprising both sexes. A quantitative field survey design ideal for the type of participants used in a prison context was employed to investigate the problem. Hierarchical multiple regression analysis with backward elimination identified prisoner marital status and age groups as significantly related to offending. Furthermore, hierarchical multinomial logistic regression analysis with backward elimination indicated that prisoners’ age, primary level education, marital status, employment status, and parental marital status as significantly related to stealing offenses with high odds ratios. All 29 nonrecidivists were false negatives and predicted to reoffend upon release. Similarly, all 33 recidivists were projected to reoffend after release. Hierarchical binary logistic regression analysis revealed age groups (24–29 years and 30–35 years), employed prisoner, and primary level education as variables with high likelihood trends for reoffending. The results suggested that prisoner interventions (educational, counseling, and psychotherapy) in Brunei should treat not only antisocial personality, psychopathy, and mental health problems but also sociodemographic factors. The study generated offending patterns, trends, and norms that may inform subsequent investigations on Brunei prisoners. PMID:27382342

Mind the Gap! A Multilevel Analysis of Factors Related to Variation in Published Cost-Effectiveness Estimates within and between Countries.

PubMed

Boehler, Christian E H; Lord, Joanne

2016-01-01

Published cost-effectiveness estimates can vary considerably, both within and between countries. Despite extensive discussion, little is known empirically about factors relating to these variations. To use multilevel statistical modeling to integrate cost-effectiveness estimates from published economic evaluations to investigate potential causes of variation. Cost-effectiveness studies of statins for cardiovascular disease prevention were identified by systematic review. Estimates of incremental costs and effects were extracted from reported base case, sensitivity, and subgroup analyses, with estimates grouped in studies and in countries. Three bivariate models were developed: a cross-classified model to accommodate data from multinational studies, a hierarchical model with multinational data allocated to a single category at country level, and a hierarchical model excluding multinational data. Covariates at different levels were drawn from a long list of factors suggested in the literature. We found 67 studies reporting 2094 cost-effectiveness estimates relating to 23 countries (6 studies reporting for more than 1 country). Data and study-level covariates included patient characteristics, intervention and comparator cost, and some study methods (e.g., discount rates and time horizon). After adjusting for these factors, the proportion of variation attributable to countries was negligible in the cross-classified model but moderate in the hierarchical models (14%-19% of total variance). Country-level variables that improved the fit of the hierarchical models included measures of income and health care finance, health care resources, and population risks. Our analysis suggested that variability in published cost-effectiveness estimates is related more to differences in study methods than to differences in national context. Multinational studies were associated with much lower country-level variation than single-country studies. These findings are for a single clinical question and may be atypical. © The Author(s) 2015.

Cluster analysis of spontaneous preterm birth phenotypes identifies potential associations among preterm birth mechanisms

PubMed Central

Esplin, M Sean; Manuck, Tracy A.; Varner, Michael W.; Christensen, Bryce; Biggio, Joseph; Bukowski, Radek; Parry, Samuel; Zhang, Heping; Huang, Hao; Andrews, William; Saade, George; Sadovsky, Yoel; Reddy, Uma M.; Ilekis, John

2015-01-01

Objective We sought to employ an innovative tool based on common biological pathways to identify specific phenotypes among women with spontaneous preterm birth (SPTB), in order to enhance investigators' ability to identify to highlight common mechanisms and underlying genetic factors responsible for SPTB. Study Design A secondary analysis of a prospective case-control multicenter study of SPTB. All cases delivered a preterm singleton at SPTB ≤34.0 weeks gestation. Each woman was assessed for the presence of underlying SPTB etiologies. A hierarchical cluster analysis was used to identify groups of women with homogeneous phenotypic profiles. One of the phenotypic clusters was selected for candidate gene association analysis using VEGAS software. Results 1028 women with SPTB were assigned phenotypes. Hierarchical clustering of the phenotypes revealed five major clusters. Cluster 1 (N=445) was characterized by maternal stress, cluster 2 (N=294) by premature membrane rupture, cluster 3 (N=120) by familial factors, and cluster 4 (N=63) by maternal comorbidities. Cluster 5 (N=106) was multifactorial, characterized by infection (INF), decidual hemorrhage (DH) and placental dysfunction (PD). These three phenotypes were highly correlated by Chi-square analysis [PD and DH (p<2.2e-6); PD and INF (p=6.2e-10); INF and DH (p=0.0036)]. Gene-based testing identified the INS (insulin) gene as significantly associated with cluster 3 of SPTB. Conclusion We identified 5 major clusters of SPTB based on a phenotype tool and hierarchal clustering. There was significant correlation between several of the phenotypes. The INS gene was associated with familial factors underlying SPTB. PMID:26070700

Generative models for discovering sparse distributed representations.

PubMed Central

Hinton, G E; Ghahramani, Z

1997-01-01

We describe a hierarchical, generative model that can be viewed as a nonlinear generalization of factor analysis and can be implemented in a neural network. The model uses bottom-up, top-down and lateral connections to perform Bayesian perceptual inference correctly. Once perceptual inference has been performed the connection strengths can be updated using a very simple learning rule that only requires locally available information. We demonstrate that the network learns to extract sparse, distributed, hierarchical representations. PMID:9304685

Using Refined Regression Analysis To Assess The Ecological Services Of Restored Wetlands

EPA Science Inventory

A hierarchical approach to regression analysis of wetland water treatment was conducted to determine which factors are the most appropriate for characterizing wetlands of differing structure and function. We used this approach in an effort to identify the types and characteristi...

Verbal Neuropsychological Functions in Aphasia: An Integrative Model

ERIC Educational Resources Information Center

Vigliecca, Nora Silvana; Báez, Sandra

2015-01-01

A theoretical framework which considers the verbal functions of the brain under a multivariate and comprehensive cognitive model was statistically analyzed. A confirmatory factor analysis was performed to verify whether some recognized aphasia constructs can be hierarchically integrated as latent factors from a homogenously verbal test. The Brief…

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…

Functions of Marijuana Use in College Students

ERIC Educational Resources Information Center

Bates, Julie K.; Accordino, Michael P.; Hewes, Robert L.

2010-01-01

Hierarchical regression analysis was used to test the hypothesis that specific functional factors of marijuana use would predict past 30-day marijuana use in 425 college students more precisely than demographic variables alone. This hypothesis was confirmed. Functional factors of personal/physical enhancement as well as activity enhancement were…

Clusters of Occupations Based on Systematically Derived Work Dimensions: An Exploratory Study.

ERIC Educational Resources Information Center

Cunningham, J. W.; And Others

The study explored the feasibility of deriving an educationally relevant occupational cluster structure based on Occupational Analysis Inventory (OAI) work dimensions. A hierarchical cluster analysis was applied to the factor score profiles of 814 occupations on 22 higher-order OAI work dimensions. From that analysis, 73 occupational clusters were…

Cluster analysis of spontaneous preterm birth phenotypes identifies potential associations among preterm birth mechanisms.

PubMed

Esplin, M Sean; Manuck, Tracy A; Varner, Michael W; Christensen, Bryce; Biggio, Joseph; Bukowski, Radek; Parry, Samuel; Zhang, Heping; Huang, Hao; Andrews, William; Saade, George; Sadovsky, Yoel; Reddy, Uma M; Ilekis, John

2015-09-01

We sought to use an innovative tool that is based on common biologic pathways to identify specific phenotypes among women with spontaneous preterm birth (SPTB) to enhance investigators' ability to identify and to highlight common mechanisms and underlying genetic factors that are responsible for SPTB. We performed a secondary analysis of a prospective case-control multicenter study of SPTB. All cases delivered a preterm singleton at SPTB ≤34.0 weeks' gestation. Each woman was assessed for the presence of underlying SPTB causes. A hierarchic cluster analysis was used to identify groups of women with homogeneous phenotypic profiles. One of the phenotypic clusters was selected for candidate gene association analysis with the use of VEGAS software. One thousand twenty-eight women with SPTB were assigned phenotypes. Hierarchic clustering of the phenotypes revealed 5 major clusters. Cluster 1 (n = 445) was characterized by maternal stress; cluster 2 (n = 294) was characterized by premature membrane rupture; cluster 3 (n = 120) was characterized by familial factors, and cluster 4 (n = 63) was characterized by maternal comorbidities. Cluster 5 (n = 106) was multifactorial and characterized by infection (INF), decidual hemorrhage (DH), and placental dysfunction (PD). These 3 phenotypes were correlated highly by χ(2) analysis (PD and DH, P < 2.2e-6; PD and INF, P = 6.2e-10; INF and DH, (P = .0036). Gene-based testing identified the INS (insulin) gene as significantly associated with cluster 3 of SPTB. We identified 5 major clusters of SPTB based on a phenotype tool and hierarch clustering. There was significant correlation between several of the phenotypes. The INS gene was associated with familial factors that were underlying SPTB. Copyright © 2015 Elsevier Inc. All rights reserved.

A comparison of hierarchical cluster analysis and league table rankings as methods for analysis and presentation of district health system performance data in Uganda.

PubMed

Tashobya, Christine K; Dubourg, Dominique; Ssengooba, Freddie; Speybroeck, Niko; Macq, Jean; Criel, Bart

2016-03-01

In 2003, the Uganda Ministry of Health introduced the district league table for district health system performance assessment. The league table presents district performance against a number of input, process and output indicators and a composite index to rank districts. This study explores the use of hierarchical cluster analysis for analysing and presenting district health systems performance data and compares this approach with the use of the league table in Uganda. Ministry of Health and district plans and reports, and published documents were used to provide information on the development and utilization of the Uganda district league table. Quantitative data were accessed from the Ministry of Health databases. Statistical analysis using SPSS version 20 and hierarchical cluster analysis, utilizing Wards' method was used. The hierarchical cluster analysis was conducted on the basis of seven clusters determined for each year from 2003 to 2010, ranging from a cluster of good through moderate-to-poor performers. The characteristics and membership of clusters varied from year to year and were determined by the identity and magnitude of performance of the individual variables. Criticisms of the league table include: perceived unfairness, as it did not take into consideration district peculiarities; and being oversummarized and not adequately informative. Clustering organizes the many data points into clusters of similar entities according to an agreed set of indicators and can provide the beginning point for identifying factors behind the observed performance of districts. Although league table ranking emphasize summation and external control, clustering has the potential to encourage a formative, learning approach. More research is required to shed more light on factors behind observed performance of the different clusters. Other countries especially low-income countries that share many similarities with Uganda can learn from these experiences. © The Author 2015. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine.

A comparison of hierarchical cluster analysis and league table rankings as methods for analysis and presentation of district health system performance data in Uganda†

PubMed Central

Tashobya, Christine K; Dubourg, Dominique; Ssengooba, Freddie; Speybroeck, Niko; Macq, Jean; Criel, Bart

2016-01-01

In 2003, the Uganda Ministry of Health introduced the district league table for district health system performance assessment. The league table presents district performance against a number of input, process and output indicators and a composite index to rank districts. This study explores the use of hierarchical cluster analysis for analysing and presenting district health systems performance data and compares this approach with the use of the league table in Uganda. Ministry of Health and district plans and reports, and published documents were used to provide information on the development and utilization of the Uganda district league table. Quantitative data were accessed from the Ministry of Health databases. Statistical analysis using SPSS version 20 and hierarchical cluster analysis, utilizing Wards’ method was used. The hierarchical cluster analysis was conducted on the basis of seven clusters determined for each year from 2003 to 2010, ranging from a cluster of good through moderate-to-poor performers. The characteristics and membership of clusters varied from year to year and were determined by the identity and magnitude of performance of the individual variables. Criticisms of the league table include: perceived unfairness, as it did not take into consideration district peculiarities; and being oversummarized and not adequately informative. Clustering organizes the many data points into clusters of similar entities according to an agreed set of indicators and can provide the beginning point for identifying factors behind the observed performance of districts. Although league table ranking emphasize summation and external control, clustering has the potential to encourage a formative, learning approach. More research is required to shed more light on factors behind observed performance of the different clusters. Other countries especially low-income countries that share many similarities with Uganda can learn from these experiences. PMID:26024882

Conceptual hierarchical modeling to describe wetland plant community organization

USGS Publications Warehouse

Little, A.M.; Guntenspergen, G.R.; Allen, T.F.H.

2010-01-01

Using multivariate analysis, we created a hierarchical modeling process that describes how differently-scaled environmental factors interact to affect wetland-scale plant community organization in a system of small, isolated wetlands on Mount Desert Island, Maine. We followed the procedure: 1) delineate wetland groups using cluster analysis, 2) identify differently scaled environmental gradients using non-metric multidimensional scaling, 3) order gradient hierarchical levels according to spatiotem-poral scale of fluctuation, and 4) assemble hierarchical model using group relationships with ordination axes and post-hoc tests of environmental differences. Using this process, we determined 1) large wetland size and poor surface water chemistry led to the development of shrub fen wetland vegetation, 2) Sphagnum and water chemistry differences affected fen vs. marsh / sedge meadows status within small wetlands, and 3) small-scale hydrologic differences explained transitions between forested vs. non-forested and marsh vs. sedge meadow vegetation. This hierarchical modeling process can help explain how upper level contextual processes constrain biotic community response to lower-level environmental changes. It creates models with more nuanced spatiotemporal complexity than classification and regression tree procedures. Using this process, wetland scientists will be able to generate more generalizable theories of plant community organization, and useful management models. ?? Society of Wetland Scientists 2009.

The contribution of reinforcement sensitivity to the personality-psychopathology hierarchical structure in childhood and adolescence.

PubMed

Slobodskaya, Helena R

2016-11-01

This study examined the contribution of reinforcement sensitivity to the hierarchical structure of child personality and common psychopathology in community samples of parent reports of children aged 2-18 (N = 968) and self-reports of adolescents aged 10-18 (N = 1,543) using the Inventory of Child Individual Differences-Short version (ICID-S), the Strengths and Difficulties Questionnaire (SDQ), and the Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ). A joint higher-order factor analysis of the ICID-S and SDQ scales suggested a 4-factor solution; congruence coefficients indicated replicability of the factors across the 2 samples at all levels of the personality-psychopathology hierarchy. The canonical correlation analyses indicated that reinforcement sensitivity and personality-psychopathology dimensions shared much of their variance. The main contribution of reinforcement sensitivity was through opposing effects of reward and punishment sensitivities. The superordinate factors Beta and Internalizing were best predicted by reinforcement sensitivity, followed by the Externalizing and Positive personality factors. These findings provide evidence for consistency of the hierarchical structure of personality and common psychopathology across informants and highlight the role of reinforcement systems in the development of normal and abnormal patterns of behavior and affect. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Reliability and Validity of the Chinese Version of the Solution-Focused Inventory in College Students

ERIC Educational Resources Information Center

Yang, Hongfei; Hai, Tang

2015-01-01

The psychometrics of the Chinese Solution-Focused Inventory (CSFI) was studied in Chinese college students. Confirmatory factor analysis confirmed the 3-factor structure. All subscales showed good reliability and convergent and incremental validity. Results of hierarchical regression analyses indicated that the 3 subscales accounted for additional…

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…

The Trait Emotional Intelligence Questionnaire: Internal Structure, Convergent, Criterion, and Incremental Validity in an Italian Sample

ERIC Educational Resources Information Center

Andrei, Federica; Smith, Martin M.; Surcinelli, Paola; Baldaro, Bruno; Saklofske, Donald H.

2016-01-01

This study investigated the structure and validity of the Italian translation of the Trait Emotional Intelligence Questionnaire. Data were self-reported from 227 participants. Confirmatory factor analysis supported the four-factor structure of the scale. Hierarchical regressions also demonstrated its incremental validity beyond demographics, the…

Measurement Invariance of the "Servant Leadership Questionnaire" across K-12 Principal Gender

ERIC Educational Resources Information Center

Xu, Lihua; Stewart, Trae; Haber-Curran, Paige

2015-01-01

Measurement invariance of the five-factor "Servant Leadership Questionnaire" between female and male K-12 principals was tested using multi-group confirmatory factor analysis. A sample of 956 principals (56.9% were females and 43.1% were males) was analysed in this study. The hierarchical multi-step measurement invariance test supported…

Coma Recovery Scale-Revised: evidentiary support for hierarchical grading of level of consciousness.

PubMed

Gerrard, Paul; Zafonte, Ross; Giacino, Joseph T

2014-12-01

To investigate the neurobehavioral pattern of recovery of consciousness as reflected by performance on the subscales of the Coma Recovery Scale-Revised (CRS-R). Retrospective item response theory (IRT) and factor analysis. Inpatient rehabilitation facilities. Rehabilitation inpatients (N=180) with posttraumatic disturbance in consciousness who participated in a double-blinded, randomized, controlled drug trial. Not applicable. Scores on CRS-R subscales. The CRS-R was found to fit factor analytic models adhering to the assumptions of unidimensionality and monotonicity. In addition, subscales were mutually independent based on residual correlations. Nonparametric IRT reaffirmed the finding of monotonicity. A highly constrained confirmatory factor analysis model, which imposed equal factor loadings on all items, was found to fit the data well and was used to estimate a 1-parameter IRT model. This study provides evidence of the unidimensionality of the CRS-R and supports the hierarchical structure of the CRS-R subscales, suggesting that it is an effective tool for establishing diagnosis and monitoring recovery of consciousness after severe traumatic brain injury. Copyright © 2014 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Mind the Gap! A Multilevel Analysis of Factors Related to Variation in Published Cost-Effectiveness Estimates within and between Countries

PubMed Central

Boehler, Christian E. H.; Lord, Joanne

2016-01-01

Background. Published cost-effectiveness estimates can vary considerably, both within and between countries. Despite extensive discussion, little is known empirically about factors relating to these variations. Objectives. To use multilevel statistical modeling to integrate cost-effectiveness estimates from published economic evaluations to investigate potential causes of variation. Methods. Cost-effectiveness studies of statins for cardiovascular disease prevention were identified by systematic review. Estimates of incremental costs and effects were extracted from reported base case, sensitivity, and subgroup analyses, with estimates grouped in studies and in countries. Three bivariate models were developed: a cross-classified model to accommodate data from multinational studies, a hierarchical model with multinational data allocated to a single category at country level, and a hierarchical model excluding multinational data. Covariates at different levels were drawn from a long list of factors suggested in the literature. Results. We found 67 studies reporting 2094 cost-effectiveness estimates relating to 23 countries (6 studies reporting for more than 1 country). Data and study-level covariates included patient characteristics, intervention and comparator cost, and some study methods (e.g., discount rates and time horizon). After adjusting for these factors, the proportion of variation attributable to countries was negligible in the cross-classified model but moderate in the hierarchical models (14%−19% of total variance). Country-level variables that improved the fit of the hierarchical models included measures of income and health care finance, health care resources, and population risks. Conclusions. Our analysis suggested that variability in published cost-effectiveness estimates is related more to differences in study methods than to differences in national context. Multinational studies were associated with much lower country-level variation than single-country studies. These findings are for a single clinical question and may be atypical. PMID:25878194

Clustering, hierarchical organization, and the topography of abstract and concrete nouns.

PubMed

Troche, Joshua; Crutch, Sebastian; Reilly, Jamie

2014-01-01

The empirical study of language has historically relied heavily upon concrete word stimuli. By definition, concrete words evoke salient perceptual associations that fit well within feature-based, sensorimotor models of word meaning. In contrast, many theorists argue that abstract words are "disembodied" in that their meaning is mediated through language. We investigated word meaning as distributed in multidimensional space using hierarchical cluster analysis. Participants (N = 365) rated target words (n = 400 English nouns) across 12 cognitive dimensions (e.g., polarity, ease of teaching, emotional valence). Factor reduction revealed three latent factors, corresponding roughly to perceptual salience, affective association, and magnitude. We plotted the original 400 words for the three latent factors. Abstract and concrete words showed overlap in their topography but also differentiated themselves in semantic space. This topographic approach to word meaning offers a unique perspective to word concreteness.

The Internet and Services Marketing--The Case of Danish Retail Banking.

ERIC Educational Resources Information Center

Mols, Niels Peter

2000-01-01

Examines various aspects of the motives, perceptions, and expectations connected with the introduction of Internet banking in Danish retail banking. Responses from questionnaires and results from a factor analysis and a hierarchical cluster analysis indicate a belief that Internet banking will become more important in the future. (Author/LRW)

Modeling Associations among Multivariate Longitudinal Categorical Variables in Survey Data: A Semiparametric Bayesian Approach

ERIC Educational Resources Information Center

Tchumtchoua, Sylvie; Dey, Dipak K.

2012-01-01

This paper proposes a semiparametric Bayesian framework for the analysis of associations among multivariate longitudinal categorical variables in high-dimensional data settings. This type of data is frequent, especially in the social and behavioral sciences. A semiparametric hierarchical factor analysis model is developed in which the…

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…

Using Structural Equation Modeling to Validate Online Game Players' Motivations Relative to Self-Concept and Life Adaptation

ERIC Educational Resources Information Center

Yang, Shu Ching; Huang, Chiao Ling

2013-01-01

This study aimed to validate a systematic instrument to measure online players' motivations for playing online games (MPOG) and examine how the interplay of differential motivations impacts young gamers' self-concept and life adaptation. Confirmatory factor analysis determined that a hierarchical model with a two-factor structure of…

Causal Relation Analysis Tool of the Case Study in the Engineer Ethics Education

NASA Astrophysics Data System (ADS)

Suzuki, Yoshio; Morita, Keisuke; Yasui, Mitsukuni; Tanada, Ichirou; Fujiki, Hiroyuki; Aoyagi, Manabu

In engineering ethics education, the virtual experiencing of dilemmas is essential. Learning through the case study method is a particularly effective means. Many case studies are, however, difficult to deal with because they often include many complex causal relationships and social factors. It would thus be convenient if there were a tool that could analyze the factors of a case example and organize them into a hierarchical structure to get a better understanding of the whole picture. The tool that was developed applies a cause-and-effect matrix and simple graph theory. It analyzes the causal relationship between facts in a hierarchical structure and organizes complex phenomena. The effectiveness of this tool is shown by presenting an actual example.

Dynamic and quantitative method of analyzing service consistency evolution based on extended hierarchical finite state automata.

PubMed

Fan, Linjun; Tang, Jun; Ling, Yunxiang; Li, Benxian

2014-01-01

This paper is concerned with the dynamic evolution analysis and quantitative measurement of primary factors that cause service inconsistency in service-oriented distributed simulation applications (SODSA). Traditional methods are mostly qualitative and empirical, and they do not consider the dynamic disturbances among factors in service's evolution behaviors such as producing, publishing, calling, and maintenance. Moreover, SODSA are rapidly evolving in terms of large-scale, reusable, compositional, pervasive, and flexible features, which presents difficulties in the usage of traditional analysis methods. To resolve these problems, a novel dynamic evolution model extended hierarchical service-finite state automata (EHS-FSA) is constructed based on finite state automata (FSA), which formally depict overall changing processes of service consistency states. And also the service consistency evolution algorithms (SCEAs) based on EHS-FSA are developed to quantitatively assess these impact factors. Experimental results show that the bad reusability (17.93% on average) is the biggest influential factor, the noncomposition of atomic services (13.12%) is the second biggest one, and the service version's confusion (1.2%) is the smallest one. Compared with previous qualitative analysis, SCEAs present good effectiveness and feasibility. This research can guide the engineers of service consistency technologies toward obtaining a higher level of consistency in SODSA.

Dynamic and Quantitative Method of Analyzing Service Consistency Evolution Based on Extended Hierarchical Finite State Automata

PubMed Central

Fan, Linjun; Tang, Jun; Ling, Yunxiang; Li, Benxian

2014-01-01

This paper is concerned with the dynamic evolution analysis and quantitative measurement of primary factors that cause service inconsistency in service-oriented distributed simulation applications (SODSA). Traditional methods are mostly qualitative and empirical, and they do not consider the dynamic disturbances among factors in service's evolution behaviors such as producing, publishing, calling, and maintenance. Moreover, SODSA are rapidly evolving in terms of large-scale, reusable, compositional, pervasive, and flexible features, which presents difficulties in the usage of traditional analysis methods. To resolve these problems, a novel dynamic evolution model extended hierarchical service-finite state automata (EHS-FSA) is constructed based on finite state automata (FSA), which formally depict overall changing processes of service consistency states. And also the service consistency evolution algorithms (SCEAs) based on EHS-FSA are developed to quantitatively assess these impact factors. Experimental results show that the bad reusability (17.93% on average) is the biggest influential factor, the noncomposition of atomic services (13.12%) is the second biggest one, and the service version's confusion (1.2%) is the smallest one. Compared with previous qualitative analysis, SCEAs present good effectiveness and feasibility. This research can guide the engineers of service consistency technologies toward obtaining a higher level of consistency in SODSA. PMID:24772033

Combination of automated high throughput platforms, flow cytometry, and hierarchical clustering to detect cell state.

PubMed

Kitsos, Christine M; Bhamidipati, Phani; Melnikova, Irena; Cash, Ethan P; McNulty, Chris; Furman, Julia; Cima, Michael J; Levinson, Douglas

2007-01-01

This study examined whether hierarchical clustering could be used to detect cell states induced by treatment combinations that were generated through automation and high-throughput (HT) technology. Data-mining techniques were used to analyze the large experimental data sets to determine whether nonlinear, non-obvious responses could be extracted from the data. Unary, binary, and ternary combinations of pharmacological factors (examples of stimuli) were used to induce differentiation of HL-60 cells using a HT automated approach. Cell profiles were analyzed by incorporating hierarchical clustering methods on data collected by flow cytometry. Data-mining techniques were used to explore the combinatorial space for nonlinear, unexpected events. Additional small-scale, follow-up experiments were performed on cellular profiles of interest. Multiple, distinct cellular profiles were detected using hierarchical clustering of expressed cell-surface antigens. Data-mining of this large, complex data set retrieved cases of both factor dominance and cooperativity, as well as atypical cellular profiles. Follow-up experiments found that treatment combinations producing "atypical cell types" made those cells more susceptible to apoptosis. CONCLUSIONS Hierarchical clustering and other data-mining techniques were applied to analyze large data sets from HT flow cytometry. From each sample, the data set was filtered and used to define discrete, usable states that were then related back to their original formulations. Analysis of resultant cell populations induced by a multitude of treatments identified unexpected phenotypes and nonlinear response profiles.

A hierarchical clustering scheme approach to assessment of IP-network traffic using detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Takuma, Takehisa; Masugi, Masao

2009-03-01

This paper presents an approach to the assessment of IP-network traffic in terms of the time variation of self-similarity. To get a comprehensive view in analyzing the degree of long-range dependence (LRD) of IP-network traffic, we use a hierarchical clustering scheme, which provides a way to classify high-dimensional data with a tree-like structure. Also, in the LRD-based analysis, we employ detrended fluctuation analysis (DFA), which is applicable to the analysis of long-range power-law correlations or LRD in non-stationary time-series signals. Based on sequential measurements of IP-network traffic at two locations, this paper derives corresponding values for the LRD-related parameter α that reflects the degree of LRD of measured data. In performing the hierarchical clustering scheme, we use three parameters: the α value, average throughput, and the proportion of network traffic that exceeds 80% of network bandwidth for each measured data set. We visually confirm that the traffic data can be classified in accordance with the network traffic properties, resulting in that the combined depiction of the LRD and other factors can give us an effective assessment of network conditions at different times.

Stability and structural properties of gene regulation networks with coregulation rules.

PubMed

Warrell, Jonathan; Mhlanga, Musa

2017-05-07

Coregulation of the expression of groups of genes has been extensively demonstrated empirically in bacterial and eukaryotic systems. Such coregulation can arise through the use of shared regulatory motifs, which allow the coordinated expression of modules (and module groups) of functionally related genes across the genome. Coregulation can also arise through the physical association of multi-gene complexes through chromosomal looping, which are then transcribed together. We present a general formalism for modeling coregulation rules in the framework of Random Boolean Networks (RBN), and develop specific models for transcription factor networks with modular structure (including module groups, and multi-input modules (MIM) with autoregulation) and multi-gene complexes (including hierarchical differentiation between multi-gene complex members). We develop a mean-field approach to analyse the dynamical stability of large networks incorporating coregulation, and show that autoregulated MIM and hierarchical gene-complex models can achieve greater stability than networks without coregulation whose rules have matching activation frequency. We provide further analysis of the stability of small networks of both kinds through simulations. We also characterize several general properties of the transients and attractors in the hierarchical coregulation model, and show using simulations that the steady-state distribution factorizes hierarchically as a Bayesian network in a Markov Jump Process analogue of the RBN model. Copyright © 2017. Published by Elsevier Ltd.

Hierarchical and coupling model of factors influencing vessel traffic flow.

PubMed

Liu, Zhao; Liu, Jingxian; Li, Huanhuan; Li, Zongzhi; Tan, Zhirong; Liu, Ryan Wen; Liu, Yi

2017-01-01

Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system.

Hierarchical and coupling model of factors influencing vessel traffic flow

PubMed Central

Liu, Jingxian; Li, Huanhuan; Li, Zongzhi; Tan, Zhirong; Liu, Ryan Wen; Liu, Yi

2017-01-01

Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system. PMID:28414747

Information Acquisition, Analysis and Integration

DTIC Science & Technology

2016-08-03

of sensing and processing, theory, applications, signal processing, image and video processing, machine learning , technology transfer. 16. SECURITY... learning . 5. Solved elegantly old problems like image and video debluring, intro- ducing new revolutionary approaches. 1 DISTRIBUTION A: Distribution...Polatkan, G. Sapiro, D. Blei, D. B. Dunson, and L. Carin, “ Deep learning with hierarchical convolution factor analysis,” IEEE 6 DISTRIBUTION A

Replication and extension of a hierarchical model of social anxiety and depression: fear of positive evaluation as a key unique factor in social anxiety.

PubMed

Weeks, Justin W

2015-01-01

Wang, Hsu, Chiu, and Liang (2012, Journal of Anxiety Disorders, 26, 215-224) recently proposed a hierarchical model of social interaction anxiety and depression to account for both the commonalities and distinctions between these conditions. In the present paper, this model was extended to more broadly encompass the symptoms of social anxiety disorder, and replicated in a large unselected, undergraduate sample (n = 585). Structural equation modeling (SEM) and hierarchical regression analyses were employed. Negative affect and positive affect were conceptualized as general factors shared by social anxiety and depression; fear of negative evaluation (FNE) and disqualification of positive social outcomes were operationalized as specific factors, and fear of positive evaluation (FPE) was operationalized as a factor unique to social anxiety. This extended hierarchical model explicates structural relationships among these factors, in which the higher-level, general factors (i.e., high negative affect and low positive affect) represent vulnerability markers of both social anxiety and depression, and the lower-level factors (i.e., FNE, disqualification of positive social outcomes, and FPE) are the dimensions of specific cognitive features. Results from SEM and hierarchical regression analyses converged in support of the extended model. FPE is further supported as a key symptom that differentiates social anxiety from depression.

Repeated measures from FIA data facilitates analysis across spatial scales of tree growth responses to nitrogen deposition from individual trees to whole ecoregions

Treesearch

Charles H. (Hobie) Perry; Kevin J. Horn; R. Quinn Thomas; Linda H. Pardo; Erica A.H. Smithwick; Doug Baldwin; Gregory B. Lawrence; Scott W. Bailey; Sabine Braun; Christopher M. Clark; Mark Fenn; Annika Nordin; Jennifer N. Phelan; Paul G. Schaberg; Sam St. Clair; Richard Warby; Shaun Watmough; Steven S. Perakis

2015-01-01

The abundance of temporally and spatially consistent Forest Inventory and Analysis data facilitates hierarchical/multilevel analysis to investigate factors affecting tree growth, scaling from plot-level to continental scales. Herein we use FIA tree and soil inventories in conjunction with various spatial climate and soils data to estimate species-specific responses of...

Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling.

PubMed

Golay, Philippe; Reverte, Isabelle; Rossier, Jérôme; Favez, Nicolas; Lecerf, Thierry

2013-06-01

The interpretation of the Wechsler Intelligence Scale for Children--Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all cross-loadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores. PsycINFO Database Record (c) 2013 APA, all rights reserved.

An Empirically Derived Taxonomy of Factors Affecting Physicians' Willingness to Disclose Medical Errors

PubMed Central

Kaldjian, Lauris C; Jones, Elizabeth W; Rosenthal, Gary E; Tripp-Reimer, Toni; Hillis, Stephen L

2006-01-01

BACKGROUND Physician disclosure of medical errors to institutions, patients, and colleagues is important for patient safety, patient care, and professional education. However, the variables that may facilitate or impede disclosure are diverse and lack conceptual organization. OBJECTIVE To develop an empirically derived, comprehensive taxonomy of factors that affects voluntary disclosure of errors by physicians. DESIGN A mixed-methods study using qualitative data collection (structured literature search and exploratory focus groups), quantitative data transformation (sorting and hierarchical cluster analysis), and validation procedures (confirmatory focus groups and expert review). RESULTS Full-text review of 316 articles identified 91 impeding or facilitating factors affecting physicians' willingness to disclose errors. Exploratory focus groups identified an additional 27 factors. Sorting and hierarchical cluster analysis organized factors into 8 domains. Confirmatory focus groups and expert review relocated 6 factors, removed 2 factors, and modified 4 domain names. The final taxonomy contained 4 domains of facilitating factors (responsibility to patient, responsibility to self, responsibility to profession, responsibility to community), and 4 domains of impeding factors (attitudinal barriers, uncertainties, helplessness, fears and anxieties). CONCLUSIONS A taxonomy of facilitating and impeding factors provides a conceptual framework for a complex field of variables that affects physicians' willingness to disclose errors to institutions, patients, and colleagues. This taxonomy can be used to guide the design of studies to measure the impact of different factors on disclosure, to assist in the design of error-reporting systems, and to inform educational interventions to promote the disclosure of errors to patients. PMID:16918739

Designing Real-time Decision Support for Trauma Resuscitations

PubMed Central

Yadav, Kabir; Chamberlain, James M.; Lewis, Vicki R.; Abts, Natalie; Chawla, Shawn; Hernandez, Angie; Johnson, Justin; Tuveson, Genevieve; Burd, Randall S.

2016-01-01

Background Use of electronic clinical decision support (eCDS) has been recommended to improve implementation of clinical decision rules. Many eCDS tools, however, are designed and implemented without taking into account the context in which clinical work is performed. Implementation of the pediatric traumatic brain injury (TBI) clinical decision rule at one Level I pediatric emergency department includes an electronic questionnaire triggered when ordering a head computed tomography using computerized physician order entry (CPOE). Providers use this CPOE tool in less than 20% of trauma resuscitation cases. A human factors engineering approach could identify the implementation barriers that are limiting the use of this tool. Objectives The objective was to design a pediatric TBI eCDS tool for trauma resuscitation using a human factors approach. The hypothesis was that clinical experts will rate a usability-enhanced eCDS tool better than the existing CPOE tool for user interface design and suitability for clinical use. Methods This mixed-methods study followed usability evaluation principles. Pediatric emergency physicians were surveyed to identify barriers to using the existing eCDS tool. Using standard trauma resuscitation protocols, a hierarchical task analysis of pediatric TBI evaluation was developed. Five clinical experts, all board-certified pediatric emergency medicine faculty members, then iteratively modified the hierarchical task analysis until reaching consensus. The software team developed a prototype eCDS display using the hierarchical task analysis. Three human factors engineers provided feedback on the prototype through a heuristic evaluation, and the software team refined the eCDS tool using a rapid prototyping process. The eCDS tool then underwent iterative usability evaluations by the five clinical experts using video review of 50 trauma resuscitation cases. A final eCDS tool was created based on their feedback, with content analysis of the evaluations performed to ensure all concerns were identified and addressed. Results Among 26 EPs (76% response rate), the main barriers to using the existing tool were that the information displayed is redundant and does not fit clinical workflow. After the prototype eCDS tool was developed based on the trauma resuscitation hierarchical task analysis, the human factors engineers rated it to be better than the CPOE tool for nine of 10 standard user interface design heuristics on a three-point scale. The eCDS tool was also rated better for clinical use on the same scale, in 84% of 50 expert–video pairs, and was rated equivalent in the remainder. Clinical experts also rated barriers to use of the eCDS tool as being low. Conclusions An eCDS tool for diagnostic imaging designed using human factors engineering methods has improved perceived usability among pediatric emergency physicians. PMID:26300010

Evidence for a General ADHD Factor from a Longitudinal General School Population Study

ERIC Educational Resources Information Center

Normand, Sebastien; Flora, David B.; Toplak, Maggie E.; Tannock, Rosemary

2012-01-01

Recent factor analytic studies in Attention-Deficit/Hyperactivity Disorder (ADHD) have shown that hierarchical models provide a better fit of ADHD symptoms than correlated models. A hierarchical model includes a general ADHD factor and specific factors for inattention, and hyperactivity/impulsivity. The aim of this 12-month longitudinal study was…

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.

Characterizing the course of back pain after osteoporotic vertebral fracture: a hierarchical cluster analysis of a prospective cohort study.

PubMed

Toyoda, Hiromitsu; Takahashi, Shinji; Hoshino, Masatoshi; Takayama, Kazushi; Iseki, Kazumichi; Sasaoka, Ryuichi; Tsujio, Tadao; Yasuda, Hiroyuki; Sasaki, Takeharu; Kanematsu, Fumiaki; Kono, Hiroshi; Nakamura, Hiroaki

2017-09-23

This study demonstrated four distinct patterns in the course of back pain after osteoporotic vertebral fracture (OVF). Greater angular instability in the first 6 months after the baseline was one factor affecting back pain after OVF. Understanding the natural course of symptomatic acute OVF is important in deciding the optimal treatment strategy. We used latent class analysis to classify the course of back pain after OVF and identify the risk factors associated with persistent pain. This multicenter cohort study included 218 consecutive patients with ≤ 2-week-old OVFs who were enrolled at 11 institutions. Dynamic x-rays and back pain assessment with a visual analog scale (VAS) were obtained at enrollment and at 1-, 3-, and 6-month follow-ups. The VAS scores were used to characterize patient groups, using hierarchical cluster analysis. VAS for 128 patients was used for hierarchical cluster analysis. Analysis yielded four clusters representing different patterns of back pain progression. Cluster 1 patients (50.8%) had stable, mild pain. Cluster 2 patients (21.1%) started with moderate pain and progressed quickly to very low pain. Patients in cluster 3 (10.9%) had moderate pain that initially improved but worsened after 3 months. Cluster 4 patients (17.2%) had persistent severe pain. Patients in cluster 4 showed significant high baseline pain intensity, higher degree of angular instability, and higher number of previous OVFs, and tended to lack regular exercise. In contrast, patients in cluster 2 had significantly lower baseline VAS and less angular instability. We identified four distinct groups of OVF patients with different patterns of back pain progression. Understanding the course of back pain after OVF may help in its management and contribute to future treatment trials.

Using Cluster Analysis to Compartmentalize a Large Managed Wetland Based on Physical, Biological, and Climatic Geospatial Attributes.

PubMed

Hahus, Ian; Migliaccio, Kati; Douglas-Mankin, Kyle; Klarenberg, Geraldine; Muñoz-Carpena, Rafael

2018-04-27

Hierarchical and partitional cluster analyses were used to compartmentalize Water Conservation Area 1, a managed wetland within the Arthur R. Marshall Loxahatchee National Wildlife Refuge in southeast Florida, USA, based on physical, biological, and climatic geospatial attributes. Single, complete, average, and Ward's linkages were tested during the hierarchical cluster analyses, with average linkage providing the best results. In general, the partitional method, partitioning around medoids, found clusters that were more evenly sized and more spatially aggregated than those resulting from the hierarchical analyses. However, hierarchical analysis appeared to be better suited to identify outlier regions that were significantly different from other areas. The clusters identified by geospatial attributes were similar to clusters developed for the interior marsh in a separate study using water quality attributes, suggesting that similar factors have influenced variations in both the set of physical, biological, and climatic attributes selected in this study and water quality parameters. However, geospatial data allowed further subdivision of several interior marsh clusters identified from the water quality data, potentially indicating zones with important differences in function. Identification of these zones can be useful to managers and modelers by informing the distribution of monitoring equipment and personnel as well as delineating regions that may respond similarly to future changes in management or climate.

A Bayesian hierarchical approach to comparative audit for carotid surgery.

PubMed

Kuhan, G; Marshall, E C; Abidia, A F; Chetter, I C; McCollum, P T

2002-12-01

the aim of this study was to illustrate how a Bayesian hierarchical modelling approach can aid the reliable comparison of outcome rates between surgeons. retrospective analysis of prospective and retrospective data. binary outcome data (death/stroke within 30 days), together with information on 15 possible risk factors specific for CEA were available on 836 CEAs performed by four vascular surgeons from 1992-99. The median patient age was 68 (range 38-86) years and 60% were men. the model was developed using the WinBUGS software. After adjusting for patient-level risk factors, a cross-validatory approach was adopted to identify "divergent" performance. A ranking exercise was also carried out. the overall observed 30-day stroke/death rate was 3.9% (33/836). The model found diabetes, stroke and heart disease to be significant risk factors. There was no significant difference between the predicted and observed outcome rates for any surgeon (Bayesian p -value>0.05). Each surgeon had a median rank of 3 with associated 95% CI 1.0-5.0, despite the variability of observed stroke/death rate from 2.9-4.4%. After risk adjustment, there was very little residual between-surgeon variability in outcome rate. Bayesian hierarchical models can help to accurately quantify the uncertainty associated with surgeons' performance and rank.

Emotional intelligence is a second-stratum factor of intelligence: evidence from hierarchical and bifactor models.

PubMed

MacCann, Carolyn; Joseph, Dana L; Newman, Daniel A; Roberts, Richard D

2014-04-01

This article examines the status of emotional intelligence (EI) within the structure of human cognitive abilities. To evaluate whether EI is a 2nd-stratum factor of intelligence, data were fit to a series of structural models involving 3 indicators each for fluid intelligence, crystallized intelligence, quantitative reasoning, visual processing, and broad retrieval ability, as well as 2 indicators each for emotion perception, emotion understanding, and emotion management. Unidimensional, multidimensional, hierarchical, and bifactor solutions were estimated in a sample of 688 college and community college students. Results suggest adequate fit for 2 models: (a) an oblique 8-factor model (with 5 traditional cognitive ability factors and 3 EI factors) and (b) a hierarchical solution (with cognitive g at the highest level and EI representing a 2nd-stratum factor that loads onto g at λ = .80). The acceptable relative fit of the hierarchical model confirms the notion that EI is a group factor of cognitive ability, marking the expression of intelligence in the emotion domain. The discussion proposes a possible expansion of Cattell-Horn-Carroll theory to include EI as a 2nd-stratum factor of similar standing to factors such as fluid intelligence and visual processing.

An empirical evaluation of the structure of DSM-IV personality disorders in a nationally representative sample: results of confirmatory factor analysis in the National Epidemiologic Survey on Alcohol and Related Conditions Waves 1 and 2.

PubMed

Cox, Brian J; Clara, Ian P; Worobec, Lydia M; Grant, Bridget F

2012-12-01

Individual personality disorders (PD) are grouped into three clusters in the DSM-IV (A, B, and C). There is very little empirical evidence available concerning the validity of this model in the general population. The current study included all 10 of the DSM-IV PD assessed in Wave 1 and Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). Confirmatory factor analysis was used to evaluate three plausible models of the structure of Axis II personality disorders (the current hierarchical DSM-IV three-factor model in which individual PD are believed to load on their assigned clusters, which in turn load onto a single Axis II factor; a general single-factor model; and three independent factors). Each of these models was tested in both the total and also separately for gender. The higher order DSM-IV model demonstrated good fit to the data on a number of goodness-of-fit indices. The results for this model were very similar across genders. A model of PD based on the current DSM-IV hierarchical conceptualization of a higher order classification scheme received strong empirical support through confirmatory factor analysis using a number of goodness-of-fit indices in a nationally representative sample. Other models involving broad, higher order personality domains such as neuroticism in relation to personality disorders have yet to be tested in epidemiologic surveys and represent an important avenue for future research.

The Relationship Between Second Language Anxiety and International Nursing Students Stress

ERIC Educational Resources Information Center

Khawaja, Nigar G.; Chan, Sabrina; Stein, Georgia

2017-01-01

We examined the relationship between second language anxiety and international nursing student stress after taking into account the demographic, cognitive, and acculturative factors. International nursing students (N = 152) completed an online questionnaire battery. Hierarchical regression analysis revealed that spoken second language anxiety and…

Multidimensional Structure of the Hypomanic Personality Scale

ERIC Educational Resources Information Center

Schalet, Benjamin D.; Durbin, C. Emily; Revelle, William

2011-01-01

The structure of the Hypomanic Personality Scale was explored in a sample of young adults (N = 884); resulting structures were validated on subsamples with measures of personality traits, internalizing symptoms, and externalizing behaviors. Hierarchical cluster analysis and estimates of general factor saturation suggested the presence of a weak…

Cross-cultural adaptation, validation and factor structure of the Insight Scale for Affective Disorders.

PubMed

de Assis da Silva, Rafael; Mograbi, Daniel C; Camelo, Evelyn V M; Morton, Gregory Duff; Landeira-Fernandez, J; Cheniaux, Elie

2015-06-01

In the last few decades, several tools for studying insight in bipolar disorders have been used. Olaya and colleagues developed the Insight Scale for Affective Disorders (ISAD), which consists of a scale measuring insight through hetero evaluation for patients with mood disorders. The objective of this work is to translate and adapt the original English version of the ISAD to Brazilian Portuguese (ISAD-BR) and to conduct an evaluation of its psychometric properties. Adaptation procedures included translation/back-translation and consultation with a panel of experts. 95 patients with the diagnosis of Type 1 bipolar disorder were evaluated with the final version of the ISAD-BR, which was applied, simultaneously, but independently, by two examiners. Internal consistency and inter-rater reliability were explored and the latent structure of the scale was investigated with principal axis factoring and promax rotation. A second-order factor analysis was conducted to test if the scale had a hierarchical factor structure. The ISAD-BR showed good internal consistency and good inter-rater reliability. The analysis pointed to a four-factor solution of the ISAD-BR: awareness of symptoms associated with activity/energy; awareness of having a disorder; awareness of self-esteem and feelings of pleasure; and awareness of social functioning and relationships. The second order factor analysis indicated a hierarchical factor structure for the ISAD-BR, with the four lower-order factors loading on a single higher-order factor. Insight into bipolar disorder is a multidimensional construct, covering different aspects of the condition and its symptomatology. Nevertheless, insight about activity/energy changes may be a crucial aspect of insight into bipolar disorder. Copyright © 2015 Elsevier B.V. All rights reserved.

Hierarchical classification strategy for Phenotype extraction from epidermal growth factor receptor endocytosis screening.

PubMed

Cao, Lu; Graauw, Marjo de; Yan, Kuan; Winkel, Leah; Verbeek, Fons J

2016-05-03

Endocytosis is regarded as a mechanism of attenuating the epidermal growth factor receptor (EGFR) signaling and of receptor degradation. There is increasing evidence becoming available showing that breast cancer progression is associated with a defect in EGFR endocytosis. In order to find related Ribonucleic acid (RNA) regulators in this process, high-throughput imaging with fluorescent markers is used to visualize the complex EGFR endocytosis process. Subsequently a dedicated automatic image and data analysis system is developed and applied to extract the phenotype measurement and distinguish different developmental episodes from a huge amount of images acquired through high-throughput imaging. For the image analysis, a phenotype measurement quantifies the important image information into distinct features or measurements. Therefore, the manner in which prominent measurements are chosen to represent the dynamics of the EGFR process becomes a crucial step for the identification of the phenotype. In the subsequent data analysis, classification is used to categorize each observation by making use of all prominent measurements obtained from image analysis. Therefore, a better construction for a classification strategy will support to raise the performance level in our image and data analysis system. In this paper, we illustrate an integrated analysis method for EGFR signalling through image analysis of microscopy images. Sophisticated wavelet-based texture measurements are used to obtain a good description of the characteristic stages in the EGFR signalling. A hierarchical classification strategy is designed to improve the recognition of phenotypic episodes of EGFR during endocytosis. Different strategies for normalization, feature selection and classification are evaluated. The results of performance assessment clearly demonstrate that our hierarchical classification scheme combined with a selected set of features provides a notable improvement in the temporal analysis of EGFR endocytosis. Moreover, it is shown that the addition of the wavelet-based texture features contributes to this improvement. Our workflow can be applied to drug discovery to analyze defected EGFR endocytosis processes.

Multivariate Statistical Analysis of MSL APXS Bulk Geochemical Data

NASA Astrophysics Data System (ADS)

Hamilton, V. E.; Edwards, C. S.; Thompson, L. M.; Schmidt, M. E.

2014-12-01

We apply cluster and factor analyses to bulk chemical data of 130 soil and rock samples measured by the Alpha Particle X-ray Spectrometer (APXS) on the Mars Science Laboratory (MSL) rover Curiosity through sol 650. Multivariate approaches such as principal components analysis (PCA), cluster analysis, and factor analysis compliment more traditional approaches (e.g., Harker diagrams), with the advantage of simultaneously examining the relationships between multiple variables for large numbers of samples. Principal components analysis has been applied with success to APXS, Pancam, and Mössbauer data from the Mars Exploration Rovers. Factor analysis and cluster analysis have been applied with success to thermal infrared (TIR) spectral data of Mars. Cluster analyses group the input data by similarity, where there are a number of different methods for defining similarity (hierarchical, density, distribution, etc.). For example, without any assumptions about the chemical contributions of surface dust, preliminary hierarchical and K-means cluster analyses clearly distinguish the physically adjacent rock targets Windjana and Stephen as being distinctly different than lithologies observed prior to Curiosity's arrival at The Kimberley. In addition, they are separated from each other, consistent with chemical trends observed in variation diagrams but without requiring assumptions about chemical relationships. We will discuss the variation in cluster analysis results as a function of clustering method and pre-processing (e.g., log transformation, correction for dust cover) and implications for interpreting chemical data. Factor analysis shares some similarities with PCA, and examines the variability among observed components of a dataset so as to reveal variations attributable to unobserved components. Factor analysis has been used to extract the TIR spectra of components that are typically observed in mixtures and only rarely in isolation; there is the potential for similar results with data from APXS. These techniques offer new ways to understand the chemical relationships between the materials interrogated by Curiosity, and potentially their relation to materials observed by APXS instruments on other landed missions.

Examining the Factor Structure and Hierarchical Nature of the Quality of Life Construct

ERIC Educational Resources Information Center

Wang, Mian; Schalock, Robert L.; Verdugo, Miguel A.; Jenaro, Christina

2010-01-01

There is considerable debate in the area of individual quality of life research regarding the factor structure and hierarchical nature of the quality of life construct. Our purpose in this study was to test via structural equation modeling an a priori quality of life model consisting of eight first-order factors and one second-order factor. Data…

Factors Influencing the Academic Achievement of First-Generation College Students

ERIC Educational Resources Information Center

Strayhorn, Terrell L.

2006-01-01

First-generation college students face a number of unique challenges in college. These obstacles may have a disparate effect on educational outcomes such as academic achievement. This study presents findings from an analysis of the Baccalaureate & Beyond Longitudinal Study using hierarchical multiple regression techniques to measure the influence…

Evolutionary analysis of groundwater flow: Application of multivariate statistical analysis to hydrochemical data in the Densu Basin, Ghana

NASA Astrophysics Data System (ADS)

Yidana, Sandow Mark; Bawoyobie, Patrick; Sakyi, Patrick; Fynn, Obed Fiifi

2018-02-01

An evolutionary trend has been postulated through the analysis of hydrochemical data of a crystalline rock aquifer system in the Densu Basin, Southern Ghana. Hydrochemcial data from 63 groundwater samples, taken from two main groundwater outlets (Boreholes and hand dug wells) were used to postulate an evolutionary theory for the basin. Sequential factor and hierarchical cluster analysis were used to disintegrate the data into three factors and five clusters (spatial associations). These were used to characterize the controls on groundwater hydrochemistry and its evolution in the terrain. The dissolution of soluble salts and cation exchange processes are the dominant processes controlling groundwater hydrochemistry in the terrain. The trend of evolution of this set of processes follows the pattern of groundwater flow predicted by a calibrated transient groundwater model in the area. The data suggest that anthropogenic activities represent the second most important process in the hydrochemistry. Silicate mineral weathering is the third most important set of processes. Groundwater associations resulting from Q-mode hierarchical cluster analysis indicate an evolutionary pattern consistent with the general groundwater flow pattern in the basin. These key findings are at variance with results of previous investigations and indicate that when carefully done, groundwater hydrochemical data can be very useful for conceptualizing groundwater flow in basins.

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.

Transforming Graph Data for Statistical Relational Learning

DTIC Science & Technology

2012-10-01

Jordan, 2003), PLSA (Hofmann, 1999), ? Classification via RMN (Taskar et al., 2003) or SVM (Hasan, Chaoji, Salem , & Zaki, 2006) ? Hierarchical...dimensionality reduction methods such as Principal 407 Rossi, McDowell, Aha, & Neville Component Analysis (PCA), Principal Factor Analysis ( PFA ), and...clustering algorithm. Journal of the Royal Statistical Society. Series C, Applied statistics, 28, 100–108. Hasan, M. A., Chaoji, V., Salem , S., & Zaki, M

Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

NASA Astrophysics Data System (ADS)

Crawford, I.; Ruske, S.; Topping, D. O.; Gallagher, M. W.

2015-07-01

In this paper we present improved methods for discriminating and quantifying Primary Biological Aerosol Particles (PBAP) by applying hierarchical agglomerative cluster analysis to multi-parameter ultra violet-light induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1×106 points on a desktop computer, allowing for each fluorescent particle in a dataset to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient dataset. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best performing methods were applied to the BEACHON-RoMBAS ambient dataset where it was found that the z-score and range normalisation methods yield similar results with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of bacterial aerosol concentration by a factor of 5. We suggest that this likely due to errors arising from misatrribution due to poor centroid definition and failure to assign particles to a cluster as a result of the subsampling and comparative attribution method employed by WASP. The methods used here allow for the entire fluorescent population of particles to be analysed yielding an explict cluster attribution for each particle, improving cluster centroid definition and our capacity to discriminate and quantify PBAP meta-classes compared to previous approaches.

Social motivation in Qatari schools and their relation to school achievement.

PubMed

Nasser, Ramzi

2014-10-01

This study assessed the relation between school-social motivation and student academic achievement. A factor analysis was performed on a set of school-social items selected a priori from three measures of school motivation: the Inventory of School Motivation, the General Achievement Goals Orientation Scale, and the Facilitating Conditions Scale. Three factors with fewer items represented Global Motivation, Peer Help, and Social Power. Hierarchical regression analysis showed social motivation measures were weak predictors of achievement scores in the various content areas. Findings are discussed in the context of Qatari education and culture.

The Case for a Hierarchical Cosmology

ERIC Educational Resources Information Center

Vaucouleurs, G. de

1970-01-01

The development of modern theoretical cosmology is presented and some questionable assumptions of orthodox cosmology are pointed out. Suggests that recent observations indicate that hierarchical clustering is a basic factor in cosmology. The implications of hierarchical models of the universe are considered. Bibliography. (LC)

A hierarchical-multiobjective framework for risk management

NASA Technical Reports Server (NTRS)

Haimes, Yacov Y.; Li, Duan

1991-01-01

A broad hierarchical-multiobjective framework is established and utilized to methodologically address the management of risk. United into the framework are the hierarchical character of decision-making, the multiple decision-makers at separate levels within the hierarchy, the multiobjective character of large-scale systems, the quantitative/empirical aspects, and the qualitative/normative/judgmental aspects. The methodological components essentially consist of hierarchical-multiobjective coordination, risk of extreme events, and impact analysis. Examples of applications of the framework are presented. It is concluded that complex and interrelated forces require an analysis of trade-offs between engineering analysis and societal preferences, as in the hierarchical-multiobjective framework, to successfully address inherent risk.

Confirmatory factor analysis of the Autonomy over Tobacco Scale (AUTOS) in adults.

PubMed

Wellman, Robert J; DiFranza, Joseph R; O'Loughlin, Jennifer

2015-11-01

The Autonomy over Tobacco Scale (AUTOS), a 12-item self-administered questionnaire, was designed to measure autonomy in three correlated lower-order symptom domains: withdrawal, psychological dependence, and cue-induced craving. The factor structure of the AUTOS remains an open question; confirmatory analyses in adolescents supported the hierarchical structure, while exploratory analyses in adolescents and adults yield single-factor solutions. Here we seek to determine whether the hypothesized hierarchical structure is valid in adult smokers. The AUTOS was administered to two independent convenience samples of adult current smokers: a calibration sample recruited in the US for online studies, and a confirmation sample drawn from the prospective Nicotine Dependence in Teens study in Montreal. We tested competing hierarchical and single-factor models using the robust weighted least-squares (WLSMV) estimation method. A single-factor model that allowed correlated error variances between theoretically related items fit well in the calibration sample (n = 434), χ(2)SB(52) = 165.71; χ(2)/df = 3.19; SRMR = 0.03; CFI = 0.96; NNFI = 0.95; RMSEA = 0.07 (95% CI: 0.06, 0.08). Reliability of the single factor was high (ωB = 0.92) and construct validity was adequate. In the confirmation sample (n = 335), a similar model fit well:χ(2)SB(53) = 126.94; χ(2)/df = 2.44; SRMR = 0.04; CFI = 0.95; NNFI = 0.93; RMSEA = 0.07 (95% CI: 0.05, 0.08). Reliability of the single factor was again high (ωB = 0.92) and construct validity was adequate. The AUTOS is unidimensional in adult smokers. Copyright © 2015 Elsevier Ltd. All rights reserved.

[Factors Influencing Quality of Life of Alcoholics Anonymous Members in Korea].

PubMed

Yoo, Jae Soon; Lee, Jongeun; Park, Woo Young

2016-04-01

The purpose of this study was to determine quality of life (QOL) related factors in Alcoholics Anonymous (AA) members based on PRECEDE Model. A cross sectional survey was conducted with participants (N =203) from AA meeting in 11 alcohol counsel centers all over South Korea. Data were collected using a specially designed questionnaire based on the PRECEDE model and including QOL, epidemiological factors (including depression and perceived health status), behavioral factors (continuous abstinence and physical health status and practice), predisposing factors (abstinence self-efficacy and self-esteem), reinforcing factors (social capital and family functioning), and enabling factors. Data were analyzed using t-test, one way ANOVA, Tukey HSD test and hierarchical multiple regression analysis with SPSS (ver. 21.0). Of the educational diagnostic variables, self-esteem (β=.23), family functioning (β=.12), abstinence self-efficacy (β=.12) and social capital (β=.11) were strong influential factors in AA members' QOL. In addition, epidemiological diagnostic variables such as depression (β=-.44) and perceived health status (β=.35) were the main factors in QOL. Also, physical health status and practice (β=.106), one of behavioral diagnostic variables was a beneficial factor in QOL. Hierarchical multiple regression analysis showed the determinant variables accounted for 44.0% of the variation in QOL (F=25.76, p<.001). The finding of the study can be used as a framework for planning interventions in order to promote the quality of life of AA members. It is necessary to develop nursing intervention strategies for strengthening educational and epidemiological diagnostic variables in order to improve AA members' QOL.

Measuring disability across cultures — the psychometric properties of the WHODAS II in older people from seven low- and middle-income countries. The 10/66 Dementia Research Group population-based survey

PubMed Central

Sousa, Renata M; Dewey, Michael E; Acosta, Daisy; Jotheeswaran, AT; Castro-Costa, Erico; Ferri, Cleusa P; Guerra, Mariella; Huang, Yueqin; Jacob, KS; Pichardo, Juana Guillermina Rodriguez; Ramírez, Nayeli Garcia; Rodriguez, Juan Llibre; Rodriguez, Marina Calvo; Salas, Aquiles; Sosa, Ana Luisa; Williams, Joseph; Prince, Martin J

2010-01-01

We evaluated the psychometric properties of the 12-item interviewer-administered screener version of the World Health Organization Disability Assessment Schedule – version II (WHODAS II) among older people living in seven low- and middle-income countries. Principal component analysis (PCA), confirmatory factor analysis (CFA) and Mokken analyses were carried out to test for unidimensionality, hierarchical structure, and measurement invariance across 10/66 Dementia Research Group sites. PCA generated a one-factor solution in most sites. In CFA, the two-factor solution generated in Dominican Republic fitted better for all sites other than rural China. The two factors were not easily interpretable, and may have been an artefact of differing item difficulties. Strong internal consistency and high factor loadings for the one-factor solution supported unidimensionality. Furthermore, the WHODAS II was found to be a ‘strong’ Mokken scale. Measurement invariance was supported by the similarity of factor loadings across sites, and by the high between-site correlations in item difficulties. The Mokken results strongly support that the WHODAS II 12-item screener is a unidimensional and hierarchical scale confirming to item response theory (IRT) principles, at least at the monotone homogeneity model level. More work is needed to assess the generalizability of our findings to different populations. Copyright © 2010 John Wiley & Sons, Ltd. PMID:20104493

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…

Escape from Discrepancy: Self-Esteem and Quality of Life as Predictors of Current Suicidal Ideation Among Individuals with Schizophrenia.

PubMed

Fulginiti, Anthony; Brekke, John S

2015-08-01

While suicidal ideation represents an "early warning" sign for suicidal behavior, studies examining suicidal ideation have been limited and largely atheorethical among those with schizophrenia. Informed by the Escape Theory of Suicide, we investigated the relationship between discrepancy factors, in the form of self-esteem and quality of life (QoL), and suicidal ideation. In a sample of 162 individuals with Schizophrenia, hierarchical logistic regression was employed to examine the contribution of (1) demographic (2) clinical and (3) discrepancy factors to suicidal ideation. A mediation analysis was performed to determine if self-esteem mediated the relationship between QoL and suicidal ideation. While QoL (in social relationships) and self-esteem collectively added value to predicting suicidal ideation beyond other factors, only self-esteem remained significant in the final hierarchical model. Self-esteem was found to mediate the relationship between QoL and suicidal ideation. Findings support Escape Theory in schizophrenia, marking self-esteem and QoL as targets for intervention.

