Virtual Levels and Role Models: N-Level Structural Equations Model of Reciprocal Ratings Data.

PubMed

Mehta, Paras D

2018-01-01

A general latent variable modeling framework called n-Level Structural Equations Modeling (NL-SEM) for dependent data-structures is introduced. NL-SEM is applicable to a wide range of complex multilevel data-structures (e.g., cross-classified, switching membership, etc.). Reciprocal dyadic ratings obtained in round-robin design involve complex set of dependencies that cannot be modeled within Multilevel Modeling (MLM) or Structural Equations Modeling (SEM) frameworks. The Social Relations Model (SRM) for round robin data is used as an example to illustrate key aspects of the NL-SEM framework. NL-SEM introduces novel constructs such as 'virtual levels' that allows a natural specification of latent variable SRMs. An empirical application of an explanatory SRM for personality using xxM, a software package implementing NL-SEM is presented. Results show that person perceptions are an integral aspect of personality. Methodological implications of NL-SEM for the analyses of an emerging class of contextual- and relational-SEMs are discussed.

At the Frontiers of Modeling Intensive Longitudinal Data: Dynamic Structural Equation Models for the Affective Measurements from the COGITO Study.

PubMed

Hamaker, E L; Asparouhov, T; Brose, A; Schmiedek, F; Muthén, B

2018-04-06

With the growing popularity of intensive longitudinal research, the modeling techniques and software options for such data are also expanding rapidly. Here we use dynamic multilevel modeling, as it is incorporated in the new dynamic structural equation modeling (DSEM) toolbox in Mplus, to analyze the affective data from the COGITO study. These data consist of two samples of over 100 individuals each who were measured for about 100 days. We use composite scores of positive and negative affect and apply a multilevel vector autoregressive model to allow for individual differences in means, autoregressions, and cross-lagged effects. Then we extend the model to include random residual variances and covariance, and finally we investigate whether prior depression affects later depression scores through the random effects of the daily diary measures. We end with discussing several urgent-but mostly unresolved-issues in the area of dynamic multilevel modeling.

Multilevel algorithms for nonlinear optimization

NASA Technical Reports Server (NTRS)

Alexandrov, Natalia; Dennis, J. E., Jr.

1994-01-01

Multidisciplinary design optimization (MDO) gives rise to nonlinear optimization problems characterized by a large number of constraints that naturally occur in blocks. We propose a class of multilevel optimization methods motivated by the structure and number of constraints and by the expense of the derivative computations for MDO. The algorithms are an extension to the nonlinear programming problem of the successful class of local Brown-Brent algorithms for nonlinear equations. Our extensions allow the user to partition constraints into arbitrary blocks to fit the application, and they separately process each block and the objective function, restricted to certain subspaces. The methods use trust regions as a globalization strategy, and they have been shown to be globally convergent under reasonable assumptions. The multilevel algorithms can be applied to all classes of MDO formulations. Multilevel algorithms for solving nonlinear systems of equations are a special case of the multilevel optimization methods. In this case, they can be viewed as a trust-region globalization of the Brown-Brent class.

Modeling Latent Interactions at Level 2 in Multilevel Structural Equation Models: An Evaluation of Mean-Centered and Residual-Centered Unconstrained Approaches

ERIC Educational Resources Information Center

Leite, Walter L.; Zuo, Youzhen

2011-01-01

Among the many methods currently available for estimating latent variable interactions, the unconstrained approach is attractive to applied researchers because of its relatively easy implementation with any structural equation modeling (SEM) software. Using a Monte Carlo simulation study, we extended and evaluated the unconstrained approach to…

Analyzing chromatographic data using multilevel modeling.

PubMed

Wiczling, Paweł

2018-06-01

It is relatively easy to collect chromatographic measurements for a large number of analytes, especially with gradient chromatographic methods coupled with mass spectrometry detection. Such data often have a hierarchical or clustered structure. For example, analytes with similar hydrophobicity and dissociation constant tend to be more alike in their retention than a randomly chosen set of analytes. Multilevel models recognize the existence of such data structures by assigning a model for each parameter, with its parameters also estimated from data. In this work, a multilevel model is proposed to describe retention time data obtained from a series of wide linear organic modifier gradients of different gradient duration and different mobile phase pH for a large set of acids and bases. The multilevel model consists of (1) the same deterministic equation describing the relationship between retention time and analyte-specific and instrument-specific parameters, (2) covariance relationships relating various physicochemical properties of the analyte to chromatographically specific parameters through quantitative structure-retention relationship based equations, and (3) stochastic components of intra-analyte and interanalyte variability. The model was implemented in Stan, which provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods. Graphical abstract Relationships between log k and MeOH content for acidic, basic, and neutral compounds with different log P. CI credible interval, PSA polar surface area.

A Multilevel Algorithm for the Solution of Second Order Elliptic Differential Equations on Sparse Grids

NASA Technical Reports Server (NTRS)

Pflaum, Christoph

1996-01-01

A multilevel algorithm is presented that solves general second order elliptic partial differential equations on adaptive sparse grids. The multilevel algorithm consists of several V-cycles. Suitable discretizations provide that the discrete equation system can be solved in an efficient way. Numerical experiments show a convergence rate of order Omicron(1) for the multilevel algorithm.

Multilevel Green's function interpolation method for scattering from composite metallic and dielectric objects.

PubMed

Shi, Yan; Wang, Hao Gang; Li, Long; Chan, Chi Hou

2008-10-01

A multilevel Green's function interpolation method based on two kinds of multilevel partitioning schemes--the quasi-2D and the hybrid partitioning scheme--is proposed for analyzing electromagnetic scattering from objects comprising both conducting and dielectric parts. The problem is formulated using the surface integral equation for homogeneous dielectric and conducting bodies. A quasi-2D multilevel partitioning scheme is devised to improve the efficiency of the Green's function interpolation. In contrast to previous multilevel partitioning schemes, noncubic groups are introduced to discretize the whole EM structure in this quasi-2D multilevel partitioning scheme. Based on the detailed analysis of the dimension of the group in this partitioning scheme, a hybrid quasi-2D/3D multilevel partitioning scheme is proposed to effectively handle objects with fine local structures. Selection criteria for some key parameters relating to the interpolation technique are given. The proposed algorithm is ideal for the solution of problems involving objects such as missiles, microstrip antenna arrays, photonic bandgap structures, etc. Numerical examples are presented to show that CPU time is between O(N) and O(N log N) while the computer memory requirement is O(N).

Model fit evaluation in multilevel structural equation models

PubMed Central

Ryu, Ehri

2014-01-01

Assessing goodness of model fit is one of the key questions in structural equation modeling (SEM). Goodness of fit is the extent to which the hypothesized model reproduces the multivariate structure underlying the set of variables. During the earlier development of multilevel structural equation models, the “standard” approach was to evaluate the goodness of fit for the entire model across all levels simultaneously. The model fit statistics produced by the standard approach have a potential problem in detecting lack of fit in the higher-level model for which the effective sample size is much smaller. Also when the standard approach results in poor model fit, it is not clear at which level the model does not fit well. This article reviews two alternative approaches that have been proposed to overcome the limitations of the standard approach. One is a two-step procedure which first produces estimates of saturated covariance matrices at each level and then performs single-level analysis at each level with the estimated covariance matrices as input (Yuan and Bentler, 2007). The other level-specific approach utilizes partially saturated models to obtain test statistics and fit indices for each level separately (Ryu and West, 2009). Simulation studies (e.g., Yuan and Bentler, 2007; Ryu and West, 2009) have consistently shown that both alternative approaches performed well in detecting lack of fit at any level, whereas the standard approach failed to detect lack of fit at the higher level. It is recommended that the alternative approaches are used to assess the model fit in multilevel structural equation model. Advantages and disadvantages of the two alternative approaches are discussed. The alternative approaches are demonstrated in an empirical example. PMID:24550882

Exploring the Association between Transformational Leadership and Teacher's Self-Efficacy in Greek Education System: A Multilevel SEM Model

ERIC Educational Resources Information Center

Gkolia, Aikaterini; Koustelios, Athanasios; Belias, Dimitrios

2018-01-01

The main aim of this study is to examine the effect of principals' transformational leadership on teachers' self-efficacy across 77 different Greek elementary and secondary schools based on a centralized education system. For the investigation of the above effect multilevel Structural Equation Modelling analysis was conducted, recognizing the…

Detecting Intervention Effects in a Cluster-Randomized Design Using Multilevel Structural Equation Modeling for Binary Responses

ERIC Educational Resources Information Center

Cho, Sun-Joo; Preacher, Kristopher J.; Bottge, Brian A.

2015-01-01

Multilevel modeling (MLM) is frequently used to detect group differences, such as an intervention effect in a pre-test--post-test cluster-randomized design. Group differences on the post-test scores are detected by controlling for pre-test scores as a proxy variable for unobserved factors that predict future attributes. The pre-test and post-test…

Estimating the resolution limit of the map equation in community detection

NASA Astrophysics Data System (ADS)

Kawamoto, Tatsuro; Rosvall, Martin

2015-01-01

A community detection algorithm is considered to have a resolution limit if the scale of the smallest modules that can be resolved depends on the size of the analyzed subnetwork. The resolution limit is known to prevent some community detection algorithms from accurately identifying the modular structure of a network. In fact, any global objective function for measuring the quality of a two-level assignment of nodes into modules must have some sort of resolution limit or an external resolution parameter. However, it is yet unknown how the resolution limit affects the so-called map equation, which is known to be an efficient objective function for community detection. We derive an analytical estimate and conclude that the resolution limit of the map equation is set by the total number of links between modules instead of the total number of links in the full network as for modularity. This mechanism makes the resolution limit much less restrictive for the map equation than for modularity; in practice, it is orders of magnitudes smaller. Furthermore, we argue that the effect of the resolution limit often results from shoehorning multilevel modular structures into two-level descriptions. As we show, the hierarchical map equation effectively eliminates the resolution limit for networks with nested multilevel modular structures.

Algebraic aspects of the driven dynamics in the density operator and correlation functions calculation for multi-level open quantum systems

NASA Astrophysics Data System (ADS)

Bogolubov, Nikolai N.; Soldatov, Andrey V.

2017-12-01

Exact and approximate master equations were derived by the projection operator method for the reduced statistical operator of a multi-level quantum system with finite number N of quantum eigenstates interacting with arbitrary external classical fields and dissipative environment simultaneously. It was shown that the structure of these equations can be simplified significantly if the free Hamiltonian driven dynamics of an arbitrary quantum multi-level system under the influence of the external driving fields as well as its Markovian and non-Markovian evolution, stipulated by the interaction with the environment, are described in terms of the SU(N) algebra representation. As a consequence, efficient numerical methods can be developed and employed to analyze these master equations for real problems in various fields of theoretical and applied physics. It was also shown that literally the same master equations hold not only for the reduced density operator but also for arbitrary nonequilibrium multi-time correlation functions as well under the only assumption that the system and the environment are uncorrelated at some initial moment of time. A calculational scheme was proposed to account for these lost correlations in a regular perturbative way, thus providing additional computable terms to the correspondent master equations for the correlation functions.

The Importance of Isomorphism for Conclusions about Homology: A Bayesian Multilevel Structural Equation Modeling Approach with Ordinal Indicators.

PubMed

Guenole, Nigel

2016-01-01

We describe a Monte Carlo study examining the impact of assuming item isomorphism (i.e., equivalent construct meaning across levels of analysis) on conclusions about homology (i.e., equivalent structural relations across levels of analysis) under varying degrees of non-isomorphism in the context of ordinal indicator multilevel structural equation models (MSEMs). We focus on the condition where one or more loadings are higher on the between level than on the within level to show that while much past research on homology has ignored the issue of psychometric isomorphism, psychometric isomorphism is in fact critical to valid conclusions about homology. More specifically, when a measurement model with non-isomorphic items occupies an exogenous position in a multilevel structural model and the non-isomorphism of these items is not modeled, the within level exogenous latent variance is under-estimated leading to over-estimation of the within level structural coefficient, while the between level exogenous latent variance is overestimated leading to underestimation of the between structural coefficient. When a measurement model with non-isomorphic items occupies an endogenous position in a multilevel structural model and the non-isomorphism of these items is not modeled, the endogenous within level latent variance is under-estimated leading to under-estimation of the within level structural coefficient while the endogenous between level latent variance is over-estimated leading to over-estimation of the between level structural coefficient. The innovative aspect of this article is demonstrating that even minor violations of psychometric isomorphism render claims of homology untenable. We also show that posterior predictive p-values for ordinal indicator Bayesian MSEMs are insensitive to violations of isomorphism even when they lead to severely biased within and between level structural parameters. We highlight conditions where poor estimation of even correctly specified models rules out empirical examination of isomorphism and homology without taking precautions, for instance, larger Level-2 sample sizes, or using informative priors.

The Importance of Isomorphism for Conclusions about Homology: A Bayesian Multilevel Structural Equation Modeling Approach with Ordinal Indicators

PubMed Central

Guenole, Nigel

2016-01-01

We describe a Monte Carlo study examining the impact of assuming item isomorphism (i.e., equivalent construct meaning across levels of analysis) on conclusions about homology (i.e., equivalent structural relations across levels of analysis) under varying degrees of non-isomorphism in the context of ordinal indicator multilevel structural equation models (MSEMs). We focus on the condition where one or more loadings are higher on the between level than on the within level to show that while much past research on homology has ignored the issue of psychometric isomorphism, psychometric isomorphism is in fact critical to valid conclusions about homology. More specifically, when a measurement model with non-isomorphic items occupies an exogenous position in a multilevel structural model and the non-isomorphism of these items is not modeled, the within level exogenous latent variance is under-estimated leading to over-estimation of the within level structural coefficient, while the between level exogenous latent variance is overestimated leading to underestimation of the between structural coefficient. When a measurement model with non-isomorphic items occupies an endogenous position in a multilevel structural model and the non-isomorphism of these items is not modeled, the endogenous within level latent variance is under-estimated leading to under-estimation of the within level structural coefficient while the endogenous between level latent variance is over-estimated leading to over-estimation of the between level structural coefficient. The innovative aspect of this article is demonstrating that even minor violations of psychometric isomorphism render claims of homology untenable. We also show that posterior predictive p-values for ordinal indicator Bayesian MSEMs are insensitive to violations of isomorphism even when they lead to severely biased within and between level structural parameters. We highlight conditions where poor estimation of even correctly specified models rules out empirical examination of isomorphism and homology without taking precautions, for instance, larger Level-2 sample sizes, or using informative priors. PMID:26973580

Adaptive mesh refinement and load balancing based on multi-level block-structured Cartesian mesh

NASA Astrophysics Data System (ADS)

Misaka, Takashi; Sasaki, Daisuke; Obayashi, Shigeru

2017-11-01

We developed a framework for a distributed-memory parallel computer that enables dynamic data management for adaptive mesh refinement and load balancing. We employed simple data structure of the building cube method (BCM) where a computational domain is divided into multi-level cubic domains and each cube has the same number of grid points inside, realising a multi-level block-structured Cartesian mesh. Solution adaptive mesh refinement, which works efficiently with the help of the dynamic load balancing, was implemented by dividing cubes based on mesh refinement criteria. The framework was investigated with the Laplace equation in terms of adaptive mesh refinement, load balancing and the parallel efficiency. It was then applied to the incompressible Navier-Stokes equations to simulate a turbulent flow around a sphere. We considered wall-adaptive cube refinement where a non-dimensional wall distance y+ near the sphere is used for a criterion of mesh refinement. The result showed the load imbalance due to y+ adaptive mesh refinement was corrected by the present approach. To utilise the BCM framework more effectively, we also tested a cube-wise algorithm switching where an explicit and implicit time integration schemes are switched depending on the local Courant-Friedrichs-Lewy (CFL) condition in each cube.

The Moderating Effect of Health-Improving Workplace Environment on Promoting Physical Activity in White-Collar Employees: A Multi-Site Longitudinal Study Using Multi-Level Structural Equation Modeling.

