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

ERIC Educational Resources Information Center

Nimon, Kim

2012-01-01

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

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,…

Image Information Mining Utilizing Hierarchical Segmentation

NASA Technical Reports Server (NTRS)

Tilton, James C.; Marchisio, Giovanni; Koperski, Krzysztof; Datcu, Mihai

2002-01-01

The Hierarchical Segmentation (HSEG) algorithm is an approach for producing high quality, hierarchically related image segmentations. The VisiMine image information mining system utilizes clustering and segmentation algorithms for reducing visual information in multispectral images to a manageable size. The project discussed herein seeks to enhance the VisiMine system through incorporating hierarchical segmentations from HSEG into the VisiMine system.

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…

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…

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

ERIC Educational Resources Information Center

Haberfield, Yitchak; Semyonov, Moshe; Addi, Audrey

1998-01-01

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

Clinical time series prediction: towards a hierarchical dynamical system framework

PubMed Central

Liu, Zitao; Hauskrecht, Milos

2014-01-01

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

Decentralization, stabilization, and estimation of large-scale linear systems

NASA Technical Reports Server (NTRS)

Siljak, D. D.; Vukcevic, M. B.

1976-01-01

In this short paper we consider three closely related aspects of large-scale systems: decentralization, stabilization, and estimation. A method is proposed to decompose a large linear system into a number of interconnected subsystems with decentralized (scalar) inputs or outputs. The procedure is preliminary to the hierarchic stabilization and estimation of linear systems and is performed on the subsystem level. A multilevel control scheme based upon the decomposition-aggregation method is developed for stabilization of input-decentralized linear systems Local linear feedback controllers are used to stabilize each decoupled subsystem, while global linear feedback controllers are utilized to minimize the coupling effect among the subsystems. Systems stabilized by the method have a tolerance to a wide class of nonlinearities in subsystem coupling and high reliability with respect to structural perturbations. The proposed output-decentralization and stabilization schemes can be used directly to construct asymptotic state estimators for large linear systems on the subsystem level. The problem of dimensionality is resolved by constructing a number of low-order estimators, thus avoiding a design of a single estimator for the overall system.

Managing Clustered Data Using Hierarchical Linear Modeling

ERIC Educational Resources Information Center

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

2012-01-01

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

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

ERIC Educational Resources Information Center

Ma, Xin; Klinger, Don A.

2000-01-01

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

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

ERIC Educational Resources Information Center

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

2009-01-01

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

Avoiding Boundary Estimates in Hierarchical Linear Models through Weakly Informative Priors

ERIC Educational Resources Information Center

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

2012-01-01

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

The Aggregation of Single-Case Results Using Hierarchical Linear Models

ERIC Educational Resources Information Center

Van den Noortgate, Wim; Onghena, Patrick

2007-01-01

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

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…

A hierarchical linear model for tree height prediction.

Treesearch

Vicente J. Monleon

2003-01-01

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

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…

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

ERIC Educational Resources Information Center

Anderson, Daniel

2012-01-01

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

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…

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…

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…

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

ERIC Educational Resources Information Center

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

2018-01-01

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

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

ERIC Educational Resources Information Center

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

2015-01-01

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

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

ERIC Educational Resources Information Center

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

2002-01-01

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

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

ERIC Educational Resources Information Center

Liu, Xing

2008-01-01

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

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

ERIC Educational Resources Information Center

Ishitani, Terry T.

2010-01-01

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

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

ERIC Educational Resources Information Center

Kara, Yusuf; Kamata, Akihito

2017-01-01

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

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.

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.

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

ERIC Educational Resources Information Center

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

2017-01-01

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

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 =…

An analytics approach to designing patient centered medical homes.

PubMed

Ajorlou, Saeede; Shams, Issac; Yang, Kai

2015-03-01

Recently the patient centered medical home (PCMH) model has become a popular team based approach focused on delivering more streamlined care to patients. In current practices of medical homes, a clinical based prediction frame is recommended because it can help match the portfolio capacity of PCMH teams with the actual load generated by a set of patients. Without such balances in clinical supply and demand, issues such as excessive under and over utilization of physicians, long waiting time for receiving the appropriate treatment, and non-continuity of care will eliminate many advantages of the medical home strategy. In this paper, by using the hierarchical generalized linear model with multivariate responses, we develop a clinical workload prediction model for care portfolio demands in a Bayesian framework. The model allows for heterogeneous variances and unstructured covariance matrices for nested random effects that arise through complex hierarchical care systems. We show that using a multivariate approach substantially enhances the precision of workload predictions at both primary and non primary care levels. We also demonstrate that care demands depend not only on patient demographics but also on other utilization factors, such as length of stay. Our analyses of a recent data from Veteran Health Administration further indicate that risk adjustment for patient health conditions can considerably improve the prediction power of the model.

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

ERIC Educational Resources Information Center

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

2016-01-01

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

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

USGS Publications Warehouse

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

2009-01-01

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

Hierarchical hollow microsphere and flower-like indium oxide: Controllable synthesis and application as H{sub 2}S cataluminescence sensing materials

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

Cai, Pingyang, E-mail: cpyxx@163.com; Bai, Wei, E-mail: weibaiscu@gmail.com; Zhang, Lichun, E-mail: lichun0203@yahoo.cn

Graphical abstract: Hierarchical hollow microsphere and flower-like In{sub 2}O{sub 3} were controllable fabricated through a novel and simple hydrothermal process, and the former showed superior cataluminescence sensing performance to H{sub 2}S. Highlights: ► In{sub 2}O{sub 3} hierarchical hollow sphere were prepared via a hydrothermal route. ► The growth process of In{sub 2}O{sub 3} hierarchical hollow sphere has been investigated. ► The sensor based on prepared In{sub 2}O{sub 3} shows good sensing performance to H{sub 2}S. -- Abstract: In the present work, In{sub 2}O{sub 3} hierarchical hollow microsphere and flower-like microstructure were achieved controllably by a hydrothermal process in the sodiummore » dodecyl sulfate (SDS)-N,N-dimethyl-formamide (DMF) system. XRD, SEM, HRTEM and N{sub 2} adsorption measurements were used to characterize the as-prepared indium oxide materials and the possible mechanism for the microstructures formation was briefly discussed. The cataluminescence gas sensor based on the as-prepared In{sub 2}O{sub 3} was utilized to detect H{sub 2}S concentrations in flowing air. Comparative gas sensing results revealed that the sensor based on hierarchical hollow microsphere exhibited much higher sensing sensitivity in detecting H{sub 2}S gas than the sensor based on flower-like microstructure. The present gas sensor had a fast response time of 5 s and a recovery time of less than 25 s, furthermore, the cataluminescence intensity vs. H{sub 2}S concentration was linear in range of 2–20 μg mL{sup −1} with a detection limit of 0.5 μg mL{sup −1}. The present highly sensitive, fast-responding, and low-cost In{sub 2}O{sub 3}-based gas sensor for H{sub 2}S would have many practical applications.« less

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

NASA Astrophysics Data System (ADS)

Akaishi, Akira; Aoki, Kazuki; Shudo, Akira

2017-05-01

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

When linearity prevails over hierarchy in syntax

PubMed Central

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

2018-01-01

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

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.

Health service utilization before and after evidence-based treatment for PTSD.

PubMed

Tuerk, Peter W; Wangelin, Bethany; Rauch, Sheila A M; Dismuke, Clara E; Yoder, Matthew; Myrick, Hugh; Eftekhari, Afsoon; Acierno, Ron

2013-11-01

Posttraumatic stress disorder (PTSD) is associated with functional impairment, co-occurring diagnoses, and increased health care utilization. Associated high demand for health care services is an important contributor to the large public-health cost of PTSD. Treatments incorporating exposure therapy are efficacious in ameliorating or eliminating PTSD symptoms. Accordingly, the Veterans Health Administration has made significant investments toward nationwide dissemination of a manualized exposure therapy protocol, prolonged exposure (PE). PE is effective with veterans; however, the relationship between PE and mental health service utilization is unknown. The current study investigates PE as it relates to actual tracked mental health service utilization in an urban VA medical center. A sample of 60 veterans with a diagnosis of PTSD was used to examine mental health service utilization in the 12-months prior to and 12-months after being offered PE. Hierarchical Linear Models and traditional repeated-measures ANOVA were used to estimate R²- and d-type effect sizes for service utilization. Associated estimated cost saving are reported. PE was associated with large reductions in symptoms and diagnosis remission. Treatment was also associated with statistically significant, large reductions in mental health service utilization for veterans who completed treatment. Findings suggest that expanding access to PE can increase access to mental health services in general by decreasing ongoing demand for specialty care clinical services.

Bayesian Correction for Misclassification in Multilevel Count Data Models.

PubMed

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

2018-01-01

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

Free-Standing Air Cathodes Based on 3D Hierarchically Porous Carbon Membranes: Kinetic Overpotential of Continuous Macropores in Li-O2 Batteries.

PubMed

Xu, Shu-Mao; Liang, Xiao; Ren, Zhi-Chu; Wang, Kai-Xue; Chen, Jie-Sheng

2018-06-04

Free-standing macroporous air electrodes with enhanced interfacial contact, rapid mass transport, and tailored deposition space for large amounts of Li 2 O 2 are essential for improving the rate performance of Li-O 2 batteries. An ordered mesoporous carbon membrane with continuous macroporous channels was prepared by inversely topological transformation from ZnO nanorod array. Utilized as a free-standing air cathode for Li-O 2 battery, the hierarchically porous carbon membrane shows superior rate performance. However, the increased cross-sectional area of the continuous macropores on the cathode surface leads to a kinetic overpotential with large voltage hysteresis and linear voltage variation against Butler-Volmer behavior. The kinetics were investigated based on the rate-determining step of second electron transfer accompanied by migration of Li + in solid or quasi-solid intermediates. These discoveries shed light on the design of the air cathode for Li-O 2 batteries with high-rate performance. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

Alverson, Charlotte Y; Yamamoto, Scott H

2018-01-01

This study utilized hierarchical linear modeling analysis of a 10-year extant dataset from Rehabilitation Services Administration to investigate significant predictors of employment outcomes for vocational rehabilitation (VR) clients with autism. Predictor variables were gender, ethnicity, attained education level, IEP status in high school, secondary disability status, and total number of VR services. Competitive employment was the criterion variable. Only one predictor variable, Total Number of VR Services, was significant across all 10 years. IEP status in high school was not significant in any year. The remaining predictors were significant in one or more years. Further research and implications for researchers and practitioners are included.

Attitude and vibration control of a large flexible space-based antenna

NASA Technical Reports Server (NTRS)

Joshi, S. M.

1982-01-01

Control systems synthesis is considered for controlling the rigid body attitude and elastic motion of a large deployable space-based antenna. Two methods for control systems synthesis are considered. The first method utilizes the stability and robustness properties of the controller consisting of torque actuators and collocated attitude and rate sensors. The second method is based on the linear-quadratic-Gaussian control theory. A combination of the two methods, which results in a two level hierarchical control system, is also briefly discussed. The performance of the controllers is analyzed by computing the variances of pointing errors, feed misalignment errors and surface contour errors in the presence of sensor and actuator noise.

Hierarchical tone mapping for high dynamic range image visualization

NASA Astrophysics Data System (ADS)

Qiu, Guoping; Duan, Jiang

2005-07-01

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

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.

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

ERIC Educational Resources Information Center

Ngu, Bing Hiong; Phan, Huy P.

2016-01-01

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

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

Science.gov Websites

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

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

NASA Astrophysics Data System (ADS)

Zhao, Liang; Huang, Shoudong; Dissanayake, Gamini

2018-07-01

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

Impact of Individual-, Environmental-, and Policy-Level Factors on Health Care Utilization Among US Farmworkers

PubMed Central

Mayer, Joni A.; Gabbard, Susan; Kronick, Richard G.; Roesch, Scott C.; Malcarne, Vanessa L.; Zuniga, Maria L.

2011-01-01

Objectives. We examined individual-, environmental-, and policy-level correlates of US farmworker health care utilization, guided by the behavioral model for vulnerable populations and the ecological model. Methods. The 2006 and 2007 administrations of the National Agricultural Workers Survey (n = 2884) provided the primary data. Geographic information systems, the 2005 Uniform Data System, and rurality and border proximity indices provided environmental variables. To identify factors associated with health care use, we performed logistic regression using weighted hierarchical linear modeling. Results. Approximately half (55.3%) of farmworkers utilized US health care in the previous 2 years. Several factors were independently associated with use at the individual level (gender, immigration and migrant status, English proficiency, transportation access, health status, and non-US health care utilization), the environmental level (proximity to US–Mexico border), and the policy level (insurance status and workplace payment structure). County Federally Qualified Health Center resources were not independently associated. Conclusions. We identified farmworkers at greatest risk for poor access. We made recommendations for change to farmworker health care access at all 3 levels of influence, emphasizing Federally Qualified Health Center service delivery. PMID:21330594

Students' motivational beliefs in science learning, school motivational contexts, and science achievement in Taiwan

NASA Astrophysics Data System (ADS)

Wang, Cheng-Lung; Liou, Pey-Yan

2017-05-01

Taiwanese students are featured as having high academic achievement but low motivational beliefs according to the serial results of the Trends in Mathematics and Science Study (TIMSS). Moreover, given that the role of context has become more important in the development of academic motivation theory, this study aimed to examine the relationship between motivational beliefs and science achievement at both the student and school levels. Based on the Expectancy-Value Theory, the three motivational beliefs, namely self-concept, intrinsic value, and utility value, were the focuses of this study. The two-level hierarchical linear model was used to analyse the Taiwanese TIMSS 2011 eighth-grade student data. The results indicated that each motivational belief had a positive predictive effect on science achievement. Additionally, a positive school contextual effect of self-concept on science achievement was identified. Furthermore, school-mean utility value had a negative moderating effect on the relationship between utility value and science achievement. In conclusion, this study sheds light on the functioning of motivational beliefs in science learning among Taiwanese adolescents with consideration of the school motivational contexts.

Hierarchical cortical transcriptome disorganization in autism.

PubMed

Lombardo, Michael V; Courchesne, Eric; Lewis, Nathan E; Pramparo, Tiziano

2017-01-01

Autism spectrum disorders (ASD) are etiologically heterogeneous and complex. Functional genomics work has begun to identify a diverse array of dysregulated transcriptomic programs (e.g., synaptic, immune, cell cycle, DNA damage, WNT signaling, cortical patterning and differentiation) potentially involved in ASD brain abnormalities during childhood and adulthood. However, it remains unclear whether such diverse dysregulated pathways are independent of each other or instead reflect coordinated hierarchical systems-level pathology. Two ASD cortical transcriptome datasets were re-analyzed using consensus weighted gene co-expression network analysis (WGCNA) to identify common co-expression modules across datasets. Linear mixed-effect models and Bayesian replication statistics were used to identify replicable differentially expressed modules. Eigengene network analysis was then utilized to identify between-group differences in how co-expression modules interact and cluster into hierarchical meta-modular organization. Protein-protein interaction analyses were also used to determine whether dysregulated co-expression modules show enhanced interactions. We find replicable evidence for 10 gene co-expression modules that are differentially expressed in ASD cortex. Rather than being independent non-interacting sources of pathology, these dysregulated co-expression modules work in synergy and physically interact at the protein level. These systems-level transcriptional signals are characterized by downregulation of synaptic processes coordinated with upregulation of immune/inflammation, response to other organism, catabolism, viral processes, translation, protein targeting and localization, cell proliferation, and vasculature development. Hierarchical organization of meta-modules (clusters of highly correlated modules) is also highly affected in ASD. These findings highlight that dysregulation of the ASD cortical transcriptome is characterized by the dysregulation of multiple coordinated transcriptional programs producing synergistic systems-level effects that cannot be fully appreciated by studying the individual component biological processes in isolation.

Multistep hierarchical self-assembly of chiral nanopore arrays

PubMed Central

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

2014-01-01

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

A Hierarchical Clustering Methodology for the Estimation of Toxicity

EPA Science Inventory

A Quantitative Structure Activity Relationship (QSAR) methodology based on hierarchical clustering was developed to predict toxicological endpoints. This methodology utilizes Ward's method to divide a training set into a series of structurally similar clusters. The structural sim...

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.

High-linearity piezoresistive response of mechanically strong graphene-based elastomer

NASA Astrophysics Data System (ADS)

Yuanzheng, Luo; Buyin, Li; Xiaoqi

2017-05-01

Traditional additive-free graphene bulk materials based on mono- three dimensional(3D) graphene networks type are fragile in most cases, which is unfavorable for their potential applications. Here we present compressible graphene foams (CGF) with superior properties endowed by the hierarchical porous structure, which taking graphene sheets as an inorganic embedding material and polyurethane sponge (PUS) as a polymer open-framework. The preparation process utilized a dip-coating method associated with directional freezing followed by lyophilization. The as-synthesized CGF not only possess a combination of ultralow density and excellent electrical conductivity, but it also can withstand large strains (>99%) without permanent deformation or fracture. We believe that these sponge/graphene embeddable multifunctional nanocomposites will expand practical applications of graphene monolith in the future.

The Protective Role of Group Identity: Sectarian Antisocial Behavior and Adolescent Emotion Problems

PubMed Central

Merrilees, Christine E.; Taylor, Laura K.; Goeke-Morey, Marcie C.; Shirlow, Peter; Cummings, E. Mark; Cairns, Ed

2013-01-01

The protective role of strength of group identity was examined for youth in a context of protracted political conflict. Participants included 814 adolescents (M age = 13.61, SD = 1.99 at Time 1) participating in a longitudinal study in Belfast, Northern Ireland. Utilizing hierarchical linear modeling, the results show that the effect of exposure to sectarian antisocial behaviors has a stronger effect on youth emotion problems for older adolescents. The results also show that youth with higher strength of group identity reported fewer emotion problems in the face of sectarian antisocial behavior, but that this buffering effect is stronger for Protestants compared to Catholics. Implications are discussed for understanding the role of social identity in post-accord societies. PMID:23682959

Abstract Linguistic Structure Correlates with Temporal Activity during Naturalistic Comprehension

PubMed Central

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

2016-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

Hierarchical Bayes approach for subgroup analysis.

PubMed

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

2017-01-01

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

Hierarchical Rhetorical Sentence Categorization for Scientific Papers

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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.

The Hierarchical Structure of Formal Operational Tasks.

ERIC Educational Resources Information Center

Bart, William M.; Mertens, Donna M.

1979-01-01

The hierarchical structure of the formal operational period of Piaget's theory of cognitive development was explored through the application of ordering theoretical methods to a set of data that systematically utilized the various formal operational schemes. Results suggested a common structure underlying task performance. (Author/BH)

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

PubMed

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

2017-02-01

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

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

ERIC Educational Resources Information Center

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

2006-01-01

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

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

PubMed Central

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

2011-01-01

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

Hierarchical structural health monitoring system combining a fiber optic spinal cord network and distributed nerve cell devices

NASA Astrophysics Data System (ADS)

Minakuchi, Shu; Tsukamoto, Haruka; Takeda, Nobuo

2009-03-01

This study proposes novel hierarchical sensing concept for detecting damages in composite structures. In the hierarchical system, numerous three-dimensionally structured sensor devices are distributed throughout the whole structural area and connected with the optical fiber network through transducing mechanisms. The distributed "sensory nerve cell" devices detect the damage, and the fiber optic "spinal cord" network gathers damage signals and transmits the information to a measuring instrument. This study began by discussing the basic concept of the hierarchical sensing system thorough comparison with existing fiber optic based systems and nerve systems in the animal kingdom. Then, in order to validate the proposed sensing concept, impact damage detection system for the composite structure was proposed. The sensor devices were developed based on Comparative Vacuum Monitoring (CVM) system and the Brillouin based distributed strain sensing was utilized to gather the damage signals from the distributed devices. Finally a verification test was conducted using prototype devices. Occurrence of barely visible impact damage was successfully detected and it was clearly indicated that the hierarchical system has better repairability, higher robustness, and wider monitorable area compared to existing systems utilizing embedded optical fiber sensors.

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

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

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

1996-10-01

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

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…

Vessel Classification in Cosmo-Skymed SAR Data Using Hierarchical Feature Selection

NASA Astrophysics Data System (ADS)

Makedonas, A.; Theoharatos, C.; Tsagaris, V.; Anastasopoulos, V.; Costicoglou, S.

2015-04-01

SAR based ship detection and classification are important elements of maritime monitoring applications. Recently, high-resolution SAR data have opened new possibilities to researchers for achieving improved classification results. In this work, a hierarchical vessel classification procedure is presented based on a robust feature extraction and selection scheme that utilizes scale, shape and texture features in a hierarchical way. Initially, different types of feature extraction algorithms are implemented in order to form the utilized feature pool, able to represent the structure, material, orientation and other vessel type characteristics. A two-stage hierarchical feature selection algorithm is utilized next in order to be able to discriminate effectively civilian vessels into three distinct types, in COSMO-SkyMed SAR images: cargos, small ships and tankers. In our analysis, scale and shape features are utilized in order to discriminate smaller types of vessels present in the available SAR data, or shape specific vessels. Then, the most informative texture and intensity features are incorporated in order to be able to better distinguish the civilian types with high accuracy. A feature selection procedure that utilizes heuristic measures based on features' statistical characteristics, followed by an exhaustive research with feature sets formed by the most qualified features is carried out, in order to discriminate the most appropriate combination of features for the final classification. In our analysis, five COSMO-SkyMed SAR data with 2.2m x 2.2m resolution were used to analyse the detailed characteristics of these types of ships. A total of 111 ships with available AIS data were used in the classification process. The experimental results show that this method has good performance in ship classification, with an overall accuracy reaching 83%. Further investigation of additional features and proper feature selection is currently in progress.

Personalized Medicine Enrichment Design for DHA Supplementation Clinical Trial.

PubMed

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

2017-03-01

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

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

PubMed Central

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

2014-01-01

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

School system evaluation by value added analysis under endogeneity.

PubMed

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

Jing, Yingqi

2017-07-01

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

Measuring the hierarchy of feedforward networks

NASA Astrophysics Data System (ADS)

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

2011-03-01

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

Predictors of Service Utilization among Youth Diagnosed with Mood Disorders

ERIC Educational Resources Information Center

Mendenhall, Amy N.

2012-01-01

In this study, I investigated patterns and predictors of service utilization for children with mood disorders. The Behavioral Model for Health Care Utilization was used as an organizing framework for identifying predictors of the number and quality of services utilized. Hierarchical regression was used in secondary data analyses of the…

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

Assessing Student Achievement in Large-Scale Educational Programs Using Hierarchical Propensity Scores

ERIC Educational Resources Information Center

Vaughan, Angela L.; Lalonde, Trent L.; Jenkins-Guarnieri, Michael A.

2014-01-01

Many researchers assessing the efficacy of educational programs face challenges due to issues with non-randomization and the likelihood of dependence between nested subjects. The purpose of the study was to demonstrate a rigorous research methodology using a hierarchical propensity score matching method that can be utilized in contexts where…

NOA: A Scalable Multi-Parent Clustering Hierarchy for WSNs

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

Cree, Johnathan V.; Delgado-Frias, Jose; Hughes, Michael A.

2012-08-10

NOA is a multi-parent, N-tiered, hierarchical clustering algorithm that provides a scalable, robust and reliable solution to autonomous configuration of large-scale wireless sensor networks. The novel clustering hierarchy's inherent benefits can be utilized by in-network data processing techniques to provide equally robust, reliable and scalable in-network data processing solutions capable of reducing the amount of data sent to sinks. Utilizing a multi-parent framework, NOA reduces the cost of network setup when compared to hierarchical beaconing solutions by removing the expense of r-hop broadcasting (r is the radius of the cluster) needed to build the network and instead passes network topologymore » information among shared children. NOA2, a two-parent clustering hierarchy solution, and NOA3, the three-parent variant, saw up to an 83% and 72% reduction in overhead, respectively, when compared to performing one round of a one-parent hierarchical beaconing, as well as 92% and 88% less overhead when compared to one round of two- and three-parent hierarchical beaconing hierarchy.« less

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

PubMed

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

2017-09-01

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

Hierarchical clustering in chameleon f(R) gravity

NASA Astrophysics Data System (ADS)

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

2013-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Reciprocal Prioritization to Dietary Glycans by Gut Bacteria in a Competitive Environment Promotes Stable Coexistence

PubMed Central

Tuncil, Yunus E.; Xiao, Yao; Porter, Nathan T.; Reuhs, Bradley L.

2017-01-01

ABSTRACT When presented with nutrient mixtures, several human gut Bacteroides species exhibit hierarchical utilization of glycans through a phenomenon that resembles catabolite repression. However, it is unclear how closely these observed physiological changes, often measured by altered transcription of glycan utilization genes, mirror actual glycan depletion. To understand the glycan prioritization strategies of two closely related human gut symbionts, Bacteroides ovatus and Bacteroides thetaiotaomicron, we performed a series of time course assays in which both species were individually grown in a medium with six different glycans that both species can degrade. Disappearance of the substrates and transcription of the corresponding polysaccharide utilization loci (PULs) were measured. Each species utilized some glycans before others, but with different priorities per species, providing insight into species-specific hierarchical preferences. In general, the presence of highly prioritized glycans repressed transcription of genes involved in utilizing lower-priority nutrients. However, transcriptional sensitivity to some glycans varied relative to the residual concentration in the medium, with some PULs that target high-priority substrates remaining highly expressed even after their target glycan had been mostly depleted. Coculturing of these organisms in the same mixture showed that the hierarchical orders generally remained the same, promoting stable coexistence. Polymer length was found to be a contributing factor for glycan utilization, thereby affecting its place in the hierarchy. Our findings not only elucidate how B. ovatus and B. thetaiotaomicron strategically access glycans to maintain coexistence but also support the prioritization of carbohydrate utilization based on carbohydrate structure, advancing our understanding of the relationships between diet and the gut microbiome. PMID:29018117

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

NASA Astrophysics Data System (ADS)

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

2013-10-01

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

Exploring the Link Between Alcohol and Marijuana Use and Teen Dating Violence Victimization Among High School Students: The Influence of School Context.

PubMed

Parker, Elizabeth M; Debnam, Katrina; Pas, Elise T; Bradshaw, Catherine P

2016-10-01

Adolescence is a developmental period when dating behavior is first initiated and when the risk of abuse by or against a dating partner begins to emerge. It is also one in which experimentation with alcohol and illicit substances typically begins. The current study examined the association between recent alcohol use and recent marijuana use and the experience of physical and verbal teen dating violence (TDV) victimization while considering the potential influence of school contextual variables. Data came from 27,758 high school students attending 58 Maryland public high schools. Hierarchical linear modeling was used to identify student- and school-level predictors associated with TDV. Results indicated that approximately 11% of students reported experiencing physical TDV and 11% of students reported experiencing verbal TDV over the past year. In addition, 33% of students reported recent alcohol use and 21% reported recent marijuana use. Hierarchical linear modeling results revealed that students who reported frequent recent alcohol or recent marijuana use were at increased odds of experiencing physical (adjusted odds ratio [AOR]alcohol = 2.80, p < .001; AORmarijuana = 2.03, p < .001) or verbal TDV (AORalcohol = 2.63, p < .001; AORmarijuana = 2.20, p < .001) victimization compared to students who reported little or no alcohol or marijuana use. School support was a protective factor for both physical TDV (AOR = 0.74, p < .001) and verbal TDV (AOR = 0.76, p < .001) victimization. Findings suggested that prevention efforts to address alcohol and marijuana use may have an effect on TDV victimization. Results also highlight the potential utility of enhancing student perceptions of school support as an approach for reducing TDV victimization. © 2015 Society for Public Health Education.

A hierarchical spatial framework for forest landscape planning.

Treesearch

Pete Bettinger; Marie Lennette; K. Norman Johnson; Thomas A. Spies

2005-01-01

A hierarchical spatial framework for large-scale, long-term forest landscape planning is presented along with example policy analyses for a 560,000 ha area of the Oregon Coast Range. The modeling framework suggests utilizing the detail provided by satellite imagery to track forest vegetation condition and for representation of fine-scale features, such as riparian...

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

PubMed

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

2011-01-01

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

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

PubMed Central

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

2011-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

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

ERIC Educational Resources Information Center

Wang, Yuqian; Barmby, Patrick; Bolden, David

2017-01-01

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

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

PubMed

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

2006-12-01

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

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

DOE PAGES

Michalak, Sarah E.; Morris, Carl N.

2015-07-17

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

Asymptotic analysis of hierarchical martensitic microstructure

NASA Astrophysics Data System (ADS)

Cesana, Pierluigi; Porta, Marcel; Lookman, Turab

2014-12-01

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

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

PubMed Central

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

2012-01-01

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

Multi-Scale and Object-Oriented Analysis for Mountain Terrain Segmentation and Geomorphological Assessment

NASA Astrophysics Data System (ADS)

Marston, B. K.; Bishop, M. P.; Shroder, J. F.

2009-12-01

Digital terrain analysis of mountain topography is widely utilized for mapping landforms, assessing the role of surface processes in landscape evolution, and estimating the spatial variation of erosion. Numerous geomorphometry techniques exist to characterize terrain surface parameters, although their utility to characterize the spatial hierarchical structure of the topography and permit an assessment of the erosion/tectonic impact on the landscape is very limited due to scale and data integration issues. To address this problem, we apply scale-dependent geomorphometric and object-oriented analyses to characterize the hierarchical spatial structure of mountain topography. Specifically, we utilized a high resolution digital elevation model to characterize complex topography in the Shimshal Valley in the Western Himalaya of Pakistan. To accomplish this, we generate terrain objects (geomorphological features and landform) including valley floors and walls, drainage basins, drainage network, ridge network, slope facets, and elemental forms based upon curvature. Object-oriented analysis was used to characterize object properties accounting for object size, shape, and morphometry. The spatial overlay and integration of terrain objects at various scales defines the nature of the hierarchical organization. Our results indicate that variations in the spatial complexity of the terrain hierarchical organization is related to the spatio-temporal influence of surface processes and landscape evolution dynamics. Terrain segmentation and the integration of multi-scale terrain information permits further assessment of process domains and erosion, tectonic impact potential, and natural hazard potential. We demonstrate this with landform mapping and geomorphological assessment examples.

Hierarchical Bayesian spatial models for multispecies conservation planning and monitoring

Treesearch

Carlos Carroll; Devin S. Johnson; Jeffrey R. Dunk; William J. Zielinski

2010-01-01

Biologists who develop and apply habitat models are often familiar with the statistical challenges posed by their data’s spatial structure but are unsure of whether the use of complex spatial models will increase the utility of model results in planning. We compared the relative performance of nonspatial and hierarchical Bayesian spatial models for three vertebrate and...

LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients

Treesearch

Chad Babcock; Andrew O. Finley; John B. Bradford; Randy Kolka; Richard Birdsey; Michael G. Ryan

2015-01-01

Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both...

Visual Attention to Global and Local Stimulus Properties in 6-Month-Old Infants: Individual Differences and Event-Related Potentials

ERIC Educational Resources Information Center

Guy, Maggie W.; Reynolds, Greg D.; Zhang, Dantong

2013-01-01

Event-related potentials (ERPs) were utilized in an investigation of 21 six-month-olds' attention to and processing of global and local properties of hierarchical patterns. Overall, infants demonstrated an advantage for processing the overall configuration (i.e., global properties) of local features of hierarchical patterns; however,…

Novel hierarchically porous carbon materials obtained from natural biopolymer as host matrixes for lithium-sulfur battery applications.