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…

Mapping the CgrA regulon of Rhodospirillum centenum reveals a hierarchal network controlling Gram-negative cyst development.

PubMed

Dong, Qian; Fang, Mingxu; Roychowdhury, Sugata; Bauer, Carl E

2015-12-16

Several Gram-negative species undergo development leading to the formation of metabolically dormant desiccation resistant cysts. Recent analysis of cyst development has revealed that ~20 % of the Rhodospirillum centenum transcriptome undergo temporal changes in expression as cells transition from vegetative to cyst forms. It has also been established that one trigger for cyst formation is the synthesis of the signaling nucleotide 3', 5'- cyclic guanosine monophosphate (cGMP) that is sensed by a homolog of the catabolite repressor protein called CgrA. CgrA in the presence of cGMP initiate a cascade of gene expression leading to the development of cysts. In this study, we have used RNA-seq and chromatin immunoprecipitation (ChIP-Seq) techniques to define the CgrA-cGMP regulon. Our results indicate that disruption of CgrA leads to altered expression of 258 genes, 131 of which have been previously reported to be involved in cyst development. ChIP-seq analysis combined with transcriptome data also demonstrates that CgrA directly regulates the expression of numerous sigma factors and transcription factors several of which are known to be involved in cyst cell development. This analysis reveals the presence of CgrA binding sites upstream of many developmentally regulated genes including many transcription factors and signal transduction components. CgrA thus functions as master controller of the cyst development by initiating a hierarchal cascade of downstream transcription factors that induces temporal expression of encystment genes.

Trade-Off between Effectiveness and Equity? An Analysis of Social Sorting between Classrooms and between Schools

ERIC Educational Resources Information Center

Ferrer-Esteban, Gerard

2016-01-01

This article analyzes whether school social segregation, derived from policies and practices of both between-school student allocation and within-school streaming, is related to the effectiveness of the Italian education system. Hierarchical regression models are used to set out territorially aggregated factors of social sorting influencing…

To Dream the Impossible Dream: College Graduation in Four Years

ERIC Educational Resources Information Center

Raikes, Mark H.; Berling, Victoria L.; Davis, Jody M.

2012-01-01

The cost of higher education continues to climb, while calls for increased institutional accountability and the value of a "four-year degree" are ever present. This research sought to identify factors by which consumers might predict four-year graduation rates at institutions within the CCCU. A hierarchical multiple regression analysis of data…

A Hierarchical Model and Analysis of Factors Affecting the Adoption of Timber as a Bridge

Treesearch

Robert L. Smith; Robert J. Bush; Daniel L. Schmoldt

1995-01-01

The Analytical Hierarchy Process was used to characterize the bridge material selection decisions of highway engineers and local highway officials across the United States. State Department of Transportation engineers, private consulting engineers, and local highway officials were personally interviewed in Mississippi, Virginia, Washington, and Wisconsin to identify...

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…

Predictors of Tuition Worth: Psychological Sense of Community, Institutional Integrity, and Student Thriving

ERIC Educational Resources Information Center

Conn, Steven M.

2017-01-01

Using hierarchical multiple regression analysis, this study examined the factors that contribute to the variation in students' subjective perceptions of the value of their tuition dollars. This study utilized data on 6,322 undergraduate students from 11 institutions in the Council for Christian Colleges & Universities (CCCU) who completed the…

Stopover habitat: management implications and guidelines

Treesearch

Frank R. Moore; Sidney A. Gauthreaux; Paul Kerlinger; Ted R. Simons

1993-01-01

If persistence of migrant populations depends on the ability to find favorable conditions for survival throughout the annual cycle, factors associated with the en-route ecology of migrants must figure in any analysis of population change and in development of a comprehensive conservation "strategy." We view en-route habitat selection as a hierarchical process...

Socially Oriented Motivational Goals and Academic Achievement: Similarities between Native and Anglo Americans

ERIC Educational Resources Information Center

Ali, Jinnat; McInerney, Dennis M.; Craven, Rhonda G.; Yeung, Alexander Seeshing; King, Ronnel B.

2014-01-01

The authors examined the relations between two socially oriented dimensions of student motivation and academic achievement of Native (Navajo) American and Anglo American students. Using confirmatory factor analysis, a multidimensional and hierarchical model was found to explain the relations between performance and social goals. Four first-order…

Factorial and Hierarchical Cluster Analysis of the Adaptive Behavior Scales (Part I & II) in a Population of Older People (50 Years +) with Severe Intellectual Impairment (Mental Handicap).

ERIC Educational Resources Information Center

Moss, S. C.; Hogg, J.

1990-01-01

Principal components analysis was employed on the Adaptive Behavior Scales with scores of 122 older (mean age 63.5) individuals with severe intellectual impairment living in England. The study found the structure of adaptive skills and interpersonal maladaptive behaviors similar to that found for younger retarded adults. Two factors, personal…

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.

Modern Conditions and the Impacts of the Creation of Architectural Environment

NASA Astrophysics Data System (ADS)

Abyzov, Vadym

2017-10-01

The purpose of this research is an attempt to identify and analyse the modern conditions and impacts of the creation of architectural environment and on this basis to determine the main directions and tasks of the development of architecture at the appropriate hierarchical levels. A comprehensive review and structural analysis of all impact factors and different current conditions that lead to the sustainable architecture design are conducted in the proposal. The main groups of factors and conditions such as social-economical, natural-geographic, urban, ergonomics, ecological, typological, technical, cultural, and aesthetics are determined in accordance with their contemporary specifics. This analysis provides an opportunity to define the appropriative hierarchical levels of the modern trends and prospects of creation an effective, attractive and friendly architectural environment. Some examples of author’s projects and implementations is presented in the article. Such methodological approach will help to create a holistic view of the creation architectural environment, will allow to systematize existing knowledges and concepts, practices and prospects of the means and methods of its formation and development.

Socio-Ecological Risk Factors for Prime-Age Adult Death in Two Coastal Areas of Vietnam

PubMed Central

Kim, Deok Ryun; Ali, Mohammad; Thiem, Vu Dinh; Wierzba, Thomas F.

2014-01-01

Background Hierarchical spatial models enable the geographic and ecological analysis of health data thereby providing useful information for designing effective health interventions. In this study, we used a Bayesian hierarchical spatial model to evaluate mortality data in Vietnam. The model enabled identification of socio-ecological risk factors and generation of risk maps to better understand the causes and geographic implications of prime-age (15 to less than 45 years) adult death. Methods and Findings The study was conducted in two sites: Nha Trang and Hue in Vietnam. The study areas were split into 500×500 meter cells to define neighborhoods. We first extracted socio-demographic data from population databases of the two sites, and then aggregated the data by neighborhood. We used spatial hierarchical model that borrows strength from neighbors for evaluating risk factors and for creating spatially smoothed risk map after adjusting for neighborhood level covariates. The Markov chain Monte Carlo procedure was used to estimate the parameters. Male mortality was more than twice the female mortality. The rates also varied by age and sex. The most frequent cause of mortality was traffic accidents and drowning for men and traffic accidents and suicide for women. Lower education of household heads in the neighborhood was an important risk factor for increased mortality. The mortality was highly variable in space and the socio-ecological risk factors are sensitive to study site and sex. Conclusion Our study suggests that lower education of the household head is an important predictor for prime age adult mortality. Variability in socio-ecological risk factors and in risk areas by sex make it challenging to design appropriate intervention strategies aimed at decreasing prime-age adult deaths in Vietnam. PMID:24587031

Socio-ecological risk factors for prime-age adult death in two coastal areas of Vietnam.

PubMed

Kim, Deok Ryun; Ali, Mohammad; Thiem, Vu Dinh; Wierzba, Thomas F

2014-01-01

Hierarchical spatial models enable the geographic and ecological analysis of health data thereby providing useful information for designing effective health interventions. In this study, we used a Bayesian hierarchical spatial model to evaluate mortality data in Vietnam. The model enabled identification of socio-ecological risk factors and generation of risk maps to better understand the causes and geographic implications of prime-age (15 to less than 45 years) adult death. The study was conducted in two sites: Nha Trang and Hue in Vietnam. The study areas were split into 500×500 meter cells to define neighborhoods. We first extracted socio-demographic data from population databases of the two sites, and then aggregated the data by neighborhood. We used spatial hierarchical model that borrows strength from neighbors for evaluating risk factors and for creating spatially smoothed risk map after adjusting for neighborhood level covariates. The Markov chain Monte Carlo procedure was used to estimate the parameters. Male mortality was more than twice the female mortality. The rates also varied by age and sex. The most frequent cause of mortality was traffic accidents and drowning for men and traffic accidents and suicide for women. Lower education of household heads in the neighborhood was an important risk factor for increased mortality. The mortality was highly variable in space and the socio-ecological risk factors are sensitive to study site and sex. Our study suggests that lower education of the household head is an important predictor for prime age adult mortality. Variability in socio-ecological risk factors and in risk areas by sex make it challenging to design appropriate intervention strategies aimed at decreasing prime-age adult deaths in Vietnam.

CHILDHOOD DEPRESSION. Exploring the association between family violence and other psychosocial factors in low-income Brazilian schoolchildren

PubMed Central

2012-01-01

Background Childhood depression affects the morbidity, mortality and life functions of children. Individual, family and environmental factors have been documented as psychosocial risk factors for childhood depression, especially family violence, which results in inadequate support, low family cohesion and poor communication. This study investigates the association between psychosocial depression factors in low-income schoolchildren and reveals the potential trouble spots, highlighting several forms of violence that take place within the family context. Methods The study was based on a cross-sectional analysis of 464 schoolchildren aged between 6 and 10, selected by random sampling from a city in the state of Rio de Janeiro, Brazil. Socio-economic, family and individual variables were investigated on the strength of the caregivers’ information and organized in blocks for analysis. A binary logistic regression model was applied, according to hierarchical blocks. Results The final hierarchical regression analysis showed that the following variables are potential psychosocial factors associated with depression in childhood: average/poor relationship with the father (OR 3.24, 95% CI 1.32-7.94), high frequency of victimization by psychological violence (humiliation) (OR 6.13, 95% CI 2.06-18.31), parental divorce (OR 2.89, 95% CI 1.14-7.32) and externalizing behavior problems (OR 3.53 IC 1.51-8.23). Conclusions The results point to multiple determinants of depressive behavior in children, as well as the potential contribution of psychological family violence. The study also reveals potential key targets for early intervention, especially for children from highly vulnerable families. PMID:22776354

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

Parameterization of aquatic ecosystem functioning and its natural variation: Hierarchical Bayesian modelling of plankton food web dynamics

NASA Astrophysics Data System (ADS)

Norros, Veera; Laine, Marko; Lignell, Risto; Thingstad, Frede

2017-10-01

Methods for extracting empirically and theoretically sound parameter values are urgently needed in aquatic ecosystem modelling to describe key flows and their variation in the system. Here, we compare three Bayesian formulations for mechanistic model parameterization that differ in their assumptions about the variation in parameter values between various datasets: 1) global analysis - no variation, 2) separate analysis - independent variation and 3) hierarchical analysis - variation arising from a shared distribution defined by hyperparameters. We tested these methods, using computer-generated and empirical data, coupled with simplified and reasonably realistic plankton food web models, respectively. While all methods were adequate, the simulated example demonstrated that a well-designed hierarchical analysis can result in the most accurate and precise parameter estimates and predictions, due to its ability to combine information across datasets. However, our results also highlighted sensitivity to hyperparameter prior distributions as an important caveat of hierarchical analysis. In the more complex empirical example, hierarchical analysis was able to combine precise identification of parameter values with reasonably good predictive performance, although the ranking of the methods was less straightforward. We conclude that hierarchical Bayesian analysis is a promising tool for identifying key ecosystem-functioning parameters and their variation from empirical datasets.

Using a Systematic Approach in the Analysis of the Factors That Influence On a Form Formation of Buildings of Higher Educational Establishments

NASA Astrophysics Data System (ADS)

Martyniv, Oleksandra; Kinasz, Roman

2017-10-01

This material covers the row of basic factors that influence on architectonically-spatial solution formation of building of Higher educational establishments (hereinafter universities). For this purpose, the systematization process of factors that influence on the university architecture was conducted and presented. The conclusion of this article was the proposed concept of considering universities as a hierarchical system, elements of which act as factors of influence, which in the process of alternating influence lead to the main goal, namely the formation of a new university building.

Factorial structure and psychometric properties of a brief version of the Reminiscence Functions Scale with Chinese older adults.

PubMed

Lou, Vivian W Q; Choy, Jacky C P

2014-05-01

The current study aims to examine the factorial structure and psychometric properties of a brief version of the Reminiscence Functions Scale (RFS), a 14-item assessment tool of reminiscence functions, with Chinese older adults. The scale, covering four reminiscence functions (boredom reduction, bitterness revival, problem solving, and identity) was translated from English into Chinese and administered to older adults (N=675). Confirmatory factor analysis and hierarchical confirmatory factor analysis were conducted to examine its factorial structure, and its psychometric properties and criterion validity were examined. Confirmatory factor analysis supports a second-order model comprising one second-order factor and four first-order factors of RFS. The Cronbach's alpha of the subscales ranged from 0.75 to 0.90. The brief RFS contains a second-order factorial structure. Its psychometric properties support it as a sound instrument for measuring reminiscence functions among Chinese older adults.

Validation of the Adolescent Concerns Measure (ACM): evidence from exploratory and confirmatory factor analysis.

PubMed

Ang, Rebecca P; Chong, Wan Har; Huan, Vivien S; Yeo, Lay See

2007-01-01

This article reports the development and initial validation of scores obtained from the Adolescent Concerns Measure (ACM), a scale which assesses concerns of Asian adolescent students. In Study 1, findings from exploratory factor analysis using 619 adolescents suggested a 24-item scale with four correlated factors--Family Concerns (9 items), Peer Concerns (5 items), Personal Concerns (6 items), and School Concerns (4 items). Initial estimates of convergent validity for ACM scores were also reported. The four-factor structure of ACM scores derived from Study 1 was confirmed via confirmatory factor analysis in Study 2 using a two-fold cross-validation procedure with a separate sample of 811 adolescents. Support was found for both the multidimensional and hierarchical models of adolescent concerns using the ACM. Internal consistency and test-retest reliability estimates were adequate for research purposes. ACM scores show promise as a reliable and potentially valid measure of Asian adolescents' concerns.

A multivariate decision tree analysis of biophysical factors in tropical forest fire occurrence

Treesearch

Rey S. Ofren; Edward Harvey

2000-01-01

A multivariate decision tree model was used to quantify the relative importance of complex hierarchical relationships between biophysical variables and the occurrence of tropical forest fires. The study site is the Huai Kha Kbaeng wildlife sanctuary, a World Heritage Site in northwestern Thailand where annual fires are common and particularly destructive. Thematic...

Examining the Antecedents of ICT Adoption in Education Using an Extended Technology Acceptance Model (TAM)

ERIC Educational Resources Information Center

Teeroovengadum, Viraiyan; Heeraman, Nabeel; Jugurnath, Bhavish

2017-01-01

This study assesses the determinants of ICT adoption by educators in the teaching and learning process in the context of a developing country, Mauritius. A hierarchical regression analysis is used, to firstly determine the incremental effects of factors from the technology acceptance model (TAM) while controlling for demographic variables such as…

Underrepresentation of Women in Public Primary School Administration: The Experience of Greece

ERIC Educational Resources Information Center

Kyriakoussis, Andreas; Saiti, Anna

2006-01-01

The purpose of this paper is to attempt to investigate the factors accounting for the lack of ambition among Greek female teachers in reaching managerial positions in the higher echelons of education's hierarchical structure. The analysis was performed on data collected from 304 female primary teachers during the academic year 1999-2000, randomly…

Hierarchical and Multidimensional Academic Self-Concept of Commercial Students.

PubMed

Yeung; Chui; Lau

1999-10-01

Adapting the Marsh (1990) Academic Self-Description Questionnaire (ASDQ), this study examined the academic self-concept of students in a school of commerce in Hong Kong (N = 212). Confirmatory factor analysis found that students clearly distinguished among self-concept constructs in English, Chinese, Math and Statistics, Economics, and Principles of Accounting, and each of these constructs was highly associated with a global Academic self-concept construct, reflecting the validity of each construct in measuring an academic component of self-concept. Domain-specific self-concepts were more highly related with students' intention of course selection in corresponding areas than in nonmatching areas, further supporting the multidimensionality of the students' academic self-concept. Students' self-concepts in the five curriculum domains can be represented by the global Academic self-concept, supporting the hierarchical structure of students' academic self-concept in an educational institution with a specific focus, such as commercial studies. The academic self-concepts of the commercial students are both multidimensional and hierarchical. Copyright 1999 Academic Press.

Group-level self-definition and self-investment: a hierarchical (multicomponent) model of in-group identification.

PubMed

Leach, Colin Wayne; van Zomeren, Martijn; Zebel, Sven; Vliek, Michael L W; Pennekamp, Sjoerd F; Doosje, Bertjan; Ouwerkerk, Jaap W; Spears, Russell

2008-07-01

Recent research shows individuals' identification with in-groups to be psychologically important and socially consequential. However, there is little agreement about how identification should be conceptualized or measured. On the basis of previous work, the authors identified 5 specific components of in-group identification and offered a hierarchical 2-dimensional model within which these components are organized. Studies 1 and 2 used confirmatory factor analysis to validate the proposed model of self-definition (individual self-stereotyping, in-group homogeneity) and self-investment (solidarity, satisfaction, and centrality) dimensions, across 3 different group identities. Studies 3 and 4 demonstrated the construct validity of the 5 components by examining their (concurrent) correlations with established measures of in-group identification. Studies 5-7 demonstrated the predictive and discriminant validity of the 5 components by examining their (prospective) prediction of individuals' orientation to, and emotions about, real intergroup relations. Together, these studies illustrate the conceptual and empirical value of a hierarchical multicomponent model of in-group identification.

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.

Setting Directions: Anisotropy in Hierarchically Organized Porous Silica

PubMed Central

2017-01-01

Structural hierarchy, porosity, and isotropy/anisotropy are highly relevant factors for mechanical properties and thereby the functionality of porous materials. However, even though anisotropic and hierarchically organized, porous materials are well known in nature, such as bone or wood, producing the synthetic counterparts in the laboratory is difficult. We report for the first time a straightforward combination of sol–gel processing and shear-induced alignment to create hierarchical silica monoliths exhibiting anisotropy on the levels of both, meso- and macropores. The resulting material consists of an anisotropic macroporous network of struts comprising 2D hexagonally organized cylindrical mesopores. While the anisotropy of the mesopores is an inherent feature of the pores formed by liquid crystal templating, the anisotropy of the macropores is induced by shearing of the network. Scanning electron microscopy and small-angle X-ray scattering show that the majority of network forming struts is oriented towards the shearing direction; a quantitative analysis of scattering data confirms that roughly 40% of the strut volume exhibits a preferred orientation. The anisotropy of the material’s macroporosity is also reflected in its mechanical properties; i.e., the Young’s modulus differs by nearly a factor of 2 between the directions of shear application and perpendicular to it. Unexpectedly, the adsorption-induced strain of the material exhibits little to no anisotropy. PMID:28989232

Dependency of magnetic microwave absorption on surface architecture of Co20Ni80 hierarchical structures studied by electron holography

NASA Astrophysics Data System (ADS)

Liu, Qinhe; Xu, Xianhui; Xia, Weixing; Che, Renchao; Chen, Chen; Cao, Qi; He, Jingang

2015-01-01

To design and fabricate rational surface architecture of individual particles is one of the key factors that affect their magnetic properties and microwave absorption capability, which is still a great challenge. Herein, a series of Co20Ni80 hierarchical structures with different surface morphologies, including flower-, urchin-, ball-, and chain-like morphologies, were obtained using structure-directing templates via a facile one-step solvothermal treatment. The microwave reflection loss (RL) of urchin-like Co20Ni80 hierarchical structures reaches as high as -33.5 dB at 3 GHz, with almost twice the RL intensity of the ball- and chain-like structures, and the absorption bandwidth (<-10 dB) is about 5.5 GHz for the flower-like morphology, indicating that the surface nanospikes and nanoflakes on the Co20Ni80 microsphere surfaces have great influences on their magnetic microwave absorption properties. Electron holography analysis reveals that the surface nanospikes and nanoflakes could generate a high density of stray magnetic flux lines and contribute a large saturation magnetization (105.62 emu g-1 for urchin-like and 96.41 emu g-1 for flower-like morphology), leading the urchin-like and flower-like Co20Ni80 to possess stronger microwave RL compared with the ball-like and chain-like Co20Ni80 alloys. The eddy-current absorption mechanism μ''(μ')-2(f)-1 is dominant in the frequency region above 8 GHz, implying that eddy-current loss is a vital factor for microwave RL in the high frequency range. It can be supposed from our findings that different surface morphologies of magnetic hierarchical structures might become an effective path to achieve high-performance microwave absorption for electromagnetic shielding and stealth camouflage applications.To design and fabricate rational surface architecture of individual particles is one of the key factors that affect their magnetic properties and microwave absorption capability, which is still a great challenge. Herein, a series of Co20Ni80 hierarchical structures with different surface morphologies, including flower-, urchin-, ball-, and chain-like morphologies, were obtained using structure-directing templates via a facile one-step solvothermal treatment. The microwave reflection loss (RL) of urchin-like Co20Ni80 hierarchical structures reaches as high as -33.5 dB at 3 GHz, with almost twice the RL intensity of the ball- and chain-like structures, and the absorption bandwidth (<-10 dB) is about 5.5 GHz for the flower-like morphology, indicating that the surface nanospikes and nanoflakes on the Co20Ni80 microsphere surfaces have great influences on their magnetic microwave absorption properties. Electron holography analysis reveals that the surface nanospikes and nanoflakes could generate a high density of stray magnetic flux lines and contribute a large saturation magnetization (105.62 emu g-1 for urchin-like and 96.41 emu g-1 for flower-like morphology), leading the urchin-like and flower-like Co20Ni80 to possess stronger microwave RL compared with the ball-like and chain-like Co20Ni80 alloys. The eddy-current absorption mechanism μ''(μ')-2(f)-1 is dominant in the frequency region above 8 GHz, implying that eddy-current loss is a vital factor for microwave RL in the high frequency range. It can be supposed from our findings that different surface morphologies of magnetic hierarchical structures might become an effective path to achieve high-performance microwave absorption for electromagnetic shielding and stealth camouflage applications. Electronic supplementary information (ESI) available: EDS analysis data, SEM images, electron holography schematic diagram, electron holography and magnetic hysteresis loops. See DOI: 10.1039/c4nr05547k

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,…

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…

Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

NASA Astrophysics Data System (ADS)

Crawford, I.; Ruske, S.; Topping, D. O.; Gallagher, M. W.

2015-11-01

In this paper we present improved methods for discriminating and quantifying primary biological aerosol particles (PBAPs) by applying hierarchical agglomerative cluster analysis to multi-parameter ultraviolet-light-induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1 × 106 points on a desktop computer, allowing for each fluorescent particle in a data set to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient data set. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best-performing methods were applied to the BEACHON-RoMBAS (Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics and Nitrogen-Rocky Mountain Biogenic Aerosol Study) ambient data set, where it was found that the z-score and range normalisation methods yield similar results, with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of bacterial aerosol concentration by a factor of 5. We suggest that this likely due to errors arising from misattribution due to poor centroid definition and failure to assign particles to a cluster as a result of the subsampling and comparative attribution method employed by WASP. The methods used here allow for the entire fluorescent population of particles to be analysed, yielding an explicit cluster attribution for each particle and improving cluster centroid definition and our capacity to discriminate and quantify PBAP meta-classes compared to previous approaches.

Insight into pattern of codon biasness and nucleotide base usage in serotonin receptor gene family from different mammalian species.

PubMed

Dass, J Febin Prabhu; Sudandiradoss, C

2012-07-15

5-HT (5-Hydroxy-tryptamine) or serotonin receptors are found both in central and peripheral nervous system as well as in non-neuronal tissues. In the animal and human nervous system, serotonin produces various functional effects through a variety of membrane bound receptors. In this study, we focus on 5-HT receptor family from different mammals and examined the factors that account for codon and nucleotide usage variation. A total of 110 homologous coding sequences from 11 different mammalian species were analyzed using relative synonymous codon usage (RSCU), correspondence analysis (COA) and hierarchical cluster analysis together with nucleotide base usage frequency of chemically similar amino acid codons. The mean effective number of codon (ENc) value of 37.06 for 5-HT(6) shows very high codon bias within the family and may be due to high selective translational efficiency. The COA and Spearman's rank correlation reveals that the nucleotide compositional mutation bias as the major factors influencing the codon usage in serotonin receptor genes. The hierarchical cluster analysis suggests that gene function is another dominant factor that affects the codon usage bias, while species is a minor factor. Nucleotide base usage was reported using Goldman, Engelman, Stietz (GES) scale reveals the presence of high uracil (>45%) content at functionally important hydrophobic regions. Our in silico approach will certainly help for further investigations on critical inference on evolution, structure, function and gene expression aspects of 5-HT receptors family which are potential antipsychotic drug targets. Copyright © 2012 Elsevier B.V. All rights reserved.

Factors of empowerment for women in recovery from substance use.

PubMed

Hunter, Bronwyn A; Jason, Leonard A; Keys, Christopher B

2013-03-01

Empowerment is an interdisciplinary construct heavily grounded in the theories of community psychology. Although empowerment has a strong theoretical foundation, few context-specific quantitative measures have been designed to evaluate empowerment for specific populations. The present study explored the factor structure of a modified empowerment scale with a cross-sectional sample of 296 women in recovery from substance use who lived in recovery homes located throughout the United States. Results from an exploratory factor analysis identified three factors of psychological empowerment which were closely related to previous conceptualizations of psychological empowerment: self-perception, resource knowledge and participation. Further analyses demonstrated a hierarchical relationship among the three factors, with resource knowledge predicting participation when controlling for self-perception. Finally, a correlational analysis demonstrated the initial construct validity of each factor, as each factor of empowerment was significantly and positively related to self-esteem. Implications for the application of psychological empowerment theory and research are discussed.

Factors of Empowerment for Women in Recovery from Substance Use

PubMed Central

Hunter, Bronwyn A.; Jason, Leonard A.; Keys, Christopher B.

2014-01-01

Empowerment is an interdisciplinary construct heavily grounded in the theories of community psychology. Although empowerment has a strong theoretical foundation, few context-specific quantitative measures have been designed to evaluate empowerment for specific populations. The present study explored the factor structure of a modified empowerment scale with a cross-sectional sample of 296 women in recovery from substance use who lived in recovery homes located throughout the United States. Results from an exploratory factor analysis identified three factors of psychological empowerment which were closely related to previous conceptualizations of psychological empowerment: self perception, resource knowledge and participation. Further analyses demonstrated a hierarchical relationship among the three factors, with resource knowledge predicting participation when controlling for self-perception. Finally, a correlational analysis demonstrated the initial construct validity of each factor, as each factor of empowerment was significantly and positively related to self-esteem. Implications for the application of psychological empowerment theory and research are discussed. PMID:22392193

Classification of Support Needs for Elderly Outpatients with Diabetes Who Live Alone.

PubMed

Miyawaki, Yoshiko; Shimizu, Yasuko; Seto, Natsuko

2016-02-01

To investigate the support needs of elderly patients with diabetes and to classify elderly patients with diabetes living alone on the basis of support needs. Support needs were derived from a literature review of relevant journals and interviews of outpatients as well as expert nurses in the field of diabetes to prepare a 45-item questionnaire. Each item was analyzed on a 4-point Likert scale. The study included 634 elderly patients with diabetes who were recruited from 3 hospitals in Japan. Exploratory factor analysis was performed to determine the underlying structure of support needs, followed by hierarchical cluster analysis to clarify the characteristics of patients living alone (n=104) who had common support needs. Exploratory factor analysis suggested a 5-factor solution with 23 items: (1) hope for class and gatherings, (2) hope for personal advice including emergency response, (3) supportlessness and hopelessness, (4) barriers to food preparation, (5) hope of safe medical therapy. The hierarchical cluster analysis of subjects yielded 7 clusters, including a no special-support needs group, a collective support group, a self-care support group, a personal-support focus group, a life-support group, a food-preparation support group and a healthcare-environment support group. The support needs of elderly patients with diabetes who live alone can be divided into 2 categories: life and self-care support. Implementation of these categories in outpatient-management programs in which contact time with patients is limited is important in the overall management of elderly patients with diabetes who are living alone. Copyright © 2015 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.

A hierarchical factor analysis of a safety culture survey.

PubMed

Frazier, Christopher B; Ludwig, Timothy D; Whitaker, Brian; Roberts, D Steve

2013-06-01

Recent reviews of safety culture measures have revealed a host of potential factors that could make up a safety culture (Flin, Mearns, O'Connor, & Bryden, 2000; Guldenmund, 2000). However, there is still little consensus regarding what the core factors of safety culture are. The purpose of the current research was to determine the core factors, as well as the structure of those factors that make up a safety culture, and establish which factors add meaningful value by factor analyzing a widely used safety culture survey. A 92-item survey was constructed by subject matter experts and was administered to 25,574 workers across five multi-national organizations in five different industries. Exploratory and hierarchical confirmatory factor analyses were conducted revealing four second-order factors of a Safety Culture consisting of Management Concern, Personal Responsibility for Safety, Peer Support for Safety, and Safety Management Systems. Additionally, a total of 12 first-order factors were found: three on Management Concern, three on Personal Responsibility, two on Peer Support, and four on Safety Management Systems. The resulting safety culture model addresses gaps in the literature by indentifying the core constructs which make up a safety culture. This clarification of the major factors emerging in the measurement of safety cultures should impact the industry through a more accurate description, measurement, and tracking of safety cultures to reduce loss due to injury. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.

Social Competence in Preschool Children: Replication of Results and Clarification of a Hierarchical Measurement Model

ERIC Educational Resources Information Center

Santos, Antonio J.; Peceguina, Ines; Daniel, Joao R.; Shin, Nana; Vaughn, Brian E.

2013-01-01

This study tested assumptions and conclusions reached in an earlier confirmatory factor analysis (CFA) study of the social competence (SC) construct for preschool children. Two samples (total N = 408; a new Portuguese sample and one from US samples that had participated in the original study) contributed data. Seven SC indicators were tested for…

Factors That Influence Mandatory Child Abuse Reporting Attitudes of Pediatric Nurses in Korea.

PubMed

Lee, In Sook; Kim, Kyoung Ja

This study aimed to identify knowledge of child abuse, awareness of child abuse reporting, factors that influence attitudes toward mandatory reporting, and professionalism among a sample of pediatric nurses in Korea. One hundred sixteen pediatric nurses working at two university hospitals in Korea took part in the study and completed self-administered questionnaires. The data were analyzed using descriptive statistics, t tests, analysis of variance, Pearson correlation coefficients, and hierarchical regression analysis. Knowledge of child abuse, awareness of child abuse reporting, and attitudes toward mandatory reporting were low. Regarding nursing professionalism, social perceptions had the lowest mean score and nursing autonomy had the highest mean score. Attitudes toward mandatory reporting significantly correlated with professionalism. In the hierarchical regression model, the influences of nursing autonomy and intentions to report child abuse on attitudes toward mandatory reporting were statistically significant (F = 2.176, p = .013), explaining 32% of the variation in attitudes toward mandatory reporting. The results of this study could be used to improve systems and policies addressing child abuse and to further develop reporting procedures for identifying children at risk of abuse, to ensure their protection as a professional responsibility.

Bayesian Hierarchical Classes Analysis

ERIC Educational Resources Information Center

Leenen, Iwin; Van Mechelen, Iven; Gelman, Andrew; De Knop, Stijn

2008-01-01

Hierarchical classes models are models for "N"-way "N"-mode data that represent the association among the "N" modes and simultaneously yield, for each mode, a hierarchical classification of its elements. In this paper we present a stochastic extension of the hierarchical classes model for two-way two-mode binary data. In line with the original…

Factors Related to Depressive Symptoms in Mothers of Technology-Dependent Children.

PubMed

Toly, Valerie Boebel; Musil, Carol M

2015-07-01

Mothers caring for technology-dependent children at home often suffer clinically significant and unrecognized depressive symptoms. The study aim was to determine factors related to elevated depressive symptoms and provide information to target interventions that assists mothers in self-management of their mental health. Secondary data analysis from a descriptive, correlational study of 75 mothers was performed. Hierarchical multiple regression analysis results indicate that younger, unpartnered mothers with lower normalization efforts and personal resourcefulness, and less care hours, had increased depressive symptoms. The importance of personal resourcefulness and the potential for a resourcefulness training intervention to reduce depressive symptoms are discussed.

Use Hierarchical Storage and Analysis to Exploit Intrinsic Parallelism

NASA Astrophysics Data System (ADS)

Zender, C. S.; Wang, W.; Vicente, P.

2013-12-01

Big Data is an ugly name for the scientific opportunities and challenges created by the growing wealth of geoscience data. How to weave large, disparate datasets together to best reveal their underlying properties, to exploit their strengths and minimize their weaknesses, to continually aggregate more information than the world knew yesterday and less than we will learn tomorrow? Data analytics techniques (statistics, data mining, machine learning, etc.) can accelerate pattern recognition and discovery. However, often researchers must, prior to analysis, organize multiple related datasets into a coherent framework. Hierarchical organization permits entire dataset to be stored in nested groups that reflect their intrinsic relationships and similarities. Hierarchical data can be simpler and faster to analyze by coding operators to automatically parallelize processes over isomorphic storage units, i.e., groups. The newest generation of netCDF Operators (NCO) embody this hierarchical approach, while still supporting traditional analysis approaches. We will use NCO to demonstrate the trade-offs involved in processing a prototypical Big Data application (analysis of CMIP5 datasets) using hierarchical and traditional analysis approaches.

Structure of the Wechsler Intelligence Scale for Children - Fourth Edition in a Group of Children with ADHD.

PubMed

Gomez, Rapson; Vance, Alasdair; Watson, Shaun D

2016-01-01

This study used confirmatory factor analysis to examine the factor structure for the 10 core WISC-IV subtests in a group of children (N = 812) with ADHD. The study examined oblique four- and five-factor models, higher order models with one general secondary factor and four and five primary factors, and a bifactor model with a general factor and four specific factors. The findings supported all models tested, with the bifactor model being the optimum model. For this model, only the general factor had high explained common variance and omega hierarchical value, and it predicted reading and arithmetic abilities. The findings favor the use of the FSIQ scores of the WISC-IV, but not the subscale index scores.

A hierarchical (multicomponent) model of in-group identification: examining in Russian samples.

PubMed

Lovakov, Andrey V; Agadullina, Elena R; Osin, Evgeny N

2015-06-03

The aim of this study was to examine the validity and reliability of Leach et al.'s (2008) model of in-group identification in two studies using Russian samples (overall N = 621). In Study 1, a series of multi-group confirmatory factor analysis revealed that the hierarchical model of in-group identification, which included two second-order factors, self-definition (individual self-stereotyping, and in-group homogeneity) and self-investment (satisfaction, solidarity, and centrality), fitted the data well for all four group identities (ethnic, religious, university, and gender) (CFI > .93, TLI > .92, RMSEA < .06, SRMR < .06) and demonstrated a better fit, compared to the alternative models. In Study 2, the construct validity and reliability of the Russian version of the in-group identification measure was examined. Results show that these measures have adequate psychometric properties. In short, our results show that Leach et al.'s model is reproduced in Russian culture. The Russian version of this measure can be recommended for use in future in-group research in Russian-speaking samples.

Genetic and environmental variance in content dimensions of the MMPI.

PubMed

Rose, R J

1988-08-01

To evaluate genetic and environmental variance in the Minnesota Multiphasic Personality Inventory (MMPI), I studied nine factor scales identified in the first item factor analysis of normal adult MMPIs in a sample of 820 adolescent and young adult co-twins. Conventional twin comparisons documented heritable variance in six of the nine MMPI factors (Neuroticism, Psychoticism, Extraversion, Somatic Complaints, Inadequacy, and Cynicism), whereas significant influence from shared environmental experience was found for four factors (Masculinity versus Femininity, Extraversion, Religious Orthodoxy, and Intellectual Interests). Genetic variance in the nine factors was more evident in results from twin sisters than those of twin brothers, and a developmental-genetic analysis, using hierarchical multiple regressions of double-entry matrixes of the twins' raw data, revealed that in four MMPI factor scales, genetic effects were significantly modulated by age or gender or their interaction during the developmental period from early adolescence to early adulthood.

Investigation of the factor structure of the Wechsler Adult Intelligence Scale--Fourth Edition (WAIS-IV): exploratory and higher order factor analyses.

PubMed

Canivez, Gary L; Watkins, Marley W

2010-12-01

The present study examined the factor structure of the Wechsler Adult Intelligence Scale--Fourth Edition (WAIS-IV; D. Wechsler, 2008a) standardization sample using exploratory factor analysis, multiple factor extraction criteria, and higher order exploratory factor analysis (J. Schmid & J. M. Leiman, 1957) not included in the WAIS-IV Technical and Interpretation Manual (D. Wechsler, 2008b). Results indicated that the WAIS-IV subtests were properly associated with the theoretically proposed first-order factors, but all but one factor-extraction criterion recommended extraction of one or two factors. Hierarchical exploratory analyses with the Schmid and Leiman procedure found that the second-order g factor accounted for large portions of total and common variance, whereas the four first-order factors accounted for small portions of total and common variance. It was concluded that the WAIS-IV provides strong measurement of general intelligence, and clinical interpretation should be primarily at that level.

Classification of municipal occupations.

PubMed

Ilmarinen, J; Suurnäkki, T; Nygård, C H; Landau, K

1991-01-01

Eighty-eight job titles were analyzed with the "ergonomic job analysis procedure" [Arbeitswissenschaftliche Erhebungsverfahren zur Tätigkeits-analyse abbreviated (AET) in German]. The objective was to classify the wide range of municipal jobs into homogeneous groups according to job demand and to provide better possibilities to study the relationships between work and health among the aging municipal working population. Altogether 216 items were classified. First, a hierarchical cluster analysis was made, and a dendrogram of the analyzed job titles was drawn. Second, a profile analysis was done in which the single items were grouped into 39 sum items, and a graphic profile was drawn. Finally, the stress factors were listed and drawn in ranking order. The cluster analysis formed 13 groups. Groups exposed to the highest stress factor level were kitchen supervisors, dentists, and physicians. More than 10 stress factors (greater than 50% of the maximum) were found in nursing, administration, installation, transport, and technical supervision.

Control, responses and modularity of cellular regulatory networks: a control analysis perspective.

PubMed

Bruggeman, F J; Snoep, J L; Westerhoff, H V

2008-11-01

Cells adapt to changes in environmental conditions through the concerted action of signalling, gene expression and metabolic subsystems. The authors will discuss a theoretical framework addressing such integrated systems. This 'hierarchical analysis' was first developed as an extension to a metabolic control analysis. It builds on the phenomenon that often the communication between signalling, gene expression and metabolic subsystems is almost exclusively via regulatory interactions and not via mass flow interactions. This allows for the treatment of the said subsystems as 'levels' in a hierarchical view of the organisation of the molecular reaction network of cells. Such a hierarchical approach has as a major advantage that levels can be analysed conceptually in isolation of each other (from a local intra-level perspective) and at a later stage integrated via their interactions (from a global inter-level perspective). Hereby, it allows for a modular approach with variable scope. A number of different approaches have been developed for the analysis of hierarchical systems, for example hierarchical control analysis and modular response analysis. The authors, here, review these methods and illustrate the strength of these types of analyses using a core model of a system with gene expression, metabolic and signal transduction levels.

Hierarchical cultural values predict success and mortality in high-stakes teams.

PubMed

Anicich, Eric M; Swaab, Roderick I; Galinsky, Adam D

2015-02-03

Functional accounts of hierarchy propose that hierarchy increases group coordination and reduces conflict. In contrast, dysfunctional accounts claim that hierarchy impairs performance by preventing low-ranking team members from voicing their potentially valuable perspectives and insights. The current research presents evidence for both the functional and dysfunctional accounts of hierarchy within the same dataset. Specifically, we offer empirical evidence that hierarchical cultural values affect the outcomes of teams in high-stakes environments through group processes. Experimental data from a sample of expert mountain climbers from 27 countries confirmed that climbers expect that a hierarchical culture leads to improved team coordination among climbing teams, but impaired psychological safety and information sharing compared with an egalitarian culture. An archival analysis of 30,625 Himalayan mountain climbers from 56 countries on 5,104 expeditions found that hierarchy both elevated and killed in the Himalayas: Expeditions from more hierarchical countries had more climbers reach the summit, but also more climbers die along the way. Importantly, we established the role of group processes by showing that these effects occurred only for group, but not solo, expeditions. These findings were robust to controlling for environmental factors, risk preferences, expedition-level characteristics, country-level characteristics, and other cultural values. Overall, this research demonstrates that endorsing cultural values related to hierarchy can simultaneously improve and undermine group performance.

Assessment of Differential Item Functioning in Health-Related Outcomes: A Simulation and Empirical Analysis with Hierarchical Polytomous Data

PubMed Central

Sharafi, Zahra

2017-01-01

Background The purpose of this study was to evaluate the effectiveness of two methods of detecting differential item functioning (DIF) in the presence of multilevel data and polytomously scored items. The assessment of DIF with multilevel data (e.g., patients nested within hospitals, hospitals nested within districts) from large-scale assessment programs has received considerable attention but very few studies evaluated the effect of hierarchical structure of data on DIF detection for polytomously scored items. Methods The ordinal logistic regression (OLR) and hierarchical ordinal logistic regression (HOLR) were utilized to assess DIF in simulated and real multilevel polytomous data. Six factors (DIF magnitude, grouping variable, intraclass correlation coefficient, number of clusters, number of participants per cluster, and item discrimination parameter) with a fully crossed design were considered in the simulation study. Furthermore, data of Pediatric Quality of Life Inventory™ (PedsQL™) 4.0 collected from 576 healthy school children were analyzed. Results Overall, results indicate that both methods performed equivalently in terms of controlling Type I error and detection power rates. Conclusions The current study showed negligible difference between OLR and HOLR in detecting DIF with polytomously scored items in a hierarchical structure. Implications and considerations while analyzing real data were also discussed. PMID:29312463

Assessment of Differential Item Functioning in Health-Related Outcomes: A Simulation and Empirical Analysis with Hierarchical Polytomous Data.

PubMed

Sharafi, Zahra; Mousavi, Amin; Ayatollahi, Seyyed Mohammad Taghi; Jafari, Peyman

2017-01-01

The purpose of this study was to evaluate the effectiveness of two methods of detecting differential item functioning (DIF) in the presence of multilevel data and polytomously scored items. The assessment of DIF with multilevel data (e.g., patients nested within hospitals, hospitals nested within districts) from large-scale assessment programs has received considerable attention but very few studies evaluated the effect of hierarchical structure of data on DIF detection for polytomously scored items. The ordinal logistic regression (OLR) and hierarchical ordinal logistic regression (HOLR) were utilized to assess DIF in simulated and real multilevel polytomous data. Six factors (DIF magnitude, grouping variable, intraclass correlation coefficient, number of clusters, number of participants per cluster, and item discrimination parameter) with a fully crossed design were considered in the simulation study. Furthermore, data of Pediatric Quality of Life Inventory™ (PedsQL™) 4.0 collected from 576 healthy school children were analyzed. Overall, results indicate that both methods performed equivalently in terms of controlling Type I error and detection power rates. The current study showed negligible difference between OLR and HOLR in detecting DIF with polytomously scored items in a hierarchical structure. Implications and considerations while analyzing real data were also discussed.

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

GC[Formula: see text]NMF: A Novel Matrix Factorization Framework for Gene-Phenotype Association Prediction.

PubMed

Zhang, Yaogong; Liu, Jiahui; Liu, Xiaohu; Hong, Yuxiang; Fan, Xin; Huang, Yalou; Wang, Yuan; Xie, Maoqiang

2018-04-24

Gene-phenotype association prediction can be applied to reveal the inherited basis of human diseases and facilitate drug development. Gene-phenotype associations are related to complex biological processes and influenced by various factors, such as relationship between phenotypes and that among genes. While due to sparseness of curated gene-phenotype associations and lack of integrated analysis of the joint effect of multiple factors, existing applications are limited to prediction accuracy and potential gene-phenotype association detection. In this paper, we propose a novel method by exploiting weighted graph constraint learned from hierarchical structures of phenotype data and group prior information among genes by inheriting advantages of Non-negative Matrix Factorization (NMF), called Weighted Graph Constraint and Group Centric Non-negative Matrix Factorization (GC[Formula: see text]NMF). Specifically, first we introduce the depth of parent-child relationships between two adjacent phenotypes in hierarchical phenotypic data as weighted graph constraint for a better phenotype understanding. Second, we utilize intra-group correlation among genes in a gene group as group constraint for gene understanding. Such information provides us with the intuition that genes in a group probably result in similar phenotypes. The model not only allows us to achieve a high-grade prediction performance, but also helps us to learn interpretable representation of genes and phenotypes simultaneously to facilitate future biological analysis. Experimental results on biological gene-phenotype association datasets of mouse and human demonstrate that GC[Formula: see text]NMF can obtain superior prediction accuracy and good understandability for biological explanation over other state-of-the-arts methods.

Effects of Military/Family Conflict on Female Naval Officer Retention

DTIC Science & Technology

2004-06-01

has the greatest impact on retention . Hierarchical regression was used to identify life domains (e.g., family factors, job experiences, job ...where work/family conflict has the greatest impact on retention . Hierarchical regression was used to identify life domains (e.g., family factors, job ...experiences, job satisfaction, and commitment) that are key drivers of retention intent among female Naval officers. By identifying areas that are

Patients' perspectives on quality of life after burn.

PubMed

Kool, Marianne B; Geenen, Rinie; Egberts, Marthe R; Wanders, Hendriët; Van Loey, Nancy E

2017-06-01

The concept quality of life (QOL) refers to both health-related outcomes and one's skills to reach these outcomes, which is not yet incorporated in the burn-related QOL conceptualisation. The aim of this study was to obtain a comprehensive overview of relevant burn-specific domains of QOL from the patient's perspective and to determine its hierarchical structure. Concept mapping was used comprising a focus group (n=6), interviews (n=25), and a card-sorting task (n=24) in burn survivors. Participants sorted aspects of QOL based on content similarity after which hierarchical cluster analysis was used to determine the hierarchical structure of burn-related QOL. Ninety-nine aspects of burn-related QOL were selected from the interviews, written on cards, and sorted. The hierarchical structure of burn-related QOL showed a core distinction between resilience and vulnerability. Resilience comprised the domains positive coping and social sharing. Vulnerability included 5 domains subdivided in 13 subdomains: the psychological domain included trauma-related symptoms, cognitive symptoms, negative emotions, body perception and depressive mood; the economical domain comprised finance and work; the social domain included stigmatisation/invalidation; the physical domain comprised somatic symptoms, scars, and functional limitations; and the intimate/sexual domain comprised the relationship with partner, and anxiety/avoidance in sexual life. From the patient's perspective, QOL following burns includes a variety of vulnerability and resilience factors, which forms a fresh basis for the development of a screening instrument. Whereas some factors are well known, this study also revealed overlooked problem and resilience areas that could be considered in client-centred clinical practice in order to customize self-management support. Copyright © 2016 Elsevier Ltd and ISBI. All rights reserved.

Internal structure of the Community Assessment of Psychic Experiences-Positive (CAPE-P15) scale: Evidence for a general factor.

PubMed

Núñez, D; Arias, V; Vogel, E; Gómez, L

2015-07-01

Psychotic-like experiences (PLEs) are prevalent in the general population and are associated with poor mental health and a higher risk of psychiatric disorders. The Community Assessment of Psychic Experiences-Positive (CAPE-P15) scale is a self-screening questionnaire to address subclinical positive psychotic symptoms (PPEs) in community contexts. Although its psychometric properties seem to be adequate to screen PLEs, further research is needed to evaluate certain validity aspects, particularly its internal structure and its functioning in different populations. To uncover the optimal factor structure of the CAPE-P15 scale in adolescents aged 13 to 18 years using factorial analysis methods suitable to manage categorical variables. A sample of 727 students from six secondary public schools and 245 university students completed the CAPE-P15. The dimensionality of the CAPE-P15 was tested through exploratory structural equation models (ESEMs). Based on the ESEM results, we conducted a confirmatory factor analysis (CFA) to contrast two factorial structures that potentially underlie the symptoms described by the scale: a) three correlated factors and b) a hierarchical model composed of a general PLE factor plus three specific factors (persecutory ideation, bizarre experiences, and perceptual abnormalities). The underlying structure of PLEs assessed by the CAPE-P15 is consistent with both multidimensional and hierarchical solutions. However, the latter show the best fit. Our findings reveal the existence of a strong general factor underlying scale scores. Compared with the specific factors, the general factor explains most of the common variance observed in subjects' responses. The findings suggest that the factor structure of subthreshold psychotic experiences addressed by the CAPE-P15 can be adequately represented by a general factor and three separable specific traits, supporting the hypothesis according to which there might be a common source underlying PLEs. Copyright © 2015 Elsevier B.V. All rights reserved.

Comparison of proteomic profiles of serum, plasma, and modified media supplements used for cell culture and expansion

PubMed Central

Ayache, Saleh; Panelli, Monica C; Byrne, Karen M; Slezak, Stefanie; Leitman, Susan F; Marincola, Francesco M; Stroncek, David F

2006-01-01

Background The culture and expansion of human cells for clinical use requires the presence of human serum or plasma in culture media. Although these supplements have been extensively characterized in their chemical composition, only recently it has been possible to provide by high throughput protein analysis, a comprehensive profile of the soluble factors contributing to cell survival. This study analyzed and compared the presence of 100 proteins including chemokines, cytokines and soluble factors in six different types of media supplements: serum, plasma, recalcified plasma, heat inactivated serum, heat inactivated plasma and heat inactivated recalcified plasma. Methods Serum, plasma, recalcified plasma, and heat inactivated supplements were prepared from ten healthy subjects. The levels of 100 soluble factors were measured in each sample using a multiplexed ELISA assay and compared by Eisen hierarchical clustering analysis. Results A comparison of serum and plasma levels of soluble factors found that 2 were greater in plasma but 18 factors were greater in serum including 11 chemokines. The levels of only four factors differed between recalcified plasma and plasma. Heat inactivation had the greatest effect on soluble factors. Supervised Eisen hierarchical clustering indicated that the differences between heat inactivated supplements and those that were not were greater than the differences within these two groups. The levels of 36 factors differed between heat inactivated plasma and plasma. Thirty one of these factors had a lower concentration in heat inactivated plasma including 12 chemokines, 4 growth factors, 4 matrix metalloproteases, and 3 adhesion molecules. Heat inactivated decalcified plasma is often used in place of heat inactivated serum and the levels of 19 soluble factors differed between these two supplements. Conclusion Our report provides a comprehensive protein profile of serum, plasma recalcified plasma, and heat inactivated supplements. This profile represents a qualitative and quantitative database that can aid in the selection of the appropriate blood derived supplement for human cell cultures with special requirements. PMID:17020621

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.

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.

SAPO-34/AlMCM-41, as a novel hierarchical nanocomposite: preparation, characterization and investigation of synthesis factors using response surface methodology

NASA Astrophysics Data System (ADS)

Roohollahi, Hossein; Halladj, Rouein; Askari, Sima; Yaripour, Fereydoon

2018-06-01

SAPO-34/AlMCM-41, as a new hierarchical nanocomposite was successfully synthesized via hydrothermal and dry-gel conversion. In an experimental and statistical study, effect of five input parameters including synthesis period, drying temperature, NaOH/Si, water/dried-gel and SAPO% were investigated on range-order degree of mesochannels and the relative crystallinity. X-ray diffraction (XRD) patterns were recorded to characterize the ordered AlMCM-41 and crystalline SAPO-34 structures. Nitrogen adsorption-desorption technique, scanning electron microscopy (SEM), field-emission SEM (FESEM) equipped with an energy-dispersive X-ray spectroscopy (EDS-Map) and transmission electron microscopy (TEM) were used to study the textural properties, morphology and surface elemental composition. Two reduced polynomials were fitted to the responses with good precision. Further, based on analysis of variances, SAPO% and time duration of dry-gel conversion were observed as the most effective parameters on the composite structure. The hierarchical porosity, narrow pore size distribution, high external surface area and large specific pore volume were of interesting characteristics for this novel nanocomposite.

Implementation of hierarchical clustering using k-mer sparse matrix to analyze MERS-CoV genetic relationship

NASA Astrophysics Data System (ADS)

Bustamam, A.; Ulul, E. D.; Hura, H. F. A.; Siswantining, T.

2017-07-01

Hierarchical clustering is one of effective methods in creating a phylogenetic tree based on the distance matrix between DNA (deoxyribonucleic acid) sequences. One of the well-known methods to calculate the distance matrix is k-mer method. Generally, k-mer is more efficient than some distance matrix calculation techniques. The steps of k-mer method are started from creating k-mer sparse matrix, and followed by creating k-mer singular value vectors. The last step is computing the distance amongst vectors. In this paper, we analyze the sequences of MERS-CoV (Middle East Respiratory Syndrome - Coronavirus) DNA by implementing hierarchical clustering using k-mer sparse matrix in order to perform the phylogenetic analysis. Our results show that the ancestor of our MERS-CoV is coming from Egypt. Moreover, we found that the MERS-CoV infection that occurs in one country may not necessarily come from the same country of origin. This suggests that the process of MERS-CoV mutation might not only be influenced by geographical factor.

A STUDY OF HIERARCHICAL ORGANIZATION LOCATION MODEL FOR SERVICE INDUSTRY ENTERPRISE

NASA Astrophysics Data System (ADS)

Okumura, Makoto; Takada, Naoki; Okubo, Kazuaki

The service industry has come to participate in many economic activities, but there are few studies, which analyze on the hierarchical organization location of a service industry enterprise that treats information. We propose a hierarchical organized location model, which endogenously determines the number of hierarchies. Furtheremore, We propose a MCMC based statistical method to obtain parameter distributions corresponding to the observed macro emplowment distribution as well as the saralies paid. By using our model, we analyzed the regional disparities about the number of employees and the wage. We found that the change of the regional disparities is caused by internal factors such as the industrial structural change, rather than external factors such as traffic condition changes.

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.

Hierarchical and Complex System Entropy Clustering Analysis Based Validation for Traditional Chinese Medicine Syndrome Patterns of Chronic Atrophic Gastritis.

PubMed

Zhang, Yin; Liu, Yue; Li, Yannan; Zhao, Xia; Zhuo, Lin; Zhou, Ajian; Zhang, Li; Su, Zeqi; Chen, Cen; Du, Shiyu; Liu, Daming; Ding, Xia

2018-03-22

Chronic atrophic gastritis (CAG) is the precancerous stage of gastric carcinoma. Traditional Chinese Medicine (TCM) has been widely used in treating CAG. This study aimed to reveal core pathogenesis of CAG by validating the TCM syndrome patterns and provide evidence for optimization of treatment strategies. This is a cross-sectional study conducted in 4 hospitals in China. Hierarchical clustering analysis (HCA) and complex system entropy clustering analysis (CSECA) were performed, respectively, to achieve syndrome pattern validation. Based on HCA, 15 common factors were assigned to 6 syndrome patterns: liver depression and spleen deficiency and blood stasis in the stomach collateral, internal harassment of phlegm-heat and blood stasis in the stomach collateral, phlegm-turbidity internal obstruction, spleen yang deficiency, internal harassment of phlegm-heat and spleen deficiency, and spleen qi deficiency. By CSECA, 22 common factors were assigned to 7 syndrome patterns: qi deficiency, qi stagnation, blood stasis, phlegm turbidity, heat, yang deficiency, and yin deficiency. Combination of qi deficiency, qi stagnation, blood stasis, phlegm turbidity, heat, yang deficiency, and yin deficiency may play a crucial role in CAG pathogenesis. In accord with this, treatment strategies by TCM herbal prescriptions should be targeted to regulating qi, activating blood, resolving turbidity, clearing heat, removing toxin, nourishing yin, and warming yang. Further explorations are needed to verify and expand the current conclusions.

Hierarchical clustering using correlation metric and spatial continuity constraint

DOEpatents

Stork, Christopher L.; Brewer, Luke N.

2012-10-02

Large data sets are analyzed by hierarchical clustering using correlation as a similarity measure. This provides results that are superior to those obtained using a Euclidean distance similarity measure. A spatial continuity constraint may be applied in hierarchical clustering analysis of images.

Chemical Structure and Molecular Dimension As Controls on the Inherent Stability of Charcoal in Boreal Forest Soil

NASA Astrophysics Data System (ADS)

Hockaday, W. C.; Kane, E. S.; Ohlson, M.; Huang, R.; Von Bargen, J.; Davis, R.

2014-12-01

Efforts have been made by various scientific disciplines to study hyporheic zones and characterize their associated processes. One way to approach the study of the hyporheic zone is to define facies, which are elements of a (hydrobio) geologic classification scheme that groups components of a complex system with high variability into a manageable set of discrete classes. In this study, we try to classify the hyporheic zone based on the geology, geochemistry, microbiology, and understand their interactive influences on the integrated biogeochemical distributions and processes. A number of measurements have been taken for 21 freeze core samples along the Columbia River bank in the Hanford 300 Area, and unique datasets have been obtained on biomass, pH, number of microbial taxa, percentage of N/C/H/S, microbial activity parameters, as well as microbial community attributes/modules. In order to gain a complete understanding of the geological control on these variables and processes, the explanatory variables are set to include quantitative gravel/sand/mud/silt/clay percentages, statistical moments of grain size distributions, as well as geological (e.g., Folk-Wentworth) and statistical (e.g., hierarchical) clusters. The dominant factors for major microbial and geochemical variables are identified and summarized using exploratory data analysis approaches (e.g., principal component analysis, hierarchical clustering, factor analysis, multivariate analysis of variance). The feasibility of extending the facies definition and its control of microbial and geochemical properties to larger scales is discussed.

Microbial facies distribution and its geological and geochemical controls at the Hanford 300 area

NASA Astrophysics Data System (ADS)

Hou, Z.; Nelson, W.; Stegen, J.; Murray, C. J.; Arntzen, E.

2015-12-01

Efforts have been made by various scientific disciplines to study hyporheic zones and characterize their associated processes. One way to approach the study of the hyporheic zone is to define facies, which are elements of a (hydrobio) geologic classification scheme that groups components of a complex system with high variability into a manageable set of discrete classes. In this study, we try to classify the hyporheic zone based on the geology, geochemistry, microbiology, and understand their interactive influences on the integrated biogeochemical distributions and processes. A number of measurements have been taken for 21 freeze core samples along the Columbia River bank in the Hanford 300 Area, and unique datasets have been obtained on biomass, pH, number of microbial taxa, percentage of N/C/H/S, microbial activity parameters, as well as microbial community attributes/modules. In order to gain a complete understanding of the geological control on these variables and processes, the explanatory variables are set to include quantitative gravel/sand/mud/silt/clay percentages, statistical moments of grain size distributions, as well as geological (e.g., Folk-Wentworth) and statistical (e.g., hierarchical) clusters. The dominant factors for major microbial and geochemical variables are identified and summarized using exploratory data analysis approaches (e.g., principal component analysis, hierarchical clustering, factor analysis, multivariate analysis of variance). The feasibility of extending the facies definition and its control of microbial and geochemical properties to larger scales is discussed.

Hierarchical analysis of cardiovascular risk factors in relation to the development of acute coronary syndromes, in different parts of Greece: the CARDIO2000 study.

PubMed

Panagiotakos, Demosthenes B; Pitsavos, Christos; Chrysohoou, Christine; Stefanadis, Christodoulos

2008-01-01

During 2000 to 2002, 700 men (59 +/- 10 years) and 148 women (65 +/- 9 years) patients with first event of an ACS were randomly selected from cardiology clinics of Greek regions. Afterwards, 1078 population-based, age-matched and sex-matched controls were randomly selected from the same hospitals. The frequency ratio between men and women in the case series of patients was about 4:1, in both south and north Greek areas. Hierarchical classification analysis showed that for north Greek areas family history of coronary heart disease, hypercholesterolemia, hypertension, diabetes (explained variability 35%), and less significantly, dietary habits, smoking, body mass index, and physical activity status (explained variability 4%) were associated with the development of ACS, whereas for south Greek areas hypercholesterolemia, family history of coronary heart disease, diabetes, smoking, hypertension, dietary habits, physical activity (explained variability 34%), and less significantly body mass index (explained variability <1%), were associated with the development of the disease.

Organizational citizenship behavior in schools: validation of a questionnaire.

PubMed

Neves, Paula C; Paixão, Rui; Alarcão, Madalena; Gomes, A Duarte

2014-01-01

The present study examines the psychometric properties (including factorial validity) of an organizational citizenship behavior (OCB) scale in a school context. A total of 321 middle and high school teachers from 59 schools in urban and rural areas of central Portugal completed the OCB scale at their schools. The confirmatory factor analysis validated a hierarchical model with four latent factors on the first level (altruism, conscientiousness, civic participation and courtesy) and a second order factor (OCB). The revised model fit with the data, χ 2 /gl = 1.97; CFI = .962; GFI = .952, RMSEA = .05. The proposed scale (comportamentos de cidadania organizacional em escolas- Revista CCOE-R)- is a valid instrument to assess teacher's perceptions of OCB in their schools, allowing investigation at the organizational level of analysis.