PubMed

Watanabe, Kazuhiro; Otsuka, Yasumasa; Shimazu, Akihito; Kawakami, Norito

2016-02-01

This longitudinal study aimed to investigate the moderating effect of health-improving workplace environment on relationships between physical activity, self-efficacy, and psychological distress. Data were collected from 16 worksites and 129 employees at two time-points. Health-improving workplace environment was measured using the Japanese version of the Environmental Assessment Tool. Physical activity, self-efficacy, and psychological distress were also measured. Multi-level structural equation modeling was used to investigate the moderating effect of health-improving workplace environment on relationships between psychological distress, self-efficacy, and physical activity. Psychological distress was negatively associated with physical activity via low self-efficacy. Physical activity was negatively related to psychological distress. Physical activity/fitness facilities in the work environment exaggerated the positive relationship between self-efficacy and physical activity. Physical activity/fitness facilities in the workplace may promote employees' physical activity.

Many-level multilevel structural equation modeling: An efficient evaluation strategy.

PubMed

Pritikin, Joshua N; Hunter, Michael D; von Oertzen, Timo; Brick, Timothy R; Boker, Steven M

2017-01-01

Structural equation models are increasingly used for clustered or multilevel data in cases where mixed regression is too inflexible. However, when there are many levels of nesting, these models can become difficult to estimate. We introduce a novel evaluation strategy, Rampart, that applies an orthogonal rotation to the parts of a model that conform to commonly met requirements. This rotation dramatically simplifies fit evaluation in a way that becomes more potent as the size of the data set increases. We validate and evaluate the implementation using a 3-level latent regression simulation study. Then we analyze data from a state-wide child behavioral health measure administered by the Oklahoma Department of Human Services. We demonstrate the efficiency of Rampart compared to other similar software using a latent factor model with a 5-level decomposition of latent variance. Rampart is implemented in OpenMx, a free and open source software.

A Multilevel CFA-MTMM Model for Nested Structurally Different Methods

ERIC Educational Resources Information Center

Koch, Tobias; Schultze, Martin; Burrus, Jeremy; Roberts, Richard D.; Eid, Michael

2015-01-01

The numerous advantages of structural equation modeling (SEM) for the analysis of multitrait-multimethod (MTMM) data are well known. MTMM-SEMs allow researchers to explicitly model the measurement error, to examine the true convergent and discriminant validity of the given measures, and to relate external variables to the latent trait as well as…

Measuring Latent Quantities

ERIC Educational Resources Information Center

McDonald, Roderick P.

2011-01-01

A distinction is proposed between measures and predictors of latent variables. The discussion addresses the consequences of the distinction for the true-score model, the linear factor model, Structural Equation Models, longitudinal and multilevel models, and item-response models. A distribution-free treatment of calibration and…

The Impact of Intraclass Correlation on the Effectiveness of Level-Specific Fit Indices in Multilevel Structural Equation Modeling

PubMed Central

Hsu, Hsien-Yuan; Lin, Jr-Hung; Kwok, Oi-Man; Acosta, Sandra; Willson, Victor

2016-01-01

Several researchers have recommended that level-specific fit indices should be applied to detect the lack of model fit at any level in multilevel structural equation models. Although we concur with their view, we note that these studies did not sufficiently consider the impact of intraclass correlation (ICC) on the performance of level-specific fit indices. Our study proposed to fill this gap in the methodological literature. A Monte Carlo study was conducted to investigate the performance of (a) level-specific fit indices derived by a partially saturated model method (e.g., CFIPS_B and CFIPS_W) and (b) SRMRW and SRMRB in terms of their performance in multilevel structural equation models across varying ICCs. The design factors included intraclass correlation (ICC: ICC1 = 0.091 to ICC6 = 0.500), numbers of groups in between-level models (NG: 50, 100, 200, and 1,000), group size (GS: 30, 50, and 100), and type of misspecification (no misspecification, between-level misspecification, and within-level misspecification). Our simulation findings raise a concern regarding the performance of between-level-specific partial saturated fit indices in low ICC conditions: the performances of both TLIPS_B and RMSEAPS_B were more influenced by ICC compared with CFIPS_B and SRMRB. However, when traditional cutoff values (RMSEA≤ 0.06; CFI, TLI≥ 0.95; SRMR≤ 0.08) were applied, CFIPS_B and TLIPS_B were still able to detect misspecified between-level models even when ICC was as low as 0.091 (ICC1). On the other hand, both RMSEAPS_B and SRMRB were not recommended under low ICC conditions. PMID:29795901

Detecting Intervention Effects in a Cluster-Randomized Design Using Multilevel Structural Equation Modeling for Binary Responses

PubMed Central

Cho, Sun-Joo; Preacher, Kristopher J.; Bottge, Brian A.

2015-01-01

Multilevel modeling (MLM) is frequently used to detect group differences, such as an intervention effect in a pre-test–post-test cluster-randomized design. Group differences on the post-test scores are detected by controlling for pre-test scores as a proxy variable for unobserved factors that predict future attributes. The pre-test and post-test scores that are most often used in MLM are summed item responses (or total scores). In prior research, there have been concerns regarding measurement error in the use of total scores in using MLM. To correct for measurement error in the covariate and outcome, a theoretical justification for the use of multilevel structural equation modeling (MSEM) has been established. However, MSEM for binary responses has not been widely applied to detect intervention effects (group differences) in intervention studies. In this article, the use of MSEM for intervention studies is demonstrated and the performance of MSEM is evaluated via a simulation study. Furthermore, the consequences of using MLM instead of MSEM are shown in detecting group differences. Results of the simulation study showed that MSEM performed adequately as the number of clusters, cluster size, and intraclass correlation increased and outperformed MLM for the detection of group differences. PMID:29881032

Detecting Intervention Effects in a Cluster-Randomized Design Using Multilevel Structural Equation Modeling for Binary Responses.

PubMed

Cho, Sun-Joo; Preacher, Kristopher J; Bottge, Brian A

2015-11-01

Multilevel modeling (MLM) is frequently used to detect group differences, such as an intervention effect in a pre-test-post-test cluster-randomized design. Group differences on the post-test scores are detected by controlling for pre-test scores as a proxy variable for unobserved factors that predict future attributes. The pre-test and post-test scores that are most often used in MLM are summed item responses (or total scores). In prior research, there have been concerns regarding measurement error in the use of total scores in using MLM. To correct for measurement error in the covariate and outcome, a theoretical justification for the use of multilevel structural equation modeling (MSEM) has been established. However, MSEM for binary responses has not been widely applied to detect intervention effects (group differences) in intervention studies. In this article, the use of MSEM for intervention studies is demonstrated and the performance of MSEM is evaluated via a simulation study. Furthermore, the consequences of using MLM instead of MSEM are shown in detecting group differences. Results of the simulation study showed that MSEM performed adequately as the number of clusters, cluster size, and intraclass correlation increased and outperformed MLM for the detection of group differences.

Handling Missing Data With Multilevel Structural Equation Modeling and Full Information Maximum Likelihood Techniques.

PubMed

Schminkey, Donna L; von Oertzen, Timo; Bullock, Linda

2016-08-01

With increasing access to population-based data and electronic health records for secondary analysis, missing data are common. In the social and behavioral sciences, missing data frequently are handled with multiple imputation methods or full information maximum likelihood (FIML) techniques, but healthcare researchers have not embraced these methodologies to the same extent and more often use either traditional imputation techniques or complete case analysis, which can compromise power and introduce unintended bias. This article is a review of options for handling missing data, concluding with a case study demonstrating the utility of multilevel structural equation modeling using full information maximum likelihood (MSEM with FIML) to handle large amounts of missing data. MSEM with FIML is a parsimonious and hypothesis-driven strategy to cope with large amounts of missing data without compromising power or introducing bias. This technique is relevant for nurse researchers faced with ever-increasing amounts of electronic data and decreasing research budgets. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Embedding Multilevel Survival Analysis of Dyadic Social Interaction in Structural Equation Models: Hazard Rates as Both Outcomes and Predictors

PubMed Central

Snyder, James

2014-01-01

Objective Demonstrate multivariate multilevel survival analysis within a larger structural equation model. Test the 3 hypotheses that when confronted by a negative parent, child rates of angry, sad/fearful, and positive emotion will increase, decrease, and stay the same, respectively, for antisocial compared with normal children. This same pattern will predict increases in future antisocial behavior. Methods Parent–child dyads were videotaped in the fall of kindergarten in the laboratory and antisocial behavior ratings were obtained in the fall of kindergarten and third grade. Results Kindergarten antisocial predicted less child sad/fear and child positive but did not predict child anger given parent negative. Less child positive and more child neutral given parent negative predicted increases in third-grade antisocial behavior. Conclusions The model is a useful analytic tool for studying rates of social behavior. Lack of positive affect or excess neutral affect may be a new risk factor for child antisocial behavior. PMID:24133296

Affect, work-goal schemas, and work-goal striving among adults with chronic pain: a multilevel structural equation analysis.

PubMed

Mun, Chung Jung; Karoly, Paul; Okun, Morris A; Kim, Hanjoe; Tennen, Howard

2016-04-01

For individuals with chronic pain, the within-person influence of affect and goal cognition on daily work-related goal striving is not yet well understood. The present study tested the hypothesis that anticipatory goal cognition in the form of a morning work goal schema mediates the relations between morning affect and later (afternoon and evening) work goal striving. Working adults with chronic pain (N = 131) completed a 21-day diary with morning, afternoon, and evening assessments analyzed via multi-level structural equation modeling. At the within-person level, morning positive and negative affect were positively associated with morning work goal schemas; and morning work goal schemas, in turn, positively predicted both afternoon and evening work goal striving. Our findings underscore the complex dynamics over time of the relationship between affect and self-regulatory processes and have implications for future studies and for interventions to assist working adults with chronic pain.

Performance of a parallel algebraic multilevel preconditioner for stabilized finite element semiconductor device modeling

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

Lin, Paul T.; Shadid, John N.; Sala, Marzio

In this study results are presented for the large-scale parallel performance of an algebraic multilevel preconditioner for solution of the drift-diffusion model for semiconductor devices. The preconditioner is the key numerical procedure determining the robustness, efficiency and scalability of the fully-coupled Newton-Krylov based, nonlinear solution method that is employed for this system of equations. The coupled system is comprised of a source term dominated Poisson equation for the electric potential, and two convection-diffusion-reaction type equations for the electron and hole concentration. The governing PDEs are discretized in space by a stabilized finite element method. Solution of the discrete system ismore » obtained through a fully-implicit time integrator, a fully-coupled Newton-based nonlinear solver, and a restarted GMRES Krylov linear system solver. The algebraic multilevel preconditioner is based on an aggressive coarsening graph partitioning of the nonzero block structure of the Jacobian matrix. Representative performance results are presented for various choices of multigrid V-cycles and W-cycles and parameter variations for smoothers based on incomplete factorizations. Parallel scalability results are presented for solution of up to 10{sup 8} unknowns on 4096 processors of a Cray XT3/4 and an IBM POWER eServer system.« less

An accelerated lambda iteration method for multilevel radiative transfer. I - Non-overlapping lines with background continuum

NASA Technical Reports Server (NTRS)

Rybicki, G. B.; Hummer, D. G.

1991-01-01

A method is presented for solving multilevel transfer problems when nonoverlapping lines and background continuum are present and active continuum transfer is absent. An approximate lambda operator is employed to derive linear, 'preconditioned', statistical-equilibrium equations. A method is described for finding the diagonal elements of the 'true' numerical lambda operator, and therefore for obtaining the coefficients of the equations. Iterations of the preconditioned equations, in conjunction with the transfer equation's formal solution, are used to solve linear equations. Some multilevel problems are considered, including an eleven-level neutral helium atom. Diagonal and tridiagonal approximate lambda operators are utilized in the problems to examine the convergence properties of the method, and it is found to be effective for the line transfer problems.

Multilevel Dynamic Generalized Structured Component Analysis for Brain Connectivity Analysis in Functional Neuroimaging Data.

PubMed

Jung, Kwanghee; Takane, Yoshio; Hwang, Heungsun; Woodward, Todd S

2016-06-01

We extend dynamic generalized structured component analysis (GSCA) to enhance its data-analytic capability in structural equation modeling of multi-subject time series data. Time series data of multiple subjects are typically hierarchically structured, where time points are nested within subjects who are in turn nested within a group. The proposed approach, named multilevel dynamic GSCA, accommodates the nested structure in time series data. Explicitly taking the nested structure into account, the proposed method allows investigating subject-wise variability of the loadings and path coefficients by looking at the variance estimates of the corresponding random effects, as well as fixed loadings between observed and latent variables and fixed path coefficients between latent variables. We demonstrate the effectiveness of the proposed approach by applying the method to the multi-subject functional neuroimaging data for brain connectivity analysis, where time series data-level measurements are nested within subjects.

Translating multilevel theory into multilevel research: Challenges and opportunities for understanding the social determinants of psychiatric disorders

PubMed Central

Dunn, Erin C.; Masyn, Katherine E.; Yudron, Monica; Jones, Stephanie M.; Subramanian, S.V.

2014-01-01

The observation that features of the social environment, including family, school, and neighborhood characteristics, are associated with individual-level outcomes has spurred the development of dozens of multilevel or ecological theoretical frameworks in epidemiology, public health, psychology, and sociology, among other disciplines. Despite the widespread use of such theories in etiological, intervention, and policy studies, challenges remain in bridging multilevel theory and empirical research. This paper set out to synthesize these challenges and provide specific examples of methodological and analytical strategies researchers are using to gain a more nuanced understanding of the social determinants of psychiatric disorders, with a focus on children’s mental health. To accomplish this goal, we begin by describing multilevel theories, defining their core elements, and discussing what these theories suggest is needed in empirical work. In the second part, we outline the main challenges researchers face in translating multilevel theory into research. These challenges are presented for each stage of the research process. In the third section, we describe two methods being used as alternatives to traditional multilevel modeling techniques to better bridge multilevel theory and multilevel research. These are: (1) multilevel factor analysis and multilevel structural equation modeling; and (2) dynamic systems approaches. Through its review of multilevel theory, assessment of existing strategies, and examination of emerging methodologies, this paper offers a framework to evaluate and guide empirical studies on the social determinants of child psychiatric disorders as well as health across the lifecourse. PMID:24469555

How Principals and Peers Influence Teaching and Learning

ERIC Educational Resources Information Center

Supovitz, Jonathan; Sirinides, Philip; May, Henry

2010-01-01

This paper examines the effects of principal leadership and peer teacher influence on teachers' instructional practice and student learning. Using teacher survey and student achievement data from a mid-sized urban southeastern school district in the United States in 2006-2007, the study employs multilevel structural equation modeling to examine…

A Hierarchical Approach to Examine Personal and School Effect on Teacher Motivation

ERIC Educational Resources Information Center

Wei, Yi-En

2012-01-01

In order to depict a better picture of teacher motivation, the researcher developed the theoretical framework based on Deci and Ryan's (1985) self-determination theory (SDT) and examined factors affecting teachers' autonomous motivation at both the personal and school level. Several multilevel structural equation models (ML-SEM) were…

The Effects of Representations, Constructivist Approaches, and Engagement on Middle School Students' Algebraic Procedure and Conceptual Understanding

ERIC Educational Resources Information Center

Ross, Amanda; Willson, Victor

2012-01-01

This study examined the effects of types of representations, constructivist teaching approaches, and student engagement on middle school algebra students' procedural knowledge and conceptual understanding. Data gathered from 16 video lessons and algebra pretest/posttests were used to run three multilevel structural equation models. Symbolic…

A multilevel structural equation modeling analysis of vulnerabilities and resilience resources influencing affective adaptation to chronic pain.