PubMed

Zhang, Bin; Xiao, Min; Wang, Shuanjin; Han, Dongmei; Song, Shuqin; Chen, Guohua; Meng, Yuezhong

2014-08-13

Novel hierarchically porous carbon materials with very high surface areas, large pore volumes and high electron conductivities were prepared from silk cocoon by carbonization with KOH activation. The prepared novel porous carbon-encapsulated sulfur composites were fabricated by a simple melting process and used as cathodes for lithium sulfur batteries. Because of the large surface area and hierarchically porous structure of the carbon material, soluble polysulfide intermediates can be trapped within the cathode and the volume expansion can be alleviated effectively. Moreover, the electron transport properties of the carbon materials can provide an electron conductive network and promote the utilization rate of sulfur in cathode. The prepared carbon-sulfur composite exhibited a high specific capacity and excellent cycle stability. The results show a high initial discharge capacity of 1443 mAh g(-1) and retain 804 mAh g(-1) after 80 discharge/charge cycles at a rate of 0.5 C. A Coulombic efficiency retained up to 92% after 80 cycles. The prepared hierarchically porous carbon materials were proven to be an effective host matrix for sulfur encapsulation to improve the sulfur utilization rate and restrain the dissolution of polysulfides into lithium-sulfur battery electrolytes.

Control Strategies for Guided Collective Motion

DTIC Science & Technology

2015-02-27

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

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

PubMed

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

2018-05-30

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

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

ERIC Educational Resources Information Center

Saupe, Joe L.

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

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

ERIC Educational Resources Information Center

Kim, Mikyong Minsun; Conrad, Clifton F.

2006-01-01

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

Control of discrete event systems modeled as hierarchical state machines

NASA Technical Reports Server (NTRS)

Brave, Y.; Heymann, M.

1991-01-01

The authors examine a class of discrete event systems (DESs) modeled as asynchronous hierarchical state machines (AHSMs). For this class of DESs, they provide an efficient method for testing reachability, which is an essential step in many control synthesis procedures. This method utilizes the asynchronous nature and hierarchical structure of AHSMs, thereby illustrating the advantage of the AHSM representation as compared with its equivalent (flat) state machine representation. An application of the method is presented where an online minimally restrictive solution is proposed for the problem of maintaining a controlled AHSM within prescribed legal bounds.

Hierarchically Superstructured Prussian Blue Analogues: Spontaneous Assembly Synthesis and Applications as Pseudocapacitive Materials

DOE PAGES

Yue, Yanfeng; Zhang, Zhiyong; Binder, Andrew J.; ...

2014-11-10

Hierarchically superstructured Prussian blue analogues (hexa- conventional hybrid graphene/MnO 2 nanostructured textiles. cyanoferrate, M = Ni II, Co II and Cu II) are synthesized through Because sodium or potassium ions are involved in energy stor- a spontaneous assembly technique. In sharp contrast to mac- age processes, more environmentally neutral electrolytes can roporous-only Prussian blue analogues, the hierarchically su- be utilized, making the superstructured porous Prussian blue perstructured porous Prussian blue materials are demonstrated analogues a great contender for applications as high-per- to possess a high capacitance, which is similar to those of the formance pseudocapacitors.

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

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

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

PubMed

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

2016-04-06

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

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

PubMed

Zhang, Hou-Dao; Yan, YiJing

2016-05-19

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

Sparse Bayesian learning for DOA estimation with mutual coupling.

PubMed

Dai, Jisheng; Hu, Nan; Xu, Weichao; Chang, Chunqi

2015-10-16

Sparse Bayesian learning (SBL) has given renewed interest to the problem of direction-of-arrival (DOA) estimation. It is generally assumed that the measurement matrix in SBL is precisely known. Unfortunately, this assumption may be invalid in practice due to the imperfect manifold caused by unknown or misspecified mutual coupling. This paper describes a modified SBL method for joint estimation of DOAs and mutual coupling coefficients with uniform linear arrays (ULAs). Unlike the existing method that only uses stationary priors, our new approach utilizes a hierarchical form of the Student t prior to enforce the sparsity of the unknown signal more heavily. We also provide a distinct Bayesian inference for the expectation-maximization (EM) algorithm, which can update the mutual coupling coefficients more efficiently. Another difference is that our method uses an additional singular value decomposition (SVD) to reduce the computational complexity of the signal reconstruction process and the sensitivity to the measurement noise.

Functional genomic Landscape of Human Breast Cancer drivers, vulnerabilities, and resistance

PubMed Central

Marcotte, Richard; Sayad, Azin; Brown, Kevin R.; Sanchez-Garcia, Felix; Reimand, Jüri; Haider, Maliha; Virtanen, Carl; Bradner, James E.; Bader, Gary D.; Mills, Gordon B.; Pe’er, Dana; Moffat, Jason; Neel, Benjamin G.

2016-01-01

Summary Large-scale genomic studies have identified multiple somatic aberrations in breast cancer, including copy number alterations, and point mutations. Still, identifying causal variants and emergent vulnerabilities that arise as a consequence of genetic alterations remain major challenges. We performed whole genome shRNA “dropout screens” on 77 breast cancer cell lines. Using a hierarchical linear regression algorithm to score our screen results and integrate them with accompanying detailed genetic and proteomic information, we identify vulnerabilities in breast cancer, including candidate “drivers,” and reveal general functional genomic properties of cancer cells. Comparisons of gene essentiality with drug sensitivity data suggest potential resistance mechanisms, effects of existing anti-cancer drugs, and opportunities for combination therapy. Finally, we demonstrate the utility of this large dataset by identifying BRD4 as a potential target in luminal breast cancer, and PIK3CA mutations as a resistance determinant for BET-inhibitors. PMID:26771497

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

PubMed

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

2013-09-01

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

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

ERIC Educational Resources Information Center

Lin, Fou-Lai; Yang, Kai-Lin

2004-01-01

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

Caregiver Life Satisfaction: Relationship to Youth Symptom Severity through Treatment

PubMed Central

Athay, M. Michele

2013-01-01

Objective This study utilized the Satisfaction with Life Scale (SWLS) to investigate the life satisfaction of caregivers for youth receiving mental health services (N = 383), specifically how it relates to youth symptom severity throughout treatment. Method Hierarchical linear modeling (HLM) with a time-varying covariate was used to estimate the linear trajectory of caregiver life satisfaction and how it relates to youth symptom severity as rated by caregivers, youth, and clinicians. Results Initial caregiver life satisfaction was inversely related to caregiver and clinician rated youth symptom severity. Additionally, subsequent caregiver life satisfaction demonstrated a small but significant relationship to changes in youth symptom severity during treatment where a decrease in youth symptoms corresponded to an increase in caregiver life satisfaction, and vice versa. Caregiver background characteristics related to higher life satisfaction include being: married, a birth-parent, under 40 years old and having the absence of previous diagnoses of an emotional, behavioral or substance use disorder. Conclusion Caregivers of clinically-referred youth report low levels of life satisfaction throughout youth treatment. Given the bi-directional influences on one another, tending to the well-being of caregivers may positively influence both caregivers and youths. PMID:22571285

Caregiver life satisfaction: relationship to youth symptom severity through treatment.

PubMed

Athay, M Michele

2012-01-01

This study utilized the Satisfaction with Life Scale to investigate the life satisfaction of caregivers for youth receiving mental health services (N = 383). Specifically, this study assessed how caregiver life satisfaction relates to youth symptom severity throughout treatment. Hierarchical linear modeling with a time-varying covariate was used to estimate the linear trajectory of caregiver life satisfaction and how it relates to youth symptom severity as rated by caregivers, youth, and clinicians. Results found initial caregiver life satisfaction was inversely related to caregiver and clinician rated youth symptom severity. In addition, subsequent caregiver life satisfaction demonstrated a small but significant relationship to changes in youth symptom severity during treatment where a decrease in youth symptoms corresponded to an increase in caregiver life satisfaction, and vice versa. Caregiver background characteristics related to higher life satisfaction included being (a) married, a birth parent, and younger than 40 years old, and (b) having the absence of previous diagnoses of an emotional, behavioral, or substance use disorder. Despite significant change over time, caregivers of clinically referred youth demonstrated low levels of life satisfaction throughout youth treatment. Given the bidirectional influences on one another, tending to the well-being of caregivers may positively influence both caregivers and youths.

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

NASA Technical Reports Server (NTRS)

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

1995-01-01

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

Single-cell characterization of metabolic switching in the sugar phosphotransferase system of Escherichia coli.

PubMed

Westermayer, Sonja A; Fritz, Georg; Gutiérrez, Joaquín; Megerle, Judith A; Weißl, Mira P S; Schnetz, Karin; Gerland, Ulrich; Rädler, Joachim O

2016-05-01

The utilization of several sugars in Escherichia coli is regulated by the Phosphotransferase System (PTS), in which diverse sugar utilization modules compete for phosphoryl flux from the general PTS proteins. Existing theoretical work predicts a winner-take-all outcome when this flux limits carbon uptake. To date, no experimental work has interrogated competing PTS uptake modules with single-cell resolution. Using time-lapse microscopy in perfused microchannels, we analyzed the competition between N-acetyl-glucosamine and sorbitol, as representative PTS sugars, by measuring both the expression of their utilization systems and the concomitant impact of sugar utilization on growth rates. We find two distinct regimes: hierarchical usage of the carbohydrates, and co-expression of the genes for both systems. Simulations of a mathematical model incorporating asymmetric sugar quality reproduce our metabolic phase diagram, indicating that under conditions of nonlimiting phosphate flux, co-expression is due to uncoupling of both sugar utilization systems. Our model reproduces hierarchical winner-take-all behaviour and stochastic co-expression, and predicts the switching between both strategies as a function of available phosphate flux. Hence, experiments and theory both suggest that PTS sugar utilization involves not only switching between the sugars utilized but also switching of utilization strategies to accommodate prevailing environmental conditions. © 2016 John Wiley & Sons Ltd.

Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems

PubMed Central

Siddiqi, Muhammad Hameed; Lee, Sungyoung; Lee, Young-Koo; Khan, Adil Mehmood; Truc, Phan Tran Ho

2013-01-01

Over the last decade, human facial expressions recognition (FER) has emerged as an important research area. Several factors make FER a challenging research problem. These include varying light conditions in training and test images; need for automatic and accurate face detection before feature extraction; and high similarity among different expressions that makes it difficult to distinguish these expressions with a high accuracy. This work implements a hierarchical linear discriminant analysis-based facial expressions recognition (HL-FER) system to tackle these problems. Unlike the previous systems, the HL-FER uses a pre-processing step to eliminate light effects, incorporates a new automatic face detection scheme, employs methods to extract both global and local features, and utilizes a HL-FER to overcome the problem of high similarity among different expressions. Unlike most of the previous works that were evaluated using a single dataset, the performance of the HL-FER is assessed using three publicly available datasets under three different experimental settings: n-fold cross validation based on subjects for each dataset separately; n-fold cross validation rule based on datasets; and, finally, a last set of experiments to assess the effectiveness of each module of the HL-FER separately. Weighted average recognition accuracy of 98.7% across three different datasets, using three classifiers, indicates the success of employing the HL-FER for human FER. PMID:24316568

A Saliency Guided Semi-Supervised Building Change Detection Method for High Resolution Remote Sensing Images

PubMed Central

Hou, Bin; Wang, Yunhong; Liu, Qingjie

2016-01-01

Characterizations of up to date information of the Earth’s surface are an important application providing insights to urban planning, resources monitoring and environmental studies. A large number of change detection (CD) methods have been developed to solve them by utilizing remote sensing (RS) images. The advent of high resolution (HR) remote sensing images further provides challenges to traditional CD methods and opportunities to object-based CD methods. While several kinds of geospatial objects are recognized, this manuscript mainly focuses on buildings. Specifically, we propose a novel automatic approach combining pixel-based strategies with object-based ones for detecting building changes with HR remote sensing images. A multiresolution contextual morphological transformation called extended morphological attribute profiles (EMAPs) allows the extraction of geometrical features related to the structures within the scene at different scales. Pixel-based post-classification is executed on EMAPs using hierarchical fuzzy clustering. Subsequently, the hierarchical fuzzy frequency vector histograms are formed based on the image-objects acquired by simple linear iterative clustering (SLIC) segmentation. Then, saliency and morphological building index (MBI) extracted on difference images are used to generate a pseudo training set. Ultimately, object-based semi-supervised classification is implemented on this training set by applying random forest (RF). Most of the important changes are detected by the proposed method in our experiments. This study was checked for effectiveness using visual evaluation and numerical evaluation. PMID:27618903

A Saliency Guided Semi-Supervised Building Change Detection Method for High Resolution Remote Sensing Images.

PubMed

Hou, Bin; Wang, Yunhong; Liu, Qingjie

2016-08-27

Characterizations of up to date information of the Earth's surface are an important application providing insights to urban planning, resources monitoring and environmental studies. A large number of change detection (CD) methods have been developed to solve them by utilizing remote sensing (RS) images. The advent of high resolution (HR) remote sensing images further provides challenges to traditional CD methods and opportunities to object-based CD methods. While several kinds of geospatial objects are recognized, this manuscript mainly focuses on buildings. Specifically, we propose a novel automatic approach combining pixel-based strategies with object-based ones for detecting building changes with HR remote sensing images. A multiresolution contextual morphological transformation called extended morphological attribute profiles (EMAPs) allows the extraction of geometrical features related to the structures within the scene at different scales. Pixel-based post-classification is executed on EMAPs using hierarchical fuzzy clustering. Subsequently, the hierarchical fuzzy frequency vector histograms are formed based on the image-objects acquired by simple linear iterative clustering (SLIC) segmentation. Then, saliency and morphological building index (MBI) extracted on difference images are used to generate a pseudo training set. Ultimately, object-based semi-supervised classification is implemented on this training set by applying random forest (RF). Most of the important changes are detected by the proposed method in our experiments. This study was checked for effectiveness using visual evaluation and numerical evaluation.

Hierarchical Bayesian sparse image reconstruction with application to MRFM.

PubMed

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

2009-09-01

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

A new fast direct solver for the boundary element method

NASA Astrophysics Data System (ADS)

Huang, S.; Liu, Y. J.

2017-09-01

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

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

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

PubMed

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

2010-09-21

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

Age, psychological skills, and golf performance: a prospective investigation.

PubMed

Hayslip, Bert; Petrie, Trent A

2014-03-01

This study explored the influence of age in understanding mental skills utilization in the context of performance at a major national golf competition. Participants, who ranged in age and in skill level, included 1150 male and 170 female amateur golfers competing in the Dupont World Amateur Golf Championship in Myrtle Beach, South Carolina. Measures targeted general mental skills used in competitions, golf-specific skills, and competitive trait anxiety. Hierarchical linear regression was utilized to explore the potential moderating role that chronological age may play in influencing the impact of psychological skills and anxiety on competitive tournament performance across the adult life span. Findings suggested no significant age-moderating effects and instead pointed to the importance of developing golf-specific psychological skills to enhance or maintain performance, irrespective of age. Although automaticity (performance feels "automatic") predicted performance for all golfers, commitment to the game and confidence in one's putting did so only for the men. These findings reinforce the age-irrelevant role of such skills in fostering the experience of peak performance in a competitive sport context and underscore the importance of interventions targeting older players to help maintain or facilitate the use of psychological skills in helping them manage their games.

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

NASA Technical Reports Server (NTRS)

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

1976-01-01

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

A hierarchical clustering methodology for the estimation of toxicity.

PubMed

Martin, Todd M; Harten, Paul; Venkatapathy, Raghuraman; Das, Shashikala; Young, Douglas M

2008-01-01

ABSTRACT A quantitative structure-activity relationship (QSAR) methodology based on hierarchical clustering was developed to predict toxicological endpoints. This methodology utilizes Ward's method to divide a training set into a series of structurally similar clusters. The structural similarity is defined in terms of 2-D physicochemical descriptors (such as connectivity and E-state indices). A genetic algorithm-based technique is used to generate statistically valid QSAR models for each cluster (using the pool of descriptors described above). The toxicity for a given query compound is estimated using the weighted average of the predictions from the closest cluster from each step in the hierarchical clustering assuming that the compound is within the domain of applicability of the cluster. The hierarchical clustering methodology was tested using a Tetrahymena pyriformis acute toxicity data set containing 644 chemicals in the training set and with two prediction sets containing 339 and 110 chemicals. The results from the hierarchical clustering methodology were compared to the results from several different QSAR methodologies.

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

EPA Science Inventory

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

Multilevel modelling: Beyond the basic applications.

PubMed

Wright, Daniel B; London, Kamala

2009-05-01

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

An analysis of integrated health care for Internet Use Disorders in adolescents and adults.

PubMed

Lindenberg, Katajun; Szász-Janocha, Carolin; Schoenmaekers, Sophie; Wehrmann, Ulrich; Vonderlin, Eva

2017-12-01

Background and aims Although first treatment approaches for Internet Use Disorders (IUDs) have proven to be effective, health care utilization remained low. New service models focus on integrated health care systems, which facilitate access and reduce burdens of health care utilization, and stepped-care interventions, which efficiently provide individualized therapy. Methods An integrated health care approach for IUD intended to (a) be easily accessible and comprehensive, (b) cover a variety of comorbid syndromes, and (c) take heterogeneous levels of impairment into account was investigated in a one-armed prospective intervention study on n = 81 patients, who were treated from 2012 to 2016. Results First, patients showed significant improvement in Compulsive Internet Use over time, as measured by hierarchical linear modeling. Effect sizes of outcome change from baseline to 6-month follow-up ranged from d = 0.48 to d = 1.46. Second, differential effects were found depending on patients' compliance, demonstrating that high compliance resulted in significantly higher rates of change. Third, patients referred to minimal interventions did not differ significantly in amount of change from patients referred to intensive psychotherapy. Discussion Tailored interventions result in higher efficiency through optimized resource allocation and equal amounts of symptom change in all treatment conditions. Moreover, comprehensive, low-threshold interventions seem to increase health service utilization.

The traveling salesman problem: a hierarchical model.

PubMed

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

2000-10-01

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

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

PubMed

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

2016-01-14

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

Multicollinearity in hierarchical linear models.

PubMed

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

2015-09-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

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.

Narrowing the error in electron correlation calculations by basis set re-hierarchization and use of the unified singlet and triplet electron-pair extrapolation scheme: Application to a test set of 106 systems

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

Varandas, A. J. C., E-mail: varandas@uc.pt; Departamento de Física, Universidade Federal do Espírito Santo, 29075-910 Vitória; Pansini, F. N. N.

2014-12-14

A method previously suggested to calculate the correlation energy at the complete one-electron basis set limit by reassignment of the basis hierarchical numbers and use of the unified singlet- and triplet-pair extrapolation scheme is applied to a test set of 106 systems, some with up to 48 electrons. The approach is utilized to obtain extrapolated correlation energies from raw values calculated with second-order Møller-Plesset perturbation theory and the coupled-cluster singles and doubles excitations method, some of the latter also with the perturbative triples corrections. The calculated correlation energies have also been used to predict atomization energies within an additive scheme.more » Good agreement is obtained with the best available estimates even when the (d, t) pair of hierarchical numbers is utilized to perform the extrapolations. This conceivably justifies that there is no strong reason to exclude double-zeta energies in extrapolations, especially if the basis is calibrated to comply with the theoretical model.« less

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

Exploring electrolyte preference of vanadium nitride supercapacitor electrodes

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

Wang, Bo; Chen, Zhaohui; Lu, Gang

Highlights: • Hierarchical VN nanostructures were prepared on graphite foam. • Electrolyte preference of VN supercapacitor electrodes was explored. • VN showed better capacitive property in organic and alkaline electrolytes than LiCl. - Abstract: Vanadium nitride hierarchical nanostructures were prepared through an ammonia annealing procedure utilizing vanadium pentoxide nanostructures grown on graphite foam. The electrochemical properties of hierarchical vanadium nitride was tested in aqueous and organic electrolytes. As a result, the vanadium nitride showed better capacitive energy storage property in organic and alkaline electrolytes. This work provides insight into the charge storage process of vanadium nitride and our findings canmore » shed light on other transition metal nitride-based electrochemical energy storage systems.« less

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

DTIC Science & Technology

2015-05-12

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

Formation Flying With Decentralized Control in Libration Point Orbits

NASA Technical Reports Server (NTRS)

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

2000-01-01

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

Apathy, not depressive symptoms, as a predictor of semantic and phonemic fluency task performance in stroke and transient ischemic attack.

PubMed

Fishman, Keera N; Ashbaugh, Andrea R; Lanctôt, Krista L; Cayley, Megan L; Herrmann, Nathan; Murray, Brian J; Sicard, Michelle; Lien, Karen; Sahlas, Demetrios J; Swartz, Richard H

2018-06-01

This study examined the relationship between apathy and cognition in patients with cerebrovascular disease. Apathy may result from damage to frontal subcortical circuits causing dysexecutive syndromes, but apathy is also related to depression. We assessed the ability of apathy to predict phonemic fluency and semantic fluency performance after controlling for depressive symptoms in 282 individuals with stroke and/or transient ischemic attack. Participants (N = 282) completed the Phonemic Fluency Test, Semantic Fluency Test, Center for Epidemiologic Studies Depression Scale, and Apathy Evaluation Scale. A cross-sectional correlational design was utilized. Using hierarchical linear regressions, apathy scores significantly predicted semantic fluency performance (β = -.159, p = .020), but not phonemic fluency performance (β = -.112, p = .129) after scaling scores by age and years of education and controlling for depressive symptoms. Depressive symptoms entered into the first step of both hierarchical linear regressions did not predict semantic fluency (β = -.035, p = .554) or phonemic fluency (β = -.081, p = .173). Apathy and depressive symptoms were moderately correlated, r(280) = .58, p < .001. The results of this study are consistent with research supporting a differentiation between phonemic and semantic fluency tasks, whereby phonemic fluency tasks primarily involve frontal regions, and semantic fluency tasks involve recruitment of more extended networks. The results also highlight a distinction between apathy and depressive symptoms and suggest that apathy may be a more reliable predictor of cognitive deficits than measures of mood in individuals with cerebrovascular disease. Apathy may also be more related to cognition due to overlapping motivational and cognitive frontal subcortical circuitry. Future research should explore whether treatments for apathy could be a novel target for improving cognitive outcomes after stroke.

The Utility of the MAPI in Predicting Urban Middle School Competence.

ERIC Educational Resources Information Center

Paulus, John A.; Perosa, Linda M.

A sample of 107 eighth graders from a large urban middle school in the Midwest was administered the Millon Adolescent Personality Inventory (MAPI) to determine its utility in predicting grades earned, attendance, and social competence. The results of hierarchical multiple regression analysis indicated that the MAPI coping patterns significantly…

Modular, Hierarchical Learning By Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Baldi, Pierre F.; Toomarian, Nikzad

1996-01-01

Modular and hierarchical approach to supervised learning by artificial neural networks leads to neural networks more structured than neural networks in which all neurons fully interconnected. These networks utilize general feedforward flow of information and sparse recurrent connections to achieve dynamical effects. The modular organization, sparsity of modular units and connections, and fact that learning is much more circumscribed are all attractive features for designing neural-network hardware. Learning streamlined by imitating some aspects of biological neural networks.

Hierarchical Mesoporous Zinc-Nickel-Cobalt Ternary Oxide Nanowire Arrays on Nickel Foam as High-Performance Electrodes for Supercapacitors.

PubMed

Wu, Chun; Cai, Junjie; Zhang, Qiaobao; Zhou, Xiang; Zhu, Ying; Shen, Pei Kang; Zhang, Kaili

2015-12-09

Nickel foam supported hierarchical mesoporous Zn-Ni-Co ternary oxide (ZNCO) nanowire arrays are synthesized by a simple two-step approach including a hydrothermal method and subsequent calcination process and directly utilized for supercapacitive investigation for the first time. The nickel foam supported hierarchical mesoporous ZNCO nanowire arrays possess an ultrahigh specific capacitance value of 2481.8 F g(-1) at 1 A g(-1) and excellent rate capability of about 91.9% capacitance retention at 5 A g(-1). More importantly, an asymmetric supercapacitor with a high energy density (35.6 Wh kg(-1)) and remarkable cycle stability performance (94% capacitance retention over 3000 cycles) is assembled successfully by employing the ZNCO electrode as positive electrode and activated carbon as negative electrode. The remarkable electrochemical behaviors demonstrate that the nickel foam supported hierarchical mesoporous ZNCO nanowire array electrodes are highly desirable for application as advanced supercapacitor electrodes.

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.

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

PubMed

Sauppe, Sebastian

2017-01-01

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

Intelligence and Accidents: A Multilevel Model

DTIC Science & Technology

2006-05-06

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

Application of Bayesian inference to the study of hierarchical organization in self-organized complex adaptive systems

NASA Astrophysics Data System (ADS)

Knuth, K. H.

2001-05-01

We consider the application of Bayesian inference to the study of self-organized structures in complex adaptive systems. In particular, we examine the distribution of elements, agents, or processes in systems dominated by hierarchical structure. We demonstrate that results obtained by Caianiello [1] on Hierarchical Modular Systems (HMS) can be found by applying Jaynes' Principle of Group Invariance [2] to a few key assumptions about our knowledge of hierarchical organization. Subsequent application of the Principle of Maximum Entropy allows inferences to be made about specific systems. The utility of the Bayesian method is considered by examining both successes and failures of the hierarchical model. We discuss how Caianiello's original statements suffer from the Mind Projection Fallacy [3] and we restate his assumptions thus widening the applicability of the HMS model. The relationship between inference and statistical physics, described by Jaynes [4], is reiterated with the expectation that this realization will aid the field of complex systems research by moving away from often inappropriate direct application of statistical mechanics to a more encompassing inferential methodology.

Development of hierarchical, tunable pore size polymer foams for ICF targets

DOE PAGES

Hamilton, Christopher E.; Lee, Matthew Nicholson; Parra-Vasquez, A. Nicholas Gerardo

2016-08-01

In this study, one of the great challenges of inertial confinement fusion experiments is poor understanding of the effects of reactant heterogeneity on fusion reactions. The Marble campaign, conceived at Los Alamos National Laboratory, aims to gather new insights into this issue by utilizing target capsules containing polymer foams of variable pore sizes, tunable over an order of magnitude. Here, we describe recent and ongoing progress in the development of CH and CH/CD polymer foams in support of Marble. Hierarchical and tunable pore sizes have been achieved by utilizing a sacrificial porogen template within an open-celled poly(divinylbenzene) or poly(divinylbenzene-co-styrene) aerogelmore » matrix, resulting in low-density foams (~30 mg/ml) with continuous multimodal pore networks.« less

Hierarchically clustered adaptive quantization CMAC and its learning convergence.

PubMed

Teddy, S D; Lai, E M K; Quek, C

2007-11-01

The cerebellar model articulation controller (CMAC) neural network (NN) is a well-established computational model of the human cerebellum. Nevertheless, there are two major drawbacks associated with the uniform quantization scheme of the CMAC network. They are the following: (1) a constant output resolution associated with the entire input space and (2) the generalization-accuracy dilemma. Moreover, the size of the CMAC network is an exponential function of the number of inputs. Depending on the characteristics of the training data, only a small percentage of the entire set of CMAC memory cells is utilized. Therefore, the efficient utilization of the CMAC memory is a crucial issue. One approach is to quantize the input space nonuniformly. For existing nonuniformly quantized CMAC systems, there is a tradeoff between memory efficiency and computational complexity. Inspired by the underlying organizational mechanism of the human brain, this paper presents a novel CMAC architecture named hierarchically clustered adaptive quantization CMAC (HCAQ-CMAC). HCAQ-CMAC employs hierarchical clustering for the nonuniform quantization of the input space to identify significant input segments and subsequently allocating more memory cells to these regions. The stability of the HCAQ-CMAC network is theoretically guaranteed by the proof of its learning convergence. The performance of the proposed network is subsequently benchmarked against the original CMAC network, as well as two other existing CMAC variants on two real-life applications, namely, automated control of car maneuver and modeling of the human blood glucose dynamics. The experimental results have demonstrated that the HCAQ-CMAC network offers an efficient memory allocation scheme and improves the generalization and accuracy of the network output to achieve better or comparable performances with smaller memory usages. Index Terms-Cerebellar model articulation controller (CMAC), hierarchical clustering, hierarchically clustered adaptive quantization CMAC (HCAQ-CMAC), learning convergence, nonuniform quantization.

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

PubMed

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

2018-04-05

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

Carbon with hierarchical pores from carbonized metal-organic frameworks for lithium sulphur batteries.

PubMed

Xi, Kai; Cao, Shuai; Peng, Xiaoyu; Ducati, Caterina; Kumar, R Vasant; Cheetham, Anthony K

2013-03-18

This paper presents a novel method and rationale for utilizing carbonized MOFs for sulphur loading to fabricate cathode structures for lithium-sulphur batteries. Unique carbon materials with differing hierarchical pore structures were synthesized from four types of zinc-containing metal-organic frameworks (MOFs). It is found that cathode materials made from MOFs-derived carbons with higher mesopore (2-50 nm) volumes exhibit increased initial discharge capacities, whereas carbons with higher micropore (<2 nm) volumes lead to cathode materials with better cycle stability.

Phase field benchmark problems for dendritic growth and linear elasticity

DOE PAGES

Jokisaari, Andrea M.; Voorhees, P. W.; Guyer, Jonathan E.; ...

2018-03-26

We present the second set of benchmark problems for phase field models that are being jointly developed by the Center for Hierarchical Materials Design (CHiMaD) and the National Institute of Standards and Technology (NIST) along with input from other members in the phase field community. As the integrated computational materials engineering (ICME) approach to materials design has gained traction, there is an increasing need for quantitative phase field results. New algorithms and numerical implementations increase computational capabilities, necessitating standard problems to evaluate their impact on simulated microstructure evolution as well as their computational performance. We propose one benchmark problem formore » solidifiication and dendritic growth in a single-component system, and one problem for linear elasticity via the shape evolution of an elastically constrained precipitate. We demonstrate the utility and sensitivity of the benchmark problems by comparing the results of 1) dendritic growth simulations performed with different time integrators and 2) elastically constrained precipitate simulations with different precipitate sizes, initial conditions, and elastic moduli. As a result, these numerical benchmark problems will provide a consistent basis for evaluating different algorithms, both existing and those to be developed in the future, for accuracy and computational efficiency when applied to simulate physics often incorporated in phase field models.« less

Assessing Local Model Adequacy in Bayesian Hierarchical Models Using the Partitioned Deviance Information Criterion

PubMed Central

Wheeler, David C.; Hickson, DeMarc A.; Waller, Lance A.

2010-01-01

Many diagnostic tools and goodness-of-fit measures, such as the Akaike information criterion (AIC) and the Bayesian deviance information criterion (DIC), are available to evaluate the overall adequacy of linear regression models. In addition, visually assessing adequacy in models has become an essential part of any regression analysis. In this paper, we focus on a spatial consideration of the local DIC measure for model selection and goodness-of-fit evaluation. We use a partitioning of the DIC into the local DIC, leverage, and deviance residuals to assess local model fit and influence for both individual observations and groups of observations in a Bayesian framework. We use visualization of the local DIC and differences in local DIC between models to assist in model selection and to visualize the global and local impacts of adding covariates or model parameters. We demonstrate the utility of the local DIC in assessing model adequacy using HIV prevalence data from pregnant women in the Butare province of Rwanda during 1989-1993 using a range of linear model specifications, from global effects only to spatially varying coefficient models, and a set of covariates related to sexual behavior. Results of applying the diagnostic visualization approach include more refined model selection and greater understanding of the models as applied to the data. PMID:21243121

Phase field benchmark problems for dendritic growth and linear elasticity

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

Jokisaari, Andrea M.; Voorhees, P. W.; Guyer, Jonathan E.