Positive predictors of quality of life for postpartum mothers with a history of childhood maltreatment.

PubMed

Irwin, Jessica L; Beeghly, Marjorie; Rosenblum, Katherine L; Muzik, Maria

2016-12-01

The postpartum period brings a host of biopsychosocial, familial, and economic changes, which may be challenging for new mothers, especially those with trauma histories. Trauma-exposed women are at heightened risk for psychiatric symptomatology and reduced quality of life. The current study sought to evaluate whether a set of hypothesized promotive factors assessed during the first 18 months postpartum (positive parenting, family cohesion, and maternal resilience) are associated with life satisfaction in this population, after controlling for income and postpartum psychiatric symptoms. Analyses were based on data collected for 266 mother-infant dyads from a longitudinal cohort study, Maternal Anxiety during the Childbearing Years (MACY), of women oversampled for childhood maltreatment history. Hierarchical linear regression was used to evaluate the study hypotheses. Consistent with prior work, greater postpartum psychiatric symptoms and less income predicted poor perceptions of life quality. In hierarchical regressions controlling for income and psychiatric symptoms, positive parenting and family cohesion predicted unique variance in mothers' positive perceptions of life quality, and resilience was predictive beyond all other factors. Factors from multiple levels of analysis (maternal, dyadic, and familial) may serve as promotive factors predicting positive perceptions of life quality among women with childhood trauma histories, even those struggling with high levels of psychiatric or economic distress.

An effective immunization strategy for airborne epidemics in modular and hierarchical social contact network

NASA Astrophysics Data System (ADS)

Song, Zhichao; Ge, Yuanzheng; Luo, Lei; Duan, Hong; Qiu, Xiaogang

2015-12-01

Social contact between individuals is the chief factor for airborne epidemic transmission among the crowd. Social contact networks, which describe the contact relationships among individuals, always exhibit overlapping qualities of communities, hierarchical structure and spatial-correlated. We find that traditional global targeted immunization strategy would lose its superiority in controlling the epidemic propagation in the social contact networks with modular and hierarchical structure. Therefore, we propose a hierarchical targeted immunization strategy to settle this problem. In this novel strategy, importance of the hierarchical structure is considered. Transmission control experiments of influenza H1N1 are carried out based on a modular and hierarchical network model. Results obtained indicate that hierarchical structure of the network is more critical than the degrees of the immunized targets and the modular network layer is the most important for the epidemic propagation control. Finally, the efficacy and stability of this novel immunization strategy have been validated as well.

Factors associated with preventable infant death: a multiple logistic regression.

PubMed

Vidal E Silva, Sandra Maria Cunha; Tuon, Rogério Antonio; Probst, Livia Fernandes; Gondinho, Brunna Verna Castro; Pereira, Antonio Carlos; Meneghim, Marcelo de Castro; Cortellazzi, Karine Laura; Ambrosano, Glaucia Maria Bovi

2018-01-01

OBJECTIVE To identify and analyze factors associated with preventable child deaths. METHODS This analytical cross-sectional study had preventable child mortality as dependent variable. From a population of 34,284 live births, we have selected a systematic sample of 4,402 children who did not die compared to 272 children who died from preventable causes during the period studied. The independent variables were analyzed in four hierarchical blocks: sociodemographic factors, the characteristics of the mother, prenatal and delivery care, and health conditions of the patient and neonatal care. We performed a descriptive statistical analysis and estimated multiple hierarchical logistic regression models. RESULTS Approximatelly 35.3% of the deaths could have been prevented with the early diagnosis and treatment of diseases during pregnancy and 26.8% of them could have been prevented with better care conditions for pregnant women. CONCLUSIONS The following characteristics of the mother are determinant for the higher mortality of children before the first year of life: living in neighborhoods with an average family income lower than four minimum wages, being aged ≤ 19 years, having one or more alive children, having a child with low APGAR level at the fifth minute of life, and having a child with low birth weight.

Predictors affecting personal health information management skills.

PubMed

Kim, Sujin; Abner, Erin

2016-01-01

This study investigated major factors affecting personal health records (PHRs) management skills associated with survey respondents' health information management related activities. A self-report survey was used to assess individuals' personal characteristics, health knowledge, PHR skills, and activities. Factors underlying respondents' current PHR-related activities were derived using principal component analysis (PCA). Scale scores were calculated based on the results of the PCA, and hierarchical linear regression analyses were used to identify respondent characteristics associated with the scale scores. Internal consistency of the derived scale scores was assessed with Cronbach's α. Among personal health information activities surveyed (N = 578 respondents), the four extracted factors were subsequently grouped and labeled as: collecting skills (Cronbach's α = 0.906), searching skills (Cronbach's α = 0.837), sharing skills (Cronbach's α = 0.763), and implementing skills (Cronbach's α = 0.908). In the hierarchical regression analyses, education and computer knowledge significantly increased the explanatory power of the models. Health knowledge (β = 0.25, p < 0.001) emerged as a positive predictor of PHR collecting skills. This study confirmed that PHR training and learning should consider a full spectrum of information management skills including collection, utilization and distribution to support patients' care and prevention continua.

Linking bovine tuberculosis on cattle farms to white-tailed deer and environmental variables using Bayesian hierarchical analysis

USGS Publications Warehouse

Walter, W. David; Smith, Rick; Vanderklok, Mike; VerCauterren, Kurt C.

2014-01-01

Bovine tuberculosis is a bacterial disease caused by Mycobacterium bovis in livestock and wildlife with hosts that include Eurasian badgers (Meles meles), brushtail possum (Trichosurus vulpecula), and white-tailed deer (Odocoileus virginianus). Risk-assessment efforts in Michigan have been initiated on farms to minimize interactions of cattle with wildlife hosts but research onM. bovis on cattle farms has not investigated the spatial context of disease epidemiology. To incorporate spatially explicit data, initial likelihood of infection probabilities for cattle farms tested for M. bovis, prevalence of M. bovis in white-tailed deer, deer density, and environmental variables for each farm were modeled in a Bayesian hierarchical framework. We used geo-referenced locations of 762 cattle farms that have been tested for M. bovis, white-tailed deer prevalence, and several environmental variables that may lead to long-term survival and viability of M. bovis on farms and surrounding habitats (i.e., soil type, habitat type). Bayesian hierarchical analyses identified deer prevalence and proportion of sandy soil within our sampling grid as the most supported model. Analysis of cattle farms tested for M. bovisidentified that for every 1% increase in sandy soil resulted in an increase in odds of infection by 4%. Our analysis revealed that the influence of prevalence of M. bovis in white-tailed deer was still a concern even after considerable efforts to prevent cattle interactions with white-tailed deer through on-farm mitigation and reduction in the deer population. Cattle farms test positive for M. bovis annually in our study area suggesting that the potential for an environmental source either on farms or in the surrounding landscape may contributing to new or re-infections with M. bovis. Our research provides an initial assessment of potential environmental factors that could be incorporated into additional modeling efforts as more knowledge of deer herd factors and cattle farm prevalence is documented.

Hierarchical Task Analysis and Training Decisions.

ERIC Educational Resources Information Center

Shepherd, A.

1985-01-01

Hierarchical task analysis (HTA), which requires description of a task in terms of a hierarchy of operations and plans, is reviewed and examined as a basis for making training decisions. Benefits of HTA in terms of economy of analysis and as a means of accounting for complex performance are outlined. (Author/MBR)

Confirmatory Factor Analysis of the Combined Social Phobia Scale and Social Interaction Anxiety Scale: Support for a Bifactor Model.

PubMed

Gomez, Rapson; Watson, Shaun D

2017-01-01

For the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS) together, this study examined support for a bifactor model, and also the internal consistency reliability and external validity of the factors in this model. Participants ( N = 526) were adults from the general community who completed the SPS and SIAS. Confirmatory factor analysis (CFA) of their ratings indicated good support for the bifactor model. For this model, the loadings for all but six items were higher on the general factor than the specific factors. The three positively worded items had negligible loadings on the general factor. The general factor explained most of the common variance in the SPS and SIAS, and demonstrated good model-based internal consistency reliability (omega hierarchical) and a strong association with fear of negative evaluation and extraversion. The practical implications of the findings for the utilization of the SPS and SIAS, and the theoretical and clinical implications for social anxiety are discussed.

Confirmatory Factor Analysis of the Combined Social Phobia Scale and Social Interaction Anxiety Scale: Support for a Bifactor Model

PubMed Central

Gomez, Rapson; Watson, Shaun D.

2017-01-01

For the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS) together, this study examined support for a bifactor model, and also the internal consistency reliability and external validity of the factors in this model. Participants (N = 526) were adults from the general community who completed the SPS and SIAS. Confirmatory factor analysis (CFA) of their ratings indicated good support for the bifactor model. For this model, the loadings for all but six items were higher on the general factor than the specific factors. The three positively worded items had negligible loadings on the general factor. The general factor explained most of the common variance in the SPS and SIAS, and demonstrated good model-based internal consistency reliability (omega hierarchical) and a strong association with fear of negative evaluation and extraversion. The practical implications of the findings for the utilization of the SPS and SIAS, and the theoretical and clinical implications for social anxiety are discussed. PMID:28210232

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

Analyzing Multilevel Factors Underlying Adolescent Smoking Behaviors: The Roles of Friendship Network, Family Relations, and School Environment.

PubMed

Kim, Harris H-S; Chun, JongSerl

2018-06-01

This study investigates the extent to which friendship network, family relations, and school context are related to adolescent cigarette smoking. Friendship network is measured in terms of delinquent peers; family relations in terms of parental supervision; and school environment in terms of objective (eg, antismoking policy) and subjective (eg, school attachment) characteristics. Findings are based on the secondary analysis of the health behavior in school-aged children, 2009-2010. Two-level hierarchical generalized linear models are estimated using hierarchical linear modeling 7. At the student level, ties to delinquent friends is significantly related to higher odds of smoking, while greater parental supervision is associated with lower odds. At the school level, antismoking policy and curriculum independently lower smoking behavior. Better within-class peer relations, greater school attachment, and higher academic performance are also negatively related to smoking. Last, the positive association between delinquent friends and smoking is weaker in schools with a formally enacted antismoking policy. However, this association is stronger in schools with better peer relations. Adolescent smoking behavior is embedded in a broader ecological setting. This research reveals that a proper understanding of it requires comprehensive analysis that incorporates factors measured at individual (student) and contextual (school) levels. © 2018, American School Health Association.

Exploring the Specifications of Spatial Adjacencies and Weights in Bayesian Spatial Modeling with Intrinsic Conditional Autoregressive Priors in a Small-area Study of Fall Injuries

PubMed Central

Law, Jane

2016-01-01

Intrinsic conditional autoregressive modeling in a Bayeisan hierarchical framework has been increasingly applied in small-area ecological studies. This study explores the specifications of spatial structure in this Bayesian framework in two aspects: adjacency, i.e., the set of neighbor(s) for each area; and (spatial) weight for each pair of neighbors. Our analysis was based on a small-area study of falling injuries among people age 65 and older in Ontario, Canada, that was aimed to estimate risks and identify risk factors of such falls. In the case study, we observed incorrect adjacencies information caused by deficiencies in the digital map itself. Further, when equal weights was replaced by weights based on a variable of expected count, the range of estimated risks increased, the number of areas with probability of estimated risk greater than one at different probability thresholds increased, and model fit improved. More importantly, significance of a risk factor diminished. Further research to thoroughly investigate different methods of variable weights; quantify the influence of specifications of spatial weights; and develop strategies for better defining spatial structure of a map in small-area analysis in Bayesian hierarchical spatial modeling is recommended. PMID:29546147

Influenza vaccine response profiles are affected by vaccine preparation and preexisting immunity, but not HIV infection.

PubMed

Berger, Christoph T; Greiff, Victor; Mehling, Matthias; Fritz, Stefanie; Meier, Marc A; Hoenger, Gideon; Conen, Anna; Recher, Mike; Battegay, Manuel; Reddy, Sai T; Hess, Christoph

2015-01-01

Vaccines dramatically reduce infection-related morbidity and mortality. Determining factors that modulate the host response is key to rational vaccine design and demands unsupervised analysis. To longitudinally resolve influenza-specific humoral immune response dynamics we constructed vaccine response profiles of influenza A- and B-specific IgM and IgG levels from 42 healthy and 31 HIV infected influenza-vaccinated individuals. Pre-vaccination antibody levels and levels at 3 predefined time points after vaccination were included in each profile. We performed hierarchical clustering on these profiles to study the extent to which HIV infection associated immune dysfunction, adaptive immune factors (pre-existing influenza-specific antibodies, T cell responses), an innate immune factor (Mannose Binding Lectin, MBL), demographic characteristics (gender, age), or the vaccine preparation (split vs. virosomal) impacted the immune response to influenza vaccination. Hierarchical clustering associated vaccine preparation and pre-existing IgG levels with the profiles of healthy individuals. In contrast to previous in vitro and animal data, MBL levels had no impact on the adaptive vaccine response. Importantly, while HIV infected subjects with low CD4 T cell counts showed a reduced magnitude of their vaccine response, their response profiles were indistinguishable from those of healthy controls, suggesting quantitative but not qualitative deficits. Unsupervised profile-based analysis ranks factors impacting the vaccine-response by relative importance, with substantial implications for comparing, designing and improving vaccine preparations and strategies. Profile similarity between HIV infected and HIV negative individuals suggests merely quantitative differences in the vaccine response in these individuals, offering a rationale for boosting strategies in the HIV infected population.

STEM development: A study of 6th--12th grade girls' interest and confidence in mathematics and science

NASA Astrophysics Data System (ADS)

Heaverlo, Carol Ann

Researchers, policymakers, business, and industry have indicated that the United States will experience a shortage of professionals in the Science, Technology, Engineering, and Mathematics (STEM) fields. Several strategies have been suggested to address this shortage, one of which includes increasing the representation of girls and women in the STEM fields. In order to increase the representation of women in the STEM fields, it is important to understand the developmental factors that impact girls' interest and confidence in STEM academics and extracurricular programs. Research indicates that greater confidence leads to greater interest and vice versa (Denissen et al., 2007). This study identifies factors that impact girls' interest and confidence in mathematics and science, defined as girls' STEM development. Using Bronfenbrenner's (2005) bioecological model of human development, several factors were hypothesized as having an impact on girls' STEM development; specifically, the macrosystems of region of residence and race/ethnicity, and the microsystems of extracurricular STEM activities, family STEM influence, and math/science teacher influence. Hierarchical regression analysis results indicated that extracurricular STEM involvement and math teacher influence were statistically significant predictors for 6--12th grade girls' interest and confidence in mathematics. Furthermore, hierarchical regression analysis results indicated that the only significant predictor for 6--12th grade girls' interest and confidence in science was science teacher influence. This study provides new knowledge about the factors that impact girls' STEM development. Results can be used to inform and guide educators, administrators, and policy makers in developing programs and policy that support and encourage the STEM development of 6--12th grade girls.

Hierarchical cultural values predict success and mortality in high-stakes teams

PubMed Central

Anicich, Eric M.; Swaab, Roderick I.; Galinsky, Adam D.

2015-01-01

Functional accounts of hierarchy propose that hierarchy increases group coordination and reduces conflict. In contrast, dysfunctional accounts claim that hierarchy impairs performance by preventing low-ranking team members from voicing their potentially valuable perspectives and insights. The current research presents evidence for both the functional and dysfunctional accounts of hierarchy within the same dataset. Specifically, we offer empirical evidence that hierarchical cultural values affect the outcomes of teams in high-stakes environments through group processes. Experimental data from a sample of expert mountain climbers from 27 countries confirmed that climbers expect that a hierarchical culture leads to improved team coordination among climbing teams, but impaired psychological safety and information sharing compared with an egalitarian culture. An archival analysis of 30,625 Himalayan mountain climbers from 56 countries on 5,104 expeditions found that hierarchy both elevated and killed in the Himalayas: Expeditions from more hierarchical countries had more climbers reach the summit, but also more climbers die along the way. Importantly, we established the role of group processes by showing that these effects occurred only for group, but not solo, expeditions. These findings were robust to controlling for environmental factors, risk preferences, expedition-level characteristics, country-level characteristics, and other cultural values. Overall, this research demonstrates that endorsing cultural values related to hierarchy can simultaneously improve and undermine group performance. PMID:25605883

DENTAL CARIES AND RELATED ORAL HEALTH FACTORS AMONG 9 TO 18 MONTH OLD THAI CHILDREN.

PubMed

Detsomboonrat, Palinee; Pisarnturakit, Pagaporn Pantuwadee

2015-07-01

Dental caries can occur as soon as the first tooth erupts. We studied the caries prevalence and related risk factors among children aged 9-18 months in U Thong District, Suphan Buri Province, Thailand. A total of 151 children, whose primary caregivers were willing to participate in this study, were evaluated for decayed, missing, and filled tooth surfaces (dmfs). Questionnaires were given to the primary caregivers of the study subjects to ascertain their socio-economic status, oral hygiene habits, and child-feeding habits. The Mann-Whitney U and Kruskal-Wallis tests were used to evaluate bivariate outcome data. Hierarchical multiple regression analysis was used to determine variables predictive of dental caries in the studied children. The prevalence of dental caries among the 151 subjects was 32.5%; 15.9% had at least one cavity (cavitated caries) and 16.6% had white lesions (non-cavitated caries). The mean dmfs score was 2.83 ± 6.48. Significant associations were seen between the dmfs score and the number of erupted teeth (p < 0.001) and toothpaste usage (p < 0.01). Hierarchical multiple regression analysis revealed four factors significantly associated with caries: number of erupted teeth, which had the highest Beta value (P = 0.35, p < 0.01), nighttime bottle feeding (P = 0.17, p < 0.05), frequency of drinking sweetened milk (P = 0.17-0.18, p < 0.05) and falling asleep with a bottle in the mouth (P = 0.18, p < 0.05). Nighttime bottle feeding, frequency of drinking sweetened milk and falling asleep with a bottle in the mouth were important caries risk factors and the number of erupted teeth was a strong caries risk predictor. Dentists should educate caregivers about these risk factors.

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…

Testing relationships from the hierarchical model of intrinsic and extrinsic motivation using flow as a motivational consequence.

PubMed

Kowal, J; Fortier, M S

2000-06-01

The purpose of this study was to test a motivational model based on Vallerand's (1997) Hierarchical Model of Intrinsic and Extrinsic Motivation. This model incorporates situational and contextual motivational variables, and was tested using a time-lagged design. Master's level swimmers (N = 104) completed a questionnaire on two separate occasions. At Time 1, situational social factors (perceptions of success and perceptions of the motivational climate), situational motivational mediators (perceptions of autonomy, competence, and relatedness), situational motivation, and flow were assessed immediately following a swim practice. Contextual measures of these same variables were assessed at Time 2, 1 week later, with the exception of flow. Results of a path analysis supported numerous links in the hypothesized model. Findings are discussed in light of research and theory on motivation and flow.

The Constraint Method for Solid Finite Elements.

DTIC Science & Technology

1980-09-30

9. ’Hierarchical Approximation in Finite Element Analysis", by I. Norman Katz, International Symposium on Innovative Numerical Analysis In Applied ... Engineering Science, Versailles, France, May 23-27, 1977. 10. "Efficient Generation of Hierarchal Finite Elamnts Through the Use of Precomputed Arrays

Association between prolonged breast-feeding and early childhood caries: a hierarchical approach.

PubMed

Nunes, Ana Margarida Melo; Alves, Claudia Maria Coelho; Borba de Araújo, Fernando; Ortiz, Tânia Mara Lopes; Ribeiro, Marizélia Rodrigues Costa; Silva, Antônio Augusto Moura da; Ribeiro, Cecília Claudia Costa

2012-12-01

This study was conducted to investigate the association between prolonged breastfeeding and early childhood caries(ECC) with adjustment for important confounders, using hieraschical approach. This retrospective cohort study involved 260 low-income children (18-42 months). The number of decayed teeth was used as a measure of caries. Following a theoretical framework, the hierarchical model was built in a forward fashion, by adding the following levels in succession: level 1: age; level 2: social variables; level 3: health variables; level 4: behavioral variables; level 5: oral hygiene-related variables; level 6: oral hygiene quality measured by visible plaque; and level 7: contamination by mutans streptococci. Sequential forward multiple Poisson regression analysis was employed. Breast-feeding was not a risk factor for ECC after adjustment for some confounders (incidence density ratio, 1.15; 95% confidence interval, 0.84-1.59, P = 0.363). Prolonged breast-feeding was not a risk factor for ECC while age, high sucrose comption between main meals and the quality of oral higiene were associated with disease in children. © 2012 John Wiley & Sons A/S.

Hierarchical Effects of School-, Classroom-, and Student-Level Factors on the Science Performance of Eighth-Grade Taiwanese Students

NASA Astrophysics Data System (ADS)

Tsai, Liang-Ting; Yang, Chih-Chien

2015-05-01

This study was conducted to understand the effect of student-, classroom-, and school-level factors on the science performance of 8th-grade Taiwanese students in the Trends in International Mathematics and Science Study (TIMSS) 2011 by using multilevel analysis. A total of 5,042 students from 153 classrooms of 150 schools participated in the TIMSS 2011 study, in which they were required to complete questionnaires. A 3-level multilevel analysis was used to assess the influence of factors at 3 levels on the science performance of 8th-grade Taiwanese students. The results showed that the provision of education resources at home, teachers' level of education, and school climate were the strongest predictor of science performance at the student, classroom, and school level, respectively. It was concluded that the science performance of 8th-grade Taiwanese students is driven largely by individual factors. Classroom-level factors accounted for a smaller proportion of the total variance in science performance than did school-level factors.

The Incremental Multiresolution Matrix Factorization Algorithm

PubMed Central

Ithapu, Vamsi K.; Kondor, Risi; Johnson, Sterling C.; Singh, Vikas

2017-01-01

Multiresolution analysis and matrix factorization are foundational tools in computer vision. In this work, we study the interface between these two distinct topics and obtain techniques to uncover hierarchical block structure in symmetric matrices – an important aspect in the success of many vision problems. Our new algorithm, the incremental multiresolution matrix factorization, uncovers such structure one feature at a time, and hence scales well to large matrices. We describe how this multiscale analysis goes much farther than what a direct “global” factorization of the data can identify. We evaluate the efficacy of the resulting factorizations for relative leveraging within regression tasks using medical imaging data. We also use the factorization on representations learned by popular deep networks, providing evidence of their ability to infer semantic relationships even when they are not explicitly trained to do so. We show that this algorithm can be used as an exploratory tool to improve the network architecture, and within numerous other settings in vision. PMID:29416293

Bayesian Variable Selection for Hierarchical Gene-Environment and Gene-Gene Interactions

PubMed Central

Liu, Changlu; Ma, Jianzhong; Amos, Christopher I.

2014-01-01

We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions and gene by environment interactions in the same model. Our approach incorporates the natural hierarchical structure between the main effects and interaction effects into a mixture model, such that our methods tend to remove the irrelevant interaction effects more effectively, resulting in more robust and parsimonious models. We consider both strong and weak hierarchical models. For a strong hierarchical model, both of the main effects between interacting factors must be present for the interactions to be considered in the model development, while for a weak hierarchical model, only one of the two main effects is required to be present for the interaction to be evaluated. Our simulation results show that the proposed strong and weak hierarchical mixture models work well in controlling false positive rates and provide a powerful approach for identifying the predisposing effects and interactions in gene-environment interaction studies, in comparison with the naive model that does not impose this hierarchical constraint in most of the scenarios simulated. We illustrated our approach using data for lung cancer and cutaneous melanoma. PMID:25154630

Isolating causal pathways between flow and fish in the regulated river hierarchy

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

McManamay, Ryan A.; Peoples, Brandon K.; Orth, Donald J.

Unregulated river systems are organized in a hierarchy in which large-scale factors (i.e., landscape and segment scales) influence local habitats (i.e., reach, meso-, and microhabitat scales), and both differentially exert selective pressures on biota. Dams, however, create discontinua in these processes and change the hierarchical structure. We examined the relative roles of hydrology and other instream factors, within a hierarchical landscape context, in organizing fish communities in regulated and unregulated tributaries to the Upper Tennessee River, USA. We also used multivariate regression trees to identify factors that partition fish assemblages based on trait similarities, irrespective of spatial scale. Then, wemore » used classical path analysis and structural equation modeling to evaluate the most plausible hierarchical causal structure of specific trait-based community components, given the data. Both statistical approaches suggested that river regulation affects stream fishes through a variety of reach-scale variables, not always through hydrology itself. Though we observed different changes in flow, temperature, and biotic responses according to regulation types, the most predominant path in which dam regulation affected biota was via temperature alterations. Diversion dams had the strongest effects on fish assemblages. Diversion dams reduced flow magnitudes, leading to declines in fish richness but increased temperatures, leading to lower abundances in equilibrium species and nest guarders. Peaking and run-of-river dams increased flow variability, leading to lower abundances in nest-guarding fishes. Flow displayed direct relationships with biotic responses; however, results indicated that changes in temperature and substrate had equal, if not stronger, effects on fish assemblage composition. The strength and nature of relationships depended on whether flow metrics were standardized for river size. Here, we suggest that restoration efforts in regulated rivers focus on improving flow conditions in conjunction with temperature and substrate restoration.« less

Isolating causal pathways between flow and fish in the regulated river hierarchy

DOE PAGES

McManamay, Ryan A.; Peoples, Brandon K.; Orth, Donald J.; ...

2015-07-07

Unregulated river systems are organized in a hierarchy in which large-scale factors (i.e., landscape and segment scales) influence local habitats (i.e., reach, meso-, and microhabitat scales), and both differentially exert selective pressures on biota. Dams, however, create discontinua in these processes and change the hierarchical structure. We examined the relative roles of hydrology and other instream factors, within a hierarchical landscape context, in organizing fish communities in regulated and unregulated tributaries to the Upper Tennessee River, USA. We also used multivariate regression trees to identify factors that partition fish assemblages based on trait similarities, irrespective of spatial scale. Then, wemore » used classical path analysis and structural equation modeling to evaluate the most plausible hierarchical causal structure of specific trait-based community components, given the data. Both statistical approaches suggested that river regulation affects stream fishes through a variety of reach-scale variables, not always through hydrology itself. Though we observed different changes in flow, temperature, and biotic responses according to regulation types, the most predominant path in which dam regulation affected biota was via temperature alterations. Diversion dams had the strongest effects on fish assemblages. Diversion dams reduced flow magnitudes, leading to declines in fish richness but increased temperatures, leading to lower abundances in equilibrium species and nest guarders. Peaking and run-of-river dams increased flow variability, leading to lower abundances in nest-guarding fishes. Flow displayed direct relationships with biotic responses; however, results indicated that changes in temperature and substrate had equal, if not stronger, effects on fish assemblage composition. The strength and nature of relationships depended on whether flow metrics were standardized for river size. Here, we suggest that restoration efforts in regulated rivers focus on improving flow conditions in conjunction with temperature and substrate restoration.« less

[The system-oriented model of psychosocial rehabilitation].

PubMed

Iastrebov V S; Mitikhin, V G; Solokhina, T A; Mikhaĭlova, I I

2008-01-01

A model of psychosocial rehabilitation based on the system approach that allows taking into account both the patient-centered approach of the rehabilitation service, the development of its resource basis, the effectiveness of this care system in whole and its patterns as well has been worked out. In the framework of this model, the authors suggest to single out three basic stages of the psychosocial rehabilitation process: evaluation and planning, rehabilitation interventions per se, achievement of the result. In author's opinion, the most successful way for constructing a modern model of psychosocial rehabilitation is a method of hierarchic modeling which can reveal a complex chain of interactions between all participants of the rehabilitation process and factors involved in this process and at the same time specify the multi-level hierarchic character of these interactions and factors. An important advantage of this method is the possibility of obtaining as static as well dynamic evaluations of the rehabilitation service activity that may be used on the following levels: 1) patient; 2) his/her close environment; 3) macrosocial level. The obvious merits of the system-oriented model appear to be the possibility of application of its principles in the organization of specialized care for psychiatric patients on the local, regional and federal levels. The authors emphasize that hierarchic models have universal character and can be implemented in the elaboration of information-analytical systems aimed at solving the problems of monitoring and analysis of social-medical service activity in order to increase its effectiveness.

[Prognostic differences of phenotypes in pT1-2N0 invasive breast cancer: a large cohort study with cluster analysis].

PubMed

Wang, Z; Wang, W H; Wang, S L; Jin, J; Song, Y W; Liu, Y P; Ren, H; Fang, H; Tang, Y; Chen, B; Qi, S N; Lu, N N; Li, N; Tang, Y; Liu, X F; Yu, Z H; Li, Y X

2016-06-23

To find phenotypic subgroups of patients with pT1-2N0 invasive breast cancer by means of cluster analysis and estimate the prognosis and clinicopathological features of these subgroups. From 1999 to 2013, 4979 patients with pT1-2N0 invasive breast cancer were recruited for hierarchical clustering analysis. Age (≤40, 41-70, 70+ years), size of primary tumor, pathological type, grade of differentiation, microvascular invasion, estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER-2) were chosen as distance metric between patients. Hierarchical cluster analysis was performed using Ward's method. Cophenetic correlation coefficient (CPCC) and Spearman correlation coefficient were used to validate clustering structures. The CPCC was 0.603. The Spearman correlation coefficient was 0.617 (P<0.001), which indicated a good fit of hierarchy to the data. A twelve-cluster model seemed to best illustrate our patient cohort. Patients in cluster 5, 9 and 12 had best prognosis and were characterized by age >40 years, smaller primary tumor, lower histologic grade, positive ER and PR status, and mainly negative HER-2. Patients in the cluster 1 and 11 had the worst prognosis, The cluster 1 was characterized by a larger tumor, higher grade and negative ER and PR status, while the cluster 11 was characterized by positive microvascular invasion. Patients in other 7 clusters had a moderate prognosis, and patients in each cluster had distinctive clinicopathological features and recurrent patterns. This study identified distinctive clinicopathologic phenotypes in a large cohort of patients with pT1-2N0 breast cancer through hierarchical clustering and revealed different prognosis. This integrative model may help physicians to make more personalized decisions regarding adjuvant therapy.

Driver injury severity outcome analysis in rural interstate highway crashes: a two-level Bayesian logistic regression interpretation.

PubMed

Chen, Cong; Zhang, Guohui; Liu, Xiaoyue Cathy; Ci, Yusheng; Huang, Helai; Ma, Jianming; Chen, Yanyan; Guan, Hongzhi

2016-12-01

There is a high potential of severe injury outcomes in traffic crashes on rural interstate highways due to the significant amount of high speed traffic on these corridors. Hierarchical Bayesian models are capable of incorporating between-crash variance and within-crash correlations into traffic crash data analysis and are increasingly utilized in traffic crash severity analysis. This paper applies a hierarchical Bayesian logistic model to examine the significant factors at crash and vehicle/driver levels and their heterogeneous impacts on driver injury severity in rural interstate highway crashes. Analysis results indicate that the majority of the total variance is induced by the between-crash variance, showing the appropriateness of the utilized hierarchical modeling approach. Three crash-level variables and six vehicle/driver-level variables are found significant in predicting driver injury severities: road curve, maximum vehicle damage in a crash, number of vehicles in a crash, wet road surface, vehicle type, driver age, driver gender, driver seatbelt use and driver alcohol or drug involvement. Among these variables, road curve, functional and disabled vehicle damage in crash, single-vehicle crashes, female drivers, senior drivers, motorcycles and driver alcohol or drug involvement tend to increase the odds of drivers being incapably injured or killed in rural interstate crashes, while wet road surface, male drivers and driver seatbelt use are more likely to decrease the probability of severe driver injuries. The developed methodology and estimation results provide insightful understanding of the internal mechanism of rural interstate crashes and beneficial references for developing effective countermeasures for rural interstate crash prevention. Copyright © 2016 Elsevier Ltd. All rights reserved.

Towards scar-free surgery: An analysis of the increasing complexity from laparoscopic surgery to NOTES

PubMed Central

Chellali, Amine; Schwaitzberg, Steven D.; Jones, Daniel B.; Romanelli, John; Miller, Amie; Rattner, David; Roberts, Kurt E.; Cao, Caroline G.L.

2014-01-01

Background NOTES is an emerging technique for performing surgical procedures, such as cholecystectomy. Debate about its real benefit over the traditional laparoscopic technique is on-going. There have been several clinical studies comparing NOTES to conventional laparoscopic surgery. However, no work has been done to compare these techniques from a Human Factors perspective. This study presents a systematic analysis describing and comparing different existing NOTES methods to laparoscopic cholecystectomy. Methods Videos of endoscopic/laparoscopic views from fifteen live cholecystectomies were analyzed to conduct a detailed task analysis of the NOTES technique. A hierarchical task analysis of laparoscopic cholecystectomy and several hybrid transvaginal NOTES cholecystectomies was performed and validated by expert surgeons. To identify similarities and differences between these techniques, their hierarchical decomposition trees were compared. Finally, a timeline analysis was conducted to compare the steps and substeps. Results At least three variations of the NOTES technique were used for cholecystectomy. Differences between the observed techniques at the substep level of hierarchy and on the instruments being used were found. The timeline analysis showed an increase in time to perform some surgical steps and substeps in NOTES compared to laparoscopic cholecystectomy. Conclusion As pure NOTES is extremely difficult given the current state of development in instrumentation design, most surgeons utilize different hybrid methods – combination of endoscopic and laparoscopic instruments/optics. Results of our hierarchical task analysis yielded an identification of three different hybrid methods to perform cholecystectomy with significant variability amongst them. The varying degrees to which laparoscopic instruments are utilized to assist in NOTES methods appear to introduce different technical issues and additional tasks leading to an increase in the surgical time. The NOTES continuum of invasiveness is proposed here as a classification scheme for these methods, which was used to construct a clear roadmap for training and technology development. PMID:24902811

Proportion of general factor variance in a hierarchical multiple-component measuring instrument: a note on a confidence interval estimation procedure.

PubMed

Raykov, Tenko; Zinbarg, Richard E

2011-05-01

A confidence interval construction procedure for the proportion of explained variance by a hierarchical, general factor in a multi-component measuring instrument is outlined. The method provides point and interval estimates for the proportion of total scale score variance that is accounted for by the general factor, which could be viewed as common to all components. The approach may also be used for testing composite (one-tailed) or simple hypotheses about this proportion, and is illustrated with a pair of examples. ©2010 The British Psychological Society.

Utilizing Hierarchical Segmentation to Generate Water and Snow Masks to Facilitate Monitoring Change with Remotely Sensed Image Data

NASA Technical Reports Server (NTRS)

Tilton, James C.; Lawrence, William T.; Plaza, Antonio J.

2006-01-01

The hierarchical segmentation (HSEG) algorithm is a hybrid of hierarchical step-wise optimization and constrained spectral clustering that produces a hierarchical set of image segmentations. This segmentation hierarchy organizes image data in a manner that makes the image's information content more accessible for analysis by enabling region-based analysis. This paper discusses data analysis with HSEG and describes several measures of region characteristics that may be useful analyzing segmentation hierarchies for various applications. Segmentation hierarchy analysis for generating landwater and snow/ice masks from MODIS (Moderate Resolution Imaging Spectroradiometer) data was demonstrated and compared with the corresponding MODIS standard products. The masks based on HSEG segmentation hierarchies compare very favorably to the MODIS standard products. Further, the HSEG based landwater mask was specifically tailored to the MODIS data and the HSEG snow/ice mask did not require the setting of a critical threshold as required in the production of the corresponding MODIS standard product.

The Analysis of Image Segmentation Hierarchies with a Graph-based Knowledge Discovery System

NASA Technical Reports Server (NTRS)

Tilton, James C.; Cooke, diane J.; Ketkar, Nikhil; Aksoy, Selim

2008-01-01

Currently available pixel-based analysis techniques do not effectively extract the information content from the increasingly available high spatial resolution remotely sensed imagery data. A general consensus is that object-based image analysis (OBIA) is required to effectively analyze this type of data. OBIA is usually a two-stage process; image segmentation followed by an analysis of the segmented objects. We are exploring an approach to OBIA in which hierarchical image segmentations provided by the Recursive Hierarchical Segmentation (RHSEG) software developed at NASA GSFC are analyzed by the Subdue graph-based knowledge discovery system developed by a team at Washington State University. In this paper we discuss out initial approach to representing the RHSEG-produced hierarchical image segmentations in a graphical form understandable by Subdue, and provide results on real and simulated data. We also discuss planned improvements designed to more effectively and completely convey the hierarchical segmentation information to Subdue and to improve processing efficiency.

Systems thinking applied to safety during manual handling tasks in the transport and storage industry.

PubMed

Goode, Natassia; Salmon, Paul M; Lenné, Michael G; Hillard, Peter

2014-07-01

Injuries resulting from manual handling tasks represent an on-going problem for the transport and storage industry. This article describes an application of a systems theory-based approach, Rasmussen's (1997. Safety Science 27, 183), risk management framework, to the analysis of the factors influencing safety during manual handling activities in a freight handling organisation. Observations of manual handling activities, cognitive decision method interviews with workers (n=27) and interviews with managers (n=35) were used to gather information about three manual handling activities. Hierarchical task analysis and thematic analysis were used to identify potential risk factors and performance shaping factors across the levels of Rasmussen's framework. These different data sources were then integrated using Rasmussen's Accimap technique to provide an overall analysis of the factors influencing safety during manual handling activities in this context. The findings demonstrate how a systems theory-based approach can be applied to this domain, and suggest that policy-orientated, rather than worker-orientated, changes are required to prevent future manual handling injuries. Copyright © 2013 Elsevier Ltd. All rights reserved.

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…

Factor Analysis of Computer-Based Multidimensional Aptitude Battery-Second Edition Intelligence Testing from Rated U.S. Air Force Pilots

DTIC Science & Technology

2012-09-01

intelligence continues to evolve as attention to cognitive processes and mechanisms, a deeper understanding of related issues, and new theories ...hierarchical models that describe specific abilities arranged according to increasing specificity and developmental complexity [6-8]. Theories have also...persistence) not tapped directly by existing measures of intellectual ability. Wechsler’s theory of intelligence is central to the development of the mostly

Modeling the risk of transmission of schistosomiasis in Akure North Local Government Area of Ondo State, Nigeria using satellite derived environmental data.

PubMed

Ajakaye, Oluwaremilekun G; Adedeji, Oluwatola I; Ajayi, Paul O

2017-07-01

Schistosomiasis is a parasitic disease and its distribution, in space and time, can be influenced by environmental factors such as rivers, elevation, slope, land surface temperature, land use/cover and rainfall. The aim of this study is to identify the areas with suitable conditions for schistosomiasis transmission on the basis of physical and environmental factors derived from satellite imagery and spatial analysis for Akure North Local Government Area (LGA) of Ondo State. Nigeria. This was done through methodology multicriteria evaluation (MCE) using Saaty's analytical hierarchy process (AHP). AHP is a multi-criteria decision method that uses hierarchical structures to represent a problem and makes decisions based on priority scales. In this research AHP was used to obtain the mapping weight or importance of each individual schistosomiasis risk factor. For the purpose of identifying areas of schistosomiasis risk, this study focused on temperature, drainage, elevation, rainfall, slope and land use/land cover as the factors controlling schistosomiasis incidence in the study area. It is by reclassifying and overlaying these factors that areas vulnerable to schistosomiasis were identified. The weighted overlay analysis was done after each factor was given the appropriate weight derived through the analytical hierarchical process. The prevalence of urinary schistosomiasis in the study area was also determined by parasitological analysis of urine samples collected through random sampling. The results showed varying risk of schistosomiasis with a larger portion of the area (82%) falling under the high and very high risk category. The study also showed that one community (Oba Ile) had the lowest risk of schistosomiasis while the risk increased in the four remaining communities (Iju, Igoba, Ita Ogbolu and Ogbese). The predictions made by the model correlated strongly with observations from field study. The high risk zones corresponded to known endemic communities. This study revealed that environmental factors can be used in identifying and predicting the transmission of schistosomiasis as well as effective monitoring of disease risk in newly established rural and agricultural communities.

Air toxics and birth defects: a Bayesian hierarchical approach to evaluate multiple pollutants and spina bifida.

PubMed

Swartz, Michael D; Cai, Yi; Chan, Wenyaw; Symanski, Elaine; Mitchell, Laura E; Danysh, Heather E; Langlois, Peter H; Lupo, Philip J

2015-02-09

While there is evidence that maternal exposure to benzene is associated with spina bifida in offspring, to our knowledge there have been no assessments to evaluate the role of multiple hazardous air pollutants (HAPs) simultaneously on the risk of this relatively common birth defect. In the current study, we evaluated the association between maternal exposure to HAPs identified by the United States Environmental Protection Agency (U.S. EPA) and spina bifida in offspring using hierarchical Bayesian modeling that includes Stochastic Search Variable Selection (SSVS). The Texas Birth Defects Registry provided data on spina bifida cases delivered between 1999 and 2004. The control group was a random sample of unaffected live births, frequency matched to cases on year of birth. Census tract-level estimates of annual HAP levels were obtained from the U.S. EPA's 1999 Assessment System for Population Exposure Nationwide. Using the distribution among controls, exposure was categorized as high exposure (>95(th) percentile), medium exposure (5(th)-95(th) percentile), and low exposure (<5(th) percentile, reference). We used hierarchical Bayesian logistic regression models with SSVS to evaluate the association between HAPs and spina bifida by computing an odds ratio (OR) for each HAP using the posterior mean, and a 95% credible interval (CI) using the 2.5(th) and 97.5(th) quantiles of the posterior samples. Based on previous assessments, any pollutant with a Bayes factor greater than 1 was selected for inclusion in a final model. Twenty-five HAPs were selected in the final analysis to represent "bins" of highly correlated HAPs (ρ > 0.80). We identified two out of 25 HAPs with a Bayes factor greater than 1: quinoline (ORhigh = 2.06, 95% CI: 1.11-3.87, Bayes factor = 1.01) and trichloroethylene (ORmedium = 2.00, 95% CI: 1.14-3.61, Bayes factor = 3.79). Overall there is evidence that quinoline and trichloroethylene may be significant contributors to the risk of spina bifida. Additionally, the use of Bayesian hierarchical models with SSVS is an alternative approach in the evaluation of multiple environmental pollutants on disease risk. This approach can be easily extended to environmental exposures, where novel approaches are needed in the context of multi-pollutant modeling.

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.

Development of a simple measurement scale to evaluate the severity of non-specific low back pain for industrial ergonomics.

PubMed

Higuchi, Yoshiyuki; Izumi, Hiroyuki; Kumashiro, Mashaharu

2010-06-01

This study developed an assessment scale that hierarchically classifies degrees of low back pain severity. This assessment scale consists of two subscales: 1) pain intensity; 2) pain interference. First, the assessment scale devised by the authors was used to administer a self-administered questionnaire to 773 male workers in the car manufacturing industry. Subsequently, the validity of the measurement items was examined and some of them were revised. Next, the corrected low back pain scale was used in a self-administered questionnaire, the subjects of which were 5053 ordinary workers. The hierarchical validity between the measurement items was checked based on the results of Mokken Scale analysis. Finally, a low back pain assessment scale consisting of seven items was perfected. Quantitative assessment is made possible by scoring the items and low back pain severity can be classified into four hierarchical levels: none; mild; moderate; severe. STATEMENT OF RELEVANCE: The use of this scale devised by the authors allows a more detailed assessment of the degree of risk factor effect and also should prove useful both in selecting remedial measures for occupational low back pain and evaluating their efficacy.

A hierarchical cluster analysis of normal-tension glaucoma using spectral-domain optical coherence tomography parameters.

PubMed

Bae, Hyoung Won; Ji, Yongwoo; Lee, Hye Sun; Lee, Naeun; Hong, Samin; Seong, Gong Je; Sung, Kyung Rim; Kim, Chan Yun

2015-01-01

Normal-tension glaucoma (NTG) is a heterogenous disease, and there is still controversy about subclassifications of this disorder. On the basis of spectral-domain optical coherence tomography (SD-OCT), we subdivided NTG with hierarchical cluster analysis using optic nerve head (ONH) parameters and retinal nerve fiber layer (RNFL) thicknesses. A total of 200 eyes of 200 NTG patients between March 2011 and June 2012 underwent SD-OCT scans to measure ONH parameters and RNFL thicknesses. We classified NTG into homogenous subgroups based on these variables using a hierarchical cluster analysis, and compared clusters to evaluate diverse NTG characteristics. Three clusters were found after hierarchical cluster analysis. Cluster 1 (62 eyes) had the thickest RNFL and widest rim area, and showed early glaucoma features. Cluster 2 (60 eyes) was characterized by the largest cup/disc ratio and cup volume, and showed advanced glaucomatous damage. Cluster 3 (78 eyes) had small disc areas in SD-OCT and were comprised of patients with significantly younger age, longer axial length, and greater myopia than the other 2 groups. A hierarchical cluster analysis of SD-OCT scans divided NTG patients into 3 groups based upon ONH parameters and RNFL thicknesses. It is anticipated that the small disc area group comprised of younger and more myopic patients may show unique features unlike the other 2 groups.

Assessing risk profiles for Salmonella serotypes in breeding pig operations in Portugal using a Bayesian hierarchical model.

PubMed

Correia-Gomes, Carla; Economou, Theodoros; Mendonça, Denisa; Vieira-Pinto, Madalena; Niza-Ribeiro, João

2012-11-21

The EU Regulation No 2160/2003 imposes a reduction in the prevalence of Salmonella in pigs. The efficiency of control programmes for Salmonella in pigs, reported among the EU Member States, varies and definitive eradication seems very difficult. Control measures currently recommended for Salmonella are not serotype-specific. Is it possible that the risk factors for different Salmonella serotypes are different? The aim of this study was to investigate potential risk factors for two groups of Salmonella sp serotypes using pen faecal samples from breeding pig holdings representative of the Portuguese pig sector. The data used come from the Baseline Survey for the Prevalence of Salmonella in breeding pigs in Portugal. A total of 1670 pen faecal samples from 167 herds were tested, and 170 samples were positive for Salmonella. The presence of Salmonella in each sample (outcome variable) was classified in three categories: i) no Salmonella, ii) Salmonella Typhimurium or S. Typhimurium-like strains with the antigenic formula: 1,4,5,12:i:-, , and iii) other serotypes. Along with the sample collection, a questionnaire concerning herd management and potential risk factors was utilised. The data have a "natural" hierarchical structure so a categorical multilevel analysis of the dataset was carried out using a Bayesian hierarchical model. The model was estimated using Markov Chain Monte Carlo methods, implemented in the software WinBUGS. The significant associations found (when compared to category "no Salmonella"), for category "serotype Typhimurium or S. Typhimurium-like strains with the antigenic formula: 1,4,5,12:i:-" were: age of breeding sows, size of the herd, number of pigs/pen and source of semen. For the category "other serotypes" the significant associations found were: control of rodents, region of the country, source of semen, breeding sector room and source of feed. The risk factors significantly associated with Salmonella shedding from the category "serotype Typhimurium or serotype 1,4,5,12:i:-" were more related to animal factors, whereas those associated with "other serotypes" were more related to environmental factors. Our findings suggest that different control measures could be used to control different Salmonella serotypes in breeding pigs.

Does history of childhood maltreatment make a difference in prison? A hierarchical approach on early family events and personality traits.

PubMed

Sergentanis, Theodoros N; Sakelliadis, Emmanouil I; Vlachodimitropoulos, Dimitrios; Goutas, Nikolaos; Sergentanis, Ioannis N; Spiliopoulou, Chara A; Papadodima, StavroulaA

2014-12-30

This study attempts to assess childhood maltreatment in prison through a hierarchical approach. The hierarchical approach principally aims to disentangle the independent effects of childhood maltreatment upon psychiatric morbidity/personality traits, if any, from the burden that the adverse family conditions have already imposed to the mental health of the maltreated individual-prisoner. To this direction, a conceptual framework with five hierarchical levels was constructed, namely: immutable demographic factors; family conditions; childhood maltreatment (physical abuse, neglect and sexual abuse); personality traits, habits and psychiatric morbidity; prison-related variables. A self-administered, anonymous set (battery) of questionnaires was administered to 173 male prisoners in the Chalkida prison, Greece; 26% of prisoners disclosed childhood maltreatment. Psychiatric condition in the family, parental alcoholism and parental divorce correlated with childhood maltreatment. After adjustment for immutable demographic factors and family conditions, childhood maltreatment was associated with aggression (both in terms of Lifetime History of Aggression and Buss–Perry Aggression Questionnaire scores), illicit substance use, personal history of psychiatric condition, current smoking, impulsivity and alcohol abuse. In conclusion, childhood maltreatment represents a pivotal, determining factor in the life course of male prisoners. Delinquents seem to suffer from long-term consequences of childhood maltreatment in terms of numerous mental health aspects.

Cognitive risk factors explain the relations between neuroticism and social anxiety for males and females.

PubMed

Allan, Nicholas P; Oglesby, Mary E; Uhl, Aubree; Schmidt, Norman B

2017-04-01

The hierarchical model of vulnerabilities to emotional distress contextualizes the relation between neuroticism and social anxiety as occurring indirectly through cognitive risk factors. In particular, inhibitory intolerance of uncertainty (IU; difficulty in uncertain circumstances), fear of negative evaluation (FNE; fear of being judged negatively), and anxiety sensitivity (AS) social concerns (fear of outwardly observable anxiety) are related to social anxiety. It is unclear whether these risk factors uniquely relate to social anxiety, and whether they account for the relations between neuroticism and social anxiety. The indirect relations between neuroticism and social anxiety through these and other risk factors were examined using structural equation modeling in a sample of 462 individuals (M age = 36.56, SD = 12.93; 64.3% female). Results indicated that the relations between neuroticism and social anxiety could be explained through inhibitory IU, FNE, and AS social concerns. No gender differences were found. These findings provide support for the hierarchical model of vulnerabilities to emotional distress disorders, although the cognitive risk factors accounted for variance beyond their contribution to the relation between neuroticism and social anxiety, suggesting a more complex model than that expressed in the hierarchical model of vulnerabilities.

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.

A Hierarchical Visualization Analysis Model of Power Big Data

NASA Astrophysics Data System (ADS)

Li, Yongjie; Wang, Zheng; Hao, Yang

2018-01-01

Based on the conception of integrating VR scene and power big data analysis, a hierarchical visualization analysis model of power big data is proposed, in which levels are designed, targeting at different abstract modules like transaction, engine, computation, control and store. The regularly departed modules of power data storing, data mining and analysis, data visualization are integrated into one platform by this model. It provides a visual analysis solution for the power big data.

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…

The Equivalence of Three Statistical Packages for Performing Hierarchical Cluster Analysis

ERIC Educational Resources Information Center

Blashfield, Roger

1977-01-01

Three different software programs which contain hierarchical agglomerative cluster analysis procedures were shown to generate different solutions on the same data set using apparently the same options. The basis for the differences in the solutions was the formulae used to calculate Euclidean distance. (Author/JKS)

The Intolerance of Uncertainty Inventory: Validity and Comparison of Scoring Methods to Assess Individuals Screening Positive for Anxiety and Depression.

PubMed

Lauriola, Marco; Mosca, Oriana; Trentini, Cristina; Foschi, Renato; Tambelli, Renata; Carleton, R Nicholas

2018-01-01

Intolerance of Uncertainty is a fundamental transdiagnostic personality construct hierarchically organized with a core general factor underlying diverse clinical manifestations. The current study evaluated the construct validity of the Intolerance of Uncertainty Inventory, a two-part scale separately assessing a unitary Intolerance of Uncertainty disposition to consider uncertainties to be unacceptable and threatening (Part A) and the consequences of such disposition, regarding experiential avoidance, chronic doubt, overestimation of threat, worrying, control of uncertain situations, and seeking reassurance (Part B). Community members ( N = 1046; Mean age = 36.69 ± 12.31 years; 61% females) completed the Intolerance of Uncertainty Inventory with the Beck Depression Inventory-II and the State-Trait Anxiety Inventory. Part A demonstrated a robust unidimensional structure and an excellent convergent validity with Part B. A bifactor model was the best fitting model for Part B. Based on these results, we compared the hierarchical factor scores with summated ratings clinical proxy groups reporting anxiety and depression symptoms. Summated rating scores were associated with both depression and anxiety and proportionally increased with the co-occurrence of depressive and anxious symptoms. By contrast, hierarchical scores were useful to detect which facets mostly separated between for depression and anxiety groups. In sum, Part A was a reliable and valid transdiagnostic measure of Intolerance of Uncertainty. The Part B was arguably more useful for assessing clinical manifestations of Intolerance of Uncertainty for specific disorders, provided that hierarchical scores are used. Overall, our study suggest that clinical assessments might need to shift toward hierarchical factor scores.

The Intolerance of Uncertainty Inventory: Validity and Comparison of Scoring Methods to Assess Individuals Screening Positive for Anxiety and Depression

PubMed Central

Lauriola, Marco; Mosca, Oriana; Trentini, Cristina; Foschi, Renato; Tambelli, Renata; Carleton, R. Nicholas

2018-01-01

Intolerance of Uncertainty is a fundamental transdiagnostic personality construct hierarchically organized with a core general factor underlying diverse clinical manifestations. The current study evaluated the construct validity of the Intolerance of Uncertainty Inventory, a two-part scale separately assessing a unitary Intolerance of Uncertainty disposition to consider uncertainties to be unacceptable and threatening (Part A) and the consequences of such disposition, regarding experiential avoidance, chronic doubt, overestimation of threat, worrying, control of uncertain situations, and seeking reassurance (Part B). Community members (N = 1046; Mean age = 36.69 ± 12.31 years; 61% females) completed the Intolerance of Uncertainty Inventory with the Beck Depression Inventory-II and the State-Trait Anxiety Inventory. Part A demonstrated a robust unidimensional structure and an excellent convergent validity with Part B. A bifactor model was the best fitting model for Part B. Based on these results, we compared the hierarchical factor scores with summated ratings clinical proxy groups reporting anxiety and depression symptoms. Summated rating scores were associated with both depression and anxiety and proportionally increased with the co-occurrence of depressive and anxious symptoms. By contrast, hierarchical scores were useful to detect which facets mostly separated between for depression and anxiety groups. In sum, Part A was a reliable and valid transdiagnostic measure of Intolerance of Uncertainty. The Part B was arguably more useful for assessing clinical manifestations of Intolerance of Uncertainty for specific disorders, provided that hierarchical scores are used. Overall, our study suggest that clinical assessments might need to shift toward hierarchical factor scores. PMID:29632505

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.

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

Instability of Hierarchical Cluster Analysis Due to Input Order of the Data: The PermuCLUSTER Solution

ERIC Educational Resources Information Center

van der Kloot, Willem A.; Spaans, Alexander M. J.; Heiser, Willem J.

2005-01-01

Hierarchical agglomerative cluster analysis (HACA) may yield different solutions under permutations of the input order of the data. This instability is caused by ties, either in the initial proximity matrix or arising during agglomeration. The authors recommend to repeat the analysis on a large number of random permutations of the rows and columns…

Factors associated with preventable infant death: a multiple logistic regression

PubMed Central

Vidal e Silva, Sandra Maria Cunha; Tuon, Rogério Antonio; Probst, Livia Fernandes; Gondinho, Brunna Verna Castro; Pereira, Antonio Carlos; Meneghim, Marcelo de Castro; Cortellazzi, Karine Laura; Ambrosano, Glaucia Maria Bovi

2018-01-01

ABSTRACT OBJECTIVE To identify and analyze factors associated with preventable child deaths. METHODS This analytical cross-sectional study had preventable child mortality as dependent variable. From a population of 34,284 live births, we have selected a systematic sample of 4,402 children who did not die compared to 272 children who died from preventable causes during the period studied. The independent variables were analyzed in four hierarchical blocks: sociodemographic factors, the characteristics of the mother, prenatal and delivery care, and health conditions of the patient and neonatal care. We performed a descriptive statistical analysis and estimated multiple hierarchical logistic regression models. RESULTS Approximatelly 35.3% of the deaths could have been prevented with the early diagnosis and treatment of diseases during pregnancy and 26.8% of them could have been prevented with better care conditions for pregnant women. CONCLUSIONS The following characteristics of the mother are determinant for the higher mortality of children before the first year of life: living in neighborhoods with an average family income lower than four minimum wages, being aged ≤ 19 years, having one or more alive children, having a child with low APGAR level at the fifth minute of life, and having a child with low birth weight. PMID:29723389

Investigating a multigene prognostic assay based on significant pathways for Luminal A breast cancer through gene expression profile analysis.

PubMed

Gao, Haiyan; Yang, Mei; Zhang, Xiaolan

2018-04-01

The present study aimed to investigate potential recurrence-risk biomarkers based on significant pathways for Luminal A breast cancer through gene expression profile analysis. Initially, the gene expression profiles of Luminal A breast cancer patients were downloaded from The Cancer Genome Atlas database. The differentially expressed genes (DEGs) were identified using a Limma package and the hierarchical clustering analysis was conducted for the DEGs. In addition, the functional pathways were screened using Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and rank ratio calculation. The multigene prognostic assay was exploited based on the statistically significant pathways and its prognostic function was tested using train set and verified using the gene expression data and survival data of Luminal A breast cancer patients downloaded from the Gene Expression Omnibus. A total of 300 DEGs were identified between good and poor outcome groups, including 176 upregulated genes and 124 downregulated genes. The DEGs may be used to effectively distinguish Luminal A samples with different prognoses verified by hierarchical clustering analysis. There were 9 pathways screened as significant pathways and a total of 18 DEGs involved in these 9 pathways were identified as prognostic biomarkers. According to the survival analysis and receiver operating characteristic curve, the obtained 18-gene prognostic assay exhibited good prognostic function with high sensitivity and specificity to both the train and test samples. In conclusion the 18-gene prognostic assay including the key genes, transcription factor 7-like 2, anterior parietal cortex and lymphocyte enhancer factor-1 may provide a new method for predicting outcomes and may be conducive to the promotion of precision medicine for Luminal A breast cancer.

Filicide-suicide ideation among Taiwanese parents with school-aged children: prevalence and associated factors.

PubMed

Wei, Hsi-Sheng; Chen, Ji-Kang

2014-03-01

This study explored the prevalence of filicide-suicide ideation among Taiwanese parents with school-aged children. Multiple risk factors associated with filicide-suicide ideation were assessed, and the potential effect of traditional family values was evaluated. A random sample of 1,564 parents was recruited from 21 elementary schools in a rural area of Taiwan. Potential risk factors, including demographics, family finance, psychological maladjustment, family interaction, and cultural beliefs, were further examined using a hierarchical logistic regression. Overall, 14.6% of the respondents reported having filicide-suicide ideation during the past year. The hierarchical logistic regression analysis showed that demographic factors including age, gender, and ethnicity had no significant effect. Family finances, depression, and conflict with the respondent's spouse were positively associated with filicide-suicide ideation. Finally, the parents' beliefs in traditional family values had a positive effect on filicide-suicide ideation. In other words, filicide-suicide thoughts were more common among those who upheld a strong parental responsibility for care giving and family solidarity. This study revealed a substantial prevalence of filicide-suicide ideation among local parents and identified a number of risk factors associated with those thoughts, namely family financial status, parental depression, and conflict with one's spouse. More importantly, the results highlighted the effect of traditional family values in the process. The potential intention of filicide-suicide as mercy killing and its cultural relevance were discussed. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

Wang, Yong; State Key Laboratory of Multiphase Complex System, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100080; Zhu, Qingshan, E-mail: qszhu@home.ipe.ac.cn

{beta}-Ni(OH){sub 2} hierarchical micro-flowers, hierarchical hollow microspheres and nanosheets were synthesized via a facile, single-step and selected-control hydrothermal method. Both hierarchical micro-flowers and hierarchical hollow microspheres were built from two-dimensional nanosheets with thickness of 50-100 nm. The as-obtained products were characterized by Brunauer-Emmett-Teller (BET) surface area analysis, X-ray powder diffraction (XRD) and field emission scanning electron microscopy (FESEM). It was observed that marked morphological changes in {beta}-Ni(OH){sub 2} depended on the initial concentrations of Ni{sup 2+} ions and glycine. A possible growth mechanism was proposed based on experimental results. In addition, the effect of morphology on the electrochemical properties wasmore » also investigated. Both hierarchical micro-flowers and hierarchical hollow microspheres exhibited enhanced specific capacity and high-rate discharge ability as compared with pure Ni(OH){sub 2} nanosheets. Investigations confirmed that hierarchical structures had a pronounced influence upon the electrochemical performance of nickel hydroxide.« less

Modeling methodology for supply chain synthesis and disruption analysis

NASA Astrophysics Data System (ADS)

Wu, Teresa; Blackhurst, Jennifer

2004-11-01

The concept of an integrated or synthesized supply chain is a strategy for managing today's globalized and customer driven supply chains in order to better meet customer demands. Synthesizing individual entities into an integrated supply chain can be a challenging task due to a variety of factors including conflicting objectives, mismatched incentives and constraints of the individual entities. Furthermore, understanding the effects of disruptions occurring at any point in the system is difficult when working toward synthesizing supply chain operations. Therefore, the goal of this research is to present a modeling methodology to manage the synthesis of a supply chain by linking hierarchical levels of the system and to model and analyze disruptions in the integrated supply chain. The contribution of this research is threefold: (1) supply chain systems can be modeled hierarchically (2) the performance of synthesized supply chain system can be evaluated quantitatively (3) reachability analysis is used to evaluate the system performance and verify whether a specific state is reachable, allowing the user to understand the extent of effects of a disruption.