PubMed

Sturgeon, John A; Zautra, Alex J; Arewasikporn, Anne

2014-02-01

The processes of individual adaptation to chronic pain are complex and occur across multiple domains. We examined the social, cognitive, and affective context of daily pain adaptation in individuals with fibromyalgia and osteoarthritis. By using a sample of 260 women with fibromyalgia or osteoarthritis, we examined the contributions of pain catastrophizing, negative interpersonal events, and positive interpersonal events to daily negative and positive affect across 30days of daily diary data. Individual differences and daily fluctuations in predictor variables were estimated simultaneously by utilizing multilevel structural equation modeling techniques. The relationships between pain and negative and positive affect were mediated by stable and day-to-day levels of pain catastrophizing as well as day-to-day positive interpersonal events, but not negative interpersonal events. There were significant and independent contributions of pain catastrophizing and positive interpersonal events to adaptation to pain and pain-related affective dysregulation. These effects occur both between persons and within a person's everyday life. Copyright © 2013 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

A multilevel correction adaptive finite element method for Kohn-Sham equation

NASA Astrophysics Data System (ADS)

Hu, Guanghui; Xie, Hehu; Xu, Fei

2018-02-01

In this paper, an adaptive finite element method is proposed for solving Kohn-Sham equation with the multilevel correction technique. In the method, the Kohn-Sham equation is solved on a fixed and appropriately coarse mesh with the finite element method in which the finite element space is kept improving by solving the derived boundary value problems on a series of adaptively and successively refined meshes. A main feature of the method is that solving large scale Kohn-Sham system is avoided effectively, and solving the derived boundary value problems can be handled efficiently by classical methods such as the multigrid method. Hence, the significant acceleration can be obtained on solving Kohn-Sham equation with the proposed multilevel correction technique. The performance of the method is examined by a variety of numerical experiments.

Finite Volume Element (FVE) discretization and multilevel solution of the axisymmetric heat equation

NASA Astrophysics Data System (ADS)

Litaker, Eric T.

1994-12-01

The axisymmetric heat equation, resulting from a point-source of heat applied to a metal block, is solved numerically; both iterative and multilevel solutions are computed in order to compare the two processes. The continuum problem is discretized in two stages: finite differences are used to discretize the time derivatives, resulting is a fully implicit backward time-stepping scheme, and the Finite Volume Element (FVE) method is used to discretize the spatial derivatives. The application of the FVE method to a problem in cylindrical coordinates is new, and results in stencils which are analyzed extensively. Several iteration schemes are considered, including both Jacobi and Gauss-Seidel; a thorough analysis of these schemes is done, using both the spectral radii of the iteration matrices and local mode analysis. Using this discretization, a Gauss-Seidel relaxation scheme is used to solve the heat equation iteratively. A multilevel solution process is then constructed, including the development of intergrid transfer and coarse grid operators. Local mode analysis is performed on the components of the amplification matrix, resulting in the two-level convergence factors for various combinations of the operators. A multilevel solution process is implemented by using multigrid V-cycles; the iterative and multilevel results are compared and discussed in detail. The computational savings resulting from the multilevel process are then discussed.

Forward and inverse uncertainty quantification using multilevel Monte Carlo algorithms for an elliptic non-local equation

DOE PAGES

Jasra, Ajay; Law, Kody J. H.; Zhou, Yan

2016-01-01

Our paper considers uncertainty quantification for an elliptic nonlocal equation. In particular, it is assumed that the parameters which define the kernel in the nonlocal operator are uncertain and a priori distributed according to a probability measure. It is shown that the induced probability measure on some quantities of interest arising from functionals of the solution to the equation with random inputs is well-defined,s as is the posterior distribution on parameters given observations. As the elliptic nonlocal equation cannot be solved approximate posteriors are constructed. The multilevel Monte Carlo (MLMC) and multilevel sequential Monte Carlo (MLSMC) sampling algorithms are usedmore » for a priori and a posteriori estimation, respectively, of quantities of interest. Furthermore, these algorithms reduce the amount of work to estimate posterior expectations, for a given level of error, relative to Monte Carlo and i.i.d. sampling from the posterior at a given level of approximation of the solution of the elliptic nonlocal equation.« less

Forward and inverse uncertainty quantification using multilevel Monte Carlo algorithms for an elliptic non-local equation

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

Jasra, Ajay; Law, Kody J. H.; Zhou, Yan

Our paper considers uncertainty quantification for an elliptic nonlocal equation. In particular, it is assumed that the parameters which define the kernel in the nonlocal operator are uncertain and a priori distributed according to a probability measure. It is shown that the induced probability measure on some quantities of interest arising from functionals of the solution to the equation with random inputs is well-defined,s as is the posterior distribution on parameters given observations. As the elliptic nonlocal equation cannot be solved approximate posteriors are constructed. The multilevel Monte Carlo (MLMC) and multilevel sequential Monte Carlo (MLSMC) sampling algorithms are usedmore » for a priori and a posteriori estimation, respectively, of quantities of interest. Furthermore, these algorithms reduce the amount of work to estimate posterior expectations, for a given level of error, relative to Monte Carlo and i.i.d. sampling from the posterior at a given level of approximation of the solution of the elliptic nonlocal equation.« less

Multiple imputation by chained equations for systematically and sporadically missing multilevel data.

PubMed

Resche-Rigon, Matthieu; White, Ian R

2018-06-01

In multilevel settings such as individual participant data meta-analysis, a variable is 'systematically missing' if it is wholly missing in some clusters and 'sporadically missing' if it is partly missing in some clusters. Previously proposed methods to impute incomplete multilevel data handle either systematically or sporadically missing data, but frequently both patterns are observed. We describe a new multiple imputation by chained equations (MICE) algorithm for multilevel data with arbitrary patterns of systematically and sporadically missing variables. The algorithm is described for multilevel normal data but can easily be extended for other variable types. We first propose two methods for imputing a single incomplete variable: an extension of an existing method and a new two-stage method which conveniently allows for heteroscedastic data. We then discuss the difficulties of imputing missing values in several variables in multilevel data using MICE, and show that even the simplest joint multilevel model implies conditional models which involve cluster means and heteroscedasticity. However, a simulation study finds that the proposed methods can be successfully combined in a multilevel MICE procedure, even when cluster means are not included in the imputation models.

School Climate and Dropping Out of School in the Era of Accountability

ERIC Educational Resources Information Center

Kotok, Stephen; Ikoma, Sakiko; Bodovski, Katerina

2016-01-01

Using data from the High School Longitudinal Study of 2009 (HSLS:09)--a large nationally representative sample of US high school students--we employed multilevel structural equation modeling (SEM) to examine the relationship between school characteristics and the likelihood that a student will drop out of high school. We used a multifaceted…

Relations among Reading Skills and Sub-Skills and Text-Level Reading Proficiency in Developing Readers

ERIC Educational Resources Information Center

Hudson, Roxanne F.; Torgesen, Joseph K.; Lane, Holly B.; Turner, Stephen J.

2012-01-01

Despite the recent attention to text reading fluency, few studies have studied the construct of oral reading rate and accuracy in connected text in a model that simultaneously examines many of the important variables in a multi-leveled fashion with young readers. Using Structural Equation Modeling, this study examined the measurement and…

PsiQuaSP-A library for efficient computation of symmetric open quantum systems.

PubMed

Gegg, Michael; Richter, Marten

2017-11-24

In a recent publication we showed that permutation symmetry reduces the numerical complexity of Lindblad quantum master equations for identical multi-level systems from exponential to polynomial scaling. This is important for open system dynamics including realistic system bath interactions and dephasing in, for instance, the Dicke model, multi-Λ system setups etc. Here we present an object-oriented C++ library that allows to setup and solve arbitrary quantum optical Lindblad master equations, especially those that are permutationally symmetric in the multi-level systems. PsiQuaSP (Permutation symmetry for identical Quantum Systems Package) uses the PETSc package for sparse linear algebra methods and differential equations as basis. The aim of PsiQuaSP is to provide flexible, storage efficient and scalable code while being as user friendly as possible. It is easily applied to many quantum optical or quantum information systems with more than one multi-level system. We first review the basics of the permutation symmetry for multi-level systems in quantum master equations. The application of PsiQuaSP to quantum dynamical problems is illustrated with several typical, simple examples of open quantum optical systems.

Improving multilevel Monte Carlo for stochastic differential equations with application to the Langevin equation

PubMed Central

Müller, Eike H.; Scheichl, Rob; Shardlow, Tony

2015-01-01

This paper applies several well-known tricks from the numerical treatment of deterministic differential equations to improve the efficiency of the multilevel Monte Carlo (MLMC) method for stochastic differential equations (SDEs) and especially the Langevin equation. We use modified equations analysis as an alternative to strong-approximation theory for the integrator, and we apply this to introduce MLMC for Langevin-type equations with integrators based on operator splitting. We combine this with extrapolation and investigate the use of discrete random variables in place of the Gaussian increments, which is a well-known technique for the weak approximation of SDEs. We show that, for small-noise problems, discrete random variables can lead to an increase in efficiency of almost two orders of magnitude for practical levels of accuracy. PMID:27547075

Improving multilevel Monte Carlo for stochastic differential equations with application to the Langevin equation.

PubMed

Müller, Eike H; Scheichl, Rob; Shardlow, Tony

2015-04-08

This paper applies several well-known tricks from the numerical treatment of deterministic differential equations to improve the efficiency of the multilevel Monte Carlo (MLMC) method for stochastic differential equations (SDEs) and especially the Langevin equation. We use modified equations analysis as an alternative to strong-approximation theory for the integrator, and we apply this to introduce MLMC for Langevin-type equations with integrators based on operator splitting. We combine this with extrapolation and investigate the use of discrete random variables in place of the Gaussian increments, which is a well-known technique for the weak approximation of SDEs. We show that, for small-noise problems, discrete random variables can lead to an increase in efficiency of almost two orders of magnitude for practical levels of accuracy.

Displacement Based Multilevel Structural Optimization

NASA Technical Reports Server (NTRS)

Sobieszezanski-Sobieski, J.; Striz, A. G.

1996-01-01

In the complex environment of true multidisciplinary design optimization (MDO), efficiency is one of the most desirable attributes of any approach. In the present research, a new and highly efficient methodology for the MDO subset of structural optimization is proposed and detailed, i.e., for the weight minimization of a given structure under size, strength, and displacement constraints. Specifically, finite element based multilevel optimization of structures is performed. In the system level optimization, the design variables are the coefficients of assumed polynomially based global displacement functions, and the load unbalance resulting from the solution of the global stiffness equations is minimized. In the subsystems level optimizations, the weight of each element is minimized under the action of stress constraints, with the cross sectional dimensions as design variables. The approach is expected to prove very efficient since the design task is broken down into a large number of small and efficient subtasks, each with a small number of variables, which are amenable to parallel computing.

Block structured adaptive mesh and time refinement for hybrid, hyperbolic + N-body systems

NASA Astrophysics Data System (ADS)

Miniati, Francesco; Colella, Phillip

2007-11-01

We present a new numerical algorithm for the solution of coupled collisional and collisionless systems, based on the block structured adaptive mesh and time refinement strategy (AMR). We describe the issues associated with the discretization of the system equations and the synchronization of the numerical solution on the hierarchy of grid levels. We implement a code based on a higher order, conservative and directionally unsplit Godunov’s method for hydrodynamics; a symmetric, time centered modified symplectic scheme for collisionless component; and a multilevel, multigrid relaxation algorithm for the elliptic equation coupling the two components. Numerical results that illustrate the accuracy of the code and the relative merit of various implemented schemes are also presented.

Quantitative Comparisons of a Coarse-Grid LES with Experimental Data for Backward-Facing Step Flow

NASA Astrophysics Data System (ADS)

McDonough, J. M.

1999-11-01

A novel approach to LES employing an additive decomposition of both solutions and governing equations (similar to ``multi-level'' approaches of Dubois et al.,Dynamic Multilevel Methods and the Simulation of Turbulence, Cambridge University Press, 1999) is presented; its main structural features are lack of filtering of governing equations (instead, solutions are filtered to remove aliasing due to under resolution) and direct modeling of subgrid-scale primitive variables (rather than modeling their correlations) in the manner proposed by Hylin and McDonough (Int. J. Fluid Mech. Res. 26, 228-256, 1999). A 2-D implementation of this formalism is applied to the backward-facing step flow studied experimentally by Driver and Seegmiller (AIAA J. 23, 163-171, 1985) and Driver et al. (AIAA J. 25, 914-919, 1987), and run on grids sufficiently coarse to permit easy extension to 3-D, industrially-realistic problems. Comparisons of computed and experimental mean quantities (velocity profiles, turbulence kinetic energy, reattachment lengths, etc.) and effects of grid refinement will be presented.

A closed-loop multi-level model of glucose homeostasis

PubMed Central

Uluseker, Cansu; Simoni, Giulia; Dauriz, Marco; Matone, Alice

2018-01-01

Background The pathophysiologic processes underlying the regulation of glucose homeostasis are considerably complex at both cellular and systemic level. A comprehensive and structured specification for the several layers of abstraction of glucose metabolism is often elusive, an issue currently solvable with the hierarchical description provided by multi-level models. In this study we propose a multi-level closed-loop model of whole-body glucose homeostasis, coupled with the molecular specifications of the insulin signaling cascade in adipocytes, under the experimental conditions of normal glucose regulation and type 2 diabetes. Methodology/Principal findings The ordinary differential equations of the model, describing the dynamics of glucose and key regulatory hormones and their reciprocal interactions among gut, liver, muscle and adipose tissue, were designed for being embedded in a modular, hierarchical structure. The closed-loop model structure allowed self-sustained simulations to represent an ideal in silico subject that adjusts its own metabolism to the fasting and feeding states, depending on the hormonal context and invariant to circadian fluctuations. The cellular level of the model provided a seamless dynamic description of the molecular mechanisms downstream the insulin receptor in the adipocytes by accounting for variations in the surrounding metabolic context. Conclusions/Significance The combination of a multi-level and closed-loop modeling approach provided a fair dynamic description of the core determinants of glucose homeostasis at both cellular and systemic scales. This model architecture is intrinsically open to incorporate supplementary layers of specifications describing further individual components influencing glucose metabolism. PMID:29420588

Determining the Effects of Pre-College STEM Contexts on STEM Major Choices in 4-Year Postsecondary Institutions Using Multilevel Structural Equation Modeling

ERIC Educational Resources Information Center

Lee, Ahlam

2013-01-01

Many STEM studies have focused on traditional learning contexts, such as math- and science-related learning factors, as pre-college learning predictors for STEM major choices in colleges. Few studies have considered a progressive learning activity embedded within STEM contexts. This study chose computer-based learning activities in K-12 math…

Multilevel ensemble Kalman filtering

DOE PAGES

Hoel, Hakon; Law, Kody J. H.; Tempone, Raul

2016-06-14

This study embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discrete-time observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. Finally, the resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.

Comparing methods of analysing datasets with small clusters: case studies using four paediatric datasets.

PubMed

Marston, Louise; Peacock, Janet L; Yu, Keming; Brocklehurst, Peter; Calvert, Sandra A; Greenough, Anne; Marlow, Neil

2009-07-01

Studies of prematurely born infants contain a relatively large percentage of multiple births, so the resulting data have a hierarchical structure with small clusters of size 1, 2 or 3. Ignoring the clustering may lead to incorrect inferences. The aim of this study was to compare statistical methods which can be used to analyse such data: generalised estimating equations, multilevel models, multiple linear regression and logistic regression. Four datasets which differed in total size and in percentage of multiple births (n = 254, multiple 18%; n = 176, multiple 9%; n = 10 098, multiple 3%; n = 1585, multiple 8%) were analysed. With the continuous outcome, two-level models produced similar results in the larger dataset, while generalised least squares multilevel modelling (ML GLS 'xtreg' in Stata) and maximum likelihood multilevel modelling (ML MLE 'xtmixed' in Stata) produced divergent estimates using the smaller dataset. For the dichotomous outcome, most methods, except generalised least squares multilevel modelling (ML GH 'xtlogit' in Stata) gave similar odds ratios and 95% confidence intervals within datasets. For the continuous outcome, our results suggest using multilevel modelling. We conclude that generalised least squares multilevel modelling (ML GLS 'xtreg' in Stata) and maximum likelihood multilevel modelling (ML MLE 'xtmixed' in Stata) should be used with caution when the dataset is small. Where the outcome is dichotomous and there is a relatively large percentage of non-independent data, it is recommended that these are accounted for in analyses using logistic regression with adjusted standard errors or multilevel modelling. If, however, the dataset has a small percentage of clusters greater than size 1 (e.g. a population dataset of children where there are few multiples) there appears to be less need to adjust for clustering.