We present the second set of benchmark problems for phase field models that are being jointly developed by the Center for Hierarchical Materials Design (CHiMaD) and the National Institute of Standards and Technology (NIST) along with input from other members in the phase field community. As the integrated computational materials engineering (ICME) approach to materials design has gained traction, there is an increasing need for quantitative phase field results. New algorithms and numerical implementations increase computational capabilities, necessitating standard problems to evaluate their impact on simulated microstructure evolution as well as their computational performance. We propose one benchmark problem formore » solidifiication and dendritic growth in a single-component system, and one problem for linear elasticity via the shape evolution of an elastically constrained precipitate. We demonstrate the utility and sensitivity of the benchmark problems by comparing the results of 1) dendritic growth simulations performed with different time integrators and 2) elastically constrained precipitate simulations with different precipitate sizes, initial conditions, and elastic moduli. As a result, these numerical benchmark problems will provide a consistent basis for evaluating different algorithms, both existing and those to be developed in the future, for accuracy and computational efficiency when applied to simulate physics often incorporated in phase field models.« less

Transfer Student Success: Educationally Purposeful Activities Predictive of Undergraduate GPA

ERIC Educational Resources Information Center

Fauria, Renee M.; Fuller, Matthew B.

2015-01-01

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

Practical Assessment, Research & Evaluation, 2000-2001.

ERIC Educational Resources Information Center

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

2001-01-01

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

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

NASA Astrophysics Data System (ADS)

Shorikov, A. F.

2017-10-01

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

A Hybrid P2P Overlay Network for Non-strictly Hierarchically Categorized Content

NASA Astrophysics Data System (ADS)

Wan, Yi; Asaka, Takuya; Takahashi, Tatsuro

In P2P content distribution systems, there are many cases in which the content can be classified into hierarchically organized categories. In this paper, we propose a hybrid overlay network design suitable for such content called Pastry/NSHCC (Pastry for Non-Strictly Hierarchically Categorized Content). The semantic information of classification hierarchies of the content can be utilized regardless of whether they are in a strict tree structure or not. By doing so, the search scope can be restrained to any granularity, and the number of query messages also decreases while maintaining keyword searching availability. Through simulation, we showed that the proposed method provides better performance and lower overhead than unstructured overlays exploiting the same semantic information.

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.

3D Printing of Hierarchical Silk Fibroin Structures.

PubMed

Sommer, Marianne R; Schaffner, Manuel; Carnelli, Davide; Studart, André R

2016-12-21

Like many other natural materials, silk is hierarchically structured from the amino acid level up to the cocoon or spider web macroscopic structures. Despite being used industrially in a number of applications, hierarchically structured silk fibroin objects with a similar degree of architectural control as in natural structures have not been produced yet due to limitations in fabrication processes. In a combined top-down and bottom-up approach, we exploit the freedom in macroscopic design offered by 3D printing and the template-guided assembly of ink building blocks at the meso- and nanolevel to fabricate hierarchical silk porous materials with unprecedented structural control. Pores with tunable sizes in the range 40-350 μm are generated by adding sacrificial organic microparticles as templates to a silk fibroin-based ink. Commercially available wax particles or monodisperse polycaprolactone made by microfluidics can be used as microparticle templates. Since closed pores are generated after template removal, an ultrasonication treatment can optionally be used to achieve open porosity. Such pore templating particles can be further modified with nanoparticles to create a hierarchical template that results in porous structures with a defined nanotopography on the pore walls. The hierarchically porous silk structures obtained with this processing technique can potentially be utilized in various application fields from structural materials to thermal insulation to tissue engineering scaffolds.

Stress, Social Support, and Burnout Among Long-Term Care Nursing Staff.

PubMed

Woodhead, Erin L; Northrop, Lynn; Edelstein, Barry

2016-01-01

Long-term care nursing staff are subject to considerable occupational stress and report high levels of burnout, yet little is known about how stress and social support are associated with burnout in this population. The present study utilized the job demands-resources model of burnout to examine relations between job demands (occupational and personal stress), job resources (sources and functions of social support), and burnout in a sample of nursing staff at a long-term care facility (N = 250). Hierarchical linear regression analyses revealed that job demands (greater occupational stress) were associated with more emotional exhaustion, more depersonalization, and less personal accomplishment. Job resources (support from supervisors and friends or family members, reassurance of worth, opportunity for nurturing) were associated with less emotional exhaustion and higher levels of personal accomplishment. Interventions to reduce burnout that include a focus on stress and social support outside of work may be particularly beneficial for long-term care staff. © The Author(s) 2014.

The sociology of health in the United States: recent theoretical contributions.

PubMed

Cockerham, William C

2014-04-01

This paper examines recent trends in theory in health sociology in the United States and finds that the use of theory is flourishing. The central thesis is that the field has reached a mature state and is in the early stage of a paradigm shift away from a past focus on methodological individualism (in which the individual is the primary unit of analysis) toward a growing utilization of theories with a structural orientation This outcome is materially aided by research methods (e.g. hierarchal linear modeling, biomarkers) providing measures of structural effects on the health of the individual that were often absent or underdeveloped in the past. Structure needs to be accounted for in any social endeavor and contemporary medical sociology appears to be doing precisely that as part of the next stage of its evolution. The recent contributions to theory in the sociology of health discussed in this paper are fundamental cause, medicalization, social capital, neighborhood disadvantage, and health lifestyle theories.

Depression socialization within friendship groups at the transition to adolescence: the roles of gender and group centrality as moderators of peer influence.

PubMed

Conway, Christopher C; Rancourt, Diana; Adelman, Caroline B; Burk, William J; Prinstein, Mitchell J

2011-11-01

Tests of interpersonal theories of depression have established that elevated depression levels among peers portend increases in individuals' own depressive symptoms, a phenomenon known as depression socialization. Susceptibility to this socialization effect may be enhanced during the transition to adolescence as the strength of peer influence rises dramatically. Socialization of depressive symptoms among members of child and adolescent friendship groups was examined over a 1-year period among 648 youth in grades six through eight. Sociometric methods were utilized to identify friendship groups and ascertain the prospective effect of group-level depressive symptoms on youths' own depressive symptoms. Hierarchical linear modeling results revealed a significant socialization effect and indicated that this effect was most potent for (a) girls and (b) individuals on the periphery of friendship groups. Future studies would benefit from incorporating child and adolescent peer groups as a developmentally salient context for interpersonal models of depression.

Dynamic cholesteric liquid crystal superstructures photoaligned by one-step polarization holography

NASA Astrophysics Data System (ADS)

Li, Sen-Sen; Shen, Yuan; Chang, Zhen-Ni; Li, Wen-Song; Xu, Yan-Chao; Fan, Xing-Yu; Chen, Lu-Jian

2017-12-01

A convenient approach to modulate the fingerprint textures of methyl red (MR) doped cholesteric liquid crystals by asymmetric photoalignment in the green-light waveband is presented, resulting in the generation of voltage-controllable helical superstructures. The interaction between the MR molecules and the incident light polarization determines the initial twisted planar geometry, providing a multivariant control over the stripe directions of fingerprint textures by applying a proper electric field. The key factors for precise manipulation of fingerprint stripes in a predictable and rewritable manner are analyzed theoretically and investigated experimentally, which involves the alignment asymmetry, the ratio of cell gap to natural pitch length, and the chirality of chiral dopant. Dynamic periodic fingerprint textures in shapes of dashed curve and dashed line are further demonstrated by utilizing a facile one-step polarization holography process using two beams with orthogonal circular and orthogonal linear polarizations, respectively. It is believed that the practical approach described in this study would enrich the research contents of self-assembled hierarchical superstructures using soft liquid crystal building blocks.

The effects of two different incentives on recruitment rates of families into a prevention program.

PubMed

Heinrichs, Nina

2006-07-01

This study experimentally manipulated two incentives for participation (monetary: paid participation for sessions and setting: group vs. individual) in a child behavior problem prevention program to analyze their effects on recruitment and retention of families. A population of 690 eligible families from 15 preschools located in socially disadvantaged neighborhoods was invited to participate in a parent training (PT) program. The study recruited parents by using advertisements that had information describing only the indicated condition (i.e., PT in group-unpaid, or PT individual-unpaid, or PT in group-paid, or PT individual-paid). Results demonstrate significant impact of payment on recruitment and initial attendance. Training setting alone (individual or group) did not significantly influence these rates. Editors' Strategic Implications: A compelling case is made for the utility of monetary incentives to increase proportions of low-income families in prevention research and programs. Evaluators and program designers should note the impressive use of the experimental design and hierarchical linear modeling to test the effects on recruitment.

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

PubMed

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

2016-01-01

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

Functional Genomic Landscape of Human Breast Cancer Drivers, Vulnerabilities, and Resistance.

PubMed

Marcotte, Richard; Sayad, Azin; Brown, Kevin R; Sanchez-Garcia, Felix; Reimand, Jüri; Haider, Maliha; Virtanen, Carl; Bradner, James E; Bader, Gary D; Mills, Gordon B; Pe'er, Dana; Moffat, Jason; Neel, Benjamin G

2016-01-14

Large-scale genomic studies have identified multiple somatic aberrations in breast cancer, including copy number alterations and point mutations. Still, identifying causal variants and emergent vulnerabilities that arise as a consequence of genetic alterations remain major challenges. We performed whole-genome small hairpin RNA (shRNA) "dropout screens" on 77 breast cancer cell lines. Using a hierarchical linear regression algorithm to score our screen results and integrate them with accompanying detailed genetic and proteomic information, we identify vulnerabilities in breast cancer, including candidate "drivers," and reveal general functional genomic properties of cancer cells. Comparisons of gene essentiality with drug sensitivity data suggest potential resistance mechanisms, effects of existing anti-cancer drugs, and opportunities for combination therapy. Finally, we demonstrate the utility of this large dataset by identifying BRD4 as a potential target in luminal breast cancer and PIK3CA mutations as a resistance determinant for BET-inhibitors. Copyright © 2016 Elsevier Inc. All rights reserved.

Depression Socialization Within Friendship Groups at the Transition to Adolescence: The Roles of Gender and Group Centrality as Moderators of Peer Influence

PubMed Central

Conway, Christopher C.; Rancourt, Diana; Adelman, Caroline B.; Burk, William J.; Prinstein, Mitchell J.

2012-01-01

Tests of interpersonal theories of depression have established that elevated depression levels among peers portend increases in individuals’ own depressive symptoms, a phenomenon known as depression socialization. Susceptibility to this socialization effect may be enhanced during the transition to adolescence as the strength of peer influence rises dramatically. Socialization of depressive symptoms among members of child and adolescent friendship groups was examined over a 1-year period among 648 youth in grades six through eight. Sociometric methods were utilized to identify friendship groups and ascertain the prospective effect of group-level depressive symptoms on youths’ own depressive symptoms. Hierarchical linear modeling results revealed a significant socialization effect and indicated that this effect was most potent for (a) girls and (b) individuals on the periphery of friendship groups. Future studies would benefit from incorporating child and adolescent peer groups as a developmentally salient context for interpersonal models of depression. PMID:21842961

Perceived diabetes task competence mediates the relationship of both negative and positive affect with blood glucose in adolescents with type 1 diabetes.

PubMed

Fortenberry, Katherine T; Butler, Jorie M; Butner, Jonathan; Berg, Cynthia A; Upchurch, Renn; Wiebe, Deborah J

2009-02-01

Adolescents dealing with type 1 diabetes experience disruptions in affect and diabetes management that may influence their blood glucose. A daily diary format examined whether daily fluctuations in both negative and positive affect were associated with adolescents' perceived diabetes task competence (DTC) and blood glucose, and whether perceived DTC mediated the relationship between daily affect and blood glucose. Sixty-two adolescents with type 1 diabetes completed a 2-week daily diary, which included daily measures of affect and perceived DTC, then recorded their blood glucose readings at the end of the day. We utilized hierarchical linear modeling to examine whether daily perceived DTC mediated the relationship between daily emotion and blood glucose. Daily perceived DTC mediated the relationship of both negative and positive affect with daily blood glucose. This study suggests that within the ongoing process of self-regulation, daily affect may be associated with blood glucose by influencing adolescents' perception of competence on daily diabetes tasks.

Emotion Regulation Predicts Pain and Functioning in Children With Juvenile Idiopathic Arthritis: An Electronic Diary Study

PubMed Central

Bromberg, Maggie H.; Anthony, Kelly K.; Gil, Karen M.; Franks, Lindsey; Schanberg, Laura E.

2012-01-01

Objectives This study utilized e-diaries to evaluate whether components of emotion regulation predict daily pain and function in children with juvenile idiopathic arthritis (JIA). Methods 43 children ages 8–17 years and their caregivers provided baseline reports of child emotion regulation. Children then completed thrice daily e-diary assessments of emotion, pain, and activity involvement for 28 days. E-diary ratings of negative and positive emotions were used to calculate emotion variability and to infer adaptive emotion modulation following periods of high or low emotion intensity. Hierarchical linear models were used to evaluate how emotion regulation related to pain and function. Results The attenuation of negative emotion following a period of high negative emotion predicted reduced pain; greater variability of negative emotion predicted higher pain and increased activity limitation. Indices of positive emotion regulation also significantly predicted pain. Conclusions Components of emotion regulation as captured by e-diaries predict important health outcomes in children with JIA. PMID:22037006

Isosurface Extraction in Time-Varying Fields Using a Temporal Hierarchical Index Tree

NASA Technical Reports Server (NTRS)

Shen, Han-Wei; Gerald-Yamasaki, Michael (Technical Monitor)

1998-01-01

Many high-performance isosurface extraction algorithms have been proposed in the past several years as a result of intensive research efforts. When applying these algorithms to large-scale time-varying fields, the storage overhead incurred from storing the search index often becomes overwhelming. this paper proposes an algorithm for locating isosurface cells in time-varying fields. We devise a new data structure, called Temporal Hierarchical Index Tree, which utilizes the temporal coherence that exists in a time-varying field and adoptively coalesces the cells' extreme values over time; the resulting extreme values are then used to create the isosurface cell search index. For a typical time-varying scalar data set, not only does this temporal hierarchical index tree require much less storage space, but also the amount of I/O required to access the indices from the disk at different time steps is substantially reduced. We illustrate the utility and speed of our algorithm with data from several large-scale time-varying CID simulations. Our algorithm can achieve more than 80% of disk-space savings when compared with the existing techniques, while the isosurface extraction time is nearly optimal.

School-based extracurricular activity involvement and adolescent self-esteem: a growth-curve analysis.

PubMed

Kort-Butler, Lisa A; Hagewen, Kellie J

2011-05-01

Research on adolescent self-esteem indicates that adolescence is a time in which individuals experience important changes in their physical, cognitive, and social identities. Prior research suggests that there is a positive relationship between an adolescent's participation in structured extracurricular activities and well-being in a variety of domains, and some research indicates that these relationships may be dependent on the type of activities in which adolescents participate. Building on previous research, a growth-curve analysis was utilized to examine self-esteem trajectories from adolescence (age 14) to young adulthood (age 26). Using 3 waves of data from National Longitudinal Study of Adolescent Health (n = 5,399; 47.8% male), the analysis estimated a hierarchical growth-curve model emphasizing the effects of age and type of school-based extracurricular activity portfolio, including sports and school clubs, on self-esteem. The results indicated that age had a linear relationship with self-esteem over time. Changes in both the initial level of self-esteem and the growth of self-esteem over time were significantly influenced by the type of extracurricular activity portfolio. The findings were consistent across race and sex. The results support the utility of examining the longitudinal impact of portfolio type on well-being outcomes.

Teacher (Mis)Perceptions of Preschoolers’ Academic Skills: Predictors and Associations With Longitudinal Outcomes

PubMed Central

Baker, Courtney N.; Tichovolsky, Marianne H.; Kupersmidt, Janis B.; Voegler-Lee, Mary Ellen; Arnold, David H.

2014-01-01

Preschool teachers have important impacts on children’s academic outcomes, and teachers’ misperceptions of children’s academic skills could have negative consequences, particularly for low-income preschoolers. This study utilized data gathered from 123 preschool teachers and their 760 preschoolers from 70 low-income, racially diverse centers. Hierarchical linear modeling was utilized to account for the nested data structure. Even after controlling for children’s actual academic skill, older children, children with stronger social skills, and children with fewer inattentive symptoms were perceived to have stronger academic abilities. Contrary to hypotheses, preschoolers with more behavior problems were perceived by teachers to have significantly better pre-academic abilities than they actually had. Teachers’ perceptions were not associated with child gender or child race/ethnicity. Although considerable variability was due to teacher-level characteristics, child characteristics explained 42% of the variability in teachers’ perceptions about children’s language and pre-literacy ability and 41% of the variability in teachers’ perceptions about mathability. Notably, these perceptions appear to have important impacts over time. Controlling for child baseline academic skill and child characteristics, teacher perceptions early in the preschool year were significantly associated with child academic outcomes during the spring for both language and pre-literacy and math. Study implications with regard to the achievement gap are discussed. PMID:26538767

Hierarchical Boltzmann simulations and model error estimation

NASA Astrophysics Data System (ADS)

Torrilhon, Manuel; Sarna, Neeraj

2017-08-01

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

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

DTIC Science & Technology

2008-02-15

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

Bonding Social Capital in Low-Income Neighborhoods

ERIC Educational Resources Information Center

Brisson, Daniel S.; Usher, Charles L.

2005-01-01

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

Indigenous Intelligence: Have We Lost Our Indigenous Mind?

ERIC Educational Resources Information Center

Dumont, Jim

2002-01-01

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

The Relationship between Counselors' Multicultural Counseling Competence and Poverty Beliefs

ERIC Educational Resources Information Center

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

2017-01-01

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

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.

Multi-scale, Hierarchically Nested Young Stellar Structures in LEGUS Galaxies

NASA Astrophysics Data System (ADS)

Thilker, David A.; LEGUS Team

2017-01-01

The study of star formation in galaxies has predominantly been limited to either young stellar clusters and HII regions, or much larger kpc-scale morphological features such as spiral arms. The HST Legacy ExtraGalactic UV Survey (LEGUS) provides a rare opportunity to link these scales in a diverse sample of nearby galaxies and obtain a more comprehensive understanding of their co-evolution for comparison against model predictions. We have utilized LEGUS stellar photometry to identify young, resolved stellar populations belonging to several age bins and then defined nested hierarchical structures as traced by these subsamples of stars. Analagous hierarchical structures were also defined using LEGUS catalogs of unresolved young stellar clusters. We will present our emerging results concerning the physical properties (e.g. area, star counts, stellar mass, star formation rate, ISM characteristics), occupancy statistics (e.g. clusters per substructure versus age and scale, parent/child demographics) and relation to overall galaxy morphology/mass for these building blocks of hierarchical star-forming structure.

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

PubMed

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

2017-11-23

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

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

PubMed

Affrunti, Nicholas W; Woodruff-Borden, Janet

2015-05-01

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

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

PubMed

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

2000-11-01

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

Fabrication of hierarchically branched SnO2 nanowires by two-step deposition method and their applications to electrocatalyst support and Li ion electrode

NASA Astrophysics Data System (ADS)

Lee, Sang Ho; Jo, Yong-Ryun; Noh, Yuseong; Kim, Bong-Joong; Kim, Won Bae

2017-11-01

This paper reports hierarchically branched structures of tin dioxide nanowires for use in electrochemical energy conversion and storage electrode systems. The shallow tin dioxide branches are epitaxially grown on the tin dioxide nanowire backbones that are directly formed on current collectors. The branched tin dioxide nanowires are applied as anode electrodes for lithium-ion batteries, while palladium-incorporated branched nanowires are utilized as electrocatalysts for ethanol electrooxidation reactions. The structural benefits of these hierarchical platforms, such as enlarged electrochemical active surface area, void space formed between the branched structures, and conformal contact of the electroactive materials with current collectors, play important roles in improving the electrochemical Li-ion storage as well as electrocatalytic activity.

Predictors of physical therapy clinic performance in the treatment of patients with low back pain syndromes.

PubMed

Resnik, Linda; Liu, Dawei; Mor, Vince; Hart, Dennis L

2008-09-01

Little is known about organizational and service delivery factors related to quality of care in physical therapy. This study sought to identify characteristics related to differences in practice outcomes and service utilization. The sample comprised 114 outpatient clinics and 1,058 therapists who treated 16,281 patients with low back pain syndromes during the period 2000-2001. Clinics participated with the Focus on Therapeutic Outcomes, Inc (FOTO) database. Hierarchical linear models were used to risk adjust treatment outcomes and number of visits per treatment episode. Aggregated residual scores from these models were used to classify each clinic into 1 of 3 categories in each of 3 types of performance groups: (1) effectiveness, (2) utilization, and (3) overall performance (ie, composite measure of effectiveness and utilization). Relationships between clinic classification and the following independent variables were examined by multinomial logistic regression: years of therapist experience, number of physical therapists, ratio of physical therapists to physical therapist assistants, proportion of patients with low back pain syndromes, number of new patients per physical therapist per month, utilization of physical therapist assistants, and setting. Clinics that were lower utilizers of physical therapist assistants were 6.6 times more likely to be classified into the high effectiveness group compared with the low effectiveness group, 6.7 times more likely to be classified in the low utilization group compared with the high utilization group, and 12.4 times more likely to be classified in the best performance group compared with the worst performance group. Serving a higher proportion of patients with low back pain syndromes was associated with an increased likelihood of being classified in the lowest or middle group. Years of physical therapist experience was inversely associated with being classified in the middle utilization group compared with the highest utilization group. These findings suggest that, in the treatment of patients with low back pain syndromes, clinics that are low utilizers of physical therapist assistants are more likely to provide superior care (ie, better patient outcomes and lower service use).

Dynamic Hierarchical Sleep Scheduling for Wireless Ad-Hoc Sensor Networks

PubMed Central

Wen, Chih-Yu; Chen, Ying-Chih

2009-01-01

This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks. PMID:22412343

Dynamic hierarchical sleep scheduling for wireless ad-hoc sensor networks.

PubMed

Wen, Chih-Yu; Chen, Ying-Chih

2009-01-01

This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks.

Pore-scale study of effects of macroscopic pores and their distributions on reactive transport in hierarchical porous media

DOE PAGES

Chen, Li; Zhang, Ruiyuan; Min, Ting; ...

2018-05-19

For applications of reactive transport in porous media, optimal porous structures should possess both high surface area for reactive sites loading and low mass transport resistance. Hierarchical porous media with a combination of pores at different scales are designed for this purpose. In this paper, using the lattice Boltzmann method, pore-scale numerical studies are conducted to investigate diffusion-reaction processes in 2D hierarchical porous media generated by self-developed reconstruction scheme. Complex interactions between porous structures and reactive transport are revealed under different conditions. Simulation results show that adding macropores can greatly enhance the mass transport, but at the same time reducemore » the reactive surface, leading to complex change trend of the total reaction rate. Effects of gradient distribution of macropores within the porous medium are also investigated. It is found that a front-loose, back-tight (FLBT) hierarchical structure is desirable for enhancing mass transport, increasing total reaction rate, and improving catalyst utilization. Finally, on the whole, from the viewpoint of reducing cost and improving material performance, hierarchical porous structures, especially gradient structures with the size of macropores gradually decreasing along the transport direction, are desirable for catalyst application.« less

Pore-scale study of effects of macroscopic pores and their distributions on reactive transport in hierarchical porous media

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

Chen, Li; Zhang, Ruiyuan; Min, Ting

For applications of reactive transport in porous media, optimal porous structures should possess both high surface area for reactive sites loading and low mass transport resistance. Hierarchical porous media with a combination of pores at different scales are designed for this purpose. In this paper, using the lattice Boltzmann method, pore-scale numerical studies are conducted to investigate diffusion-reaction processes in 2D hierarchical porous media generated by self-developed reconstruction scheme. Complex interactions between porous structures and reactive transport are revealed under different conditions. Simulation results show that adding macropores can greatly enhance the mass transport, but at the same time reducemore » the reactive surface, leading to complex change trend of the total reaction rate. Effects of gradient distribution of macropores within the porous medium are also investigated. It is found that a front-loose, back-tight (FLBT) hierarchical structure is desirable for enhancing mass transport, increasing total reaction rate, and improving catalyst utilization. Finally, on the whole, from the viewpoint of reducing cost and improving material performance, hierarchical porous structures, especially gradient structures with the size of macropores gradually decreasing along the transport direction, are desirable for catalyst application.« less

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Reciprocal Prioritization to Dietary Glycans by Gut Bacteria in a Competitive Environment Promotes Stable Coexistence.

PubMed

Tuncil, Yunus E; Xiao, Yao; Porter, Nathan T; Reuhs, Bradley L; Martens, Eric C; Hamaker, Bruce R

2017-10-10

When presented with nutrient mixtures, several human gut Bacteroides species exhibit hierarchical utilization of glycans through a phenomenon that resembles catabolite repression. However, it is unclear how closely these observed physiological changes, often measured by altered transcription of glycan utilization genes, mirror actual glycan depletion. To understand the glycan prioritization strategies of two closely related human gut symbionts, Bacteroides ovatus and Bacteroides thetaiotaomicron , we performed a series of time course assays in which both species were individually grown in a medium with six different glycans that both species can degrade. Disappearance of the substrates and transcription of the corresponding polysaccharide utilization loci (PULs) were measured. Each species utilized some glycans before others, but with different priorities per species, providing insight into species-specific hierarchical preferences. In general, the presence of highly prioritized glycans repressed transcription of genes involved in utilizing lower-priority nutrients. However, transcriptional sensitivity to some glycans varied relative to the residual concentration in the medium, with some PULs that target high-priority substrates remaining highly expressed even after their target glycan had been mostly depleted. Coculturing of these organisms in the same mixture showed that the hierarchical orders generally remained the same, promoting stable coexistence. Polymer length was found to be a contributing factor for glycan utilization, thereby affecting its place in the hierarchy. Our findings not only elucidate how B. ovatus and B. thetaiotaomicron strategically access glycans to maintain coexistence but also support the prioritization of carbohydrate utilization based on carbohydrate structure, advancing our understanding of the relationships between diet and the gut microbiome. IMPORTANCE The microorganisms that reside in the human colon fulfill their energy requirements mainly from diet- and host-derived complex carbohydrates. Members of this ecosystem possess poorly understood strategies to prioritize and compete for these nutrients. Based on direct carbohydrate measurements and corresponding transcriptional analyses, our findings showed that individual bacterial species exhibit different preferences for the same set of glycans and that this prioritization is maintained in a competitive environment, which may promote stable coexistence. Such understanding of gut bacterial glycan utilization will be essential to eliciting predictable changes in the gut microbiota to improve health through the diet. Copyright © 2017 Tuncil et al.

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.

Multiplex acute leukemia cytosensing using multifunctional hybrid electrochemical nanoprobes at a hierarchically nanoarchitectured electrode interface

NASA Astrophysics Data System (ADS)

Zheng, Tingting; Tan, Tingting; Zhang, Qingfeng; Fu, Jia-Ju; Wu, Jia-Jun; Zhang, Kui; Zhu, Jun-Jie; Wang, Hui

2013-10-01

We have developed a robust, nanobiotechnology-based electrochemical cytosensing approach with high sensitivity, selectivity, and reproducibility toward the simultaneous multiplex detection and classification of both acute myeloid leukemia and acute lymphocytic leukemia cells. The construction of the electrochemical cytosensor involves the hierarchical assembly of dual aptamer-functionalized, multilayered graphene-Au nanoparticle electrode interface and the utilization of hybrid electrochemical nanoprobes co-functionalized with redox tags, horseradish peroxidase, and cell-targeting nucleic acid aptamers. The hybrid nanoprobes are multifunctional, capable of specifically targeting the cells of interest, amplifying the electrochemical signals, and generating distinguishable signals for multiplex cytosensing. The as-assembled electrode interface not only greatly facilitates the interfacial electron transfer process due to its high conductivity and surface area but also exhibits excellent biocompatibility and specificity for cell recognition and adhesion. A superstructured sandwich-type sensor geometry is adopted for electrochemical cytosensing, with the cells of interest sandwiched between the nanoprobes and the electrode interface. Such an electrochemical sensing strategy allows for ultrasensitive, multiplex acute leukemia cytosensing with a detection limit as low as ~350 cells per mL and a wide linear response range from 5 × 102 to 1 × 107 cells per mL for HL-60 and CEM cells, with minimal cross-reactivity and interference from non-targeting cells. This electrochemical cytosensing approach holds great promise as a new point-of-care diagnostic tool for early detection and classification of human acute leukemia and may be readily expanded to multiplex cytosensing of other cancer cells.We have developed a robust, nanobiotechnology-based electrochemical cytosensing approach with high sensitivity, selectivity, and reproducibility toward the simultaneous multiplex detection and classification of both acute myeloid leukemia and acute lymphocytic leukemia cells. The construction of the electrochemical cytosensor involves the hierarchical assembly of dual aptamer-functionalized, multilayered graphene-Au nanoparticle electrode interface and the utilization of hybrid electrochemical nanoprobes co-functionalized with redox tags, horseradish peroxidase, and cell-targeting nucleic acid aptamers. The hybrid nanoprobes are multifunctional, capable of specifically targeting the cells of interest, amplifying the electrochemical signals, and generating distinguishable signals for multiplex cytosensing. The as-assembled electrode interface not only greatly facilitates the interfacial electron transfer process due to its high conductivity and surface area but also exhibits excellent biocompatibility and specificity for cell recognition and adhesion. A superstructured sandwich-type sensor geometry is adopted for electrochemical cytosensing, with the cells of interest sandwiched between the nanoprobes and the electrode interface. Such an electrochemical sensing strategy allows for ultrasensitive, multiplex acute leukemia cytosensing with a detection limit as low as ~350 cells per mL and a wide linear response range from 5 × 102 to 1 × 107 cells per mL for HL-60 and CEM cells, with minimal cross-reactivity and interference from non-targeting cells. This electrochemical cytosensing approach holds great promise as a new point-of-care diagnostic tool for early detection and classification of human acute leukemia and may be readily expanded to multiplex cytosensing of other cancer cells. Electronic supplementary information (ESI) available: Additional figures as noted in the text. See DOI: 10.1039/c3nr02903d

Exploring Growth Trajectories of Problem Behavior in Young Children

ERIC Educational Resources Information Center

McCaffrey, Bethany L.

2012-01-01

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

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

ERIC Educational Resources Information Center

Auchlin, Antoine; And Others

1981-01-01

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

Hierarchical Bayesian modelling of mobility metrics for hazard model input calibration

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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

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

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

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

Comparison of the Utility of Two Assessments for Explaining and Predicting Productivity Change: Well-Being Versus an HRA.

PubMed

Gandy, William M; Coberley, Carter; Pope, James E; Rula, Elizabeth Y

2016-01-01

To compare utility of employee well-being to health risk assessment (HRA) as predictors of productivity change. Panel data from 2189 employees who completed surveys 2 years apart were used in hierarchical models comparing the influence of well-being and health risk on longitudinal changes in presenteeism and job performance. Absenteeism change was evaluated in a nonexempt subsample. Change in well-being was the most significant independent predictor of productivity change across all three measures. Comparing hierarchical models, well-being models performed significantly better than HRA models. The HRA added no incremental explanatory power over well-being in combined models. Alone, nonphysical health well-being components outperformed the HRA for all productivity measures. Well-being offers a more comprehensive measure of factors that influence productivity and can be considered preferential to HRA in understanding and addressing suboptimal productivity.

Contextual Effects on Kindergarten Teachers' Intention to Report Child Abuse

ERIC Educational Resources Information Center

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

2012-01-01

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

Hierarchy and Scope of Planning in Subject-Verb Agreement Production

ERIC Educational Resources Information Center

Gillespie, Maureen; Pearlmutter, Neal J.

2011-01-01

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

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

ERIC Educational Resources Information Center

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

2009-01-01

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

Using Hierarchical Linear Modeling for Proformative Evaluation: A Case Example

ERIC Educational Resources Information Center

Coryn, Chris L. S.