Assessing and monitoring urban resilience using COPD in Porto.

PubMed

Monteiro, Ana; Carvalho, Vânia; Velho, Sara; Sousa, Carlos

2012-01-01

COPD morbidity is a good example of how the urban form may interfere with a disease's severity. Then, it may play an important role as a stimulus to increase the acceptability of several policy actions that aim to upgrade urban resilience. Despite the multiple dimensions of wellbeing, health is surely a key variable attracting everyone's attention, which is thus more likely to be able to persuade people that actions that may at first seem undesirable are fundamental in improving urban sustainability and well-being. After creating a short list of socio-economic and environmental factors relating to the onset and aggravation of COPD, daily admissions distributions were compared using both a non-weighted and a weighted multi-criteria hierarchical analysis procedure. Porto's COPD Social and Environmental Inequalities Index (SEII), calculated with a hierarchical analysis procedure, accurately illustrates a great relationship between COPD admissions and adverse urban form variables. COPD may be an important communication tool to stimulate the acceptability of some otherwise unpopular planning measures to improve urban resilience (sustainability and well-being). Copyright © 2011 Elsevier B.V. All rights reserved.

[Tooth decay and associated factors among adolescents in the north of the State of Minas Gerais, Brazil: a hierarchical analysis].

PubMed

Silveira, Marise Fagundes; Freire, Rafael Silveira; Nepomuceno, Marcela Oliveira; Martins, Andréa Maria Eleutério de Barros Lima; Marcopito, Luiz Francisco

2015-11-01

This is a cross-sectional population-based study (n = 763) conducted in the north of the State of Minas Gerais, which aimed to investigate the prevalence of tooth decay among adolescents and to identify the potential determinants of same. Probability sampling by conglomerates in multiple stages was used. Trained and calibrated professionals performed the data collection by means of intraoral examination and interviews in the previously selected households. In the analysis of the determinant factor for the presence of tooth decay, hierarchical binary logistic regression models were used. The prevalence of tooth decay, decayed, missing and filled teeth were 71.3%, 36.5%, 55.6% and 16%, respectively. The following averages were observed: DMFT (3.4 teeth), number of decayed (0.8 teeth), restored (2.4 teeth) and missing (0.2 teeth). The incidence of tooth decay was higher among adolescents who stated they were black/indigenous/brown (OR = 1.76), lived in crowded households (OR = 2.4), did not regularly visit or had never been to a dentist (OR = 1.9), used public or philanthropic services (OR = 1,8), had smoking habits (OR = 4.1), consumed alcohol (OR = 1.8), perceived their oral health negatively (OR = 5.9 and OR = 1.9) and had toothac in the last six months (OR = 2.0).

Settlement-Size Scaling among Prehistoric Hunter-Gatherer Settlement Systems in the New World

PubMed Central

Haas, W. Randall; Klink, Cynthia J.; Maggard, Greg J.; Aldenderfer, Mark S.

2015-01-01

Settlement size predicts extreme variation in the rates and magnitudes of many social and ecological processes in human societies. Yet, the factors that drive human settlement-size variation remain poorly understood. Size variation among economically integrated settlements tends to be heavy tailed such that the smallest settlements are extremely common and the largest settlements extremely large and rare. The upper tail of this size distribution is often formalized mathematically as a power-law function. Explanations for this scaling structure in human settlement systems tend to emphasize complex socioeconomic processes including agriculture, manufacturing, and warfare—behaviors that tend to differentially nucleate and disperse populations hierarchically among settlements. But, the degree to which heavy-tailed settlement-size variation requires such complex behaviors remains unclear. By examining the settlement patterns of eight prehistoric New World hunter-gatherer settlement systems spanning three distinct environmental contexts, this analysis explores the degree to which heavy-tailed settlement-size scaling depends on the aforementioned socioeconomic complexities. Surprisingly, the analysis finds that power-law models offer plausible and parsimonious statistical descriptions of prehistoric hunter-gatherer settlement-size variation. This finding reveals that incipient forms of hierarchical settlement structure may have preceded socioeconomic complexity in human societies and points to a need for additional research to explicate how mobile foragers came to exhibit settlement patterns that are more commonly associated with hierarchical organization. We propose that hunter-gatherer mobility with preferential attachment to previously occupied locations may account for the observed structure in site-size variation. PMID:26536241

Quantifying the Strength of General Factors in Psychopathology: A Comparison of CFA with Maximum Likelihood Estimation, BSEM, and ESEM/EFA Bifactor Approaches.

PubMed

Murray, Aja Louise; Booth, Tom; Eisner, Manuel; Obsuth, Ingrid; Ribeaud, Denis

2018-05-22

Whether or not importance should be placed on an all-encompassing general factor of psychopathology (or p factor) in classifying, researching, diagnosing, and treating psychiatric disorders depends (among other issues) on the extent to which comorbidity is symptom-general rather than staying largely within the confines of narrower transdiagnostic factors such as internalizing and externalizing. In this study, we compared three methods of estimating p factor strength. We compared omega hierarchical and explained common variance calculated from confirmatory factor analysis (CFA) bifactor models with maximum likelihood (ML) estimation, from exploratory structural equation modeling/exploratory factor analysis models with a bifactor rotation, and from Bayesian structural equation modeling (BSEM) bifactor models. Our simulation results suggested that BSEM with small variance priors on secondary loadings might be the preferred option. However, CFA with ML also performed well provided secondary loadings were modeled. We provide two empirical examples of applying the three methodologies using a normative sample of youth (z-proso, n = 1,286) and a university counseling sample (n = 359).

Managerial and environmental factors in the continuity of mental health care across institutions.

PubMed

Greenberg, Greg A; Rosenheck, Robert A

2003-04-01

The authors examined the association of continuity of care with factors assumed to be under the control of health care administrators and environmental factors not under managerial control. The authors used a facility-level administrative data set for 139 Department of Veterans Affairs medical centers over a six-year period and supplemental data on environmental factors to conduct two types of analysis. First, simple correlations were used to examine bivariate associations between eight continuity-of-care measures and nine measures of the institutional environment and the social context. Second, to control for potential autocorrelation, multivariate hierarchical linear models with all nine independent measures were created. The strongest predictors of continuity of care were per capita outpatient expenditure and the degree of emphasis on outpatient care as measured by the percentage of all mental health expenditures devoted to outpatient care. The former was significantly associated with greater continuity of care on six of eight measures and the latter on seven of eight measures. The environmental factor of social capital (the degree of civic involvement and trust at the state level) was associated with greater continuity of care on five measures. The degree to which non-VA mental health services were funded in a state was unexpectedly found to be positively associated with greater continuity of care. In multivariate analysis using hierarchical linear modeling, significant relationships with continuity of care remained for per capita outpatient expenditures, overall outpatient emphasis, and social capital, but not for non-VA mental health funding. A linear term representing the year was positively and significantly associated with six of the eight examined continuity-of-care measures, indicating improvement in continuity of care for the period under study, although the explanation for this trend over time is unclear. Several factors potentially under managerial control are associated with increased mental health continuity of care.

A Hierarchical Modeling Approach to Data Analysis and Study Design in a Multi-Site Experimental fMRI Study

ERIC Educational Resources Information Center

Zhou, Bo; Konstorum, Anna; Duong, Thao; Tieu, Kinh H.; Wells, William M.; Brown, Gregory G.; Stern, Hal S.; Shahbaba, Babak

2013-01-01

We propose a hierarchical Bayesian model for analyzing multi-site experimental fMRI studies. Our method takes the hierarchical structure of the data (subjects are nested within sites, and there are multiple observations per subject) into account and allows for modeling between-site variation. Using posterior predictive model checking and model…

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,…

Correlates of Social Support Among Latino Immigrants.

PubMed

Held, Mary L

2018-04-01

Latino immigrants encounter considerable stressors that pose risks to health and well-being during settlement in the USA. Social support serves as a protective factor that can help to buffer the negative effects of stress. Despite the importance of social support, we know little about how Latino immigrants differentially experience this protective factor. The current study analyzed data from 100 Latino immigrants residing in Tennessee. Hierarchical multiple regression analysis was employed to examine variation in self-reported social support by immigrant characteristics and immigration-related factors. Females, immigrants who are not married/cohabitating, and those who reported experiencing a greater number of discrete stressors in the USA each reported lower levels of social support. Implications for practice include an increased emphasis on assessing levels of social support and designing services to strengthen support for the most vulnerable immigrants. Future research should consider a longitudinal analysis and specific types of social support.

Modeling Choice Under Uncertainty in Military Systems Analysis

DTIC Science & Technology

1991-11-01

operators rather than fuzzy operators. This is suggested for further research. 4.3 ANALYTIC HIERARCHICAL PROCESS ( AHP ) In AHP , objectives, functions and...14 4.1 IMPRECISELY SPECIFIED MULTIPLE A’ITRIBUTE UTILITY THEORY... 14 4.2 FUZZY DECISION ANALYSIS...14 4.3 ANALYTIC HIERARCHICAL PROCESS ( AHP ) ................................... 14 4.4 SUBJECTIVE TRANSFER FUNCTION APPROACH

"Sentido de Pertenencia": A Hierarchical Analysis Predicting Sense of Belonging among Latino College Students

ERIC Educational Resources Information Center

Strayhorn, Terrell Lamont

2008-01-01

The present study estimated the influence of academic and social collegiate experiences on Latino students' sense of belonging, controlling for background differences, using hierarchical analysis techniques with a nested design. In addition, results were compared between Latino students and their White counterparts. Findings reveal that grades,…

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…

Groundwater flow and hydrogeochemical evolution in the Jianghan Plain, central China

NASA Astrophysics Data System (ADS)

Gan, Yiqun; Zhao, Ke; Deng, Yamin; Liang, Xing; Ma, Teng; Wang, Yanxin

2018-05-01

Hydrogeochemical analysis and multivariate statistics were applied to identify flow patterns and major processes controlling the hydrogeochemistry of groundwater in the Jianghan Plain, which is located in central Yangtze River Basin (central China) and characterized by intensive surface-water/groundwater interaction. Although HCO3-Ca-(Mg) type water predominated in the study area, the 457 (21 surface water and 436 groundwater) samples were effectively classified into five clusters by hierarchical cluster analysis. The hydrochemical variations among these clusters were governed by three factors from factor analysis. Major components (e.g., Ca, Mg and HCO3) in surface water and groundwater originated from carbonate and silicate weathering (factor 1). Redox conditions (factor 2) influenced the geogenic Fe and As contamination in shallow confined groundwater. Anthropogenic activities (factor 3) primarily caused high levels of Cl and SO4 in surface water and phreatic groundwater. Furthermore, the factor score 1 of samples in the shallow confined aquifer gradually increased along the flow paths. This study demonstrates that enhanced information on hydrochemistry in complex groundwater flow systems, by multivariate statistical methods, improves the understanding of groundwater flow and hydrogeochemical evolution due to natural and anthropogenic impacts.

Underage drinking: prevalence and risk factors associated with drinking experiences among Argentinean children.

PubMed

Pilatti, Angelina; Godoy, Juan Carlos; Brussino, Silvina; Pautassi, Ricardo Marcos

2013-06-01

The aim of this study was to describe the prevalence and predictors of alcohol drinking behavior in children. Data were obtained from 367 children, aged 8-12 years (M = 10.44 years, SD = 1.21 years; 61.9% female) from the city of Córdoba, Argentina. Several scales were used to assess risk factors, including personality traits, alcohol expectancy (i.e., beliefs about the consequences of using alcohol), and perceived peer alcohol use, for alcohol drinking and alcohol drinking experiences. Hierarchical regression analysis was used to determine the contribution of multiple risk factors to the quantity of alcohol consumed. The results showed that 58% of the children had tasted alcohol, and approximately one-third drank alcohol again after the first drinking experience. Twelve-year-old children had a significantly higher prevalence of tasting and drinking alcohol and a significantly greater frequency and quantity of alcohol consumed than younger children. Eighty percent of the children who liked alcohol during their first drinking experience reported that they drank alcohol again. Among the children who did not like alcohol during their first drinking experience, only 31% drank alcohol again. Underage drinking usually occurred under adult supervision in family settings when parents or other relatives allowed them to drink or were aware of their children's drinking. The hierarchical regression analysis showed that being older and male, having more peers that drink alcohol, having higher levels of extroversion, and having alcohol expectancy for social facilitation increased the risk for greater alcohol use. The final model explained 33% of the total variance. Copyright © 2013 Elsevier Inc. All rights reserved.

Perceived cognitive impairment in Chinese patients with breast cancer and its relationship with post-traumatic stress disorder symptoms and fatigue.

PubMed

Li, Jie; Yu, Lixiang; Long, Zhouting; Li, Yang; Cao, Fenglin

2015-06-01

Clinical reports have shown that adjuvant chemotherapy has a negative impact on perceived cognitive impairment (PCI) of patients with breast cancer; however, evidence concerning the effects of psychological factors such as post-traumatic stress disorder (PTSD) symptoms on PCI is limited, especially in relation to Chinese patients with breast cancer. This research investigated the associations between psychological factors and PCI in Chinese women with breast cancer. In total, 204 women with breast cancer were assessed for PCI, PTSD symptoms, fatigue, anxiety, and depression using self-report measures. Hierarchical linear regression was conducted to investigate the associations between the variables of interest and PCI. Two hundred and two women were included in the final analysis; two of those originally tested were excluded because of missing data. A univariate analysis showed that PCI was significantly related to education, PTSD symptoms (re-experience, avoidance, and hyperarousal), fatigue, depression, anxiety, and undergoing chemotherapy or radiotherapy. Hierarchical linear regression revealed that PTSD symptoms and fatigue (ΔR(2)  = 0.26, P < 0.001) independently accounted for PCI in Chinese women with breast cancer regardless of age, education level, chemotherapy and radiotherapy. Hyperarousal was the only contributing PTSD symptom to PCI (B = -1.24, SE = 0.33, β = -0.39, P < 0.001). Besides chemotherapy, PTSD symptoms, especially hyperarousal, and fatigue are important risk factors for significant PCI and are therefore worthy of further investigation. Copyright © 2014 John Wiley & Sons, Ltd.

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.

Evaluation of B2C website based on the usability factors by using fuzzy AHP & hierarchical fuzzy TOPSIS

NASA Astrophysics Data System (ADS)

Masudin, I.; Saputro, T. E.

2016-02-01

In today's technology, electronic trading transaction via internet has been utilized properly with rapid growth. This paper intends to evaluate related to B2C e-commerce website in order to find out the one which meets the usability factors better than another. The influential factors to B2C e-commerce website are determined for two big retailer websites. The factors are investigated based on the consideration of several studies and conformed to the website characteristics. The evaluation is conducted by using different methods namely fuzzy AHP and hierarchical fuzzy TOPSIS so that the final evaluation can be compared. Fuzzy triangular number is adopted to deal with imprecise judgment under fuzzy environment.

Buckling Load Calculations of the Isotropic Shell A-8 Using a High-Fidelity Hierarchical Approach

NASA Technical Reports Server (NTRS)

Arbocz, Johann; Starnes, James H.

2002-01-01

As a step towards developing a new design philosophy, one that moves away from the traditional empirical approach used today in design towards a science-based design technology approach, a test series of 7 isotropic shells carried out by Aristocrat and Babcock at Caltech is used. It is shown how the hierarchical approach to buckling load calculations proposed by Arbocz et al can be used to perform an approach often called 'high fidelity analysis', where the uncertainties involved in a design are simulated by refined and accurate numerical methods. The Delft Interactive Shell DEsign COde (short, DISDECO) is employed for this hierarchical analysis to provide an accurate prediction of the critical buckling load of the given shell structure. This value is used later as a reference to establish the accuracy of the Level-3 buckling load predictions. As a final step in the hierarchical analysis approach, the critical buckling load and the estimated imperfection sensitivity of the shell are verified by conducting an analysis using a sufficiently refined finite element model with one of the current generation two-dimensional shell analysis codes with the advanced capabilities needed to represent both geometric and material nonlinearities.

On a High-Fidelity Hierarchical Approach to Buckling Load Calculations

NASA Technical Reports Server (NTRS)

Arbocz, Johann; Starnes, James H.; Nemeth, Michael P.

2001-01-01

As a step towards developing a new design philosophy, one that moves away from the traditional empirical approach used today in design towards a science-based design technology approach, a recent test series of 5 composite shells carried out by Waters at NASA Langley Research Center is used. It is shown how the hierarchical approach to buckling load calculations proposed by Arbocz et al can be used to perform an approach often called "high fidelity analysis", where the uncertainties involved in a design are simulated by refined and accurate numerical methods. The Delft Interactive Shell DEsign COde (short, DISDECO) is employed for this hierarchical analysis to provide an accurate prediction of the critical buckling load of the given shell structure. This value is used later as a reference to establish the accuracy of the Level-3 buckling load predictions. As a final step in the hierarchical analysis approach, the critical buckling load and the estimated imperfection sensitivity of the shell are verified by conducting an analysis using a sufficiently refined finite element model with one of the current generation two-dimensional shell analysis codes with the advanced capabilities needed to represent both geometric and material nonlinearities.

Fabrication of micro/nano hierarchical structures with analysis on the surface mechanics

NASA Astrophysics Data System (ADS)

Jheng, Yu-Sheng; Lee, Yeeu-Chang

2016-10-01

Biomimicry refers to the imitation of mechanisms and features found in living creatures using artificial methods. This study used optical lithography, colloidal lithography, and dry etching to mimic the micro/nano hierarchical structures covering the soles of gecko feet. We measured the static contact angle and contact angle hysteresis to reveal the behavior of liquid drops on the hierarchical structures. Pulling tests were also performed to measure the resistance of movement between the hierarchical structures and a testing plate. Our results reveal that hierarchical structures at the micro-/nano-scale are considerably hydrophobic, they provide good flow characteristics, and they generate more contact force than do surfaces with micro-scale cylindrical structures.

A hierarchical approach to forest landscape pattern characterization.

PubMed

Wang, Jialing; Yang, Xiaojun

2012-01-01

Landscape spatial patterns have increasingly been considered to be essential for environmental planning and resources management. In this study, we proposed a hierarchical approach for landscape classification and evaluation by characterizing landscape spatial patterns across different hierarchical levels. The case study site is the Red Hills region of northern Florida and southwestern Georgia, well known for its biodiversity, historic resources, and scenic beauty. We used one Landsat Enhanced Thematic Mapper image to extract land-use/-cover information. Then, we employed principal-component analysis to help identify key class-level landscape metrics for forests at different hierarchical levels, namely, open pine, upland pine, and forest as a whole. We found that the key class-level landscape metrics varied across different hierarchical levels. Compared with forest as a whole, open pine forest is much more fragmented. The landscape metric, such as CONTIG_MN, which measures whether pine patches are contiguous or not, is more important to characterize the spatial pattern of pine forest than to forest as a whole. This suggests that different metric sets should be used to characterize landscape patterns at different hierarchical levels. We further used these key metrics, along with the total class area, to classify and evaluate subwatersheds through cluster analysis. This study demonstrates a promising approach that can be used to integrate spatial patterns and processes for hierarchical forest landscape planning and management.

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.

Australian Validation of the Hierarchical Personality Inventory for Children (HiPIC)

ERIC Educational Resources Information Center

Hopkinson, Laura; Watt, Dianne; Roodenburg, John

2014-01-01

The Hierarchical Personality Inventory for Children (HiPIC) is a developmentally appropriate parent-report measure of the Five Factor Model (FFM) that has been validated in several European languages but only recently in English. The English translation of the HiPIC was evaluated in an Australian context. Parent-rated HiPIC scores were obtained…

Physical Self-Concept in Adolescence: Generalizability of a Multidimensional, Hierarchical Model Across Gender and Grade

ERIC Educational Resources Information Center

Hagger, Martin S.; Biddle, Stuart J. H.; John Wang, C. K.

2005-01-01

This study tests the generalizability of the factor pattern, structural parameters, and latent mean structure of a multidimensional, hierarchical model of physical self-concept in adolescents across gender and grade. A children's version of the Physical Self-Perception Profile (C-PSPP) was administered to seventh-, eighth- and ninth-grade high…

Hierarchical storage management system evaluation

NASA Technical Reports Server (NTRS)

Woodrow, Thomas S.

1993-01-01

The Numerical Aerodynamic Simulation (NAS) Program at NASA Ames Research Center has been developing a hierarchical storage management system, NAStore, for some 6 years. This evaluation compares functionality, performance, reliability, and other factors of NAStore and three commercial alternatives. FileServ is found to be slightly better overall than NAStore and DMF. UniTree is found to be severely lacking in comparison.

A hierarchical approach employing metabolic and gene expression profiles to identify the pathways that confer cytotoxicity in HepG2 cells

PubMed Central

Li, Zheng; Srivastava, Shireesh; Yang, Xuerui; Mittal, Sheenu; Norton, Paul; Resau, James; Haab, Brian; Chan, Christina

2007-01-01

Background Free fatty acids (FFA) and tumor necrosis factor alpha (TNF-α) have been implicated in the pathogenesis of many obesity-related metabolic disorders. When human hepatoblastoma cells (HepG2) were exposed to different types of FFA and TNF-α, saturated fatty acid was found to be cytotoxic and its toxicity was exacerbated by TNF-α. In order to identify the processes associated with the toxicity of saturated FFA and TNF-α, the metabolic and gene expression profiles were measured to characterize the cellular states. A computational model was developed to integrate these disparate data to reveal the underlying pathways and mechanisms involved in saturated fatty acid toxicity. Results A hierarchical framework consisting of three stages was developed to identify the processes and genes that regulate the toxicity. First, discriminant analysis identified that fatty acid oxidation and intracellular triglyceride accumulation were the most relevant in differentiating the cytotoxic phenotype. Second, gene set enrichment analysis (GSEA) was applied to the cDNA microarray data to identify the transcriptionally altered pathways and processes. Finally, the genes and gene sets that regulate the metabolic responses identified in step 1 were identified by integrating the expression of the enriched gene sets and the metabolic profiles with a multi-block partial least squares (MBPLS) regression model. Conclusion The hierarchical approach suggested potential mechanisms involved in mediating the cytotoxic and cytoprotective pathways, as well as identified novel targets, such as NADH dehydrogenases, aldehyde dehydrogenases 1A1 (ALDH1A1) and endothelial membrane protein 3 (EMP3) as modulator of the toxic phenotypes. These predictions, as well as, some specific targets that were suggested by the analysis were experimentally validated. PMID:17498300

Marker-Based Hierarchical Segmentation and Classification Approach for Hyperspectral Imagery

NASA Technical Reports Server (NTRS)

Tarabalka, Yuliya; Tilton, James C.; Benediktsson, Jon Atli; Chanussot, Jocelyn

2011-01-01

The Hierarchical SEGmentation (HSEG) algorithm, which is a combination of hierarchical step-wise optimization and spectral clustering, has given good performances for hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically selected markers for this purpose. In this paper, a novel Marker-based HSEG (M-HSEG) method for spectral-spatial classification of hyperspectral images is proposed. First, pixelwise classification is performed and the most reliably classified pixels are selected as markers, with the corresponding class labels. Then, a novel constrained marker-based HSEG algorithm is applied, resulting in a spectral-spatial classification map. The experimental results show that the proposed approach yields accurate segmentation and classification maps, and thus is attractive for hyperspectral image analysis.

Factors that influence the efficiency of beef and dairy cattle recording system in Kenya: A SWOT-AHP analysis.

PubMed

Wasike, Chrilukovian B; Magothe, Thomas M; Kahi, Alexander K; Peters, Kurt J

2011-01-01

Animal recording in Kenya is characterised by erratic producer participation and high drop-out rates from the national recording scheme. This study evaluates factors influencing efficiency of beef and dairy cattle recording system. Factors influencing efficiency of animal identification and registration, pedigree and performance recording, and genetic evaluation and information utilisation were generated using qualitative and participatory methods. Pairwise comparison of factors was done by strengths, weaknesses, opportunities and threats-analytical hierarchical process analysis and priority scores to determine their relative importance to the system calculated using Eigenvalue method. For identification and registration, and evaluation and information utilisation, external factors had high priority scores. For pedigree and performance recording, threats and weaknesses had the highest priority scores. Strengths factors could not sustain the required efficiency of the system. Weaknesses of the system predisposed it to threats. Available opportunities could be explored as interventions to restore efficiency in the system. Defensive strategies such as reorienting the system to offer utility benefits to recording, forming symbiotic and binding collaboration between recording organisations and NARS, and development of institutions to support recording were feasible.

Hierarchical recruitment of ribosomal proteins and assembly factors remodels nucleolar pre-60S ribosomes.

PubMed

Biedka, Stephanie; Micic, Jelena; Wilson, Daniel; Brown, Hailey; Diorio-Toth, Luke; Woolford, John L

2018-04-24

Ribosome biogenesis involves numerous preribosomal RNA (pre-rRNA) processing events to remove internal and external transcribed spacer sequences, ultimately yielding three mature rRNAs. Removal of the internal transcribed spacer 2 spacer RNA is the final step in large subunit pre-rRNA processing and begins with endonucleolytic cleavage at the C 2 site of 27SB pre-rRNA. C 2 cleavage requires the hierarchical recruitment of 11 ribosomal proteins and 14 ribosome assembly factors. However, the function of these proteins in C 2 cleavage remained unclear. In this study, we have performed a detailed analysis of the effects of depleting proteins required for C 2 cleavage and interpreted these results using cryo-electron microscopy structures of assembling 60S subunits. This work revealed that these proteins are required for remodeling of several neighborhoods, including two major functional centers of the 60S subunit, suggesting that these remodeling events form a checkpoint leading to C 2 cleavage. Interestingly, when C 2 cleavage is directly blocked by depleting or inactivating the C 2 endonuclease, assembly progresses through all other subsequent steps. © 2018 Biedka et al.

Hierarchical Bayesian Spatio–Temporal Analysis of Climatic and Socio–Economic Determinants of Rocky Mountain Spotted Fever

PubMed Central

Raghavan, Ram K.; Goodin, Douglas G.; Neises, Daniel; Anderson, Gary A.; Ganta, Roman R.

2016-01-01

This study aims to examine the spatio-temporal dynamics of Rocky Mountain spotted fever (RMSF) prevalence in four contiguous states of Midwestern United States, and to determine the impact of environmental and socio–economic factors associated with this disease. Bayesian hierarchical models were used to quantify space and time only trends and spatio–temporal interaction effect in the case reports submitted to the state health departments in the region. Various socio–economic, environmental and climatic covariates screened a priori in a bivariate procedure were added to a main–effects Bayesian model in progressive steps to evaluate important drivers of RMSF space-time patterns in the region. Our results show a steady increase in RMSF incidence over the study period to newer geographic areas, and the posterior probabilities of county-specific trends indicate clustering of high risk counties in the central and southern parts of the study region. At the spatial scale of a county, the prevalence levels of RMSF is influenced by poverty status, average relative humidity, and average land surface temperature (>35°C) in the region, and the relevance of these factors in the context of climate–change impacts on tick–borne diseases are discussed. PMID:26942604

Hierarchical Bayesian Spatio-Temporal Analysis of Climatic and Socio-Economic Determinants of Rocky Mountain Spotted Fever.

PubMed

Raghavan, Ram K; Goodin, Douglas G; Neises, Daniel; Anderson, Gary A; Ganta, Roman R

2016-01-01

This study aims to examine the spatio-temporal dynamics of Rocky Mountain spotted fever (RMSF) prevalence in four contiguous states of Midwestern United States, and to determine the impact of environmental and socio-economic factors associated with this disease. Bayesian hierarchical models were used to quantify space and time only trends and spatio-temporal interaction effect in the case reports submitted to the state health departments in the region. Various socio-economic, environmental and climatic covariates screened a priori in a bivariate procedure were added to a main-effects Bayesian model in progressive steps to evaluate important drivers of RMSF space-time patterns in the region. Our results show a steady increase in RMSF incidence over the study period to newer geographic areas, and the posterior probabilities of county-specific trends indicate clustering of high risk counties in the central and southern parts of the study region. At the spatial scale of a county, the prevalence levels of RMSF is influenced by poverty status, average relative humidity, and average land surface temperature (>35°C) in the region, and the relevance of these factors in the context of climate-change impacts on tick-borne diseases are discussed.

Models for Rational Decision Making. Analysis of Literature and Selected Bibliography. Analysis and Bibliography Series, No. 6.

ERIC Educational Resources Information Center

Hall, John S.

This review analyzes the trend in educational decision making to replace hierarchical authority structures with more rational models for decision making drawn from management science. Emphasis is also placed on alternatives to a hierarchical decision-making model, including governing models, union models, and influence models. A 54-item…

Meshfree truncated hierarchical refinement for isogeometric analysis

NASA Astrophysics Data System (ADS)

Atri, H. R.; Shojaee, S.

2018-05-01

In this paper truncated hierarchical B-spline (THB-spline) is coupled with reproducing kernel particle method (RKPM) to blend advantages of the isogeometric analysis and meshfree methods. Since under certain conditions, the isogeometric B-spline and NURBS basis functions are exactly represented by reproducing kernel meshfree shape functions, recursive process of producing isogeometric bases can be omitted. More importantly, a seamless link between meshfree methods and isogeometric analysis can be easily defined which provide an authentic meshfree approach to refine the model locally in isogeometric analysis. This procedure can be accomplished using truncated hierarchical B-splines to construct new bases and adaptively refine them. It is also shown that the THB-RKPM method can provide efficient approximation schemes for numerical simulations and represent a promising performance in adaptive refinement of partial differential equations via isogeometric analysis. The proposed approach for adaptive locally refinement is presented in detail and its effectiveness is investigated through well-known benchmark examples.

Hierarchical structures consisting of SiO2 nanorods and p-GaN microdomes for efficiently harvesting solar energy for InGaN quantum well photovoltaic cells.

PubMed

Ho, Cheng-Han; Lien, Der-Hsien; Chang, Hung-Chih; Lin, Chin-An; Kang, Chen-Fang; Hsing, Meng-Kai; Lai, Kun-Yu; He, Jr-Hau

2012-12-07

We experimentally and theoretically demonstrated the hierarchical structure of SiO(2) nanorod arrays/p-GaN microdomes as a light harvesting scheme for InGaN-based multiple quantum well solar cells. The combination of nano- and micro-structures leads to increased internal multiple reflection and provides an intermediate refractive index between air and GaN. Cells with the hierarchical structure exhibit improved short-circuit current densities and fill factors, rendering a 1.47 fold efficiency enhancement as compared to planar cells.

Assessing an organizational culture instrument based on the Competing Values Framework: Exploratory and confirmatory factor analyses

PubMed Central

Helfrich, Christian D; Li, Yu-Fang; Mohr, David C; Meterko, Mark; Sales, Anne E

2007-01-01

Background The Competing Values Framework (CVF) has been widely used in health services research to assess organizational culture as a predictor of quality improvement implementation, employee and patient satisfaction, and team functioning, among other outcomes. CVF instruments generally are presented as well-validated with reliable aggregated subscales. However, only one study in the health sector has been conducted for the express purpose of validation, and that study population was limited to hospital managers from a single geographic locale. Methods We used exploratory and confirmatory factor analyses to examine the underlying structure of data from a CVF instrument. We analyzed cross-sectional data from a work environment survey conducted in the Veterans Health Administration (VHA). The study population comprised all staff in non-supervisory positions. The survey included 14 items adapted from a popular CVF instrument, which measures organizational culture according to four subscales: hierarchical, entrepreneurial, team, and rational. Results Data from 71,776 non-supervisory employees (approximate response rate 51%) from 168 VHA facilities were used in this analysis. Internal consistency of the subscales was moderate to strong (α = 0.68 to 0.85). However, the entrepreneurial, team, and rational subscales had higher correlations across subscales than within, indicating poor divergent properties. Exploratory factor analysis revealed two factors, comprising the ten items from the entrepreneurial, team, and rational subscales loading on the first factor, and two items from the hierarchical subscale loading on the second factor, along with one item from the rational subscale that cross-loaded on both factors. Results from confirmatory factor analysis suggested that the two-subscale solution provides a more parsimonious fit to the data as compared to the original four-subscale model. Conclusion This study suggests that there may be problems applying conventional CVF subscales to non-supervisors, and underscores the importance of assessing psychometric properties of instruments in each new context and population to which they are applied. It also further highlights the challenges management scholars face in assessing organizational culture in a reliable and comparable way. More research is needed to determine if the emergent two-subscale solution is a valid or meaningful alternative and whether these findings generalize beyond VHA. PMID:17459167

Global Trends and Factors Associated with the Illegal Killing of Elephants: A Hierarchical Bayesian Analysis of Carcass Encounter Data

PubMed Central

Burn, Robert W.; Underwood, Fiona M.; Blanc, Julian

2011-01-01

Elephant poaching and the ivory trade remain high on the agenda at meetings of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). Well-informed debates require robust estimates of trends, the spatial distribution of poaching, and drivers of poaching. We present an analysis of trends and drivers of an indicator of elephant poaching of all elephant species. The site-based monitoring system known as Monitoring the Illegal Killing of Elephants (MIKE), set up by the 10th Conference of the Parties of CITES in 1997, produces carcass encounter data reported mainly by anti-poaching patrols. Data analyzed were site by year totals of 6,337 carcasses from 66 sites in Africa and Asia from 2002–2009. Analysis of these observational data is a serious challenge to traditional statistical methods because of the opportunistic and non-random nature of patrols, and the heterogeneity across sites. Adopting a Bayesian hierarchical modeling approach, we used the proportion of carcasses that were illegally killed (PIKE) as a poaching index, to estimate the trend and the effects of site- and country-level factors associated with poaching. Important drivers of illegal killing that emerged at country level were poor governance and low levels of human development, and at site level, forest cover and area of the site in regions where human population density is low. After a drop from 2002, PIKE remained fairly constant from 2003 until 2006, after which it increased until 2008. The results for 2009 indicate a decline. Sites with PIKE ranging from the lowest to the highest were identified. The results of the analysis provide a sound information base for scientific evidence-based decision making in the CITES process. PMID:21912670

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.

Global trends and factors associated with the illegal killing of elephants: A hierarchical bayesian analysis of carcass encounter data.

PubMed

Burn, Robert W; Underwood, Fiona M; Blanc, Julian

2011-01-01

Elephant poaching and the ivory trade remain high on the agenda at meetings of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). Well-informed debates require robust estimates of trends, the spatial distribution of poaching, and drivers of poaching. We present an analysis of trends and drivers of an indicator of elephant poaching of all elephant species. The site-based monitoring system known as Monitoring the Illegal Killing of Elephants (MIKE), set up by the 10(th) Conference of the Parties of CITES in 1997, produces carcass encounter data reported mainly by anti-poaching patrols. Data analyzed were site by year totals of 6,337 carcasses from 66 sites in Africa and Asia from 2002-2009. Analysis of these observational data is a serious challenge to traditional statistical methods because of the opportunistic and non-random nature of patrols, and the heterogeneity across sites. Adopting a bayesian hierarchical modeling approach, we used the proportion of carcasses that were illegally killed (PIKE) as a poaching index, to estimate the trend and the effects of site- and country-level factors associated with poaching. Important drivers of illegal killing that emerged at country level were poor governance and low levels of human development, and at site level, forest cover and area of the site in regions where human population density is low. After a drop from 2002, PIKE remained fairly constant from 2003 until 2006, after which it increased until 2008. The results for 2009 indicate a decline. Sites with PIKE ranging from the lowest to the highest were identified. The results of the analysis provide a sound information base for scientific evidence-based decision making in the CITES process.

ZnO Hierarchical Nanostructure Photoanode in a CdS Quantum Dot-Sensitized Solar Cell

PubMed Central

Liu, Huan; Zhang, Gengmin; Sun, Wentao; Shen, Ziyong; Shi, Mingji

2015-01-01

A hierarchical array of ZnO nanocones covered with ZnO nanospikes was hydrothermally fabricated and employed as the photoanode in a CdS quantum dot-sensitized solar cell (QDSSC). This QDSSC outperformed the QDSSC based on a simple ZnO nanocone photoanode in all the four principal photovoltaic parameters. Using the hierarchical photoanode dramatically increased the short circuit current density and also slightly raised the open circuit voltage and the fill factor. As a result, the conversion efficiency of the QDSSC based on the hierarchical photoanode was more than twice that of the QDSSC based on the simple ZnO nanocone photoanode. This improvement is attributable to both the enlarged specific area of the photoanode and the reduction in the recombination of the photoexcited electrons. PMID:26379268

Structural and incremental validity of the Wechsler Adult Intelligence Scale-Fourth Edition with a clinical sample.

PubMed

Nelson, Jason M; Canivez, Gary L; Watkins, Marley W

2013-06-01

Structural and incremental validity of the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV; Wechsler, 2008a) was examined with a sample of 300 individuals referred for evaluation at a university-based clinic. Confirmatory factor analysis indicated that the WAIS-IV structure was best represented by 4 first-order factors as well as a general intelligence factor in a direct hierarchical model. The general intelligence factor accounted for the most common and total variance among the subtests. Incremental validity analyses indicated that the Full Scale IQ (FSIQ) generally accounted for medium to large portions of academic achievement variance. For all measures of academic achievement, the first-order factors combined accounted for significant achievement variance beyond that accounted for by the FSIQ, but individual factor index scores contributed trivial amounts of achievement variance. Implications for interpreting WAIS-IV results are discussed. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Structure of the Wechsler Intelligence Scale for Children--Fourth Edition among a national sample of referred students.

PubMed

Watkins, Marley W

2010-12-01

The structure of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV; D. Wechsler, 2003a) was analyzed via confirmatory factor analysis among a national sample of 355 students referred for psychoeducational evaluation by 93 school psychologists from 35 states. The structure of the WISC-IV core battery was best represented by four first-order factors as per D. Wechsler (2003b), plus a general intelligence factor in a direct hierarchical model. The general factor was the predominate source of variation among WISC-IV subtests, accounting for 48% of the total variance and 75% of the common variance. The largest 1st-order factor, Processing Speed, only accounted for 6.1% total and 9.5% common variance. Given these explanatory contributions, recommendations favoring interpretation of the 1st-order factor scores over the general intelligence score appear to be misguided.

An exploration of the structure of mentors' behavior in nursing education using exploratory factor analysis and Mokken scale analysis.

PubMed

Chen, Yanhua; Watson, Roger; Hilton, Andrea

2016-05-01

To understand nursing students' expectation from their mentors and assess mentors' performance, a scale of mentors' behavior was developed based on literature review and focus group in China. This study aims to explore the structure of mentors' behavior. A cross-sectional survey. Data were collected from nursing students in three hospitals in southwest China in 2014. A total of 669 pre-registered nursing students in their final year clinical learning participated in this study. Exploratory factor analysis and Mokken scale analysis was employed to explore the structure and hierarchical property of mentors' behavior. Three dimensions (professional development, facilitating learning and psychosocial support) were identified by factor analysis and confirmed by Mokken scaling analysis. The three sub-scales showed internal consistency reliability from 87% to 91%, and moderate to strong precision in ordering students' expectation about mentors' behavior and a small Mokken scale showing hierarchy was identified. Some insight into the structure of mentoring in nursing education has been obtained and a scale which could be used in the study of mentoring and in the preparation of mentors has been developed. Copyright © 2016 Elsevier Ltd. All rights reserved.

External validity of a hierarchical dimensional model of child and adolescent psychopathology: Tests using confirmatory factor analyses and multivariate behavior genetic analyses.

PubMed

Waldman, Irwin D; Poore, Holly E; van Hulle, Carol; Rathouz, Paul J; Lahey, Benjamin B

2016-11-01

Several recent studies of the hierarchical phenotypic structure of psychopathology have identified a General psychopathology factor in addition to the more expected specific Externalizing and Internalizing dimensions in both youth and adult samples and some have found relevant unique external correlates of this General factor. We used data from 1,568 twin pairs (599 MZ & 969 DZ) age 9 to 17 to test hypotheses for the underlying structure of youth psychopathology and the external validity of the higher-order factors. Psychopathology symptoms were assessed via structured interviews of caretakers and youth. We conducted phenotypic analyses of competing structural models using Confirmatory Factor Analysis and used Structural Equation Modeling and multivariate behavior genetic analyses to understand the etiology of the higher-order factors and their external validity. We found that both a General factor and specific Externalizing and Internalizing dimensions are necessary for characterizing youth psychopathology at both the phenotypic and etiologic levels, and that the 3 higher-order factors differed substantially in the magnitudes of their underlying genetic and environmental influences. Phenotypically, the specific Externalizing and Internalizing dimensions were slightly negatively correlated when a General factor was included, which reflected a significant inverse correlation between the nonshared environmental (but not genetic) influences on Internalizing and Externalizing. We estimated heritability of the general factor of psychopathology for the first time. Its moderate heritability suggests that it is not merely an artifact of measurement error but a valid construct. The General, Externalizing, and Internalizing factors differed in their relations with 3 external validity criteria: mother's smoking during pregnancy, parent's harsh discipline, and the youth's association with delinquent peers. Multivariate behavior genetic analyses supported the external validity of the 3 higher-order factors by suggesting that the General, Externalizing, and Internalizing factors were correlated with peer delinquency and parent's harsh discipline for different etiologic reasons. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Hierarchical porous ZnO microflowers with ultra-high ethanol gas-sensing at low concentration

NASA Astrophysics Data System (ADS)

Song, Liming; Yue, He; Li, Haiying; Liu, Li; Li, Yu; Du, Liting; Duan, Haojie; Klyui, N. I.

2018-05-01

Hierarchical porous and non-porous ZnO microflowers have been successfully fabricated by hydrothermal method. Their crystal structure, morphology and gas-sensing properties were studied by X-ray diffraction (XRD), scanning electron microscopy (SEM), and chemical gas sensing intelligent analysis system (CGS). Compared with hierarchical non-porous ZnO microflowers, hierarchical porous ZnO microflowers exhibited ultra-high sensitivity with 50 ppm ethanol at 260 °C and the response is 110, which is 1.8 times higher than that of non-porous ZnO microflowers. Moreover, the lowest concentration limit of hierarchical porous ZnO microflowers (non-porous ZnO microflowers) to ethanol is 0.1 (1) ppm, the response value is 1.6 (1).

Analysis and compensation for the effect of the catheter position on image intensities in intravascular optical coherence tomography

NASA Astrophysics Data System (ADS)

Liu, Shengnan; Eggermont, Jeroen; Wolterbeek, Ron; Broersen, Alexander; Busk, Carol A. G. R.; Precht, Helle; Lelieveldt, Boudewijn P. F.; Dijkstra, Jouke

2016-12-01

Intravascular optical coherence tomography (IVOCT) is an imaging technique that is used to analyze the underlying cause of cardiovascular disease. Because a catheter is used during imaging, the intensities can be affected by the catheter position. This work aims to analyze the effect of the catheter position on IVOCT image intensities and to propose a compensation method to minimize this effect in order to improve the visualization and the automatic analysis of IVOCT images. The effect of catheter position is modeled with respect to the distance between the catheter and the arterial wall (distance-dependent factor) and the incident angle onto the arterial wall (angle-dependent factor). A light transmission model incorporating both factors is introduced. On the basis of this model, the interaction effect of both factors is estimated with a hierarchical multivariant linear regression model. Statistical analysis shows that IVOCT intensities are significantly affected by both factors with p<0.001, as either aspect increases the intensity decreases. This effect differs for different pullbacks. The regression results were used to compensate for this effect. Experiments show that the proposed compensation method can improve the performance of the automatic bioresorbable vascular scaffold strut detection.

The contribution of genetics and early rearing experiences to hierarchical personality dimensions in chimpanzees (Pan troglodytes).

PubMed

Latzman, Robert D; Freeman, Hani D; Schapiro, Steven J; Hopkins, William D

2015-11-01

A reliable literature finds that traits are related to each other in an organized hierarchy encompassing various conceptualizations of personality (e.g., Big Three, five-factor model). Recent work suggests the potential of a similar organization among our closest nonhuman relative, chimpanzees (Pan troglodytes), with significant links to neurobiology suggesting an evolutionarily and neurobiologically based hierarchical structure of personality. The current study investigated this hierarchical structure, the heritability of the various personality dimensions across levels of the hierarchy, and associations with early social rearing experience in a large sample (N = 238) of socially housed, captive chimpanzees residing in 2 independent colonies of apes. Results provide support for a hierarchical structure of personality in chimpanzees with significant associations with early rearing experiences. Further, heritabilities of the various dimensions varied by early rearing, with affective dimensions found to be significantly heritable among mother-reared apes, whereas personality dimensions were largely independent of relatedness among the nursery-reared apes. Taken together, these findings provide evidence for the influence of both genetic and environmental factors on personality profiles across levels of the hierarchy, supporting the importance of considering environmental variation in models of quantitative trait evolution. (c) 2015 APA, all rights reserved).

The contribution of genetics and early rearing experiences to hierarchical personality dimensions in chimpanzees (Pan troglodytes)

PubMed Central

Latzman, Robert D.; Freeman, Hani D.; Schapiro, Steven J.; Hopkins, William D.

2015-01-01

A reliable literature finds that traits are related to each other in an organized hierarchy encompassing various conceptualizations of personality (e.g., Big Three, Five Factor Model). Recent work suggests the potential of a similar organization among our closest nonhuman relative, chimpanzees (Pan troglodytes), with significant links to neurobiology suggesting an evolutionarily- and neurobiologically-based hierarchical structure of personality. The current study investigated this hierarchical structure, the heritability of the various personality dimensions across levels of the hierarchy, and associations with early social rearing experience in a large sample (N = 238) of socially-housed, captive chimpanzees residing in two independent colonies of apes. Results provide support for a hierarchical structure of personality in chimpanzees with significant associations with early rearing experiences. Further, heritabilities of the various dimensions varied by early rearing, with affective dimensions found to be significantly heritable among mother-reared apes, while personality dimensions were largely independent of relatedness among the nursery-reared apes. Taken together, these findings provide evidence for the influence of both genetic and environmental factors on personality profiles across levels of the hierarchy, supporting the importance of considering environmental variation in models of quantitative trait evolution. PMID:25915132

Further Evaluation of the Tripartite Structure of Subjective Well-Being: Evidence From Longitudinal and Experimental Studies.

PubMed

Metler, Samantha J; Busseri, Michael A

2017-04-01

Subjective well-being (SWB; Diener, 1984) comprises three primary components: life satisfaction (LS), positive affect (PA), and negative affect (NA). Multiple competing conceptualizations of the tripartite structure of SWB have been employed, resulting in widespread ambiguity concerning the definition, operationalization, analysis, and synthesis of SWB-related findings (Busseri & Sadava, 2011). We report two studies evaluating two predominant structural models (as recently identified by Busseri, 2015): a hierarchical model comprising a higher-order latent SWB factor with LS, PA, and NA as indicators; and a causal systems model specifying unidirectional effects of PA and NA on LS. A longitudinal study (N = 452; M age  = 18.54; 76.5% female) and a lab-based experiment (N = 195; M age  = 20.42 years; 87.6% female; 81.5% Caucasian) were undertaken. Structural models were evaluated with respect to (a) associations among SWB components across time (three months, three years in Study 1; one week in Study 2) and (b) the impact of manipulating the individual SWB components (Study 2). A hierarchical structural model was supported in both studies; conflicting evidence was found for the causal systems model. A hierarchical model provides a robust conceptualization for the tripartite structure of SWB. © 2015 Wiley Periodicals, Inc.

Preoperative factors affecting cost and length of stay for isolated off-pump coronary artery bypass grafting: hierarchical linear model analysis.

PubMed

Shinjo, Daisuke; Fushimi, Kiyohide

2015-11-17

To determine the effect of preoperative patient and hospital factors on resource use, cost and length of stay (LOS) among patients undergoing off-pump coronary artery bypass grafting (OPCAB). Observational retrospective study. Data from the Japanese Administrative Database. Patients who underwent isolated, elective OPCAB between April 2011 and March 2012. The primary outcomes of this study were inpatient cost and LOS associated with OPCAB. A two-level hierarchical linear model was used to examine the effects of patient and hospital characteristics on inpatient costs and LOS. The independent variables were patient and hospital factors. We identified 2491 patients who underwent OPCAB at 268 hospitals. The mean cost of OPCAB was $40 665 ±7774, and the mean LOS was 23.4±8.2 days. The study found that select patient factors and certain comorbidities were associated with a high cost and long LOS. A high hospital OPCAB volume was associated with a low cost (-6.6%; p=0.024) as well as a short LOS (-17.6%, p<0.001). The hospital OPCAB volume is associated with efficient resource use. The findings of the present study indicate the need to focus on hospital elective OPCAB volume in Japan in order to improve cost and LOS. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Hierarchical organization of macaque and cat cortical sensory systems explored with a novel network processor.

PubMed

Hilgetag, C C; O'Neill, M A; Young, M P

2000-01-29

Neuroanatomists have described a large number of connections between the various structures of monkey and cat cortical sensory systems. Because of the complexity of the connection data, analysis is required to unravel what principles of organization they imply. To date, analysis of laminar origin and termination connection data to reveal hierarchical relationships between the cortical areas has been the most widely acknowledged approach. We programmed a network processor that searches for optimal hierarchical orderings of cortical areas given known hierarchical constraints and rules for their interpretation. For all cortical systems and all cost functions, the processor found a multitude of equally low-cost hierarchies. Laminar hierarchical constraints that are presently available in the anatomical literature were therefore insufficient to constrain a unique ordering for any of the sensory systems we analysed. Hierarchical orderings of the monkey visual system that have been widely reported, but which were derived by hand, were not among the optimal orderings. All the cortical systems we studied displayed a significant degree of hierarchical organization, and the anatomical constraints from the monkey visual and somato-motor systems were satisfied with very few constraint violations in the optimal hierarchies. The visual and somato-motor systems in that animal were therefore surprisingly strictly hierarchical. Most inconsistencies between the constraints and the hierarchical relationships in the optimal structures for the visual system were related to connections of area FST (fundus of superior temporal sulcus). We found that the hierarchical solutions could be further improved by assuming that FST consists of two areas, which differ in the nature of their projections. Indeed, we found that perfect hierarchical arrangements of the primate visual system, without any violation of anatomical constraints, could be obtained under two reasonable conditions, namely the subdivision of FST into two distinct areas, whose connectivity we predict, and the abolition of at least one of the less reliable rule constraints. Our analyses showed that the future collection of the same type of laminar constraints, or the inclusion of new hierarchical constraints from thalamocortical connections, will not resolve the problem of multiple optimal hierarchical representations for the primate visual system. Further data, however, may help to specify the relative ordering of some more areas. This indeterminacy of the visual hierarchy is in part due to the reported absence of some connections between cortical areas. These absences are consistent with limited cross-talk between differentiated processing streams in the system. Hence, hierarchical representation of the visual system is affected by, and must take into account, other organizational features, such as processing streams.

Leuconostoc strains isolated from dairy products: Response against food stress conditions.

PubMed

D'Angelo, Luisa; Cicotello, Joaquín; Zago, Miriam; Guglielmotti, Daniela; Quiberoni, Andrea; Suárez, Viviana

2017-09-01

A systematic study about the intrinsic resistance of 29 strains (26 autochthonous and 3 commercial ones), belonging to Leuconostoc genus, against diverse stress factors (thermal, acidic, alkaline, osmotic and oxidative) commonly present at industrial or conservation processes were evaluated. Exhaustive result processing was made by applying one-way ANOVA, Student's test (t), multivariate analysis by Principal Component Analysis (PCA) and Matrix Hierarchical Cluster Analysis. In addition, heat adaptation on 4 strains carefully selected based on previous data analysis was assayed. The strains revealed wide diversity of resistance to stress factors and, in general, a clear relationship between resistance and Leuconostoc species was established. In this sense, the highest resistance was shown by Leuconostoc lactis followed by Leuconostoc mesenteroides strains, while Leuconostoc pseudomesenteroides and Leuconostoc citreum strains revealed the lowest resistance to the stress factors applied. Heat adaptation improved thermal cell survival and resulted in a cross-resistance against the acidic factor. However, all adapted cells showed diminished their oxidative resistance. According to our knowledge, this is the first study regarding response of Leuconostoc strains against technological stress factors and could establish the basis for the selection of "more robust" strains and propose the possibility of improving their performance during industrial processes. Copyright © 2017 Elsevier Ltd. All rights reserved.

[Reliability and validity of the Occupational Stress Scale for Chinese offshore oil platform workers].

PubMed

Chen, Wei-qing; Huang, Zi-hui; Yu, De-xin; Lin, Yan-zu; Ling, Zhi-ming; Tang, Ji-song

2003-02-01

To evaluate the validity and reliability of the Occupational Stress Scale (OSS) for Chinese offshore oil platform workers. A 51-item self-administered questionnaire developed in the light of Cooper's questionnaire and company's special situation was used to investigate 561 subjects. 51 occupational stress items relating to offshore oil production were subjected to factor analysis, and nine latent factors were identified, which explained 62.5% of the total variance. According to the contents described by the items included in each factor, they were respectively defined as: "the interface between job and family/social life (factor 1)", "career and achievement (factor 2)", "safety (factor 3)", "management problem and relationship with others at work (factor 4)", "physical factors of workplace (factor 5)", "platform living environment (factor 6)", "role in management (factor 7)", "ergonomics (factor 8)" and "organization structure (factor 9)". Significant difference in the score of five factors was observed among 12 different job categories by analysis of variance. After adjusting for potential confounding factors (age, educational level), hierarchical multiple regression analysis indicated that the score of the OSS was significantly and positively correlated with the poor mental health of the workers (P < 0.01). The consistent test between OSS and each factor showed that Cronbach's alpha were 0.72 - 0.91. The OSS is a valid and reliable tool for measuring occupational stress, and can be used to explore occupational stress and its influence on health and safety problems in offshore oil workers.

Investigation of variety resources and quantitative analysis on Heyin pomegranate in Xingyang City

NASA Astrophysics Data System (ADS)

Li, Wenzeng; Wang, Zhihong

2018-04-01

Various factors that should be considered in variety breeding of Heyin pomegranate, the hierarchical analysis is carried out through analytic hierarchy process (AHP) and its analytic result can be used to help fruit farmers make scientific decision on the variety breeding of pomegranate. In the six main Heyin pomegranate varieties, the ranking weight value of Tunisian soft-seeded pomegranate is 0.3105, which is No.1 in all pomegranate varieties and is obviously better than other varieties in comprehensive feature. It shows that, in the cultivation of pomegranate in Xingyang, the Tunisian soft-seeded pomegranate is the preferred variety for fruit farmers.

Development of a hierarchical model for predicting microbiological contamination of private groundwater supplies in a geologically heterogeneous region.

PubMed

O'Dwyer, Jean; Hynds, Paul D; Byrne, Kenneth A; Ryan, Michael P; Adley, Catherine C

2018-06-01

Private groundwater sources in the Republic of Ireland provide drinking water to an estimated 750,000 people or 16% of the national population. Consumers of untreated groundwater are at increased risk of infection from pathogenic microorganisms. However, given the volume of private wells in operation, remediation or even quantification of public risk is both costly and time consuming. In this study, a hierarchical logistic regression model was developed to 'predict' contamination with E. coli based on the results of groundwater quality analyses of private wells (n = 132) during the period of September 2011 to November 2012. Assessment of potential microbial contamination risk factors were categorised into three groups: Intrinsic (environmental factors), Specific (local features) and Infrastructural (groundwater source characteristics) which included a total of 15 variables. Overall, 51.4% of wells tested positive for E. coli during the study period with univariate analysis indicating that 11 of the 15 assessed risk factors, including local bedrock type, local subsoil type, septic tank reliance, 5 day antecedent precipitation and temperature, along with well type and depth, were all significantly associated with E. coli presence (p < 0.05). Hierarchical logistic regression was used to develop a private well susceptibility model with the final model containing 8 of the 11 associated variables. The model was shown to be highly efficient; correctly classifying the presence of E. coli in 94.2% of cases, and the absence of E. coli in 84.7% of cases. Model validation was performed using an external data set (n = 32) and it was shown that the model has promising accuracy with 90% of positive E. coli cases correctly predicted. The developed model represents a risk assessment and management tool that may be used to develop effective water-quality management strategies to minimize public health risks both in Ireland and abroad. Copyright © 2018 Elsevier Ltd. All rights reserved.

Statistical Significance for Hierarchical Clustering

PubMed Central

Kimes, Patrick K.; Liu, Yufeng; Hayes, D. Neil; Marron, J. S.

2017-01-01

Summary Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this paper, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets. PMID:28099990

Comparative analysis of hierarchical triangulated irregular networks to represent 3D elevation in terrain databases

NASA Astrophysics Data System (ADS)

Abdelguerfi, Mahdi; Wynne, Chris; Cooper, Edgar; Ladner, Roy V.; Shaw, Kevin B.

1997-08-01

Three-dimensional terrain representation plays an important role in a number of terrain database applications. Hierarchical triangulated irregular networks (TINs) provide a variable-resolution terrain representation that is based on a nested triangulation of the terrain. This paper compares and analyzes existing hierarchical triangulation techniques. The comparative analysis takes into account how aesthetically appealing and accurate the resulting terrain representation is. Parameters, such as adjacency, slivers, and streaks, are used to provide a measure on how aesthetically appealing the terrain representation is. Slivers occur when the triangulation produces thin and slivery triangles. Streaks appear when there are too many triangulations done at a given vertex. Simple mathematical expressions are derived for these parameters, thereby providing a fairer and a more easily duplicated comparison. In addition to meeting the adjacency requirement, an aesthetically pleasant hierarchical TINs generation algorithm is expected to reduce both slivers and streaks while maintaining accuracy. A comparative analysis of a number of existing approaches shows that a variant of a method originally proposed by Scarlatos exhibits better overall performance.

Overlapping communities detection based on spectral analysis of line graphs

NASA Astrophysics Data System (ADS)

Gui, Chun; Zhang, Ruisheng; Hu, Rongjing; Huang, Guoming; Wei, Jiaxuan

2018-05-01

Community in networks are often overlapping where one vertex belongs to several clusters. Meanwhile, many networks show hierarchical structure such that community is recursively grouped into hierarchical organization. In order to obtain overlapping communities from a global hierarchy of vertices, a new algorithm (named SAoLG) is proposed to build the hierarchical organization along with detecting the overlap of community structure. SAoLG applies the spectral analysis into line graphs to unify the overlap and hierarchical structure of the communities. In order to avoid the limitation of absolute distance such as Euclidean distance, SAoLG employs Angular distance to compute the similarity between vertices. Furthermore, we make a micro-improvement partition density to evaluate the quality of community structure and use it to obtain the more reasonable and sensible community numbers. The proposed SAoLG algorithm achieves a balance between overlap and hierarchy by applying spectral analysis to edge community detection. The experimental results on one standard network and six real-world networks show that the SAoLG algorithm achieves higher modularity and reasonable community number values than those generated by Ahn's algorithm, the classical CPM and GN ones.

Hierarchical models and the analysis of bird survey information

USGS Publications Warehouse

Sauer, J.R.; Link, W.A.

2003-01-01

Management of birds often requires analysis of collections of estimates. We describe a hierarchical modeling approach to the analysis of these data, in which parameters associated with the individual species estimates are treated as random variables, and probability statements are made about the species parameters conditioned on the data. A Markov-Chain Monte Carlo (MCMC) procedure is used to fit the hierarchical model. This approach is computer intensive, and is based upon simulation. MCMC allows for estimation both of parameters and of derived statistics. To illustrate the application of this method, we use the case in which we are interested in attributes of a collection of estimates of population change. Using data for 28 species of grassland-breeding birds from the North American Breeding Bird Survey, we estimate the number of species with increasing populations, provide precision-adjusted rankings of species trends, and describe a measure of population stability as the probability that the trend for a species is within a certain interval. Hierarchical models can be applied to a variety of bird survey applications, and we are investigating their use in estimation of population change from survey data.

New insight in magnetic saturation behavior of nickel hierarchical structures

NASA Astrophysics Data System (ADS)

Ma, Ji; Zhang, Jianxing; Liu, Chunting; Chen, Kezheng

2017-09-01

It is unanimously accepted that non-ferromagnetic inclusions in a ferromagnetic system will lower down total saturation magnetization in unit of emu/g. In this study, ;lattice strain; was found to be another key factor to have critical impact on magnetic saturation behavior of the system. The lattice strain determined assembling patterns of primary nanoparticles in hierarchical structures and was intimately related with the formation process of these architectures. Therefore, flower-necklace-like and cauliflower-like nickel hierarchical structures were used as prototype systems to evidence the relationship between assembling patterns of primary nanoparticles and magnetic saturation behaviors of these architectures. It was found that the influence of lattice strain on saturation magnetization outperformed that of non-ferromagnetic inclusions in these hierarchical structures. This will enable new insights into fundamental understanding of related magnetic effects.

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.

Construction of anatase/rutile TiO2 hollow boxes for highly efficient photocatalytic performance

NASA Astrophysics Data System (ADS)

Jia, Changchao; Zhang, Xiao; Yang, Ping

2018-02-01

Hollow TiO2 hierarchical boxes with suitable anatase and rutile ratios were designed for photocatalysis. The unique hierarchical structure was fabricated via a Topotactic synthetic method. CaTiO3 cubes were acted as the sacrificial templates to create TiO2 hollow hierarchical boxes with well-defined phase distribution. The phase composition of the hollow TiO2 hierarchical boxes is similar to that of TiO2 P25 nanoparticles (∼80% anatase, and 20% rutile). Compared with nanaoparticles, TiO2 hollow boxes with hierarchical structures exhibited an excellent performance in the photocatalytic degradation of methylene blue organic pollutant. Quantificationally, the degradation rate of the hollow boxes is higher than that of TiO2 P25 nanoparticles by a factor of 2.7. This is ascribed that hollow structure provide an opportunity for using incident light more efficiently. The surface hierarchical and well-organized porous structures are beneficial to supply more active sites and enough transport channels for reactant molecules. The boxes consist of single crystal anatase and rutile combined well with each other, which gives photon-generated carriers transfer efficiently.