An Investigation of the Linkage between Technology-Based Activities and STEM Major Selection in 4-Year Postsecondary Institutions in the United States: Multilevel Structural Equation Modelling

ERIC Educational Resources Information Center

Lee, Ahlam

2015-01-01

Among the disciplines of science, technology, engineering, and math (STEM), much attention has been paid to the influences of math- and science-related learning contexts on students' STEM major selection. However, the technology and engineering learning contexts that are linked to STEM major selection have been overlooked. In response, a…

A multilevel cross-lagged structural equation analysis for reciprocal relationship between social capital and health.

PubMed

Yu, Ge; Sessions, John G; Fu, Yu; Wall, Martin

2015-10-01

We investigated the reciprocal relationship between individual social capital and perceived mental and physical health in the UK. Using data from the British Household Panel Survey from 1991 to 2008, we fitted cross-lagged structural equation models that include three indicators of social capital vis. social participation, social network, and loneliness. Given that multiple measurement points (level 1) are nested within individuals (level 2), we also applied a multilevel model to allow for residual variation in the outcomes at the occasion and individual levels. Controlling for gender, age, employment status, educational attainment, marital status, household wealth, and region, our analyses suggest that social participation predicts subsequent change in perceived mental health, and vice versa. However, whilst loneliness is found to be significantly related to perceived mental and physical health, reciprocal causality is not found for perceived mental health. Furthermore, we find evidence for reverse effects with both perceived mental and physical health appearing to be the dominant causal factor with respect to the prospective level of social network. Our findings thus shed further light on the importance of social participation and social inclusion in health promotion and aid the development of more effective public health policies in the UK. Copyright © 2015 Elsevier Ltd. All rights reserved.

Analyzing latent state-trait and multiple-indicator latent growth curve models as multilevel structural equation models

PubMed Central

Geiser, Christian; Bishop, Jacob; Lockhart, Ginger; Shiffman, Saul; Grenard, Jerry L.

2013-01-01

Latent state-trait (LST) and latent growth curve (LGC) models are frequently used in the analysis of longitudinal data. Although it is well-known that standard single-indicator LGC models can be analyzed within either the structural equation modeling (SEM) or multilevel (ML; hierarchical linear modeling) frameworks, few researchers realize that LST and multivariate LGC models, which use multiple indicators at each time point, can also be specified as ML models. In the present paper, we demonstrate that using the ML-SEM rather than the SL-SEM framework to estimate the parameters of these models can be practical when the study involves (1) a large number of time points, (2) individually-varying times of observation, (3) unequally spaced time intervals, and/or (4) incomplete data. Despite the practical advantages of the ML-SEM approach under these circumstances, there are also some limitations that researchers should consider. We present an application to an ecological momentary assessment study (N = 158 youths with an average of 23.49 observations of positive mood per person) using the software Mplus (Muthén and Muthén, 1998–2012) and discuss advantages and disadvantages of using the ML-SEM approach to estimate the parameters of LST and multiple-indicator LGC models. PMID:24416023

Space construction base control system

NASA Technical Reports Server (NTRS)

Kaczynski, R. F.

1979-01-01

Several approaches for an attitude control system are studied and developed for a large space construction base that is structurally flexible. Digital simulations were obtained using the following techniques: (1) the multivariable Nyquist array method combined with closed loop pole allocation, (2) the linear quadratic regulator method. Equations for the three-axis simulation using the multilevel control method were generated and are presented. Several alternate control approaches are also described. A technique is demonstrated for obtaining the dynamic structural properties of a vehicle which is constructed of two or more submodules of known dynamic characteristics.

Multilevel Structural Equation Models for Investigating the Effects of Computer-Based Learning in Math Classrooms on Science Technology Engineering and Math (STEM) Major Selection in 4-Year Postsecondary Institutions

ERIC Educational Resources Information Center

Lee, Ahlam

2017-01-01

Background/Context: Because of the growing concern over the decline of bachelor degree recipients in the disciplines of science, technology, engineering, and math (STEM) in the U.S., several studies have been devoted to identifying the factors that affect students' STEM major choices. A majority of these studies have focused on factors relevant to…

Assessing the multidimensional and hierarchical structure of SERVQUAL.

PubMed

Ma, Jun; Harvey, Milton E; Hu, Michael Y

2007-10-01

Parasuraman, Zeithaml, and Berry introduced SERVQUAL in 1998 as a scale to measure service quality. Since then, researchers have proposed several variations. This study examines the development of the tool. Marketing researchers have first challenged the conceptualization of a perceptions-expectations gap and have concluded that the performance-based measures are adequate to capture consumers' perception of service quality. Some researchers have argued that the five dimensions of the SERVQUAL scale only focus on the process of service delivery and have extended the SERVQUAL scale into six dimensions by including the service outcome dimension. Others have proposed that service quality is a multilevel construct and should be measured accordingly. From a sample of 467 undergraduate students data on service quality toward up-scale restaurants were collected. Using the structural equation approach, two measurement models of service quality were compared, the extended SERVQUAL model and the restructured multilevel SERVQUAL model. Analysis suggested that the latter model fits the data better than the extended one.

Effect of Differential Item Functioning on Test Equating

ERIC Educational Resources Information Center

Kabasakal, Kübra Atalay; Kelecioglu, Hülya

2015-01-01

This study examines the effect of differential item functioning (DIF) items on test equating through multilevel item response models (MIRMs) and traditional IRMs. The performances of three different equating models were investigated under 24 different simulation conditions, and the variables whose effects were examined included sample size, test…

Multilevel Preconditioners for Reaction-Diffusion Problems with Discontinuous Coefficients

DOE PAGES

Kolev, Tzanio V.; Xu, Jinchao; Zhu, Yunrong

2015-08-23

In this study, we extend some of the multilevel convergence results obtained by Xu and Zhu, to the case of second order linear reaction-diffusion equations. Specifically, we consider the multilevel preconditioners for solving the linear systems arising from the linear finite element approximation of the problem, where both diffusion and reaction coefficients are piecewise-constant functions. We discuss in detail the influence of both the discontinuous reaction and diffusion coefficients to the performance of the classical BPX and multigrid V-cycle preconditioner.

Master equation theory applied to the redistribution of polarized radiation in the weak radiation field limit. III. Theory for the multilevel atom

NASA Astrophysics Data System (ADS)

Bommier, Véronique

2016-06-01

Context. We discuss the case of lines formed by scattering, which comprises both coherent and incoherent scattering. Both processes contribute to form the line profiles in the so-called second solar spectrum, which is the spectrum of the linear polarization of such lines observed close to the solar limb. However, most of the lines cannot be simply modeled with a two-level or two-term atom model, and we present a generalized formalism for this purpose. Aims: The aim is to obtain a formalism that is able to describe scattering in line centers (resonant scattering or incoherent scattering) and in far wings (Rayleigh/Raman scattering or coherent scattering) for a multilevel and multiline atom. Methods: The method is designed to overcome the Markov approximation, which is often performed in the atom-photon interaction description. The method was already presented in the two first papers of this series, but the final equations of those papers were for a two-level atom. Results: We present here the final equations generalized for the multilevel and multiline atom. We describe the main steps of the theoretical development, and, in particular, how we performed the series development to overcome the Markov approximation. Conclusions: The statistical equilibrium equations for the atomic density matrix and the radiative transfer equation coefficients are obtained with line profiles. The Doppler redistribution is also taken into account because we show that the statistical equilibrium equations must be solved for each atomic velocity class.

Multilevel Sequential Monte Carlo Samplers for Normalizing Constants

DOE PAGES

Moral, Pierre Del; Jasra, Ajay; Law, Kody J. H.; ...

2017-08-24

This article considers the sequential Monte Carlo (SMC) approximation of ratios of normalizing constants associated to posterior distributions which in principle rely on continuum models. Therefore, the Monte Carlo estimation error and the discrete approximation error must be balanced. A multilevel strategy is utilized to substantially reduce the cost to obtain a given error level in the approximation as compared to standard estimators. Two estimators are considered and relative variance bounds are given. The theoretical results are numerically illustrated for two Bayesian inverse problems arising from elliptic partial differential equations (PDEs). The examples involve the inversion of observations of themore » solution of (i) a 1-dimensional Poisson equation to infer the diffusion coefficient, and (ii) a 2-dimensional Poisson equation to infer the external forcing.« less

Modeling Floor Effects in Standardized Vocabulary Test Scores in a Sample of Low SES Hispanic Preschool Children under the Multilevel Structural Equation Modeling Framework.

PubMed

Zhu, Leina; Gonzalez, Jorge

2017-01-01

Researchers and practitioners often use standardized vocabulary tests such as the Peabody Picture Vocabulary Test-4 (PPVT-4; Dunn and Dunn, 2007) and its companion, the Expressive Vocabulary Test-2 (EVT-2; Williams, 2007), to assess English vocabulary skills as an indicator of children's school readiness. Despite their psychometric excellence in the norm sample, issues arise when standardized vocabulary tests are used to asses children from culturally, linguistically and ethnically diverse backgrounds (e.g., Spanish-speaking English language learners) or delayed in some manner. One of the biggest challenges is establishing the appropriateness of these measures with non-English or non-standard English speaking children as often they score one to two standard deviations below expected levels (e.g., Lonigan et al., 2013). This study re-examines the issues in analyzing the PPVT-4 and EVT-2 scores in a sample of 4-to-5-year-old low SES Hispanic preschool children who were part of a larger randomized clinical trial on the effects of a supplemental English shared-reading vocabulary curriculum (Pollard-Durodola et al., 2016). It was found that data exhibited strong floor effects and the presence of floor effects made it difficult to differentiate the invention group and the control group on their vocabulary growth in the intervention. A simulation study is then presented under the multilevel structural equation modeling (MSEM) framework and results revealed that in regular multilevel data analysis, ignoring floor effects in the outcome variables led to biased results in parameter estimates, standard error estimates, and significance tests. Our findings suggest caution in analyzing and interpreting scores of ethnically and culturally diverse children on standardized vocabulary tests (e.g., floor effects). It is recommended appropriate analytical methods that take into account floor effects in outcome variables should be considered.

On the Multilevel Nature of Meta-Analysis: A Tutorial, Comparison of Software Programs, and Discussion of Analytic Choices.

PubMed

Pastor, Dena A; Lazowski, Rory A

2018-01-01

The term "multilevel meta-analysis" is encountered not only in applied research studies, but in multilevel resources comparing traditional meta-analysis to multilevel meta-analysis. In this tutorial, we argue that the term "multilevel meta-analysis" is redundant since all meta-analysis can be formulated as a special kind of multilevel model. To clarify the multilevel nature of meta-analysis the four standard meta-analytic models are presented using multilevel equations and fit to an example data set using four software programs: two specific to meta-analysis (metafor in R and SPSS macros) and two specific to multilevel modeling (PROC MIXED in SAS and HLM). The same parameter estimates are obtained across programs underscoring that all meta-analyses are multilevel in nature. Despite the equivalent results, not all software programs are alike and differences are noted in the output provided and estimators available. This tutorial also recasts distinctions made in the literature between traditional and multilevel meta-analysis as differences between meta-analytic choices, not between meta-analytic models, and provides guidance to inform choices in estimators, significance tests, moderator analyses, and modeling sequence. The extent to which the software programs allow flexibility with respect to these decisions is noted, with metafor emerging as the most favorable program reviewed.

Integrated structure/control law design by multilevel optimization

NASA Technical Reports Server (NTRS)

Gilbert, Michael G.; Schmidt, David K.

1989-01-01

A new approach to integrated structure/control law design based on multilevel optimization is presented. This new approach is applicable to aircraft and spacecraft and allows for the independent design of the structure and control law. Integration of the designs is achieved through use of an upper level coordination problem formulation within the multilevel optimization framework. The method requires the use of structure and control law design sensitivity information. A general multilevel structure/control law design problem formulation is given, and the use of Linear Quadratic Gaussian (LQG) control law design and design sensitivity methods within the formulation is illustrated. Results of three simple integrated structure/control law design examples are presented. These results show the capability of structure and control law design tradeoffs to improve controlled system performance within the multilevel approach.

Integrable time-dependent Hamiltonians, solvable Landau-Zener models and Gaudin magnets

NASA Astrophysics Data System (ADS)

Yuzbashyan, Emil A.

2018-05-01

We solve the non-stationary Schrödinger equation for several time-dependent Hamiltonians, such as the BCS Hamiltonian with an interaction strength inversely proportional to time, periodically driven BCS and linearly driven inhomogeneous Dicke models as well as various multi-level Landau-Zener tunneling models. The latter are Demkov-Osherov, bow-tie, and generalized bow-tie models. We show that these Landau-Zener problems and their certain interacting many-body generalizations map to Gaudin magnets in a magnetic field. Moreover, we demonstrate that the time-dependent Schrödinger equation for the above models has a similar structure and is integrable with a similar technique as Knizhnik-Zamolodchikov equations. We also discuss applications of our results to the problem of molecular production in an atomic Fermi gas swept through a Feshbach resonance and to the evaluation of the Landau-Zener transition probabilities.

Culture Matters in Successful Curriculum Change: An International Study of the Influence of National and Organizational Culture Tested With Multilevel Structural Equation Modeling.

PubMed

Jippes, Mariëlle; Driessen, Erik W; Broers, Nick J; Majoor, Gerard D; Gijselaers, Wim H; van der Vleuten, Cees P M

2015-07-01

National culture has been shown to play a role in curriculum change in medical schools, and business literature has described a similar influence of organizational culture on change processes in organizations. This study investigated the impact of both national and organizational culture on successful curriculum change in medical schools internationally. The authors tested a literature-based conceptual model using multilevel structural equation modeling. For the operationalization of national and organizational culture, the authors used Hofstede's dimensions of culture and Quinn and Spreitzer's competing values framework, respectively. To operationalize successful curriculum change, the authors used two derivates: medical schools' organizational readiness for curriculum change developed by Jippes and colleagues, and change-related behavior developed by Herscovitch and Meyer. The authors administered a questionnaire in 2012 measuring the described operationalizations to medical schools in the process of changing their curriculum. Nine hundred ninety-one of 1,073 invited staff members from 131 of 345 medical schools in 56 of 80 countries completed the questionnaire. An initial poor fit of the model improved to a reasonable fit by two suggested modifications which seemed theoretically plausible. In sum, characteristics of national culture and organizational culture, such as a certain level of risk taking, flexible policies and procedures, and strong leadership, affected successful curriculum change. National and organizational culture influence readiness for change in medical schools. Therefore, medical schools considering curriculum reform should anticipate the potential impact of national and organizational culture.

Multidimensional radiative transfer with multilevel atoms. II. The non-linear multigrid method.

NASA Astrophysics Data System (ADS)

Fabiani Bendicho, P.; Trujillo Bueno, J.; Auer, L.

1997-08-01

A new iterative method for solving non-LTE multilevel radiative transfer (RT) problems in 1D, 2D or 3D geometries is presented. The scheme obtains the self-consistent solution of the kinetic and RT equations at the cost of only a few (<10) formal solutions of the RT equation. It combines, for the first time, non-linear multigrid iteration (Brandt, 1977, Math. Comp. 31, 333; Hackbush, 1985, Multi-Grid Methods and Applications, springer-Verlag, Berlin), an efficient multilevel RT scheme based on Gauss-Seidel iterations (cf. Trujillo Bueno & Fabiani Bendicho, 1995ApJ...455..646T), and accurate short-characteristics formal solution techniques. By combining a valid stopping criterion with a nested-grid strategy a converged solution with the desired true error is automatically guaranteed. Contrary to the current operator splitting methods the very high convergence speed of the new RT method does not deteriorate when the grid spatial resolution is increased. With this non-linear multigrid method non-LTE problems discretized on N grid points are solved in O(N) operations. The nested multigrid RT method presented here is, thus, particularly attractive in complicated multilevel transfer problems where small grid-sizes are required. The properties of the method are analyzed both analytically and with illustrative multilevel calculations for Ca II in 1D and 2D schematic model atmospheres.