2007-01-01

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

Individual and School Predictors of Middle School Aggression

ERIC Educational Resources Information Center

Reis, Janet; Trockel, Mickey; Mulhall, Peter

2007-01-01

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

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…

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

ERIC Educational Resources Information Center

Lee, Diane Sookyoung; Padilla, Amado M.

2016-01-01

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

The Effects of Academic Optimism on Elementary Reading Achievement

ERIC Educational Resources Information Center

Bevel, Raymona K.; Mitchell, Roxanne M.

2012-01-01

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

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

ERIC Educational Resources Information Center

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

2015-01-01

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

Centering Effects in HLM Level-1 Predictor Variables.

ERIC Educational Resources Information Center

Schumacker, Randall E.; Bembry, Karen

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

Substance Use, Anxiety, and Depressive Symptoms among College Students

ERIC Educational Resources Information Center

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

2018-01-01

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

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…

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

ERIC Educational Resources Information Center

Byrd, Christy M.; Chavous, Tabbye M.

2009-01-01

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

Psychopathology and Marital Satisfaction: The Importance of Evaluating Both Partners

ERIC Educational Resources Information Center

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

2004-01-01

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

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

ERIC Educational Resources Information Center

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

2010-01-01

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

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

ERIC Educational Resources Information Center

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

2011-01-01

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

Working-Class Jobs and New Parents' Mental Health

ERIC Educational Resources Information Center

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

2011-01-01

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

Handling Correlations between Covariates and Random Slopes in Multilevel Models

ERIC Educational Resources Information Center

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

2014-01-01

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

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

ERIC Educational Resources Information Center

McCoach, D. Betsy

2010-01-01

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

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

ERIC Educational Resources Information Center

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

2006-01-01

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

A Multilevel Analysis on Student Learning in Colleges and Universities.

ERIC Educational Resources Information Center

Hu, Shouping; Kuh, George D.

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

Predictors of Burnout in Children's Residential Treatment Center Staff

ERIC Educational Resources Information Center

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

2008-01-01

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

Multilevel Correlates of Childhood Physical Aggression and Prosocial Behavior

ERIC Educational Resources Information Center

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

2005-01-01

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

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

ERIC Educational Resources Information Center

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

2013-01-01

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

Leader-Member Exchange, Learning Orientation and Innovative Work Behavior

ERIC Educational Resources Information Center

Atitumpong, Aungkhana; Badir, Yuosre F.

2018-01-01

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

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

ERIC Educational Resources Information Center

Herzog, Serge

2007-01-01

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

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…

Neighborhood Disadvantage and Variations in Blood Pressure

ERIC Educational Resources Information Center

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

2015-01-01

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

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

ERIC Educational Resources Information Center

Bryk, Anthony S.; Thum, Yeow Meng

1989-01-01

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

Departmental Contexts and Faculty Research Activity in Norway

ERIC Educational Resources Information Center

Smeby, Jens-Christian; Try, Sverre

2005-01-01

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

Unpacking the Inequality among Turkish Schools: Findings from PISA 2006

ERIC Educational Resources Information Center

Alacaci, Cengiz; Erbas, Ayhan Kursat

2010-01-01

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

Predicting Successful Mathematics Remediation among Latina/o Students

ERIC Educational Resources Information Center

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

2017-01-01

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

Accelerating Recovery from Poverty: Prevention Effects for Recently Separated Mothers

ERIC Educational Resources Information Center

Forgatch, Marion S.; DeGarmo, David S.

2007-01-01

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

Neighborhood Context and Police Vigor: A Multilevel Analysis

ERIC Educational Resources Information Center

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

2013-01-01

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

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

ERIC Educational Resources Information Center

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

2016-01-01

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

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

ERIC Educational Resources Information Center

Little, Michael H.

2017-01-01

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

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

PubMed

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

2015-08-15

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

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

NASA Technical Reports Server (NTRS)

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

1991-01-01

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

A hierarchical porous electrode using a micron-sized honeycomb-like carbon material for high capacity lithium-oxygen batteries

NASA Astrophysics Data System (ADS)

Li, Jing; Zhang, Huamin; Zhang, Yining; Wang, Meiri; Zhang, Fengxiang; Nie, Hongjiao

2013-05-01

A micron-sized honeycomb-like carbon material (MHC) is prepared in a facile way using nano-CaCO3 as a hard template. A novel electrode for lithium-oxygen batteries is fabricated and displays a superior discharge capacity as high as 5862 mA h g-1. The higher electrode space utilization is attributed to its hierarchical pore structure, with intrinsic mesopores in the MHC particles for Li2O2 depositions and macropores among them for oxygen transport.A micron-sized honeycomb-like carbon material (MHC) is prepared in a facile way using nano-CaCO3 as a hard template. A novel electrode for lithium-oxygen batteries is fabricated and displays a superior discharge capacity as high as 5862 mA h g-1. The higher electrode space utilization is attributed to its hierarchical pore structure, with intrinsic mesopores in the MHC particles for Li2O2 depositions and macropores among them for oxygen transport. Electronic supplementary information (ESI) available: Synthesis of the MHC material. Cathode preparation. Material characterization. Assembly of Li-O2 battery cells and performance evaluation. SEM image of the CaCO3-sucrose composite before carbonization. See DOI: 10.1039/c3nr00337j

Hierarchical prisoner’s dilemma in hierarchical game for resource competition

NASA Astrophysics Data System (ADS)

Fujimoto, Yuma; Sagawa, Takahiro; Kaneko, Kunihiko

2017-07-01

Dilemmas in cooperation are one of the major concerns in game theory. In a public goods game, each individual cooperates by paying a cost or defecting without paying it, and receives a reward from the group out of the collected cost. Thus, defecting is beneficial for each individual, while cooperation is beneficial for the group. Now, groups (say, countries) consisting of individuals also play games. To study such a multi-level game, we introduce a hierarchical game in which multiple groups compete for limited resources by utilizing the collected cost in each group, where the power to appropriate resources increases with the population of the group. Analyzing this hierarchical game, we found a hierarchical prisoner’s dilemma, in which groups choose the defecting policy (say, armament) as a Nash strategy to optimize each group’s benefit, while cooperation optimizes the total benefit. On the other hand, for each individual, refusing to pay the cost (say, tax) is a Nash strategy, which turns out to be a cooperation policy for the group, thus leading to a hierarchical dilemma. Here the group reward increases with the group size. However, we find that there exists an optimal group size that maximizes the individual payoff. Furthermore, when the population asymmetry between two groups is large, the smaller group will choose a cooperation policy (say, disarmament) to avoid excessive response from the larger group, and the prisoner’s dilemma between the groups is resolved. Accordingly, the relevance of this hierarchical game on policy selection in society and the optimal size of human or animal groups are discussed.

Embodied linearity of speed control in Drosophila melanogaster.

PubMed

Medici, V; Fry, S N

2012-12-07

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

Embodied linearity of speed control in Drosophila melanogaster

PubMed Central

Medici, V.; Fry, S. N.

2012-01-01

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

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

NASA Astrophysics Data System (ADS)

Hsieh, Chang-Yu; Cao, Jianshu

2018-01-01

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

Hierarchical nucleus segmentation in digital pathology images

NASA Astrophysics Data System (ADS)

Gao, Yi; Ratner, Vadim; Zhu, Liangjia; Diprima, Tammy; Kurc, Tahsin; Tannenbaum, Allen; Saltz, Joel

2016-03-01

Extracting nuclei is one of the most actively studied topic in the digital pathology researches. Most of the studies directly search the nuclei (or seeds for the nuclei) from the finest resolution available. While the richest information has been utilized by such approaches, it is sometimes difficult to address the heterogeneity of nuclei in different tissues. In this work, we propose a hierarchical approach which starts from the lower resolution level and adaptively adjusts the parameters while progressing into finer and finer resolution. The algorithm is tested on brain and lung cancers images from The Cancer Genome Atlas data set.

Pushing typists back on the learning curve: revealing chunking in skilled typewriting.

PubMed

Yamaguchi, Motonori; Logan, Gordon D

2014-04-01

Theories of skilled performance propose that highly trained skills involve hierarchically structured control processes. The present study examined and demonstrated hierarchical control at several levels of processing in skilled typewriting. In the first two experiments, we scrambled the order of letters in words to prevent skilled typists from chunking letters, and compared typing words and scrambled words. Experiment 1 manipulated stimulus quality to reveal chunking in perception, and Experiment 2 manipulated concurrent memory load to reveal chunking in short-term memory (STM). Both experiments manipulated the number of letters in words and nonwords to reveal chunking in motor planning. In the next two experiments, we degraded typing skill by altering the usual haptic feedback by using a laser-projection keyboard, so that typists had to monitor keystrokes. Neither the number of motor chunks (Experiment 3) nor the number of STM items (Experiment 4) was influenced by the manipulation. The results indicate that the utilization of hierarchical control depends on whether the input allows chunking but not on whether the output is generated automatically. We consider the role of automaticity in hierarchical control of skilled performance.

Hierarchical video summarization

NASA Astrophysics Data System (ADS)

Ratakonda, Krishna; Sezan, M. Ibrahim; Crinon, Regis J.

1998-12-01

We address the problem of key-frame summarization of vide in the absence of any a priori information about its content. This is a common problem that is encountered in home videos. We propose a hierarchical key-frame summarization algorithm where a coarse-to-fine key-frame summary is generated. A hierarchical key-frame summary facilitates multi-level browsing where the user can quickly discover the content of the video by accessing its coarsest but most compact summary and then view a desired segment of the video with increasingly more detail. At the finest level, the summary is generated on the basis of color features of video frames, using an extension of a recently proposed key-frame extraction algorithm. The finest level key-frames are recursively clustered using a novel pairwise K-means clustering approach with temporal consecutiveness constraint. We also address summarization of MPEG-2 compressed video without fully decoding the bitstream. We also propose efficient mechanisms that facilitate decoding the video when the hierarchical summary is utilized in browsing and playback of video segments starting at selected key-frames.

Chunking dynamics: heteroclinics in mind

PubMed Central

Rabinovich, Mikhail I.; Varona, Pablo; Tristan, Irma; Afraimovich, Valentin S.

2014-01-01

Recent results of imaging technologies and non-linear dynamics make possible to relate the structure and dynamics of functional brain networks to different mental tasks and to build theoretical models for the description and prediction of cognitive activity. Such models are non-linear dynamical descriptions of the interaction of the core components—brain modes—participating in a specific mental function. The dynamical images of different mental processes depend on their temporal features. The dynamics of many cognitive functions are transient. They are often observed as a chain of sequentially changing metastable states. A stable heteroclinic channel (SHC) consisting of a chain of saddles—metastable states—connected by unstable separatrices is a mathematical image for robust transients. In this paper we focus on hierarchical chunking dynamics that can represent several forms of transient cognitive activity. Chunking is a dynamical phenomenon that nature uses to perform information processing of long sequences by dividing them in shorter information items. Chunking, for example, makes more efficient the use of short-term memory by breaking up long strings of information (like in language where one can see the separation of a novel on chapters, paragraphs, sentences, and finally words). Chunking is important in many processes of perception, learning, and cognition in humans and animals. Based on anatomical information about the hierarchical organization of functional brain networks, we propose a cognitive network architecture that hierarchically chunks and super-chunks switching sequences of metastable states produced by winnerless competitive heteroclinic dynamics. PMID:24672469

Chunking dynamics: heteroclinics in mind.

PubMed

Rabinovich, Mikhail I; Varona, Pablo; Tristan, Irma; Afraimovich, Valentin S

2014-01-01

Recent results of imaging technologies and non-linear dynamics make possible to relate the structure and dynamics of functional brain networks to different mental tasks and to build theoretical models for the description and prediction of cognitive activity. Such models are non-linear dynamical descriptions of the interaction of the core components-brain modes-participating in a specific mental function. The dynamical images of different mental processes depend on their temporal features. The dynamics of many cognitive functions are transient. They are often observed as a chain of sequentially changing metastable states. A stable heteroclinic channel (SHC) consisting of a chain of saddles-metastable states-connected by unstable separatrices is a mathematical image for robust transients. In this paper we focus on hierarchical chunking dynamics that can represent several forms of transient cognitive activity. Chunking is a dynamical phenomenon that nature uses to perform information processing of long sequences by dividing them in shorter information items. Chunking, for example, makes more efficient the use of short-term memory by breaking up long strings of information (like in language where one can see the separation of a novel on chapters, paragraphs, sentences, and finally words). Chunking is important in many processes of perception, learning, and cognition in humans and animals. Based on anatomical information about the hierarchical organization of functional brain networks, we propose a cognitive network architecture that hierarchically chunks and super-chunks switching sequences of metastable states produced by winnerless competitive heteroclinic dynamics.

Hierarchical Context Modeling for Video Event Recognition.

PubMed

Wang, Xiaoyang; Ji, Qiang

2016-10-11

Current video event recognition research remains largely target-centered. For real-world surveillance videos, targetcentered event recognition faces great challenges due to large intra-class target variation, limited image resolution, and poor detection and tracking results. To mitigate these challenges, we introduced a context-augmented video event recognition approach. Specifically, we explicitly capture different types of contexts from three levels including image level, semantic level, and prior level. At the image level, we introduce two types of contextual features including the appearance context features and interaction context features to capture the appearance of context objects and their interactions with the target objects. At the semantic level, we propose a deep model based on deep Boltzmann machine to learn event object representations and their interactions. At the prior level, we utilize two types of prior-level contexts including scene priming and dynamic cueing. Finally, we introduce a hierarchical context model that systematically integrates the contextual information at different levels. Through the hierarchical context model, contexts at different levels jointly contribute to the event recognition. We evaluate the hierarchical context model for event recognition on benchmark surveillance video datasets. Results show that incorporating contexts in each level can improve event recognition performance, and jointly integrating three levels of contexts through our hierarchical model achieves the best performance.

Hierarchical FeTiO3-TiO2 hollow spheres for efficient simulated sunlight-driven water oxidation.

PubMed

Han, Taoran; Chen, Yajie; Tian, Guohui; Wang, Jian-Qiang; Ren, Zhiyu; Zhou, Wei; Fu, Honggang

2015-10-14

Oxygen generation is the key step for the photocatalytic overall water splitting and considered to be kinetically more challenging than hydrogen generation. Here, an effective water oxidation catalyst of hierarchical FeTiO3-TiO2 hollow spheres are prepared via a two-step sequential solvothermal processes and followed by thermal treatment. The existence of an effective heterointerface and built-in electric field in the surface space charge region in FeTiO3-TiO2 hollow spheres plays a positive role in promoting the separation of photoinduced electron-hole pairs. Surface photovoltage, transient-state photovoltage, fluorescence and electrochemical characterization are used to investigate the transfer process of photoinduced charge carriers. The photogenerated charge carriers in the hierarchical FeTiO3-TiO2 hollow spheres with a proper molar ratio display much higher separation efficiency and longer lifetime than those in the FeTiO3 alone. Moreover, it is suggested that the hierarchical porous hollow structure can contribute to the enhancement of light utilization, surface active sites and material transportation through the framework walls. This specific synergy significantly contributes to the remarkable improvement of the photocatalytic water oxidation activity of the hierarchical FeTiO3-TiO2 hollow spheres under simulated sunlight (AM1.5).

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.

Parameterizations for ensemble Kalman inversion

NASA Astrophysics Data System (ADS)

Chada, Neil K.; Iglesias, Marco A.; Roininen, Lassi; Stuart, Andrew M.

2018-05-01

The use of ensemble methods to solve inverse problems is attractive because it is a derivative-free methodology which is also well-adapted to parallelization. In its basic iterative form the method produces an ensemble of solutions which lie in the linear span of the initial ensemble. Choice of the parameterization of the unknown field is thus a key component of the success of the method. We demonstrate how both geometric ideas and hierarchical ideas can be used to design effective parameterizations for a number of applied inverse problems arising in electrical impedance tomography, groundwater flow and source inversion. In particular we show how geometric ideas, including the level set method, can be used to reconstruct piecewise continuous fields, and we show how hierarchical methods can be used to learn key parameters in continuous fields, such as length-scales, resulting in improved reconstructions. Geometric and hierarchical ideas are combined in the level set method to find piecewise constant reconstructions with interfaces of unknown topology.

An Amperometric Acetylcholinesterase Sensor Based on the Bio-templated Synthesis of Hierarchical Mesoporous Bioactive Glass Microspheres

NASA Astrophysics Data System (ADS)

Lv, Zhuo; Luo, Ruiping; Xi, Lijuan; Chen, Yang; Wang, Hongsu

2017-11-01

This work describes the synthesis of three-dimensional hollow hierarchical mesoporous bioactive glass (HMBG) microspheres based on Herba leonuri pollen grains via a hydrothermal method. The HMBG microspheres perfectly copied the hierarchical porous structure and inner hollow structure constituting the double-layer surface of the natural Herba leonuri pollen grains. This structural mimicry of the pollen grains resulted in a higher degree of adsorption of acetylcholinesterase (AChE) on HMBG microspheres in comparison with mesoporous bioactive glass. Subsequently, an amperometric biosensor for the detection of Malathion was fabricated by immobilizing AChE onto an HMBG microspheres-modified carbon paste electrode. The biosensor response exhibited two good linear ranges during an incubation time of 10 min in the malathion concentration ranges of 0.02-50 ppb and 50-600 ppb, with a detection limit of 0.0135 ppb ( S/ N = 3). Overall, the prepared enzymatic biosensor showed high sensitivity in the rapid detection of Malathion and could be applied to detect pesticide residues in vegetable matter.

Nanoporous platinum-cobalt alloy for electrochemical sensing for ethanol, hydrogen peroxide, and glucose.

PubMed

Xu, Caixia; Sun, Fenglei; Gao, Hua; Wang, Jinping

2013-05-30

Nanoporous platinum-cobalt (NP-PtCo) alloy with hierarchical nanostructure is straightforwardly fabricated by dealloying PtCoAl alloy in a mild alkaline solution. Selectively etching Al resulted in a hierarchical three-dimensional network nanostructure with a narrow size distribution at 3 nm. The as-prepared NP-PtCo alloy shows superior performance toward ethanol and hydrogen peroxide (H2O2) with highly sensitive response due to its unique electrocatalytic activity. In addition, NP-PtCo also exhibits excellent amperometric durability and long-term stability for H2O2 as well as a good anti-interference toward ascorbic acid, uric acid, and dopamine. The hierarchical nanoporous architecture in PtCo alloy is also highly active for glucose sensing electrooxidation and sensing in a wide linear range. The NP-PtCo alloy holds great application potential for electrochemical sensing with simple preparation, unique catalytic activity, and high structure stability. Copyright © 2013 Elsevier B.V. All rights reserved.

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.

Microfibres and macroscopic films from the coordination-driven hierarchical self-assembly of cylindrical micelles

PubMed Central

Lunn, David J.; Gould, Oliver E. C.; Whittell, George R.; Armstrong, Daniel P.; Mineart, Kenneth P.; Winnik, Mitchell A.; Spontak, Richard J.; Pringle, Paul G.; Manners, Ian

2016-01-01

Anisotropic nanoparticles prepared from block copolymers are of growing importance as building blocks for the creation of synthetic hierarchical materials. However, the assembly of these structural units is generally limited to the use of amphiphilic interactions. Here we report a simple, reversible coordination-driven hierarchical self-assembly strategy for the preparation of micron-scale fibres and macroscopic films based on monodisperse cylindrical block copolymer micelles. Coordination of Pd(0) metal centres to phosphine ligands immobilized within the soluble coronas of block copolymer micelles is found to induce intermicelle crosslinking, affording stable linear fibres comprised of micelle subunits in a staggered arrangement. The mean length of the fibres can be varied by altering the micelle concentration, reaction stoichiometry or aspect ratio of the micelle building blocks. Furthermore, the fibres aggregate on drying to form robust, self-supporting macroscopic micelle-based thin films with useful mechanical properties that are analogous to crosslinked polymer networks, but on a longer length scale. PMID:27538877

Automated tetraploid genotype calling by hierarchical clustering

USDA-ARS?s Scientific Manuscript database

SNP arrays are transforming breeding and genetics research for autotetraploids. To fully utilize these arrays, however, the relationship between signal intensity and allele dosage must be inferred independently for each marker. We developed an improved computational method to automate this process, ...

Familial and Religious Influences on Adolescent Alcohol Use: A Multi-Level Study of Students and School Communities

ERIC Educational Resources Information Center

Bjarnason, Thoroddur; Thorlindsson, Thorolfur; Sigfusdottir, Inga D.; Welch, Michael R.

2005-01-01

A multi-level Durkheimian theory of familial and religious influences on adolescent alcohol use is developed and tested with hierarchical linear modeling of data from Icelandic schools and students. On the individual level, traditional family structure, parental monitoring, parental support, religious participation, and perceptions of divine…

Comparing Private Schools and Public Schools Using Hierarchical Linear Modeling. NCES 2006-461

ERIC Educational Resources Information Center

Braun, Henry; Jenkins, Frank; Grigg, Wendy

2006-01-01

The goal of the study was to examine differences in mean National Assessment of Educational Progress (NAEP) reading and mathematics scores between public and private schools when selected characteristics of students and/or schools were taken into account. Among the student characteristics considered were gender, race/ethnicity, disability status,…

Classroom Age Composition and Developmental Change in 70 Urban Preschool Classrooms

ERIC Educational Resources Information Center

Moller, Arlen C.; Forbes-Jones, Emma; Hightower, A. Dirk

2008-01-01

A multilevel modeling approach was used to investigate the influence of age composition in 70 urban preschool classrooms. A series of hierarchical linear models demonstrated that greater variance in classroom age composition was negatively related to development on the Child Observation Record (COR) Cognitive, Motor, and Social subscales. This was…

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

ERIC Educational Resources Information Center

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

2014-01-01

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

Motivations and Benefits for Attaining HR Certifications

ERIC Educational Resources Information Center

Lester, Scott W.; Dwyer, Dale J.

2012-01-01

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

The Role of Evaluative Metadata in an Online Teacher Resource Exchange

ERIC Educational Resources Information Center

Abramovich, Samuel; Schunn, Christian D.; Correnti, Richard J.

2013-01-01

A large-scale online teacher resource exchange is studied to examine the ways in which metadata influence teachers' selection of resources. A hierarchical linear modeling approach was used to tease apart the simultaneous effects of resource features and author features. From a decision heuristics theoretical perspective, teachers appear to…

A Three-Level Hierarchical Linear Model Using Student Growth Curve Modeling and Contextual Data

ERIC Educational Resources Information Center

Giorgio, Dorian

2012-01-01

Educational experts have criticized status models of school accountability, as required by the No Child Left Behind Act (NCLB), describing them as ineffectual in measuring achievement because their one-time assessment of student knowledge ignores student growth. Research on student achievement has instead identified growth models as superior…

Item Response Theory Using Hierarchical Generalized Linear Models

ERIC Educational Resources Information Center

Ravand, Hamdollah

2015-01-01

Multilevel models (MLMs) are flexible in that they can be employed to obtain item and person parameters, test for differential item functioning (DIF) and capture both local item and person dependence. Papers on the MLM analysis of item response data have focused mostly on theoretical issues where applications have been add-ons to simulation…

How Does District Principal Evaluation Affect Learning-Centered Principal Leadership? Evidence from Michigan School Districts

ERIC Educational Resources Information Center

Sun, Min; Youngs, Peter

2009-01-01

This study used Hierarchical Multivariate Linear models to investigate relationships between principals' behaviors and district principal evaluation purpose, focus, and assessed leadership activities in 13 school districts in Michigan. The study found that principals were more likely to engage in learning-centered leadership behaviors when the…

Analyzing Hierarchical Relationships Among Modes of Cognitive Reasoning and Integrated Science Process Skills.

ERIC Educational Resources Information Center

Yeany, Russell H.; And Others

1986-01-01

Searched for a learning hierarchy among skills comprising formal operations and integrated science processes. Ordering, theoretic, and probabilistic latent structure methods were used to analyze data collected from 700 science students. Both linear and branching relationships were identified within and across the two sets of skills. (Author/JN)

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

ERIC Educational Resources Information Center

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

2011-01-01

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

A Multi-Level Examination of College and Its Influence on Ecumenical Worldview Development

ERIC Educational Resources Information Center

Mayhew, Matthew J.

2012-01-01

This multi-level, longitudinal study investigated the ecumenical worldview development of 13,932 students enrolled in one of 126 institutions. Results indicated that the final hierarchical linear model, consisting of institution-and-student-level predictors as well as slopes explaining the relationships among some of these predictors, explained…

A Multilevel Study of the Role of Environment in Adolescent Substance Use

ERIC Educational Resources Information Center

Steen, Julie A.

2010-01-01

The purpose of this study is to assess the relationships between county-level characteristics and adolescent use of alcohol, cigarettes, and marijuana. The study consisted of a hierarchical generalized linear analysis of secondary data from the Florida Youth Substance Abuse Survey. Variables on the county level included the percent of adolescents…

Trajectories of Family Management Practices and Early Adolescent Behavioral Outcomes

ERIC Educational Resources Information Center

Wang, Ming-Te; Dishion, Thomas J.; Stormshak, Elizabeth A.; Willett, John B.

2011-01-01

Stage-environment fit theory was used to examine the reciprocal lagged relations between family management practices and early adolescent problem behavior during the middle school years. In addition, the potential moderating roles of family structure and of gender were explored. Hierarchical linear modeling was used to describe patterns of growth…

Marriage, Cohabitation, and Happiness: A Cross-National Analysis of 27 Countries

ERIC Educational Resources Information Center

Lee, Kristen Schultz; Ono, Hiroshi

2012-01-01

The authors investigated how the reported happiness of married and cohabiting individuals varies cross-nationally with societal gender beliefs and religious context. They used the 2002 International Social Survey Programme data from 27 countries (N = 36,889) and specified hierarchical linear models with macro-micro level interactions in order to…

Do Nondomestic Undergraduates Choose a Major Field in Order to Maximize Grade Point Averages?

ERIC Educational Resources Information Center

Bergman, Matthew E.; Fass-Holmes, Barry

2016-01-01

The authors investigated whether undergraduates attending an American West Coast public university who were not U.S. citizens (nondomestic) maximized their grade point averages (GPA) through their choice of major field. Multiple regression hierarchical linear modeling analyses showed that major field's effect size was small for these…

Treatment Effects of a Relationship-Strengthening Intervention for Economically Disadvantaged New Parents

ERIC Educational Resources Information Center

Charles, Pajarita; Jones, Anne; Guo, Shenyang

2014-01-01

Objective: The purpose of the present study was to evaluate the treatment effects of a relationship skills and family strengthening intervention for n = 726 high-risk, disadvantaged new parents. Method: Hierarchical linear modeling and regression models were used to assess intervention treatment effects. These findings were subsequently verified…

To Enter Stone, Be Water: Situating Literacy Coaching as Rhizomatic

ERIC Educational Resources Information Center

Reilly, Mary Ann

2014-01-01

Reilly leans on the metaphor of rhizomes to remind readers that the work of a coach is not linear or hierarchical, but fluid and dynamic. Reilly frames literacy coaches as rhizomatic agents in schools and urges coaches to appreciate resistance and interruptions as critical and necessary for transformative teaching and learning.

Rural Compared to Urban Home Community Settings as Predictors of First-Year Students' Adjustment to University

ERIC Educational Resources Information Center

Ames, Megan E.; Wintre, Maxine G.; Prancer, S. Mark; Pratt, Michael W.; Birnie-Lefcovitch, Shelly; Polivy, Janet; Adams, Gerald R.

2014-01-01

Undergraduates (N = 2,823) at 6 universities were surveyed longitudinally to examine the relevance of student home setting on the transition to university. Preliminary results indicated that rural students seem less likely to attend large, ethnically diverse universities. Hierarchical linear models revealed that "proximal rural" students…

Predictors of Tobacco and Alcohol Refusal Efficacy for Urban and Rural African-American Adolescents

ERIC Educational Resources Information Center

Nasim, Aashir; Belgrave, Faye Z.; Corona, Rosalie; Townsend, Tiffany G.

2009-01-01

This study sought to determine the relative contributions of individual, family, peer, and community risk and promotive factors in explaining alcohol and tobacco refusal attitudes among 227 African-American adolescents (ages 12 to 17) from urban and rural areas. Hierarchical linear regression (HLR) results revealed differences in the predictive…

Information Technology, Mathematics Achievement and Educational Equity in Developed Economies

ERIC Educational Resources Information Center

Tan, Cheng Yong; Hew, Khe Foon

2017-01-01

The present study examined how access to home and school IT resources impacted student mathematics achievement. Data comprised 144,395 secondary school students from 7,308 schools in 22 developed economies who participated in the Programme for International Student Assessment (PISA) 2012. Results of hierarchical linear modelling showed that after…

The Contributions of Teachers' Emotional Support to Children's Social Behaviors and Self-Regulatory Skills in First Grade

ERIC Educational Resources Information Center

Merritt, Eileen G.; Wanless, Shannon B.; Rimm-Kaufman, Sara E.; Cameron, Claire; Peugh, James L.

2012-01-01

The present observational study used hierarchical linear modeling to examine predictors of children's social and self-regulatory outcomes in first-grade classrooms. Specifically, goals were the following: (1) to explore relations between emotionally supportive teacher-child interactions and children's social behaviors (aggression with peers,…

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

ERIC Educational Resources Information Center

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

2010-01-01

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

Perceived Family Resources Based on Number of Members with ADHD

ERIC Educational Resources Information Center

Corwin, Melinda; Mulsow, Miriam; Feng, Du

2012-01-01

Objective: This study examines how the number of family members with ADHD affects other family members' perceived resources. Method: A total of 40 adolescents diagnosed with ADHD and their mothers, fathers, and adolescent siblings living in the household participated. Hierarchical linear modeling was used to analyze family-level data from a total…

A Multilevel Analysis of Phase II of the Louisiana School Effectiveness Study.

ERIC Educational Resources Information Center

Kennedy, Eugene; And Others

This paper presents findings of a study that used conventional modeling strategies (student- and school-level) and a new multilevel modeling strategy, Hierarchical Linear Modeling, to investigate school effects on student-achievement outcomes for data collected as part of Phase 2 of the Louisiana School Effectiveness Study. The purpose was to…

What Is the Relationship between Teacher Quality and Student Achievement? An Exploratory Study

ERIC Educational Resources Information Center

Stronge, James H.; Ward, Thomas J.; Tucker, Pamela D.; Hindman, Jennifer L.

2007-01-01

The major purpose of the study was to examine what constitutes effective teaching as defined by measured increases in student learning with a focus on the instructional behaviors and practices. Ordinary least squares (OLS) regression analyses and hierarchical linear modeling (HLM) were used to identify teacher effectiveness levels while…

Testing the Intervention Effect in Single-Case Experiments: A Monte Carlo Simulation Study

ERIC Educational Resources Information Center

Heyvaert, Mieke; Moeyaert, Mariola; Verkempynck, Paul; Van den Noortgate, Wim; Vervloet, Marlies; Ugille, Maaike; Onghena, Patrick

2017-01-01

This article reports on a Monte Carlo simulation study, evaluating two approaches for testing the intervention effect in replicated randomized AB designs: two-level hierarchical linear modeling (HLM) and using the additive method to combine randomization test "p" values (RTcombiP). Four factors were manipulated: mean intervention effect,…

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…

Hierarchical Bio-Inspired Cooperative Control for Nonlinear Dynamical Systems and Hardware Demonstration

DTIC Science & Technology

2013-04-03

cooperative control, LEGO robotic testbed, non-linear dynamics 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES...testbed The architecture of the LEGO robots (® LEGO is a trademark and/or copyright of the LEGO Group) used in tests were based off the quick-start

An Investigation of Teacher Impact on Student Inquiry Science Performance Using a Hierarchical Linear Model

ERIC Educational Resources Information Center

Liu, Ou Lydia; Lee, Hee-Sun; Linn, Marcia C.