Assessing risk profiles for Salmonella serotypes in breeding pig operations in Portugal using a Bayesian hierarchical model

PubMed Central

2012-01-01

Background The EU Regulation No 2160/2003 imposes a reduction in the prevalence of Salmonella in pigs. The efficiency of control programmes for Salmonella in pigs, reported among the EU Member States, varies and definitive eradication seems very difficult. Control measures currently recommended for Salmonella are not serotype-specific. Is it possible that the risk factors for different Salmonella serotypes are different? The aim of this study was to investigate potential risk factors for two groups of Salmonella sp serotypes using pen faecal samples from breeding pig holdings representative of the Portuguese pig sector. Methods The data used come from the Baseline Survey for the Prevalence of Salmonella in breeding pigs in Portugal. A total of 1670 pen faecal samples from 167 herds were tested, and 170 samples were positive for Salmonella. The presence of Salmonella in each sample (outcome variable) was classified in three categories: i) no Salmonella, ii) Salmonella Typhimurium or S. Typhimurium-like strains with the antigenic formula: 1,4,5,12:i:-, , and iii) other serotypes. Along with the sample collection, a questionnaire concerning herd management and potential risk factors was utilised. The data have a “natural” hierarchical structure so a categorical multilevel analysis of the dataset was carried out using a Bayesian hierarchical model. The model was estimated using Markov Chain Monte Carlo methods, implemented in the software WinBUGS. Results The significant associations found (when compared to category “no Salmonella”), for category “serotype Typhimurium or S. Typhimurium-like strains with the antigenic formula: 1,4,5,12:i:-” were: age of breeding sows, size of the herd, number of pigs/pen and source of semen. For the category “other serotypes” the significant associations found were: control of rodents, region of the country, source of semen, breeding sector room and source of feed. Conclusions The risk factors significantly associated with Salmonella shedding from the category “serotype Typhimurium or serotype 1,4,5,12:i:-“ were more related to animal factors, whereas those associated with “other serotypes” were more related to environmental factors. Our findings suggest that different control measures could be used to control different Salmonella serotypes in breeding pigs. PMID:23171637

Integrative analysis of the Caenorhabditis elegans genome by the modENCODE project.

PubMed

Gerstein, Mark B; Lu, Zhi John; Van Nostrand, Eric L; Cheng, Chao; Arshinoff, Bradley I; Liu, Tao; Yip, Kevin Y; Robilotto, Rebecca; Rechtsteiner, Andreas; Ikegami, Kohta; Alves, Pedro; Chateigner, Aurelien; Perry, Marc; Morris, Mitzi; Auerbach, Raymond K; Feng, Xin; Leng, Jing; Vielle, Anne; Niu, Wei; Rhrissorrakrai, Kahn; Agarwal, Ashish; Alexander, Roger P; Barber, Galt; Brdlik, Cathleen M; Brennan, Jennifer; Brouillet, Jeremy Jean; Carr, Adrian; Cheung, Ming-Sin; Clawson, Hiram; Contrino, Sergio; Dannenberg, Luke O; Dernburg, Abby F; Desai, Arshad; Dick, Lindsay; Dosé, Andréa C; Du, Jiang; Egelhofer, Thea; Ercan, Sevinc; Euskirchen, Ghia; Ewing, Brent; Feingold, Elise A; Gassmann, Reto; Good, Peter J; Green, Phil; Gullier, Francois; Gutwein, Michelle; Guyer, Mark S; Habegger, Lukas; Han, Ting; Henikoff, Jorja G; Henz, Stefan R; Hinrichs, Angie; Holster, Heather; Hyman, Tony; Iniguez, A Leo; Janette, Judith; Jensen, Morten; Kato, Masaomi; Kent, W James; Kephart, Ellen; Khivansara, Vishal; Khurana, Ekta; Kim, John K; Kolasinska-Zwierz, Paulina; Lai, Eric C; Latorre, Isabel; Leahey, Amber; Lewis, Suzanna; Lloyd, Paul; Lochovsky, Lucas; Lowdon, Rebecca F; Lubling, Yaniv; Lyne, Rachel; MacCoss, Michael; Mackowiak, Sebastian D; Mangone, Marco; McKay, Sheldon; Mecenas, Desirea; Merrihew, Gennifer; Miller, David M; Muroyama, Andrew; Murray, John I; Ooi, Siew-Loon; Pham, Hoang; Phippen, Taryn; Preston, Elicia A; Rajewsky, Nikolaus; Rätsch, Gunnar; Rosenbaum, Heidi; Rozowsky, Joel; Rutherford, Kim; Ruzanov, Peter; Sarov, Mihail; Sasidharan, Rajkumar; Sboner, Andrea; Scheid, Paul; Segal, Eran; Shin, Hyunjin; Shou, Chong; Slack, Frank J; Slightam, Cindie; Smith, Richard; Spencer, William C; Stinson, E O; Taing, Scott; Takasaki, Teruaki; Vafeados, Dionne; Voronina, Ksenia; Wang, Guilin; Washington, Nicole L; Whittle, Christina M; Wu, Beijing; Yan, Koon-Kiu; Zeller, Georg; Zha, Zheng; Zhong, Mei; Zhou, Xingliang; Ahringer, Julie; Strome, Susan; Gunsalus, Kristin C; Micklem, Gos; Liu, X Shirley; Reinke, Valerie; Kim, Stuart K; Hillier, LaDeana W; Henikoff, Steven; Piano, Fabio; Snyder, Michael; Stein, Lincoln; Lieb, Jason D; Waterston, Robert H

2010-12-24

We systematically generated large-scale data sets to improve genome annotation for the nematode Caenorhabditis elegans, a key model organism. These data sets include transcriptome profiling across a developmental time course, genome-wide identification of transcription factor-binding sites, and maps of chromatin organization. From this, we created more complete and accurate gene models, including alternative splice forms and candidate noncoding RNAs. We constructed hierarchical networks of transcription factor-binding and microRNA interactions and discovered chromosomal locations bound by an unusually large number of transcription factors. Different patterns of chromatin composition and histone modification were revealed between chromosome arms and centers, with similarly prominent differences between autosomes and the X chromosome. Integrating data types, we built statistical models relating chromatin, transcription factor binding, and gene expression. Overall, our analyses ascribed putative functions to most of the conserved genome.

Combined analysis of roadside and off-road breeding bird survey data to assess population change in Alaska

USGS Publications Warehouse

Handel, Colleen M.; Sauer, John

2017-01-01

Management interest in North American birds has increasingly focused on species that breed in Alaska, USA, and Canada, where habitats are changing rapidly in response to climatic and anthropogenic factors. We used a series of hierarchical models to estimate rates of population change in 2 forested Bird Conservation Regions (BCRs) in Alaska based on data from the roadside North American Breeding Bird Survey (BBS) and the Alaska Landbird Monitoring Survey, which samples off-road areas on public resource lands. We estimated long-term (1993–2015) population trends for 84 bird species from the BBS and short-term (2003–2015) trends for 31 species from both surveys. Among the 84 species with long-term estimates, 11 had positive trends and 17 had negative trends in 1 or both BCRs; negative trends were primarily found among aerial insectivores and wetland-associated species, confirming range-wide negative continental trends for many of these birds. Three species with negative trends in the contiguous United States and southern Canada had positive trends in Alaska, suggesting different population dynamics at the northern edges of their ranges. Regional population trends within Alaska differed for several species, particularly those represented by different subspecies in the 2 BCRs, which are separated by rugged, glaciated mountain ranges. Analysis of the roadside and off-road data in a joint hierarchical model with shared parameters resulted in improved precision of trend estimates and suggested a roadside-related difference in underlying population trends for several species, particularly within the Northwestern Interior Forest BCR. The combined analysis highlights the importance of considering population structure, physiographic barriers, and spatial heterogeneity in habitat change when assessing patterns of population change across a landscape as broad as Alaska. Combined analysis of roadside and off-road survey data in a hierarchical framework may be particularly useful for evaluating patterns of population change in relatively undeveloped regions with sparse roadside BBS coverage.

MC EMiNEM maps the interaction landscape of the Mediator.

PubMed

Niederberger, Theresa; Etzold, Stefanie; Lidschreiber, Michael; Maier, Kerstin C; Martin, Dietmar E; Fröhlich, Holger; Cramer, Patrick; Tresch, Achim

2012-01-01

The Mediator is a highly conserved, large multiprotein complex that is involved essentially in the regulation of eukaryotic mRNA transcription. It acts as a general transcription factor by integrating regulatory signals from gene-specific activators or repressors to the RNA Polymerase II. The internal network of interactions between Mediator subunits that conveys these signals is largely unknown. Here, we introduce MC EMiNEM, a novel method for the retrieval of functional dependencies between proteins that have pleiotropic effects on mRNA transcription. MC EMiNEM is based on Nested Effects Models (NEMs), a class of probabilistic graphical models that extends the idea of hierarchical clustering. It combines mode-hopping Monte Carlo (MC) sampling with an Expectation-Maximization (EM) algorithm for NEMs to increase sensitivity compared to existing methods. A meta-analysis of four Mediator perturbation studies in Saccharomyces cerevisiae, three of which are unpublished, provides new insight into the Mediator signaling network. In addition to the known modular organization of the Mediator subunits, MC EMiNEM reveals a hierarchical ordering of its internal information flow, which is putatively transmitted through structural changes within the complex. We identify the N-terminus of Med7 as a peripheral entity, entailing only local structural changes upon perturbation, while the C-terminus of Med7 and Med19 appear to play a central role. MC EMiNEM associates Mediator subunits to most directly affected genes, which, in conjunction with gene set enrichment analysis, allows us to construct an interaction map of Mediator subunits and transcription factors.

The relation of a family history of alcoholism, obstetric complications and family environment to behavioral problems among 154 adolescents in Germany: results from the children of alcoholics study in Pomerania.

PubMed

Barnow, Sven; Lucht, Michael; Hamm, Alfons; John, Ulrich; Freyberger, Harald-J

2004-01-01

Behavioral problems in adolescence have been shown to be associated with the presence of a positive family history of alcoholism (FH+), obstetric complications (OCs), and negative parenting practices. This study tested the relation of these factors to aggression/delinquency and attention problems in an untreated population sample of 154 adolescents in Pomerania. Furthermore, we evaluated the predictive strength of a FH+, OCs and negative parenting styles in a prospective subsample of 127 adolescents using a hierarchical regression analysis. Group comparisons between offspring with higher vs. lower values on aggression/delinquency revealed that only rejection by the parents was significantly more often reported by teenagers with higher measures on these behavioral problems. Offspring with higher values on attention problems had more OCs reported by the mother and also had more feelings of parental rejection compared to controls. The results of the hierarchical regression analysis showed that parental rejection was the only significant predictor for both aggression/delinquency, and attention problems measured 1 year after the initial assessment. We conclude that parental rejection is a major risk factor for both aggression/delinquency and attention problems. Reflecting the fact that these behavioral problems have been reported to be strongly associated with later substance misuse, the improvement of parenting practices should be considered in prevention and intervention programs. Copyright 2004 S. Karger AG, Basel

Assimilating multi-source uncertainties of a parsimonious conceptual hydrological model using hierarchical Bayesian modeling

Treesearch

Wei Wu; James Clark; James Vose

2010-01-01

Hierarchical Bayesian (HB) modeling allows for multiple sources of uncertainty by factoring complex relationships into conditional distributions that can be used to draw inference and make predictions. We applied an HB model to estimate the parameters and state variables of a parsimonious hydrological model – GR4J – by coherently assimilating the uncertainties from the...

Self-organized Criticality in Hierarchical Brain Network

NASA Astrophysics Data System (ADS)

Yang, Qiu-Ying; Zhang, Ying-Yue; Chen, Tian-Lun

2008-11-01

It is shown that the cortical brain network of the macaque displays a hierarchically clustered organization and the neuron network shows small-world properties. Now the two factors will be considered in our model and the dynamical behavior of the model will be studied. We study the characters of the model and find that the distribution of avalanche size of the model follows power-law behavior.

[A case-control study of factors associated with repeat teen pregnancy based on a sample from a university maternity hospital].

PubMed

Silva, Andréa de Albuquerque Arruda; Coutinho, Isabela C; Katz, Leila; Souza, Alex Sandro Rolland

2013-03-01

Repeat teen pregnancy is a frequent issue and is considered an aggravating factor for increased maternal and fetal morbidity and social problems. The aim of the study was to identify factors associated with repeat teen pregnancy. A case-control study was conducted in 90 postpartum adolescents with more than one pregnancy (cases) and 90 adult women with a history of only one pregnancy during adolescence (controls). Statistical analysis used hierarchical logistic regression with 5% significance. Early sexual initiation (< 15 years), early age at first pregnancy (< 16 years), not raising the children themselves, and low family income (< one minimum wage) were associated with repeat teenage pregnancy, while partner change was inversely associated. Repeat teen pregnancy was mainly associated with reproductive and socioeconomic factors. Partner change appeared as a protective factor. Measures should be adopted during the postpartum period of teenage mothers in order to avoid repeat pregnancy.

Organizational Benchmarks for Test Utilization Performance: An Example Based on Positivity Rates for Genetic Tests.

PubMed

Rudolf, Joseph; Jackson, Brian R; Wilson, Andrew R; Smock, Kristi J; Schmidt, Robert L

2017-04-01

Health care organizations are under increasing pressure to deliver value by improving test utilization management. Many factors, including organizational factors, could affect utilization performance. Past research has focused on the impact of specific interventions in single organizations. The impact of organizational factors is unknown. The objective of this study is to determine whether testing patterns are subject to organizational effects, ie, are utilization patterns for individual tests correlated within organizations. Comparative analysis of ordering patterns (positivity rates for three genetic tests) across 659 organizations. Hierarchical regression was used to assess the impact of organizational factors after controlling for test-level factors (mutation prevalence) and hospital bed size. Test positivity rates were correlated within organizations. Organizations have a statistically significant impact on the positivity rate of three genetic tests. © American Society for Clinical Pathology, 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

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

Dose-response relations between occupational exposures to physical and psychosocial factors and the risk of low back pain

PubMed Central

Jansen, J; Morgenstern, H; Burdorf, A

2004-01-01

Aims: To assess dose-response relations between occupational exposures to physical and psychosocial factors and the risk of low back pain. Methods: A cohort of 523 subjects, working in nursing homes and homes for the elderly, was followed prospectively for one year. Physical load for different occupations was assessed by quantitative observations at the workplace. Information on low back pain and other factors was gathered with questionnaires administered at baseline and at one year. Two outcome measures of low back pain incidence were used: any new episode of pain lasting for at least a few hours during follow up (LBP); and any new episode of disabling pain that interfered with daily activities during follow up (LBP/D). Hierarchical regression analysis with a spline function was used to estimate dose-response relations. Results: The risk of LBP was not associated with physical factors, controlling for confounders; but this outcome was inversely associated with age and weakly, though imprecisely, associated with two psychosocial factors—low decision authority and high work demands. In contrast, the risk of LBP/D was positively associated with age and not associated with the psychosocial factors. Trunk flexion over 45 degrees was monotonically associated with the risk of LBP/D; the estimated relative risk was 3.18 (95% CI 1.13 to 9.00) for 1 hour and 45 minutes of bending per week (90th centile), relative to 30 minutes per week. The hierarchical estimates of effect were more stable than were the maximum likelihood estimates. Conclusion: Occupational exposure to trunk flexion over 45 degrees appears to be a risk factor for low back pain with disability among persons employed in nursing homes and homes for the elderly in the Netherlands. PMID:15550602

Vasopressin compared with norepinephrine augments the decline of plasma cytokine levels in septic shock.

PubMed

Russell, James A; Fjell, Chris; Hsu, Joseph L; Lee, Terry; Boyd, John; Thair, Simone; Singer, Joel; Patterson, Andrew J; Walley, Keith R

2013-08-01

Changes in plasma cytokine levels may predict mortality, and therapies (vasopressin versus norepinephrine) could change plasma cytokine levels in early septic shock. Our hypotheses were that changes in plasma cytokine levels over 24 hours differ between survivors and nonsurvivors, and that there are different effects of vasopressin and norepinephrine on plasma cytokine levels in septic shock. We studied 394 patients in a randomized, controlled trial of vasopressin versus norepinephrine in septic shock. We used hierarchical clustering and principal components analysis of the baseline cytokine concentrations to subgroup cytokines; we then compared survivors to nonsurvivors (28 d) and compared vasopressin- versus norepinephrine-induced changes in cytokine levels over 24 hours. A total of 39 plasma cytokines were measured at baseline and at 24 hours. Hierarchical clustering and principal components analysis grouped cytokines similarly. Survivors (versus nonsurvivors) had greater decreases of overall cytokine levels (P < 0.001). Vasopressin decreased overall 24-hour cytokine concentration compared with norepinephrine (P = 0.037). In less severe septic shock, the difference in plasma cytokine reduction over 24 hours between survivors and nonsurvivors was less pronounced than that seen in more severe septic shock. Furthermore, vasopressin decreased interferon-inducible protein 10 and granulocyte colony-stimulating factor more than did norepinephrine in less severe septic shock, whereas vasopressin decreased granulocyte-macrophage colony-stimulating factor in patients who had more severe shock. Survivors of septic shock had greater decreases of cytokines, chemokines and growth factors in early septic shock. Vasopressin decreased 24-hour plasma cytokine levels more than did norepinephrine. The vasopressin-associated decrease of cytokines differed according to severity of shock. Clinical trial registered with www.controlled-trials.com (ISRCTN94845869).

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.

Predictive Ability of Pender's Health Promotion Model for Physical Activity and Exercise in People with Spinal Cord Injuries: A Hierarchical Regression Analysis

ERIC Educational Resources Information Center

Keegan, John P.; Chan, Fong; Ditchman, Nicole; Chiu, Chung-Yi

2012-01-01

The main objective of this study was to validate Pender's Health Promotion Model (HPM) as a motivational model for exercise/physical activity self-management for people with spinal cord injuries (SCIs). Quantitative descriptive research design using hierarchical regression analysis (HRA) was used. A total of 126 individuals with SCI were recruited…

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 =…

Hierarchical Traces for Reduced NSM Memory Requirements

NASA Astrophysics Data System (ADS)

Dahl, Torbjørn S.

This paper presents work on using hierarchical long term memory to reduce the memory requirements of nearest sequence memory (NSM) learning, a previously published, instance-based reinforcement learning algorithm. A hierarchical memory representation reduces the memory requirements by allowing traces to share common sub-sequences. We present moderated mechanisms for estimating discounted future rewards and for dealing with hidden state using hierarchical memory. We also present an experimental analysis of how the sub-sequence length affects the memory compression achieved and show that the reduced memory requirements do not effect the speed of learning. Finally, we analyse and discuss the persistence of the sub-sequences independent of specific trace instances.

On the Structure of Personality Disorder Traits: Conjoint Analyses of the CAT-PD, PID-5, and NEO-PI-3 Trait Models

PubMed Central

Wright, Aidan G.C.; Simms, Leonard J.

2014-01-01

The current study examines the relations among contemporary models of pathological and normal range personality traits. Specifically, we report on (a) conjoint exploratory factor analyses of the Computerized Adaptive Test of Personality Disorder static form (CAT-PD-SF) with the Personality Inventory for the DSM-5 (PID-5; Krueger et al., 2012) and NEO Personality Inventory-3 First Half (NEI-PI-3FH; McCrae & Costa, 2007), and (b) unfolding hierarchical analyses of the three measures in a large general psychiatric outpatient sample (N = 628; 64% Female). A five-factor solution provided conceptually coherent alignment among the CAT-PD-SF, PID-5, and NEO-PI-3FH scales. Hierarchical solutions suggested that higher-order factors bear strong resemblance to dimensions that emerge from structural models of psychopathology (e.g., Internalizing and Externalizing spectra). These results demonstrate that the CAT-PD-SF adheres to the consensual structure of broad trait domains at the five-factor level. Additionally, patterns of scale loadings further inform questions of structure and bipolarity of facet and domain level constructs. Finally, hierarchical analyses strengthen the argument for using broad dimensions that span normative and pathological functioning to scaffold a quantitatively derived phenotypic structure of psychopathology to orient future research on explanatory, etiological, and maintenance mechanisms. PMID:24588061

On the structure of personality disorder traits: conjoint analyses of the CAT-PD, PID-5, and NEO-PI-3 trait models.

PubMed

Wright, Aidan G C; Simms, Leonard J

2014-01-01

The current study examines the relations among contemporary models of pathological and normal range personality traits. Specifically, we report on (a) conjoint exploratory factor analyses of the Computerized Adaptive Test of Personality Disorder static form (CAT-PD-SF) with the Personality Inventory for the Diagnostic and Statistical Manual of Mental Disorders, fifth edition and NEO Personality Inventory-3 First Half, and (b) unfolding hierarchical analyses of the three measures in a large general psychiatric outpatient sample (n = 628; 64% Female). A five-factor solution provided conceptually coherent alignment among the CAT-PD-SF, PID-5, and NEO-PI-3FH scales. Hierarchical solutions suggested that higher-order factors bear strong resemblance to dimensions that emerge from structural models of psychopathology (e.g., Internalizing and Externalizing spectra). These results demonstrate that the CAT-PD-SF adheres to the consensual structure of broad trait domains at the five-factor level. Additionally, patterns of scale loadings further inform questions of structure and bipolarity of facet and domain level constructs. Finally, hierarchical analyses strengthen the argument for using broad dimensions that span normative and pathological functioning to scaffold a quantitatively derived phenotypic structure of psychopathology to orient future research on explanatory, etiological, and maintenance mechanisms.

Cryptanalysis of Chatterjee-Sarkar Hierarchical Identity-Based Encryption Scheme at PKC 06

NASA Astrophysics Data System (ADS)

Park, Jong Hwan; Lee, Dong Hoon

In 2006, Chatterjee and Sarkar proposed a hierarchical identity-based encryption (HIBE) scheme which can support an unbounded number of identity levels. This property is particularly useful in providing forward secrecy by embedding time components within hierarchical identities. In this paper we show that their scheme does not provide the claimed property. Our analysis shows that if the number of identity levels becomes larger than the value of a fixed public parameter, an unintended receiver can reconstruct a new valid ciphertext and decrypt the ciphertext using his or her own private key. The analysis is similarly applied to a multi-receiver identity-based encryption scheme presented as an application of Chatterjee and Sarkar's HIBE scheme.

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

A study of the kinetics and isotherms for Cr(VI) adsorption in a binary mixture of Cr(VI)-Ni(II) using hierarchical porous carbon obtained from pig bone.

PubMed

Li, Chengxian; Huang, Zhe; Huang, Bicheng; Liu, Changfeng; Li, Chengming; Huang, Yaqin

2014-01-01

Cr(VI) adsorption in a binary mixture Cr(VI)-Ni(II) using the hierarchical porous carbon prepared from pig bone (HPC) was investigated. The various factors affecting adsorption of Cr(VI) ions from aqueous solutions such as initial concentration, pH, temperature and contact time were analyzed. The results showed excellent efficiency of Cr(VI) adsorption by HPC. The kinetics and isotherms for Cr(VI) adsorption from a binary mixture Cr(VI)-Ni(II) by HPC were studied. The adsorption equilibrium described by the Langmuir isotherm model is better than that described by the Freundlich isotherm model for the binary mixture in this study. The maximum adsorption capacity was reliably found to be as high as 192.68 mg/g in the binary mixture at pH 2. On fitting the experimental data to both pseudo-first- and second-order equations, the regression analysis of the second-order equation gave a better R² value.

The importance of trait emotional intelligence and feelings in the prediction of perceived and biological stress in adolescents: hierarchical regressions and fsQCA models.

PubMed

Villanueva, Lidón; Montoya-Castilla, Inmaculada; Prado-Gascó, Vicente

2017-07-01

The purpose of this study is to analyze the combined effects of trait emotional intelligence (EI) and feelings on healthy adolescents' stress. Identifying the extent to which adolescent stress varies with trait emotional differences and the feelings of adolescents is of considerable interest in the development of intervention programs for fostering youth well-being. To attain this goal, self-reported questionnaires (perceived stress, trait EI, and positive/negative feelings) and biological measures of stress (hair cortisol concentrations, HCC) were collected from 170 adolescents (12-14 years old). Two different methodologies were conducted, which included hierarchical regression models and a fuzzy-set qualitative comparative analysis (fsQCA). The results support trait EI as a protective factor against stress in healthy adolescents and suggest that feelings reinforce this relation. However, the debate continues regarding the possibility of optimal levels of trait EI for effective and adaptive emotional management, particularly in the emotional attention and clarity dimensions and for female adolescents.

Assessment of relevant factors and relationships concerning human dermal exposure to pesticides in greenhouse applications.

PubMed

Martínez Vidal, Jose L; Egea González, Francisco J; Garrido Frenich, Antonia; Martínez Galera, María; Aguilera, Pedro A; López Carrique, Enrique

2002-08-01

Principal component analysis (PCA) was applied to the gas chromatographic data obtained from 23 different greenhouse trials. This was used to establish which factors, including application technique (very small, small, medium and large drop-size), crop characteristics (short/tall, thin/dense) and pattern application of the operator (walking towards or away from the treated area) are relevant to the dermal exposure levels of greenhouse applicators. The results showed that the highest exposure by pesticides during field applications in greenhouses, in the climatic conditions and in the crop conditions typical of a southern European country, occurs on the lower legs and front thighs of the applicators. Similar results were obtained by hierarchical cluster analysis (HCA). Drop-size seems to be very important in determining total exposure, while height and density of crops have little influence on total exposure under the conditions of the present study. No pesticide type is a major factor in total exposure. The application of multiple regression analysis (MRA) allowed assessment of the relationships between the pesticide exposure of the less affected parts of the body with the most affected parts.

Parallel and competitive processes in hierarchical analysis: perceptual grouping and encoding of closure.

PubMed

Han, S; Humphreys, G W; Chen, L

1999-10-01

The role of perceptual grouping and the encoding of closure of local elements in the processing of hierarchical patterns was studied. Experiments 1 and 2 showed a global advantage over the local level for 2 tasks involving the discrimination of orientation and closure, but there was a local advantage for the closure discrimination task relative to the orientation discrimination task. Experiment 3 showed a local precedence effect for the closure discrimination task when local element grouping was weakened by embedding the stimuli from Experiment 1 in a background made up of cross patterns. Experiments 4A and 4B found that dissimilarity of closure between the local elements of hierarchical stimuli and the background figures could facilitate the grouping of closed local elements and enhanced the perception of global structure. Experiment 5 showed that the advantage for detecting the closure of local elements in hierarchical analysis also held under divided- and selective-attention conditions. Results are consistent with the idea that grouping between local elements takes place in parallel and competes with the computation of closure of local elements in determining the selection between global and local levels of hierarchical patterns for response.

The Plastic Surgery Match: A Quantitative Analysis of Applicant Impressions From the Interview Visit.

PubMed

Frojo, Gianfranco; Tadisina, Kashyap Komarraju; Pressman, Zachary; Chibnall, John T; Lin, Alexander Y; Kraemer, Bruce A

2016-12-01

The integrated plastic surgery match is a competitive process not only for applicants but also for programs vying for highly qualified candidates. Interactions between applicants and program constituents are limited to a single interview visit. The authors aimed to identify components of the interview visit that influence applicant decision making when determining a final program rank list. Thirty-six applicants who were interviewed (100% response) completed the survey. Applicants rated the importance of 20 elements of the interview visit regarding future ranking of the program on a 1 to 5 Likert scale. Data were analyzed using descriptive statistics, hierarchical cluster analysis, analysis of variance, and Pearson correlations. A literature review was performed regarding the plastic surgery integrated residency interview process. Survey questions were categorized into four groups based on mean survey responses:1. Interactions with faculty and residents (mean response > 4),2. Information about the program (3.5-4),3. Ancillaries (food, amenities, stipends) (3-3.5),4. Hospital tour, hotel (<3).Hierarchical item cluster analysis and analysis of variance testing validated these groupings. Average summary scores were calculated for the items representing Interactions, Information, and Ancillaries. Correlation analysis between clusters yielded no significant correlations. A review of the literature yielded a paucity of data on analysis of the interview visit. The interview visit consists of a discrete hierarchy of perceived importance by applicants. The strongest independent factor in determining future program ranking is the quality of interactions between applicants and program constituents on the interview visit. This calls for further investigation and optimization of the interview visit experience.

Perceived Effects of Scholarships on STEM Majors' Commitment to Teaching in High Need Schools

NASA Astrophysics Data System (ADS)

Liou, Pey-Yan; Kirchhoff, Allison; Lawrenz, Frances

2010-06-01

This study examines the Noyce Program, which provides scholarships for STEM majors in return for teaching in high need schools. The perceptions of 555 scholarship recipients were investigated using hierarchical cluster analysis, confirmatory factor analysis, and Rasch analysis to determine how the scholarship influenced their commitments to teaching in high need schools. The analyses indicated that recipients perceived the scholarship in two ways: it influenced their commitment to complete their certification program and to teach in high need schools. Implications for teacher education programs include that recruitment strategies should identify candidates who are committed to teaching in high need schools and programs should provide experiences to encourage this commitment not just to become certified.

Analytic methods for questions pertaining to a randomized pretest, posttest, follow-up design.

PubMed

Rausch, Joseph R; Maxwell, Scott E; Kelley, Ken

2003-09-01

Delineates 5 questions regarding group differences that are likely to be of interest to researchers within the framework of a randomized pretest, posttest, follow-up (PPF) design. These 5 questions are examined from a methodological perspective by comparing and discussing analysis of variance (ANOVA) and analysis of covariance (ANCOVA) methods and briefly discussing hierarchical linear modeling (HLM) for these questions. This article demonstrates that the pretest should be utilized as a covariate in the model rather than as a level of the time factor or as part of the dependent variable within the analysis of group differences. It is also demonstrated that how the posttest and the follow-up are utilized in the analysis of group differences is determined by the specific question asked by the researcher.

The MIL-88A-Derived Fe3O4-Carbon Hierarchical Nanocomposites for Electrochemical Sensing

PubMed Central

Wang, Li; Zhang, Yayun; Li, Xia; Xie, Yingzhen; He, Juan; Yu, Jie; Song, Yonghai

2015-01-01

Metal or metal oxides/carbon nanocomposites with hierarchical superstructures have become one of the most promising functional materials in sensor, catalysis, energy conversion, etc. In this work, novel hierarchical Fe3O4/carbon superstructures have been fabricated based on metal-organic frameworks (MOFs)-derived method. Three kinds of Fe-MOFs (MIL-88A) with different morphologies were prepared beforehand as templates, and then pyrolyzed to fabricate the corresponding novel hierarchical Fe3O4/carbon superstructures. The systematic studies on the thermal decomposition process of the three kinds of MIL-88A and the effect of template morphology on the products were carried out in detail. Scanning electron microscopy, transmission electron microscopy, X-ray powder diffraction, X-ray photoelectron spectroscopy and thermal analysis were employed to investigate the hierarchical Fe3O4/carbon superstructures. Based on these resulted hierarchical Fe3O4/carbon superstructures, a novel and sensitive nonenzymatic N-acetyl cysteine sensor was developed. The porous and hierarchical superstructures and large surface area of the as-formed Fe3O4/carbon superstructures eventually contributed to the good electrocatalytic activity of the prepared sensor towards the oxidation of N-acetyl cysteine. The proposed preparation method of the hierarchical Fe3O4/carbon superstructures is simple, efficient, cheap and easy to mass production. It might open up a new way for hierarchical superstructures preparation. PMID:26387535

The hierarchical structure of childhood personality in five countries: continuity from early childhood to early adolescence.

PubMed

Tackett, Jennifer L; Slobodskaya, Helena R; Mar, Raymond A; Deal, James; Halverson, Charles F; Baker, Spencer R; Pavlopoulos, Vassilis; Besevegis, Elias

2012-08-01

Childhood personality is a rapidly growing area of investigation within individual differences research. One understudied topic is the universality of the hierarchical structure of childhood personality. In the present investigation, parents rated the personality characteristics of 3,751 children from 5 countries and 4 age groups. The hierarchical structure of childhood personality was examined for 1-, 2-, 3-, 4-, and 5-factor models across country (Canada, China, Greece, Russia, and the United States) and age group (3-5, 6-8, 9-11, and 12-14 years of age). Many similarities were noted across both country and age. The Five-Factor Model was salient beginning in early childhood (ages 3-5). Deviations across groups and from adult findings are noted, including the prominent role of antagonism in childhood personality and the high covariation between Conscientiousness and intellect. Future directions, including the need for more explicit attempts to merge temperament and personality models, are discussed. © 2011 The Authors. Journal of Personality © 2011, Wiley Periodicals, Inc.

Performance Analysis of Hierarchical Group Key Management Integrated with Adaptive Intrusion Detection in Mobile ad hoc Networks

DTIC Science & Technology

2016-04-05

applications in wireless networks such as military battlefields, emergency response, mobile commerce , online gaming, and collaborative work are based on the...www.elsevier.com/locate/peva Performance analysis of hierarchical group key management integrated with adaptive intrusion detection in mobile ad hoc...Accepted 19 September 2010 Available online 26 September 2010 Keywords: Mobile ad hoc networks Intrusion detection Group communication systems Group

Periorbital melasma: Hierarchical cluster analysis of clinical features in Asian patients.

PubMed

Jung, Y S; Bae, J M; Kim, B J; Kang, J-S; Cho, S B

2017-11-01

Studies have shown melasma lesions to be distributed across the face in centrofacial, malar, and mandibular patterns. Meanwhile, however, melasma lesions of the periorbital area have yet to be thoroughly described. We analyzed normal and ultraviolet light-exposed photographs of patients with melasma. The periorbital melasma lesions were measured according to anatomical reference points and a hierarchical cluster analysis was performed. The periorbital melasma lesions showed clinical features of fine and homogenous melasma pigmentation, involving both the upper and lower eyelids that extended to other anatomical sites with a darker and coarser appearance. The hierarchical cluster analysis indicated that patients with periorbital melasma can be categorized into two clusters according to the surface anatomy of the face. Significant differences between cluster 1 and cluster 2 were found in lateral distance and inferolateral distance, but not in medial distance and superior distance. Comparing the two clusters, patients in cluster 2 were found to be significantly older and more commonly accompanied by melasma lesions of the temple and medial cheek. Our hierarchical cluster analysis of periorbital melasma lesions demonstrated that Asian patients with periorbital melasma can be categorized into two clusters according to the surface anatomy of the face. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Proton Nuclear Magnetic Resonance-Spectroscopic Discrimination of Wines Reflects Genetic Homology of Several Different Grape (V. vinifera L.) Cultivars.

PubMed

Hu, Boran; Yue, Yaqing; Zhu, Yong; Wen, Wen; Zhang, Fengmin; Hardie, Jim W

2015-01-01

Proton nuclear magnetic resonance spectroscopy coupled multivariate analysis (1H NMR-PCA/PLS-DA) is an important tool for the discrimination of wine products. Although 1H NMR has been shown to discriminate wines of different cultivars, a grape genetic component of the discrimination has been inferred only from discrimination of cultivars of undefined genetic homology and in the presence of many confounding environmental factors. We aimed to confirm the influence of grape genotypes in the absence of those factors. We applied 1H NMR-PCA/PLS-DA and hierarchical cluster analysis (HCA) to wines from five, variously genetically-related grapevine (V. vinifera) cultivars; all grown similarly on the same site and vinified similarly. We also compared the semi-quantitative profiles of the discriminant metabolites of each cultivar with previously reported chemical analyses. The cultivars were clearly distinguishable and there was a general correlation between their grouping and their genetic homology as revealed by recent genomic studies. Between cultivars, the relative amounts of several of the cultivar-related discriminant metabolites conformed closely with reported chemical analyses. Differences in grape-derived metabolites associated with genetic differences alone are a major source of 1H NMR-based discrimination of wines and 1H NMR has the capacity to discriminate between very closely related cultivars. The study confirms that genetic variation among grape cultivars alone can account for the discrimination of wine by 1H NMR-PCA/PLS and indicates that 1H NMR spectra of wine of single grape cultivars may in future be used in tandem with hierarchical cluster analysis to elucidate genetic lineages and metabolomic relations of grapevine cultivars. In the absence of genetic information, for example, where predecessor varieties are no longer extant, this may be a particularly useful approach.

Chemical grafting of the superhydrophobic surface on copper with hierarchical microstructure and its formation mechanism

NASA Astrophysics Data System (ADS)

Cai, Junyan; Wang, Shuhui; Zhang, Junhong; Liu, Yang; Hang, Tao; Ling, Huiqin; Li, Ming

2018-04-01

In this paper, a superhydrophobic surface with hierarchical structure was fabricated by chemical deposition of Cu micro-cones array, followed by chemical grafting of poly(methyl methacrylate) (PMMA). Water contact measurements give contact angle of 131.0° on these surfaces after PMMA grafting of 2 min and 165.2° after 6 min. The superhydrophobicity results from two factors: (1) the hierarchical structure due to Cu micro-cones array and the second level structure caused by intergranular corrosion during grafting of PMMA (confirmed by the scanning electron microscopy) and (2) the chemical modification of a low surface energy PMMA layer (confirmed by Fourier transform infrared spectrometer and X-ray photoelectron spectroscopy). In the chemical grafting process, the spontaneous reduction of nitrobenzene diazonium (NBD) tetrafluoroborate not only causes the corrosion of the Cu surface that leads to a hierarchical structure, but also initiates the polymerization of methyl methacrylate (MMA) monomers and thus the low free energy surface. Such a robust approach to fabricate the hierarchical structured surface with superhydrophobicity is expected to have practical application in anti-corrosion industry.

Multiple directed graph large-class multi-spectral processor

NASA Technical Reports Server (NTRS)

Casasent, David; Liu, Shiaw-Dong; Yoneyama, Hideyuki

1988-01-01

Numerical analysis techniques for the interpretation of high-resolution imaging-spectrometer data are described and demonstrated. The method proposed involves the use of (1) a hierarchical classifier with a tree structure generated automatically by a Fisher linear-discriminant-function algorithm and (2) a novel multiple-directed-graph scheme which reduces the local maxima and the number of perturbations required. Results for a 500-class test problem involving simulated imaging-spectrometer data are presented in tables and graphs; 100-percent-correct classification is achieved with an improvement factor of 5.

Cognitive Diagnostic Analysis Using Hierarchically Structured Skills

ERIC Educational Resources Information Center

Su, Yu-Lan

2013-01-01

This dissertation proposes two modified cognitive diagnostic models (CDMs), the deterministic, inputs, noisy, "and" gate with hierarchy (DINA-H) model and the deterministic, inputs, noisy, "or" gate with hierarchy (DINO-H) model. Both models incorporate the hierarchical structures of the cognitive skills in the model estimation…

Obstructive Sleep Apnea: A Cluster Analysis at Time of Diagnosis

PubMed Central

Grillet, Yves; Richard, Philippe; Stach, Bruno; Vivodtzev, Isabelle; Timsit, Jean-Francois; Lévy, Patrick; Tamisier, Renaud; Pépin, Jean-Louis

2016-01-01

Background The classification of obstructive sleep apnea is on the basis of sleep study criteria that may not adequately capture disease heterogeneity. Improved phenotyping may improve prognosis prediction and help select therapeutic strategies. Objectives: This study used cluster analysis to investigate the clinical clusters of obstructive sleep apnea. Methods An ascending hierarchical cluster analysis was performed on baseline symptoms, physical examination, risk factor exposure and co-morbidities from 18,263 participants in the OSFP (French national registry of sleep apnea). The probability for criteria to be associated with a given cluster was assessed using odds ratios, determined by univariate logistic regression. Results: Six clusters were identified, in which patients varied considerably in age, sex, symptoms, obesity, co-morbidities and environmental risk factors. The main significant differences between clusters were minimally symptomatic versus sleepy obstructive sleep apnea patients, lean versus obese, and among obese patients different combinations of co-morbidities and environmental risk factors. Conclusions Our cluster analysis identified six distinct clusters of obstructive sleep apnea. Our findings underscore the high degree of heterogeneity that exists within obstructive sleep apnea patients regarding clinical presentation, risk factors and consequences. This may help in both research and clinical practice for validating new prevention programs, in diagnosis and in decisions regarding therapeutic strategies. PMID:27314230

The evolution of Zipf's law indicative of city development

NASA Astrophysics Data System (ADS)

Chen, Yanguang

2016-02-01

Zipf's law of city-size distributions can be expressed by three types of mathematical models: one-parameter form, two-parameter form, and three-parameter form. The one-parameter and one of the two-parameter models are familiar to urban scientists. However, the three-parameter model and another type of two-parameter model have not attracted attention. This paper is devoted to exploring the conditions and scopes of application of these Zipf models. By mathematical reasoning and empirical analysis, new discoveries are made as follows. First, if the size distribution of cities in a geographical region cannot be described with the one- or two-parameter model, maybe it can be characterized by the three-parameter model with a scaling factor and a scale-translational factor. Second, all these Zipf models can be unified by hierarchical scaling laws based on cascade structure. Third, the patterns of city-size distributions seem to evolve from three-parameter mode to two-parameter mode, and then to one-parameter mode. Four-year census data of Chinese cities are employed to verify the three-parameter Zipf's law and the corresponding hierarchical structure of rank-size distributions. This study is revealing for people to understand the scientific laws of social systems and the property of urban development.

A new instrument to measure quality of life of heart failure family caregivers.

PubMed

Nauser, Julie A; Bakas, Tamilyn; Welch, Janet L

2011-01-01

Family caregivers of heart failure (HF) patients experience poor physical and mental health leading to poor quality of life. Although several quality-of-life measures exist, they are often too generic to capture the unique experience of this population. The purpose of this study was to evaluate the psychometric properties of the Family Caregiver Quality of Life (FAMQOL) Scale that was designed to assess the physical, psychological, social, and spiritual dimensions of quality of life among caregivers of HF patients. Psychometric testing of the FAMQOL with 100 HF family caregivers was conducted using item analysis, Cronbach α, intraclass correlation, factor analysis, and hierarchical multiple regression guided by a conceptual model. Caregivers were predominately female (89%), white, (73%), and spouses (62%). Evidence of internal consistency reliability (α=.89) was provided for the FAMQOL, with item-total correlations of 0.39 to 0.74. Two-week test-retest reliability was supported by an intraclass correlation coefficient of 0.91. Using a 1-factor solution and principal axis factoring, loadings ranged from 0.31 to 0.78, with 41% of the variance explained by the first factor (eigenvalue=6.5). With hierarchical multiple regression, 56% of the FAMQOL variance was explained by model constructs (F8,91=16.56, P<.001). Criterion-related validity was supported by correlations with SF-36 General (r=0.45, P<.001) and Mental (r=0.59, P<.001) Health subscales and Bakas Caregiving Outcomes Scale (r=0.73, P<.001). Evidence of internal and test-retest reliability and construct and criterion validity was provided for physical, psychological, and social well-being subscales. The 16-item FAMQOL is a brief, easy-to-administer instrument that has evidence of reliability and validity in HF family caregivers. Physical, psychological, and social well-being can be measured with 4-item subscales. The FAMQOL scale could serve as a valuable measure in research, as well as an assessment tool to identify caregivers in need of intervention.

Water quality analysis of the Rapur area, Andhra Pradesh, South India using multivariate techniques

NASA Astrophysics Data System (ADS)

Nagaraju, A.; Sreedhar, Y.; Thejaswi, A.; Sayadi, Mohammad Hossein

2017-10-01

The groundwater samples from Rapur area were collected from different sites to evaluate the major ion chemistry. The large number of data can lead to difficulties in the integration, interpretation, and representation of the results. Two multivariate statistical methods, hierarchical cluster analysis (HCA) and factor analysis (FA), were applied to evaluate their usefulness to classify and identify geochemical processes controlling groundwater geochemistry. Four statistically significant clusters were obtained from 30 sampling stations. This has resulted two important clusters viz., cluster 1 (pH, Si, CO3, Mg, SO4, Ca, K, HCO3, alkalinity, Na, Na + K, Cl, and hardness) and cluster 2 (EC and TDS) which are released to the study area from different sources. The application of different multivariate statistical techniques, such as principal component analysis (PCA), assists in the interpretation of complex data matrices for a better understanding of water quality of a study area. From PCA, it is clear that the first factor (factor 1), accounted for 36.2% of the total variance, was high positive loading in EC, Mg, Cl, TDS, and hardness. Based on the PCA scores, four significant cluster groups of sampling locations were detected on the basis of similarity of their water quality.

Spatial Bayesian Latent Factor Regression Modeling of Coordinate-based Meta-analysis Data

PubMed Central

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D.; Nichols, Thomas E.

2017-01-01

Summary Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to 1) identify areas of consistent activation; and 2) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterised as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. PMID:28498564

Internal Structure and Partial Invariance across Gender in the Spanish Version of the Reasoning Test Battery.

PubMed

Elosua, Paula; Mujika, Josu

2015-10-13

The Reasoning Test Battery (BPR) is an instrument built on theories of the hierarchical organization of cognitive abilities and therefore consists of different tasks related with abstract, numerical, verbal, practical, spatial and mechanical reasoning. It was originally created in Belgium and later adapted to Portuguese. There are three forms of the battery consisting of different items and scales which cover an age range from 9 to 22. This paper focuses on the adaptation of the BPR to Spanish, and analyzes different aspects of its internal structure: (a) exploratory item factor analysis was applied to assess the presence of a dominant factor for each partial scale; (b) the general underlined model was evaluated through confirmatory factor analysis, and (c) factorial invariance across gender was studied. The sample consisted of 2624 Spanish students. The results concluded the presence of a general factor beyond the scales, with equivalent values for men and women, and gender differences in the factorial structure which affect the numerical reasoning, abstract reasoning and mechanical reasoning scales.

Exploration of Individual and Family Factors Related to Community Reintegration in Veterans With Traumatic Brain Injury.

PubMed

Moriarty, Helene; Winter, Laraine; Robinson, Keith; True, Gala; Piersol, Catherine; Vause-Earland, Tracey; Iacovone, Dolores Blazer; Holbert, Laura; Newhart, Brian; Fishman, Deborah; Short, Thomas H

2015-01-01

Community reintegration (CR) poses a major problem for military veterans who have experienced a traumatic brain injury (TBI). Factors contributing to CR after TBI are poorly understood. To address the gap in knowledge, an ecological framework was used to explore individual and family factors related to CR. Baseline data from an intervention study with 83 veterans with primarily mild to moderate TBI were analyzed. Instruments measured CR, depressive symptoms, physical health, quality of the relationship with the family member, and sociodemographics. Posttraumatic stress disorder and TBI characteristics were determined through record review. Five variables that exhibited significant bivariate relationships with CR (veteran rating of quality of relationship, physical functioning, bodily pain, posttraumatic stress disorder diagnosis, and depressive symptoms) were entered into hierarchical regression analysis. In the final analysis, the five variables together accounted for 35% of the variance, but only depression was a significant predictor of CR, with more depressed veterans exhibiting lower CR. Efforts to support CR of Veterans with TBI should carefully assess and target depression, a modifiable factor. © The Author(s) 2015.

Grouping of Bulgarian wines according to grape variety by using statistical methods

NASA Astrophysics Data System (ADS)

Milev, M.; Nikolova, Kr.; Ivanova, Ir.; Minkova, St.; Evtimov, T.; Krustev, St.

2017-12-01

68 different types of Bulgarian wines were studied in accordance with 9 optical parameters as follows: color parameters in XYZ and SIE Lab color systems, lightness, Hue angle, chroma, fluorescence intensity and emission wavelength. The main objective of this research is using hierarchical cluster analysis to evaluate the similarity and the distance between examined different types of Bulgarian wines and their grouping based on physical parameters. We have found that wines are grouped in clusters on the base of the degree of identity between them. There are two main clusters each one with two subclusters. The first one contains white wines and Sira, the second contains red wines and rose. The results from cluster analysis are presented graphically by a dendrogram. The other statistical technique used is factor analysis performed by the Method of Principal Components (PCA). The aim is to reduce the large number of variables to a few factors by grouping the correlated variables into one factor and subdividing the noncorrelated variables into different factors. Moreover the factor analysis provided the possibility to determine the parameters with the greatest influence over the distribution of samples in different clusters. In our study after the rotation of the factors with Varimax method the parameters were combined into two factors, which explain about 80 % of the total variation. The first one explains the 61.49% and correlates with color characteristics, the second one explains 18.34% from the variation and correlates with the parameters connected with fluorescence spectroscopy.

Internal and External Factors Related to Burnout among Iron and Steel Workers: A Cross-Sectional Study in Anshan, China.

PubMed

Guo, Haiqiang; Guo, Huifang; Yang, Yilong; Sun, Baozhi

2015-01-01

Burnout is a syndrome of emotional exhaustion, cynicism and reduced professional efficacy, which can result from long-term work stress. Although the burnout level is high among iron and steel workers, little is known concerning burnout among iron and steel worker. This study aimed to evaluate the burnout and to explore its associated internal and external factors in iron and steel workers. A cross-sectional survey was conducted in iron and steel workers at the Anshan iron-steel complex in Anshan, northeast China. Self-administered questionnaires were distributed to 1,600 workers, and finally 1,300 questionnaires were returned. Burnout was measured using the Chinese version of the Maslach Burnout Inventory-General Survey (MBI-GS). Effort-reward imbalance (ERI), perceived organizational support (POS), and psychological capital (PsyCap) were measured anonymously. A hierarchical regression model was applied to explore the internal and external factors associated with burnout. Mean MBI-GS scores were 13.11±8.06 for emotional exhaustion, 6.64±6.44 for cynicism, and 28.96±10.39 for professional efficacy. Hierarchical linear regression analysis showed that ERI and POS were the most powerful predictors for emotional exhaustion and cynicism, and PsyCap was the most robust predictor for high professional efficacy. Chinese iron and steel workers have a high level of burnout. Burnout might be associated with internal and external factors, including ERI, POS, and PsyCap. Further studies are recommended to develop an integrated model including both internal and external factors, to reduce the level of ERI, and improve POS and workers' PsyCap, thereby alleviating the level of burnout among iron and steel workers.

Internal and External Factors Related to Burnout among Iron and Steel Workers: A Cross-Sectional Study in Anshan, China

PubMed Central

Guo, Haiqiang; Guo, Huifang; Yang, Yilong; Sun, Baozhi

2015-01-01

Background Burnout is a syndrome of emotional exhaustion, cynicism and reduced professional efficacy, which can result from long-term work stress. Although the burnout level is high among iron and steel workers, little is known concerning burnout among iron and steel worker. This study aimed to evaluate the burnout and to explore its associated internal and external factors in iron and steel workers. Methods A cross-sectional survey was conducted in iron and steel workers at the Anshan iron-steel complex in Anshan, northeast China. Self-administered questionnaires were distributed to 1,600 workers, and finally 1,300 questionnaires were returned. Burnout was measured using the Chinese version of the Maslach Burnout Inventory-General Survey (MBI-GS). Effort-reward imbalance (ERI), perceived organizational support (POS), and psychological capital (PsyCap) were measured anonymously. A hierarchical regression model was applied to explore the internal and external factors associated with burnout. Results Mean MBI-GS scores were 13.11±8.06 for emotional exhaustion, 6.64±6.44 for cynicism, and 28.96±10.39 for professional efficacy. Hierarchical linear regression analysis showed that ERI and POS were the most powerful predictors for emotional exhaustion and cynicism, and PsyCap was the most robust predictor for high professional efficacy. Conclusions Chinese iron and steel workers have a high level of burnout. Burnout might be associated with internal and external factors, including ERI, POS, and PsyCap. Further studies are recommended to develop an integrated model including both internal and external factors, to reduce the level of ERI, and improve POS and workers’ PsyCap, thereby alleviating the level of burnout among iron and steel workers. PMID:26575031

Characterization of selected volatile organic compounds, polycyclic aromatic hydrocarbons and carbonyl compounds at a roadside monitoring station

NASA Astrophysics Data System (ADS)

Ho, K. F.; Lee, S. C.; Chiu, Gloria M. Y.

Volatile organic compounds (VOCs), PAHs and carbonyl compounds are the major toxic components in Hong Kong. Emissions from motor vehicles have been one of the primary pollution sources in the metropolitan areas throughout Hong Kong for a long time. A 1-yr monitoring program for VOCs, PAHs and carbonyl compounds had been performed at a roadside urban station at Hong Kong Polytechnic University in order to determine the variations and correlations of each selected species (VOCs, PAHs and carbonyl compounds). This study is aimed to analyze toxic volatile organic compounds (benzene, toluene, ethylbenzene and xylene), two carbonyl compounds (formaldehyde, acetaldehyde), and selective polycyclic aromatic hydrocarbons. The monitoring program started from 16 April 1999 to 30 March 2000. Ambient VOC concentrations, many of which originate from the same sources as particulate PAHs and carbonyls compounds, show significant quantities of benzene, toluene and xylenes. Correlations and multivariate analysis of selected gaseous and particulate phase organic pollutants were performed. Source identification by principle component analysis and hierarchical cluster analysis allowed the identification of four sources (factors) for the roadside monitoring station. Factor 1 represents the effect of diesel vehicle exhaust. Factor 2 shows the contribution of aromatic compounds. Factor 3 explains photochemical products—formaldehyde and acetaldehyde. Factor 4 explains the effect of gasoline vehicle exhaust.

Bayesian models: A statistical primer for ecologists

USGS Publications Warehouse

Hobbs, N. Thompson; Hooten, Mevin B.

2015-01-01

Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods—in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach.Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. This unique book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals.This primer enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management.Presents the mathematical and statistical foundations of Bayesian modeling in language accessible to non-statisticiansCovers basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and moreDeemphasizes computer coding in favor of basic principlesExplains how to write out properly factored statistical expressions representing Bayesian models

Family influences on adolescents' birth control and condom use, likelihood of sexually transmitted infections.

PubMed

Kao, Tsui-Sui Annie; Manczak, Melissa

2013-02-01

This study explored the relationships among personal factors, family structure and family function, adolescents' self-efficacy for safe sex, and sexual behaviors among sexually active adolescents. A subset sample from the first three waves of the National Longitudinal Study of Adolescent Health (Add Health) was selected for this exploratory secondary data analysis. Hierarchal and logistic regressions were conducted to explore the relationships among personal factors, family factors, and adolescents' self-reported sexually transmitted infections (STI) over time. Findings suggest that adolescents' racial/ethnic background, parents' disapproving attitudes, and family connectedness are significant predictors for birth control and condom use among adolescents. Although adolescents' personal factor and family structure play a role in their sexual behavior, positive family function significantly protects adolescents from STIs over time. School nurses can provide a vital point of care for at-risk adolescents by finding ways to encourage and incorporate parental and familial influences.

Individual and Contextual Factors Associated with Immigrant Youth Feeling Unsafe in School: A Social-Ecological Analysis.

PubMed

Hong, Jun Sung; Merrin, Gabriel J; Crosby, Shantel; Jozefowicz, Debra M Hernandez; Lee, Jeoung Min; Allen-Meares, Paula

2016-10-01

Despite the increasing proportion of immigrant youth in U.S. school districts, no studies have investigated their perceptions of their school. This study examines factors associated with perceptions of school safety among immigrant youth within individual, family, peer, and school contexts. Data were drawn from Wave II of the Children of Immigrants Longitudinal Study (n = 4288) and hierarchical logistic regression analyses were conducted. African-Americans, females, and youth with limited English proficiency were more likely to perceive their school as unsafe. Youth who reported that family cohesion was important and those who had close friends perceived their school as safe. Also, those who experienced illegal activities in school reported feeling unsafe. Assessment and intervention in schools needs to consider individual and contextual factors associated with perceptions of school safety. Additional research is needed to examine individual and contextual factors related to immigrant youths' perceptions of school.

Factors Influencing Successful Prescribing by Intern Doctors: A Qualitative Systematic Review

PubMed Central

R. Hansen, Christina; Bradley, Colin P.; Sahm, Laura J.

2016-01-01

As the majority of prescribing in hospital is undertaken by intern doctors, the aims of this systematic review were to compile the evidence of the qualitative literature on the views and experiences of intern doctors and to examine the role of the pharmacist in assisting in prescribing by interns. A systematic review of the qualitative literature was done according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement. The findings were synthesized using thematic analysis. Seven publications were included. Factors influencing prescribing behaviour were related to the environment; collaboration in medical teams; hierarchical structures; and patient and individual factors. This review confirmed that interns’ prescribing behaviour is influenced by multiple factors, and further highlighted the need for an educational intervention that supports the intern completing the prescribing task in a complex environment, and not just addresses the presumed knowledge gap(s). PMID:28970397

Factors Influencing Successful Prescribing by Intern Doctors: A Qualitative Systematic Review.

PubMed

R Hansen, Christina; Bradley, Colin P; Sahm, Laura J

2016-08-24

As the majority of prescribing in hospital is undertaken by intern doctors, the aims of this systematic review were to compile the evidence of the qualitative literature on the views and experiences of intern doctors and to examine the role of the pharmacist in assisting in prescribing by interns. A systematic review of the qualitative literature was done according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement. The findings were synthesized using thematic analysis. Seven publications were included. Factors influencing prescribing behaviour were related to the environment; collaboration in medical teams; hierarchical structures; and patient and individual factors. This review confirmed that interns' prescribing behaviour is influenced by multiple factors, and further highlighted the need for an educational intervention that supports the intern completing the prescribing task in a complex environment, and not just addresses the presumed knowledge gap(s).

Analysis of interstellar fragmentation structure based on IRAS images

NASA Technical Reports Server (NTRS)

Scalo, John M.

1989-01-01

The goal of this project was to develop new tools for the analysis of the structure of densely sampled maps of interstellar star-forming regions. A particular emphasis was on the recognition and characterization of nested hierarchical structure and fractal irregularity, and their relation to the level of star formation activity. The panoramic IRAS images provided data with the required range in spatial scale, greater than a factor of 100, and in column density, greater than a factor of 50. In order to construct a densely sampled column density map of a cloud complex which is both self-gravitating and not (yet?) stirred up much by star formation, a column density image of the Taurus region has been constructed from IRAS data. The primary drawback to using the IRAS data for this purpose is that it contains no velocity information, and the possible importance of projection effects must be kept in mind.

Computer-based analysis of microvascular alterations in a mouse model for Alzheimer's disease

NASA Astrophysics Data System (ADS)

Heinzer, Stefan; Müller, Ralph; Stampanoni, Marco; Abela, Rafael; Meyer, Eric P.; Ulmann-Schuler, Alexandra; Krucker, Thomas

2007-03-01

Vascular factors associated with Alzheimer's disease (AD) have recently gained increased attention. To investigate changes in vascular, particularly microvascular architecture, we developed a hierarchical imaging framework to obtain large-volume, high-resolution 3D images from brains of transgenic mice modeling AD. In this paper, we present imaging and data analysis methods which allow compiling unique characteristics from several hundred gigabytes of image data. Image acquisition is based on desktop micro-computed tomography (µCT) and local synchrotron-radiation µCT (SRµCT) scanning with a nominal voxel size of 16 µm and 1.4 µm, respectively. Two visualization approaches were implemented: stacks of Z-buffer projections for fast data browsing, and progressive-mesh based surface rendering for detailed 3D visualization of the large datasets. In a first step, image data was assessed visually via a Java client connected to a central database. Identified characteristics of interest were subsequently quantified using global morphometry software. To obtain even deeper insight into microvascular alterations, tree analysis software was developed providing local morphometric parameters such as number of vessel segments or vessel tortuosity. In the context of ever increasing image resolution and large datasets, computer-aided analysis has proven both powerful and indispensable. The hierarchical approach maintains the context of local phenomena, while proper visualization and morphometry provide the basis for detailed analysis of the pathology related to structure. Beyond analysis of microvascular changes in AD this framework will have significant impact considering that vascular changes are involved in other neurodegenerative diseases as well as in cancer, cardiovascular disease, asthma, and arthritis.

Hierarchical cluster analysis of progression patterns in open-angle glaucoma patients with medical treatment.

PubMed

Bae, Hyoung Won; Rho, Seungsoo; Lee, Hye Sun; Lee, Naeun; Hong, Samin; Seong, Gong Je; Sung, Kyung Rim; Kim, Chan Yun

2014-04-29

To classify medically treated open-angle glaucoma (OAG) by the pattern of progression using hierarchical cluster analysis, and to determine OAG progression characteristics by comparing clusters. Ninety-five eyes of 95 OAG patients who received medical treatment, and who had undergone visual field (VF) testing at least once per year for 5 or more years. OAG was classified into subgroups using hierarchical cluster analysis based on the following five variables: baseline mean deviation (MD), baseline visual field index (VFI), MD slope, VFI slope, and Glaucoma Progression Analysis (GPA) printout. After that, other parameters were compared between clusters. Two clusters were made after a hierarchical cluster analysis. Cluster 1 showed -4.06 ± 2.43 dB baseline MD, 92.58% ± 6.27% baseline VFI, -0.28 ± 0.38 dB per year MD slope, -0.52% ± 0.81% per year VFI slope, and all "no progression" cases in GPA printout, whereas cluster 2 showed -8.68 ± 3.81 baseline MD, 77.54 ± 12.98 baseline VFI, -0.72 ± 0.55 MD slope, -2.22 ± 1.89 VFI slope, and seven "possible" and four "likely" progression cases in GPA printout. There were no significant differences in age, sex, mean IOP, central corneal thickness, and axial length between clusters. However, cluster 2 included more high-tension glaucoma patients and used a greater number of antiglaucoma eye drops significantly compared with cluster 1. Hierarchical cluster analysis of progression patterns divided OAG into slow and fast progression groups, evidenced by assessing the parameters of glaucomatous progression in VF testing. In the fast progression group, the prevalence of high-tension glaucoma was greater and the number of antiglaucoma medications administered was increased versus the slow progression group. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

Effects of Combined Loads on the Nonlinear Response and Residual Strength of Damaged Stiffened Shells

NASA Technical Reports Server (NTRS)

Starnes, James H., Jr.; Rose, Cheryl A.; Rankin, Charles C.