A global multilevel atmospheric model using a vector semi-Lagrangian finite-difference scheme. I - Adiabatic formulation

NASA Technical Reports Server (NTRS)

Bates, J. R.; Moorthi, S.; Higgins, R. W.

1993-01-01

An adiabatic global multilevel primitive equation model using a two time-level, semi-Lagrangian semi-implicit finite-difference integration scheme is presented. A Lorenz grid is used for vertical discretization and a C grid for the horizontal discretization. The momentum equation is discretized in vector form, thus avoiding problems near the poles. The 3D model equations are reduced by a linear transformation to a set of 2D elliptic equations, whose solution is found by means of an efficient direct solver. The model (with minimal physics) is integrated for 10 days starting from an initialized state derived from real data. A resolution of 16 levels in the vertical is used, with various horizontal resolutions. The model is found to be stable and efficient, and to give realistic output fields. Integrations with time steps of 10 min, 30 min, and 1 h are compared, and the differences are found to be acceptable.

A taxonomy and comparison of parallel block multi-level preconditioners for the incompressible Navier-Stokes equations.

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

Shadid, John Nicolas; Elman, Howard; Shuttleworth, Robert R.

2007-04-01

In recent years, considerable effort has been placed on developing efficient and robust solution algorithms for the incompressible Navier-Stokes equations based on preconditioned Krylov methods. These include physics-based methods, such as SIMPLE, and purely algebraic preconditioners based on the approximation of the Schur complement. All these techniques can be represented as approximate block factorization (ABF) type preconditioners. The goal is to decompose the application of the preconditioner into simplified sub-systems in which scalable multi-level type solvers can be applied. In this paper we develop a taxonomy of these ideas based on an adaptation of a generalized approximate factorization of themore » Navier-Stokes system first presented in [25]. This taxonomy illuminates the similarities and differences among these preconditioners and the central role played by efficient approximation of certain Schur complement operators. We then present a parallel computational study that examines the performance of these methods and compares them to an additive Schwarz domain decomposition (DD) algorithm. Results are presented for two and three-dimensional steady state problems for enclosed domains and inflow/outflow systems on both structured and unstructured meshes. The numerical experiments are performed using MPSalsa, a stabilized finite element code.« less

Situational and dispositional influences on nurses' workplace well-being: the role of empowering unit leadership.

PubMed

Spence Laschinger, Heather K; Finegan, Joan; Wilk, Piotr

2011-01-01

Unit-level leadership and structural empowerment play key roles in creating healthy work environments, yet few researchers have examined these contextual effects on nurses' well-being. The aim of this study was to test a multilevel model of structural empowerment examining the effect of nursing unit leadership quality and structural empowerment on nurses' experiences of burnout and job satisfaction and to examine the effect of a personal dispositional variable, core self-evaluation, on these nurse experiences. Nurses (n = 3,156) from 217 hospital units returned surveys that included measures of leader-member exchange, structural empowerment, burnout, core self-evaluation, and job satisfaction. Multilevel structural equation modeling was used to test the model. Nurses' shared perceptions of leader-member exchange quality on their units positively influenced their shared perceptions of unit structural empowerment (Level 2), which resulted in significantly higher levels of individual nurse job satisfaction (Level 1). Unit-level leader-member exchange quality also directly influenced individual nurse job satisfaction. Unit leader-member exchange quality and structural empowerment influenced emotional exhaustion and cynicism differentially. Higher unit-level leader-member exchange quality was associated with lower cynicism; higher unit-level structural empowerment was associated with lower emotional exhaustion. At Level 1, higher core self-evaluation was associated with lower levels of both emotional exhaustion and cynicism, both of which were associated with lower job satisfaction. This study provides a theoretical understanding of how unit leadership affects both unit- and individual-level outcomes.

Parallel Element Agglomeration Algebraic Multigrid and Upscaling Library

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

Barker, Andrew T.; Benson, Thomas R.; Lee, Chak Shing

ParELAG is a parallel C++ library for numerical upscaling of finite element discretizations and element-based algebraic multigrid solvers. It provides optimal complexity algorithms to build multilevel hierarchies and solvers that can be used for solving a wide class of partial differential equations (elliptic, hyperbolic, saddle point problems) on general unstructured meshes. Additionally, a novel multilevel solver for saddle point problems with divergence constraint is implemented.

A Multilevel, Hierarchical Sampling Technique for Spatially Correlated Random Fields

DOE PAGES

Osborn, Sarah; Vassilevski, Panayot S.; Villa, Umberto

2017-10-26

In this paper, we propose an alternative method to generate samples of a spatially correlated random field with applications to large-scale problems for forward propagation of uncertainty. A classical approach for generating these samples is the Karhunen--Loève (KL) decomposition. However, the KL expansion requires solving a dense eigenvalue problem and is therefore computationally infeasible for large-scale problems. Sampling methods based on stochastic partial differential equations provide a highly scalable way to sample Gaussian fields, but the resulting parametrization is mesh dependent. We propose a multilevel decomposition of the stochastic field to allow for scalable, hierarchical sampling based on solving amore » mixed finite element formulation of a stochastic reaction-diffusion equation with a random, white noise source function. Lastly, numerical experiments are presented to demonstrate the scalability of the sampling method as well as numerical results of multilevel Monte Carlo simulations for a subsurface porous media flow application using the proposed sampling method.« less

A Multilevel, Hierarchical Sampling Technique for Spatially Correlated Random Fields

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

Osborn, Sarah; Vassilevski, Panayot S.; Villa, Umberto

In this paper, we propose an alternative method to generate samples of a spatially correlated random field with applications to large-scale problems for forward propagation of uncertainty. A classical approach for generating these samples is the Karhunen--Loève (KL) decomposition. However, the KL expansion requires solving a dense eigenvalue problem and is therefore computationally infeasible for large-scale problems. Sampling methods based on stochastic partial differential equations provide a highly scalable way to sample Gaussian fields, but the resulting parametrization is mesh dependent. We propose a multilevel decomposition of the stochastic field to allow for scalable, hierarchical sampling based on solving amore » mixed finite element formulation of a stochastic reaction-diffusion equation with a random, white noise source function. Lastly, numerical experiments are presented to demonstrate the scalability of the sampling method as well as numerical results of multilevel Monte Carlo simulations for a subsurface porous media flow application using the proposed sampling method.« less

Multigrid techniques for the solution of the passive scalar advection-diffusion equation

NASA Technical Reports Server (NTRS)

Phillips, R. E.; Schmidt, F. W.

1985-01-01

The solution of elliptic passive scalar advection-diffusion equations is required in the analysis of many turbulent flow and convective heat transfer problems. The accuracy of the solution may be affected by the presence of regions containing large gradients of the dependent variables. The multigrid concept of local grid refinement is a method for improving the accuracy of the calculations in these problems. In combination with the multilevel acceleration techniques, an accurate and efficient computational procedure is developed. In addition, a robust implementation of the QUICK finite-difference scheme is described. Calculations of a test problem are presented to quantitatively demonstrate the advantages of the multilevel-multigrid method.

The Impact of Ignoring the Level of Nesting Structure in Nonparametric Multilevel Latent Class Models

ERIC Educational Resources Information Center

Park, Jungkyu; Yu, Hsiu-Ting

2016-01-01

The multilevel latent class model (MLCM) is a multilevel extension of a latent class model (LCM) that is used to analyze nested structure data structure. The nonparametric version of an MLCM assumes a discrete latent variable at a higher-level nesting structure to account for the dependency among observations nested within a higher-level unit. In…

Computational electromagnetics: the physics of smooth versus oscillatory fields.

PubMed

Chew, W C

2004-03-15

This paper starts by discussing the difference in the physics between solutions to Laplace's equation (static) and Maxwell's equations for dynamic problems (Helmholtz equation). Their differing physical characters are illustrated by how the two fields convey information away from their source point. The paper elucidates the fact that their differing physical characters affect the use of Laplacian field and Helmholtz field in imaging. They also affect the design of fast computational algorithms for electromagnetic scattering problems. Specifically, a comparison is made between fast algorithms developed using wavelets, the simple fast multipole method, and the multi-level fast multipole algorithm for electrodynamics. The impact of the physical characters of the dynamic field on the parallelization of the multi-level fast multipole algorithm is also discussed. The relationship of diagonalization of translators to group theory is presented. Finally, future areas of research for computational electromagnetics are described.

A multilevel control system for the large space telescope. [numerical analysis/optimal control

NASA Technical Reports Server (NTRS)

Siljak, D. D.; Sundareshan, S. K.; Vukcevic, M. B.

1975-01-01

A multilevel scheme was proposed for control of Large Space Telescope (LST) modeled by a three-axis-six-order nonlinear equation. Local controllers were used on the subsystem level to stabilize motions corresponding to the three axes. Global controllers were applied to reduce (and sometimes nullify) the interactions among the subsystems. A multilevel optimization method was developed whereby local quadratic optimizations were performed on the subsystem level, and global control was again used to reduce (nullify) the effect of interactions. The multilevel stabilization and optimization methods are presented as general tools for design and then used in the design of the LST Control System. The methods are entirely computerized, so that they can accommodate higher order LST models with both conceptual and numerical advantages over standard straightforward design techniques.

Measuring psychosocial environments using individual responses: an application of multilevel factor analysis to examining students in schools.

PubMed

Dunn, Erin C; Masyn, Katherine E; Jones, Stephanie M; Subramanian, S V; Koenen, Karestan C

2015-07-01

Interest in understanding how psychosocial environments shape youth outcomes has grown considerably. School environments are of particular interest to prevention scientists as many prevention interventions are school-based. Therefore, effective conceptualization and operationalization of the school environment is critical. This paper presents an illustration of an emerging analytic method called multilevel factor analysis (MLFA) that provides an alternative strategy to conceptualize, measure, and model environments. MLFA decomposes the total sample variance-covariance matrix for variables measured at the individual level into within-cluster (e.g., student level) and between-cluster (e.g., school level) matrices and simultaneously models potentially distinct latent factor structures at each level. Using data from 79,362 students from 126 schools in the National Longitudinal Study of Adolescent to Adult Health (formerly known as the National Longitudinal Study of Adolescent Health), we use MLFA to show how 20 items capturing student self-reported behaviors and emotions provide information about both students (within level) and their school environment (between level). We identified four latent factors at the within level: (1) school adjustment, (2) externalizing problems, (3) internalizing problems, and (4) self-esteem. Three factors were identified at the between level: (1) collective school adjustment, (2) psychosocial environment, and (3) collective self-esteem. The finding of different and substantively distinct latent factor structures at each level emphasizes the need for prevention theory and practice to separately consider and measure constructs at each level of analysis. The MLFA method can be applied to other nested relationships, such as youth in neighborhoods, and extended to a multilevel structural equation model to better understand associations between environments and individual outcomes and therefore how to best implement preventive interventions.

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.

A multi-level solution algorithm for steady-state Markov chains

NASA Technical Reports Server (NTRS)

Horton, Graham; Leutenegger, Scott T.

1993-01-01

A new iterative algorithm, the multi-level algorithm, for the numerical solution of steady state Markov chains is presented. The method utilizes a set of recursively coarsened representations of the original system to achieve accelerated convergence. It is motivated by multigrid methods, which are widely used for fast solution of partial differential equations. Initial results of numerical experiments are reported, showing significant reductions in computation time, often an order of magnitude or more, relative to the Gauss-Seidel and optimal SOR algorithms for a variety of test problems. The multi-level method is compared and contrasted with the iterative aggregation-disaggregation algorithm of Takahashi.

Raetrad model extensions for radon entry into multi-level buildings with basements or crawl spaces.

PubMed

Nielson, K K; Rogers, V C; Rogers, V; Holt, R B

1997-10-01

The RAETRAD model was generalized to characterize radon generation and movement from soils and building materials into multi-level buildings with basements or crawl spaces. With the generalization, the model retains its original simplicity and ease of use. The model calculates radon entry rates that are consistent with measurements published for basement test structures at Colorado State University, confirming approximately equal contributions from diffusion and pressure-driven air flow at indoor-outdoor air pressure differences of deltaP(i-o) = -3.5 Pa. About one-fourth of the diffusive radon entry comes from concrete slabs and three-fourths comes from the surrounding soils. Calculated radon entry rates with and without a barrier over floor-wall shrinkage cracks generally agree with Colorado State University measurements when a sustained pressure of deltaP(i-o) = -2 Pa is used to represent calm wind (<1 m s(-1)) conditions. Calculated radon distributions in a 2-level house also are consistent with published measurements and equations.

Using iMCFA to Perform the CFA, Multilevel CFA, and Maximum Model for Analyzing Complex Survey Data.

PubMed

Wu, Jiun-Yu; Lee, Yuan-Hsuan; Lin, John J H

2018-01-01

To construct CFA, MCFA, and maximum MCFA with LISREL v.8 and below, we provide iMCFA (integrated Multilevel Confirmatory Analysis) to examine the potential multilevel factorial structure in the complex survey data. Modeling multilevel structure for complex survey data is complicated because building a multilevel model is not an infallible statistical strategy unless the hypothesized model is close to the real data structure. Methodologists have suggested using different modeling techniques to investigate potential multilevel structure of survey data. Using iMCFA, researchers can visually set the between- and within-level factorial structure to fit MCFA, CFA and/or MAX MCFA models for complex survey data. iMCFA can then yield between- and within-level variance-covariance matrices, calculate intraclass correlations, perform the analyses and generate the outputs for respective models. The summary of the analytical outputs from LISREL is gathered and tabulated for further model comparison and interpretation. iMCFA also provides LISREL syntax of different models for researchers' future use. An empirical and a simulated multilevel dataset with complex and simple structures in the within or between level was used to illustrate the usability and the effectiveness of the iMCFA procedure on analyzing complex survey data. The analytic results of iMCFA using Muthen's limited information estimator were compared with those of Mplus using Full Information Maximum Likelihood regarding the effectiveness of different estimation methods.

The Consequences of Ignoring Individuals' Mobility in Multilevel Growth Models: A Monte Carlo Study

ERIC Educational Resources Information Center

Luo, Wen; Kwok, Oi-man

2012-01-01

In longitudinal multilevel studies, especially in educational settings, it is fairly common that participants change their group memberships over time (e.g., students switch to different schools). Participant's mobility changes the multilevel data structure from a purely hierarchical structure with repeated measures nested within individuals and…

On the Multilevel Solution Algorithm for Markov Chains

NASA Technical Reports Server (NTRS)

Horton, Graham

1997-01-01

We discuss the recently introduced multilevel algorithm for the steady-state solution of Markov chains. The method is based on an aggregation principle which is well established in the literature and features a multiplicative coarse-level correction. Recursive application of the aggregation principle, which uses an operator-dependent coarsening, yields a multi-level method which has been shown experimentally to give results significantly faster than the typical methods currently in use. When cast as a multigrid-like method, the algorithm is seen to be a Galerkin-Full Approximation Scheme with a solution-dependent prolongation operator. Special properties of this prolongation lead to the cancellation of the computationally intensive terms of the coarse-level equations.

Error and Complexity Analysis for a Collocation-Grid-Projection Plus Precorrected-FFT Algorithm for Solving Potential Integral Equations with LaPlace or Helmholtz Kernels

NASA Technical Reports Server (NTRS)

Phillips, J. R.

1996-01-01

In this paper we derive error bounds for a collocation-grid-projection scheme tuned for use in multilevel methods for solving boundary-element discretizations of potential integral equations. The grid-projection scheme is then combined with a precorrected FFT style multilevel method for solving potential integral equations with 1/r and e(sup ikr)/r kernels. A complexity analysis of this combined method is given to show that for homogeneous problems, the method is order n natural log n nearly independent of the kernel. In addition, it is shown analytically and experimentally that for an inhomogeneity generated by a very finely discretized surface, the combined method slows to order n(sup 4/3). Finally, examples are given to show that the collocation-based grid-projection plus precorrected-FFT scheme is competitive with fast-multipole algorithms when considering realistic problems and 1/r kernels, but can be used over a range of spatial frequencies with only a small performance penalty.