2010-01-01

Teachers play a central role in inquiry science classrooms. In this study, we investigate how seven teacher variables (i.e., gender, experience, perceived importance of inquiry and traditional teaching, workshop attendance, partner teacher, use of technology) affect student knowledge integration understanding of science topics drawing on previous…

Outdoor Behavioral Health Care: Client and Treatment Characteristics Effects on Young Adult Outcomes

ERIC Educational Resources Information Center

Roberts, Sean D.; Stroud, Daniel; Hoag, Matthew J.; Combs, Katie M.

2016-01-01

A lack of clarity exists regarding how different clients respond to outdoor behavioral health care (OBH). In this study, specific client and treatment characteristics were assessed for 186 young adults completing an OBH therapeutic wilderness program. Clinical outcomes were measured with the Outcome Questionnaire-45.2. Hierarchical linear modeling…

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…

Suppressor Variables and Multilevel Mixture Modelling

ERIC Educational Resources Information Center

Darmawan, I Gusti Ngurah; Keeves, John P.

2006-01-01

A major issue in educational research involves taking into consideration the multilevel nature of the data. Since the late 1980s, attempts have been made to model social science data that conform to a nested structure. Among other models, two-level structural equation modelling or two-level path modelling and hierarchical linear modelling are two…

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

ERIC Educational Resources Information Center

Nie, Youyan; Lau, Shun

2010-01-01

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

Community Context, Social Integration into Family, and Youth Violence

ERIC Educational Resources Information Center

Knoester, Chris; Haynie, Dana L.

2005-01-01

The purpose of this study is to analyze the extent to which neighborhood-level family structure and feelings of family integration are associated with acts of violence among 16,910 adolescents from the National Longitudinal Study of Adolescent Health. The results from our hierarchical linear models indicate that adolescents who live in…

Does Mission Matter? An Analysis of Private School Achievement Differences

ERIC Educational Resources Information Center

Boerema, Albert J.

2009-01-01

Using student achievement data from British Columbia, Canada, this study is an exploration of the differences that lie within the private school sector using hierarchical linear modeling to analyze the data. The analysis showed that when controlling for language, parents' level of educational attainment, and prior achievement, the private school…

The Role of Schools, Families, and Psychological Variables on Math Achievement of Black High School Students

ERIC Educational Resources Information Center

Strayhorn, Terrell L.

2010-01-01

Using data from the National Education Longitudinal Study (NELS;1988/2000), the author conducted hierarchical linear regression analyses, with a nested design, to estimate the influence of affective variables--parent involvement, teacher perceptions, and school environments--on Black students' math achievement in grade 10. Drawing on…

A Cluster Analysis of Personality Style in Adults with ADHD

ERIC Educational Resources Information Center

Robin, Arthur L.; Tzelepis, Angela; Bedway, Marquita

2008-01-01

Objective: The purpose of this study was to use hierarchical linear cluster analysis to examine the normative personality styles of adults with ADHD. Method: A total of 311 adults with ADHD completed the Millon Index of Personality Styles, which consists of 24 scales assessing motivating aims, cognitive modes, and interpersonal behaviors. Results:…

Racial Differences in Perceptions of Social Support in Consumer-Centered Services

ERIC Educational Resources Information Center

Woodward, Amanda Toler; Mowbray, Carol T.; Holter, Mark C.; Bybee, Deborah

2007-01-01

The purpose of this study was to explore potential racial differences in the experience of support offered by consumer-centered services for adults with serious mental illness. The study used hierarchical linear modeling to examine the level of support consumers report receiving from programs and the extent to which program-level characteristics…

Student Engagement and Academic Performance in Mexico: Evidence and Puzzles from PISA

ERIC Educational Resources Information Center

Weiss, Christopher C.; García, Emma

2015-01-01

This paper investigates the relationship between student engagement--with teachers and schools--and academic performance in Mexico. It uses hierarchical linear models and data from the OECD 2003 PISA study to examine the relative importance of engagement in comparison to other educational inputs--school and family characteristics--as predictors of…

Student Motivation in Low-Stakes Assessment Contexts: An Exploratory Analysis in Engineering Mechanics

ERIC Educational Resources Information Center

Musekamp, Frank; Pearce, Jacob

2016-01-01

The goal of this paper is to examine the relationship of student motivation and achievement in low-stakes assessment contexts. Using Pearson product-moment correlations and hierarchical linear regression modelling to analyse data on 794 tertiary students who undertook a low-stakes engineering mechanics assessment (along with the questionnaire of…

Principals' Leadership Behaviors as Perceived by Teachers in At-Risk Middle Schools

ERIC Educational Resources Information Center

Johnson, R. Anthony

2011-01-01

A need for greater understanding of teachers' (N = 530) perceptions of the leadership behaviors of principals in Title I middle schools (n = 13) is prevalent exists. The researcher used the "Audit of Principal Effectiveness" survey to collect data. The researcher also used Hierarchical Linear Modeling as the quantitative analysis.…

Family Structure States and Transitions: Associations with Children's Well-Being during Middle Childhood

ERIC Educational Resources Information Center

Magnuson, Katherine; Berger, Lawrence M.

2009-01-01

Using longitudinal data from the Maternal and Child Supplement of the National Longitudinal Survey of Youth (N = 3,862) and Hierarchical Linear Models, we estimated associations of family structure states and transitions with children's achievement and behavior trajectories during middle childhood. Results suggest that residing in a single-mother…

A Multilevel Analysis of Gender Differences in Psychological Distress over Time

ERIC Educational Resources Information Center

Botticello, Amanda L.

2009-01-01

Females have higher rates of depression than males, a disparity that emerges in adolescence and persists into adulthood. This study uses hierarchical linear modeling to assess the effects of school context on gender differences in depressive symptoms among adolescents based on two waves of data from the National Longitudinal Study of Adolescent…

Just Another Club? The Distinctiveness of the Relation between Religious Service Attendance and Adolescent Psychosocial Adjustment

ERIC Educational Resources Information Center

Good, Marie; Willoughby, Teena; Fritjers, Jan

2009-01-01

This study used hierarchical linear modeling to compare longitudinal patterns of adolescent religious service attendance and club attendance, and to contrast the longitudinal relations between adolescent adjustment and religious service versus club attendance. Participants included 1050 students (47% girls) encompassing a school district in…

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

ERIC Educational Resources Information Center

Nie, Youyan; Lau, Shun

2009-01-01

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

Falling Off Track: How Teacher-Student Relationships Predict Early High School Failure Rates.

ERIC Educational Resources Information Center

Miller, Shazia Rafiullah

This paper examines the relationship between the climate of teacher-student relations within a school and individual student's likelihood of freshman year success. Using administrative data from the Chicago Public Schools and survey data, researchers used hierarchical linear modeling to determine whether teacher-student climate predicts students'…

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…

An International Meta-Analysis of Reading Recovery

ERIC Educational Resources Information Center

D'Agostino, Jerome V.; Harmey, Sinéad J.

2016-01-01

Reading Recovery is one of the most researched literacy programs worldwide. Although there have been at least 4 quantitative reviews of its effectiveness, none have considered all rigorous group-comparison studies from all implementing nations from the late 1970s to 2015. Using a hierarchical linear modeling (HLM) v-known analysis, we examined if…

Bottom-Up Analysis of Single-Case Research Designs

ERIC Educational Resources Information Center

Parker, Richard I.; Vannest, Kimberly J.

2012-01-01

This paper defines and promotes the qualities of a "bottom-up" approach to single-case research (SCR) data analysis. Although "top-down" models, for example, multi-level or hierarchical linear models, are gaining momentum and have much to offer, interventionists should be cautious about analyses that are not easily understood, are not governed by…

Student and School Factors Affecting Mathematics Achievement: International Comparisons between Korea, Japan and the USA

ERIC Educational Resources Information Center

Shin, Jongho; Lee, Hyunjoo; Kim, Yongnam

2009-01-01

The purpose of the study was to comparatively investigate student- and school-level factors affecting mathematics achievement of Korean, Japanese and American students. For international comparisons, the PISA 2003 data were analysed by using the Hierarchical Linear Modeling method. The variables of competitive-learning preference, instrumental…

Assessment and Innovation: One Darn Thing Leads to Another

ERIC Educational Resources Information Center

Rutz, Carol; Lauer-Glebov, Jacqulyn

2005-01-01

Using recent experience at Carleton College in Minnesota as a case history, the authors offer a model for assessment that provides more flexibility than the well-known assessment feedback loop, which assumes a linear progression within a hierarchical administrative structure. The proposed model is based on a double helix, with values and feedback…

The Relationship between School Collective Reflective Practice and Teacher Physiological Efficacy Sources

ERIC Educational Resources Information Center

Kennedy, Sheryl Y.; Smith, Julia B.

2013-01-01

This study used Hierarchical Linear Modeling to analyze the relationship between school organizational behaviors and practices (at the school level) on teachers' reports of internal and external physiological sources of efficacy. Six hundred sixty-one teachers from 42 schools in the United States were surveyed to measure both individual sources of…

3D deformable image matching: a hierarchical approach over nested subspaces

NASA Astrophysics Data System (ADS)

Musse, Olivier; Heitz, Fabrice; Armspach, Jean-Paul

2000-06-01

This paper presents a fast hierarchical method to perform dense deformable inter-subject matching of 3D MR Images of the brain. To recover the complex morphological variations in neuroanatomy, a hierarchy of 3D deformations fields is estimated, by minimizing a global energy function over a sequence of nested subspaces. The nested subspaces, generated from a single scaling function, consist of deformation fields constrained at different scales. The highly non linear energy function, describing the interactions between the target and the source images, is minimized using a coarse-to-fine continuation strategy over this hierarchy. The resulting deformable matching method shows low sensitivity to local minima and is able to track large non-linear deformations, with moderate computational load. The performances of the approach are assessed both on simulated 3D transformations and on a real data base of 3D brain MR Images from different individuals. The method has shown efficient in putting into correspondence the principle anatomical structures of the brain. An application to atlas-based MRI segmentation, by transporting a labeled segmentation map on patient data, is also presented.

Identification of multivariable nonlinear systems in the presence of colored noises using iterative hierarchical least squares algorithm.

PubMed

Jafari, Masoumeh; Salimifard, Maryam; Dehghani, Maryam

2014-07-01

This paper presents an efficient method for identification of nonlinear Multi-Input Multi-Output (MIMO) systems in the presence of colored noises. The method studies the multivariable nonlinear Hammerstein and Wiener models, in which, the nonlinear memory-less block is approximated based on arbitrary vector-based basis functions. The linear time-invariant (LTI) block is modeled by an autoregressive moving average with exogenous (ARMAX) model which can effectively describe the moving average noises as well as the autoregressive and the exogenous dynamics. According to the multivariable nature of the system, a pseudo-linear-in-the-parameter model is obtained which includes two different kinds of unknown parameters, a vector and a matrix. Therefore, the standard least squares algorithm cannot be applied directly. To overcome this problem, a Hierarchical Least Squares Iterative (HLSI) algorithm is used to simultaneously estimate the vector and the matrix of unknown parameters as well as the noises. The efficiency of the proposed identification approaches are investigated through three nonlinear MIMO case studies. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Hierarchical design of an electro-hydraulic actuator based on robust LPV methods

NASA Astrophysics Data System (ADS)

Németh, Balázs; Varga, Balázs; Gáspár, Péter

2015-08-01

The paper proposes a hierarchical control design of an electro-hydraulic actuator, which is used to improve the roll stability of vehicles. The purpose of the control system is to generate a reference torque, which is required by the vehicle dynamic control. The control-oriented model of the actuator is formulated in two subsystems. The high-level hydromotor is described in a linear form, while the low-level spool valve is a polynomial system. These subsystems require different control strategies. At the high level, a linear parameter-varying control is used to guarantee performance specifications. At the low level, a control Lyapunov-function-based algorithm, which creates discrete control input values of the valve, is proposed. The interaction between the two subsystems is guaranteed by the spool displacement, which is control input at the high level and must be tracked at the low-level control. The spool displacement has physical constraints, which must also be incorporated into the control design. The robust design of the high-level control incorporates the imprecision of the low-level control as an uncertainty of the system.

TiO2 with controlled nanoring/nanotube hierarchical structure: Multiabsorption oscillating peaks and photoelectrochemical properties

NASA Astrophysics Data System (ADS)

Sang, Lixia; Zhao, Yangbo; Niu, Youchen; Bai, Guangmei

2018-02-01

TiO2 with Nanoring/Nanotube (R/T) hierarchical structure can be prepared by tuning the oxidation time and oxidation voltage in the second step anodization. The resulting multiabsorption oscillating peaks in the visible light region present a strong dependence on the tube length which are derived from the interference of light reflected from the top nanorings and the bottom Ti substrate, and the optical path length in TiO2 R/T hierarchical structure can be estimated as about 2 μm. The tube length of the as-prepared TiO2 photoelectrode affects greatly its saturation photocurrent density, and the different tube-wall thickness can change the photocurrent-saturation potential. Under simulated AM 1.5 irradiation (100 mW/cm2), TiO2 R/T hierarchical structure with tube diameters of 20-40 nm and tube length of about 1.5 μm shows higher photocurrent density and hydrogen production rate at the bias of 0 V (vs. Ag/AgCl). The results from the IPCE plots and I-t curves verify that TiO2 R/T hierarchical structure can exhibit the visible light activity, which is more related to the absorption induced by the defects rather than oscillating peaks. Based on the unique multiple light reflection in TiO2 R/T hierarchical structure, surface treatment will pave a way for the better utilization of oscillating peaks in the visible light region.

Effects of a strategy to improve offender assessment practices: Staff perceptions of implementation outcomes.

PubMed

Welsh, Wayne N; Lin, Hsiu-Ju; Peters, Roger H; Stahler, Gerald J; Lehman, Wayne E K; Stein, Lynda A R; Monico, Laura; Eggers, Michele; Abdel-Salam, Sami; Pierce, Joshua C; Hunt, Elizabeth; Gallagher, Colleen; Frisman, Linda K

2015-07-01

This implementation study examined the impact of an organizational process improvement intervention (OPII) on a continuum of evidence based practices related to assessment and community reentry of drug-involved offenders: Measurement/Instrumentation, Case Plan Integration, Conveyance/Utility, and Service Activation/Delivery. To assess implementation outcomes (staff perceptions of evidence-based assessment practices), a survey was administered to correctional and treatment staff (n=1509) at 21 sites randomly assigned to an Early- or Delayed-Start condition. Hierarchical linear models with repeated measures were used to examine changes in evidence-based assessment practices over time, and organizational characteristics were examined as covariates to control for differences across the 21 research sites. Results demonstrated significant intervention and sustainability effects for three of the four assessment domains examined, although stronger effects were obtained for intra- than inter-agency outcomes. No significant effects were found for Conveyance/Utility. Implementation interventions such as the OPII represent an important tool to enhance the use of evidence-based assessment practices in large and diverse correctional systems. Intra-agency assessment activities that were more directly under the control of correctional agencies were implemented most effectively. Activities in domains that required cross-systems collaboration were not as successfully implemented, although longer follow-up periods might afford detection of stronger effects. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Multicast Routing of Hierarchical Data

NASA Technical Reports Server (NTRS)

Shacham, Nachum

1992-01-01

The issue of multicast of broadband, real-time data in a heterogeneous environment, in which the data recipients differ in their reception abilities, is considered. Traditional multicast schemes, which are designed to deliver all the source data to all recipients, offer limited performance in such an environment, since they must either force the source to overcompress its signal or restrict the destination population to those who can receive the full signal. We present an approach for resolving this issue by combining hierarchical source coding techniques, which allow recipients to trade off reception bandwidth for signal quality, and sophisticated routing algorithms that deliver to each destination the maximum possible signal quality. The field of hierarchical coding is briefly surveyed and new multicast routing algorithms are presented. The algorithms are compared in terms of network utilization efficiency, lengths of paths, and the required mechanisms for forwarding packets on the resulting paths.

Wavelet compression of multichannel ECG data by enhanced set partitioning in hierarchical trees algorithm.

PubMed

Sharifahmadian, Ershad

2006-01-01

The set partitioning in hierarchical trees (SPIHT) algorithm is very effective and computationally simple technique for image and signal compression. Here the author modified the algorithm which provides even better performance than the SPIHT algorithm. The enhanced set partitioning in hierarchical trees (ESPIHT) algorithm has performance faster than the SPIHT algorithm. In addition, the proposed algorithm reduces the number of bits in a bit stream which is stored or transmitted. I applied it to compression of multichannel ECG data. Also, I presented a specific procedure based on the modified algorithm for more efficient compression of multichannel ECG data. This method employed on selected records from the MIT-BIH arrhythmia database. According to experiments, the proposed method attained the significant results regarding compression of multichannel ECG data. Furthermore, in order to compress one signal which is stored for a long time, the proposed multichannel compression method can be utilized efficiently.

Materials Knowledge Systems in Python - A Data Science Framework for Accelerated Development of Hierarchical Materials.

PubMed

Brough, David B; Wheeler, Daniel; Kalidindi, Surya R

2017-03-01

There is a critical need for customized analytics that take into account the stochastic nature of the internal structure of materials at multiple length scales in order to extract relevant and transferable knowledge. Data driven Process-Structure-Property (PSP) linkages provide systemic, modular and hierarchical framework for community driven curation of materials knowledge, and its transference to design and manufacturing experts. The Materials Knowledge Systems in Python project (PyMKS) is the first open source materials data science framework that can be used to create high value PSP linkages for hierarchical materials that can be leveraged by experts in materials science and engineering, manufacturing, machine learning and data science communities. This paper describes the main functions available from this repository, along with illustrations of how these can be accessed, utilized, and potentially further refined by the broader community of researchers.

Semiconductor hierarchically structured flower-like clusters for dye-sensitized solar cells with nearly 100% charge collection efficiency.

PubMed

Xin, Xukai; Liu, Hsiang-Yu; Ye, Meidan; Lin, Zhiqun

2013-11-21

By combining the ease of producing ZnO nanoflowers with the advantageous chemical stability of TiO2, hierarchically structured hollow TiO2 flower-like clusters were yielded via chemical bath deposition (CBD) of ZnO nanoflowers, followed by their conversion into TiO2 flower-like clusters in the presence of TiO2 precursors. The effects of ZnO precursor concentration, precursor amount, and reaction time on the formation of ZnO nanoflowers were systematically explored. Dye-sensitized solar cells fabricated by utilizing these hierarchically structured ZnO and TiO2 flower clusters exhibited a power conversion efficiency of 1.16% and 2.73%, respectively, under 100 mW cm(-2) illumination. The intensity modulated photocurrent/photovoltage spectroscopy (IMPS/IMVS) studies suggested that flower-like structures had a fast electron transit time and their charge collection efficiency was nearly 100%.

Materials Knowledge Systems in Python - A Data Science Framework for Accelerated Development of Hierarchical Materials

PubMed Central

Brough, David B; Wheeler, Daniel; Kalidindi, Surya R.

2017-01-01

There is a critical need for customized analytics that take into account the stochastic nature of the internal structure of materials at multiple length scales in order to extract relevant and transferable knowledge. Data driven Process-Structure-Property (PSP) linkages provide systemic, modular and hierarchical framework for community driven curation of materials knowledge, and its transference to design and manufacturing experts. The Materials Knowledge Systems in Python project (PyMKS) is the first open source materials data science framework that can be used to create high value PSP linkages for hierarchical materials that can be leveraged by experts in materials science and engineering, manufacturing, machine learning and data science communities. This paper describes the main functions available from this repository, along with illustrations of how these can be accessed, utilized, and potentially further refined by the broader community of researchers. PMID:28690971

Changes of hierarchical network in local and world stock market

NASA Astrophysics Data System (ADS)

Patwary, Enayet Ullah; Lee, Jong Youl; Nobi, Ashadun; Kim, Doo Hwan; Lee, Jae Woo

2017-10-01

We consider the cross-correlation coefficients of the daily returns in the local and global stock markets. We generate the minimal spanning tree (MST) using the correlation matrix. We observe that the MSTs change their structure from chain-like networks to star-like networks during periods of market uncertainty. We quantify the measure of the hierarchical network utilizing the value of the hierarchy measured by the hierarchical path. The hierarchy and betweenness centrality characterize the state of the market regarding the impact of crises. During crises, the non-financial company is established as the central node of the MST. However, before the crisis and during stable periods, the financial company is occupying the central node of the MST in the Korean and the U.S. stock markets. The changes in the network structure and the central node are good indicators of an upcoming crisis.

Association between surgeon volume and hospitalisation costs for patients with oral cancer: a nationwide population base study in Taiwan.

PubMed

Lee, C-C; Ho, H-C; Jack, Lee C-C; Su, Y-C; Lee, M-S; Hung, S-K; Chou, Pesus

2010-02-01

Oral cancer leads to a considerable use of and expenditure on health care. Wide resection of the tumour and reconstruction with a pedicle flap/free flap is widely used. This study was conducted to explore the relationship between hospitalisation costs and surgeon case volume when this operation was performed. A population-based study. This study uses data for the years 2005-2006 obtained from the National Health Insurance Research Database published in the Taiwanese National Health Research Institute. From this population-based data, the authors selected a total of 2663 oral cancer patients who underwent tumour resection and reconstruction. Case volume relationships were based on the following criteria; low-, medium-, high-, very high-volume surgeons were defined by or= 56 resections with reconstruction, respectively. Hierarchical linear regression analysis was subsequently performed to explore the relationship between surgeon case volume and the cost and length of hospitalisation. The mean hospitalisation cost among the 2663 patients was US$ 9528 (all costs are given in US dollars). After adjusting for physician, hospital, and patient characteristics in a hierarchical linear regression model, the cost per patient for low-volume surgeons was found to be US$ 741 (P = 0.012) higher than that for medium-volume surgeons, US$ 1546 (P < 0.001) higher than that for high-volume surgeons, and US$ 1820 (P < 0.001) higher than that for very-high-volume surgeons. After adjustment for physician, hospital, and patient characteristics, the hierarchical linear regression model revealed that the mean length of stay per patient for low-volume surgeons was the highest (P < 0.001). After adjustment for physician, hospital, and patient characteristics, low-volume surgeons performing wide excision with reconstructive surgery in oral cancer patients incurred significantly higher costs and longer hospital stays per patient than did other surgeons. Treatment strategies adopted by high- and very-high-volume surgeons should be analysed further and utilised more widely.

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

Linear scaling computation of the Fock matrix. VI. Data parallel computation of the exchange-correlation matrix

NASA Astrophysics Data System (ADS)

Gan, Chee Kwan; Challacombe, Matt

2003-05-01

Recently, early onset linear scaling computation of the exchange-correlation matrix has been achieved using hierarchical cubature [J. Chem. Phys. 113, 10037 (2000)]. Hierarchical cubature differs from other methods in that the integration grid is adaptive and purely Cartesian, which allows for a straightforward domain decomposition in parallel computations; the volume enclosing the entire grid may be simply divided into a number of nonoverlapping boxes. In our data parallel approach, each box requires only a fraction of the total density to perform the necessary numerical integrations due to the finite extent of Gaussian-orbital basis sets. This inherent data locality may be exploited to reduce communications between processors as well as to avoid memory and copy overheads associated with data replication. Although the hierarchical cubature grid is Cartesian, naive boxing leads to irregular work loads due to strong spatial variations of the grid and the electron density. In this paper we describe equal time partitioning, which employs time measurement of the smallest sub-volumes (corresponding to the primitive cubature rule) to load balance grid-work for the next self-consistent-field iteration. After start-up from a heuristic center of mass partitioning, equal time partitioning exploits smooth variation of the density and grid between iterations to achieve load balance. With the 3-21G basis set and a medium quality grid, equal time partitioning applied to taxol (62 heavy atoms) attained a speedup of 61 out of 64 processors, while for a 110 molecule water cluster at standard density it achieved a speedup of 113 out of 128. The efficiency of equal time partitioning applied to hierarchical cubature improves as the grid work per processor increases. With a fine grid and the 6-311G(df,p) basis set, calculations on the 26 atom molecule α-pinene achieved a parallel efficiency better than 99% with 64 processors. For more coarse grained calculations, superlinear speedups are found to result from reduced computational complexity associated with data parallelism.

Personality Accounts for the Connection Between Volunteering and Health

PubMed Central

Jackson, Joshua J.; Morrow-Howell, Nancy; Oltmanns, Thomas F.

2015-01-01

Objectives. Existing literature has shown that volunteering is related to better physical and mental health outcomes. The purpose of this study is to examine whether personality traits and volunteering are independent predictors of physical and mental health. Methods. The current study utilizes data from the St. Louis Personality and Aging Network (SPAN), a representative sample of community-based adults between the ages of 55 and 64. Using hierarchical linear regressions, we test whether volunteering is a significant predictor of both physical and mental health while controlling for personality traits. Results. We find that volunteering is not significantly related to either physical or mental health while controlling for personality traits. We also find that lower neuroticism is related to better physical functioning and mental health, whereas higher extraversion is related to better mental health. Discussion. These results indicate that volunteering may be related to health outcomes because of the personality characteristics of volunteers, not the volunteering experience in and of itself. Future longitudinal studies are needed to further explore the relationship between personality, volunteering, and health. PMID:24704620

Utilization of emergency and hospital services among individuals in substance abuse treatment

PubMed Central

2014-01-01

Background To examine risk factors for use of hospital services among racial and ethnic minority clients in publicly funded substance abuse treatment in Los Angeles County, California. We explored cross-sectional annual data (2006 to 2009) from the Los Angeles County Participant Reporting System for adult participants (n = 73,251) who received services from treatment programs (n = 231). Methods This retrospective analysis of county admission data relied on hierarchical linear negative binomial regression models to explore number of hospital visits, accounting for clients nested in programs. Client data were collected during personal interviews at admission. Findings Our findings support previous work that noted increased use of emergency rooms among individuals suffering from mental health- and substance use-related issues and extend the knowledge base by highlighting other important features such as treatment need, i.e., residential compared to outpatient treatment. Conclusions These findings have implications for health care policy in terms of the need to increase prevention services and reduce costly hospitalization for a population at significant risk of co-occurring mental and physical disorders. PMID:24708866

Meal and snack-time eating disorder cognitions predict eating disorder behaviors and vice versa in a treatment seeking sample: A mobile technology based ecological momentary assessment study.

PubMed

Levinson, Cheri A; Sala, Margarita; Fewell, Laura; Brosof, Leigh C; Fournier, Lauren; Lenze, Eric J

2018-06-01

Individuals with eating disorders experience high anxiety when eating, which may contribute to the high relapse rates seen in the eating disorders. However, it is unknown if specific cognitions associated with such anxiety (e.g., fears of gaining weight) may lead to engagement in eating disorder behaviors (e.g., weighing oneself). Participants (N = 66) recently treated at a residential eating disorder facility and diagnosed with an eating disorder (primarily anorexia nervosa; n = 40; 60.6%) utilized a mobile application to answer questions about mealtime cognitions, anxiety, and eating disorder behaviors four times a day for one week. Hierarchical linear models using cross-lag analyses identified that there were quasi-causal (and sometimes reciprocal) within-person relationships between specific eating disorder cognitions and subsequent eating disorder behaviors. These cognitions predicted higher anxiety during the next meal and eating disorder pathology at one-month follow-up. Interventions personalized to target these specific cognitions in real time might reduce eating disorder relapse. Copyright © 2018 Elsevier Ltd. All rights reserved.

UNIX: A Tool for Information Management.

ERIC Educational Resources Information Center

Frey, Dean

1989-01-01

Describes UNIX, a computer operating system that supports multi-task and multi-user operations. Characteristics that make it especially suitable for library applications are discussed, including a hierarchical file structure and utilities for text processing, database activities, and bibliographic work. Sources of information on hardware…

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

NASA Astrophysics Data System (ADS)

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

2005-10-01

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

Cross-regulation among arabinose, xylose and rhamnose utilization systems in E. coli.

PubMed

Choudhury, D; Saini, S

2018-02-01

Bacteria frequently encounter multiple sugars in their natural surroundings. While the dynamics of utilization of glucose-containing sugar mixtures have been well investigated, there are few reports addressing regulation of utilization of glucose-free mixtures particularly pentoses. These sugars comprise a considerable fraction in hemicellulose which can be converted by suitable biocatalysts to biofuels and other value-added products. Hence, understanding of transcriptional cross-regulation among different pentose sugar utilization systems is essential for successful development of industrial strains. In this work, we study mixed-sugar utilization with respect to three secondary carbon sources - arabinose, xylose and rhamnose at single-cell resolution in Escherichia coli. Our results reveal that hierarchical utilization among these systems is not strict but rather can be eliminated or reversed by altering the relative ratios of the preferred and nonpreferred sugars. Since transcriptional cross-regulation among pentose sugar systems operates through competitive binding of noncognate sugar-regulator complex, altering sugar concentrations is thought to eliminate nonspecific binding by affecting concentration of the regulator - sugar complexes. Plant biomass comprises of hexose and pentose sugar mixtures. These sugars are processed by micro-organisms to form products like biofuels, polymers etc. One of the major challenges with mixed-sugar processing by micro-organisms is hierarchical utilization of sugars due to cross-regulation among sugar systems. In this work, we discuss cross-regulation among three secondary carbon sources - arabinose, xylose and rhamnose. Our results show that cross-regulation between pentose sugars is complex with multiple layers of regulation. These aspects need to be addressed for effective design of processes to extract energy from biomass. © 2017 The Society for Applied Microbiology.

Bayesian Hierarchical Random Intercept Model Based on Three Parameter Gamma Distribution

NASA Astrophysics Data System (ADS)

Wirawati, Ika; Iriawan, Nur; Irhamah

2017-06-01

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

Multilevel Hierarchical Modeling of Benthic Macroinvertebrate Responses to Urbanization in Nine Metropolitan Regions across the Conterminous United States

USGS Publications Warehouse

Kashuba, Roxolana; Cha, YoonKyung; Alameddine, Ibrahim; Lee, Boknam; Cuffney, Thomas F.

2010-01-01

Multilevel hierarchical modeling methodology has been developed for use in ecological data analysis. The effect of urbanization on stream macroinvertebrate communities was measured across a gradient of basins in each of nine metropolitan regions across the conterminous United States. The hierarchical nature of this dataset was harnessed in a multi-tiered model structure, predicting both invertebrate response at the basin scale and differences in invertebrate response at the region scale. Ordination site scores, total taxa richness, Ephemeroptera, Plecoptera, Trichoptera (EPT) taxa richness, and richness-weighted mean tolerance of organisms at a site were used to describe invertebrate responses. Percentage of urban land cover was used as a basin-level predictor variable. Regional mean precipitation, air temperature, and antecedent agriculture were used as region-level predictor variables. Multilevel hierarchical models were fit to both levels of data simultaneously, borrowing statistical strength from the complete dataset to reduce uncertainty in regional coefficient estimates. Additionally, whereas non-hierarchical regressions were only able to show differing relations between invertebrate responses and urban intensity separately for each region, the multilevel hierarchical regressions were able to explain and quantify those differences within a single model. In this way, this modeling approach directly establishes the importance of antecedent agricultural conditions in masking the response of invertebrates to urbanization in metropolitan regions such as Milwaukee-Green Bay, Wisconsin; Denver, Colorado; and Dallas-Fort Worth, Texas. Also, these models show that regions with high precipitation, such as Atlanta, Georgia; Birmingham, Alabama; and Portland, Oregon, start out with better regional background conditions of invertebrates prior to urbanization but experience faster negative rates of change with urbanization. Ultimately, this urbanization-invertebrate response example is used to detail the multilevel hierarchical construction methodology, showing how the result is a set of models that are both statistically more rigorous and ecologically more interpretable than simple linear regression models.