1996-01-01

The results of an analytical study of the nonlinear response of stiffened fuselage shells with long cracks are presented. The shells are modeled with a hierarchical modeling strategy and analyzed with a nonlinear shell analysis code that maintains the shell in a nonlinear equilibrium state while the crack is grown. The analysis accurately accounts for global and local structural response phenomena. Results are presented for various combinations of internal pressure and mechanical loads, and the effects of crack orientation on the shell response are described. The effects of combined loading conditions and the effects of varying structural parameters on the stress-intensity factors associated with a crack are presented.

A hierarchical model for regional analysis of population change using Christmas Bird Count data, with application to the American Black Duck

USGS Publications Warehouse

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

2006-01-01

Analysis of Christmas Bird Count (CBC) data is complicated by the need to account for variation in effort on counts and to provide summaries over large geographic regions. We describe a hierarchical model for analysis of population change using CBC data that addresses these needs. The effect of effort is modeled parametrically, with parameter values varying among strata as identically distributed random effects. Year and site effects are modeled hierarchically, accommodating large regional variation in number of samples and precision of estimates. The resulting model is complex, but a Bayesian analysis can be conducted using Markov chain Monte Carlo techniques. We analyze CBC data for American Black Ducks (Anas rubripes), a species of considerable management interest that has historically been monitored using winter surveys. Over the interval 1966-2003, Black Duck populations showed distinct regional patterns of population change. The patterns shown by CBC data are similar to those shown by the Midwinter Waterfowl Inventory for the United States.

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.

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.

Application of Bayesian networks in a hierarchical structure for environmental risk assessment: a case study of the Gabric Dam, Iran.

PubMed

Malekmohammadi, Bahram; Tayebzadeh Moghadam, Negar

2018-04-13

Environmental risk assessment (ERA) is a commonly used, effective tool applied to reduce adverse effects of environmental risk factors. In this study, ERA was investigated using the Bayesian network (BN) model based on a hierarchical structure of variables in an influence diagram (ID). ID facilitated ranking of the different alternatives under uncertainty that were then used to evaluate comparisons of the different risk factors. BN was used to present a new model for ERA applicable to complicated development projects such as dam construction. The methodology was applied to the Gabric Dam, in southern Iran. The main environmental risk factors in the region, presented by the Gabric Dam, were identified based on the Delphi technique and specific features of the study area. These included the following: flood, water pollution, earthquake, changes in land use, erosion and sedimentation, effects on the population, and ecosensitivity. These risk factors were then categorized based on results from the output decision node of the BN, including expected utility values for risk factors in the decision node. ERA was performed for the Gabric Dam using the analytical hierarchy process (AHP) method to compare results of BN modeling with those of conventional methods. Results determined that a BN-based hierarchical structure to ERA present acceptable and reasonable risk assessment prioritization in proposing suitable solutions to reduce environmental risks and can be used as a powerful decision support system for evaluating environmental risks.

Analysis hierarchical model for discrete event systems

NASA Astrophysics Data System (ADS)

Ciortea, E. M.

2015-11-01

The This paper presents the hierarchical model based on discrete event network for robotic systems. Based on the hierarchical approach, Petri network is analysed as a network of the highest conceptual level and the lowest level of local control. For modelling and control of complex robotic systems using extended Petri nets. Such a system is structured, controlled and analysed in this paper by using Visual Object Net ++ package that is relatively simple and easy to use, and the results are shown as representations easy to interpret. The hierarchical structure of the robotic system is implemented on computers analysed using specialized programs. Implementation of hierarchical model discrete event systems, as a real-time operating system on a computer network connected via a serial bus is possible, where each computer is dedicated to local and Petri model of a subsystem global robotic system. Since Petri models are simplified to apply general computers, analysis, modelling, complex manufacturing systems control can be achieved using Petri nets. Discrete event systems is a pragmatic tool for modelling industrial systems. For system modelling using Petri nets because we have our system where discrete event. To highlight the auxiliary time Petri model using transport stream divided into hierarchical levels and sections are analysed successively. Proposed robotic system simulation using timed Petri, offers the opportunity to view the robotic time. Application of goods or robotic and transmission times obtained by measuring spot is obtained graphics showing the average time for transport activity, using the parameters sets of finished products. individually.

An approach based on Hierarchical Bayesian Graphical Models for measurement interpretation under uncertainty

NASA Astrophysics Data System (ADS)

Skataric, Maja; Bose, Sandip; Zeroug, Smaine; Tilke, Peter

2017-02-01

It is not uncommon in the field of non-destructive evaluation that multiple measurements encompassing a variety of modalities are available for analysis and interpretation for determining the underlying states of nature of the materials or parts being tested. Despite and sometimes due to the richness of data, significant challenges arise in the interpretation manifested as ambiguities and inconsistencies due to various uncertain factors in the physical properties (inputs), environment, measurement device properties, human errors, and the measurement data (outputs). Most of these uncertainties cannot be described by any rigorous mathematical means, and modeling of all possibilities is usually infeasible for many real time applications. In this work, we will discuss an approach based on Hierarchical Bayesian Graphical Models (HBGM) for the improved interpretation of complex (multi-dimensional) problems with parametric uncertainties that lack usable physical models. In this setting, the input space of the physical properties is specified through prior distributions based on domain knowledge and expertise, which are represented as Gaussian mixtures to model the various possible scenarios of interest for non-destructive testing applications. Forward models are then used offline to generate the expected distribution of the proposed measurements which are used to train a hierarchical Bayesian network. In Bayesian analysis, all model parameters are treated as random variables, and inference of the parameters is made on the basis of posterior distribution given the observed data. Learned parameters of the posterior distribution obtained after the training can therefore be used to build an efficient classifier for differentiating new observed data in real time on the basis of pre-trained models. We will illustrate the implementation of the HBGM approach to ultrasonic measurements used for cement evaluation of cased wells in the oil industry.

Filling gaps in large ecological databases: consequences for the study of global-scale plant functional trait patterns

NASA Astrophysics Data System (ADS)

Schrodt, Franziska; Shan, Hanhuai; Fazayeli, Farideh; Karpatne, Anuj; Kattge, Jens; Banerjee, Arindam; Reichstein, Markus; Reich, Peter

2013-04-01

With the advent of remotely sensed data and coordinated efforts to create global databases, the ecological community has progressively become more data-intensive. However, in contrast to other disciplines, statistical ways of handling these large data sets, especially the gaps which are inherent to them, are lacking. Widely used theoretical approaches, for example model averaging based on Akaike's information criterion (AIC), are sensitive to missing values. Yet, the most common way of handling sparse matrices - the deletion of cases with missing data (complete case analysis) - is known to severely reduce statistical power as well as inducing biased parameter estimates. In order to address these issues, we present novel approaches to gap filling in large ecological data sets using matrix factorization techniques. Factorization based matrix completion was developed in a recommender system context and has since been widely used to impute missing data in fields outside the ecological community. Here, we evaluate the effectiveness of probabilistic matrix factorization techniques for imputing missing data in ecological matrices using two imputation techniques. Hierarchical Probabilistic Matrix Factorization (HPMF) effectively incorporates hierarchical phylogenetic information (phylogenetic group, family, genus, species and individual plant) into the trait imputation. Advanced Hierarchical Probabilistic Matrix Factorization (aHPMF) on the other hand includes climate and soil information into the matrix factorization by regressing the environmental variables against residuals of the HPMF. One unique opportunity opened up by aHPMF is out-of-sample prediction, where traits can be predicted for specific species at locations different to those sampled in the past. This has potentially far-reaching consequences for the study of global-scale plant functional trait patterns. We test the accuracy and effectiveness of HPMF and aHPMF in filling sparse matrices, using the TRY database of plant functional traits (http://www.try-db.org). TRY is one of the largest global compilations of plant trait databases (750 traits of 1 million plants), encompassing data on morphological, anatomical, biochemical, phenological and physiological features of plants. However, despite of unprecedented coverage, the TRY database is still very sparse, severely limiting joint trait analyses. Plant traits are the key to understanding how plants as primary producers adjust to changes in environmental conditions and in turn influence them. Forming the basis for Dynamic Global Vegetation Models (DGVMs), plant traits are also fundamental in global change studies for predicting future ecosystem changes. It is thus imperative that missing data is imputed in as accurate and precise a way as possible. In this study, we show the advantages and disadvantages of applying probabilistic matrix factorization techniques in incorporating hierarchical and environmental information for the prediction of missing plant traits as compared to conventional imputation techniques such as the complete case and mean approaches. We will discuss the implications of using gap-filled data for global-scale studies of plant functional trait - environment relationship as opposed to the above-mentioned conventional techniques, using examples of out-of-sample predictions of foliar Nitrogen across several species' ranges and biomes.

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

PubMed Central

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

2018-01-01

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

Hierarchical Modeling and Robust Synthesis for the Preliminary Design of Large Scale Complex Systems

NASA Technical Reports Server (NTRS)

Koch, Patrick N.

1997-01-01

Large-scale complex systems are characterized by multiple interacting subsystems and the analysis of multiple disciplines. The design and development of such systems inevitably requires the resolution of multiple conflicting objectives. The size of complex systems, however, prohibits the development of comprehensive system models, and thus these systems must be partitioned into their constituent parts. Because simultaneous solution of individual subsystem models is often not manageable iteration is inevitable and often excessive. In this dissertation these issues are addressed through the development of a method for hierarchical robust preliminary design exploration to facilitate concurrent system and subsystem design exploration, for the concurrent generation of robust system and subsystem specifications for the preliminary design of multi-level, multi-objective, large-scale complex systems. This method is developed through the integration and expansion of current design techniques: Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis; Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration; and Noise modeling techniques for implementing robust preliminary design when approximate models are employed. Hierarchical partitioning and modeling techniques including intermediate responses, linking variables, and compatibility constraints are incorporated within a hierarchical compromise decision support problem formulation for synthesizing subproblem solutions for a partitioned system. Experimentation and approximation techniques are employed for concurrent investigations and modeling of partitioned subproblems. A modified composite experiment is introduced for fitting better predictive models across the ranges of the factors, and an approach for constructing partitioned response surfaces is developed to reduce the computational expense of experimentation for fitting models in a large number of factors. Noise modeling techniques are compared and recommendations are offered for the implementation of robust design when approximate models are sought. These techniques, approaches, and recommendations are incorporated within the method developed for hierarchical robust preliminary design exploration. This method as well as the associated approaches are illustrated through their application to the preliminary design of a commercial turbofan turbine propulsion system. The case study is developed in collaboration with Allison Engine Company, Rolls Royce Aerospace, and is based on the Allison AE3007 existing engine designed for midsize commercial, regional business jets. For this case study, the turbofan system-level problem is partitioned into engine cycle design and configuration design and a compressor modules integrated for more detailed subsystem-level design exploration, improving system evaluation. The fan and low pressure turbine subsystems are also modeled, but in less detail. Given the defined partitioning, these subproblems are investigated independently and concurrently, and response surface models are constructed to approximate the responses of each. These response models are then incorporated within a commercial turbofan hierarchical compromise decision support problem formulation. Five design scenarios are investigated, and robust solutions are identified. The method and solutions identified are verified by comparison with the AE3007 engine. The solutions obtained are similar to the AE3007 cycle and configuration, but are better with respect to many of the requirements.

Constructing accountability in inter-organisational collaboration: the implications of a narrow performance-based focus.

PubMed

Andersson, Johanna; Wikström, Ewa

2014-01-01

The purpose of this paper is to analyse how accounts of collaboration practice were made and used to construct accountability in the empirical context of coordination associations, a Swedish form of collaboration between four authorities in health and social care. They feature pooled budgets, joint leadership and joint reporting systems, intended to facilitate both collaboration and (shared) accountability. Empirical data were collected in field observations in local, regional and national settings. In addition, the study is based on analysis of local association documents such as evaluations and annual reports, and analysis of national agency reports. Accountability is constructed hierarchically with a narrow focus on performance, and horizontal (shared) accountability as well as outcomes are de-emphasised. Through this narrow construction of accountability the coordination associations are re-created as hierarchical and accountability is delegated rather than shared. Features such as pooled budgets, joint leadership and joint reporting systems can support collaboration but do not necessarily translate into shared accountability if accountability is interpreted and constructed hierarchically. When practice conforms to what is counted and accounted for, using the hierarchical and narrow construction of accountability, the result may be that the associations become an additional authority. That would increase rather than decrease fragmentation in the field. This research derives from first-hand observations of actor-to-actor episodes complemented with the analysis of documents and reports. It provides critical analysis of the construction and evaluation of accounts and accountability related to practice and performance in collaboration. The main contribution is the finding that despite the conditions intended to facilitate inter-organisational collaboration and horizontal accountability, the hierarchical accountability persisted.

Oak Ridge Computerized Hierarchical Information System (ORCHIS) status report, July 1973

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

Brooks, A.A.

1974-01-01

This report summarizes the concepts, software, and contents of the Oak Ridge Computerized Hierarchical Information System. This data analysis and text processing system was developed as an integrated, comprehensive information processing capability to meet the needs of an on-going multidisciplinary research and development organization. (auth)

Hierarchical Network Models for Education Research: Hierarchical Latent Space Models

ERIC Educational Resources Information Center

Sweet, Tracy M.; Thomas, Andrew C.; Junker, Brian W.

2013-01-01

Intervention studies in school systems are sometimes aimed not at changing curriculum or classroom technique, but rather at changing the way that teachers, teaching coaches, and administrators in schools work with one another--in short, changing the professional social networks of educators. Current methods of social network analysis are…

A Hierarchical Analysis of Bridge Decision Makers; the Role of New Technology Adoption in the Timber Bridge Market: Special Project Fiscal Year 1992

DOT National Transportation Integrated Search

1995-08-01

Bridge design engineers and local highway officials make bridge replacement decsions across the U.S. The Analytical Hierarchical Process was used to characterize the bridge material selection decisions of these individuals. State Departments of Trans...

Multilevel Analysis of Structural Equation Models via the EM Algorithm.

ERIC Educational Resources Information Center

Jo, See-Heyon

The question of how to analyze unbalanced hierarchical data generated from structural equation models has been a common problem for researchers and analysts. Among difficulties plaguing statistical modeling are estimation bias due to measurement error and the estimation of the effects of the individual's hierarchical social milieu. This paper…

[Factors that influence sexual intercourse among middle school students: using data from the 8th (2012) Korea Youth Risk Behavior Web-based Survey].

PubMed

Gwon, Seok Hyun; Lee, Chung Yul

2015-02-01

The purpose of this study was to investigate factors that influence sexual intercourse among middle school students in South Korea. Using statistics from the 8th (2012) Korea Youth Risk Behavior Web-based Survey, hierarchical logistic regression analysis was conducted. The study sample comprised 37,297 middle school students aged primarily 12 to 15. The significant predictors of sexual intercourse were grade, ever smoking, ever drinking, habitual or purposeful drug use, economic status, weekly allowance, cohabitation with family, and type of school. The results suggest that intensified sex education is needed not only in the 1st grade of middle school, but also in the upper grades of elementary school. Sexual health interventions for high-risk groups may be needed, given the factors predicting sexual intercourse.

High- and low-level hierarchical classification algorithm based on source separation process

NASA Astrophysics Data System (ADS)

Loghmari, Mohamed Anis; Karray, Emna; Naceur, Mohamed Saber

2016-10-01

High-dimensional data applications have earned great attention in recent years. We focus on remote sensing data analysis on high-dimensional space like hyperspectral data. From a methodological viewpoint, remote sensing data analysis is not a trivial task. Its complexity is caused by many factors, such as large spectral or spatial variability as well as the curse of dimensionality. The latter describes the problem of data sparseness. In this particular ill-posed problem, a reliable classification approach requires appropriate modeling of the classification process. The proposed approach is based on a hierarchical clustering algorithm in order to deal with remote sensing data in high-dimensional space. Indeed, one obvious method to perform dimensionality reduction is to use the independent component analysis process as a preprocessing step. The first particularity of our method is the special structure of its cluster tree. Most of the hierarchical algorithms associate leaves to individual clusters, and start from a large number of individual classes equal to the number of pixels; however, in our approach, leaves are associated with the most relevant sources which are represented according to mutually independent axes to specifically represent some land covers associated with a limited number of clusters. These sources contribute to the refinement of the clustering by providing complementary rather than redundant information. The second particularity of our approach is that at each level of the cluster tree, we combine both a high-level divisive clustering and a low-level agglomerative clustering. This approach reduces the computational cost since the high-level divisive clustering is controlled by a simple Boolean operator, and optimizes the clustering results since the low-level agglomerative clustering is guided by the most relevant independent sources. Then at each new step we obtain a new finer partition that will participate in the clustering process to enhance semantic capabilities and give good identification rates.

MC EMiNEM Maps the Interaction Landscape of the Mediator

PubMed Central

Niederberger, Theresa; Etzold, Stefanie; Lidschreiber, Michael; Maier, Kerstin C.; Martin, Dietmar E.; Fröhlich, Holger; Cramer, Patrick; Tresch, Achim

2012-01-01

The Mediator is a highly conserved, large multiprotein complex that is involved essentially in the regulation of eukaryotic mRNA transcription. It acts as a general transcription factor by integrating regulatory signals from gene-specific activators or repressors to the RNA Polymerase II. The internal network of interactions between Mediator subunits that conveys these signals is largely unknown. Here, we introduce MC EMiNEM, a novel method for the retrieval of functional dependencies between proteins that have pleiotropic effects on mRNA transcription. MC EMiNEM is based on Nested Effects Models (NEMs), a class of probabilistic graphical models that extends the idea of hierarchical clustering. It combines mode-hopping Monte Carlo (MC) sampling with an Expectation-Maximization (EM) algorithm for NEMs to increase sensitivity compared to existing methods. A meta-analysis of four Mediator perturbation studies in Saccharomyces cerevisiae, three of which are unpublished, provides new insight into the Mediator signaling network. In addition to the known modular organization of the Mediator subunits, MC EMiNEM reveals a hierarchical ordering of its internal information flow, which is putatively transmitted through structural changes within the complex. We identify the N-terminus of Med7 as a peripheral entity, entailing only local structural changes upon perturbation, while the C-terminus of Med7 and Med19 appear to play a central role. MC EMiNEM associates Mediator subunits to most directly affected genes, which, in conjunction with gene set enrichment analysis, allows us to construct an interaction map of Mediator subunits and transcription factors. PMID:22737066

Evaluations of the psychometric properties of the Recovery-Stress Questionnaire for Athletes among a sample of young French table tennis players.

PubMed

Martinent, Guillaume; Decret, Jean-Claude; Isoard-Gautheur, Sandrine; Filaire, Edith; Ferrand, Claude

2014-04-01

This study used confirmatory factor analyses (CFAs) among a sample of young French table tennis players to test: (a) original 19-factor structure, (b) 14-factor structure recently suggested in literature, and (c) hierarchical factor structure of the Recovery-Stress Questionnaire for Athletes (RESTQ-Sport). 148 table tennis players completed the RESTQ-Sport and other self-report questionnaires between one to five occasions with a delay of 1 mo. between each completion. Results of CFAs showed: (a) evidence for relative superiority of the original model in comparison to an alternative model recently proposed in literature, (b) a good fit of the data for the 67-item 17-factor model of the RESTQ-Sport, and (c) an acceptable fit of the data for the hierarchical model of the RESTQ-Sport. Correlations between RESTQ-Sport subscales and burnout and motivation subscales also provided evidence for criterion-related validity of the RESTQ-Sport. This study provided support for reliability and validity of the RESTQ-Sport.

Credit networks and systemic risk of Chinese local financing platforms: Too central or too big to fail?. -based on different credit correlations using hierarchical methods

NASA Astrophysics Data System (ADS)

He, Fang; Chen, Xi

2016-11-01

The accelerating accumulation and risk concentration of Chinese local financing platforms debts have attracted wide attention throughout the world. Due to the network of financial exposures among institutions, the failure of several platforms or regions of systemic importance will probably trigger systemic risk and destabilize the financial system. However, the complex network of credit relationships in Chinese local financing platforms at the state level remains unknown. To fill this gap, we presented the first complex networks and hierarchical cluster analysis of the credit market of Chinese local financing platforms using the ;bottom up; method from firm-level data. Based on balance-sheet channel, we analyzed the topology and taxonomy by applying the analysis paradigm of subdominant ultra-metric space to an empirical data in 2013. It is remarked that we chose to extract the network of co-financed financing platforms in order to evaluate the effect of risk contagion from platforms to bank system. We used the new credit similarity measure by combining the factor of connectivity and size, to extract minimal spanning trees (MSTs) and hierarchical trees (HTs). We found that: (1) the degree distributions of credit correlation backbone structure of Chinese local financing platforms are fat tailed, and the structure is unstable with respect to targeted failures; (2) the backbone is highly hierarchical, and largely explained by the geographic region; (3) the credit correlation backbone structure based on connectivity and size is significantly heterogeneous; (4) key platforms and regions of systemic importance, and contagion path of systemic risk are obtained, which are contributed to preventing systemic risk and regional risk of Chinese local financing platforms and preserving financial stability under the framework of macro prudential supervision. Our approach of credit similarity measure provides a means of recognizing ;systemically important; institutions and regions for a targeted policy with risk minimization which gives a flexible and comprehensive consideration to both aspects of ;too big to fail; and ;too central to fail;.

Au functionalized ZnO rose-like hierarchical structures and their enhanced NO2 sensing performance

NASA Astrophysics Data System (ADS)

Shingange, K.; Swart, H. C.; Mhlongo, G. H.

2018-04-01

Herein, we present ZnO rose-like hierarchical nanostructures employed as support to Au nanoparticles to produce Au functionalized three dimensional (3D) ZnO hierarchical nanostructures (Au/ZnO) for NO2 detection using a microwave-assisted method. Comparative analysis of NO2 sensing performance between the pristine ZnO and Au/ZnO rose-like structures at 300 °C revealed improved NO2 response and rapid response-recovery times with Au incorporation owing to a combination of high surface accessibility induced by hierarchical nanostructure design and catalytic activity of the small Au nanoparticles. Structural and optical analyses acquired from X-ray diffraction, scanning electron microscopy, transmission electron microscope and photoluminescence spectroscopy were also performed.

Aircraft optimization by a system approach: Achievements and trends

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, Jaroslaw

1992-01-01

Recently emerging methodology for optimal design of aircraft treated as a system of interacting physical phenomena and parts is examined. The methodology is found to coalesce into methods for hierarchic, non-hierarchic, and hybrid systems all dependent on sensitivity analysis. A separate category of methods has also evolved independent of sensitivity analysis, hence suitable for discrete problems. References and numerical applications are cited. Massively parallel computer processing is seen as enabling technology for practical implementation of the methodology.

Fabrication of Advanced Thermoelectric Materials by Hierarchical Nanovoid Generation

NASA Technical Reports Server (NTRS)

Park, Yeonjoon (Inventor); Elliott, James R. (Inventor); Stoakley, Diane M. (Inventor); Chu, Sang-Hyon (Inventor); King, Glen C. (Inventor); Kim, Jae-Woo (Inventor); Choi, Sang Hyouk (Inventor); Lillehei, Peter T. (Inventor)

2011-01-01

A novel method to prepare an advanced thermoelectric material has hierarchical structures embedded with nanometer-sized voids which are key to enhancement of the thermoelectric performance. Solution-based thin film deposition technique enables preparation of stable film of thermoelectric material and void generator (voigen). A subsequent thermal process creates hierarchical nanovoid structure inside the thermoelectric material. Potential application areas of this advanced thermoelectric material with nanovoid structure are commercial applications (electronics cooling), medical and scientific applications (biological analysis device, medical imaging systems), telecommunications, and defense and military applications (night vision equipments).

Hierarchical Parallelism in Finite Difference Analysis of Heat Conduction

NASA Technical Reports Server (NTRS)

Padovan, Joseph; Krishna, Lala; Gute, Douglas

1997-01-01

Based on the concept of hierarchical parallelism, this research effort resulted in highly efficient parallel solution strategies for very large scale heat conduction problems. Overall, the method of hierarchical parallelism involves the partitioning of thermal models into several substructured levels wherein an optimal balance into various associated bandwidths is achieved. The details are described in this report. Overall, the report is organized into two parts. Part 1 describes the parallel modelling methodology and associated multilevel direct, iterative and mixed solution schemes. Part 2 establishes both the formal and computational properties of the scheme.

Factor analysis and Mokken scaling of the Organizational Commitment Questionnaire in nurses.

PubMed

Al-Yami, M; Galdas, P; Watson, R

2018-03-22

To generate an Arabic version of the Organizational Commitment Questionnaire that would be easily understood by Arabic speakers and would be sensitive to Arabic culture. The nursing workforce in Saudi Arabia is undergoing a process of Saudization but there is a need to understand the factors that will help to retain this workforce. No organizational commitment tools exist in Arabic that are specifically designed for health organizations. An Arabic version of the organizational commitment tool could aid Arabic speaking employers to understand their employees' perceptions of their organizations. Translation and back-translation followed by factor analysis (principal components analysis and confirmatory factor analysis) to test the factorial validity and item response theory (Mokken scaling). A two-factor structure was obtained for the Organizational Commitment Questionnaire comprising Factor 1: Value commitment; and Factor 2: Commitment to stay with acceptable reliability measured by internal consistency. A Mokken scale was obtained including items from both factors showing a hierarchy of items running from commitment to the organization and commitment to self. This study shows that the Arabic version of the OCQ retained the established two-factor structure of the original English-language version. Although the two factors - 'value commitment' and 'commitment to stay' - repudiate the original developers' single factor claim. A useful insight into the structure of the Organizational Commitment Questionnaire has been obtained with the novel addition of a hierarchical scale. The Organizational Commitment Questionnaire is now ready to be used with nurses in the Arab speaking world and could be used a tool to measure the contemporary commitment of nursing employees and in future interventions aimed at increasing commitment and retention of valuable nursing staff. © 2018 International Council of Nurses.

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.

Multiscale factors affecting human attitudes toward snow leopards and wolves.

PubMed

Suryawanshi, Kulbhushansingh R; Bhatia, Saloni; Bhatnagar, Yash Veer; Redpath, Stephen; Mishra, Charudutt

2014-12-01

The threat posed by large carnivores to livestock and humans makes peaceful coexistence between them difficult. Effective implementation of conservation laws and policies depends on the attitudes of local residents toward the target species. There are many known correlates of human attitudes toward carnivores, but they have only been assessed at the scale of the individual. Because human societies are organized hierarchically, attitudes are presumably influenced by different factors at different scales of social organization, but this scale dependence has not been examined. We used structured interview surveys to quantitatively assess the attitudes of a Buddhist pastoral community toward snow leopards (Panthera uncia) and wolves (Canis lupus). We interviewed 381 individuals from 24 villages within 6 study sites across the high-elevation Spiti Valley in the Indian Trans-Himalaya. We gathered information on key explanatory variables that together captured variation in individual and village-level socioeconomic factors. We used hierarchical linear models to examine how the effect of these factors on human attitudes changed with the scale of analysis from the individual to the community. Factors significant at the individual level were gender, education, and age of the respondent (for wolves and snow leopards), number of income sources in the family (wolves), agricultural production, and large-bodied livestock holdings (snow leopards). At the community level, the significant factors included the number of smaller-bodied herded livestock killed by wolves and mean agricultural production (wolves) and village size and large livestock holdings (snow leopards). Our results show that scaling up from the individual to higher levels of social organization can highlight important factors that influence attitudes of people toward wildlife and toward formal conservation efforts in general. Such scale-specific information can help managers apply conservation measures at appropriate scales. Our results reiterate the need for conflict management programs to be multipronged. © 2014 Society for Conservation Biology.

Predicting Resilience in Sexually Abused Adolescents

ERIC Educational Resources Information Center

Williams, Javonda; Nelson-Gardell, Debra

2012-01-01

This research examined factors that predicted resilience in sexually abused adolescents. Using Bronfenbrenner's Process-Person-Context-Time (PPCT) ecological model, this study considered the proximal and distal factors that would contribute to adolescents' reactions to sexual victimization. This correlational study used hierarchical regression…

Controllable fabrication of large-scale hierarchical silver nanostructures for long-term stable and ultrasensitive SERS substrates

NASA Astrophysics Data System (ADS)

Wu, Jing; Fang, Jinghuai; Cheng, Mingfei; Gong, Xiao

2016-09-01

In this work, we aim to prepare effective and long-term stable hierarchical silver nanostructures serving as surface-enhanced Raman scattering (SERS) substrates simply via displacement reaction on Aluminum foils. In our experiments, Hexadecyltrimethylammonium bromide (CTAB) is used as cationic surfactant to control the velocity of displacement reaction as well as the hierarchical morphology of the resultant. We find that the volume ratio of CTAB to AgNO3 plays a dominant role in regulating the hierarchical structures besides the influence of displacement reaction time. These as-prepared hierarchical morphologies demonstrate excellent SERS sensitivity, structural stability and reproducibility with low values of relative standard deviation less than 20 %. The high SERS analytical enhancement factor of ~6.7 × 108 is achieved even at the concentration of Crystal Violet (CV) as low as 10-7 M, which is sufficient for single-molecule detection. The detection limit of CV is 10-9 M in this study. We believe that this simple and rapid approach integrating advantages of low-cost production and high reproducibility would be a promising way to facilitate routine SERS detection and will get wide applications in chemical synthesis.

Metastability on the hierarchical lattice

NASA Astrophysics Data System (ADS)

den Hollander, Frank; Jovanovski, Oliver

2017-07-01

We study metastability for Glauber spin-flip dynamics on the N-dimensional hierarchical lattice with n hierarchical levels. Each vertex carries an Ising spin that can take the values -1 or +1 . Spins interact with an external magnetic field h>0 . Pairs of spins interact with each other according to a ferromagnetic pair potential J=\\{J_i\\}i=1n , where J_i>0 is the strength of the interaction between spins at hierarchical distance i. Spins flip according to a Metropolis dynamics at inverse temperature β. In the limit as β\\to∞ , we analyse the crossover time from the metastable state \\boxminus (all spins -1 ) to the stable state \\boxplus (all spins +1 ). Under the assumption that J is non-increasing, we identify the mean transition time up to a multiplicative factor 1+o_β(1) . On the scale of its mean, the transition time is exponentially distributed. We also identify the set of configurations representing the gate for the transition. For the special case where Ji = \\tilde{J}/Ni , 1 ≤slant i ≤slant n , with \\tilde{J}>0 the relevant formulas simplify considerably. Also the hierarchical mean-field limit N\\to∞ can be analysed in detail.

Hierarchical Nanostructures of Metal-Organic Frameworks Applied in Gas Separating ZIF-8-on-ZIF-67 Membranes.

PubMed

Knebel, Alexander; Wulfert-Holzmann, Paul; Friebe, Sebastian; Pavel, Janet; Strauß, Ina; Mundstock, Alexander; Steinbach, Frank; Caro, Jürgen

2018-04-17

Membranes from metal-organic frameworks (MOFs) are highly interesting for industrial gas separation applications. Strongly improved performances for carbon capture and H 2 purification tasks in MOF membranes are obtained by using highly reproducable and very accuratly, hierarchically grown ZIF-8-on-ZIF-67 (ZIF-8@ZIF-67) nanostructures. To forgo hardly controllable solvothermal synthesis, particles and layers are prepared by self-assembling methods. It was possible for the first time to confirm ZIF-8-on-ZIF-67 membrane growth on rough and porous ceramic supports using the layer-by-layer deposition. Additionally, hierarchical particles are made in a fast RT synthesis with high monodispersity. Characterization of the hierarchical and epitaxial grown layers and particles is performed by SEM, TEM, EDXM and gas permeation. The system ZIF-8@ZIF-67 shows a nearly doubled H 2 /CO 2 separation factor, regardless of whether neat membrane or mixed-matrix-membrane in comparison to other MOF materials. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Social Influence on Information Technology Adoption and Sustained Use in Healthcare: A Hierarchical Bayesian Learning Method Analysis

ERIC Educational Resources Information Center

Hao, Haijing

2013-01-01

Information technology adoption and diffusion is currently a significant challenge in the healthcare delivery setting. This thesis includes three papers that explore social influence on information technology adoption and sustained use in the healthcare delivery environment using conventional regression models and novel hierarchical Bayesian…

A Comparison of Techniques for Handling and Assessing the Influence of Mobility on Student Achievement

ERIC Educational Resources Information Center

Smith, Lindsey J. Wolff; Beretvas, S. Natasha

2017-01-01

Conventional multilevel modeling works well with purely hierarchical data; however, pure hierarchies rarely exist in real datasets. Applied researchers employ ad hoc procedures to create purely hierarchical data. For example, applied educational researchers either delete mobile participants' data from the analysis or identify the student only with…

An Analysis of Prospective Teachers' Knowledge for Constructing Concept Maps

ERIC Educational Resources Information Center

Subramaniam, Karthigeyan; Esprívalo Harrell, Pamela

2015-01-01

Background: Literature contends that a teacher's knowledge of concept map-based tasks influence how their students perceive the task and execute the creation of acceptable concept maps. Teachers who are skilled concept mappers are able to (1) understand and apply the operational terms to construct a hierarchical/non-hierarchical concept map; (2)…

Wavelet-based hierarchical surface approximation from height fields

Treesearch

Sang-Mook Lee; A. Lynn Abbott; Daniel L. Schmoldt

2004-01-01

This paper presents a novel hierarchical approach to triangular mesh generation from height fields. A wavelet-based multiresolution analysis technique is used to estimate local shape information at different levels of resolution. Using predefined templates at the coarsest level, the method constructs an initial triangulation in which underlying object shapes are well...

Hierarchical Multiple Regression in Counseling Research: Common Problems and Possible Remedies.

ERIC Educational Resources Information Center

Petrocelli, John V.

2003-01-01

A brief content analysis was conducted on the use of hierarchical regression in counseling research published in the "Journal of Counseling Psychology" and the "Journal of Counseling & Development" during the years 1997-2001. Common problems are cited and possible remedies are described. (Contains 43 references and 3 tables.) (Author)

Hierarchical organization of functional connectivity in the mouse brain: a complex network approach.

PubMed

Bardella, Giampiero; Bifone, Angelo; Gabrielli, Andrea; Gozzi, Alessandro; Squartini, Tiziano

2016-08-18

This paper represents a contribution to the study of the brain functional connectivity from the perspective of complex networks theory. More specifically, we apply graph theoretical analyses to provide evidence of the modular structure of the mouse brain and to shed light on its hierarchical organization. We propose a novel percolation analysis and we apply our approach to the analysis of a resting-state functional MRI data set from 41 mice. This approach reveals a robust hierarchical structure of modules persistent across different subjects. Importantly, we test this approach against a statistical benchmark (or null model) which constrains only the distributions of empirical correlations. Our results unambiguously show that the hierarchical character of the mouse brain modular structure is not trivially encoded into this lower-order constraint. Finally, we investigate the modular structure of the mouse brain by computing the Minimal Spanning Forest, a technique that identifies subnetworks characterized by the strongest internal correlations. This approach represents a faster alternative to other community detection methods and provides a means to rank modules on the basis of the strength of their internal edges.

Hierarchical organization of functional connectivity in the mouse brain: a complex network approach

NASA Astrophysics Data System (ADS)

Bardella, Giampiero; Bifone, Angelo; Gabrielli, Andrea; Gozzi, Alessandro; Squartini, Tiziano

2016-08-01

This paper represents a contribution to the study of the brain functional connectivity from the perspective of complex networks theory. More specifically, we apply graph theoretical analyses to provide evidence of the modular structure of the mouse brain and to shed light on its hierarchical organization. We propose a novel percolation analysis and we apply our approach to the analysis of a resting-state functional MRI data set from 41 mice. This approach reveals a robust hierarchical structure of modules persistent across different subjects. Importantly, we test this approach against a statistical benchmark (or null model) which constrains only the distributions of empirical correlations. Our results unambiguously show that the hierarchical character of the mouse brain modular structure is not trivially encoded into this lower-order constraint. Finally, we investigate the modular structure of the mouse brain by computing the Minimal Spanning Forest, a technique that identifies subnetworks characterized by the strongest internal correlations. This approach represents a faster alternative to other community detection methods and provides a means to rank modules on the basis of the strength of their internal edges.

Resolution of Singularities Introduced by Hierarchical Structure in Deep Neural Networks.

PubMed

Nitta, Tohru

2017-10-01

We present a theoretical analysis of singular points of artificial deep neural networks, resulting in providing deep neural network models having no critical points introduced by a hierarchical structure. It is considered that such deep neural network models have good nature for gradient-based optimization. First, we show that there exist a large number of critical points introduced by a hierarchical structure in deep neural networks as straight lines, depending on the number of hidden layers and the number of hidden neurons. Second, we derive a sufficient condition for deep neural networks having no critical points introduced by a hierarchical structure, which can be applied to general deep neural networks. It is also shown that the existence of critical points introduced by a hierarchical structure is determined by the rank and the regularity of weight matrices for a specific class of deep neural networks. Finally, two kinds of implementation methods of the sufficient conditions to have no critical points are provided. One is a learning algorithm that can avoid critical points introduced by the hierarchical structure during learning (called avoidant learning algorithm). The other is a neural network that does not have some critical points introduced by the hierarchical structure as an inherent property (called avoidant neural network).

Hierarchical Kohonenen net for anomaly detection in network security.

PubMed

Sarasamma, Suseela T; Zhu, Qiuming A; Huff, Julie

2005-04-01

A novel multilevel hierarchical Kohonen Net (K-Map) for an intrusion detection system is presented. Each level of the hierarchical map is modeled as a simple winner-take-all K-Map. One significant advantage of this multilevel hierarchical K-Map is its computational efficiency. Unlike other statistical anomaly detection methods such as nearest neighbor approach, K-means clustering or probabilistic analysis that employ distance computation in the feature space to identify the outliers, our approach does not involve costly point-to-point computation in organizing the data into clusters. Another advantage is the reduced network size. We use the classification capability of the K-Map on selected dimensions of data set in detecting anomalies. Randomly selected subsets that contain both attacks and normal records from the KDD Cup 1999 benchmark data are used to train the hierarchical net. We use a confidence measure to label the clusters. Then we use the test set from the same KDD Cup 1999 benchmark to test the hierarchical net. We show that a hierarchical K-Map in which each layer operates on a small subset of the feature space is superior to a single-layer K-Map operating on the whole feature space in detecting a variety of attacks in terms of detection rate as well as false positive rate.

Psychometric structure of the Chinese Multiethnic Adolescent Cultural Identity Questionnaire.

PubMed

Hu, Fa-Wen; Wang, Pei; Li, Li-Ju

2014-12-01

In this study, we used the Chinese Multiethnic Adolescent Cultural Identity Questionnaire (CMACIQ) and collected valid data from 1,036 participants to systematically examine the mental model of cultural identity in Chinese multiethnic adolescents. Exploratory factor analysis and structural equation modeling were performed on the data to discover the factor structure and dimensions of cultural identity. The psychometric properties of the scale were rigorously validated in 2,744 new multiethnic participants from 5 native ethnic groups in Yunnan province in China. The results indicated that CMACIQ had reasonable metric properties and good fit indices. The hierarchical model of cultural identity consisted of 2 second-order factors, Ethnic Cultural Identity and Mainstream Cultural Identity in School. The first higher order factor was composed of preference for ethnic things, ethnic acceptance, religious belief, and ethnic convention, while the second comprised 2 first-order factors, Social Norms and Dominant Culture. The potential application and limitations of CMACIQ are discussed. (c) 2014 APA, all rights reserved.

Predictors of health-related quality of life among low-income midlife women.

PubMed

Ham, Ok Kyung

2011-02-01

The purpose of this study was to determine whether any of the sociodemographic, biomedical, psychosocial, and medical-care factors independently predict health-related quality of life (HRQoL) among low-income women. Cross-sectional data were used to predict factors that determine HRQoL. A survey was conducted targeting a convenience sample of 200 midlife women. Blood samples were drawn from all participants, who also received a physical examination. Hierarchical multiple regression analysis was used to test the independent effects of each factor. The study found that sociodemographic and psychosocial factors were independently associated with HRQoL. Compared to married women, widowed or divorced women had significantly lower HRQoL, whereas those with higher levels of stress perception and those not performing regular exercise had significantly lower HRQoL (p < .01). The full model accounted for 44.7% of the variance in HRQoL. The HRQoL of low-income midlife women was associated with multiple factors, with stress perception exerting the major influence.

The influence of mindfulness, self-compassion, psychological flexibility, and posttraumatic stress disorder on disability and quality of life over time in war veterans.

PubMed

Meyer, Eric C; Frankfurt, Sheila B; Kimbrel, Nathan A; DeBeer, Bryann B; Gulliver, Suzy B; Morrisette, Sandra B

2018-07-01

Posttraumatic stress disorder (PTSD) strongly predicts greater disability and lower quality of life (QOL). Mindfulness-based and other third-wave behavior therapy interventions improve well-being by enhancing mindfulness, self-compassion, and psychological flexibility. We hypothesized that these mechanisms of therapeutic change would comprise a single latent factor that would predict disability and QOL after accounting for PTSD symptom severity. Iraq and Afghanistan war veterans (N = 117) completed a study of predictors of successful reintegration. Principal axis factor analysis tested whether mindfulness, self-compassion, and psychological flexibility comprised a single latent factor. Hierarchical regression tested whether this factor predicted disability and QOL 1 year later. Mindfulness, self-compassion, and psychological flexibility comprised a single factor that predicted disability and QOL after accounting for PTSD symptom severity. PTSD symptoms remained a significant predictor of disability but not QOL. Targeting these mechanisms may help veterans achieve functional recovery, even in the presence of PTSD symptoms. © 2018 Wiley Periodicals, Inc.

Psychometric properties of the Belgian coach version of the coach-athlete relationship questionnaire (CART-Q).

PubMed

Balduck, A-L; Jowett, S

2010-10-01

The study examined the psychometric properties of the Belgian coach version of the Coach-Athlete Relationship Questionnaire (CART-Q). The questionnaire includes three dimensions (Closeness, Commitment, and Complementarity) in a model that intends to measure the quality of the coach-athlete relationship. Belgian coaches (n=144) of athletes who performed at various competition levels in such sports as football, basketball, and volleyball responded to the CART-Q and to the Leadership Scale for Sport (LSS). A confirmatory factor analysis proved to be slightly more satisfactory for a three-order factor model, compared with a hierarchical first-order factor model. The three factors showed acceptable internal consistency scores. Moreover, functional associations between the three factors and coach leadership behaviors were found offering support to the instrument's concurrent validity. The findings support previous validation studies and verify the psychometric properties of the CART-Q applied to Belgian coaches of team sports. © 2009 John Wiley & Sons A/S.

Application of advanced multidisciplinary analysis and optimization methods to vehicle design synthesis

NASA Technical Reports Server (NTRS)

Consoli, Robert David; Sobieszczanski-Sobieski, Jaroslaw

1990-01-01

Advanced multidisciplinary analysis and optimization methods, namely system sensitivity analysis and non-hierarchical system decomposition, are applied to reduce the cost and improve the visibility of an automated vehicle design synthesis process. This process is inherently complex due to the large number of functional disciplines and associated interdisciplinary couplings. Recent developments in system sensitivity analysis as applied to complex non-hierarchic multidisciplinary design optimization problems enable the decomposition of these complex interactions into sub-processes that can be evaluated in parallel. The application of these techniques results in significant cost, accuracy, and visibility benefits for the entire design synthesis process.

The Topic Analysis of Hospice Care Research Using Co-word Analysis and GHSOM

NASA Astrophysics Data System (ADS)

Yang, Yu-Hsiang; Bhikshu, Huimin; Tsaih, Rua-Huan

The purpose of this study was to propose a multi-layer topic map analysis of palliative care research using co-word analysis of informetrics with Growing Hierarchical Self-Organizing Map (GHSOM). The topic map illustrated the delicate intertwining of subject areas and provided a more explicit illustration of the concepts within each subject area. We applied GHSOM, a text-mining Neural Networks tool, to obtain a hierarchical topic map. The result of the topic map may indicate that the subject area of health care science and service played an importance role in multidiscipline within the research related to palliative care.

Drosophila histone locus bodies form by hierarchical recruitment of components

PubMed Central

White, Anne E.; Burch, Brandon D.; Yang, Xiao-cui; Gasdaska, Pamela Y.; Dominski, Zbigniew; Marzluff, William F.

2011-01-01

Nuclear bodies are protein- and RNA-containing structures that participate in a wide range of processes critical to genome function. Molecular self-organization is thought to drive nuclear body formation, but whether this occurs stochastically or via an ordered, hierarchical process is not fully understood. We addressed this question using RNAi and proteomic approaches in Drosophila melanogaster to identify and characterize novel components of the histone locus body (HLB), a nuclear body involved in the expression of replication-dependent histone genes. We identified the transcription elongation factor suppressor of Ty 6 (Spt6) and a homologue of mammalian nuclear protein of the ataxia telangiectasia–mutated locus that is encoded by the homeotic gene multisex combs (mxc) as novel HLB components. By combining genetic manipulation in both cell culture and embryos with cytological observations of Mxc, Spt6, and the known HLB components, FLICE-associated huge protein, Mute, U7 small nuclear ribonucleoprotein, and MPM-2 phosphoepitope, we demonstrated sequential recruitment and hierarchical dependency for localization of factors to HLBs during development, suggesting that ordered assembly can play a role in nuclear body formation. PMID:21576393

Implications of the Hierarchical Structure of Psychopathology for Psychiatric Neuroimaging.

PubMed

Zald, David H; Lahey, Benjamin B

2017-05-01

Research into the neurobiological substrates of psychopathology has been impeded by heterogeneity within diagnostic categories, comorbidity among mental disorders, and the presence of symptoms that transcend diagnostic categories. Solutions to these issues increasingly focus neurobiological research on isolated or narrow groupings of symptoms or functional constructs rather than categorical diagnoses. Here we argue for a more integrative approach that also incorporates the broad hierarchical structure of psychopathological symptoms and their etiological mechanisms. This approach places clinical neuroscience research in the context of a hierarchy of empirically defined factors of symptoms such as internalizing disorders, externalizing disorders, and the general factor of psychopathology. Application of this hierarchical approach has the potential to reveal neural substrates that nonspecifically contribute to multiple forms of psychopathology and their comorbidity, and in doing so, facilitate the study of mechanisms that are specific to single dimensions and subsets of symptoms. Neurobiological research on the hierarchy of dimensions of psychopathology is only just beginning to emerge, but has the potential to radically alter our understanding of the neurobiology of abnormal behavior.

Beyond comorbidity: Toward a dimensional and hierarchal approach to understanding psychopathology across the lifespan

PubMed Central

Forbes, Miriam K.; Tackett, Jennifer L.; Markon, Kristian E.; Krueger, Robert F.

2016-01-01

In this review, we propose a novel developmentally informed framework to push research beyond a focus on comorbidity between discrete diagnostic categories, and to move towards research based on the well-validated dimensional and hierarchical structure of psychopathology. For example, a large body of research speaks to the validity and utility of the Internalizing and Externalizing (IE) spectra as organizing constructs for research on common forms of psychopathology. The IE spectra act as powerful explanatory variables that channel the psychopathological effects of genetic and environmental risk factors, predict adaptive functioning, and account for the likelihood of disorder-level manifestations of psychopathology. As such, our proposed theoretical framework uses the IE spectra as central constructs to guide future psychopathology research across the lifespan. The framework is particularly flexible, as any of the facets or factors from the dimensional and hierarchical structure of psychopathology can form the focus of research. We describe the utility and strengths of this framework for developmental psychopathology in particular, and explore avenues for future research. PMID:27739384

Implications of the Hierarchical Structure of Psychopathology for Psychiatric Neuroimaging

PubMed Central

Zald, David H.; Lahey, Benjamin B.

2017-01-01

Research into the neurobiological substrates of psychopathology has been impeded by heterogeneity within diagnostic categories, comorbidity among mental disorders, and the presence of symptoms that transcend diagnostic categories. Solutions to these issues increasingly focus neurobiological research on isolated or narrow groupings of symptoms or functional constructs rather than categorical diagnoses. Here we argue for a more integrative approach that also incorporates the broad hierarchical structure of psychopathological symptoms and their etiological mechanisms. This approach places clinical neuroscience research in the context of a hierarchy of empirically defined factors of symptoms such as internalizing disorders, externalizing disorders, and the general factor of psychopathology. Application of this hierarchical approach has the potential to reveal neural substrates that nonspecifically contribute to multiple forms of psychopathology and their comorbidity, and in doing so, facilitate the study of mechanisms that are specific to single dimensions and subsets of symptoms. Neurobiological research on the hierarchy of dimensions of psychopathology is only just beginning to emerge, but has the potential to radically alter our understanding of the neurobiology of abnormal behavior. PMID:28713866

Subtypes of female juvenile offenders: a cluster analysis of the Millon Adolescent Clinical Inventory.

PubMed

Stefurak, Tres; Calhoun, Georgia B

2007-01-01

The current study sought to explore subtypes of adolescents within a sample of female juvenile offenders. Using the Millon Adolescent Clinical Inventory with 101 female juvenile offenders, a two-step cluster analysis was performed beginning with a Ward's method hierarchical cluster analysis followed by a K-Means iterative partitioning cluster analysis. The results suggest an optimal three-cluster solution, with cluster profiles leading to the following group labels: Externalizing Problems, Depressed/Interpersonally Ambivalent, and Anxious Prosocial. Analysis along the factors of age, race, offense typology and offense chronicity were conducted to further understand the nature of found clusters. Only the effect for race was significant with the Anxious Prosocial and Depressed Intepersonally Ambivalent clusters appearing disproportionately comprised of African American girls. To establish external validity, clusters were compared across scales of the Behavioral Assessment System for Children - Self Report of Personality, and corroborative distinctions between clusters were found here.

Assessment of changes of vector borne diseases with wetland characteristics using multivariate analysis.

PubMed

Sheela, A M; Sarun, S; Justus, J; Vineetha, P; Sheeja, R V

2015-04-01

Vector borne diseases are a threat to human health. Little attention has been paid to the prevention of these diseases. We attempted to identify the significant wetland characteristics associated with the spread of chikungunya, dengue fever and malaria in Kerala, a tropical region of South West India using multivariate analyses (hierarchical cluster analysis, factor analysis and multiple regression). High/medium turbid coastal lagoons and inland water-logged wetlands with aquatic vegetation have significant effect on the incidence of chikungunya while dengue influenced by high turbid coastal beaches and malaria by medium turbid coastal beaches. The high turbidity in water is due to the urban waste discharge namely sewage, sullage and garbage from the densely populated cities and towns. The large extent of wetland is low land area favours the occurrence of vector borne diseases. Hence the provision of pollution control measures at source including soil erosion control measures is vital. The identification of vulnerable zones favouring the vector borne diseases will help the authorities to control pollution especially from urban areas and prevent these vector borne diseases. Future research should cover land use cover changes, climatic factors, seasonal variations in weather and pollution factors favouring the occurrence of vector borne diseases.

Characterization of dissolved organic matter in Dongjianghu Lake by UV-visible absorption spectroscopy with multivariate analysis.

PubMed

Zhu, Yanzhong; Song, Yonghui; Yu, Huibin; Liu, Ruixia; Liu, Lusan; Lv, Chunjian

2017-08-08

UV-visible absorption spectroscopy coupled with principal component analysis (PCA) and hierarchical cluster analysis (HCA) was applied to characterize spectroscopic components, detect latent factors, and investigate spatial variations of dissolved organic matter (DOM) in a large-scale lake. Twelve surface water samples were collected from Dongjianghu Lake in China. DOM contained lignin and quinine moieties, carboxylic acid, microbial products, and aromatic and alkyl groups, which in the northern part of the lake was largely different from the southern part. Fifteen spectroscopic indices were deduced from the absorption spectra to indicate molecular weight or humification degree of DOM. The northern part of the lake presented the smaller molecular weight or the lower humification degree of DOM than the southern part. E 2/4 , E 3/4 , E 2/3 , and S 2 were latent factors of characterizing the molecular weight of DOM, while E 2/5 , E 3/5 , E 2/6 , E 4/5 , E 3/6 , and A 2/1 were latent factors of evaluating the humification degree of DOM. The UV-visible absorption spectroscopy combined with PCA and HCA may not only characterize DOM fractions of lakes, but may be transferred to other types of waterscape.

Photocatalytic properties of hierarchical ZnO flowers synthesized by a sucrose-assisted hydrothermal method

NASA Astrophysics Data System (ADS)

Lv, Wei; Wei, Bo; Xu, Lingling; Zhao, Yan; Gao, Hong; Liu, Jia

2012-10-01

In this work, hierarchical ZnO flowers were synthesized via a sucrose-assisted urea hydrothermal method. The thermogravimetric analysis/differential thermal analysis (TGA-DTA) and Fourier transform infrared spectra (FTIR) showed that sucrose acted as a complexing agent in the synthesis process and assisted combustion during annealing. Photocatalytic activity was evaluated using the degradation of organic dye methyl orange. The sucrose added ZnO flowers showed improved activity, which was mainly attributed to the better crystallinity as confirmed by X-ray photoelectron spectroscopy (XPS) analysis. The effect of sucrose amount on photocatalytic activity was also studied.

Psychosocial factors affecting resilience in Nepalese individuals with earthquake-related spinal cord injury: a cross-sectional study.

PubMed

Bhattarai, Muna; Maneewat, Khomapak; Sae-Sia, Wipa

2018-03-02

One of many types of injuries following an earthquake is spinal cord injury (SCI) which is a life-long medically complex injury and high-cost health problem. Despite several negative consequences, some persons with SCI are resilient enough to achieve positive adjustment, greater acceptance, and better quality of life. Since resilience is influenced by several factors and can vary by context, it is beneficial to explore factors that affect the resilience of people who sustained spinal cord injury from the 2015 earthquake in Nepal. A descriptive cross-sectional study included 82 participants from the Spinal Injury Rehabilitation Center and communities in Nepal. Participants completed the Demographic and Injury-related Questionnaire, Connor-Davidson Resilience Scale, Multidimensional Scale of Perceived Social Support, Moorong Self-efficacy Scale, Intrinsic Spirituality Scale, and Patient Health Questionnaire-9. Pearson's correlation and point biserial correlation analyses were performed to examine associations between resilience and independent variables. A hierarchical regression analysis was used to identify the influence of certain factors. Findings indicated significant associations between resilience and social support (r = 0.42, p < 0.001), self-efficacy (r = 0.53, p < 0.001), depressive mood (r = - 0.50, p < 0.001) and demographic variables which included sex (r = 0.47, p < 0.001), employment (r = 0.27, p = 0.016), and current living location (r = 0.24, p = 0.029). There was a non-significant association between resilience and spirituality (r = - 0.12, p > 0.05). In hierarchical regression analysis, an overall regression model explained 46% of the variance in resilience. Self-efficacy (β = 0.28, p = 0.007) and depressive mood (β = - 0.24, p = 0.016) significantly determined resilience after controlling the effect of demographic variables. Among the demographic factors, being male significantly explained the variance in resilience (β = 0.31, p = 0.001). Multiple psychosocial and demographic factors were associated with resilience in people who sustained an earthquake-related SCI. Mental health professionals should demonstrate concern and consider such factors in allocating care in this group. Development of intervention research concerning resilience is recommended to strengthen resilience in order to improve rehabilitation outcomes and enhance reintegration of individuals with SCI into their communities.

Nanoscale Analysis of a Hierarchical Hybrid Solar Cell in 3D.

PubMed

Divitini, Giorgio; Stenzel, Ole; Ghadirzadeh, Ali; Guarnera, Simone; Russo, Valeria; Casari, Carlo S; Bassi, Andrea Li; Petrozza, Annamaria; Di Fonzo, Fabio; Schmidt, Volker; Ducati, Caterina

2014-05-01

A quantitative method for the characterization of nanoscale 3D morphology is applied to the investigation of a hybrid solar cell based on a novel hierarchical nanostructured photoanode. A cross section of the solar cell device is prepared by focused ion beam milling in a micropillar geometry, which allows a detailed 3D reconstruction of the titania photoanode by electron tomography. It is found that the hierarchical titania nanostructure facilitates polymer infiltration, thus favoring intermixing of the two semiconducting phases, essential for charge separation. The 3D nanoparticle network is analyzed with tools from stochastic geometry to extract information related to the charge transport in the hierarchical solar cell. In particular, the experimental dataset allows direct visualization of the percolation pathways that contribute to the photocurrent.

Nanoscale Analysis of a Hierarchical Hybrid Solar Cell in 3D

PubMed Central

Divitini, Giorgio; Stenzel, Ole; Ghadirzadeh, Ali; Guarnera, Simone; Russo, Valeria; Casari, Carlo S; Bassi, Andrea Li; Petrozza, Annamaria; Di Fonzo, Fabio; Schmidt, Volker; Ducati, Caterina

2014-01-01

A quantitative method for the characterization of nanoscale 3D morphology is applied to the investigation of a hybrid solar cell based on a novel hierarchical nanostructured photoanode. A cross section of the solar cell device is prepared by focused ion beam milling in a micropillar geometry, which allows a detailed 3D reconstruction of the titania photoanode by electron tomography. It is found that the hierarchical titania nanostructure facilitates polymer infiltration, thus favoring intermixing of the two semiconducting phases, essential for charge separation. The 3D nanoparticle network is analyzed with tools from stochastic geometry to extract information related to the charge transport in the hierarchical solar cell. In particular, the experimental dataset allows direct visualization of the percolation pathways that contribute to the photocurrent. PMID:25834481

A hierarchical approach to reliability modeling of fault-tolerant systems. M.S. Thesis

NASA Technical Reports Server (NTRS)

Gossman, W. E.

1986-01-01

A methodology for performing fault tolerant system reliability analysis is presented. The method decomposes a system into its subsystems, evaluates vent rates derived from the subsystem's conditional state probability vector and incorporates those results into a hierarchical Markov model of the system. This is done in a manner that addresses failure sequence dependence associated with the system's redundancy management strategy. The method is derived for application to a specific system definition. Results are presented that compare the hierarchical model's unreliability prediction to that of a more complicated tandard Markov model of the system. The results for the example given indicate that the hierarchical method predicts system unreliability to a desirable level of accuracy while achieving significant computational savings relative to component level Markov model of the system.

Radiation efficiency of earthquake sources at different hierarchical levels

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

Kocharyan, G. G., E-mail: gevorgkidg@mail.ru; Moscow Institute of Physics and Technology

Such factors as earthquake size and its mechanism define common trends in alteration of radiation efficiency. The macroscopic parameter that controls the efficiency of a seismic source is stiffness of fault or fracture. The regularities of this parameter alteration with scale define several hierarchical levels, within which earthquake characteristics obey different laws. Small variations of physical and mechanical properties of the fault principal slip zone can lead to dramatic differences both in the amplitude of released stress and in the amount of radiated energy.

Hierarchical structure of the energy landscape of proteins revisited by time series analysis. II. Investigation of explicit solvent effects

NASA Astrophysics Data System (ADS)

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

2005-10-01

Time series analysis tools are employed on the principal modes obtained from the Cα trajectories from two independent molecular-dynamics simulations of α-amylase inhibitor (tendamistat). Fluctuations inside an energy minimum (intraminimum motions), transitions between minima (interminimum motions), and relaxations in different hierarchical energy levels are investigated and compared with those encountered in vacuum by using different sampling window sizes and intervals. The low-frequency low-indexed mode relationship, established in vacuum, is also encountered in water, which shows the reliability of the important dynamics information offered by principal components analysis in water. It has been shown that examining a short data collection period (100ps) may result in a high population of overdamped modes, while some of the low-frequency oscillations (<10cm-1) can be captured in water by using a longer data collection period (1200ps). Simultaneous analysis of short and long sampling window sizes gives the following picture of the effect of water on protein dynamics. Water makes the protein lose its memory: future conformations are less dependent on previous conformations due to the lowering of energy barriers in hierarchical levels of the energy landscape. In short-time dynamics (<10ps), damping factors extracted from time series model parameters are lowered. For tendamistat, the friction coefficient in the Langevin equation is found to be around 40-60cm-1 for the low-indexed modes, compatible with literature. The fact that water has increased the friction and that on the other hand has lubrication effect at first sight contradicts. However, this comes about because water enhances the transitions between minima and forces the protein to reduce its already inherent inability to maintain oscillations observed in vacuum. Some of the frequencies lower than 10cm-1 are found to be overdamped, while those higher than 20cm-1 are slightly increased. As for the long-time dynamics in water, it is found that random-walk motion is maintained for approximately 200ps (about five times of that in vacuum) in the low-indexed modes, showing the lowering of energy barriers between the higher-level minima.

Creating the environment for driver distraction: A thematic framework of sociotechnical factors.