A multivariate multilevel Gaussian model with a mixed effects structure in the mean and covariance part.

PubMed

Li, Baoyue; Bruyneel, Luk; Lesaffre, Emmanuel

2014-05-20

A traditional Gaussian hierarchical model assumes a nested multilevel structure for the mean and a constant variance at each level. We propose a Bayesian multivariate multilevel factor model that assumes a multilevel structure for both the mean and the covariance matrix. That is, in addition to a multilevel structure for the mean we also assume that the covariance matrix depends on covariates and random effects. This allows to explore whether the covariance structure depends on the values of the higher levels and as such models heterogeneity in the variances and correlation structure of the multivariate outcome across the higher level values. The approach is applied to the three-dimensional vector of burnout measurements collected on nurses in a large European study to answer the research question whether the covariance matrix of the outcomes depends on recorded system-level features in the organization of nursing care, but also on not-recorded factors that vary with countries, hospitals, and nursing units. Simulations illustrate the performance of our modeling approach. Copyright © 2013 John Wiley & Sons, Ltd.

Coarse mesh and one-cell block inversion based diffusion synthetic acceleration

NASA Astrophysics Data System (ADS)

Kim, Kang-Seog

DSA (Diffusion Synthetic Acceleration) has been developed to accelerate the SN transport iteration. We have developed solution techniques for the diffusion equations of FLBLD (Fully Lumped Bilinear Discontinuous), SCB (Simple Comer Balance) and UCB (Upstream Corner Balance) modified 4-step DSA in x-y geometry. Our first multi-level method includes a block Gauss-Seidel iteration for the discontinuous diffusion equation, uses the continuous diffusion equation derived from the asymptotic analysis, and avoids void cell calculation. We implemented this multi-level procedure and performed model problem calculations. The results showed that the FLBLD, SCB and UCB modified 4-step DSA schemes with this multi-level technique are unconditionally stable and rapidly convergent. We suggested a simplified multi-level technique for FLBLD, SCB and UCB modified 4-step DSA. This new procedure does not include iterations on the diffusion calculation or the residual calculation. Fourier analysis results showed that this new procedure was as rapidly convergent as conventional modified 4-step DSA. We developed new DSA procedures coupled with 1-CI (Cell Block Inversion) transport which can be easily parallelized. We showed that 1-CI based DSA schemes preceded by SI (Source Iteration) are efficient and rapidly convergent for LD (Linear Discontinuous) and LLD (Lumped Linear Discontinuous) in slab geometry and for BLD (Bilinear Discontinuous) and FLBLD in x-y geometry. For 1-CI based DSA without SI in slab geometry, the results showed that this procedure is very efficient and effective for all cases. We also showed that 1-CI based DSA in x-y geometry was not effective for thin mesh spacings, but is effective and rapidly convergent for intermediate and thick mesh spacings. We demonstrated that the diffusion equation discretized on a coarse mesh could be employed to accelerate the transport equation. Our results showed that coarse mesh DSA is unconditionally stable and is as rapidly convergent as fine mesh DSA in slab geometry. For x-y geometry our coarse mesh DSA is very effective for thin and intermediate mesh spacings independent of the scattering ratio, but is not effective for purely scattering problems and high aspect ratio zoning. However, if the scattering ratio is less than about 0.95, this procedure is very effective for all mesh spacing.

Final Technical Report for "Applied Mathematics Research: Simulation Based Optimization and Application to Electromagnetic Inverse Problems"

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

Haber, Eldad

2014-03-17

The focus of research was: Developing adaptive mesh for the solution of Maxwell's equations; Developing a parallel framework for time dependent inverse Maxwell's equations; Developing multilevel methods for optimization problems with inequality constraints; A new inversion code for inverse Maxwell's equations in the 0th frequency (DC resistivity); A new inversion code for inverse Maxwell's equations in low frequency regime. Although the research concentrated on electromagnetic forward and in- verse problems the results of the research was applied to the problem of image registration.

Inversion of magnetotelluric data using integral equation approach with variable sensitivity domain: Application to EarthScope MT data

NASA Astrophysics Data System (ADS)

Čuma, Martin; Gribenko, Alexander; Zhdanov, Michael S.

2017-09-01

We have developed a multi-level parallel magnetotelluric (MT) integral equation based inversion program which uses variable sensitivity domain. The limited sensitivity of the data, which decreases with increasing frequency, is exploited by a receiver sensitivity domain, which also varies with frequency. We assess the effect of inverting principal impedances, full impedance tensor, and full tensor jointly with magnetovariational data (tipper). We first apply this method to several models and then invert the EarthScope MT data. We recover well the prominent features in the area including resistive structure associated with the Juan de Fuca slab subducting beneath the northwestern United States, the conductive zone of partially melted material above the subducting slab at the Cascade volcanic arc, conductive features in the Great Basin and in the area of Yellowstone associated with the hot spot, and resistive areas to the east corresponding to the older and more stable cratons.

Explaining Differences in Subjective Well-Being Across 33 Nations Using Multilevel Models: Universal Personality, Cultural Relativity, and National Income.

PubMed

Cheng, Cecilia; Cheung, Mike W-L; Montasem, Alex

2016-02-01

This multinational study simultaneously tested three prominent hypotheses--universal disposition, cultural relativity, and livability--that explained differences in subjective well-being across nations. We performed multilevel structural equation modeling to examine the hypothesized relationships at both individual and cultural levels in 33 nations. Participants were 6,753 university students (2,215 men; 4,403 women; 135 did not specify), and the average age of the entire sample was 20.97 years (SD = 2.39). Both individual- and cultural-level analyses supported the universal disposition and cultural relativity hypotheses by revealing significant associations of subjective well-being with Extraversion, Neuroticism, and independent self-construal. In addition, interdependent self-construal was positively related to life satisfaction at the individual level only, whereas aggregated negative affect was positively linked with aggregate levels of Extraversion and interdependent self-construal at the cultural level only. Consistent with the livability hypothesis, gross national income (GNI) was related to aggregate levels of negative affect and life satisfaction. There was also a quadratic relationship between GNI and aggregated positive affect. Our findings reveal that universal disposition, cultural self-construal, and national income can elucidate differences in subjective well-being, but the multilevel analyses advance the literature by yielding new findings that cannot be identified in studies using individual-level analyses alone. © 2014 Wiley Periodicals, Inc.

Leadership, Organizational Climate, and Working Alliance in a Children's Mental Health Service System

PubMed Central

Green, Amy E.; Albanese, Brian J.; Cafri, Guy; Aarons, Gregory A.

2014-01-01

The goal of this study was to examine the relationships of transformational leadership and organizational climate with working alliance, in a children's mental health service system. Using multilevel structural equation modeling, the effect of leadership on working alliance was mediated by organizational climate. These results suggest that supervisors may be able to impact quality of care through improving workplace climate. Organizational factors should be considered in efforts to improve public sector services. Understanding these issues is important for program leaders, mental health service providers, and consumers because they can affect both the way services are delivered and ultimately, clinical outcomes. PMID:24323137

Leadership, organizational climate, and working alliance in a children's mental health service system.

PubMed

Green, Amy E; Albanese, Brian J; Cafri, Guy; Aarons, Gregory A

2014-10-01

The goal of this study was to examine the relationships of transformational leadership and organizational climate with working alliance, in a children's mental health service system. Using multilevel structural equation modeling, the effect of leadership on working alliance was mediated by organizational climate. These results suggest that supervisors may be able to impact quality of care through improving workplace climate. Organizational factors should be considered in efforts to improve public sector services. Understanding these issues is important for program leaders, mental health service providers, and consumers because they can affect both the way services are delivered and ultimately, clinical outcomes.

Probabilistic sizing of laminates with uncertainties

NASA Technical Reports Server (NTRS)

Shah, A. R.; Liaw, D. G.; Chamis, C. C.

1993-01-01

A reliability based design methodology for laminate sizing and configuration for a special case of composite structures is described. The methodology combines probabilistic composite mechanics with probabilistic structural analysis. The uncertainties of constituent materials (fiber and matrix) to predict macroscopic behavior are simulated using probabilistic theory. Uncertainties in the degradation of composite material properties are included in this design methodology. A multi-factor interaction equation is used to evaluate load and environment dependent degradation of the composite material properties at the micromechanics level. The methodology is integrated into a computer code IPACS (Integrated Probabilistic Assessment of Composite Structures). Versatility of this design approach is demonstrated by performing a multi-level probabilistic analysis to size the laminates for design structural reliability of random type structures. The results show that laminate configurations can be selected to improve the structural reliability from three failures in 1000, to no failures in one million. Results also show that the laminates with the highest reliability are the least sensitive to the loading conditions.

Findings from Encontros: a multi-level STI/HIV intervention to increase condom use, reduce STI, and change the social environment among sex workers in Brazil

PubMed Central

Lippman, Sheri A.; Chinaglia, Magda; Donini, Angela A.; Diaz, Juan; Reingold, Arthur; Kerrigan, Deanna L.

2012-01-01

Background Sexually transmitted infection (STI)/HIV prevention programs which do not modify social-structural contexts that contribute to risk of STI/HIV may fail to bring about improvements in health, particularly among groups who experience discrimination and exclusion from public life. We conducted a multi-level intervention with sex workers, including improved clinical care and community mobilizing strategies to modify social-structural factors that shape sexual behavior, in order to improve condom use and reduce incident STI. Methods We followed 420 sex workers participating in the Encontros intervention in Corumbá, Brazil from 2003-2005. We estimated the effect of the intervention on incident chlamydia and gonorrhea infections and condom use using generalized estimating equations and inverse probability weighting by comparing those who actively engaged in the intervention activities (exposed) to those who were less engaged (unexposed). We also determined the association of participation on reported social cohesion and participation in networks. Results Exposed participants had significantly higher odds of reporting consistent condom use with regular clients (OR:1.9, 95%CI:1.1-3.3) and non-significantly increased odds with both new clients (OR:1.6, 0.9-2.8) and nonpaying partners (OR:1.5, 0.9-1.5). The odds of an incident STI were non-significantly reduced for exposed participants compared to unexposed (OR:0.46, 0.2-1.3). Participation was significantly associated with increased perceived cohesion and participation in networks. Conclusion This prospective study provides evidence that multi-level interventions with mobilizing strategies to modify aspects of the social environment can improve condom use, reduce STIs, and increase social cohesion and participation in networks among sex workers. PMID:22337108

Findings from Encontros: a multilevel STI/HIV intervention to increase condom use, reduce STI, and change the social environment among sex workers in Brazil.

PubMed

Lippman, Sheri A; Chinaglia, Magda; Donini, Angela A; Diaz, Juan; Reingold, Arthur; Kerrigan, Deanna L

2012-03-01

Sexually transmitted infection (STI)/HIV prevention programs, which do not modify social structural contexts that contribute to risk of STI/HIV may fail to bring about improvements in health, particularly among groups who experience discrimination and exclusion from public life. We conducted a multilevel intervention with sex workers, including improved clinical care and community-mobilizing strategies to modify social structural factors that shape sexual behavior, to improve condom use and reduce incident STI. We followed 420 sex workers participating in the Encontros intervention in Corumbá, Brazil, between 2003 and 2005. We estimated the effect of the intervention on incident chlamydia and gonorrhea infections and condom use using generalized estimating equations and inverse probability weighting by comparing those who actively engaged in the intervention activities (exposed) with those who were less engaged (unexposed). We also determined the association of participation on reported social cohesion and participation in networks. Exposed participants had significantly higher odds of reporting consistent condom use with regular clients (odds ratio [OR]: 1.9, 95% confidence interval:1.1-3.3) and nonsignificantly increased odds with both new clients (OR: 1.6, 0.9-2.8) and nonpaying partners (OR: 1.5, 0.9-1.5). The odds of an incident STI were nonsignificantly reduced for exposed participants compared with unexposed (OR: 0.46, 0.2-1.3). Participation was significantly associated with increased perceived cohesion and participation in networks. This prospective study provides evidence that multilevel interventions with mobilizing strategies to modify aspects of the social environment can improve condom use, reduce STIs, and increase social cohesion and participation in networks among sex workers.

Data Mining of Web-Based Documents on Social Networking Sites That Included Suicide-Related Words Among Korean Adolescents.

PubMed

Song, Juyoung; Song, Tae Min; Seo, Dong-Chul; Jin, Jae Hyun

2016-12-01

To investigate online search activity of suicide-related words in South Korean adolescents through data mining of social media Web sites as the suicide rate in South Korea is one of the highest in the world. Out of more than 2.35 billion posts for 2 years from January 1, 2011 to December 31, 2012 on 163 social media Web sites in South Korea, 99,693 suicide-related documents were retrieved by Crawler and analyzed using text mining and opinion mining. These data were further combined with monthly employment rate, monthly rental prices index, monthly youth suicide rate, and monthly number of reported bully victims to fit multilevel models as well as structural equation models. The link from grade pressure to suicide risk showed the largest standardized path coefficient (beta = .357, p < .001) in structural models and a significant random effect (p < .01) in multilevel models. Depression was a partial mediator between suicide risk and grade pressure, low body image, victims of bullying, and concerns about disease. The largest total effect was observed in the grade pressure to depression to suicide risk. The multilevel models indicate about 27% of the variance in the daily suicide-related word search activity is explained by month-to-month variations. A lower employment rate, a higher rental prices index, and more bullying were associated with an increased suicide-related word search activity. Academic pressure appears to be the biggest contributor to Korean adolescents' suicide risk. Real-time suicide-related word search activity monitoring and response system needs to be developed. Copyright © 2016 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

A Teacher-Focused Intervention to Decrease PE Students' Amotivation by Increasing Need Satisfaction and Decreasing Need Frustration.

PubMed

Cheon, Sung Hyeon; Reeve, Johnmarshall; Song, Yong-Gwan

2016-06-01

Intervention-induced gains in need satisfaction decrease PE students' amotivation. The present study adopted a dual-process model to test whether an intervention could also decrease need frustration and hence provide a second supplemental source to further decrease students' PE amotivation. Using an experimental, longitudinal research design, 19 experienced PE teachers (9 experimental, 10 control) and their 1,017 students participated in an intervention program to help teachers become both more autonomy supportive and less controlling. Multilevel repeated measures analyses showed that students of teachers in the experimental group reported greater T2, T3, and T4 perceived autonomy support, need satisfaction, and engagement and lesser T2, T3, and T4 perceived teacher control, need frustration, and amotivation than did students of teachers in the control group. Multilevel structural equation modeling analyses confirmed the hypothesized dual-process model in which both intervention-induced increases in need satisfaction and intervention-induced decreases need frustration decreased students' end-of-semester amotivation. We discuss the theoretical and practical implications of this new finding on the dual antecedents of diminished amotivation.

Modeling of the multilevel conduction characteristics and fatigue profile of Ag/La1/3Ca2/3MnO3/Pt structures using a compact memristive approach

NASA Astrophysics Data System (ADS)

Miranda, E.; Román Acevedo, W.; Rubi, D.; Lüders, U.; Granell, P.; Suñé, J.; Levy, P.

2017-05-01

The hysteretic conduction characteristics and fatigue profile of La1/3Ca2/3MnO3 (LCMO)-based memristive devices were investigated. The oxide films were grown by pulsed laser deposition (PLD) and sandwiched between Ag and Pt electrodes. The devices exhibit bipolar resistive switching (RS) effect with well-defined intermediate conduction states that arise from partial SET and RESET events. The current-voltage curves are modeled and simulated using a compact memristive approach. Two equations are considered: one for the electron transport based on the double-diode equation and the other for the memory state of the device driven by the play operator with logistic ridge functions. An expression that accounts for the remnant resistance of the device is obtained after simplifying the model equations in the low-voltage limit. The role played by the power dissipation in the LCMO reset dynamics as well as the asymmetrical reduction of the resistance window caused by long trains of switching pulses are discussed.