A nonlinear mechanics model of bio-inspired hierarchical lattice materials consisting of horseshoe microstructures

PubMed Central

Ma, Qiang; Cheng, Huanyu; Jang, Kyung-In; Luan, Haiwen; Hwang, Keh-Chih; Rogers, John A.; Huang, Yonggang; Zhang, Yihui

2016-01-01

Development of advanced synthetic materials that can mimic the mechanical properties of non-mineralized soft biological materials has important implications in a wide range of technologies. Hierarchical lattice materials constructed with horseshoe microstructures belong to this class of bio-inspired synthetic materials, where the mechanical responses can be tailored to match the nonlinear J-shaped stress-strain curves of human skins. The underlying relations between the J-shaped stress-strain curves and their microstructure geometry are essential in designing such systems for targeted applications. Here, a theoretical model of this type of hierarchical lattice material is developed by combining a finite deformation constitutive relation of the building block (i.e., horseshoe microstructure), with the analyses of equilibrium and deformation compatibility in the periodical lattices. The nonlinear J-shaped stress-strain curves and Poisson ratios predicted by this model agree very well with results of finite element analyses (FEA) and experiment. Based on this model, analytic solutions were obtained for some key mechanical quantities, e.g., elastic modulus, Poisson ratio, peak modulus, and critical strain around which the tangent modulus increases rapidly. A negative Poisson effect is revealed in the hierarchical lattice with triangular topology, as opposed to a positive Poisson effect in hierarchical lattices with Kagome and honeycomb topologies. The lattice topology is also found to have a strong influence on the stress-strain curve. For the three isotropic lattice topologies (triangular, Kagome and honeycomb), the hierarchical triangular lattice material renders the sharpest transition in the stress-strain curve and relative high stretchability, given the same porosity and arc angle of horseshoe microstructure. Furthermore, a demonstrative example illustrates the utility of the developed model in the rapid optimization of hierarchical lattice materials for reproducing the desired stress-strain curves of human skins. This study provides theoretical guidelines for future designs of soft bio-mimetic materials with hierarchical lattice constructions. PMID:27087704

A nonlinear mechanics model of bio-inspired hierarchical lattice materials consisting of horseshoe microstructures

NASA Astrophysics Data System (ADS)

Ma, Qiang; Cheng, Huanyu; Jang, Kyung-In; Luan, Haiwen; Hwang, Keh-Chih; Rogers, John A.; Huang, Yonggang; Zhang, Yihui

2016-05-01

Development of advanced synthetic materials that can mimic the mechanical properties of non-mineralized soft biological materials has important implications in a wide range of technologies. Hierarchical lattice materials constructed with horseshoe microstructures belong to this class of bio-inspired synthetic materials, where the mechanical responses can be tailored to match the nonlinear J-shaped stress-strain curves of human skins. The underlying relations between the J-shaped stress-strain curves and their microstructure geometry are essential in designing such systems for targeted applications. Here, a theoretical model of this type of hierarchical lattice material is developed by combining a finite deformation constitutive relation of the building block (i.e., horseshoe microstructure), with the analyses of equilibrium and deformation compatibility in the periodical lattices. The nonlinear J-shaped stress-strain curves and Poisson ratios predicted by this model agree very well with results of finite element analyses (FEA) and experiment. Based on this model, analytic solutions were obtained for some key mechanical quantities, e.g., elastic modulus, Poisson ratio, peak modulus, and critical strain around which the tangent modulus increases rapidly. A negative Poisson effect is revealed in the hierarchical lattice with triangular topology, as opposed to a positive Poisson effect in hierarchical lattices with Kagome and honeycomb topologies. The lattice topology is also found to have a strong influence on the stress-strain curve. For the three isotropic lattice topologies (triangular, Kagome and honeycomb), the hierarchical triangular lattice material renders the sharpest transition in the stress-strain curve and relative high stretchability, given the same porosity and arc angle of horseshoe microstructure. Furthermore, a demonstrative example illustrates the utility of the developed model in the rapid optimization of hierarchical lattice materials for reproducing the desired stress-strain curves of human skins. This study provides theoretical guidelines for future designs of soft bio-mimetic materials with hierarchical lattice constructions.

A nonlinear mechanics model of bio-inspired hierarchical lattice materials consisting of horseshoe microstructures.

PubMed

Ma, Qiang; Cheng, Huanyu; Jang, Kyung-In; Luan, Haiwen; Hwang, Keh-Chih; Rogers, John A; Huang, Yonggang; Zhang, Yihui

2016-05-01

Development of advanced synthetic materials that can mimic the mechanical properties of non-mineralized soft biological materials has important implications in a wide range of technologies. Hierarchical lattice materials constructed with horseshoe microstructures belong to this class of bio-inspired synthetic materials, where the mechanical responses can be tailored to match the nonlinear J-shaped stress-strain curves of human skins. The underlying relations between the J-shaped stress-strain curves and their microstructure geometry are essential in designing such systems for targeted applications. Here, a theoretical model of this type of hierarchical lattice material is developed by combining a finite deformation constitutive relation of the building block (i.e., horseshoe microstructure), with the analyses of equilibrium and deformation compatibility in the periodical lattices. The nonlinear J-shaped stress-strain curves and Poisson ratios predicted by this model agree very well with results of finite element analyses (FEA) and experiment. Based on this model, analytic solutions were obtained for some key mechanical quantities, e.g., elastic modulus, Poisson ratio, peak modulus, and critical strain around which the tangent modulus increases rapidly. A negative Poisson effect is revealed in the hierarchical lattice with triangular topology, as opposed to a positive Poisson effect in hierarchical lattices with Kagome and honeycomb topologies. The lattice topology is also found to have a strong influence on the stress-strain curve. For the three isotropic lattice topologies (triangular, Kagome and honeycomb), the hierarchical triangular lattice material renders the sharpest transition in the stress-strain curve and relative high stretchability, given the same porosity and arc angle of horseshoe microstructure. Furthermore, a demonstrative example illustrates the utility of the developed model in the rapid optimization of hierarchical lattice materials for reproducing the desired stress-strain curves of human skins. This study provides theoretical guidelines for future designs of soft bio-mimetic materials with hierarchical lattice constructions.

Construction of Matryoshka-type structures from supercharged protein nanocages.

PubMed

Beck, Tobias; Tetter, Stephan; Künzle, Matthias; Hilvert, Donald

2015-01-12

Designing nanoscaled hierarchical structures with increasing levels of complexity is challenging. Here we show that electrostatic interactions between two complementarily supercharged protein nanocages can be effectively utilized to create nested Matryoshka-type structures. Cage-within-cage complexes containing spatially ordered iron oxide nanoparticles spontaneously self-assemble upon mixing positively supercharged ferritin compartments with AaLS-13, a larger shell-forming protein with a negatively supercharged lumen. Exploiting engineered Coulombic interactions and protein dynamics in this way opens up new avenues for creating hierarchically organized supramolecular assemblies for application as delivery vehicles, reaction chambers, and artificial organelles. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

High School Grade Inflation from 2004 to 2011. ACT Research Report Series, 2013 (3)

ERIC Educational Resources Information Center

Zhang, Qian; Sanchez, Edgar I.

2013-01-01

This study explores inflation in high school grade point average (HSGPA), defined as trend over time in the conditional average of HSGPA, given ACT® Composite score. The time period considered is 2004 to 2011. Using hierarchical linear modeling, the study updates a previous analysis of Woodruff and Ziomek (2004). The study also investigates…

A Hierarchical Linear Modeling Analysis of Working Memory and Implicit Prosody in the Resolution of Adjunct Attachment Ambiguity

ERIC Educational Resources Information Center

Traxler, Matthew J.

2009-01-01

An eye-movement monitoring experiment investigated readers' response to temporarily ambiguous sentences. The sentences were ambiguous because a relative clause could attach to one of two preceding nouns. Semantic information disambiguated the sentences. Working memory considerations predict an overall preference for the second of the two nouns, as…

Equity in Educational Resources at the School Level in Korea

ERIC Educational Resources Information Center

Woo, Myung Suk

2010-01-01

This paper analyzed the equity of resources at the elementary school level in Korea using hierarchical linear modeling (HLM). The data included 2,327 Korean public elementary schools in 101 Local Governments within five Local Educational Offices (LEOs). This study found that schools in low property tax per resident areas receive fewer grants,…

Teacher-Child Relationship Quality and Academic Achievement in Elementary School: Does Gender Matter?

ERIC Educational Resources Information Center

McCormick, Meghan P.; O'Connor, Erin E.

2015-01-01

Using data from the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development (N = 1,364) and 2-level hierarchical linear models with site fixed effects, we examined between- and within-child associations between teacher-child relationship closeness and conflict and standardized measures of children's…

A Multilevel Study of Students' Motivations of Studying Accounting: Implications for Employers

ERIC Educational Resources Information Center

Law, Philip; Yuen, Desmond

2012-01-01

Purpose: The purpose of this study is to examine the influence of factors affecting students' choice of accounting as a study major in Hong Kong. Design/methodology/approach: Multinomial logistic regression and Hierarchical Generalized Linear Modeling (HGLM) are used to analyze the survey data for the level one and level two data, which is the…

A Multiple Risk Factors Model of the Development of Aggression among Early Adolescents from Urban Disadvantaged Neighborhoods

ERIC Educational Resources Information Center

Kim, Sangwon; Orpinas, Pamela; Kamphaus, Randy; Kelder, Steven H.

2011-01-01

This study empirically derived a multiple risk factors model of the development of aggression among middle school students in urban, low-income neighborhoods, using Hierarchical Linear Modeling (HLM). Results indicated that aggression increased from sixth to eighth grade. Additionally, the influences of four risk domains (individual, family,…

Universal Beliefs and Specific Practices: Students' Math Self-Efficacy and Related Factors in the United States and China

ERIC Educational Resources Information Center

Wu, Yin

2016-01-01

This study intends to compare and contrast student and school factors that are associated with students' mathematics self-efficacy in the United States and China. Using hierarchical linear regressions to analyze the Programme for International Student Assessment (PISA) 2012 data, this study compares math self-efficacy, achievement, and variables…

Trajectory of Life Satisfaction and Its Relationship with Subjective Economic Status and Successful Aging

ERIC Educational Resources Information Center

Hsu, Hui-Chuan

2010-01-01

The aim of the study was to explore the relationship between subjective economic status and indicators of successful aging to life satisfaction trajectories among the elderly in Taiwan. Data were from the four waves of "Survey of Health and Living Status of the Elderly in Taiwan". Hierarchical linear modeling was conducted. Subjective…

Toward Addressing the Issues of Site Selection in District Effectiveness Research: A Two-Level Hierarchical Linear Growth Model

ERIC Educational Resources Information Center

Bowers, Alex J.

2010-01-01

Purpose: District effectiveness research (DER) is an emerging field concerned with identifying the organizational structures, administration, and leadership practices at the school district level that help districts find success with all of their students across the schools within the system. This work has mirrored much of the early school…

Science Teaching Reform through Professional Development: Teachers' Use of a Scientific Classroom Discourse Community Model

ERIC Educational Resources Information Center

Lewis, Elizabeth B.; Baker, Dale R.; Helding, Brandon A.

2015-01-01

This report outlines a 2-year investigation into how secondary science teachers used professional development (PD) to build scientific classroom discourse communities (SCDCs). Observation data, teacher, student, and school demographic information were used to build a hierarchical linear model. The length of time that teachers received PD was the…

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

ERIC Educational Resources Information Center

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

2008-01-01

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

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

ERIC Educational Resources Information Center

Huang, Haigen; Zhu, Hao

2017-01-01

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

Classification Based on Hierarchical Linear Models: The Need for Incorporation of Social Contexts in Classification Analysis

ERIC Educational Resources Information Center

Vaughn, Brandon K.; Wang, Qui

2009-01-01

Many areas in educational and psychological research involve the use of classification statistical analysis. For example, school districts might be interested in attaining variables that provide optimal prediction of school dropouts. In psychology, a researcher might be interested in the classification of a subject into a particular psychological…

Modeling Reader and Text Interactions during Narrative Comprehension: A Test of the Lexical Quality Hypothesis

ERIC Educational Resources Information Center

Hamilton, Stephen T.; Freed, Erin M.; Long, Debra L.

2013-01-01

The goal of this study was to examine predictions derived from the Lexical Quality Hypothesis regarding relations among word decoding, working-memory capacity, and the ability to integrate new concepts into a developing discourse representation. Hierarchical Linear Modeling was used to quantify the effects of three text properties (length,…

Psychosocial Development from College through Midlife: A 34-Year Sequential Study

ERIC Educational Resources Information Center

Whitbourne, Susan Krauss; Sneed, Joel R.; Sayer, Aline

2009-01-01

Two cohorts of alumni, leading-edge and trailing-edge baby boomers, first tested in their college years, were followed to ages 43 (N = 136) and 54 (N = 182) on a measure of Erikson's theory of psychosocial development. Hierarchical linear modeling was used to model the trajectory of growth for each psychosocial issue across middle adulthood. As…

Analysis of Student Performance in Large-Enrollment Life Science Courses

ERIC Educational Resources Information Center

Creech, Leah Renee; Sweeder, Ryan D.

2012-01-01

This study examined the historical performance of students at Michigan State University in 12 life sciences courses over 13 yr to find variables impacting student success. Hierarchical linear modeling predicted 25.0-62.8% of the variance in students' grades in the courses analyzed. The primary predictor of a student's course grade was his or her…

Connecting the Dots: How Connectedness to Multiple Contexts Influences the Psychological and Academic Adjustment of Urban Youth

ERIC Educational Resources Information Center

Witherspoon, Dawn; Schotland, Marieka; Way, Niobe; Hughes, Diane

2009-01-01

Cluster analyses and hierarchical linear modeling were used to investigate the impact of perceptions of connectedness to family, school, and neighborhood contexts on academic and psycho-social outcomes for 437 urban ethnically diverse adolescents. Five profiles of connectedness to family, school, and neighborhood were identified. Two profiles were…

Does High School Facility Quality Affect Student Achievement? A Two-Level Hierarchical Linear Model

ERIC Educational Resources Information Center

Bowers, Alex J.; Urick, Angela

2011-01-01

The purpose of this study is to isolate the independent effects of high school facility quality on student achievement using a large, nationally representative U.S. database of student achievement and school facility quality. Prior research on linking school facility quality to student achievement has been mixed. Studies that relate overall…

Building a Multicontextual Model of Latino College Enrollment: Student, School, and State-Level Effects

ERIC Educational Resources Information Center

Nunez, Anne-Marie; Kim, Dongbin

2012-01-01

Latinos' college enrollment rates, particularly in four-year institutions, have not kept pace with their population growth in the United States. Using three-level hierarchical generalized linear modeling, this study analyzes data from the Educational Longitudinal Study (ELS) to examine the influence of high school and state contexts, in addition…

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

ERIC Educational Resources Information Center

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

2007-01-01

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

The Impact of School Environment and Grade Level on Student Delinquency: A Multilevel Modeling Approach

ERIC Educational Resources Information Center

Lo, Celia C.; Kim, Young S.; Allen, Thomas M.; Allen, Andrea N.; Minugh, P. Allison; Lomuto, Nicoletta

2011-01-01

Effects on delinquency made by grade level, school type (based on grade levels accommodated), and prosocial school climate were assessed, controlling for individual-level risk and protective factors. Data were obtained from the Substance Abuse Services Division of Alabama's state mental health agency and analyzed via hierarchical linear modeling,…

Adolescents' as Active Agents in the Socialization Process: Legitimacy of Parental Authority and Obligation to Obey as Predictors of Obedience

ERIC Educational Resources Information Center

Darling, Nancy; Cumsille, Patricio; Loreto Martinez, M.

2007-01-01

Adolescents' agreement with parental standards and beliefs about the legitimacy of parental authority and their own obligation to obey were used to predict adolescents' obedience, controlling for parental monitoring, rules, and rule enforcement. Hierarchical linear models were used to predict both between-adolescent and within-adolescent,…

Peer Victimization within the Ethnic Context of High School

ERIC Educational Resources Information Center

Felix, Erika D.; You, Sukkyung

2011-01-01

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

Concordance of Interests in Dynamic Models of Social Partnership in the System of Continuing Professional Education

ERIC Educational Resources Information Center

Tarasenko, Larissa V.; Ougolnitsky, Guennady A.; Usov, Anatoly B.; Vaskov, Maksim A.; Kirik, Vladimir A.; Astoyanz, Margarita S.; Angel, Olga Y.

2016-01-01

A dynamic game theoretic model of concordance of interests in the process of social partnership in the system of continuing professional education is proposed. Non-cooperative, cooperative, and hierarchical setups are examined. Analytical solution for a linear state version of the model is provided. Nash equilibrium algorithms (for non-cooperative…

Illustration of a Multilevel Model for Meta-Analysis

ERIC Educational Resources Information Center

de la Torre, Jimmy; Camilli, Gregory; Vargas, Sadako; Vernon, R. Fox

2007-01-01

In this article, the authors present a multilevel (or hierarchical linear) model that illustrates issues in the application of the model to data from meta-analytic studies. In doing so, several issues are discussed that typically arise in the course of a meta-analysis. These include the presence of non-zero between-study variability, how multiple…

HLM in Cluster-Randomised Trials--Measuring Efficacy across Diverse Populations of Learners

ERIC Educational Resources Information Center

Hegedus, Stephen; Tapper, John; Dalton, Sara; Sloane, Finbarr

2013-01-01

We describe the application of Hierarchical Linear Modelling (HLM) in a cluster-randomised study to examine learning algebraic concepts and procedures in an innovative, technology-rich environment in the US. HLM is applied to measure the impact of such treatment on learning and on contextual variables. We provide a detailed description of such…

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

ERIC Educational Resources Information Center

Lehrer, Richard

2017-01-01

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

Union Status and Faculty Job Satisfaction: Contemporary Evidence from the 2004 National Study of Postsecondary Faculty

ERIC Educational Resources Information Center

Myers, Carrie B.

2011-01-01

This study tests the association between union status and job satisfaction using 8,000+ U.S. faculty at four-year public institutions surveyed in the 2004 National Study of Postsecondary Faculty. The results from hierarchical linear models that included individual and institutional variables found that nonunion faculty reported significantly…

Effects of a Reform High School Mathematics Curriculum on Student Achievement: Whom Does It Benefit?

ERIC Educational Resources Information Center

Krupa, Erin E.; Confrey, Jere

2017-01-01

This study compared the effects of an integrated reform-based curriculum to a subject-specific curriculum on student learning of 19,526 high school algebra students. Using hierarchical linear modelling to account for variation in student achievement, the impact of the reform-based "Core-Plus Mathematics" curricular materials on student…

Parent Involvement and Children's Academic and Social Development in Elementary School

ERIC Educational Resources Information Center

El Nokali, Nermeen E.; Bachman, Heather J.; Votruba-Drzal, Elizabeth

2010-01-01

Data from the National Institute of Child Health and Human Development (NICHD) Study of Early Childcare and Youth Development (N = 1,364) were used to investigate children's trajectories of academic and social development across 1st, 3rd, and 5th grades. Hierarchical linear modeling was used to examine within- and between-child associations among…

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

ERIC Educational Resources Information Center

Shiovitz-Ezra, Sharon; Leitsch, Sara A.

2010-01-01

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

Parental Characteristics and the Achievement Gap in Mathematics: Hierarchical Linear Modeling Analysis of Longitudinal Study of American Youth (LSAY)

ERIC Educational Resources Information Center

Shoraka, Mohammad; Arnold, Robert; Kim, Eun Sook; Salinitri, Geri; Kromrey, Jeffrey

2015-01-01

One of the most salient problems in education is the achievement gap. The researchers investigated the effects of parental education and parental occupations in science, technology, engineering, mathematics, or medical professions (STEMM) on the achievement gap in mathematics. Because students were nested within schools, two-level Hierarchical…

Division of Labor in German Dual-Earner Families: Testing Equity Theoretical Hypotheses

ERIC Educational Resources Information Center

Klumb, Petra; Hoppmann, Christiane; Staats, Melanie

2006-01-01

On the basis of 52 German dual-earner couples with at least 1 child younger than 5 years, we tested the effects of an unequal division of labor on relationship satisfaction. We analyzed diary reports of time allocated to productive activities according to the actor-partner-interdependence model. Hierarchical linear models showed that rather than…

Relationships of Out-of-School-Time Mathematics Lessons to Mathematical Literacy in Singapore and Australia

ERIC Educational Resources Information Center

Kaur, Berinderjeet; Areepattamannil, Shaljan

2013-01-01

This study, drawing on date from the Programme for International Student Assessment (PISA) 2009, examined the relationships of out-of-school-time mathematics lessons to mathematical literacy in Singapore and Australia. Results of two-level hierarchical linear modelling (HLM) analyses revealed that out-of-school-time enrichment lessons in…

Marginal and Random Intercepts Models for Longitudinal Binary Data with Examples from Criminology

ERIC Educational Resources Information Center

Long, Jeffrey D.; Loeber, Rolf; Farrington, David P.

2009-01-01

Two models for the analysis of longitudinal binary data are discussed: the marginal model and the random intercepts model. In contrast to the linear mixed model (LMM), the two models for binary data are not subsumed under a single hierarchical model. The marginal model provides group-level information whereas the random intercepts model provides…

For Richer, for Poorer: Money as a Topic of Marital Conflict in the Home

ERIC Educational Resources Information Center

Papp, Lauren M.; Cummings, E. Mark; Goeke-Morey, Marcie C.

2009-01-01

Guided by a family stress perspective, we examined the hypothesis that discussing money would be associated with the handling of marital conflict in the home. Analyses were based on dyadic hierarchical linear modeling of 100 husbands' and 100 wives' diary reports of 748 conflict instances. Contrary to findings from previous laboratory-based…

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

ERIC Educational Resources Information Center

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

2011-01-01

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

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

ERIC Educational Resources Information Center

Rumberger, Russell W.; Palardy, Gregory J.

2005-01-01

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

Increasing Equity and Achievement in Fifth Grade Mathematics: The Contribution of Content Exposure

ERIC Educational Resources Information Center

Ottmar, Erin R.; Konold, Timothy R.; Berry, Robert Q.; Grissmer, David W.; Cameron, Claire E.

2013-01-01

This study uses a large nationally representative data set (ECLS-K) of 5,181 students to examine the extent to which exposure to content and instructional practice contributes to mathematics achievement in fifth grade. Using hierarchical linear modeling, results suggest that more exposure to content beyond numbers and operations (i.e., geometry,…

Effect Sizes for Growth-Modeling Analysis for Controlled Clinical Trials in the Same Metric as for Classical Analysis

ERIC Educational Resources Information Center

Feingold, Alan

2009-01-01

The use of growth-modeling analysis (GMA)--including hierarchical linear models, latent growth models, and general estimating equations--to evaluate interventions in psychology, psychiatry, and prevention science has grown rapidly over the last decade. However, an effect size associated with the difference between the trajectories of the…

The Influence of Classroom Disciplinary Climate of Schools on Reading Achievement: A Cross-Country Comparative Study

ERIC Educational Resources Information Center

Ning, Bo; Van Damme, Jan; Van Den Noortgate, Wim; Yang, Xiangdong; Gielen, Sarah

2015-01-01

Despite considerable interest in research and practice in the effect of classroom disciplinary climate of schools on academic achievement, little is known about the generalizability of this effect over countries. Using hierarchical linear analyses, the present study reveals that a better classroom disciplinary climate in a school is significantly…

Bilingual Education in an Aboriginal Context: Examining the Transfer of Language Skills from Inuktitut to English or French

ERIC Educational Resources Information Center

Usborne, Esther; Caouette, Julie; Qumaaluk, Qiallak; Taylor, Donald M.

2009-01-01

Bilingual education is thought to be one of the principal means of simultaneously revitalizing threatened language and preparing students for success in mainstream society. However, little research has examined, in a comprehensive and longitudinal fashion, bilingual programs in Aboriginal contexts. Hierarchical linear modeling was used to conduct…

Bullying Victimization and Student Engagement in Elementary, Middle, and High Schools: Moderating Role of School Climate

ERIC Educational Resources Information Center

Yang, Chunyan; Sharkey, Jill D.; Reed, Lauren A.; Chen, Chun; Dowdy, Erin

2018-01-01

Bullying is the most common form of school violence and is associated with a range of negative outcomes, including traumatic responses. This study used hierarchical linear modeling to examine the multilevel moderating effects of school climate and school level (i.e., elementary, middle, and high schools) on the association between bullying…

Examining the Variability of Mathematics Performance and Its Correlates Using Data from TIMSS '95 and TIMSS '99

ERIC Educational Resources Information Center

O'Dwyer, Laura M.

2005-01-01

International studies in education provide researchers with opportunities to examine how students with both similar and dissimilar formal education systems perform on a single test and provide rich information about the relationships among student outcomes and the factors that affect them. Using hierarchical linear regression techniques and TIMSS…

When Money Really Matters: Tying Resources of Specific Programmatic and Instructional Elements to Student Academic Growth

ERIC Educational Resources Information Center

Goetz, Michael Eric

2012-01-01

This study explores the cost-effectiveness ratios associated with individual tutoring, intensive reading/language arts instruction, and a focus on core subject areas. Using the Early Childhood Longitudinal Study (ECLS-K) database, this study analyzes these programs using a three-level hierarchical linear model (HLM) with a nationally…

Obesity, High-Calorie Food Intake, and Academic Achievement Trends among U.S. School Children

ERIC Educational Resources Information Center

Li, Jian; O'Connell, Ann A.

2012-01-01

The authors investigated children's self-reported high-calorie food intake in Grade 5 and its relationship to trends in obesity status and academic achievement over the first 6 years of school. They used 3-level hierarchical linear models in the large-scale database (the Early Childhood Longitudinal Study--Kindergarten Cohort). Findings indicated…

The Challenge of Separating Effects of Simultaneous Education Projects on Student Achievement

ERIC Educational Resources Information Center

Ma, Xin; Ma, Lingling

2009-01-01

When multiple education projects operate in an overlapping or rear-ended manner, it is always a challenge to separate unique project effects on schooling outcomes. Our analysis represents a first attempt to address this challenge. A three-level hierarchical linear model (HLM) was presented as a general analytical framework to separate program…

Aspirations, Progress and Perceptions of Boys from a Single Sex School Following the Changeover to Coeducation

ERIC Educational Resources Information Center

Yates, Shirley M.

2004-01-01

Career and further education aspirations, educational progress and perceptions of the learning environment were measured annually over three years in primary and secondary boys from a single sex non-government school, following the changeover to coeducation. Hierarchical Linear Modelling analyses revealed the significant role played by the career…

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

ERIC Educational Resources Information Center

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

2008-01-01

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

FRIT characterized hierarchical kernel memory arrangement for multiband palmprint recognition

NASA Astrophysics Data System (ADS)

Kisku, Dakshina R.; Gupta, Phalguni; Sing, Jamuna K.

2015-10-01

In this paper, we present a hierarchical kernel associative memory (H-KAM) based computational model with Finite Ridgelet Transform (FRIT) representation for multispectral palmprint recognition. To characterize a multispectral palmprint image, the Finite Ridgelet Transform is used to achieve a very compact and distinctive representation of linear singularities while it also captures the singularities along lines and edges. The proposed system makes use of Finite Ridgelet Transform to represent multispectral palmprint image and it is then modeled by Kernel Associative Memories. Finally, the recognition scheme is thoroughly tested with a benchmarking multispectral palmprint database CASIA. For recognition purpose a Bayesian classifier is used. The experimental results exhibit robustness of the proposed system under different wavelengths of palm image.

Minimax terminal approach problem in two-level hierarchical nonlinear discrete-time dynamical system

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

Shorikov, A. F., E-mail: afshorikov@mail.ru

We consider a discrete–time dynamical system consisting of three controllable objects. The motions of all objects are given by the corresponding vector nonlinear or linear discrete–time recurrent vector relations, and control system for its has two levels: basic (first or I level) that is dominating and subordinate level (second or II level) and both have different criterions of functioning and united a priori by determined informational and control connections defined in advance. For the dynamical system in question, we propose a mathematical formalization in the form of solving a multistep problem of two-level hierarchical minimax program control over the terminalmore » approach process with incomplete information and give a general scheme for its solving.« less

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

Chen, Chao; Pouransari, Hadi; Rajamanickam, Sivasankaran

We present a parallel hierarchical solver for general sparse linear systems on distributed-memory machines. For large-scale problems, this fully algebraic algorithm is faster and more memory-efficient than sparse direct solvers because it exploits the low-rank structure of fill-in blocks. Depending on the accuracy of low-rank approximations, the hierarchical solver can be used either as a direct solver or as a preconditioner. The parallel algorithm is based on data decomposition and requires only local communication for updating boundary data on every processor. Moreover, the computation-to-communication ratio of the parallel algorithm is approximately the volume-to-surface-area ratio of the subdomain owned by everymore » processor. We also provide various numerical results to demonstrate the versatility and scalability of the parallel algorithm.« less

On the usefulness of 'what' and 'where' pathways in vision.

PubMed

de Haan, Edward H F; Cowey, Alan

2011-10-01

The primate visual brain is classically portrayed as a large number of separate 'maps', each dedicated to the processing of specific visual cues, such as colour, motion or faces and their many features. In order to understand this fractionated architecture, the concept of cortical 'pathways' or 'streams' was introduced. In the currently prevailing view, the different maps are organised hierarchically into two major pathways, one involved in recognition and memory (the ventral stream or 'what' pathway) and the other in the programming of action (the dorsal stream or 'where' pathway). In this review, we question this heuristically influential but potentially misleading linear hierarchical pathway model and argue instead for a 'patchwork' or network model. Copyright © 2011 Elsevier Ltd. All rights reserved.

Highly efficient solar vapour generation via hierarchically nanostructured gels.

PubMed

Zhao, Fei; Zhou, Xingyi; Shi, Ye; Qian, Xin; Alexander, Megan; Zhao, Xinpeng; Mendez, Samantha; Yang, Ronggui; Qu, Liangti; Yu, Guihua

2018-04-02

Solar vapour generation is an efficient way of harvesting solar energy for the purification of polluted or saline water. However, water evaporation suffers from either inefficient utilization of solar energy or relies on complex and expensive light-concentration accessories. Here, we demonstrate a hierarchically nanostructured gel (HNG) based on polyvinyl alcohol (PVA) and polypyrrole (PPy) that serves as an independent solar vapour generator. The converted energy can be utilized in situ to power the vaporization of water contained in the molecular meshes of the PVA network, where water evaporation is facilitated by the skeleton of the hydrogel. A floating HNG sample evaporated water with a record high rate of 3.2 kg m -2  h -1 via 94% solar energy from 1 sun irradiation, and 18-23 litres of water per square metre of HNG was delivered daily when purifying brine water. These values were achievable due to the reduced latent heat of water evaporation in the molecular mesh under natural sunlight.

Highly efficient solar vapour generation via hierarchically nanostructured gels

NASA Astrophysics Data System (ADS)

Zhao, Fei; Zhou, Xingyi; Shi, Ye; Qian, Xin; Alexander, Megan; Zhao, Xinpeng; Mendez, Samantha; Yang, Ronggui; Qu, Liangti; Yu, Guihua

2018-06-01

Solar vapour generation is an efficient way of harvesting solar energy for the purification of polluted or saline water. However, water evaporation suffers from either inefficient utilization of solar energy or relies on complex and expensive light-concentration accessories. Here, we demonstrate a hierarchically nanostructured gel (HNG) based on polyvinyl alcohol (PVA) and polypyrrole (PPy) that serves as an independent solar vapour generator. The converted energy can be utilized in situ to power the vaporization of water contained in the molecular meshes of the PVA network, where water evaporation is facilitated by the skeleton of the hydrogel. A floating HNG sample evaporated water with a record high rate of 3.2 kg m-2 h-1 via 94% solar energy from 1 sun irradiation, and 18-23 litres of water per square metre of HNG was delivered daily when purifying brine water. These values were achievable due to the reduced latent heat of water evaporation in the molecular mesh under natural sunlight.