PubMed

Parnell, Katie J; Stanton, Neville A; Plant, Katherine L

2018-04-01

As modern society becomes more reliant on technology, its use within the vehicle is becoming a concern for road safety due to both portable and built-in devices offering sources of distraction. While the effects of distracting technologies are well documented, little is known about the causal factors that lead to the drivers' engagement with technological devices. The relevance of the sociotechnical system within which the behaviour occurs requires further research. This paper presents two experiments, the first aims to assess the drivers self-reported decision to engage with technological tasks while driving and their reasoning for doing so with respect to the wider sociotechnical system. This utilised a semi-structured interview method, conducted with 30 drivers to initiate a discussion on their likelihood of engaging with 22 different tasks across 7 different road types. Inductive thematic analysis provided a hierarchical thematic framework that detailed the self-reported causal factors that influence the drivers' use of technology whilst driving. The second experiment assessed the relevance of the hierarchical framework to a model of distraction that was established from within the literature on the drivers use of distracting technologies while driving. The findings provide validation for some relationships studied in the literature, as well as providing insights into relationships that require further study. The role of the sociotechnical system in the engagement of distractions while driving is highlighted, with the causal factors reported by drivers suggesting the importance of considering the wider system within which the behaviour is occurring and how it may be creating the conditions for distraction to occur. This supports previous claims made within the literature based model. Recommendations are proposed that encourage a movement away from individual focused countermeasures towards systemic actors. Copyright © 2017 Elsevier Ltd. All rights reserved.

Improving job satisfaction of Chinese doctors: the positive effects of perceived organizational support and psychological capital.

PubMed

Fu, J; Sun, W; Wang, Y; Yang, X; Wang, L

2013-10-01

The huge population basic and the transformational changes to healthcare system in China have gained wide public attention in recent years. Along with these issues is a growing literature about doctor's job satisfaction; however, more is known about its negative related factors. Thus, this study was an attempt to assess the level of job satisfaction among Chinese doctors and to explore factors that enhance their job satisfaction. Cross-sectional questionnaire-based survey. A cross-sectional study was conducted during the period of September/October 2010. A questionnaire containing job satisfaction assessed by Minnesota Satisfaction Questionnaire (MSQ), demographic characteristics, work conditions, psychological capital (PsyCap) and perceived organizational support (POS) was distributed to 1300 registered doctors in Liaoning province. A total of 984 respondents became our subjects (effective response rate 75.7%). Hierarchical regression was performed to explore the factors associated with satisfaction. The average MSQ score was 65.86 (level ranking for MSQ, 20-100) in our study population. Hierarchical regression analysis showed that POS (β = 0.412, P < 0.001), PsyCap (β = 0.255, P < 0.001), incentive system (β = 0.119, P < 0.001) and educational background (β = 0.056, P = 0.042) were positively associated with job satisfaction. The job satisfaction of Chinese doctors was at a moderate level. POS and PsyCap seemed to be the most crucial factors in relation to job satisfaction. Therefore, efficient measures such as building a supportive work environment and developing doctors' PsyCap should be considered by health administrators in order to promote job satisfaction among Chinese doctors. Copyright © 2013 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Autogrid-based clustering of kinases: selection of representative conformations for docking purposes.

PubMed

Marzaro, Giovanni; Ferrarese, Alessandro; Chilin, Adriana

2014-08-01

The selection of the most appropriate protein conformation is a crucial aspect in molecular docking experiments. In order to reduce the errors arising from the use of a single protein conformation, several authors suggest the use of several tridimensional structures for the target. However, the selection of the most appropriate protein conformations still remains a challenging goal. The protein 3D-structures selection is mainly performed based on pairwise root-mean-square-deviation (RMSD) values computation, followed by hierarchical clustering. Herein we report an alternative strategy, based on the computation of only two atom affinity map for each protein conformation, followed by multivariate analysis and hierarchical clustering. This methodology was applied on seven different kinases of pharmaceutical interest. The comparison with the classical RMSD-based strategy was based on cross-docking of co-crystallized ligands. In the case of epidermal growth factor receptor kinase, also the docking performance on 220 known ligands were evaluated, followed by 3D-QSAR studies. In all the cases, the herein proposed methodology outperformed the RMSD-based one.

Hierarchical dose response of E. coli O157:H7 from human outbreaks incorporating heterogeneity in exposure.

PubMed

Teunis, P F M; Ogden, I D; Strachan, N J C

2008-06-01

The infectivity of pathogenic microorganisms is a key factor in the transmission of an infectious disease in a susceptible population. Microbial infectivity is generally estimated from dose-response studies in human volunteers. This can only be done with mildly pathogenic organisms. Here a hierarchical Beta-Poisson dose-response model is developed utilizing data from human outbreaks. On the lowest level each outbreak is modelled separately and these are then combined at a second level to produce a group dose-response relation. The distribution of foodborne pathogens often shows strong heterogeneity and this is incorporated by introducing an additional parameter to the dose-response model, accounting for the degree of overdispersion relative to Poisson distribution. It was found that heterogeneity considerably influences the shape of the dose-response relationship and increases uncertainty in predicted risk. This uncertainty is greater than previously reported surrogate and outbreak models using a single level of analysis. Monte Carlo parameter samples (alpha, beta of the Beta-Poisson model) can be readily incorporated in risk assessment models built using tools such as S-plus and @ Risk.

Show me the money: incorporating financial motives into the gambling motives questionnaire.

PubMed

Dechant, Kristianne

2014-12-01

Although research has only recently begun to measure what motivates all levels of gambling involvement, motives could offer a theoretically interesting and practical way to subtype gamblers in research and for responsible gambling initiatives. The Gambling Motives Questionnaire (GMQ) is one measure that weaves together much of the gambling motives literature, but it has been criticized for neglecting financial reasons for gambling. This study uses a series of factor analyses to explore the effect of adding nine financial motives to the GMQ in a heterogeneous sample of 1,014 adult past-year gamblers. After trimming trivial financial motives, the penultimate factor analysis of the 15 GMQ items and four financial motives led to a four-factor solution, with factors tapping enhancement, social, coping and financial motives, as predicted. A final factor analysis performed on a modified GMQ-F (i.e., 16 items, including a financial subscale) revealed the same four factors, and hierarchical regression showed that the financial motives improve the GMQ-F's prediction of gambling frequency. This study provides evidence that omitting financial motives is a clear gap in the GMQ, yet suggests that the GMQ is a promising tool that can be conceptually and empirically strengthened with the simple addition of financial items.

Gender differences in predicting high-risk drinking among undergraduate students.

PubMed

Wilke, Dina J; Siebert, Darcy Clay; Delva, Jorge; Smith, Michael P; Howell, Richard L

2005-01-01

The purpose of this study was to examine gender differences in college students' high-risk drinking as measured by an estimated blood alcohol concentration (eBAC) based on gender, height, weight, self-reported number of drinks, and hours spent drinking. Using a developmental/contextual framework, high-risk drinking is conceptualized as a function of relevant individual characteristics, interpersonal factors, and contextual factors regularly mentioned in the college drinking literature. Individual characteristics include race, gender, and age; interpersonal characteristics include number of sexual partners and having experienced forced sexual contact. Finally, contextual factors include Greek membership, living off-campus, and perception of peer drinking behavior. This study is a secondary data analysis of 1,422 students at a large university in the Southeast. Data were gathered from a probability sample of students through a mail survey. A three-step hierarchical logistic regression analysis showed gender differences in the pathway for high-risk drinking. For men, high-risk drinking was predicted by a combination of individual characteristics and contextual factors. For women, interpersonal factors, along with individual characteristics and contextual factors, predicted high-risk drinking, highlighting the importance of understanding female sexual relationships and raising questions about women's risk-taking behavior. Implications for prevention and assessment are discussed.

Relation between financial market structure and the real economy: comparison between clustering methods.

PubMed

Musmeci, Nicoló; Aste, Tomaso; Di Matteo, T

2015-01-01

We quantify the amount of information filtered by different hierarchical clustering methods on correlations between stock returns comparing the clustering structure with the underlying industrial activity classification. We apply, for the first time to financial data, a novel hierarchical clustering approach, the Directed Bubble Hierarchical Tree and we compare it with other methods including the Linkage and k-medoids. By taking the industrial sector classification of stocks as a benchmark partition, we evaluate how the different methods retrieve this classification. The results show that the Directed Bubble Hierarchical Tree can outperform other methods, being able to retrieve more information with fewer clusters. Moreover,we show that the economic information is hidden at different levels of the hierarchical structures depending on the clustering method. The dynamical analysis on a rolling window also reveals that the different methods show different degrees of sensitivity to events affecting financial markets, like crises. These results can be of interest for all the applications of clustering methods to portfolio optimization and risk hedging [corrected].

Fabrication of free-standing hierarchical carbon nanofiber/graphene oxide/polyaniline films for supercapacitors.

PubMed

Xu, Dongdong; Xu, Qun; Wang, Kaixi; Chen, Jun; Chen, Zhimin

2014-01-08

A hierarchical high-performance electrode with nanoacanthine-style polyaniline (PANI) deposited onto a carbon nanofiber/graphene oxide (CNF/GO) template was successfully prepared via an in situ polymerization process. The morphology analysis shows that introducing one-dimensional (1D) CNF could significantly decrease/inhibit the staking of laminated GO to form an open-porous CNF/GO architecture. Followed with in situ facial deposition of PANI, the as-synthesized PANI modified CNF/GO exhibits three-dimensional (3D) hierarchical layered nanoarchitecture, which favors the diffusion of the electrolyte ions into the inner region of active materials. The hierarchical free-standing electrodes were directly fabricated into sandwich structured supercapacitors using 1 M H2SO4 as the electrolyte showing a significant specific capacitance of 450.2 F/g at the voltage scan rate of 10 mV/s. The electrochemical properties of the hierarchical structure can be further improved by a reduction procedure of GO before the deposition of PANI.

Band-gap analysis of a novel lattice with a hierarchical periodicity using the spectral element method

NASA Astrophysics Data System (ADS)

Wu, Zhijing; Li, Fengming; Zhang, Chuanzeng

2018-05-01

Inspired by the hierarchical structures of butterfly wing surfaces, a new kind of lattice structures with a two-order hierarchical periodicity is proposed and designed, and the band-gap properties are investigated by the spectral element method (SEM). The equations of motion of the whole structure are established considering the macro and micro periodicities of the system. The efficiency of the SEM is exploited in the modeling process and validated by comparing the results with that of the finite element method (FEM). Based on the highly accurate results in the frequency domain, the dynamic behaviors of the proposed two-order hierarchical structures are analyzed. An original and interesting finding is the existence of the distinct macro and micro stop-bands in the given frequency domain. The mechanisms for these two types of band-gaps are also explored. Finally, the relations between the hierarchical periodicities and the different types of the stop-bands are investigated by analyzing the parametrical influences.

Relation between Financial Market Structure and the Real Economy: Comparison between Clustering Methods

PubMed Central

Musmeci, Nicoló; Aste, Tomaso; Di Matteo, T.

2015-01-01

We quantify the amount of information filtered by different hierarchical clustering methods on correlations between stock returns comparing the clustering structure with the underlying industrial activity classification. We apply, for the first time to financial data, a novel hierarchical clustering approach, the Directed Bubble Hierarchical Tree and we compare it with other methods including the Linkage and k-medoids. By taking the industrial sector classification of stocks as a benchmark partition, we evaluate how the different methods retrieve this classification. The results show that the Directed Bubble Hierarchical Tree can outperform other methods, being able to retrieve more information with fewer clusters. Moreover, we show that the economic information is hidden at different levels of the hierarchical structures depending on the clustering method. The dynamical analysis on a rolling window also reveals that the different methods show different degrees of sensitivity to events affecting financial markets, like crises. These results can be of interest for all the applications of clustering methods to portfolio optimization and risk hedging. PMID:25786703

Application of Multiple Imputation for Missing Values in Three-Way Three-Mode Multi-Environment Trial Data

PubMed Central

Tian, Ting; McLachlan, Geoffrey J.; Dieters, Mark J.; Basford, Kaye E.

2015-01-01

It is a common occurrence in plant breeding programs to observe missing values in three-way three-mode multi-environment trial (MET) data. We proposed modifications of models for estimating missing observations for these data arrays, and developed a novel approach in terms of hierarchical clustering. Multiple imputation (MI) was used in four ways, multiple agglomerative hierarchical clustering, normal distribution model, normal regression model, and predictive mean match. The later three models used both Bayesian analysis and non-Bayesian analysis, while the first approach used a clustering procedure with randomly selected attributes and assigned real values from the nearest neighbour to the one with missing observations. Different proportions of data entries in six complete datasets were randomly selected to be missing and the MI methods were compared based on the efficiency and accuracy of estimating those values. The results indicated that the models using Bayesian analysis had slightly higher accuracy of estimation performance than those using non-Bayesian analysis but they were more time-consuming. However, the novel approach of multiple agglomerative hierarchical clustering demonstrated the overall best performances. PMID:26689369

Application of Multiple Imputation for Missing Values in Three-Way Three-Mode Multi-Environment Trial Data.

PubMed

Tian, Ting; McLachlan, Geoffrey J; Dieters, Mark J; Basford, Kaye E

2015-01-01

It is a common occurrence in plant breeding programs to observe missing values in three-way three-mode multi-environment trial (MET) data. We proposed modifications of models for estimating missing observations for these data arrays, and developed a novel approach in terms of hierarchical clustering. Multiple imputation (MI) was used in four ways, multiple agglomerative hierarchical clustering, normal distribution model, normal regression model, and predictive mean match. The later three models used both Bayesian analysis and non-Bayesian analysis, while the first approach used a clustering procedure with randomly selected attributes and assigned real values from the nearest neighbour to the one with missing observations. Different proportions of data entries in six complete datasets were randomly selected to be missing and the MI methods were compared based on the efficiency and accuracy of estimating those values. The results indicated that the models using Bayesian analysis had slightly higher accuracy of estimation performance than those using non-Bayesian analysis but they were more time-consuming. However, the novel approach of multiple agglomerative hierarchical clustering demonstrated the overall best performances.

Chi-squared Automatic Interaction Detection Decision Tree Analysis of Risk Factors for Infant Anemia in Beijing, China

PubMed Central

Ye, Fang; Chen, Zhi-Hua; Chen, Jie; Liu, Fang; Zhang, Yong; Fan, Qin-Ying; Wang, Lin

2016-01-01

Background: In the past decades, studies on infant anemia have mainly focused on rural areas of China. With the increasing heterogeneity of population in recent years, available information on infant anemia is inconclusive in large cities of China, especially with comparison between native residents and floating population. This population-based cross-sectional study was implemented to determine the anemic status of infants as well as the risk factors in a representative downtown area of Beijing. Methods: As useful methods to build a predictive model, Chi-squared automatic interaction detection (CHAID) decision tree analysis and logistic regression analysis were introduced to explore risk factors of infant anemia. A total of 1091 infants aged 6–12 months together with their parents/caregivers living at Heping Avenue Subdistrict of Beijing were surveyed from January 1, 2013 to December 31, 2014. Results: The prevalence of anemia was 12.60% with a range of 3.47%–40.00% in different subgroup characteristics. The CHAID decision tree model has demonstrated multilevel interaction among risk factors through stepwise pathways to detect anemia. Besides the three predictors identified by logistic regression model including maternal anemia during pregnancy, exclusive breastfeeding in the first 6 months, and floating population, CHAID decision tree analysis also identified the fourth risk factor, the maternal educational level, with higher overall classification accuracy and larger area below the receiver operating characteristic curve. Conclusions: The infant anemic status in metropolis is complex and should be carefully considered by the basic health care practitioners. CHAID decision tree analysis has demonstrated a better performance in hierarchical analysis of population with great heterogeneity. Risk factors identified by this study might be meaningful in the early detection and prompt treatment of infant anemia in large cities. PMID:27174328

Chi-squared Automatic Interaction Detection Decision Tree Analysis of Risk Factors for Infant Anemia in Beijing, China.

PubMed

Ye, Fang; Chen, Zhi-Hua; Chen, Jie; Liu, Fang; Zhang, Yong; Fan, Qin-Ying; Wang, Lin

2016-05-20

In the past decades, studies on infant anemia have mainly focused on rural areas of China. With the increasing heterogeneity of population in recent years, available information on infant anemia is inconclusive in large cities of China, especially with comparison between native residents and floating population. This population-based cross-sectional study was implemented to determine the anemic status of infants as well as the risk factors in a representative downtown area of Beijing. As useful methods to build a predictive model, Chi-squared automatic interaction detection (CHAID) decision tree analysis and logistic regression analysis were introduced to explore risk factors of infant anemia. A total of 1091 infants aged 6-12 months together with their parents/caregivers living at Heping Avenue Subdistrict of Beijing were surveyed from January 1, 2013 to December 31, 2014. The prevalence of anemia was 12.60% with a range of 3.47%-40.00% in different subgroup characteristics. The CHAID decision tree model has demonstrated multilevel interaction among risk factors through stepwise pathways to detect anemia. Besides the three predictors identified by logistic regression model including maternal anemia during pregnancy, exclusive breastfeeding in the first 6 months, and floating population, CHAID decision tree analysis also identified the fourth risk factor, the maternal educational level, with higher overall classification accuracy and larger area below the receiver operating characteristic curve. The infant anemic status in metropolis is complex and should be carefully considered by the basic health care practitioners. CHAID decision tree analysis has demonstrated a better performance in hierarchical analysis of population with great heterogeneity. Risk factors identified by this study might be meaningful in the early detection and prompt treatment of infant anemia in large cities.

Complexity of major UK companies between 2006 and 2010: Hierarchical structure method approach

NASA Astrophysics Data System (ADS)

Ulusoy, Tolga; Keskin, Mustafa; Shirvani, Ayoub; Deviren, Bayram; Kantar, Ersin; Çaǧrı Dönmez, Cem

2012-11-01

This study reports on topology of the top 40 UK companies that have been analysed for predictive verification of markets for the period 2006-2010, applying the concept of minimal spanning tree and hierarchical tree (HT) analysis. Construction of the minimal spanning tree (MST) and the hierarchical tree (HT) is confined to a brief description of the methodology and a definition of the correlation function between a pair of companies based on the London Stock Exchange (LSE) index in order to quantify synchronization between the companies. A derivation of hierarchical organization and the construction of minimal-spanning and hierarchical trees for the 2006-2008 and 2008-2010 periods have been used and the results validate the predictive verification of applied semantics. The trees are known as useful tools to perceive and detect the global structure, taxonomy and hierarchy in financial data. From these trees, two different clusters of companies in 2006 were detected. They also show three clusters in 2008 and two between 2008 and 2010, according to their proximity. The clusters match each other as regards their common production activities or their strong interrelationship. The key companies are generally given by major economic activities as expected. This work gives a comparative approach between MST and HT methods from statistical physics and information theory with analysis of financial markets that may give new valuable and useful information of the financial market dynamics.

Psychosocial risk and protective factors for depression in the dialysis population: a systematic review and meta-regression analysis.

PubMed

Chan, Ramony; Steel, Zachary; Brooks, Robert; Heung, Tracy; Erlich, Jonathan; Chow, Josephine; Suranyi, Michael

2011-11-01

Research into the association between psychosocial factors and depression in End-Stage Renal Disease (ESRD) has expanded considerably in recent years identifying a range of factors that may act as important risk and protective factors of depression for this population. The present study provides the first systematic review and meta-analysis of this body of research. Published studies reporting associations between any psychosocial factor and depression were identified and retrieved from Medline, Embase, and PsycINFO, by applying optimised search strategies. Mean effect sizes were calculated for the associations across five psychosocial constructs (social support, personality attributes, cognitive appraisal, coping process, stress/stressor). Multiple hierarchical meta-regression analysis was applied to examine the moderating effects of methodological and substantive factors on the strength of the observed associations. 57 studies covering 58 independent samples with 5956 participants were identified, resulting in 246 effect sizes of the association between a range of psychosocial factors and depression. The overall mean effect size (Pearsons correlation coefficient) of the association between psychosocial factor and depression was 0.36. The effect sizes between the five psychosocial constructs and depression ranged from medium (0.27) to large levels (0.46) with personality attributes (0.46) and cognitive appraisal (0.46) having the largest effect sizes. In the meta-regression analyses, identified demographic (gender, age, location of study) and treatment (type of dialysis) characteristics moderated the strength of the associations with depression. The current analysis documents a moderate to large association between the presence of psychosocial risk factors and depression in ESRD. 2011. Published by Elsevier Inc. All rights reserved.

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.

Bayesian hierarchical functional data analysis via contaminated informative priors.

PubMed

Scarpa, Bruno; Dunson, David B

2009-09-01

A variety of flexible approaches have been proposed for functional data analysis, allowing both the mean curve and the distribution about the mean to be unknown. Such methods are most useful when there is limited prior information. Motivated by applications to modeling of temperature curves in the menstrual cycle, this article proposes a flexible approach for incorporating prior information in semiparametric Bayesian analyses of hierarchical functional data. The proposed approach is based on specifying the distribution of functions as a mixture of a parametric hierarchical model and a nonparametric contamination. The parametric component is chosen based on prior knowledge, while the contamination is characterized as a functional Dirichlet process. In the motivating application, the contamination component allows unanticipated curve shapes in unhealthy menstrual cycles. Methods are developed for posterior computation, and the approach is applied to data from a European fecundability study.

Radiomics of CT Features May Be Nonreproducible and Redundant: Influence of CT Acquisition Parameters.

PubMed

Berenguer, Roberto; Pastor-Juan, María Del Rosario; Canales-Vázquez, Jesús; Castro-García, Miguel; Villas, María Victoria; Legorburo, Francisco Mansilla; Sabater, Sebastià

2018-04-24

Purpose To identify the reproducible and nonredundant radiomics features (RFs) for computed tomography (CT). Materials and Methods Two phantoms were used to test RF reproducibility by using test-retest analysis, by changing the CT acquisition parameters (hereafter, intra-CT analysis), and by comparing five different scanners with the same CT parameters (hereafter, inter-CT analysis). Reproducible RFs were selected by using the concordance correlation coefficient (as a measure of the agreement between variables) and the coefficient of variation (defined as the ratio of the standard deviation to the mean). Redundant features were grouped by using hierarchical cluster analysis. Results A total of 177 RFs including intensity, shape, and texture features were evaluated. The test-retest analysis showed that 91% (161 of 177) of the RFs were reproducible according to concordance correlation coefficient. Reproducibility of intra-CT RFs, based on coefficient of variation, ranged from 89.3% (151 of 177) to 43.1% (76 of 177) where the pitch factor and the reconstruction kernel were modified, respectively. Reproducibility of inter-CT RFs, based on coefficient of variation, also showed large material differences, from 85.3% (151 of 177; wood) to only 15.8% (28 of 177; polyurethane). Ten clusters were identified after the hierarchical cluster analysis and one RF per cluster was chosen as representative. Conclusion Many RFs were redundant and nonreproducible. If all the CT parameters are fixed except field of view, tube voltage, and milliamperage, then the information provided by the analyzed RFs can be summarized in only 10 RFs (each representing a cluster) because of redundancy. © RSNA, 2018 Online supplemental material is available for this article.

Hierarchical faunal filters: An approach to assessing effects of habitat and nonnative species on native fishes

USGS Publications Warehouse

Quist, M.C.; Rahel, F.J.; Hubert, W.A.

2005-01-01

Understanding factors related to the occurrence of species across multiple spatial and temporal scales is critical to the conservation and management of native fishes, especially for those species at the edge of their natural distribution. We used the concept of hierarchical faunal filters to provide a framework for investigating the influence of habitat characteristics and normative piscivores on the occurrence of 10 native fishes in streams of the North Platte River watershed in Wyoming. Three faunal filters were developed for each species: (i) large-scale biogeographic, (ii) local abiotic, and (iii) biotic. The large-scale biogeographic filter, composed of elevation and stream-size thresholds, was used to determine the boundaries within which each species might be expected to occur. Then, a local abiotic filter (i.e., habitat associations), developed using binary logistic-regression analysis, estimated the probability of occurrence of each species from features such as maximum depth, substrate composition, submergent aquatic vegetation, woody debris, and channel morphology (e.g., amount of pool habitat). Lastly, a biotic faunal filter was developed using binary logistic regression to estimate the probability of occurrence of each species relative to the abundance of nonnative piscivores in a reach. Conceptualising fish assemblages within a framework of hierarchical faunal filters is simple and logical, helps direct conservation and management activities, and provides important information on the ecology of fishes in the western Great Plains of North America. ?? Blackwell Munksgaard, 2004.

A Stochastic Model for Detecting Overlapping and Hierarchical Community Structure

PubMed Central

Cao, Xiaochun; Wang, Xiao; Jin, Di; Guo, Xiaojie; Tang, Xianchao

2015-01-01

Community detection is a fundamental problem in the analysis of complex networks. Recently, many researchers have concentrated on the detection of overlapping communities, where a vertex may belong to more than one community. However, most current methods require the number (or the size) of the communities as a priori information, which is usually unavailable in real-world networks. Thus, a practical algorithm should not only find the overlapping community structure, but also automatically determine the number of communities. Furthermore, it is preferable if this method is able to reveal the hierarchical structure of networks as well. In this work, we firstly propose a generative model that employs a nonnegative matrix factorization (NMF) formulization with a l2,1 norm regularization term, balanced by a resolution parameter. The NMF has the nature that provides overlapping community structure by assigning soft membership variables to each vertex; the l2,1 regularization term is a technique of group sparsity which can automatically determine the number of communities by penalizing too many nonempty communities; and hence the resolution parameter enables us to explore the hierarchical structure of networks. Thereafter, we derive the multiplicative update rule to learn the model parameters, and offer the proof of its correctness. Finally, we test our approach on a variety of synthetic and real-world networks, and compare it with some state-of-the-art algorithms. The results validate the superior performance of our new method. PMID:25822148

Clinical Phenotype of Diabetic Peripheral Neuropathy and Relation to Symptom Patterns: Cluster and Factor Analysis in Patients with Type 2 Diabetes in Korea.

PubMed

Won, Jong Chul; Im, Yong-Jin; Lee, Ji-Hyun; Kim, Chong Hwa; Kwon, Hyuk Sang; Cha, Bong-Yun; Park, Tae Sun

2017-01-01

Patients with diabetic peripheral neuropathy (DPN) is the most common complication. However, patients are usually suffering from not only diverse sensory deficit but also neuropathy-related discomforts. The aim of this study is to identify distinct groups of patients with DPN with respect to its clinical impacts on symptom patterns and comorbidities. A hierarchical cluster analysis and factor analysis were performed to identify relevant subgroups of patients with DPN ( n = 1338) and symptom patterns. Patients with DPN were divided into three clusters: asymptomatic (cluster 1, n = 448, 33.5%), moderate symptoms with disturbed sleep (cluster 2, n = 562, 42.0%), and severe symptoms with decreased quality of life (cluster 3, n = 328, 24.5%). Patients in cluster 3, compared with clusters 1 and 2, were characterized by higher levels of HbA1c and more severe pain and physical impairments. Patients in cluster 2 had moderate pain levels but disturbed sleep patterns comparable to those in cluster 3. The frequency of symptoms on each item of MNSI by "painful" symptom pattern showed a similar distribution pattern with increasing intensities along the three clusters. Cluster and factor analysis endorsed the use of comprehensive and symptomatic subgrouping to individualize the evaluation of patients with DPN.

Motivation and Self-Management Behavior of the Individuals With Chronic Low Back Pain.

PubMed

Jung, Mi Jung; Jeong, Younhee

2016-01-01

Self-management behavior is an important component for successful pain management in individuals with chronic low back pain. Motivation has been considered as an effective way to change behavior. Because there are other physical, social, and psychological factors affecting individuals with pain, it is necessary to identify the main effect of motivation on self-management behavior without the influence of those factors. The purpose of this study was to investigate the effect of motivation on self-management in controlling pain, depression, and social support. We used a nonexperimental, cross-sectional, descriptive design with mediation analysis and included 120 participants' data in the final analysis. We also used hierarchical multiple regression to test the effect of motivation, and multiple regression analysis and Sobel test were used to examine the mediating effect. Motivation itself accounted for 23.4% of the variance in self-management, F(1, 118) = 35.003, p < .001. After controlling covariates, motivation was also a significant factor for self-management. In the mediation analysis, motivation completely mediated the relationship between education and self-management, z = 2.292, p = .021. Motivation is an important part of self-management, and self-management education is not effective without motivation. The results of our study suggest that nurses incorporate motivation in nursing intervention, rather than only giving information.

Analysis of caries status development in relation to socio-economic variables using a case-based system.

PubMed

Swedberg, Y; Norén, J G

2001-01-01

The aim of this study was to detect, using case-based reasoning (CBR) induction methods in time series analysis, how measurable socio-economical adjustments were related to the caries status development. The study concerned the year classes leaving the organised dental care for the time period 1987-95, and had received dental care at the Public Dental Service of Göteborg. The results, as presented by a caries incidence index, indicated that at least one socioeconomical factor, individuals seeking employment, was of importance for the caries status development, a factor with an increase of considerable proportions since 1990. The findings indicated that the other socio-economic variables used did not have the same importance for the caries status development. One feasible explanation is that these factors reflect more upon the social family situation than the economical. If the caries status reflects the social situation of the individual more than the economical, this argument will elucidate the reasoning. Using CBR for the analysis of relationships between oral disease and parameters possibly influencing health development has proven to be a valuable tool and complement to more traditional statistical methods. The analysis can make relationships explicit through the hierarchic knowledge trees and also show redundant information, attributes not appearing in the trees.

Relationship between personality traits and vocational choice.

PubMed

Garcia-Sedeño, Manuel; Navarro, Jose I; Menacho, Inmaculada

2009-10-01

Summary.-The relationship between occupational preferences and personality traits was examined. A randomly chosen sample of 735 students (age range = 17 to 23 years; 50.5% male) in their last year of high school participated in this study. Participants completed Cattell's Sixteen Personality Factor-5 Questionnaire (16PF-5 Questionnaire) and the Kuder-C Professional Tendencies Questionnaire. Initial hierarchical cluster analysis categorized the participants into two groups by Kuder-C vocational factors: one showed a predilection for scientific or technological careers and the other a bias toward the humanities and social sciences. Based on these groupings, differences in 16PF-5 personality traits were analyzed and differences associated with three first-order personality traits (warmth, dominance, and sensitivity), three second-order factors (extraversion, control, and independence), and some areas of professional interest (mechanical, arithmetical artistic, persuasive, and welfare) were identified. The data indicated that there was congruency between personality profiles and vocational interests.

Psychometric properties and the predictive validity of the insomnia daytime worry scale: a pilot study.

PubMed

Kallestad, Håvard; Hansen, Bjarne; Langsrud, Knut; Hjemdal, Odin; Stiles, Tore C

2010-01-01

The relationship between presleep worry and insomnia has been investigated in previous studies, but less attention has been given to the role of daytime worry and symptoms of insomnia. The aims of the current study were (a) to assess the psychometric properties of a novel scale measuring insomnia-specific worry during daytime and (b) to examine whether levels of daytime worry predict severity of insomnia symptoms. Participants (N = 353) completed the Insomnia Daytime Worry Scale (IDWS) and the Insomnia Severity Index. An explorative principal-axis factor analysis extracted two factors from the IDWS, accounting for 70.5% of the variance. The IDWS demonstrated good reliability. The total score of IDWS and both factors predicted levels of insomnia severity in two separate hierarchical regression analyses. This preliminary evidence suggests that the IDWS is a valid and reliable scale to measure daytime worry in insomnia.

Limited association between perceived control and health-related quality of life in patients with heart failure.

PubMed

Banerjee, Teesta; Lee, Kyoung Suk; Browning, Steven R; Hopenhayn, Claudia; Westneat, Susan; Biddle, Martha J; Arslanian-Engoren, Cynthia; Eastwood, Jo-Ann; Mudd, Gia; Moser, Debra K

2014-01-01

Perceived control has been suggested as a modifiable factor associated with health-related quality of life (HRQOL). However, the relationship between perceived control and HRQOL has not been evaluated in patients with heart failure (HF). The purpose of this study was to determine whether perceived control independently predicts HRQOL in HF patients. A total of 423 HF patients were included. Hierarchical linear regression was performed to determine the independent association of perceived control to HRQOL after controlling for covariates. Higher levels of perceived control were associated with better HRQOL in univariate analysis. However, this relationship was strongly attenuated after controlling for relevant demographic, clinical, and psychological factors; the variance in HRQOL explained by the addition of perceived control to this model was small (1.4%). We found only a weak relationship between perceived control and HRQOL when considered in the presence of demographic, clinical, and psychological factors.

Self-efficacy in weight management.

PubMed

Clark, M M; Abrams, D B; Niaura, R S; Eaton, C A; Rossi, J S

1991-10-01

Self-efficacy is an important mediating mechanism in advancing understanding of the treatment of obesity. This study developed and validated the Weight Efficacy Life-Style Questionnaire (WEL), improving on previous studies by the use of clinical populations, cross-validation of the initial factor analysis, exploration of the best fitting theoretical model of self-efficacy, and examination of change in treatment. The resulting 20-item WEL consists of five situational factors: Negative Emotions, Availability, Social Pressure, Physical Discomfort, and Positive Activities. A hierarchical model was found to provide the best fit to the data. Results from two separate clinical treatment studies (total N = 382) show that the WEL is sensitive to changes in global scores as well as to a subset of the five situational factor scores. Treatment programs may be incomplete if they change only a subset of the situational dimensions of self-efficacy. Theoretical and clinical implications are discussed.

Spatial pattern of spring phytoplankton community in the coastal waters of northern Zhejiang, East China Sea

NASA Astrophysics Data System (ADS)

Ye, Ran; Cai, Yanhong; Wei, Yongjie; Li, Xiaoming

2017-04-01

The spatial pattern of phytoplankton community can indicate potential environmental variation in different water bodies. In this context, spatial pattern of phytoplankton community and its response to environmental and spatial factors were studied in the coastal waters of northern Zhejiang, East China Sea using multivariate statistical techniques. Results showed that 94 species belonging to 40 genera, 5 phyla were recorded (the remaining 9 were identified to genus level) with diatoms being the most dominant followed by dinoflagellates. Hierarchical clustering analysis (HCA), nonmetric multidimentional scaling (NMDS), and analysis of similarity (ANOSIM) all demomstrated that the whole study area could be divided into 3 subareas with significant differences. Indicator species analysis (ISA) further confirmed that the indicator species of each subarea correlated significantly with specific environmental factors. Distance-based linear model (Distlm) and Mantel test revealed that silicate (SiO32-), phosphate (PO43-), pH, and dissolved oxygen (DO) were the most important environmental factors influencing phytoplankton community. Variation portioning (VP) finally concluded that the shared fractions of environmental and spatial factors were higher than either the pure environmental effects or the pure spatial effects, suggesting phytoplankton biogeography were mainly affected by both the environmental variability and dispersal limitation. Additionally, other factors (eg., trace metals, biological grazing, climate change, and time-scale variation) may also be the sources of the unexplained variation which need further study.

Psychological factors influence the gastroesophageal reflux disease (GERD) and their effect on quality of life among firefighters in South Korea.

PubMed

Jang, Seung-Ho; Ryu, Han-Seung; Choi, Suck-Chei; Lee, Sang-Yeol

2016-10-01

The purpose of this study was to examine psychosocial factors related to gastroesophageal reflux disease (GERD) and their effects on quality of life (QOL) in firefighters. Data were collected from 1217 firefighters in a Korean province. We measured psychological symptoms using the scale. In order to observe the influence of the high-risk group on occupational stress, we conduct logistic multiple linear regression. The correlation between psychological factors and QOL was also analyzed and performed a hierarchical regression analysis. GERD was observed in 32.2% of subjects. Subjects with GERD showed higher depressive symptom, anxiety and occupational stress scores, and lower self-esteem and QOL scores relative to those observed in GERD - negative subject. GERD risk was higher for the following occupational stress subcategories: job demand, lack of reward, interpersonal conflict, and occupational climate. The stepwise regression analysis showed that depressive symptoms, occupational stress, self-esteem, and anxiety were the best predictors of QOL. The results suggest that psychological and medical approaches should be combined in GERD assessment.

Psychological factors influence the gastroesophageal reflux disease (GERD) and their effect on quality of life among firefighters in South Korea

PubMed Central

Jang, Seung-Ho; Ryu, Han-Seung; Choi, Suck-Chei; Lee, Sang-Yeol

2016-01-01

Objectives The purpose of this study was to examine psychosocial factors related to gastroesophageal reflux disease (GERD) and their effects on quality of life (QOL) in firefighters. Methods Data were collected from 1217 firefighters in a Korean province. We measured psychological symptoms using the scale. In order to observe the influence of the high-risk group on occupational stress, we conduct logistic multiple linear regression. The correlation between psychological factors and QOL was also analyzed and performed a hierarchical regression analysis. Results GERD was observed in 32.2% of subjects. Subjects with GERD showed higher depressive symptom, anxiety and occupational stress scores, and lower self-esteem and QOL scores relative to those observed in GERD – negative subject. GERD risk was higher for the following occupational stress subcategories: job demand, lack of reward, interpersonal conflict, and occupational climate. The stepwise regression analysis showed that depressive symptoms, occupational stress, self-esteem, and anxiety were the best predictors of QOL. Conclusions The results suggest that psychological and medical approaches should be combined in GERD assessment. PMID:27691373

Hierarchical Parallelization of Gene Differential Association Analysis

PubMed Central

2011-01-01

Background Microarray gene differential expression analysis is a widely used technique that deals with high dimensional data and is computationally intensive for permutation-based procedures. Microarray gene differential association analysis is even more computationally demanding and must take advantage of multicore computing technology, which is the driving force behind increasing compute power in recent years. In this paper, we present a two-layer hierarchical parallel implementation of gene differential association analysis. It takes advantage of both fine- and coarse-grain (with granularity defined by the frequency of communication) parallelism in order to effectively leverage the non-uniform nature of parallel processing available in the cutting-edge systems of today. Results Our results show that this hierarchical strategy matches data sharing behavior to the properties of the underlying hardware, thereby reducing the memory and bandwidth needs of the application. The resulting improved efficiency reduces computation time and allows the gene differential association analysis code to scale its execution with the number of processors. The code and biological data used in this study are downloadable from http://www.urmc.rochester.edu/biostat/people/faculty/hu.cfm. Conclusions The performance sweet spot occurs when using a number of threads per MPI process that allows the working sets of the corresponding MPI processes running on the multicore to fit within the machine cache. Hence, we suggest that practitioners follow this principle in selecting the appropriate number of MPI processes and threads within each MPI process for their cluster configurations. We believe that the principles of this hierarchical approach to parallelization can be utilized in the parallelization of other computationally demanding kernels. PMID:21936916

Hierarchical parallelization of gene differential association analysis.

PubMed

Needham, Mark; Hu, Rui; Dwarkadas, Sandhya; Qiu, Xing

2011-09-21

Microarray gene differential expression analysis is a widely used technique that deals with high dimensional data and is computationally intensive for permutation-based procedures. Microarray gene differential association analysis is even more computationally demanding and must take advantage of multicore computing technology, which is the driving force behind increasing compute power in recent years. In this paper, we present a two-layer hierarchical parallel implementation of gene differential association analysis. It takes advantage of both fine- and coarse-grain (with granularity defined by the frequency of communication) parallelism in order to effectively leverage the non-uniform nature of parallel processing available in the cutting-edge systems of today. Our results show that this hierarchical strategy matches data sharing behavior to the properties of the underlying hardware, thereby reducing the memory and bandwidth needs of the application. The resulting improved efficiency reduces computation time and allows the gene differential association analysis code to scale its execution with the number of processors. The code and biological data used in this study are downloadable from http://www.urmc.rochester.edu/biostat/people/faculty/hu.cfm. The performance sweet spot occurs when using a number of threads per MPI process that allows the working sets of the corresponding MPI processes running on the multicore to fit within the machine cache. Hence, we suggest that practitioners follow this principle in selecting the appropriate number of MPI processes and threads within each MPI process for their cluster configurations. We believe that the principles of this hierarchical approach to parallelization can be utilized in the parallelization of other computationally demanding kernels.

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…

The Local Minima Problem in Hierarchical Classes Analysis: An Evaluation of a Simulated Annealing Algorithm and Various Multistart Procedures

ERIC Educational Resources Information Center

Ceulemans, Eva; Van Mechelen, Iven; Leenen, Iwin

2007-01-01

Hierarchical classes models are quasi-order retaining Boolean decomposition models for N-way N-mode binary data. To fit these models to data, rationally started alternating least squares (or, equivalently, alternating least absolute deviations) algorithms have been proposed. Extensive simulation studies showed that these algorithms succeed quite…

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…

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…

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…

3D hierarchical Ag nanostructures formed on poly(acrylic acid) brushes grafted graphene oxide as promising SERS substrates

NASA Astrophysics Data System (ADS)

Xing, Guoke; Wang, Ke; Li, Ping; Wang, Wenqin; Chen, Tao

2018-03-01

In this study, in situ generation of Ag nanostructures with various morphology on poly(acrylic acid) (PAA) brushes grafted onto graphene oxide (GO), for use as substrates for surface-enhanced Raman scattering (SERS), is demonstrated. The overall synthetic strategy involves the loading of Ag precursor ions ((Ag+ and [Ag(NH3)2]+) onto PAA brush-grafted GO, followed by their in situ reduction to Ag nanostructures of various morphology using a reducing agent (NaBH4 or ascorbic acid). Novel 3D hierarchical flowerlike Ag nanostructures were obtained by using AgNO3 as precursor and ascorbic acid as reducing agent. Using 4-aminothiophenol as probe molecules, the as-prepared hierarchical Ag nanostructures exhibited excellent SERS performance, providing enhancement factors of ˜107.

Understanding seasonal variability of uncertainty in hydrological prediction

NASA Astrophysics Data System (ADS)

Li, M.; Wang, Q. J.

2012-04-01

Understanding uncertainty in hydrological prediction can be highly valuable for improving the reliability of streamflow prediction. In this study, a monthly water balance model, WAPABA, in a Bayesian joint probability with error models are presented to investigate the seasonal dependency of prediction error structure. A seasonal invariant error model, analogous to traditional time series analysis, uses constant parameters for model error and account for no seasonal variations. In contrast, a seasonal variant error model uses a different set of parameters for bias, variance and autocorrelation for each individual calendar month. Potential connection amongst model parameters from similar months is not considered within the seasonal variant model and could result in over-fitting and over-parameterization. A hierarchical error model further applies some distributional restrictions on model parameters within a Bayesian hierarchical framework. An iterative algorithm is implemented to expedite the maximum a posterior (MAP) estimation of a hierarchical error model. Three error models are applied to forecasting streamflow at a catchment in southeast Australia in a cross-validation analysis. This study also presents a number of statistical measures and graphical tools to compare the predictive skills of different error models. From probability integral transform histograms and other diagnostic graphs, the hierarchical error model conforms better to reliability when compared to the seasonal invariant error model. The hierarchical error model also generally provides the most accurate mean prediction in terms of the Nash-Sutcliffe model efficiency coefficient and the best probabilistic prediction in terms of the continuous ranked probability score (CRPS). The model parameters of the seasonal variant error model are very sensitive to each cross validation, while the hierarchical error model produces much more robust and reliable model parameters. Furthermore, the result of the hierarchical error model shows that most of model parameters are not seasonal variant except for error bias. The seasonal variant error model is likely to use more parameters than necessary to maximize the posterior likelihood. The model flexibility and robustness indicates that the hierarchical error model has great potential for future streamflow predictions.

Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data.

PubMed

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D; Nichols, Thomas E

2018-03-01

Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to (i) identify areas of consistent activation; and (ii) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterized as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. © 2017, The International Biometric Society.

Hierarchic models for laminated plates. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Actis, Ricardo Luis

1991-01-01

Structural plates and shells are three-dimensional bodies, one dimension of which happens to be much smaller than the other two. Thus, the quality of a plate or shell model must be judged on the basis of how well its exact solution approximates the corresponding three-dimensional problem. Of course, the exact solution depends not only on the choice of the model but also on the topology, material properties, loading and constraints. The desired degree of approximation depends on the analyst's goals in performing the analysis. For these reasons models have to be chosen adaptively. Hierarchic sequences of models make adaptive selection of the model which is best suited for the purposes of a particular analysis possible. The principles governing the formulation of hierarchic models for laminated plates are presented. The essential features of the hierarchic models described models are: (1) the exact solutions corresponding to the hierarchic sequence of models converge to the exact solution of the corresponding problem of elasticity for a fixed laminate thickness; and (2) the exact solution of each model converges to the same limit as the exact solution of the corresponding problem of elasticity with respect to the laminate thickness approaching zero. The formulation is based on one parameter (beta) which characterizes the hierarchic sequence of models, and a set of constants whose influence was assessed by a numerical sensitivity study. The recommended selection of these constants results in the number of fields increasing by three for each increment in the power of beta. Numerical examples analyzed with the proposed sequence of models are included and good correlation with the reference solutions was found. Results were obtained for laminated strips (plates in cylindrical bending) and for square and rectangular plates with uniform loading and with homogeneous boundary conditions. Cross-ply and angle-ply laminates were evaluated and the results compared with those of MSC/PROBE. Hierarchic models make the computation of any engineering data possible to an arbitrary level of precision within the framework of the theory of elasticity.

Orthogonal Higher Order Structure of the WISC-IV Spanish Using Hierarchical Exploratory Factor Analytic Procedures

ERIC Educational Resources Information Center

McGill, Ryan J.; Canivez, Gary L.

2016-01-01

As recommended by Carroll, the present study examined the factor structure of the Wechsler Intelligence Scale for Children-Fourth Edition Spanish (WISC-IV Spanish) normative sample using higher order exploratory factor analytic techniques not included in the WISC-IV Spanish Technical Manual. Results indicated that the WISC-IV Spanish subtests were…

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.

Epidemic spreading on hierarchical geographical networks with mobile agents

NASA Astrophysics Data System (ADS)

Han, Xiao-Pu; Zhao, Zhi-Dan; Hadzibeganovic, Tarik; Wang, Bing-Hong

2014-05-01

Hierarchical geographical traffic networks are critical for our understanding of scaling laws in human trajectories. Here, we investigate the susceptible-infected epidemic process evolving on hierarchical networks in which agents randomly walk along the edges and establish contacts in network nodes. We employ a metapopulation modeling framework that allows us to explore the contagion spread patterns in relation to multi-scale mobility behaviors. A series of computer simulations revealed that a shifted power-law-like negative relationship between the peak timing of epidemics τ0 and population density, and a logarithmic positive relationship between τ0 and the network size, can both be explained by the gradual enlargement of fluctuations in the spreading process. We employ a semi-analytical method to better understand the nature of these relationships and the role of pertinent demographic factors. Additionally, we provide a quantitative discussion of the efficiency of a border screening procedure in delaying epidemic outbreaks on hierarchical networks, yielding a rather limited feasibility of this mitigation strategy but also its non-trivial dependence on population density, infector detectability, and the diversity of the susceptible region. Our results suggest that the interplay between the human spatial dynamics, network topology, and demographic factors can have important consequences for the global spreading and control of infectious diseases. These findings provide novel insights into the combined effects of human mobility and the organization of geographical networks on spreading processes, with important implications for both epidemiological research and health policy.

Quantum chemical calculations in the structural analysis of phloretin

NASA Astrophysics Data System (ADS)

Gómez-Zavaglia, Andrea

2009-07-01

In this work, a conformational search on the molecule of phloretin [2',4',6'-Trihydroxy-3-(4-hydroxyphenyl)-propiophenone] has been performed. The molecule of phloretin has eight dihedral angles, four of them taking part in the carbon backbone and the other four, related with the orientation of the hydroxyl groups. A systematic search involving a random variation of the dihedral angles has been used to generate input structures for the quantum chemical calculations. Calculations at the DFT(B3LYP)/6-311++G(d,p) level of theory permitted the identification of 58 local minima belonging to the C 1 symmetry point group. The molecular structures of the conformers have been analyzed using hierarchical cluster analysis. This method allowed us to group conformers according to their similarities, and thus, to correlate the conformers' stability with structural parameters. The dendrogram obtained from the hierarchical cluster analysis depicted two main clusters. Cluster I included all the conformers with relative energies lower than 25 kJ mol -1 and cluster II, the remaining conformers. The possibility of forming intramolecular hydrogen bonds resulted the main factor contributing for the stability. Accordingly, all conformers depicting intramolecular H-bonds belong to cluster I. These conformations are clearly favored when the carbon backbone is as planar as possible. The values of the νC dbnd O and νOH vibrational modes were compared among all the conformers of phloretin. The redshifts associated with intramolecular H-bonds were correlated with the H-bonds distances and energies.

INVESTIGATING DIFFERENCES IN BRAIN FUNCTIONAL NETWORKS USING HIERARCHICAL COVARIATE-ADJUSTED INDEPENDENT COMPONENT ANALYSIS.

PubMed

Shi, Ran; Guo, Ying

2016-12-01

Human brains perform tasks via complex functional networks consisting of separated brain regions. A popular approach to characterize brain functional networks in fMRI studies is independent component analysis (ICA), which is a powerful method to reconstruct latent source signals from their linear mixtures. In many fMRI studies, an important goal is to investigate how brain functional networks change according to specific clinical and demographic variabilities. Existing ICA methods, however, cannot directly incorporate covariate effects in ICA decomposition. Heuristic post-ICA analysis to address this need can be inaccurate and inefficient. In this paper, we propose a hierarchical covariate-adjusted ICA (hc-ICA) model that provides a formal statistical framework for estimating covariate effects and testing differences between brain functional networks. Our method provides a more reliable and powerful statistical tool for evaluating group differences in brain functional networks while appropriately controlling for potential confounding factors. We present an analytically tractable EM algorithm to obtain maximum likelihood estimates of our model. We also develop a subspace-based approximate EM that runs significantly faster while retaining high accuracy. To test the differences in functional networks, we introduce a voxel-wise approximate inference procedure which eliminates the need of computationally expensive covariance matrix estimation and inversion. We demonstrate the advantages of our methods over the existing method via simulation studies. We apply our method to an fMRI study to investigate differences in brain functional networks associated with post-traumatic stress disorder (PTSD).

Phrase Mining of Textual Data to Analyze Extracellular Matrix Protein Patterns Across Cardiovascular Disease.

PubMed

Liem, David Alexandre; Murali, Sanjana; Sigdel, Dibakar; Shi, Yu; Wang, Xuan; Shen, Jiaming; Choi, Howard; Caufield, J Harry; Wang, Wei; Ping, Peipei; Han, Jiawei

2018-05-18

Extracellular matrix (ECM) proteins have been shown to play important roles regulating multiple biological processes in an array of organ systems, including the cardiovascular system. By using a novel bioinformatics text-mining tool, we studied six categories of cardiovascular disease (CVD), namely ischemic heart disease (IHD), cardiomyopathies (CM), cerebrovascular accident (CVA), congenital heart disease (CHD), arrhythmias (ARR), and valve disease (VD), anticipating novel ECM protein-disease and protein-protein relationships hidden within vast quantities of textual data. We conducted a phrase-mining analysis, delineating the relationships of 709 ECM proteins with the six groups of CVDs reported in 1,099,254 abstracts. The technology pipeline known as Context-aware Semantic Online Analytical Processing (CaseOLAP) was applied to semantically rank the association of proteins to each and all six CVDs, performing analyses to quantify each protein-disease relationship. We performed principal component analysis and hierarchical clustering of the data, where each protein is visualized as a six dimensional vector. We found that ECM proteins display variable degrees of association with the six CVDs; certain CVDs share groups of associated proteins whereas others have divergent protein associations. We identified 82 ECM proteins sharing associations with all six CVDs. Our bioinformatics analysis ascribed distinct ECM pathways (via Reactome) from this subset of proteins, namely insulin-like growth factor regulation and interleukin-4 and interleukin-13 signaling, suggesting their contribution to the pathogenesis of all six CVDs. Finally, we performed hierarchical clustering analysis and identified protein clusters associated with a targeted CVD; analyses revealed unexpected insights underlying ECM-pathogenesis of CVDs.

Brief Report: Bifactor Modeling of General vs. Specific Factors of Religiousness Differentially Predicting Substance Use Risk in Adolescence

PubMed Central

Kim-Spoon, Jungmeen; Longo, Gregory S.; Holmes, Christopher J.

2015-01-01

Religiousness is important to adolescents in the U.S., and the significant link between high religiousness and low substance use is well known. There is a debate between multidimensional and unidimensional perspectives of religiousness (Gorsuch, 1984); yet, no empirical study has tested this hierarchical model of religiousness related to adolescent health outcomes. The current study presents the first attempt to test a bifactor model of religiousness related to substance use among adolescents (N = 220, 45% female). Our bifactor model using structural equation modeling suggested the multidimensional nature of religiousness as well as the presence of a superordinate general religiousness factor directly explaining the covariation among the specific factors including organizational and personal religiousness and religious social support. The general religiousness factor was inversely related to substance use. After accounting for the contribution of the general religiousness factor, high organizational religiousness related to low substance use, whereas personal religiousness and religious support were positively related to substance use. The findings present the first evidence that supports hierarchical structures of adolescent religiousness that contribute differentially to adolescent substance use. PMID:26043168

Stigma of People with Epilepsy in China: Views of health professionals, teachers, employers and community leaders

PubMed Central

Yang, Rongrong; Wang, Wenzhi; Snape, Dee; Chen, Gong; Zhang, Lei; Wu, Jianzhong; Baker, Gus A; Zheng, Xiaoying; Jacoby, Ann

2011-01-01

To identify the possible sources of stigma of epilepsy in key informant groups, “mini-ethnographic” studies were conducted in rural and urban locations in China. Data from 45 semi-structured interviews and 8 focus group discussions (6 persons each) were analysed to investigate the world experienced by people with epilepsy. Underpinned by a social constructionist approach to data analysis, emerging themes were identified with the use of computer-assisted data analysis (NVivo 8). A hierarchical model was then constructed, to include: Practical Level issues: attitudes to risk, attitudes towards costs of epilepsy; and Cultural Level issues: the contrast between rurality and tradition and urbanization and modernity in the Chinese context. The analysis enriches current research on factors and sources of stigma of epilepsy and highlights issues for future practice. PMID:21606005

Effects of additional data on Bayesian clustering.

PubMed

Yamazaki, Keisuke

2017-10-01

Hierarchical probabilistic models, such as mixture models, are used for cluster analysis. These models have two types of variables: observable and latent. In cluster analysis, the latent variable is estimated, and it is expected that additional information will improve the accuracy of the estimation of the latent variable. Many proposed learning methods are able to use additional data; these include semi-supervised learning and transfer learning. However, from a statistical point of view, a complex probabilistic model that encompasses both the initial and additional data might be less accurate due to having a higher-dimensional parameter. The present paper presents a theoretical analysis of the accuracy of such a model and clarifies which factor has the greatest effect on its accuracy, the advantages of obtaining additional data, and the disadvantages of increasing the complexity. Copyright © 2017 Elsevier Ltd. All rights reserved.

GOTHIC: Gravitational oct-tree code accelerated by hierarchical time step controlling

NASA Astrophysics Data System (ADS)

Miki, Yohei; Umemura, Masayuki

2017-04-01

The tree method is a widely implemented algorithm for collisionless N-body simulations in astrophysics well suited for GPU(s). Adopting hierarchical time stepping can accelerate N-body simulations; however, it is infrequently implemented and its potential remains untested in GPU implementations. We have developed a Gravitational Oct-Tree code accelerated by HIerarchical time step Controlling named GOTHIC, which adopts both the tree method and the hierarchical time step. The code adopts some adaptive optimizations by monitoring the execution time of each function on-the-fly and minimizes the time-to-solution by balancing the measured time of multiple functions. Results of performance measurements with realistic particle distribution performed on NVIDIA Tesla M2090, K20X, and GeForce GTX TITAN X, which are representative GPUs of the Fermi, Kepler, and Maxwell generation of GPUs, show that the hierarchical time step achieves a speedup by a factor of around 3-5 times compared to the shared time step. The measured elapsed time per step of GOTHIC is 0.30 s or 0.44 s on GTX TITAN X when the particle distribution represents the Andromeda galaxy or the NFW sphere, respectively, with 224 = 16,777,216 particles. The averaged performance of the code corresponds to 10-30% of the theoretical single precision peak performance of the GPU.

Quantitative analysis of organizational culture in occupational health research: a theory-based validation in 30 workplaces of the organizational culture profile instrument.

PubMed

Marchand, Alain; Haines, Victor Y; Dextras-Gauthier, Julie

2013-05-04

This study advances a measurement approach for the study of organizational culture in population-based occupational health research, and tests how different organizational culture types are associated with psychological distress, depression, emotional exhaustion, and well-being. Data were collected over a sample of 1,164 employees nested in 30 workplaces. Employees completed the 26-item OCP instrument. Psychological distress was measured with the General Health Questionnaire (12-item); depression with the Beck Depression Inventory (21-item); and emotional exhaustion with five items from the Maslach Burnout Inventory general survey. Exploratory factor analysis evaluated the dimensionality of the OCP scale. Multilevel regression models estimated workplace-level variations, and the contribution of organizational culture factors to mental health and well-being after controlling for gender, age, and living with a partner. Exploratory factor analysis of OCP items revealed four factors explaining about 75% of the variance, and supported the structure of the Competing Values Framework. Factors were labeled Group, Hierarchical, Rational and Developmental. Cronbach's alphas were high (0.82-0.89). Multilevel regression analysis suggested that the four culture types varied significantly between workplaces, and correlated with mental health and well-being outcomes. The Group culture type best distinguished between workplaces and had the strongest associations with the outcomes. This study provides strong support for the use of the OCP scale for measuring organizational culture in population-based occupational health research in a way that is consistent with the Competing Values Framework. The Group organizational culture needs to be considered as a relevant factor in occupational health studies.

Asthma exacerbations in children immediately following stressful life events: a Cox's hierarchical regression.

PubMed

Sandberg, S; Järvenpää, S; Penttinen, A; Paton, J Y; McCann, D C

2004-12-01

A recent prospective study of children with asthma employing a within subject, over time analysis using dynamic logistic regression showed that severely negative life events significantly increased the risk of an acute exacerbation during the subsequent 6 week period. The timing of the maximum risk depended on the degree of chronic psychosocial stress also present. A hierarchical Cox regression analysis was undertaken to examine whether there were any immediate effects of negative life events in children without a background of high chronic stress. Sixty children with verified chronic asthma were followed prospectively for 18 months with continuous monitoring of asthma by daily symptom diaries and peak flow measurements, accompanied by repeated interview assessments of life events. The key outcome measures were asthma exacerbations and severely negative life events. An immediate effect evident within the first 2 days following a severely negative life event increased the risk of a new asthma attack by a factor of 4.69, 95% confidence interval 2.33 to 9.44 (p<0.001) [corrected] In the period 3-10 days after a severe event there was no increased risk of an asthma attack (p = 0.5). In addition to the immediate effect, an increased risk of 1.81 (95% confidence interval 1.24 to 2.65) [corrected] was found 5-7 weeks after a severe event (p = 0.002). This is consistent with earlier findings. There was a statistically significant variation due to unobserved factors in the incidence of asthma attacks between the children. The use of statistical methods capable of investigating short time lags showed that stressful life events significantly increase the risk of a new asthma attack immediately after the event; a more delayed increase in risk was also evident 5-7 weeks later.

Bayesian Poisson hierarchical models for crash data analysis: Investigating the impact of model choice on site-specific predictions.

PubMed

Khazraee, S Hadi; Johnson, Valen; Lord, Dominique

2018-08-01

The Poisson-gamma (PG) and Poisson-lognormal (PLN) regression models are among the most popular means for motor vehicle crash data analysis. Both models belong to the Poisson-hierarchical family of models. While numerous studies have compared the overall performance of alternative Bayesian Poisson-hierarchical models, little research has addressed the impact of model choice on the expected crash frequency prediction at individual sites. This paper sought to examine whether there are any trends among candidate models predictions e.g., that an alternative model's prediction for sites with certain conditions tends to be higher (or lower) than that from another model. In addition to the PG and PLN models, this research formulated a new member of the Poisson-hierarchical family of models: the Poisson-inverse gamma (PIGam). Three field datasets (from Texas, Michigan and Indiana) covering a wide range of over-dispersion characteristics were selected for analysis. This study demonstrated that the model choice can be critical when the calibrated models are used for prediction at new sites, especially when the data are highly over-dispersed. For all three datasets, the PIGam model would predict higher expected crash frequencies than would the PLN and PG models, in order, indicating a clear link between the models predictions and the shape of their mixing distributions (i.e., gamma, lognormal, and inverse gamma, respectively). The thicker tail of the PIGam and PLN models (in order) may provide an advantage when the data are highly over-dispersed. The analysis results also illustrated a major deficiency of the Deviance Information Criterion (DIC) in comparing the goodness-of-fit of hierarchical models; models with drastically different set of coefficients (and thus predictions for new sites) may yield similar DIC values, because the DIC only accounts for the parameters in the lowest (observation) level of the hierarchy and ignores the higher levels (regression coefficients). Copyright © 2018. Published by Elsevier Ltd.

Appreciating Complexity in Adolescent Self-Harm Risk Factors: Psychological Profiling in a Longitudinal Community Sample.

PubMed

Stanford, Sarah; Jones, Michael P; Hudson, Jennifer L

2018-05-01

Past research identifies a number of risk factors for adolescent self-harm, but often fails to account for overlap between these factors. This study investigated the underlying, broader concepts by identifying different psychological profiles among adolescents. We then compared new self-harm rates over a six-month period across different psychological profiles. Australian high school students (n = 326, 68.1% female) completed a questionnaire including a broad range of psychological and socioenvironmental risk and protective factors. Non-hierarchical cluster analysis produced six groups with different psychological profiles at baseline and rate of new self-harm at follow-up. The lowest rate was 1.4% in a group that appeared psychologically healthy; the highest rate was 37.5% in a group that displayed numerous psychological difficulties. Four groups with average self-harm had varied psychological profiles including low impulsivity, anxiety, impulsivity, and poor use of positive coping strategies. Identifying multiple profiles with distinct psychological characteristics can improve detection, guide prevention, and tailor treatment.