A Methodological Review of Statistical Methods for Handling Multilevel Non-Nested Longitudinal Data in Educational Research

ERIC Educational Resources Information Center

Sun, Shuyan; Pan, Wei

2014-01-01

As applications of multilevel modelling in educational research increase, researchers realize that multilevel data collected in many educational settings are often not purely nested. The most common multilevel non-nested data structure is one that involves student mobility in longitudinal studies. This article provides a methodological review of…

Application of a multi-level grid method to transonic flow calculations

NASA Technical Reports Server (NTRS)

South, J. C., Jr.; Brandt, A.

1976-01-01

A multi-level grid method was studied as a possible means of accelerating convergence in relaxation calculations for transonic flows. The method employs a hierarchy of grids, ranging from very coarse to fine. The coarser grids are used to diminish the magnitude of the smooth part of the residuals. The method was applied to the solution of the transonic small disturbance equation for the velocity potential in conservation form. Nonlifting transonic flow past a parabolic arc airfoil is studied with meshes of both constant and variable step size.

Multilevel Monte Carlo for two phase flow and Buckley–Leverett transport in random heterogeneous porous media

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

Müller, Florian, E-mail: florian.mueller@sam.math.ethz.ch; Jenny, Patrick, E-mail: jenny@ifd.mavt.ethz.ch; Meyer, Daniel W., E-mail: meyerda@ethz.ch

2013-10-01

Monte Carlo (MC) is a well known method for quantifying uncertainty arising for example in subsurface flow problems. Although robust and easy to implement, MC suffers from slow convergence. Extending MC by means of multigrid techniques yields the multilevel Monte Carlo (MLMC) method. MLMC has proven to greatly accelerate MC for several applications including stochastic ordinary differential equations in finance, elliptic stochastic partial differential equations and also hyperbolic problems. In this study, MLMC is combined with a streamline-based solver to assess uncertain two phase flow and Buckley–Leverett transport in random heterogeneous porous media. The performance of MLMC is compared tomore » MC for a two dimensional reservoir with a multi-point Gaussian logarithmic permeability field. The influence of the variance and the correlation length of the logarithmic permeability on the MLMC performance is studied.« less

A Review of Structure Construction of Silk Fibroin Biomaterials from Single Structures to Multi-Level Structures.

PubMed

Qi, Yu; Wang, Hui; Wei, Kai; Yang, Ya; Zheng, Ru-Yue; Kim, Ick Soo; Zhang, Ke-Qin

2017-03-03

The biological performance of artificial biomaterials is closely related to their structure characteristics. Cell adhesion, migration, proliferation, and differentiation are all strongly affected by the different scale structures of biomaterials. Silk fibroin (SF), extracted mainly from silkworms, has become a popular biomaterial due to its excellent biocompatibility, exceptional mechanical properties, tunable degradation, ease of processing, and sufficient supply. As a material with excellent processability, SF can be processed into various forms with different structures, including particulate, fiber, film, and three-dimensional (3D) porous scaffolds. This review discusses and summarizes the various constructions of SF-based materials, from single structures to multi-level structures, and their applications. In combination with single structures, new techniques for creating special multi-level structures of SF-based materials, such as micropatterning and 3D-printing, are also briefly addressed.

Assessing dose–response effects of national essential medicine policy in China: comparison of two methods for handling data with a stepped wedge-like design and hierarchical structure

PubMed Central

Ren, Yan; Yang, Min; Li, Qian; Pan, Jay; Chen, Fei; Li, Xiaosong; Meng, Qun

2017-01-01

Objectives To introduce multilevel repeated measures (RM) models and compare them with multilevel difference-in-differences (DID) models in assessing the linear relationship between the length of the policy intervention period and healthcare outcomes (dose–response effect) for data from a stepped-wedge design with a hierarchical structure. Design The implementation of national essential medicine policy (NEMP) in China was a stepped-wedge-like design of five time points with a hierarchical structure. Using one key healthcare outcome from the national NEMP surveillance data as an example, we illustrate how a series of multilevel DID models and one multilevel RM model can be fitted to answer some research questions on policy effects. Setting Routinely and annually collected national data on China from 2008 to 2012. Participants 34 506 primary healthcare facilities in 2675 counties of 31 provinces. Outcome measures Agreement and differences in estimates of dose–response effect and variation in such effect between the two methods on the logarithm-transformed total number of outpatient visits per facility per year (LG-OPV). Results The estimated dose–response effect was approximately 0.015 according to four multilevel DID models and precisely 0.012 from one multilevel RM model. Both types of model estimated an increase in LG-OPV by 2.55 times from 2009 to 2012, but 2–4.3 times larger SEs of those estimates were found by the multilevel DID models. Similar estimates of mean effects of covariates and random effects of the average LG-OPV among all levels in the example dataset were obtained by both types of model. Significant variances in the dose–response among provinces, counties and facilities were estimated, and the ‘lowest’ or ‘highest’ units by their dose–response effects were pinpointed only by the multilevel RM model. Conclusions For examining dose–response effect based on data from multiple time points with hierarchical structure and the stepped wedge-like designs, multilevel RM models are more efficient, convenient and informative than the multilevel DID models. PMID:28399510

A Review of Structure Construction of Silk Fibroin Biomaterials from Single Structures to Multi-Level Structures

PubMed Central

Qi, Yu; Wang, Hui; Wei, Kai; Yang, Ya; Zheng, Ru-Yue; Kim, Ick Soo; Zhang, Ke-Qin

2017-01-01

The biological performance of artificial biomaterials is closely related to their structure characteristics. Cell adhesion, migration, proliferation, and differentiation are all strongly affected by the different scale structures of biomaterials. Silk fibroin (SF), extracted mainly from silkworms, has become a popular biomaterial due to its excellent biocompatibility, exceptional mechanical properties, tunable degradation, ease of processing, and sufficient supply. As a material with excellent processability, SF can be processed into various forms with different structures, including particulate, fiber, film, and three-dimensional (3D) porous scaffolds. This review discusses and summarizes the various constructions of SF-based materials, from single structures to multi-level structures, and their applications. In combination with single structures, new techniques for creating special multi-level structures of SF-based materials, such as micropatterning and 3D-printing, are also briefly addressed. PMID:28273799

Individual, social and environmental correlates of physical activity in overweight and obese African American and Hispanic women: A structural equation model analysis.

PubMed

Mama, Scherezade K; Diamond, Pamela M; McCurdy, Sheryl A; Evans, Alexandra E; McNeill, Lorna H; Lee, Rebecca E

Ecologic frameworks account for multilevel factors related to physical activity (PA) and may be used to develop effective interventions for women. The purpose of this study was to examine the influence of individual, social and environmental factors on PA among African American and Hispanic women using structural equation modeling. Overweight and obese women ( N =164, 65.9% African American) completed a 7-day accelerometer protocol, a physical assessment, and questionnaires on body image, self-efficacy, motivational readiness, social support, home environment for physical activity and perceived environment. Trained assessors evaluated each participant's neighborhood and collected objective measures of physical activity resources and the pedestrian environment. Assessments were completed between 2006 and 2008. Structural model fit was acceptable (RMSEA=.030). Body composition and image was negatively associated with PA, and motivational readiness had an indirect effect on PA through body composition and image. PA resources and the pedestrian environment operated through the perceived environment to positively influence neighborhood cohesion, which was positively associated with body composition and image. PA is more heavily influenced by intrapersonal factors related to weight. Improving intrapersonal factors related to weight and perceptions of the environment may lead to increased PA in African American and Hispanic women.

Multilevel examination of facility characteristics, social integration, and health for older adults living in nursing homes.

PubMed

Leedahl, Skye N; Chapin, Rosemary K; Little, Todd D

2015-01-01

Testing a model based on past research and theory, this study assessed relationships between facility characteristics (i.e., culture change efforts, social workers) and residents' social networks and social support across nursing homes; and examined relationships between multiple aspects of social integration (i.e., social networks, social capital, social engagement, social support) and mental and functional health for older adults in nursing homes. Data were collected at nursing homes using a planned missing data design with random sampling techniques. Data collection occurred at the individual-level through in-person structured interviews with older adult nursing home residents (N = 140) and at the facility-level (N = 30) with nursing home staff. The best fitting multilevel structural equation model indicated that the culture change subscale for relationships significantly predicted differences in residents' social networks. Additionally, social networks had a positive indirect relationship with mental and functional health among residents primarily via social engagement. Social capital had a positive direct relationship with both health outcomes. To predict better social integration and mental and functional health outcomes for nursing homes residents, study findings support prioritizing that close relationships exist among staff, residents, and the community as well as increased resident social engagement and social trust. © The Author 2014. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The Refinement-Tree Partition for Parallel Solution of Partial Differential Equations

PubMed Central

Mitchell, William F.

1998-01-01

Dynamic load balancing is considered in the context of adaptive multilevel methods for partial differential equations on distributed memory multiprocessors. An approach that periodically repartitions the grid is taken. The important properties of a partitioning algorithm are presented and discussed in this context. A partitioning algorithm based on the refinement tree of the adaptive grid is presented and analyzed in terms of these properties. Theoretical and numerical results are given. PMID:28009355

The Refinement-Tree Partition for Parallel Solution of Partial Differential Equations.

PubMed

Mitchell, William F

1998-01-01

Dynamic load balancing is considered in the context of adaptive multilevel methods for partial differential equations on distributed memory multiprocessors. An approach that periodically repartitions the grid is taken. The important properties of a partitioning algorithm are presented and discussed in this context. A partitioning algorithm based on the refinement tree of the adaptive grid is presented and analyzed in terms of these properties. Theoretical and numerical results are given.

Multi-Level Adaptive Techniques (MLAT) for singular-perturbation problems

NASA Technical Reports Server (NTRS)

Brandt, A.

1978-01-01

The multilevel (multigrid) adaptive technique, a general strategy of solving continuous problems by cycling between coarser and finer levels of discretization is described. It provides very fast general solvers, together with adaptive, nearly optimal discretization schemes. In the process, boundary layers are automatically either resolved or skipped, depending on a control function which expresses the computational goal. The global error decreases exponentially as a function of the overall computational work, in a uniform rate independent of the magnitude of the singular-perturbation terms. The key is high-order uniformly stable difference equations, and uniformly smoothing relaxation schemes.

Multilevel Higher-Order Item Response Theory Models

ERIC Educational Resources Information Center

Huang, Hung-Yu; Wang, Wen-Chung

2014-01-01

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

Building Path Diagrams for Multilevel Models

ERIC Educational Resources Information Center

Curran, Patrick J.; Bauer, Daniel J.

2007-01-01

Multilevel models have come to play an increasingly important role in many areas of social science research. However, in contrast to other modeling strategies, there is currently no widely used approach for graphically diagramming multilevel models. Ideally, such diagrams would serve two functions: to provide a formal structure for deriving the…

A Multilevel Structural Equation Model of Within- and Between-Person Associations among Subjective Responses to Alcohol, Craving, and Laboratory Alcohol Self-Administration

PubMed Central

Wardell, Jeffrey D.; Ramchandani, Vijay A.; Hendershot, Christian S.

2017-01-01

Subjective responses to alcohol are important determinants of drinking behavior and have been linked with risk for alcohol use disorders. However, few attempts have been made to examine proximal within-person associations among state changes in subjective responses and ongoing alcohol self-administration in the laboratory. This study disaggregated within- and between-person associations among subjective responses and alcohol self-administration, while also examining the mediating role of craving and the moderating role of trait impaired control over alcohol. Sixty young heavy drinkers (mean age=19.90, SD=0.86) completed self-report measures including the Impaired Control Scale, then participated in a 2-hour intravenous alcohol self-administration session using the Computer-Assisted Self-infusion of Ethanol (CASE) paradigm. Repeated assessments of subjective stimulation, subjective sedation, and craving were examined in relation to ongoing in-session self-administration, as indexed by breath alcohol concentration (BrAC) assessed 15 minutes later. Multilevel structural equation modeling was used to disentangle within-person and between-person associations. The results showed few significant associations at the between-person level, except for a direct negative association between sedation and BrAC. At the within-person level, state fluctuations in stimulation were positively associated with both craving and subsequent BrAC, whereas state changes in sedation were negatively associated with craving and positively associated with BrAC. Within-person indirect associations from subjective stimulation and sedation to subsequent BrAC mediated via craving were statistically significant. Also, participants higher on impaired control showed stronger within-person associations between craving and greater subsequent BrAC. The results suggest that subjective responses to alcohol and craving have proximal associations with self-administration behavior, the strength of which is linked with trait impaired control over alcohol. PMID:26595481

Standardized Mean Differences in Two-Level Cross-Classified Random Effects Models

ERIC Educational Resources Information Center

Lai, Mark H. C.; Kwok, Oi-Man

2014-01-01

Multilevel modeling techniques are becoming more popular in handling data with multilevel structure in educational and behavioral research. Recently, researchers have paid more attention to cross-classified data structure that naturally arises in educational settings. However, unlike traditional single-level research, methodological studies about…

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

PubMed

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

2009-01-01

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

Assessing dose-response effects of national essential medicine policy in China: comparison of two methods for handling data with a stepped wedge-like design and hierarchical structure.

PubMed

Ren, Yan; Yang, Min; Li, Qian; Pan, Jay; Chen, Fei; Li, Xiaosong; Meng, Qun

2017-02-22

To introduce multilevel repeated measures (RM) models and compare them with multilevel difference-in-differences (DID) models in assessing the linear relationship between the length of the policy intervention period and healthcare outcomes (dose-response effect) for data from a stepped-wedge design with a hierarchical structure. The implementation of national essential medicine policy (NEMP) in China was a stepped-wedge-like design of five time points with a hierarchical structure. Using one key healthcare outcome from the national NEMP surveillance data as an example, we illustrate how a series of multilevel DID models and one multilevel RM model can be fitted to answer some research questions on policy effects. Routinely and annually collected national data on China from 2008 to 2012. 34 506 primary healthcare facilities in 2675 counties of 31 provinces. Agreement and differences in estimates of dose-response effect and variation in such effect between the two methods on the logarithm-transformed total number of outpatient visits per facility per year (LG-OPV). The estimated dose-response effect was approximately 0.015 according to four multilevel DID models and precisely 0.012 from one multilevel RM model. Both types of model estimated an increase in LG-OPV by 2.55 times from 2009 to 2012, but 2-4.3 times larger SEs of those estimates were found by the multilevel DID models. Similar estimates of mean effects of covariates and random effects of the average LG-OPV among all levels in the example dataset were obtained by both types of model. Significant variances in the dose-response among provinces, counties and facilities were estimated, and the 'lowest' or 'highest' units by their dose-response effects were pinpointed only by the multilevel RM model. For examining dose-response effect based on data from multiple time points with hierarchical structure and the stepped wedge-like designs, multilevel RM models are more efficient, convenient and informative than the multilevel DID models. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

THE COMPONENTS OF KIN COMPETITION

PubMed Central

Van Dyken, J. David

2011-01-01

It is well known that competition among kin alters the rate and often the direction of evolution in subdivided populations. Yet much remains unclear about the ecological and demographic causes of kin competition, or what role life cycle plays in promoting or ameliorating its effects. Using the multilevel Price equation, I derive a general equation for evolution in structured populations under an arbitrary intensity of kin competition. This equation partitions the effects of selection and demography, and recovers numerous previous models as special cases. I quantify the degree of kin competition, α, which explicitly depends on life cycle. I show how life cycle and demographic assumptions can be incorporated into kin selection models via α, revealing life cycles that are more or less permissive of altruism. As an example, I give closed-form results for Hamilton’s rule in a three-stage life cycle. Although results are sensitive to life cycle in general, I identify three demographic conditions that give life cycle invariant results. Under the infinite island model, α is a function of the scale of density regulation and dispersal rate, effectively disentangling these two phenomena. Population viscosity per se does not impede kin selection. PMID:20482610

Multilevel selection analysis of a microbial social trait

PubMed Central

de Vargas Roditi, Laura; Boyle, Kerry E; Xavier, Joao B

2013-01-01

The study of microbial communities often leads to arguments for the evolution of cooperation due to group benefits. However, multilevel selection models caution against the uncritical assumption that group benefits will lead to the evolution of cooperation. We analyze a microbial social trait to precisely define the conditions favoring cooperation. We combine the multilevel partition of the Price equation with a laboratory model system: swarming in Pseudomonas aeruginosa. We parameterize a population dynamics model using competition experiments where we manipulate expression, and therefore the cost-to-benefit ratio of swarming cooperation. Our analysis shows that multilevel selection can favor costly swarming cooperation because it causes population expansion. However, due to high costs and diminishing returns constitutive cooperation can only be favored by natural selection when relatedness is high. Regulated expression of cooperative genes is a more robust strategy because it provides the benefits of swarming expansion without the high cost or the diminishing returns. Our analysis supports the key prediction that strong group selection does not necessarily mean that microbial cooperation will always emerge. PMID:23959025

New evidence favoring multilevel decomposition and optimization

NASA Technical Reports Server (NTRS)

Padula, Sharon L.; Polignone, Debra A.