HECLIB. Volume 2: HECDSS Subroutines Programmer’s Manual

DTIC Science & Technology

1991-05-01

algorithm and hierarchical design for database accesses. This algorithm provides quick access to data sets and an efficient means of adding new data set...Description of How DSS Works DSS version 6 utilizes a modified hash algorithm based upon the pathname to store and retrieve data. This structure allows...balancing disk space and record access times. A variation in this algorithm is for "stable" files. In a stable file, a hash table is not utilized

Longitudinal data analyses using linear mixed models in SPSS: concepts, procedures and illustrations.

PubMed

Shek, Daniel T L; Ma, Cecilia M S

2011-01-05

Although different methods are available for the analyses of longitudinal data, analyses based on generalized linear models (GLM) are criticized as violating the assumption of independence of observations. Alternatively, linear mixed models (LMM) are commonly used to understand changes in human behavior over time. In this paper, the basic concepts surrounding LMM (or hierarchical linear models) are outlined. Although SPSS is a statistical analyses package commonly used by researchers, documentation on LMM procedures in SPSS is not thorough or user friendly. With reference to this limitation, the related procedures for performing analyses based on LMM in SPSS are described. To demonstrate the application of LMM analyses in SPSS, findings based on six waves of data collected in the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes) in Hong Kong are presented.

Longitudinal Data Analyses Using Linear Mixed Models in SPSS: Concepts, Procedures and Illustrations

PubMed Central

Shek, Daniel T. L.; Ma, Cecilia M. S.

2011-01-01

Although different methods are available for the analyses of longitudinal data, analyses based on generalized linear models (GLM) are criticized as violating the assumption of independence of observations. Alternatively, linear mixed models (LMM) are commonly used to understand changes in human behavior over time. In this paper, the basic concepts surrounding LMM (or hierarchical linear models) are outlined. Although SPSS is a statistical analyses package commonly used by researchers, documentation on LMM procedures in SPSS is not thorough or user friendly. With reference to this limitation, the related procedures for performing analyses based on LMM in SPSS are described. To demonstrate the application of LMM analyses in SPSS, findings based on six waves of data collected in the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes) in Hong Kong are presented. PMID:21218263

Hierarchical additive modeling of nonlinear association with spatial correlations--an application to relate alcohol outlet density and neighborhood assault rates.

PubMed

Yu, Qingzhao; Li, Bin; Scribner, Richard Allen

2009-06-30

Previous studies have suggested a link between alcohol outlets and assaults. In this paper, we explore the effects of alcohol availability on assaults at the census tract level over time. In addition, we use a natural experiment to check whether a sudden loss of alcohol outlets is associated with deeper decreasing in assault violence. Several features of the data raise statistical challenges: (1) the association between covariates (for example, the alcohol outlet density of each census tract) and the assault rates may be complex and therefore cannot be described using a linear model without covariates transformation, (2) the covariates may be highly correlated with each other, (3) there are a number of observations that have missing inputs, and (4) there is spatial association in assault rates at the census tract level. We propose a hierarchical additive model, where the nonlinear correlations and the complex interaction effects are modeled using the multiple additive regression trees and the residual spatial association in the assault rates that cannot be explained in the model are smoothed using a conditional autoregressive (CAR) method. We develop a two-stage algorithm that connects the nonparametric trees with CAR to look for important covariates associated with the assault rates, while taking into account the spatial association of assault rates in adjacent census tracts. The proposed method is applied to the Los Angeles assault data (1990-1999). To assess the efficiency of the method, the results are compared with those obtained from a hierarchical linear model. Copyright (c) 2009 John Wiley & Sons, Ltd.

Towards a hierarchical optimization modeling framework for ...

EPA Pesticide Factsheets

Background:Bilevel optimization has been recognized as a 2-player Stackelberg game where players are represented as leaders and followers and each pursue their own set of objectives. Hierarchical optimization problems, which are a generalization of bilevel, are especially difficult because the optimization is nested, meaning that the objectives of one level depend on solutions to the other levels. We introduce a hierarchical optimization framework for spatially targeting multiobjective green infrastructure (GI) incentive policies under uncertainties related to policy budget, compliance, and GI effectiveness. We demonstrate the utility of the framework using a hypothetical urban watershed, where the levels are characterized by multiple levels of policy makers (e.g., local, regional, national) and policy followers (e.g., landowners, communities), and objectives include minimization of policy cost, implementation cost, and risk; reduction of combined sewer overflow (CSO) events; and improvement in environmental benefits such as reduced nutrient run-off and water availability. Conclusions: While computationally expensive, this hierarchical optimization framework explicitly simulates the interaction between multiple levels of policy makers (e.g., local, regional, national) and policy followers (e.g., landowners, communities) and is especially useful for constructing and evaluating environmental and ecological policy. Using the framework with a hypothetical urba

Efficient Parallel Formulations of Hierarchical Methods and Their Applications

NASA Astrophysics Data System (ADS)

Grama, Ananth Y.

1996-01-01

Hierarchical methods such as the Fast Multipole Method (FMM) and Barnes-Hut (BH) are used for rapid evaluation of potential (gravitational, electrostatic) fields in particle systems. They are also used for solving integral equations using boundary element methods. The linear systems arising from these methods are dense and are solved iteratively. Hierarchical methods reduce the complexity of the core matrix-vector product from O(n^2) to O(n log n) and the memory requirement from O(n^2) to O(n). We have developed highly scalable parallel formulations of a hybrid FMM/BH method that are capable of handling arbitrarily irregular distributions. We apply these formulations to astrophysical simulations of Plummer and Gaussian galaxies. We have used our parallel formulations to solve the integral form of the Laplace equation. We show that our parallel hierarchical mat-vecs yield high efficiency and overall performance even on relatively small problems. A problem containing approximately 200K nodes takes under a second to compute on 256 processors and yet yields over 85% efficiency. The efficiency and raw performance is expected to increase for bigger problems. For the 200K node problem, our code delivers about 5 GFLOPS of performance on a 256 processor T3D. This is impressive considering the fact that the problem has floating point divides and roots, and very little locality resulting in poor cache performance. A dense matrix-vector product of the same dimensions would require about 0.5 TeraBytes of memory and about 770 TeraFLOPS of computing speed. Clearly, if the loss in accuracy resulting from the use of hierarchical methods is acceptable, our code yields significant savings in time and memory. We also study the convergence of a GMRES solver built around this mat-vec. We accelerate the convergence of the solver using three preconditioning techniques: diagonal scaling, block-diagonal preconditioning, and inner-outer preconditioning. We study the performance and parallel efficiency of these preconditioned solvers. Using this solver, we solve dense linear systems with hundreds of thousands of unknowns. Solving a 105K unknown problem takes about 10 minutes on a 64 processor T3D. Until very recently, boundary element problems of this magnitude could not even be generated, let alone solved.

Sensory processing and world modeling for an active ranging device

NASA Technical Reports Server (NTRS)

Hong, Tsai-Hong; Wu, Angela Y.

1991-01-01

In this project, we studied world modeling and sensory processing for laser range data. World Model data representation and operation were defined. Sensory processing algorithms for point processing and linear feature detection were designed and implemented. The interface between world modeling and sensory processing in the Servo and Primitive levels was investigated and implemented. In the primitive level, linear features detectors for edges were also implemented, analyzed and compared. The existing world model representations is surveyed. Also presented is the design and implementation of the Y-frame model, a hierarchical world model. The interfaces between the world model module and the sensory processing module are discussed as well as the linear feature detectors that were designed and implemented.

An Instruction Support System for Competency-Based Programs.

ERIC Educational Resources Information Center

Singh, Jane M.; And Others

This report discusses the Pennsylvania State University Instruction Support System (ISS) designed to meet the needs of large classes for competency-based teacher education (CBTE) programs. The ISS seven-step hierarchical developmental procedure is reported to free the instructor for specialized instruction and evaluation by utilizing a…

Markerless human motion tracking using hierarchical multi-swarm cooperative particle swarm optimization.

PubMed

Saini, Sanjay; Zakaria, Nordin; Rambli, Dayang Rohaya Awang; Sulaiman, Suziah

2015-01-01

The high-dimensional search space involved in markerless full-body articulated human motion tracking from multiple-views video sequences has led to a number of solutions based on metaheuristics, the most recent form of which is Particle Swarm Optimization (PSO). However, the classical PSO suffers from premature convergence and it is trapped easily into local optima, significantly affecting the tracking accuracy. To overcome these drawbacks, we have developed a method for the problem based on Hierarchical Multi-Swarm Cooperative Particle Swarm Optimization (H-MCPSO). The tracking problem is formulated as a non-linear 34-dimensional function optimization problem where the fitness function quantifies the difference between the observed image and a projection of the model configuration. Both the silhouette and edge likelihoods are used in the fitness function. Experiments using Brown and HumanEva-II dataset demonstrated that H-MCPSO performance is better than two leading alternative approaches-Annealed Particle Filter (APF) and Hierarchical Particle Swarm Optimization (HPSO). Further, the proposed tracking method is capable of automatic initialization and self-recovery from temporary tracking failures. Comprehensive experimental results are presented to support the claims.

Discriminative Hierarchical K-Means Tree for Large-Scale Image Classification.

PubMed

Chen, Shizhi; Yang, Xiaodong; Tian, Yingli

2015-09-01

A key challenge in large-scale image classification is how to achieve efficiency in terms of both computation and memory without compromising classification accuracy. The learning-based classifiers achieve the state-of-the-art accuracies, but have been criticized for the computational complexity that grows linearly with the number of classes. The nonparametric nearest neighbor (NN)-based classifiers naturally handle large numbers of categories, but incur prohibitively expensive computation and memory costs. In this brief, we present a novel classification scheme, i.e., discriminative hierarchical K-means tree (D-HKTree), which combines the advantages of both learning-based and NN-based classifiers. The complexity of the D-HKTree only grows sublinearly with the number of categories, which is much better than the recent hierarchical support vector machines-based methods. The memory requirement is the order of magnitude less than the recent Naïve Bayesian NN-based approaches. The proposed D-HKTree classification scheme is evaluated on several challenging benchmark databases and achieves the state-of-the-art accuracies, while with significantly lower computation cost and memory requirement.

Chassis integrated control for active suspension, active front steering and direct yaw moment systems using hierarchical strategy

NASA Astrophysics Data System (ADS)

Zhao, Jing; Wong, Pak Kin; Ma, Xinbo; Xie, Zhengchao

2017-01-01

This paper proposes a novel integrated controller with three-layer hierarchical structure to coordinate the interactions among active suspension system (ASS), active front steering (AFS) and direct yaw moment control (DYC). First of all, a 14-degree-of-freedom nonlinear vehicle dynamic model is constructed. Then, an upper layer is designed to calculate the total corrected moment for ASS and intermediate layer based on linear moment distribution. By considering the working regions of the AFS and DYC, the intermediate layer is functionalised to determine the trigger signal for the lower layer with corresponding weights. The lower layer is utilised to separately trace the desired value of each local controller and achieve the local control objectives of each subsystem. Simulation results show that the proposed three-layer hierarchical structure is effective in handling the working region of the AFS and DYC, while the quasi-experimental result shows that the proposed integrated controller is able to improve the lateral and vertical dynamics of the vehicle effectively as compared with a conventional electronic stability controller.

Efficient Record Linkage Algorithms Using Complete Linkage Clustering.

PubMed

Mamun, Abdullah-Al; Aseltine, Robert; Rajasekaran, Sanguthevar

2016-01-01

Data from different agencies share data of the same individuals. Linking these datasets to identify all the records belonging to the same individuals is a crucial and challenging problem, especially given the large volumes of data. A large number of available algorithms for record linkage are prone to either time inefficiency or low-accuracy in finding matches and non-matches among the records. In this paper we propose efficient as well as reliable sequential and parallel algorithms for the record linkage problem employing hierarchical clustering methods. We employ complete linkage hierarchical clustering algorithms to address this problem. In addition to hierarchical clustering, we also use two other techniques: elimination of duplicate records and blocking. Our algorithms use sorting as a sub-routine to identify identical copies of records. We have tested our algorithms on datasets with millions of synthetic records. Experimental results show that our algorithms achieve nearly 100% accuracy. Parallel implementations achieve almost linear speedups. Time complexities of these algorithms do not exceed those of previous best-known algorithms. Our proposed algorithms outperform previous best-known algorithms in terms of accuracy consuming reasonable run times.

Efficient Record Linkage Algorithms Using Complete Linkage Clustering

PubMed Central

Mamun, Abdullah-Al; Aseltine, Robert; Rajasekaran, Sanguthevar

2016-01-01

Data from different agencies share data of the same individuals. Linking these datasets to identify all the records belonging to the same individuals is a crucial and challenging problem, especially given the large volumes of data. A large number of available algorithms for record linkage are prone to either time inefficiency or low-accuracy in finding matches and non-matches among the records. In this paper we propose efficient as well as reliable sequential and parallel algorithms for the record linkage problem employing hierarchical clustering methods. We employ complete linkage hierarchical clustering algorithms to address this problem. In addition to hierarchical clustering, we also use two other techniques: elimination of duplicate records and blocking. Our algorithms use sorting as a sub-routine to identify identical copies of records. We have tested our algorithms on datasets with millions of synthetic records. Experimental results show that our algorithms achieve nearly 100% accuracy. Parallel implementations achieve almost linear speedups. Time complexities of these algorithms do not exceed those of previous best-known algorithms. Our proposed algorithms outperform previous best-known algorithms in terms of accuracy consuming reasonable run times. PMID:27124604

Synthesis of Pt@TiO2@CNTs Hierarchical Structure Catalyst by Atomic Layer Deposition and Their Photocatalytic and Photoelectrochemical Activity.

PubMed

Liao, Shih-Yun; Yang, Ya-Chu; Huang, Sheng-Hsin; Gan, Jon-Yiew

2017-04-29

Pt@TiO2@CNTs hierarchical structures were prepared by first functionalizing carbon nanotubes (CNTs) with nitric acid at 140 °C. Coating of TiO2 particles on the CNTs at 300 °C was then conducted by atomic layer deposition (ALD). After the TiO2@CNTs structure was fabricated, Pt particles were deposited on the TiO2 surface as co-catalyst by plasma-enhanced ALD. The saturated deposition rates of TiO2 on a-CNTs were 1.5 Å/cycle and 0.4 Å/cycle for substrate-enhanced process and linear process, respectively. The saturated deposition rate of Pt on TiO2 was 0.39 Å/cycle. The photocatalytic activities of Pt@TiO2@CNTs hierarchical structures were higher than those without Pt co-catalyst. The particle size of Pt on TiO2@CNTs was a key factor to determine the efficiency of methylene blue (MB) degradation. The Pt@TiO2@CNTs of 2.41 ± 0.27 nm exhibited the best efficiency of MB degradation.

Highly conductive ribbons prepared by stick-slip assembly of organosoluble gold nanoparticles.

PubMed

Lawrence, Jimmy; Pham, Jonathan T; Lee, Dong Yun; Liu, Yujie; Crosby, Alfred J; Emrick, Todd

2014-02-25

Precisely positioning and assembling nanoparticles (NPs) into hierarchical nanostructures is opening opportunities in a wide variety of applications. Many techniques employed to produce hierarchical micrometer and nanoscale structures are limited by complex fabrication of templates and difficulties with scalability. Here we describe the fabrication and characterization of conductive nanoparticle ribbons prepared from surfactant-free organosoluble gold nanoparticles (Au NPs). We used a flow-coating technique in a controlled, stick-slip assembly to regulate the deposition of Au NPs into densely packed, multilayered structures. This affords centimeter-scale long, high-resolution Au NP ribbons with precise periodic spacing in a rapid manner, up to 2 orders-of-magnitude finer and faster than previously reported methods. These Au NP ribbons exhibit linear ohmic response, with conductivity that varies by changing the binding headgroup of the ligands. Controlling NP percolation during sintering (e.g., by adding polymer to retard rapid NP coalescence) enables the formation of highly conductive ribbons, similar to thermally sintered conductive adhesives. Hierarchical, conductive Au NP ribbons represent a promising platform to enable opportunities in sensing, optoelectronics, and electromechanical devices.

Extreme close approaches in hierarchical triple systems with comparable masses

NASA Astrophysics Data System (ADS)

Haim, Niv; Katz, Boaz

2018-06-01

We study close approaches in hierarchical triple systems with comparable masses using full N-body simulations, motivated by a recent model for type Ia supernovae involving direct collisions of white dwarfs (WDs). For stable hierarchical systems where the inner binary components have equal masses, we show that the ability of the inner binary to achieve very close approaches, where the separation between the components of the inner binary reaches values which are orders of magnitude smaller than the semi-major axis, can be analytically predicted from initial conditions. The rate of close approaches is found to be roughly linear with the mass of the tertiary. The rate increases in systems with unequal inner binaries by a marginal factor of ≲ 2 for mass ratios 0.5 ≤ m1/m2 ≤ 1 relevant for the inner white-dwarf binaries. For an average tertiary mass of ˜0.3M⊙ which is representative of typical M-dwarfs, the chance for clean collisions is ˜1% setting challenging constraints on the collisional model for type Ia's.

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.

Synthesis of Pt@TiO2@CNTs Hierarchical Structure Catalyst by Atomic Layer Deposition and Their Photocatalytic and Photoelectrochemical Activity

PubMed Central

Liao, Shih-Yun; Yang, Ya-Chu; Huang, Sheng-Hsin; Gan, Jon-Yiew

2017-01-01

Pt@TiO2@CNTs hierarchical structures were prepared by first functionalizing carbon nanotubes (CNTs) with nitric acid at 140 °C. Coating of TiO2 particles on the CNTs at 300 °C was then conducted by atomic layer deposition (ALD). After the TiO2@CNTs structure was fabricated, Pt particles were deposited on the TiO2 surface as co-catalyst by plasma-enhanced ALD. The saturated deposition rates of TiO2 on a-CNTs were 1.5 Å/cycle and 0.4 Å/cycle for substrate-enhanced process and linear process, respectively. The saturated deposition rate of Pt on TiO2 was 0.39 Å/cycle. The photocatalytic activities of Pt@TiO2@CNTs hierarchical structures were higher than those without Pt co-catalyst. The particle size of Pt on TiO2@CNTs was a key factor to determine the efficiency of methylene blue (MB) degradation. The Pt@TiO2@CNTs of 2.41 ± 0.27 nm exhibited the best efficiency of MB degradation. PMID:28468248

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

ERIC Educational Resources Information Center

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

2014-01-01

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

Revisiting the Impact of NCLB High-Stakes School Accountability, Capacity, and Resources: State NAEP 1990-2009 Reading and Math Achievement Gaps and Trends

ERIC Educational Resources Information Center

Lee, Jaekyung; Reeves, Todd

2012-01-01

This study examines the impact of high-stakes school accountability, capacity, and resources under NCLB on reading and math achievement outcomes through comparative interrupted time-series analyses of 1990-2009 NAEP state assessment data. Through hierarchical linear modeling latent variable regression with inverse probability of treatment…

The Relationship of School-Based Parental Involvement with Student Achievement: A Comparison of Principal and Parent Survey Reports from PISA 2012

ERIC Educational Resources Information Center

Sebastian, James; Moon, Jeong-Mi; Cunningham, Matt

2017-01-01

This paper explores parental involvement using principal and parent survey reports to examine whether parents' involvement in their children's schools predicts academic achievement. Survey data from principals and parents of seven countries from the PISA 2012 database and hierarchical linear modelling were used to analyse between- and within-…

Plant functional group responses to fire frequency and tree canopy cover gradients in oak savannas and woodlands.

Treesearch

D.W. Peterson; P.B. Reich; K.J. Wrage

2007-01-01

We measured plant functional group cover and tree canopy cover on permanent plots within a long-term prescribed fire frequency experiment and used hierarchical linear modeling to assess plant functional group responses to fire frequency and tree canopy cover. Understory woody plant cover was highest in unburned woodlands and was negatively correlated with fire...

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

ERIC Educational Resources Information Center

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

2012-01-01

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

Using HLM to Explore the Effects of Perceptions of Learning Environments and Assessments on Students' Test Performance

ERIC Educational Resources Information Center

Chu, Man-Wai; Babenko, Oksana; Cui, Ying; Leighton, Jacqueline P.

2014-01-01

The study examines the role that perceptions or impressions of learning environments and assessments play in students' performance on a large-scale standardized test. Hierarchical linear modeling (HLM) was used to test aspects of the Learning Errors and Formative Feedback model to determine how much variation in students' performance was explained…

Effect of School and Home Factors on Learning Outcomes at Elementary School Level: A Hierarchical Linear Model

ERIC Educational Resources Information Center

Singh, Jai

2016-01-01

India is a democratic, socialistic republic that is committed to providing high quality elementary education to all children. This research paper examines and analyses the effects of school, teacher and home factors on learning outcomes in elementary schools in the urban slum areas of Varanasi city and assesses the learning outcomes of students of…

Latino Adolescents' Civic Development in the United States: Research Results from the IEA Civic Education Study

ERIC Educational Resources Information Center

Torney-Purta, Judith; Barber, Carolyn H.; Wilkenfeld, Britt

2007-01-01

Many studies have reported gaps between Latino and non-Latino adolescents in academic and political outcomes. The current study presents possible explanations for such gaps, both at the individual and school level. Hierarchical linear modeling is employed to examine data from 2,811 American ninth graders (approximately 14 years of age) who had…

Longitudinal Change in Happiness during Aging: The Predictive Role of Positive Expectancies

ERIC Educational Resources Information Center

Holahan, Carole K.; Holahan, Charles J.; Velasquez, Katherine E.; North, Rebecca J.

2008-01-01

This study employed hierarchical linear modeling to document the time course of happiness across 20 years from average ages of 66 to 86 among 717 members of the Terman Study of the Gifted. In addition, the study examined the role of positive expectancies about aging, assessed at an average age of 61, in enhancing happiness in aging. The results…

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

ERIC Educational Resources Information Center

Leos-Urbel, Jacob

2015-01-01

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

Helping Struggling Adolescent Readers: Is Implementation of Different Components of Scholastic's READ 180 Associated with Differences in Student Achievement Gains?

ERIC Educational Resources Information Center

Coffey, Debra J.

2013-01-01

This dissertation uses data from the evaluation of a Striving Readers project to examine the associations between levels of implementation of different components of Scholastic's "READ 180" and student achievement as measured on the Iowa Test of Basic Skills (ITBS) reading assessment. The approach was hierarchical linear modeling using…

Effects of Inquiry-Based Science Instruction on Science Achievement and Interest in Science: Evidence from Qatar

ERIC Educational Resources Information Center

Areepattamannil, Shaljan

2012-01-01

The author sought to investigate the effects of inquiry-based science instruction on science achievement and interest in science of 5,120 adolescents from 85 schools in Qatar. Results of hierarchical linear modeling analyses revealed the substantial positive effects of science teaching and learning with a focus on model or applications and…

Associations of Home and Classroom Environments with Head Start Children's Code-Related and Oral Language Skills

ERIC Educational Resources Information Center

Han, Jisu; Schlieber, Marisa; Gregory, Bradley

2017-01-01

This study used data from the Head Start Family and Child Experiences Survey (FACES) 2009 4-year-old cohort to examine associations among family characteristics, home and classroom environments, and the emergent literacy skills of Head Start children. Results from hierarchical linear models suggest that both family and classroom contexts play a…

Effects of Prior Knowledge and Concept-Map Structure on Disorientation, Cognitive Load, and Learning

ERIC Educational Resources Information Center

Amadieu, Franck; van Gog, Tamara; Paas, Fred; Tricot, Andre; Marine, Claudette

2009-01-01

This study explored the effects of prior knowledge (high vs. low; HPK and LPK) and concept-map structure (hierarchical vs. network; HS and NS) on disorientation, cognitive load, and learning from non-linear documents on "the infection process of a retrograde virus (HIV)". Participants in the study were 24 adults. Overall subjective ratings of…

Early Reading Achievement of Children in Immigrant Families: Is There an Immigrant Paradox?

ERIC Educational Resources Information Center

Palacios, Natalia; Guttmanova, Katarina; Chase-Lansdale, P. Lindsay

2008-01-01

This article examines whether longitudinal reading trajectories vary by the generational status of immigrant children as they begin formal schooling through the 3rd grade. The results of the hierarchical linear model indicated that 1st and 2nd generation children (i.e., those born in a foreign country and those born in the United States to…

Educational Leadership as Best Practice in Highly Effective Schools in the Autonomous Region of the Basque County (Spain)

ERIC Educational Resources Information Center

Intxausti, Nahia; Joaristi, Luis; Lizasoain, Luis

2016-01-01

This study presents part of a research project currently underway which aims to characterise the best practices of highly effective schools in the Autonomous Region of the Basque Country (Spain). Multilevel statistical modelling and hierarchical linear models were used to select 32 highly effective schools, with highly effective being taken to…

School Effects on Educational Achievement in Mathematics and Science: 1985-86. National Assessment of Educational Progress. Research and Development Report.

ERIC Educational Resources Information Center

Arnold, Carolyn L.; Kaufman, Phillip D.

This report examines the effects of both student and school characteristics on mathematics and science achievement levels in the third, seventh, and eleventh grades using data from the 1985-86 National Assessment of Educational Progress (NAEP). Analyses feature hierarchical linear models (HLM), a regression-like statistical technique that…

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

ERIC Educational Resources Information Center

Kanyongo, Gibbs Y.; Ayieko, Rachel

2017-01-01

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

Unpacking the Gender Gap in Postsecondary Participation among African Americans and Caucasians Using Hierarchical Generalized Linear Modeling

ERIC Educational Resources Information Center

Tekleselassie, Abebayehu; Mallery, Coretta; Choi, Jaehwa

2013-01-01

National reports recognize a growing gender gap in postsecondary enrollment as a major challenge impacting the lives of young men, particularly African Americans. Previous gender and race specific research is largely inconclusive. It is, for example, unclear from previous research how persistent the gender gap is across various school contexts,…

Interaction of 5-HTTLPR and Idiographic Stressors Predicts Prospective Depressive Symptoms Specifically among Youth in a Multiwave Design

ERIC Educational Resources Information Center

Hankin, Benjamin L.; Jenness, Jessica; Abela, John R. Z.; Smolen, Andrew

2011-01-01

5-HTTLPR, episodic stressors, depressive and anxious symptoms were assessed prospectively (child and parent report) every 3 months over 1 year (5 waves of data) among community youth ages 9 to 15 (n = 220). Lagged hierarchical linear modeling analyses showed 5-HTTLPR interacted with idiographic stressors (increases relative to the child's own…

Contextual Differential Item Functioning: Examining the Validity of Teaching Self-Efficacy Instruments Using Hierarchical Generalized Linear Modeling

ERIC Educational Resources Information Center

Zhao, Jing

2012-01-01

The purpose of the study is to further investigate the validity of instruments used for collecting preservice teachers' perceptions of self-efficacy adapting the three-level IRT model described in Cheong's study (2006). The focus of the present study is to investigate whether the polytomously-scored items on the preservice teachers' self-efficacy…

Seeking Effectiveness and Equity in a Large College Chemistry Course: An HLM Investigation of Peer-Led Guided Inquiry

ERIC Educational Resources Information Center

Lewis, Scott E.; Lewis, Jennifer E.

2008-01-01

This study employed hierarchical linear models (HLM) to investigate Peer-Led Guided Inquiry (PLGI), a teaching practice combining cooperative learning and inquiry and tailored for a large class. Ultimately, the study provided an example of the effective introduction of a reform pedagogical approach in a large class setting. In the narrative, the…

The Development of Science Achievement in Middle and High School: Individual Differences and School Effects.

ERIC Educational Resources Information Center

Ma, Xin; Wilkins, Jessie L. M.

2002-01-01

Used hierarchical linear models with data from the Longitudinal Study of American Youth to model the growth of student science achievement in biology, physical science, and environmental science during middle and high school. Growth was quadratic across all areas, with rapid growth at the beginning of middle school and slow growth at the ending…

Student Engagement in Two Countries: A Comparative Study Using National Survey of Student Engagement (NSSE) Data

ERIC Educational Resources Information Center

Kandiko, C. B.

2008-01-01

To compare college and university student engagement in two countries with different responses to global forces, Canada and the United States (US), a series of hierarchical linear regression (HLM) models were developed to analyse data from the 2006 administration of the National Survey of Student Engagement (NSSE). Overall, students in the U.S.…

The Relationship among School Safety, School Liking, and Students' Self-Esteem: Based on a Multilevel Mediation Model

ERIC Educational Resources Information Center

Zhang, Xinghui; Xuan, Xin; Chen, Fumei; Zhang, Cai; Luo, Yuhan; Wang, Yun

2016-01-01

Background: Perceptions of school safety have an important effect on students' development. Based on the model of "context-process-outcomes," we examined school safety as a context variable to explore how school safety at the school level affected students' self-esteem. Methods: We used hierarchical linear modeling to examine the link…

What Motivates High School Students to Want to Be Teachers? The Role of Salary, Working Conditions, and Societal Evaluations about Occupations in a Comparative Perspective

ERIC Educational Resources Information Center

Han, Seong Won; Borgonovi, Francesca; Guerriero, Sonia

2018-01-01

This study examines between-country differences in the degree to which teachers' working conditions, salaries, and societal evaluations about desirable job characteristics are associated with students' teaching career expectations. Three-level hierarchical generalized linear models are employed to analyze cross-national data from the Programme for…

Peer Assessment in the Digital Age: A Meta-Analysis Comparing Peer and Teacher Ratings

ERIC Educational Resources Information Center

Li, Hongli; Xiong, Yao; Zang, Xiaojiao; Kornhaber, Mindy L.; Lyu, Youngsun; Chung, Kyung Sun; Suen, Hoi K.

2016-01-01

Given the wide use of peer assessment, especially in higher education, the relative accuracy of peer ratings compared to teacher ratings is a major concern for both educators and researchers. This concern has grown with the increase of peer assessment in digital platforms. In this meta-analysis, using a variance-known hierarchical linear modelling…

The Influences of Inductive Instruction and Resources on Students' Attitudes toward Reading: Evidence from PISA 2009

ERIC Educational Resources Information Center

Jhang, Fang-Hua

2014-01-01

The declining trend in the positive reading attitude of students' has concerned scholars. This paper aims to apply a 3-level hierarchical linear model to analyse how inductive instruction and resources influence both students' positive and negative attitudes towards reading. Approximately 470,000 15-year-old students, and their school principals,…

Revisiting Fixed- and Random-Effects Models: Some Considerations for Policy-Relevant Education Research

ERIC Educational Resources Information Center

Clarke, Paul; Crawford, Claire; Steele, Fiona; Vignoles, Anna

2015-01-01

The use of fixed (FE) and random effects (RE) in two-level hierarchical linear regression is discussed in the context of education research. We compare the robustness of FE models with the modelling flexibility and potential efficiency of those from RE models. We argue that the two should be seen as complementary approaches. We then compare both…

Applying an Integrative Framework of Executive Function to Preschoolers With Specific Language Impairment.

PubMed

Kapa, Leah L; Plante, Elena; Doubleday, Kevin

2017-08-16

The first goal of this research was to compare verbal and nonverbal executive function abilities between preschoolers with and without specific language impairment (SLI). The second goal was to assess the group differences on 4 executive function components in order to determine if the components may be hierarchically related as suggested within a developmental integrative framework of executive function. This study included 26 4- and 5-year-olds diagnosed with SLI and 26 typically developing age- and sex-matched peers. Participants were tested on verbal and nonverbal measures of sustained selective attention, working memory, inhibition, and shifting. The SLI group performed worse compared with typically developing children on both verbal and nonverbal measures of sustained selective attention and working memory, the verbal inhibition task, and the nonverbal shifting task. Comparisons of standardized group differences between executive function measures revealed a linear increase with the following order: working memory, inhibition, shifting, and sustained selective attention. The pattern of results suggests that preschoolers with SLI have deficits in executive functioning compared with typical peers, and deficits are not limited to verbal tasks. A significant linear relationship between group differences across executive function components supports the possibility of a hierarchical relationship between executive function skills.