Prospective Predictors of Body Dissatisfaction in Young Adults: 10-year Longitudinal Findings

PubMed Central

Quick, Virginia; Eisenberg, Marla E.; Bucchianeri, Michaela M.; Neumark-Sztainer, Dianne

2014-01-01

This study identified longitudinal risk factors for body dissatisfaction (BD) over a 10-year period from adolescence to young adulthood. Participants (N = 2134; age at baseline: M =15.0, SD =1.6 years) provided two waves of survey data. A 6-step hierarchical linear regression analysis examined the predictive contribution of Time 1 BD, weight status, demographics, family and peer environmental factors, and psychological factors. Among females, Asian race/ethnicity, low self-esteem, greater BD, and higher body mass index during adolescence contributed significantly to predicting greater BD at 10-year follow up (R2 = 0.27). Among males, demographics (i.e., Asian, other-mixed ethnicity, education attainment), depressive symptoms, greater BD, higher body mass index, more parent communication, and less peer weight teasing during adolescence contributed to BD at follow-up (R2 = 0.27). Findings indicate who may be at greatest risk for BD in young adulthood and the types of factors that should be addressed during adolescence. PMID:25045599

Risk factors for infection with Giardia duodenalis in pre-school children in the city of Salvador, Brazil.

PubMed Central

Prado, M. S.; Strina, A.; Barreto, M. L.; Oliveira-Assis, Ana Marlúcia; Paz, Lívia Maria; Cairncross, S.

2003-01-01

A cross-sectional study of 694 children aged 2 to 45 months selected from 30 clusters throughout the city of Salvador, Bahia (pop. 2.3 million) was carried out as part of a longitudinal study of diarrhoea in order to identify risk factors for infection with Giardia duodenalis. Variables studied included three social and demographic factors (such as mother's education and marital status), five relating to the peri-domestic environment (rubbish disposal, open sewers, paving of the street), seven relating to the home itself (house construction, susceptibility to flooding, water supply and sanitation) as well as a score for hygiene behaviour based on structured observation. After multivariate analysis using a hierarchical model, only four significant risk factors were found: (a) number of children in the household under five years (b) rubbish not collected from the house (c) presence of visible sewage nearby, and (d) absence of a toilet. All four were significant at the 1% level. PMID:14596531

Psychosocial correlates of HIV protection motivation among black adolescents in Venda, South Africa.

PubMed

Boer, Henk; Mashamba, M Tshilidzi

2005-12-01

We assessed the usefulness of the theory of planned behavior (TPB) and protection motivation theory (PMT) to predict intended condom use among 201 adolescents from Venda, South Africa. Results indicated that both the TPB and the PMT could significantly predict intended condom use, although the level of explained variance was limited. Hierarchical regression analysis indicated that there was considerable overlap between the TPB and the PMT in predicting condom use intention. In the regression analysis that used both the TPB and the PMT variables subjective norms and response efficacy were positively related to intended condom use. The results indicated that both the TPB and the PMT were valuable in explaining intended condom use among African adolescents. The TPB made clear that the social environment is an important contextual factor, whereas the PMT made clear that response efficacy is positively related to condom use intention. The results of this study indicated that social cognition models have some value in the analysis of condom use intention of African adolescents, but the role of other factors like myths about condoms should be further examined.

Analysis of interstellar cloud structure based on IRAS images

NASA Technical Reports Server (NTRS)

Scalo, John M.

1992-01-01

The goal of this project was to develop new tools for the analysis of the structure of densely sampled maps of interstellar star-forming regions. A particular emphasis was on the recognition and characterization of nested hierarchical structure and fractal irregularity, and their relation to the level of star formation activity. The panoramic IRAS images provided data with the required range in spatial scale, greater than a factor of 100, and in column density, greater than a factor of 50. In order to construct densely sampled column density maps of star-forming clouds, column density images of four nearby cloud complexes were constructed from IRAS data. The regions have various degrees of star formation activity, and most of them have probably not been affected much by the disruptive effects of young massive stars. The largest region, the Scorpius-Ophiuchus cloud complex, covers about 1000 square degrees (it was subdivided into a few smaller regions for analysis). Much of the work during the early part of the project focused on an 80 square degree region in the core of the Taurus complex, a well-studied region of low-mass star formation.

Application of hierarchical cascading technique to finite element method simulation in bulk acoustic wave devices

NASA Astrophysics Data System (ADS)

Li, Xinyi; Bao, Jingfu; Huang, Yulin; Zhang, Benfeng; Omori, Tatsuya; Hashimoto, Ken-ya

2018-07-01

In this paper, we propose the use of the hierarchical cascading technique (HCT) for the finite element method (FEM) analysis of bulk acoustic wave (BAW) devices. First, the implementation of this technique is presented for the FEM analysis of BAW devices. It is shown that the traveling-wave excitation sources proposed by the authors are fully compatible with the HCT. Furthermore, a HCT-based absorbing mechanism is also proposed to replace the perfectly matched layer (PML). Finally, it is demonstrated how the technique is much more efficient in terms of memory consumption and execution time than the full FEM analysis.

A hierarchical structure for automatic meshing and adaptive FEM analysis

NASA Technical Reports Server (NTRS)

Kela, Ajay; Saxena, Mukul; Perucchio, Renato

1987-01-01

A new algorithm for generating automatically, from solid models of mechanical parts, finite element meshes that are organized as spatially addressable quaternary trees (for 2-D work) or octal trees (for 3-D work) is discussed. Because such meshes are inherently hierarchical as well as spatially addressable, they permit efficient substructuring techniques to be used for both global analysis and incremental remeshing and reanalysis. The global and incremental techniques are summarized and some results from an experimental closed loop 2-D system in which meshing, analysis, error evaluation, and remeshing and reanalysis are done automatically and adaptively are presented. The implementation of 3-D work is briefly discussed.

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…

One-pot pseudomorphic crystallization of mesoporous porous silica to hierarchical porous zeolites

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

Xing, Jun-Ling; Jiang, Shu-Hua; Pang, Jun-Ling

2015-09-15

Hierarchically porous silica with mesopore and zeolitic micropore was synthesized via pseudomorphic crystallization under high-temperature hydrothermal treatment in the presence of cetyltrimethylammonium tosylate and tetrapropylammonium ions. A combined characterization using small-angle X-ray diffraction (XRD), nitrogen adsorption, high-resolution transmission electron microscopy (TEM), thermogravimetric analysis (TG), and elemental analysis showed that dual templates, CTA{sup +} and TPA{sup +} molecules, can work in a cooperative manner to synthesize mesoporous zeolite in a one-pot system by precisely tuning the reaction conditions, such as reaction time and temperature, and type and amount of heterometal atoms. It is found that the presence of Ti precursor ismore » critical to the successful synthesis of such nanostructure. It not only retards the nucleation and growth of crystalline MFI domains, but also acts as nano-binder or nano-glue to favor the assembly of zeolite nanoblocks. - Graphical abstract: Display Omitted - Highlights: • A facile method to synthesize mesoporous zeolites with hierarchical porosity was presented. • It gives a new insight into keeping the balance between mesoscopic and molecular ordering in hierarchical porous materials. • A new understanding on the solid–solid transformation mechanism for the synthesis of titanosilicate zeolites was proposed.« less

Hierarchical models and Bayesian analysis of bird survey information

USGS Publications Warehouse

Sauer, J.R.; Link, W.A.; Royle, J. Andrew; Ralph, C. John; Rich, Terrell D.

2005-01-01

Summary of bird survey information is a critical component of conservation activities, but often our summaries rely on statistical methods that do not accommodate the limitations of the information. Prioritization of species requires ranking and analysis of species by magnitude of population trend, but often magnitude of trend is a misleading measure of actual decline when trend is poorly estimated. Aggregation of population information among regions is also complicated by varying quality of estimates among regions. Hierarchical models provide a reasonable means of accommodating concerns about aggregation and ranking of quantities of varying precision. In these models the need to consider multiple scales is accommodated by placing distributional assumptions on collections of parameters. For collections of species trends, this allows probability statements to be made about the collections of species-specific parameters, rather than about the estimates. We define and illustrate hierarchical models for two commonly encountered situations in bird conservation: (1) Estimating attributes of collections of species estimates, including ranking of trends, estimating number of species with increasing populations, and assessing population stability with regard to predefined trend magnitudes; and (2) estimation of regional population change, aggregating information from bird surveys over strata. User-friendly computer software makes hierarchical models readily accessible to scientists.

Bayesian Analysis of the Association between Family-Level Factors and Siblings' Dental Caries.

PubMed

Wen, A; Weyant, R J; McNeil, D W; Crout, R J; Neiswanger, K; Marazita, M L; Foxman, B

2017-07-01

We conducted a Bayesian analysis of the association between family-level socioeconomic status and smoking and the prevalence of dental caries among siblings (children from infant to 14 y) among children living in rural and urban Northern Appalachia using data from the Center for Oral Health Research in Appalachia (COHRA). The observed proportion of siblings sharing caries was significantly different from predicted assuming siblings' caries status was independent. Using a Bayesian hierarchical model, we found the inclusion of a household factor significantly improved the goodness of fit. Other findings showed an inverse association between parental education and siblings' caries and a positive association between households with smokers and siblings' caries. Our study strengthens existing evidence suggesting that increased parental education and decreased parental cigarette smoking are associated with reduced childhood caries in the household. Our results also demonstrate the value of a Bayesian approach, which allows us to include household as a random effect, thereby providing more accurate estimates than obtained using generalized linear mixed models.

Desire thinking: A risk factor for binge eating?

PubMed

Spada, Marcantonio M; Caselli, Gabriele; Fernie, Bruce A; Manfredi, Chiara; Boccaletti, Fabio; Dallari, Giulia; Gandini, Federica; Pinna, Eleonora; Ruggiero, Giovanni M; Sassaroli, Sandra

2015-08-01

In the current study we explored the role of desire thinking in predicting binge eating independently of Body Mass Index, negative affect and irrational food beliefs. A sample of binge eaters (n=77) and a sample of non-binge eaters (n=185) completed the following self-report instruments: Hospital Anxiety and Depression Scale, Irrational Food Beliefs Scale, Desire Thinking Questionnaire, and Binge Eating Scale. Mann-Whitney U tests revealed that all variable scores were significantly higher for binge eaters than non-binge eaters. A logistic regression analysis indicated that verbal perseveration was a predictor of classification as a binge eater over and above Body Mass Index, negative affect and irrational food beliefs. A hierarchical regression analysis, on the combined sample, indicated that verbal perseveration predicted levels of binge eating independently of Body Mass Index, negative affect and irrational food beliefs. These results highlight the possible role of desire thinking as a risk factor for binge eating. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modeling association among demographic parameters in analysis of open population capture-recapture data.

PubMed

Link, William A; Barker, Richard J

2005-03-01

We present a hierarchical extension of the Cormack-Jolly-Seber (CJS) model for open population capture-recapture data. In addition to recaptures of marked animals, we model first captures of animals and losses on capture. The parameter set includes capture probabilities, survival rates, and birth rates. The survival rates and birth rates are treated as a random sample from a bivariate distribution, thus the model explicitly incorporates correlation in these demographic rates. A key feature of the model is that the likelihood function, which includes a CJS model factor, is expressed entirely in terms of identifiable parameters; losses on capture can be factored out of the model. Since the computational complexity of classical likelihood methods is prohibitive, we use Markov chain Monte Carlo in a Bayesian analysis. We describe an efficient candidate-generation scheme for Metropolis-Hastings sampling of CJS models and extensions. The procedure is illustrated using mark-recapture data for the moth Gonodontis bidentata.

Modeling association among demographic parameters in analysis of open population capture-recapture data

USGS Publications Warehouse

Link, William A.; Barker, Richard J.

2005-01-01

We present a hierarchical extension of the Cormack–Jolly–Seber (CJS) model for open population capture–recapture data. In addition to recaptures of marked animals, we model first captures of animals and losses on capture. The parameter set includes capture probabilities, survival rates, and birth rates. The survival rates and birth rates are treated as a random sample from a bivariate distribution, thus the model explicitly incorporates correlation in these demographic rates. A key feature of the model is that the likelihood function, which includes a CJS model factor, is expressed entirely in terms of identifiable parameters; losses on capture can be factored out of the model. Since the computational complexity of classical likelihood methods is prohibitive, we use Markov chain Monte Carlo in a Bayesian analysis. We describe an efficient candidate-generation scheme for Metropolis–Hastings sampling of CJS models and extensions. The procedure is illustrated using mark-recapture data for the moth Gonodontis bidentata.

Environmental Factors Affecting Brook Trout Occurrence in Headwater Stream Segments

Treesearch

Yoichiro Kanno; Benjamin H. Letcher; Ana L. Rosner; Kyle P. O' Neil; Keith H. Nislow

2015-01-01

We analyzed the associations of catchment-scale and riparian-scale environmental factors with occurrence of Brook Trout Salvelinus fontinalis in Connecticut headwater stream segments with catchment areas of 15 < km2. A hierarchical Bayesian approach was applied to a statewide stream survey data set, in which Brook...

Psychosocial Factors Predicting First-Year College Student Success

ERIC Educational Resources Information Center

Krumrei-Mancuso, Elizabeth J.; Newton, Fred B.; Kim, Eunhee; Wilcox, Dan

2013-01-01

This study made use of a model of college success that involves students achieving academic goals and life satisfaction. Hierarchical regressions examined the role of six psychosocial factors for college success among 579 first-year college students. Academic self-efficacy and organization and attention to study were predictive of first semester…

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…

Biculturalism and Academic Achievement of African American High School Students

ERIC Educational Resources Information Center

Rust, Jonathan P.; Jackson, Margo A.; Ponterotto, Joseph G.; Blumberg, Fran C.

2011-01-01

Biculturalism was examined as a factor that may positively affect the academic achievement of African American high school students, beyond cultural identity and self-esteem. Hierarchical regression analyses determined that cultural identity and academic self-esteem were important factors for academic achievement, but not biculturalism.…

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…

Psychosocial and Cultural Factors Influencing Expectations of Menarche: A Study on Chinese Premenarcheal Teenage Girls

ERIC Educational Resources Information Center

Yeung, Dannii Y. L.; Tang, Catherine So-kum; Lee, Antoinette

2005-01-01

This study explored how psychosocial and cultural factors influenced expectations of menarche among 476 Chinese premenarcheal teenage girls. Results showed that participants' expectations of menarche were largely negative and heavily influenced by cultural beliefs about menstruation. Findings of hierarchical regression analyses revealed that…

The covariates of parent and youth reporting differences on youth secondary exposure to community violence.

PubMed

Zimmerman, Gregory M

2014-09-01

Survey data for studying youth's secondary exposure to community violence (i.e., witnessing or hearing violence in the community) come from both parents and their children. There are benefits of considering multiple informants in psychosocial assessments, but parents and youths often disagree about comparable information. These reporting differences present challenges for both researchers and clinicians. To shed new light on the individual, family, and neighborhood factors that contribute to parent and youth reporting differences regarding youth's secondary exposure to community violence, this study analyzed hierarchical item response models on a sample of youth respondents from the Project on Human Development in Chicago Neighborhoods. Participants were aged approximately 9, 12, and 15 years (trimodal distribution; mean age = 12.0 years) at baseline (N = 2,344; 49.6% female). Descriptive analyses indicated that parents significantly underestimated their children's exposure to community violence. Logistic hierarchical item response models indicated that absolute discrepancies between parent and youth reports were a function of youth demographic characteristics (male, Hispanic or African American as compared to white, age, 3rd as compared to 1st generation immigrant), individual difference factors (lower levels of self-control, higher levels of violent peer exposure), and family factors (lower household socioeconomic status). Parental under-reporting of youth's exposure to violence was associated with youth demographic characteristics (male, age, 2nd as compared to 3rd generation immigrant), family factors (lower levels of parental supervision), and neighborhood characteristics (higher levels of violence, less access to youth services). The results suggest that a constellation of individual and contextual factors may contribute to the understanding of parent and youth reporting differences. The findings speak to the utility of examining parent and youth reporting differences from a hierarchical lens.

A model clarifying the role of mediators in the variability of mood states over time in people who stutter.

PubMed

Craig, Ashley; Blumgart, Elaine; Tran, Yvonne

2015-06-01

Elevated negative mood states such as social anxiety and depressive mood have been found in adults who stutter. Research is needed to assist in the development of a model that clarifies how factors like self-efficacy and social support contribute to the variability of negative mood states over time. Participants included 200 adults who stutter. A longitudinal design was employed to assess change in mood states over a period of five months. Hierarchical directed regression (path analysis) was used to determine contributory relationships between change in mood states and self-efficacy, social support, socio-demographic and stuttering disorder variables. Participants completed a comprehensive assessment regimen, including validated measures of mood states, perceived control (self-efficacy) and social support. Results confirmed that self-efficacy performs a protective role in the change in mood states like anxiety and depressive mood. That is, self-efficacy cushioned the impact of negative mood states. Social support was only found to contribute a limited protective influence. Socio-demographic variables had little direct impact on mood states, while perceived severity of stuttering also failed to contribute directly to mood at any time point. Mood was found to be influenced by factors that are arguably important for a person to cope and adjust adaptively to the adversity associated with fluency disorder. A model that explains how mood states are influenced over time is described. Implications of these results for managing adults who stutter with elevated negative mood states like social anxiety are discussed. The reader will be able to describe: (a) the method involved in hierarchical (directed) regression used in path analysis; (b) the variability of mood states over a period of five months; (c) the nature of the mediator relationship between factors like self-efficacy and social support and mood states like anxiety, and (d) the contribution to mood states of socio-demographic factors like age and education and stuttering disorder variables like stuttering frequency and perceived severity. Copyright © 2015 Elsevier Inc. All rights reserved.

The Psychometric Structure of Items Assessing Autogynephilia.

PubMed

Hsu, Kevin J; Rosenthal, A M; Bailey, J Michael

2015-07-01

Autogynephilia, or paraphilic sexual arousal in a man to the thought or image of himself as a woman, manifests in a variety of different behaviors and fantasies. We examined the psychometric structure of 22 items assessing five known types of autogynephilia by subjecting them to exploratory factor analysis in a sample of 149 autogynephilic men. Results of oblique factor analyses supported the ability to distinguish five group factors with suitable items. Results of hierarchical factor analyses suggest that the five group factors were strongly underlain by a general factor of autogynephilia. Because the general factor accounted for a much greater amount of the total variance of the 22 items than did the group factors, the types of autogynephilia that a man has seem less important than the degree to which he has autogynephilia. However, the five types of autogynephilia remain conceptually useful because meaningful distinctions were found among them, including differential rates of endorsement and differential ability to predict other relevant variables like gender dysphoria. Factor-derived scales and subscales demonstrated good internal consistency reliabilities, and validity, with large differences found between autogynephilic men and heterosexual male controls. Future research should attempt to replicate our findings, which were mostly exploratory.

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

Hierarchical Bayesian Markov switching models with application to predicting spawning success of shovelnose sturgeon

USGS Publications Warehouse

Holan, S.H.; Davis, G.M.; Wildhaber, M.L.; DeLonay, A.J.; Papoulias, D.M.

2009-01-01

The timing of spawning in fish is tightly linked to environmental factors; however, these factors are not very well understood for many species. Specifically, little information is available to guide recruitment efforts for endangered species such as the sturgeon. Therefore, we propose a Bayesian hierarchical model for predicting the success of spawning of the shovelnose sturgeon which uses both biological and behavioural (longitudinal) data. In particular, we use data that were produced from a tracking study that was conducted in the Lower Missouri River. The data that were produced from this study consist of biological variables associated with readiness to spawn along with longitudinal behavioural data collected by using telemetry and archival data storage tags. These high frequency data are complex both biologically and in the underlying behavioural process. To accommodate such complexity we developed a hierarchical linear regression model that uses an eigenvalue predictor, derived from the transition probability matrix of a two-state Markov switching model with generalized auto-regressive conditional heteroscedastic dynamics. Finally, to minimize the computational burden that is associated with estimation of this model, a parallel computing approach is proposed. ?? Journal compilation 2009 Royal Statistical Society.

Hierarchical cluster analysis of labour market regulations and population health: a taxonomy of low- and middle-income countries.

PubMed

Muntaner, Carles; Chung, Haejoo; Benach, Joan; Ng, Edwin

2012-04-18

An important contribution of the social determinants of health perspective has been to inquire about non-medical determinants of population health. Among these, labour market regulations are of vital significance. In this study, we investigate the labour market regulations among low- and middle-income countries (LMICs) and propose a labour market taxonomy to further understand population health in a global context. Using Gross National Product per capita, we classify 113 countries into either low-income (n = 71) or middle-income (n = 42) strata. Principal component analysis of three standardized indicators of labour market inequality and poverty is used to construct 2 factor scores. Factor score reliability is evaluated with Cronbach's alpha. Using these scores, we conduct a hierarchical cluster analysis to produce a labour market taxonomy, conduct zero-order correlations, and create box plots to test their associations with adult mortality, healthy life expectancy, infant mortality, maternal mortality, neonatal mortality, under-5 mortality, and years of life lost to communicable and non-communicable diseases. Labour market and health data are retrieved from the International Labour Organization's Key Indicators of Labour Markets and World Health Organization's Statistical Information System. Six labour market clusters emerged: Residual (n = 16), Emerging (n = 16), Informal (n = 10), Post-Communist (n = 18), Less Successful Informal (n = 22), and Insecure (n = 31). Primary findings indicate: (i) labour market poverty and population health is correlated in both LMICs; (ii) association between labour market inequality and health indicators is significant only in low-income countries; (iii) Emerging (e.g., East Asian and Eastern European countries) and Insecure (e.g., sub-Saharan African nations) clusters are the most advantaged and disadvantaged, respectively, with the remaining clusters experiencing levels of population health consistent with their labour market characteristics. The labour market regulations of LMICs appear to be important social determinant of population health. This study demonstrates the heuristic value of understanding the labour markets of LMICs and their health effects using exploratory taxonomy approaches.

An Educational Intervention to Enhance Nurse Leaders' Perceptions of Patient Safety Culture

PubMed Central

Ginsburg, Liane; Norton, Peter G; Casebeer, Ann; Lewis, Steven

2005-01-01

Objective To design a training intervention and then test its effect on nurse leaders' perceptions of patient safety culture. Study Setting Three hundred and fifty-six nurses in clinical leadership roles (nurse managers and educators/CNSs) in two Canadian multi-site teaching hospitals (study and control). Study Design A prospective evaluation of a patient safety training intervention using a quasi-experimental untreated control group design with pretest and posttest. Nurses in clinical leadership roles in the study group were invited to participate in two patient safety workshops over a 6-month period. Individuals in the study and control groups completed surveys measuring patient safety culture and leadership for improvement prior to training and 4 months following the second workshop. Extraction Methods Individual nurse clinical leaders were the unit of analysis. Exploratory factor analysis of the safety culture items was conducted; repeated-measures analysis of variance and paired t-tests were used to evaluate the effect of the training intervention on perceived safety culture (three factors). Hierarchical regression analyses looked at the influence of demographics, leadership for improvement, and the training intervention on nurse leaders' perceptions of safety culture. Principal Findings A statistically significant improvement in one of three safety culture measures was shown for the study group (p<.001) and a significant decline was seen on one of the safety culture measures for the control group (p<.05). Leadership support for improvement was found to explain significant amounts of variance in all three patient safety culture measures; workshop attendance explained significant amounts of variance in one of the three safety culture measures. The total R2 for the three full hierarchical regression models ranged from 0.338 and 0.554. Conclusions Sensitively delivered training initiatives for nurse leaders can help to foster a safety culture. Organizational leadership support for improvement is, however, also critical for fostering a culture of safety. Together, training interventions and leadership support may have the most significant impact on patient safety culture. PMID:16033489

Proton Nuclear Magnetic Resonance-Spectroscopic Discrimination of Wines Reflects Genetic Homology of Several Different Grape (V. vinifera L.) Cultivars

PubMed Central

Zhu, Yong; Wen, Wen; Zhang, Fengmin; Hardie, Jim W.

2015-01-01

Background and Aims Proton nuclear magnetic resonance spectroscopy coupled multivariate analysis (1H NMR-PCA/PLS-DA) is an important tool for the discrimination of wine products. Although 1H NMR has been shown to discriminate wines of different cultivars, a grape genetic component of the discrimination has been inferred only from discrimination of cultivars of undefined genetic homology and in the presence of many confounding environmental factors. We aimed to confirm the influence of grape genotypes in the absence of those factors. Methods and Results We applied 1H NMR-PCA/PLS-DA and hierarchical cluster analysis (HCA) to wines from five, variously genetically-related grapevine (V. vinifera) cultivars; all grown similarly on the same site and vinified similarly. We also compared the semi-quantitative profiles of the discriminant metabolites of each cultivar with previously reported chemical analyses. The cultivars were clearly distinguishable and there was a general correlation between their grouping and their genetic homology as revealed by recent genomic studies. Between cultivars, the relative amounts of several of the cultivar-related discriminant metabolites conformed closely with reported chemical analyses. Conclusions Differences in grape-derived metabolites associated with genetic differences alone are a major source of 1H NMR-based discrimination of wines and 1H NMR has the capacity to discriminate between very closely related cultivars. Significance of the Study The study confirms that genetic variation among grape cultivars alone can account for the discrimination of wine by 1H NMR-PCA/PLS and indicates that 1H NMR spectra of wine of single grape cultivars may in future be used in tandem with hierarchical cluster analysis to elucidate genetic lineages and metabolomic relations of grapevine cultivars. In the absence of genetic information, for example, where predecessor varieties are no longer extant, this may be a particularly useful approach. PMID:26658757

Convex Clustering: An Attractive Alternative to Hierarchical Clustering

PubMed Central

Chen, Gary K.; Chi, Eric C.; Ranola, John Michael O.; Lange, Kenneth

2015-01-01

The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims. Despite its shortcomings in accuracy, hierarchical clustering is the dominant clustering method in bioinformatics. Biologists find the trees constructed by hierarchical clustering visually appealing and in tune with their evolutionary perspective. Hierarchical clustering operates on multiple scales simultaneously. This is essential, for instance, in transcriptome data, where one may be interested in making qualitative inferences about how lower-order relationships like gene modules lead to higher-order relationships like pathways or biological processes. The recently developed method of convex clustering preserves the visual appeal of hierarchical clustering while ameliorating its propensity to make false inferences in the presence of outliers and noise. The solution paths generated by convex clustering reveal relationships between clusters that are hidden by static methods such as k-means clustering. The current paper derives and tests a novel proximal distance algorithm for minimizing the objective function of convex clustering. The algorithm separates parameters, accommodates missing data, and supports prior information on relationships. Our program CONVEXCLUSTER incorporating the algorithm is implemented on ATI and nVidia graphics processing units (GPUs) for maximal speed. Several biological examples illustrate the strengths of convex clustering and the ability of the proximal distance algorithm to handle high-dimensional problems. CONVEXCLUSTER can be freely downloaded from the UCLA Human Genetics web site at http://www.genetics.ucla.edu/software/ PMID:25965340

Hierarchical Flowerlike Gold Nanoparticles Labeled Immunochromatography Test Strip for Highly Sensitive Detection of Escherichia coli O157:H7.

PubMed

Zhang, Lei; Huang, Youju; Wang, Jingyun; Rong, Yun; Lai, Weihua; Zhang, Jiawei; Chen, Tao

2015-05-19

Gold nanoparticles (AuNPs) labeled lateral-flow test strip immunoassay (LFTS) has been widely used in biomedical, feed/food, and environmental analysis fields. Conventional ILFS assay usually uses spherical AuNPs as labeled probes and shows low detection sensitivity, which further limits its widespread practical application. Unlike spherical AuNP used as labeled probe in conventional ILFS, in our present study, a hierarchical flowerlike AuNP specific probe was designed for LFTS and further used to detect Escherichia coli O157:H7 (E. coli O157:H7). Three types of hierarchical flowerlike AuNPs, such as tipped flowerlike, popcornlike, and large-sized flowerlike AuNPs were synthesized in a one-step method. Compared with other two kinds of Au particles, tipped flowerlike AuNPs probes for LFTS particularly exhibited highly sensitive detection of E. coli O157:H7. The remarkable improvement of detection sensitivity of tipped flowerlike AuNPs probes can be achieved even as low as 10(3) colony-forming units (CFU)/mL by taking advantages of its appropriate size and hierarchical structures, which is superior over the detection performance of conventional LFTS. Using this novel tipped flower AuNPs probes, quantitative detection of E. coli O157:H7 can be obtained partially in a wide concentration range with good repeatability. This hierarchical tipped flower-shaped AuNPs probe for LFTS is promising for the practical applications in widespread analysis fields.

Convex clustering: an attractive alternative to hierarchical clustering.

PubMed

Chen, Gary K; Chi, Eric C; Ranola, John Michael O; Lange, Kenneth

2015-05-01

The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims. Despite its shortcomings in accuracy, hierarchical clustering is the dominant clustering method in bioinformatics. Biologists find the trees constructed by hierarchical clustering visually appealing and in tune with their evolutionary perspective. Hierarchical clustering operates on multiple scales simultaneously. This is essential, for instance, in transcriptome data, where one may be interested in making qualitative inferences about how lower-order relationships like gene modules lead to higher-order relationships like pathways or biological processes. The recently developed method of convex clustering preserves the visual appeal of hierarchical clustering while ameliorating its propensity to make false inferences in the presence of outliers and noise. The solution paths generated by convex clustering reveal relationships between clusters that are hidden by static methods such as k-means clustering. The current paper derives and tests a novel proximal distance algorithm for minimizing the objective function of convex clustering. The algorithm separates parameters, accommodates missing data, and supports prior information on relationships. Our program CONVEXCLUSTER incorporating the algorithm is implemented on ATI and nVidia graphics processing units (GPUs) for maximal speed. Several biological examples illustrate the strengths of convex clustering and the ability of the proximal distance algorithm to handle high-dimensional problems. CONVEXCLUSTER can be freely downloaded from the UCLA Human Genetics web site at http://www.genetics.ucla.edu/software/.

Application of growing hierarchical SOM for visualisation of network forensics traffic data.

PubMed

Palomo, E J; North, J; Elizondo, D; Luque, R M; Watson, T

2012-08-01

Digital investigation methods are becoming more and more important due to the proliferation of digital crimes and crimes involving digital evidence. Network forensics is a research area that gathers evidence by collecting and analysing network traffic data logs. This analysis can be a difficult process, especially because of the high variability of these attacks and large amount of data. Therefore, software tools that can help with these digital investigations are in great demand. In this paper, a novel approach to analysing and visualising network traffic data based on growing hierarchical self-organising maps (GHSOM) is presented. The self-organising map (SOM) has been shown to be successful for the analysis of highly-dimensional input data in data mining applications as well as for data visualisation in a more intuitive and understandable manner. However, the SOM has some problems related to its static topology and its inability to represent hierarchical relationships in the input data. The GHSOM tries to overcome these limitations by generating a hierarchical architecture that is automatically determined according to the input data and reflects the inherent hierarchical relationships among them. Moreover, the proposed GHSOM has been modified to correctly treat the qualitative features that are present in the traffic data in addition to the quantitative features. Experimental results show that this approach can be very useful for a better understanding of network traffic data, making it easier to search for evidence of attacks or anomalous behaviour in a network environment. Copyright © 2012 Elsevier Ltd. All rights reserved.

Compiler-Directed File Layout Optimization for Hierarchical Storage Systems

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

Ding, Wei; Zhang, Yuanrui; Kandemir, Mahmut

File layout of array data is a critical factor that effects the behavior of storage caches, and has so far taken not much attention in the context of hierarchical storage systems. The main contribution of this paper is a compiler-driven file layout optimization scheme for hierarchical storage caches. This approach, fully automated within an optimizing compiler, analyzes a multi-threaded application code and determines a file layout for each disk-resident array referenced by the code, such that the performance of the target storage cache hierarchy is maximized. We tested our approach using 16 I/O intensive application programs and compared its performancemore » against two previously proposed approaches under different cache space management schemes. Our experimental results show that the proposed approach improves the execution time of these parallel applications by 23.7% on average.« less

Compiler-Directed File Layout Optimization for Hierarchical Storage Systems

DOE PAGES

Ding, Wei; Zhang, Yuanrui; Kandemir, Mahmut; ...

2013-01-01

File layout of array data is a critical factor that effects the behavior of storage caches, and has so far taken not much attention in the context of hierarchical storage systems. The main contribution of this paper is a compiler-driven file layout optimization scheme for hierarchical storage caches. This approach, fully automated within an optimizing compiler, analyzes a multi-threaded application code and determines a file layout for each disk-resident array referenced by the code, such that the performance of the target storage cache hierarchy is maximized. We tested our approach using 16 I/O intensive application programs and compared its performancemore » against two previously proposed approaches under different cache space management schemes. Our experimental results show that the proposed approach improves the execution time of these parallel applications by 23.7% on average.« less

Automated Subscores for TOEFL iBT[R] Independent Essays. Research Report. ETS RR-11-39

ERIC Educational Resources Information Center

Attali, Yigal

2011-01-01

The e-rater[R] automated essay scoring system is used operationally in the scoring of TOEFL iBT[R] independent essays. Previous research has found support for a 3-factor structure of the e-rater features. This 3-factor structure has an attractive hierarchical linguistic interpretation with a word choice factor, a grammatical convention within a…

Exploring the hierarchical structure of the MMPI-2-RF Personality Psychopathology Five in psychiatric patient and university student samples.

PubMed

Bagby, R Michael; Sellbom, Martin; Ayearst, Lindsay E; Chmielewski, Michael S; Anderson, Jaime L; Quilty, Lena C

2014-01-01

In this study our goal was to examine the hierarchical structure of personality pathology as conceptualized by Harkness and McNulty's (1994) Personality Psychopathology Five (PSY-5) model, as recently operationalized by the MMPI-2-RF (Ben-Porath & Tellegen, 2011) PSY-5r scales. We used Goldberg's (2006) "bass-ackwards" method to obtain factor structure using PSY-5r item data, successively extracting from 1 to 5 factors in a sample of psychiatric patients (n = 1,000) and a sample of university undergraduate students (n = 1,331). Participants from these samples had completed either the MMPI-2 or the MMPI-2-RF. The results were mostly consistent across the 2 samples, with some differences at the 3-factor level. In the patient sample a factor structure representing 3 broad psychopathology domains (internalizing, externalizing, and psychoticism) emerged; in the student sample the 3-factor level represented what is more commonly observed in "normal-range" personality models (negative emotionality, introversion, and disconstraint). At the 5-factor level the basic structure was similar across the 2 samples and represented well the PSY-5r domains.

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.

The study of dynamic force acted on water strider leg departing from water surface

NASA Astrophysics Data System (ADS)

Sun, Peiyuan; Zhao, Meirong; Jiang, Jile; Zheng, Yelong

2018-01-01

Water-walking insects such as water striders can skate on the water surface easily with the help of the hierarchical structure on legs. Numerous theoretical and experimental studies show that the hierarchical structure would help water strider in quasi-static case such as load-bearing capacity. However, the advantage of the hierarchical structure in the dynamic stage has not been reported yet. In this paper, the function of super hydrophobicity and the hierarchical structure was investigated by measuring the adhesion force of legs departing from the water surface at different lifting speed by a dynamic force sensor. The results show that the adhesion force decreased with the increase of lifting speed from 0.02 m/s to 0.4 m/s, whose mechanic is investigated by Energy analysis. In addition, it can be found that the needle shape setae on water strider leg can help them depart from water surface easily. Thus, it can serve as a starting point to understand how the hierarchical structure on the legs help water-walking insects to jump upward rapidly to avoid preying by other insects.

Energy-efficient hierarchical processing in the network of wireless intelligent sensors (WISE)

NASA Astrophysics Data System (ADS)

Raskovic, Dejan

Sensor network nodes have benefited from technological advances in the field of wireless communication, processing, and power sources. However, the processing power of microcontrollers is often not sufficient to perform sophisticated processing, while the power requirements of digital signal processing boards or handheld computers are usually too demanding for prolonged system use. We are matching the intrinsic hierarchical nature of many digital signal-processing applications with the natural hierarchy in distributed wireless networks, and building the hierarchical system of wireless intelligent sensors. Our goal is to build a system that will exploit the hierarchical organization to optimize the power consumption and extend battery life for the given time and memory constraints, while providing real-time processing of sensor signals. In addition, we are designing our system to be able to adapt to the current state of the environment, by dynamically changing the algorithm through procedure replacement. This dissertation presents the analysis of hierarchical environment and methods for energy profiling used to evaluate different system design strategies, and to optimize time-effective and energy-efficient processing.

Scaling functional status within the interRAI suite of assessment instruments

PubMed Central

2013-01-01

Background As one ages, physical, cognitive, and clinical problems accumulate and the pattern of loss follows a distinct progression. The first areas requiring outside support are the Instrumental Activities of Daily Living and over time there is a need for support in performing the Activities of Daily Living. Two new functional hierarchies are presented, an IADL hierarchical capacity scale and a combination scale integrating both IADL and ADL hierarchies. Methods A secondary analyses of data from a cross-national sample of community residing persons was conducted using 762,023 interRAI assessments. The development of the new IADL Hierarchy and a new IADL-ADL combined scale proceeded through a series of interrelated steps first examining individual IADL and ADL item scores among persons receiving home care and those living independently without services. A factor analysis demonstrated the overall continuity across the IADL-ADL continuum. Evidence of the validity of the scales was explored with associative analyses of factors such as a cross-country distributional analysis for persons in home care programs, a count of functional problems across the categories of the hierarchy, an assessment of the hours of informal and formal care received each week by persons in the different categories of the hierarchy, and finally, evaluation of the relationship between cognitive status and the hierarchical IADL-ADL assignments. Results Using items from interRAI’s suite of assessment instruments, two new functional scales were developed, the interRAI IADL Hierarchy Scale and the interRAI IADL-ADL Functional Hierarchy Scale. The IADL Hierarchy Scale consisted of 5 items, meal preparation, housework, shopping, finances and medications. The interRAI IADL-ADL Functional Hierarchy Scale was created through an amalgamation of the ADL Hierarchy (developed previously) and IADL Hierarchy Scales. These scales cover the spectrum of IADL and ADL challenges faced by persons in the community. Conclusions An integrated IADL and ADL functional assessment tool is valuable. The loss in these areas follows a general hierarchical pattern and with the interRAI IADL-ADL Functional Hierarchy Scale, this progression can be reliably and validly assessed. Used across settings within the health continuum, it allows for monitoring of individuals from relative independence through episodes of care. PMID:24261417

Manifold implications of obesity in ischemic heart disease among Japanese patients according to covariance structure analysis: Low reactivity of B-type natriuretic peptide as an intervening risk factor.

PubMed

Tsutsumi, Joshi; Minai, Kosuke; Kawai, Makoto; Ogawa, Kazuo; Inoue, Yasunori; Morimoto, Satoshi; Tanaka, Toshikazu; Nagoshi, Tomohisa; Ogawa, Takayuki; Yoshimura, Michihiro

2017-01-01

Obesity is believed to be one of the major risk factors for cardiovascular disease in Western countries. However, the effects of obesity should be continuously examined in the Japanese population because the average bodily habitus differs among countries. In this study, we collectively examined the significance of obesity and obesity-triggered risk factors including the low reactivity of B-type natriuretic peptide (BNP), for ischemic heart disease (IHD) in Japanese patients. The study patients consisted of 1252 subjects (IHD: n = 970; non-IHD: n = 282). Multiple logistic regression analysis revealed that dyslipidemia, hypertension, diabetes, and the low reactivity of BNP were significant risk factors for IHD, but body mass index (BMI) was not. A theoretical path model was proposed by positioning BMI at the top of the hierarchical model. Exploratory factor analysis revealed that BMI did not play a causative role in IHD (P = NS). BMI was causatively linked to other risk factors (P<0.001 for hypertension; P<0.001 for dyslipidemia; P<0.001 for HbA1c; P<0.001 for LogBNP), and these factors played a causative role in IHD (P<0.001 for hypertension; P<0.001 for dyslipidemia; P<0.001 for HbA1c; P<0.001 for LogBNP). The intrinsic power of the low reactivity of BNP induced by high BMI on the promotion of IHD was fairly potent. This study demonstrated that obesity per se is not a strong risk factor for IHD in Japanese patients. However, several important risk factors triggered by obesity exhibited a causative role for IHD. The low reactivity of BNP is a substantial risk factor for IHD.

Assessment of Gait Characteristics in Total Knee Arthroplasty Patients Using a Hierarchical Partial Least Squares Method.

PubMed

Wang, Wei; Ackland, David C; McClelland, Jodie A; Webster, Kate E; Halgamuge, Saman

2018-01-01

Quantitative gait analysis is an important tool in objective assessment and management of total knee arthroplasty (TKA) patients. Studies evaluating gait patterns in TKA patients have tended to focus on discrete data such as spatiotemporal information, joint range of motion and peak values of kinematics and kinetics, or consider selected principal components of gait waveforms for analysis. These strategies may not have the capacity to capture small variations in gait patterns associated with each joint across an entire gait cycle, and may ultimately limit the accuracy of gait classification. The aim of this study was to develop an automatic feature extraction method to analyse patterns from high-dimensional autocorrelated gait waveforms. A general linear feature extraction framework was proposed and a hierarchical partial least squares method derived for discriminant analysis of multiple gait waveforms. The effectiveness of this strategy was verified using a dataset of joint angle and ground reaction force waveforms from 43 patients after TKA surgery and 31 healthy control subjects. Compared with principal component analysis and partial least squares methods, the hierarchical partial least squares method achieved generally better classification performance on all possible combinations of waveforms, with the highest classification accuracy . The novel hierarchical partial least squares method proposed is capable of capturing virtually all significant differences between TKA patients and the controls, and provides new insights into data visualization. The proposed framework presents a foundation for more rigorous classification of gait, and may ultimately be used to evaluate the effects of interventions such as surgery and rehabilitation.

Hierarchical structure for audio-video based semantic classification of sports video sequences

NASA Astrophysics Data System (ADS)

Kolekar, M. H.; Sengupta, S.

2005-07-01

A hierarchical structure for sports event classification based on audio and video content analysis is proposed in this paper. Compared to the event classifications in other games, those of cricket are very challenging and yet unexplored. We have successfully solved cricket video classification problem using a six level hierarchical structure. The first level performs event detection based on audio energy and Zero Crossing Rate (ZCR) of short-time audio signal. In the subsequent levels, we classify the events based on video features using a Hidden Markov Model implemented through Dynamic Programming (HMM-DP) using color or motion as a likelihood function. For some of the game-specific decisions, a rule-based classification is also performed. Our proposed hierarchical structure can easily be applied to any other sports. Our results are very promising and we have moved a step forward towards addressing semantic classification problems in general.

A Bayesian hierarchical diffusion model decomposition of performance in Approach–Avoidance Tasks

PubMed Central

Krypotos, Angelos-Miltiadis; Beckers, Tom; Kindt, Merel; Wagenmakers, Eric-Jan

2015-01-01

Common methods for analysing response time (RT) tasks, frequently used across different disciplines of psychology, suffer from a number of limitations such as the failure to directly measure the underlying latent processes of interest and the inability to take into account the uncertainty associated with each individual's point estimate of performance. Here, we discuss a Bayesian hierarchical diffusion model and apply it to RT data. This model allows researchers to decompose performance into meaningful psychological processes and to account optimally for individual differences and commonalities, even with relatively sparse data. We highlight the advantages of the Bayesian hierarchical diffusion model decomposition by applying it to performance on Approach–Avoidance Tasks, widely used in the emotion and psychopathology literature. Model fits for two experimental data-sets demonstrate that the model performs well. The Bayesian hierarchical diffusion model overcomes important limitations of current analysis procedures and provides deeper insight in latent psychological processes of interest. PMID:25491372

Hierarchical cluster-tendency analysis of the group structure in the foreign exchange market

NASA Astrophysics Data System (ADS)

Wu, Xin-Ye; Zheng, Zhi-Gang

2013-08-01

A hierarchical cluster-tendency (HCT) method in analyzing the group structure of networks of the global foreign exchange (FX) market is proposed by combining the advantages of both the minimal spanning tree (MST) and the hierarchical tree (HT). Fifty currencies of the top 50 World GDP in 2010 according to World Bank's database are chosen as the underlying system. By using the HCT method, all nodes in the FX market network can be "colored" and distinguished. We reveal that the FX networks can be divided into two groups, i.e., the Asia-Pacific group and the Pan-European group. The results given by the hierarchical cluster-tendency method agree well with the formerly observed geographical aggregation behavior in the FX market. Moreover, an oil-resource aggregation phenomenon is discovered by using our method. We find that gold could be a better numeraire for the weekly-frequency FX data.

Chemical Fingerprint and Quantitative Analysis for the Quality Evaluation of Platycladi cacumen by Ultra-performance Liquid Chromatography Coupled with Hierarchical Cluster Analysis.

PubMed

Shan, Mingqiu; Li, Sam Fong Yau; Yu, Sheng; Qian, Yan; Guo, Shuchen; Zhang, Li; Ding, Anwei

2018-01-01

Platycladi cacumen (dried twigs and leaves of Platycladus orientalis (L.) Franco) is a frequently utilized Chinese medicinal herb. To evaluate the quality of the phytomedcine, an ultra-performance liquid chromatographic method with diode array detection was established for chemical fingerprinting and quantitative analysis. In this study, 27 batches of P. cacumen from different regions were collected for analysis. A chemical fingerprint with 20 common peaks was obtained using Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine (Version 2004A). Among these 20 components, seven flavonoids (myricitrin, isoquercitrin, quercitrin, afzelin, cupressuflavone, amentoflavone and hinokiflavone) were identified and determined simultaneously. In the method validation, the seven analytes showed good regressions (R ≥ 0.9995) within linear ranges and good recoveries from 96.4% to 103.3%. Furthermore, with the contents of these seven flavonoids, hierarchical clustering analysis was applied to distinguish the 27 batches into five groups. The chemometric results showed that these groups were almost consistent with geographical positions and climatic conditions of the production regions. Integrating fingerprint analysis, simultaneous determination and hierarchical clustering analysis, the established method is rapid, sensitive, accurate and readily applicable, and also provides a significant foundation for quality control of P. cacumen efficiently. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Elevated levels of serum cholesterol are associated with better performance on tasks of episodic memory.

PubMed

Leritz, Elizabeth C; McGlinchey, Regina E; Salat, David H; Milberg, William P

2016-04-01

We examined how serum cholesterol, an established risk factor for cerebrovascular disease (CVD), relates to cognitive function in healthy middle-older aged individuals with no neurologic or CVD history. A complete lipid panel was obtained from a cohort of one hundred twenty individuals, ages 43-85, who also underwent a comprehensive neuropsychological examination. In order to reduce the number of variables and empirically identify broad cognitive domains, scores from neuropsychological tests were submitted into a factor analysis. This analysis revealed three explainable factors: Memory, Executive Function and Memory/Language. Three separate hierarchical multiple regression analyses were conducted using individual cholesterol metrics (total cholesterol, low density lipoprotein; LDL, high density lipoprotein; HDL, and triglycerides), as well as age, education, medication status (lipid lowering agents), ApoE status, and additional risk factors for CVD to predict neuropsychological function. The Memory Factor was predicted by a combination of age, LDL, and triglyceride levels; both age and triglycerides were negatively associated with factor score, while LDL levels revealed a positive relationship. Both the Executive and Memory/Language factor were only explained by education, whereby more years were associated with better performance. These results provide evidence that individual cholesterol lipoproteins and triglycerides may differentially impact cognitive function, over and above other common CVD risk factors and ApoE status. Our findings demonstrate the importance of consideration of vascular risk factors, such as cholesterol, in studies of cognitive aging.

Exploring Factors Associated with Educational Outcomes for Orphan and Abandoned Children in India

PubMed Central

Sinha, Aakanksha; Lombe, Margaret; Saltzman, Leia Y.; Whetten, Kathryn; Whetten, Rachel

2016-01-01

India has more than 25 million orphan and abandoned children (UNICEF, 2012). The burden of care for these OAC is on caregivers that are often ill equipped to meet their needs due to inadequate assets. Previous studies suggest that in communities with limited resources, OAC residing with non-biological caregivers are more at risk than those fostered by a biological parent. This study explores the association of caregiver and child characteristics with OAC educational outcome in India. The analysis was conducted using hierarchical logistic regression. The findings have implications for practice and policy in the global child welfare field. PMID:27088068

An empirical, hierarchical typology of tree species assemblages for assessing forest dynamics under global change scenarios

Treesearch

Jennifer K. Costanza; John W. Coulston; David N. Wear

2017-01-01

The composition of tree species occurring in a forest is important and can be affected by global change drivers such as climate change. To inform assessment and projection of global change impacts at broad extents, we used hierarchical cluster analysis and over 120,000 recent forest inventory plots to empirically define forest tree assemblages across the U.S., and...

Bayesian hierarchical model for large-scale covariance matrix estimation.

PubMed

Zhu, Dongxiao; Hero, Alfred O

2007-12-01

Many bioinformatics problems implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy due to "overfitting." We cast the large-scale covariance matrix estimation problem into the Bayesian hierarchical model framework, and introduce dependency between covariance parameters. We demonstrate the advantages of our approaches over the traditional approaches using simulations and OMICS data analysis.

Network Intrusion Detection and Visualization using Aggregations in a Cyber Security Data Warehouse

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

Czejdo, Bogdan; Ferragut, Erik M; Goodall, John R

2012-01-01

The challenge of achieving situational understanding is a limiting factor in effective, timely, and adaptive cyber-security analysis. Anomaly detection fills a critical role in network assessment and trend analysis, both of which underlie the establishment of comprehensive situational understanding. To that end, we propose a cyber security data warehouse implemented as a hierarchical graph of aggregations that captures anomalies at multiple scales. Each node of our pro-posed graph is a summarization table of cyber event aggregations, and the edges are aggregation operators. The cyber security data warehouse enables domain experts to quickly traverse a multi-scale aggregation space systematically. We describemore » the architecture of a test bed system and a summary of results on the IEEE VAST 2012 Cyber Forensics data.« less

Private prayer among Alzheimer's caregivers: mediating burden and resiliency.

PubMed

Wilks, Scott E; Vonk, M Elizabeth

2008-01-01

This study examined whether the coping method of private prayer served as a protective factor of resiliency among a sample (N = 304) of Alzheimer's caregivers. Participants in caregiver support groups completed questionnaires that assessed a number of constructs, including caregiving burden; prayer frequency; use of private prayer as a means of coping; and perceived resiliency. The sample averaged a moderate level of burden and a great extent of prayer usage. Caregiving burden had positively affected the extent of prayer usage and negatively influenced perceived resiliency. Findings from hierarchical regression analysis showed that caregiving burden and private prayer significantly influenced variation in perceived resiliency scores. Results from a regression equation series and path analysis provided support for prayer as a mediator between burden and perceived resiliency. Implications for social work practice and education are discussed.

Risk Assessment for Mobile Systems Through a Multilayered Hierarchical Bayesian Network.

PubMed

Li, Shancang; Tryfonas, Theo; Russell, Gordon; Andriotis, Panagiotis

2016-08-01

Mobile systems are facing a number of application vulnerabilities that can be combined together and utilized to penetrate systems with devastating impact. When assessing the overall security of a mobile system, it is important to assess the security risks posed by each mobile applications (apps), thus gaining a stronger understanding of any vulnerabilities present. This paper aims at developing a three-layer framework that assesses the potential risks which apps introduce within the Android mobile systems. A Bayesian risk graphical model is proposed to evaluate risk propagation in a layered risk architecture. By integrating static analysis, dynamic analysis, and behavior analysis in a hierarchical framework, the risks and their propagation through each layer are well modeled by the Bayesian risk graph, which can quantitatively analyze risks faced to both apps and mobile systems. The proposed hierarchical Bayesian risk graph model offers a novel way to investigate the security risks in mobile environment and enables users and administrators to evaluate the potential risks. This strategy allows to strengthen both app security as well as the security of the entire system.

[Identification of different Citrus sinensis (L.) Osbeck trees varieties using Fourier transform infrared spectroscopy and hierarchical cluster analysis].

PubMed

Yi, Shi-Lai; Deng, Lie; He, Shao-Lan; Shi, You-Ming; Zheng, Yong-Qiang; Lu, Qiang; Xie, Rang-Jin; Wei, Xian-Guoi; Li, Song-Wei; Jian, Shui-Xian

2012-11-01

Researched on diversity of the spring leaf samples of seven different Citrus sinensis (L.) Osbeck varieties by Fourier transform infrared (FTIR) spectroscopy technology, the results showed that the Fourier transform infrared spectra of seven varieties leaves was composited by the absorption band of cellulose and polysaccharide mainly, the wave number of characteristics absorption peaks were similar at their FTIR spectra. However, there were some differences in shape of peaks and relatively absorption intensity. The conspicuous difference was presented at the region between 1 500 and 700 cm(-1) by second derivative spectra. Through the hierarchical cluster analysis (HCA) of second derivative spectra between 1 500 and 700 cm(-1), the results showed that the clustering of the different varieties of Citrus sinensis (L.) Osbeck varieties was classification according to genetic relationship. The results showed that FTIR spectroscopy combined with hierarchical cluster analysis could be used to identify and classify of citrus varieties rapidly, it was an extension method to study on early leaves of varieties orange seedlings.

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.

Gender difference in sickness absence from work: a multiple mediation analysis of psychosocial factors.

PubMed

Casini, Annalisa; Godin, Isabelle; Clays, Els; Kittel, France

2013-08-01

Previous research has shown that job characteristics, private life and psychosocial factors partially account for gender difference in work absences because of sickness. Most studies have analysed these factors separately. The aim of the present study was to evaluate whether these explanatory factors act as mediators when they are considered simultaneously. The evaluated data set comprises the merger of two Belgian longitudinal studies, BELSTRESS III and SOMSTRESS. It includes 3821 workers (1541 men) aged 21-66 years, employed in eight organizations. A multiple mediation analysis was performed to explain the higher prevalence among women. Estimated factors were occupational grade, total number of paid working hours per week, job strain, overcommitment, home-work interference and social support at and outside work. Prospective data concerning duration and frequency of medically justified sickness absence (registered by the organizations) were used as outcomes. Overall, the mediating factors partially account for gender difference in sickness absence. The strongest mediator for both outcomes is job strain. In addition, difference in absence duration is mediated by social support at work, whereas difference in frequency is mediated by professional grade and home-work interference. Our results call attention to the necessity to elaborate actual preventive actions aiming at favouring a better positioning of women on the labour market in term of hierarchical level as well as in terms of quality of work for reducing sickness absence in this group.

Attitude Toward Ambiguity: Empirically Robust Factors in Self-Report Personality Scales.

PubMed

Lauriola, Marco; Foschi, Renato; Mosca, Oriana; Weller, Joshua

2016-06-01

Two studies were conducted to examine the factor structure of attitude toward ambiguity, a broad personality construct that refers to personal reactions to perceived ambiguous stimuli in a variety of context and situations. Using samples from two countries, Study 1 mapped the hierarchical structure of 133 items from seven tolerance-intolerance of ambiguity scales (N = 360, Italy; N = 306, United States). Three major factors-Discomfort with Ambiguity, Moral Absolutism/Splitting, and Need for Complexity and Novelty-were recovered in each country with high replicability coefficients across samples. In Study 2 (N = 405, Italian community sample; N =366, English native speakers sample), we carried out a confirmatory analysis on selected factor markers. A bifactor model had an acceptable fit for each sample and reached the construct-level invariance for general and group factors. Convergent validity with related traits was assessed in both studies. We conclude that attitude toward ambiguity can be best represented a multidimensional construct involving affective (Discomfort with Ambiguity), cognitive (Moral Absolutism/Splitting), and epistemic (Need for Complexity and Novelty) components. © The Author(s) 2015.

[Torrance Tests of Creative Thinking (TTCT): elements for construct validity in Portuguese adolescents].

PubMed

Oliveira, Ema; Almeida, Leandro; Ferrándiz, Carmen; Ferrando, Mercedes; Sainz, Marta; Prieto, María Dolores

2009-11-01

The aim of this work is to study the unidimensional and multidimensional nature of creativity when assessed through divergent thinking tasks, as proposed in Torrance's battery (Torrance Creative Thinking Test, TTCT). This battery is made up of various tasks with verbal and figurative content, aimed at estimating the level of creativity according to the dimensions or cognitive functions of fluency, flexibility, originality and elaboration of the individuals' ideas. This work used a sample of 595 Portuguese students from 5th and 6th grade. The results of confirmatory factor analysis reveals that the unidimensional model (a general factor of creativity) and the model of factors as a function of the cognitive dimensions of creativity, based on task content, do not fit well. The model with the best fit has a hierarchical factor structure, in which the first level comprises the factors for each of the subtests applied and the second level includes verbal or figurative content. The difficulty to verify the structural validity of the TTCT is noted, and the need for further studies to achieve, in practice, better individual creativity scores.

Quantitative Classification and Environmental Interpretation of Secondary Forests 18 Years After the Invasion of Pine Forests by Bursaphelenchus xylophilus (Nematoda: Aphelenchoididae) in China

PubMed Central

Wang, Zhuang; Luo, You-Qing; Shi, Juan; Gao, Ruihe; Wang, Guoming

2014-01-01

Abstract With growing concerns over the serious ecological problems in pine forests ( Pinus massoniana , P. thunbergii ) caused by the invasion of Bursaphelenchus xylophilus (the pine wood nematode), a particular challenge is to determine the succession and restoration of damaged pine forests in Asia. We used two-way indicator species analysis and canonical correlation analysis for the hierarchical classification of existing secondary forests that have been restored since the invasion of B. xylophilus 18 years ago. Biserial correlation analysis was used to relate the spatial distribution of species to environmental factors. After 18 years of natural recovery, the original pine forest had evolved into seven types of secondary forest. Seven environmental factors, namely soil depth, humus depth, soil pH, aspect, slope position, bare rock ratio, and distance to the sea, were significantly correlated with species distribution. Furthermore, we proposed specific reform measures and suggestions for the different types of secondary forest formed after the damage and identified the factors driving the various forms of restoration. These results suggest that it is possible to predict the restoration paths of damaged pine forests, which would reduce the negative impact of B. xylophilus invasions. PMID:25527600

Validation of the Center for Epidemiological Studies Depression Scale among Korean Adolescents.

PubMed

Heo, Eun-Hye; Choi, Kyeong-Sook; Yu, Je-Chun; Nam, Ji-Ae

2018-02-01

The Center for Epidemiological Studies Depression Scale (CES-D) is designed to measure the current level of depressive symptomatology in the general population. However, no review has examined whether the scale is reliable and valid among children and adolescents in Korea. The purpose of this study was to test whether the Korean form of the CES-D is valid in adolescents. Data were obtained from 1,884 adolescents attending grades 1-3 in Korean middle schools. Reliability was evaluated by internal consistency (Cronbach's alpha). Concurrent validity was evaluated by a correlation analysis between the CES-D and other scales. Construct validity was evaluated by exploratory factor and confirmatory factor analyses. The internal consistency coefficient for the entire group was 0.88. The CES-D was positively correlated with scales that measure negative psychological constructs, such as the State Anxiety Inventory for Children, the Korean Social Anxiety Scale for Children and Adolescents, and the Reynold Suicidal Ideation Questionnaire, but it was negatively correlated with scales that measure positive psychological constructs, such as the Korean version of the Rosenberg Self-Esteem Scale and the Connor-Davidson Resilience Scale-2. The CES-D was examined by three-dimensional exploratory factor analysis, and the three-factor structure of the scale explained 53.165% of the total variance. The variance explained by factor I was 24.836%, that explained by factor II was 15.988%, and that explained by factor III was 12.341%. The construct validity of the CES-D was tested by confirmatory factor analysis, and we applied the entire group's data using a three-factor hierarchical model. The fit index showed a level similar to those of other countries' adolescent samples. The CES-D has high internal consistency and addresses psychological constructs similar to those addressed by other scales. The CES-D showed a three-factor structure in an exploratory factor analysis. The present findings suggest that the CES-D is a useful and reliable tool for measuring depression in Korean adolescents.

Testing for Divergent Transmission Histories among Cultural Characters: A Study Using Bayesian Phylogenetic Methods and Iranian Tribal Textile Data

PubMed Central

Matthews, Luke J.; Tehrani, Jamie J.; Jordan, Fiona M.; Collard, Mark; Nunn, Charles L.

2011-01-01

Background Archaeologists and anthropologists have long recognized that different cultural complexes may have distinct descent histories, but they have lacked analytical techniques capable of easily identifying such incongruence. Here, we show how Bayesian phylogenetic analysis can be used to identify incongruent cultural histories. We employ the approach to investigate Iranian tribal textile traditions. Methods We used Bayes factor comparisons in a phylogenetic framework to test two models of cultural evolution: the hierarchically integrated system hypothesis and the multiple coherent units hypothesis. In the hierarchically integrated system hypothesis, a core tradition of characters evolves through descent with modification and characters peripheral to the core are exchanged among contemporaneous populations. In the multiple coherent units hypothesis, a core tradition does not exist. Rather, there are several cultural units consisting of sets of characters that have different histories of descent. Results For the Iranian textiles, the Bayesian phylogenetic analyses supported the multiple coherent units hypothesis over the hierarchically integrated system hypothesis. Our analyses suggest that pile-weave designs represent a distinct cultural unit that has a different phylogenetic history compared to other textile characters. Conclusions The results from the Iranian textiles are consistent with the available ethnographic evidence, which suggests that the commercial rug market has influenced pile-rug designs but not the techniques or designs incorporated in the other textiles produced by the tribes. We anticipate that Bayesian phylogenetic tests for inferring cultural units will be of great value for researchers interested in studying the evolution of cultural traits including language, behavior, and material culture. PMID:21559083