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.

Applying Bayesian Modeling and Receiver Operating Characteristic Methodologies for Test Utility Analysis

ERIC Educational Resources Information Center

Wang, Qiu; Diemer, Matthew A.; Maier, Kimberly S.

2013-01-01

This study integrated Bayesian hierarchical modeling and receiver operating characteristic analysis (BROCA) to evaluate how interest strength (IS) and interest differentiation (ID) predicted low–socioeconomic status (SES) youth's interest-major congruence (IMC). Using large-scale Kuder Career Search online-assessment data, this study fit three…

Fuzzy coordinator in control problems

NASA Technical Reports Server (NTRS)

Rueda, A.; Pedrycz, W.

1992-01-01

In this paper a hierarchical control structure using a fuzzy system for coordination of the control actions is studied. The architecture involves two levels of control: a coordination level and an execution level. Numerical experiments will be utilized to illustrate the behavior of the controller when it is applied to a nonlinear plant.

A Framework for Teaching Social and Environmental Sustainability to Undergraduate Business Majors

ERIC Educational Resources Information Center

Brumagim, Alan L.; Cann, Cynthia W.

2012-01-01

The authors outline an undergraduate exercise to help students more fully understand the environmental and social justice aspects of business sustainability activities. A simple hierarchical framework, based on Maslow's (1943) work, was utilized to help the students understand, analyze, and judge the vast amount of corporate sustainability…

Hierarchical Clustering: A Bibliography. Technical Report No. 1.

ERIC Educational Resources Information Center

Farrell, William T.

"Classification: Purposes, Principles, Progress, Prospects" by Robert R. Sokal is reprinted in this document. It summarizes the principles of classification and cluster analysis in a manner which is of specific value to the Marine Corps Office of Manpower Utilization. Following the article is a 184 item bibliography on cluster analysis…

Job Satisfaction, School Rule Enforcement, and Teacher Victimization

ERIC Educational Resources Information Center

Kapa, Ryan; Gimbert, Belinda

2018-01-01

Job satisfaction is an essential component of teacher motivation, performance, and retention. Teacher job satisfaction is primarily affected by workplace conditions. This paper analyzes data from over 37,000 public school teachers from the 2011--2012 Schools and Staffing Survey. Hierarchical ordinal logistic regression was utilized to analyze…

The Status of the School Public Relations Practitioner: A Statewide Exploration.

ERIC Educational Resources Information Center

Zoch, Lynn M.; Patterson, Beth S.; Olson, Deborah L.

1997-01-01

Studies public relations practitioners in school districts in South Carolina. Utilizes survey research to investigate several questions relating to public relations role enactment, hierarchical level of the public relations function, salary, job satisfaction, and encroachment into public relations. Finds that practitioners fulfill both the manager…

Structural and Organisational Features of Sensorimotor Intelligence among Retarded Infants and Toddlers.

ERIC Educational Resources Information Center

Dunst, C. J.; And Others

1981-01-01

The structural features of sensorimotor intelligence were assessed among three groups of retarded infants and toddlers. Hierarchical cluster analysis (HCA) was performed on two measures of relationship (stage congruence and intercorrelations). The potential utility of HCA for studying Piaget's "structure d'ensemble" stage criteria is…

United States Medical Licensing Examination and American Board of Pediatrics Certification Examination Results: Does the Residency Program Contribute to Trainee Achievement.

PubMed

Welch, Thomas R; Olson, Brad G; Nelsen, Elizabeth; Beck Dallaghan, Gary L; Kennedy, Gloria A; Botash, Ann

2017-09-01

To determine whether training site or prior examinee performance on the US Medical Licensing Examination (USMLE) step 1 and step 2 might predict pass rates on the American Board of Pediatrics (ABP) certifying examination. Data from graduates of pediatric residency programs completing the ABP certifying examination between 2009 and 2013 were obtained. For each, results of the initial ABP certifying examination were obtained, as well as results on National Board of Medical Examiners (NBME) step 1 and step 2 examinations. Hierarchical linear modeling was used to nest first-time ABP results within training programs to isolate program contribution to ABP results while controlling for USMLE step 1 and step 2 scores. Stepwise linear regression was then used to determine which of these examinations was a better predictor of ABP results. A total of 1110 graduates of 15 programs had complete testing results and were subject to analysis. Mean ABP scores for these programs ranged from 186.13 to 214.32. The hierarchical linear model suggested that the interaction of step 1 and 2 scores predicted ABP performance (F[1,1007.70] = 6.44, P = .011). By conducting a multilevel model by training program, both USMLE step examinations predicted first-time ABP results (b = .002, t = 2.54, P = .011). Linear regression analyses indicated that step 2 results were a better predictor of ABP performance than step 1 or a combination of the two USMLE scores. Performance on the USMLE examinations, especially step 2, predicts performance on the ABP certifying examination. The contribution of training site to ABP performance was statistically significant, though contributed modestly to the effect compared with prior USMLE scores. Copyright © 2017 Elsevier Inc. All rights reserved.

Ecoregions of the conterminous United States: evolution of a hierarchical spatial framework

USGS Publications Warehouse

Omernik, James M.; Griffith, Glenn E.

2014-01-01

A map of ecological regions of the conterminous United States, first published in 1987, has been greatly refined and expanded into a hierarchical spatial framework in response to user needs, particularly by state resource management agencies. In collaboration with scientists and resource managers from numerous agencies and institutions in the United States, Mexico, and Canada, the framework has been expanded to cover North America, and the original ecoregions (now termed Level III) have been refined, subdivided, and aggregated to identify coarser as well as more detailed spatial units. The most generalized units (Level I) define 10 ecoregions in the conterminous U.S., while the finest-scale units (Level IV) identify 967 ecoregions. In this paper, we explain the logic underpinning the approach, discuss the evolution of the regional mapping process, and provide examples of how the ecoregions were distinguished at each hierarchical level. The variety of applications of the ecoregion framework illustrates its utility in resource assessment and management.

Ecoregions of the Conterminous United States: Evolution of a Hierarchical Spatial Framework

NASA Astrophysics Data System (ADS)

Omernik, James M.; Griffith, Glenn E.

2014-12-01

A map of ecological regions of the conterminous United States, first published in 1987, has been greatly refined and expanded into a hierarchical spatial framework in response to user needs, particularly by state resource management agencies. In collaboration with scientists and resource managers from numerous agencies and institutions in the United States, Mexico, and Canada, the framework has been expanded to cover North America, and the original ecoregions (now termed Level III) have been refined, subdivided, and aggregated to identify coarser as well as more detailed spatial units. The most generalized units (Level I) define 10 ecoregions in the conterminous U.S., while the finest-scale units (Level IV) identify 967 ecoregions. In this paper, we explain the logic underpinning the approach, discuss the evolution of the regional mapping process, and provide examples of how the ecoregions were distinguished at each hierarchical level. The variety of applications of the ecoregion framework illustrates its utility in resource assessment and management.

Hierarchically Porous Graphitic Carbon with Simultaneously High Surface Area and Colossal Pore Volume Engineered via Ice Templating

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

Estevez, Luis; Prabhakaran, Venkateshkumar; Garcia, Adam L.

Developing hierarchical porous carbon (HPC) materials with competing textural characteristics such as surface area and pore volume in one material is difficult to accomplish—particulalry for an atomically ordered (graphitic) carbon. Herein we describe a synthesis strategy to engineer tunable hierarchically porous carbon (HPC) materials across micro- meso- and macroporous length scales, allowing the fabrication of a graphitic HPC with both very high surface area (> 2500 m2/g) and pore volume (>10 cm3/g), the combination of which has not been seen previously. The mesopore volume alone for these materials is up to 7.91 cm3/g, the highest ever reported. The unique materialmore » was explored for use as a supercapaictor electrode and for oil adsorption; two applications that require textural properties that are typicaly exclusive to one another. This design scheme for HPCs can be utilized in broad applications, including electrochemical systems such as batteries and supercapacitors, sorbents, and catalyst supports.« less

A neural network with modular hierarchical learning

NASA Technical Reports Server (NTRS)

Baldi, Pierre F. (Inventor); Toomarian, Nikzad (Inventor)

1994-01-01

This invention provides a new hierarchical approach for supervised neural learning of time dependent trajectories. The modular hierarchical methodology leads to architectures which are more structured than fully interconnected networks. The networks utilize a general feedforward flow of information and sparse recurrent connections to achieve dynamic effects. The advantages include the sparsity of units and connections, the modular organization. A further advantage is that the learning is much more circumscribed learning than in fully interconnected systems. The present invention is embodied by a neural network including a plurality of neural modules each having a pre-established performance capability wherein each neural module has an output outputting present results of the performance capability and an input for changing the present results of the performance capabilitiy. For pattern recognition applications, the performance capability may be an oscillation capability producing a repeating wave pattern as the present results. In the preferred embodiment, each of the plurality of neural modules includes a pre-established capability portion and a performance adjustment portion connected to control the pre-established capability portion.

A hierarchical exact accelerated stochastic simulation algorithm

NASA Astrophysics Data System (ADS)

Orendorff, David; Mjolsness, Eric

2012-12-01

A new algorithm, "HiER-leap" (hierarchical exact reaction-leaping), is derived which improves on the computational properties of the ER-leap algorithm for exact accelerated simulation of stochastic chemical kinetics. Unlike ER-leap, HiER-leap utilizes a hierarchical or divide-and-conquer organization of reaction channels into tightly coupled "blocks" and is thereby able to speed up systems with many reaction channels. Like ER-leap, HiER-leap is based on the use of upper and lower bounds on the reaction propensities to define a rejection sampling algorithm with inexpensive early rejection and acceptance steps. But in HiER-leap, large portions of intra-block sampling may be done in parallel. An accept/reject step is used to synchronize across blocks. This method scales well when many reaction channels are present and has desirable asymptotic properties. The algorithm is exact, parallelizable and achieves a significant speedup over the stochastic simulation algorithm and ER-leap on certain problems. This algorithm offers a potentially important step towards efficient in silico modeling of entire organisms.

Near-Infrared Trigged Stimulus-Responsive Photonic Crystals with Hierarchical Structures.

PubMed

Lu, Tao; Pan, Hui; Ma, Jun; Li, Yao; Zhu, Shenmin; Zhang, Di

2017-10-04

Stimuli-responsive photonic crystals (PCs) trigged by light would provide a novel intuitive and quantitative method for noninvasive detection. Inspired by the flame-detecting aptitude of fire beetles and the hierarchical photonic structures of butterfly wings, we herein developed near-infrared stimuli-responsive PCs through coupling photothermal Fe 3 O 4 nanoparticles with thermoresponsive poly(N-isopropylacrylamide) (PNIPAM), with hierarchical photonic structured butterfly wing scales as the template. The nanoparticles within 10 s transferred near-infrared radiation into heat that triggered the phase transition of PNIPAM; this almost immediately posed an anticipated effect on the PNIPAM refractive index and resulted in a composite spectrum change of ∼26 nm, leading to the direct visual readout. It is noteworthy that the whole process is durable and stable mainly owing to the chemical bonding formed between PNIPAM and the biotemplate. We envision that this biologically inspired approach could be utilized in a broad range of applications and would have a great impact on various monitoring processes and medical sensing.

dendextend: an R package for visualizing, adjusting and comparing trees of hierarchical clustering

PubMed Central

2015-01-01

Summary: dendextend is an R package for creating and comparing visually appealing tree diagrams. dendextend provides utility functions for manipulating dendrogram objects (their color, shape and content) as well as several advanced methods for comparing trees to one another (both statistically and visually). As such, dendextend offers a flexible framework for enhancing R's rich ecosystem of packages for performing hierarchical clustering of items. Availability and implementation: The dendextend R package (including detailed introductory vignettes) is available under the GPL-2 Open Source license and is freely available to download from CRAN at: (http://cran.r-project.org/package=dendextend) Contact: Tal.Galili@math.tau.ac.il PMID:26209431

Aesthetic perception of visual textures: a holistic exploration using texture analysis, psychological experiment, and perception modeling.

PubMed

Liu, Jianli; Lughofer, Edwin; Zeng, Xianyi

2015-01-01

Modeling human aesthetic perception of visual textures is important and valuable in numerous industrial domains, such as product design, architectural design, and decoration. Based on results from a semantic differential rating experiment, we modeled the relationship between low-level basic texture features and aesthetic properties involved in human aesthetic texture perception. First, we compute basic texture features from textural images using four classical methods. These features are neutral, objective, and independent of the socio-cultural context of the visual textures. Then, we conduct a semantic differential rating experiment to collect from evaluators their aesthetic perceptions of selected textural stimuli. In semantic differential rating experiment, eights pairs of aesthetic properties are chosen, which are strongly related to the socio-cultural context of the selected textures and to human emotions. They are easily understood and connected to everyday life. We propose a hierarchical feed-forward layer model of aesthetic texture perception and assign 8 pairs of aesthetic properties to different layers. Finally, we describe the generation of multiple linear and non-linear regression models for aesthetic prediction by taking dimensionality-reduced texture features and aesthetic properties of visual textures as dependent and independent variables, respectively. Our experimental results indicate that the relationships between each layer and its neighbors in the hierarchical feed-forward layer model of aesthetic texture perception can be fitted well by linear functions, and the models thus generated can successfully bridge the gap between computational texture features and aesthetic texture properties.

Hierarchical Graphene coating for highly sensitive solid phase microextraction of organochlorine pesticides.

PubMed

Wang, Fuxin; Liu, Shuqin; Yang, Hao; Zheng, Juan; Qiu, Junlang; Xu, Jianqiao; Tong, Yexiang; Zhu, Fang; Ouyang, Gangfeng

2016-11-01

Graphene, a novel class of carbon nanostructures, has received great attention as sorbents due to its fascinating structures, ultrahigh specific surface area, and good extraction ability. In this paper, a new type of hierarchical graphene was synthesized through employing a mild and environment-friendly method. Such 3D interconnected graphene own a high specific surface area up to 524m(2)g(-1), which is about 2.5 fold larger than the graphene, since the synthetic material has interlayer pores between nanosheets and in-plane pores. Then a superior solid-phase microextraction fiber was fabricated by sequentially coating the stainless steel fiber with silicone sealant film and hierarchical graphene powder. Since the novel hierarchical graphene possessed large surface area and good adsorption property, the as-prepared fiber exhibited good extraction properties of the organochlorine pesticides (OCPs). As for the analytical performance, the as-prepared fiber achieved low detection limits (0.08-0.80ngL(-1)) and wide linearity (10-30,000ngL(-1)) under the optimal conditions. The repeatability (n=5) for single fiber were between 5.1% and 11%, while the reproducibility (n=3) of fiber-to-fiber were range from 6.2% to14%. Moreover, the fiber was successfully applied to the analysis of OCPs in the Pearl River water. Copyright © 2016 Elsevier B.V. All rights reserved.

Instructional and behavior management practices implemented by elementary general education teachers.

PubMed

Reddy, Linda A; Fabiano, Gregory A; Dudek, Christopher M; Hsu, Louis

2013-12-01

This investigation examined 317 general education kindergarten through fifth-grade teachers' use of instructional and behavioral management strategies as measured by the Classroom Strategy Scale (CSS)-Observer Form, a multidimensional tool for assessing classroom practices. The CSS generates frequency of strategy use and discrepancy scores reflecting the difference between recommended and actual frequencies of strategy use. Hierarchical linear models (HLMs) suggested that teachers' grade-level assignment was related to their frequency of using instructional and behavioral management strategies: Lower grade teachers utilized more clear 1 to 2 step commands, praise statements, and behavioral corrective feedback strategies than upper grade teachers, whereas upper grade teachers utilized more academic monitoring and feedback strategies, content/concept summaries, student focused learning and engagement, and student thinking strategies than lower grade teachers. Except for the use of praise statements, teachers' usage of instructional and behavioral management strategies was not found to be related to years of teaching experience or to the interaction of years of teaching experience and grade-level assignment. HLMs suggested that teachers' grade level was related to their discrepancy scores of some instructional and behavioral management strategies: Upper grade teachers had higher discrepancy scores in academic performance feedback, behavioral feedback, and praise than lower grade teachers. Teachers' discrepancy scores of instructional and behavioral management strategies were not found to be related to years of teaching experience or to the interaction of years of teaching experience and grade-level assignment. Implications of results for school psychology practice are outlined. © 2013.

Hierarchical Image Segmentation of Remotely Sensed Data using Massively Parallel GNU-LINUX Software

NASA Technical Reports Server (NTRS)

Tilton, James C.

2003-01-01

A hierarchical set of image segmentations is a set of several image segmentations of the same image at different levels of detail in which the segmentations at coarser levels of detail can be produced from simple merges of regions at finer levels of detail. In [1], Tilton, et a1 describes an approach for producing hierarchical segmentations (called HSEG) and gave a progress report on exploiting these hierarchical segmentations for image information mining. The HSEG algorithm is a hybrid of region growing and constrained spectral clustering that produces a hierarchical set of image segmentations based on detected convergence points. In the main, HSEG employs the hierarchical stepwise optimization (HSWO) approach to region growing, which was described as early as 1989 by Beaulieu and Goldberg. The HSWO approach seeks to produce segmentations that are more optimized than those produced by more classic approaches to region growing (e.g. Horowitz and T. Pavlidis, [3]). In addition, HSEG optionally interjects between HSWO region growing iterations, merges between spatially non-adjacent regions (i.e., spectrally based merging or clustering) constrained by a threshold derived from the previous HSWO region growing iteration. While the addition of constrained spectral clustering improves the utility of the segmentation results, especially for larger images, it also significantly increases HSEG s computational requirements. To counteract this, a computationally efficient recursive, divide-and-conquer, implementation of HSEG (RHSEG) was devised, which includes special code to avoid processing artifacts caused by RHSEG s recursive subdivision of the image data. The recursive nature of RHSEG makes for a straightforward parallel implementation. This paper describes the HSEG algorithm, its recursive formulation (referred to as RHSEG), and the implementation of RHSEG using massively parallel GNU-LINUX software. Results with Landsat TM data are included comparing RHSEG with classic region growing.

Room temperature synthesis and highly enhanced visible light photocatalytic activity of porous BiOI/BiOCl composites nanoplates microflowers.

PubMed

Dong, Fan; Sun, Yanjuan; Fu, Min; Wu, Zhongbiao; Lee, S C

2012-06-15

This research represents a highly enhanced visible light photocatalytic removal of 450 ppb level of nitric oxide (NO) in air by utilizing flower-like hierarchical porous BiOI/BiOCl composites synthesized by a room temperature template free method for the first time. The facile synthesis method avoids high temperature treatment, use of organic precursors and production of undesirable organic byproducts during synthesis process. The result indicated that the as-prepared BiOI/BiOCl composites samples were solid solution and were self-assembled hierarchically with single-crystal nanoplates. The aggregation of the self-assembled nanoplates resulted in the formation of 3D hierarchical porous architecture containing tri-model mesopores. The coupling to BiOI with BiOCl led to down-lowered valence band (VB) and up-lifted conduction band (CB) in contrast to BiOI, making the composites suitable for visible light excitation. The BiOI/BiOCl composites samples exhibited highly enhanced visible light photocatalytic activity for removal of NO in air due to the large surface areas and pore volume, hierarchical structure and modified band structure, exceeding that of P25, BiOI, C-doped TiO(2) and Bi(2)WO(6). This research results could provide a cost-effective approach for the synthesis of porous hierarchical materials and enhancement of photocatalyst performance for environmental and energetic applications owing to its low cost and easy scaling up. Copyright © 2012 Elsevier B.V. All rights reserved.

Methodological quality and reporting of generalized linear mixed models in clinical medicine (2000-2012): a systematic review.

PubMed

Casals, Martí; Girabent-Farrés, Montserrat; Carrasco, Josep L

2014-01-01

Modeling count and binary data collected in hierarchical designs have increased the use of Generalized Linear Mixed Models (GLMMs) in medicine. This article presents a systematic review of the application and quality of results and information reported from GLMMs in the field of clinical medicine. A search using the Web of Science database was performed for published original articles in medical journals from 2000 to 2012. The search strategy included the topic "generalized linear mixed models","hierarchical generalized linear models", "multilevel generalized linear model" and as a research domain we refined by science technology. Papers reporting methodological considerations without application, and those that were not involved in clinical medicine or written in English were excluded. A total of 443 articles were detected, with an increase over time in the number of articles. In total, 108 articles fit the inclusion criteria. Of these, 54.6% were declared to be longitudinal studies, whereas 58.3% and 26.9% were defined as repeated measurements and multilevel design, respectively. Twenty-two articles belonged to environmental and occupational public health, 10 articles to clinical neurology, 8 to oncology, and 7 to infectious diseases and pediatrics. The distribution of the response variable was reported in 88% of the articles, predominantly Binomial (n = 64) or Poisson (n = 22). Most of the useful information about GLMMs was not reported in most cases. Variance estimates of random effects were described in only 8 articles (9.2%). The model validation, the method of covariate selection and the method of goodness of fit were only reported in 8.0%, 36.8% and 14.9% of the articles, respectively. During recent years, the use of GLMMs in medical literature has increased to take into account the correlation of data when modeling qualitative data or counts. According to the current recommendations, the quality of reporting has room for improvement regarding the characteristics of the analysis, estimation method, validation, and selection of the model.

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

Detecting multiple outliers in linear functional relationship model for circular variables using clustering technique

NASA Astrophysics Data System (ADS)

Mokhtar, Nurkhairany Amyra; Zubairi, Yong Zulina; Hussin, Abdul Ghapor

2017-05-01

Outlier detection has been used extensively in data analysis to detect anomalous observation in data and has important application in fraud detection and robust analysis. In this paper, we propose a method in detecting multiple outliers for circular variables in linear functional relationship model. Using the residual values of the Caires and Wyatt model, we applied the hierarchical clustering procedure. With the use of tree diagram, we illustrate the graphical approach of the detection of outlier. A simulation study is done to verify the accuracy of the proposed method. Also, an illustration to a real data set is given to show its practical applicability.

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

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

PubMed

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

2018-05-01

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

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.

A Bayesian Hierarchical Model for Glacial Dynamics Based on the Shallow Ice Approximation and its Evaluation Using Analytical Solutions

NASA Astrophysics Data System (ADS)

Gopalan, Giri; Hrafnkelsson, Birgir; Aðalgeirsdóttir, Guðfinna; Jarosch, Alexander H.; Pálsson, Finnur

2018-03-01

Bayesian hierarchical modeling can assist the study of glacial dynamics and ice flow properties. This approach will allow glaciologists to make fully probabilistic predictions for the thickness of a glacier at unobserved spatio-temporal coordinates, and it will also allow for the derivation of posterior probability distributions for key physical parameters such as ice viscosity and basal sliding. The goal of this paper is to develop a proof of concept for a Bayesian hierarchical model constructed, which uses exact analytical solutions for the shallow ice approximation (SIA) introduced by Bueler et al. (2005). A suite of test simulations utilizing these exact solutions suggests that this approach is able to adequately model numerical errors and produce useful physical parameter posterior distributions and predictions. A byproduct of the development of the Bayesian hierarchical model is the derivation of a novel finite difference method for solving the SIA partial differential equation (PDE). An additional novelty of this work is the correction of numerical errors induced through a numerical solution using a statistical model. This error correcting process models numerical errors that accumulate forward in time and spatial variation of numerical errors between the dome, interior, and margin of a glacier.

A hierarchical classification approach for recognition of low-density (LDPE) and high-density polyethylene (HDPE) in mixed plastic waste based on short-wave infrared (SWIR) hyperspectral imaging

NASA Astrophysics Data System (ADS)

Bonifazi, Giuseppe; Capobianco, Giuseppe; Serranti, Silvia

2018-06-01

The aim of this work was to recognize different polymer flakes from mixed plastic waste through an innovative hierarchical classification strategy based on hyperspectral imaging, with particular reference to low density polyethylene (LDPE) and high-density polyethylene (HDPE). A plastic waste composition assessment, including also LDPE and HDPE identification, may help to define optimal recycling strategies for product quality control. Correct handling of plastic waste is essential for its further "sustainable" recovery, maximizing the sorting performance in particular for plastics with similar characteristics as LDPE and HDPE. Five different plastic waste samples were chosen for the investigation: polypropylene (PP), LDPE, HDPE, polystyrene (PS) and polyvinyl chloride (PVC). A calibration dataset was realized utilizing the corresponding virgin polymers. Hyperspectral imaging in the short-wave infrared range (1000-2500 nm) was thus applied to evaluate the different plastic spectral attributes finalized to perform their recognition/classification. After exploring polymer spectral differences by principal component analysis (PCA), a hierarchical partial least squares discriminant analysis (PLS-DA) model was built allowing the five different polymers to be recognized. The proposed methodology, based on hierarchical classification, is very powerful and fast, allowing to recognize the five different polymers in a single step.

Hierarchical structure of moral stages assessed by a sorting task.

PubMed

Boom, J; Brugman, D; van der Heijden, P G

2001-01-01

Following criticism of Kohlberg's theory of moral judgment, an empirical re-examination of hierarchical stage structure was desirable. Utilizing Piaget's concept of reflective abstraction as a basis, the hierarchical stage structure was investigated using a new method. Study participants (553 Dutch university students and 196 Russian high school students) sorted statements in terms of moral sophistication. These statements were typical for the different stages of moral development as defined in Colby and Kohlberg. The rank ordering performed by participants confirmed the hypotheses. First, despite large individual variation, the ordering of the statements that gave the best fit revealed that each consecutive Kohlbergian stage was perceived to be more morally sophisticated. Second, the lower the stage as represented by the items, the higher the agreement among the participants in their ranking; and the higher the stage as represented by the items, the lower the agreement among the participants in the rankings. Moreover, the pivotal point depended on the developmental characteristics of the sample, which demonstrated a developmental effect: The ordering of statements representative of moral stages below one's own current stage was straightforward, whereas the ordering of statements above one's own stage was difficult. It was concluded that the Piagetian idea of reflective abstraction can be used successfully to operationalize and measure the hierarchical nature of moral development.

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

ERIC Educational Resources Information Center

Thum, Yeow Meng; Bhattacharya, Suman Kumar

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

Assessing Validity of Measurement in Learning Disabilities Using Hierarchical Generalized Linear Modeling: The Roles of Anxiety and Motivation

ERIC Educational Resources Information Center

Sideridis, Georgios D.

2016-01-01

The purpose of the present studies was to test the hypothesis that the psychometric characteristics of ability scales may be significantly distorted if one accounts for emotional factors during test taking. Specifically, the present studies evaluate the effects of anxiety and motivation on the item difficulties of the Rasch model. In Study 1, the…

Daily Stress and Emotional Well-Being among Asian American Adolescents: Same-Day, Lagged, and Chronic Associations

ERIC Educational Resources Information Center

Kiang, Lisa; Buchanan, Christy M.

2014-01-01

Daily-diary data from 180 Asian American 9th-10th graders (58% female, 75% second generation; "M" age = 14.97 years) were used to investigate how family, school, and peer stress are each associated with same-day and next-day (lagged) well-being, and vice versa. Hierarchical linear modeling provided support for reciprocal links when…

Transitioning to Middle School in the Sixth Grade: A Hierarchical Linear Modeling (HLM) Analysis of Substance Use, Violence, and Suicidal Thoughts

ERIC Educational Resources Information Center

Gunter, Whitney D.; Bakken, Nicholas W.

2010-01-01

In recent years, public schools have moved away from traditional grade configurations with junior high schools and have shifted toward integrating sixth-grade students into middle schools. It has been argued that the effect this will have on students is to allow for additional freedom and earlier social growth. However, the counterargument to this…

Feeling Good, Feeling Bad: Influences of Maternal Perceptions of the Child and Marital Adjustment on Well-Being in Mothers of Children with an Autism Spectrum Disorder

ERIC Educational Resources Information Center

Lickenbrock, Diane M.; Ekas, Naomi V.; Whitman, Thomas L.

2011-01-01

Mothers of children with an autism spectrum disorder (n = 49) participated in a 30-day diary study which examined associations between mothers' positive and negative perceptions of their children, marital adjustment, and maternal well-being. Hierarchical linear modeling results revealed that marital adjustment mediated associations between…

Predicting Urban Elementary Student Success and Passage on Ohio's High-Stakes Achievement Measures Using DIBELS Oral Reading Fluency and Informal Math Concepts and Applications: An Exploratory Study Employing Hierarchical Linear Modeling

ERIC Educational Resources Information Center

Merkle, Erich Robert

2011-01-01

Contemporary education is experiencing substantial reform across legislative, pedagogical, and assessment dimensions. The increase in school-based accountability systems has brought forth a culture where states, school districts, teachers, and individual students are required to demonstrate their efficacy towards improvement of the educational…

Language Shift in the United States and Foreign-Born Older Mexican Heritage Individuals: Co-Ethnic Context for Language Resistance

ERIC Educational Resources Information Center

Siordia, Carlos; Diaz, Maria E.

2012-01-01

In this study, we investigate individual-level language shift in a population of Mexican origin Latinos/as aged 65 and up. By using data from the Hispanic Established Populations for the Epidemiologic Study of the Elderly, we investigate their English language use as the dependent variable in a hierarchical linear model. The microlevel independent…

Determinants of Salary Growth in Shenzhen, China: An Analysis of Formal Education, On-the-Job Training, and Adult Education with a Three-Level Model.

ERIC Educational Resources Information Center

Xiao, Jin

2002-01-01

Uses hierarchical linear model to estimate the effects of three forms of human capital on employee salary in China: Formal education, employer-provided on-the-job training, and adult education. Finds, for example, that employees' experience in changing production technology and on-the-job training are positively associated with salary increases…

Gene-Environment Contributions to the Development of Infant Vagal Reactivity: The Interaction of Dopamine and Maternal Sensitivity

ERIC Educational Resources Information Center

Propper, Cathi; Moore, Ginger A.; Mills-Koonce, W. Roger; Halpern, Carolyn Tucker; Hill-Soderlund, Ashley L.; Calkins, Susan D.; Carbone, Mary Anna; Cox, Martha

2008-01-01

This study investigated dopamine receptor genes ("DRD2" and "DRD4") and maternal sensitivity as predictors of infant respiratory sinus arrhythmia (RSA) and RSA reactivity, purported indices of vagal tone and vagal regulation, in a challenge task at 3, 6, and 12 months in 173 infant-mother dyads. Hierarchical linear modeling (HLM) revealed that at…

A Multi-Level Simultaneous Analysis of How Student and School Characteristics Are Related to Students' English Language Achievement

ERIC Educational Resources Information Center

Güvendir, Emre

2015-01-01

This study examines how student and school characteristics are related to Turkish students' English language achievement in Evaluation of Student Achievement Test (ÖBBS) of 2009. The participants of the study involve 43707 ninth year students who were required to take ÖBBS in 2009. For data analysis two level hierarchical linear modeling was…

Developmental Course of Impulsivity and Capability from Age 10 to Age 25 as Related to Trajectory of Suicide Attempt in a Community Cohort

ERIC Educational Resources Information Center

Kasen, Stephanie; Cohen, Patricia; Chen, Henian

2011-01-01

Hierarchical linear models were used to examine trajectories of impulsivity and capability between ages 10 and 25 in relation to suicide attempt in 770 youths followed longitudinally: intercepts were set at age 17. The impulsivity measure assessed features of urgency (e.g., poor control, quick provocation, and disregard for external constraints);…

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

ERIC Educational Resources Information Center

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

2014-01-01

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