1990-01-01

The issue of the utility of multilevel decomposition and optimization remains controversial. To date, only the structural optimization community has actively developed and promoted multilevel optimization techniques. However, even this community acknowledges that multilevel optimization is ideally suited for a rather limited set of problems. It is warned that decomposition typically requires eliminating local variables by using global variables and that this in turn causes ill-conditioning of the multilevel optimization by adding equality constraints. The purpose is to suggest a new multilevel optimization technique. This technique uses behavior variables, in addition to design variables and constraints, to decompose the problem. The new technique removes the need for equality constraints, simplifies the decomposition of the design problem, simplifies the programming task, and improves the convergence speed of multilevel optimization compared to conventional optimization.

Multilevel Motivation and Engagement: Assessing Construct Validity across Students and Schools

ERIC Educational Resources Information Center

Martin, Andrew J.; Malmberg, Lars-Erik; Liem, Gregory Arief D.

2010-01-01

Statistical biases associated with single-level analyses underscore the importance of partitioning variance/covariance matrices into individual and group levels. From a multilevel perspective based on data from 21,579 students in 58 high schools, the present study assesses the multilevel factor structure of motivation and engagement with a…

Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media

NASA Astrophysics Data System (ADS)

Crevillén-García, D.; Power, H.

2017-08-01

In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen-Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error.

Operating Quantum States in Single Magnetic Molecules: Implementation of Grover's Quantum Algorithm.

PubMed

Godfrin, C; Ferhat, A; Ballou, R; Klyatskaya, S; Ruben, M; Wernsdorfer, W; Balestro, F

2017-11-03

Quantum algorithms use the principles of quantum mechanics, such as, for example, quantum superposition, in order to solve particular problems outperforming standard computation. They are developed for cryptography, searching, optimization, simulation, and solving large systems of linear equations. Here, we implement Grover's quantum algorithm, proposed to find an element in an unsorted list, using a single nuclear 3/2 spin carried by a Tb ion sitting in a single molecular magnet transistor. The coherent manipulation of this multilevel quantum system (qudit) is achieved by means of electric fields only. Grover's search algorithm is implemented by constructing a quantum database via a multilevel Hadamard gate. The Grover sequence then allows us to select each state. The presented method is of universal character and can be implemented in any multilevel quantum system with nonequal spaced energy levels, opening the way to novel quantum search algorithms.

Operating Quantum States in Single Magnetic Molecules: Implementation of Grover's Quantum Algorithm

NASA Astrophysics Data System (ADS)

Godfrin, C.; Ferhat, A.; Ballou, R.; Klyatskaya, S.; Ruben, M.; Wernsdorfer, W.; Balestro, F.

2017-11-01

Quantum algorithms use the principles of quantum mechanics, such as, for example, quantum superposition, in order to solve particular problems outperforming standard computation. They are developed for cryptography, searching, optimization, simulation, and solving large systems of linear equations. Here, we implement Grover's quantum algorithm, proposed to find an element in an unsorted list, using a single nuclear 3 /2 spin carried by a Tb ion sitting in a single molecular magnet transistor. The coherent manipulation of this multilevel quantum system (qudit) is achieved by means of electric fields only. Grover's search algorithm is implemented by constructing a quantum database via a multilevel Hadamard gate. The Grover sequence then allows us to select each state. The presented method is of universal character and can be implemented in any multilevel quantum system with nonequal spaced energy levels, opening the way to novel quantum search algorithms.

Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media.

PubMed

Crevillén-García, D; Power, H

2017-08-01

In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen-Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error.

Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media

PubMed Central

Power, H.

2017-01-01

In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen–Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error. PMID:28878974

New modified multi-level residue harmonic balance method for solving nonlinearly vibrating double-beam problem

NASA Astrophysics Data System (ADS)

Rahman, Md. Saifur; Lee, Yiu-Yin

2017-10-01

In this study, a new modified multi-level residue harmonic balance method is presented and adopted to investigate the forced nonlinear vibrations of axially loaded double beams. Although numerous nonlinear beam or linear double-beam problems have been tackled and solved, there have been few studies of this nonlinear double-beam problem. The geometric nonlinear formulations for a double-beam model are developed. The main advantage of the proposed method is that a set of decoupled nonlinear algebraic equations is generated at each solution level. This heavily reduces the computational effort compared with solving the coupled nonlinear algebraic equations generated in the classical harmonic balance method. The proposed method can generate the higher-level nonlinear solutions that are neglected by the previous modified harmonic balance method. The results from the proposed method agree reasonably well with those from the classical harmonic balance method. The effects of damping, axial force, and excitation magnitude on the nonlinear vibrational behaviour are examined.

Teaching quality: High school students' autonomy and competence.

PubMed

León, Jaime; Medina-Garrido, Elena; Ortega, Miriam

2018-05-01

How teachers manage class learning and interact with students affects students’ motivation and engagement. However, it could be that the effect of students’ representation of teaching quality on the students’ motivation varies between classes. Students from 90 classes participated in the study. We used multilevel random structural equation modeling to analyze whether the relationship of the students’ perception of teaching quality (as an indicator of the students’ mental representation) and students’ motivation varies between classes, and if this variability depends on the class assessment of teaching quality (as an indicator of teaching quality). The effect of teachers’ structure on the regression slope of student perception of student competence was .127. The effect of teachers’ autonomy support on the regression slope of student perception of student autonomy was .066. With this study we contribute a more detailed description of the relationship between teaching quality, competence and autonomy.

A multi-level model accounting for the effects of JAK2-STAT5 signal modulation in erythropoiesis.

PubMed

Lai, Xin; Nikolov, Svetoslav; Wolkenhauer, Olaf; Vera, Julio

2009-08-01

We develop a multi-level model, using ordinary differential equations, based on quantitative experimental data, accounting for murine erythropoiesis. At the sub-cellular level, the model includes a description of the regulation of red blood cell differentiation through Epo-stimulated JAK2-STAT5 signalling activation, while at the cell population level the model describes the dynamics of (STAT5-mediated) red blood cell differentiation from their progenitors. Furthermore, the model includes equations depicting the hypoxia-mediated regulation of hormone erythropoietin blood levels. Take all together, the model constitutes a multi-level, feedback loop-regulated biological system, involving processes in different organs and at different organisational levels. We use our model to investigate the effect of deregulation in the proteins involved in the JAK2-STAT5 signalling pathway in red blood cells. Our analysis results suggest that down-regulation in any of the three signalling system components affects the hematocrit level in an individual considerably. In addition, our analysis predicts that exogenous Epo injection (an already existing treatment for several blood diseases) may compensate the effects of single down-regulation of Epo hormone level, STAT5 or EpoR/JAK2 expression level, and that it may be insufficient to counterpart a combined down-regulation of all the elements in the JAK2-STAT5 signalling cascade.

Moving in Parallel Toward a Modern Modeling Epistemology: Bayes Factors and Frequentist Modeling Methods.

PubMed

Rodgers, Joseph Lee

2016-01-01

The Bayesian-frequentist debate typically portrays these statistical perspectives as opposing views. However, both Bayesian and frequentist statisticians have expanded their epistemological basis away from a singular focus on the null hypothesis, to a broader perspective involving the development and comparison of competing statistical/mathematical models. For frequentists, statistical developments such as structural equation modeling and multilevel modeling have facilitated this transition. For Bayesians, the Bayes factor has facilitated this transition. The Bayes factor is treated in articles within this issue of Multivariate Behavioral Research. The current presentation provides brief commentary on those articles and more extended discussion of the transition toward a modern modeling epistemology. In certain respects, Bayesians and frequentists share common goals.

Transforming SIBTEST to Account for Multilevel Data Structures

ERIC Educational Resources Information Center

French, Brian F.; Finch, W. Holmes

2015-01-01

SIBTEST is a differential item functioning (DIF) detection method that is accurate and effective with small samples, in the presence of group mean differences, and for assessment of both uniform and nonuniform DIF. The presence of multilevel data with DIF detection has received increased attention. Ignoring such structure can inflate Type I error.…

Using Multilevel Factor Analysis with Clustered Data: Investigating the Factor Structure of the Positive Values Scale

ERIC Educational Resources Information Center

Huang, Francis L.; Cornell, Dewey G.

2016-01-01

Advances in multilevel modeling techniques now make it possible to investigate the psychometric properties of instruments using clustered data. Factor models that overlook the clustering effect can lead to underestimated standard errors, incorrect parameter estimates, and model fit indices. In addition, factor structures may differ depending on…

Solutions of large-scale electromagnetics problems involving dielectric objects with the parallel multilevel fast multipole algorithm.

PubMed

Ergül, Özgür

2011-11-01

Fast and accurate solutions of large-scale electromagnetics problems involving homogeneous dielectric objects are considered. Problems are formulated with the electric and magnetic current combined-field integral equation and discretized with the Rao-Wilton-Glisson functions. Solutions are performed iteratively by using the multilevel fast multipole algorithm (MLFMA). For the solution of large-scale problems discretized with millions of unknowns, MLFMA is parallelized on distributed-memory architectures using a rigorous technique, namely, the hierarchical partitioning strategy. Efficiency and accuracy of the developed implementation are demonstrated on very large problems involving as many as 100 million unknowns.

ML-Space: Hybrid Spatial Gillespie and Particle Simulation of Multi-Level Rule-Based Models in Cell Biology.

PubMed

Bittig, Arne T; Uhrmacher, Adelinde M

2017-01-01

Spatio-temporal dynamics of cellular processes can be simulated at different levels of detail, from (deterministic) partial differential equations via the spatial Stochastic Simulation algorithm to tracking Brownian trajectories of individual particles. We present a spatial simulation approach for multi-level rule-based models, which includes dynamically hierarchically nested cellular compartments and entities. Our approach ML-Space combines discrete compartmental dynamics, stochastic spatial approaches in discrete space, and particles moving in continuous space. The rule-based specification language of ML-Space supports concise and compact descriptions of models and to adapt the spatial resolution of models easily.

A Multi-Level Decision Fusion Strategy for Condition Based Maintenance of Composite Structures

PubMed Central

Sharif Khodaei, Zahra; Aliabadi, M.H.

2016-01-01

In this work, a multi-level decision fusion strategy is proposed which weighs the Value of Information (VoI) against the intended functions of a Structural Health Monitoring (SHM) system. This paper presents a multi-level approach for three different maintenance strategies in which the performance of the SHM systems is evaluated against its intended functions. Level 1 diagnosis results in damage existence with minimum sensors covering a large area by finding the maximum energy difference for the guided waves propagating in pristine structure and the post-impact state; Level 2 diagnosis provides damage detection and approximate localization using an approach based on Electro-Mechanical Impedance (EMI) measures, while Level 3 characterizes damage (exact location and size) in addition to its detection by utilising a Weighted Energy Arrival Method (WEAM). The proposed multi-level strategy is verified and validated experimentally by detection of Barely Visible Impact Damage (BVID) on a curved composite fuselage panel. PMID:28773910

Master equation theory applied to the redistribution of polarized radiation in the weak radiation field limit. V. The two-term atom

NASA Astrophysics Data System (ADS)

Bommier, Véronique

2017-11-01

Context. In previous papers of this series, we presented a formalism able to account for both statistical equilibrium of a multilevel atom and coherent and incoherent scatterings (partial redistribution). Aims: This paper provides theoretical expressions of the redistribution function for the two-term atom. This redistribution function includes both coherent (RII) and incoherent (RIII) scattering contributions with their branching ratios. Methods: The expressions were derived by applying the formalism outlined above. The statistical equilibrium equation for the atomic density matrix is first formally solved in the case of the two-term atom with unpolarized and infinitely sharp lower levels. Then the redistribution function is derived by substituting this solution for the expression of the emissivity. Results: Expressions are provided for both magnetic and non-magnetic cases. Atomic fine structure is taken into account. Expressions are also separately provided under zero and non-zero hyperfine structure. Conclusions: Redistribution functions are widely used in radiative transfer codes. In our formulation, collisional transitions between Zeeman sublevels within an atomic level (depolarizing collisions effect) are taken into account when possible (I.e., in the non-magnetic case). However, the need for a formal solution of the statistical equilibrium as a preliminary step prevents us from taking into account collisional transfers between the levels of the upper term. Accounting for these collisional transfers could be done via a numerical solution of the statistical equilibrium equation system.

The Impact of Misspecifying the Within-Subject Covariance Structure in Multiwave Longitudinal Multilevel Models: A Monte Carlo Study

ERIC Educational Resources Information Center

Kwok, Oi-man; West, Stephen G.; Green, Samuel B.

2007-01-01

This Monte Carlo study examined the impact of misspecifying the [big sum] matrix in longitudinal data analysis under both the multilevel model and mixed model frameworks. Under the multilevel model approach, under-specification and general-misspecification of the [big sum] matrix usually resulted in overestimation of the variances of the random…

Theoretical and software considerations for nonlinear dynamic analysis

NASA Technical Reports Server (NTRS)

Schmidt, R. J.; Dodds, R. H., Jr.

1983-01-01

In the finite element method for structural analysis, it is generally necessary to discretize the structural model into a very large number of elements to accurately evaluate displacements, strains, and stresses. As the complexity of the model increases, the number of degrees of freedom can easily exceed the capacity of present-day software system. Improvements of structural analysis software including more efficient use of existing hardware and improved structural modeling techniques are discussed. One modeling technique that is used successfully in static linear and nonlinear analysis is multilevel substructuring. This research extends the use of multilevel substructure modeling to include dynamic analysis and defines the requirements for a general purpose software system capable of efficient nonlinear dynamic analysis. The multilevel substructuring technique is presented, the analytical formulations and computational procedures for dynamic analysis and nonlinear mechanics are reviewed, and an approach to the design and implementation of a general purpose structural software system is presented.

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…

A model and variance reduction method for computing statistical outputs of stochastic elliptic partial differential equations

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

Vidal-Codina, F., E-mail: fvidal@mit.edu; Nguyen, N.C., E-mail: cuongng@mit.edu; Giles, M.B., E-mail: mike.giles@maths.ox.ac.uk

We present a model and variance reduction method for the fast and reliable computation of statistical outputs of stochastic elliptic partial differential equations. Our method consists of three main ingredients: (1) the hybridizable discontinuous Galerkin (HDG) discretization of elliptic partial differential equations (PDEs), which allows us to obtain high-order accurate solutions of the governing PDE; (2) the reduced basis method for a new HDG discretization of the underlying PDE to enable real-time solution of the parameterized PDE in the presence of stochastic parameters; and (3) a multilevel variance reduction method that exploits the statistical correlation among the different reduced basismore » approximations and the high-fidelity HDG discretization to accelerate the convergence of the Monte Carlo simulations. The multilevel variance reduction method provides efficient computation of the statistical outputs by shifting most of the computational burden from the high-fidelity HDG approximation to the reduced basis approximations. Furthermore, we develop a posteriori error estimates for our approximations of the statistical outputs. Based on these error estimates, we propose an algorithm for optimally choosing both the dimensions of the reduced basis approximations and the sizes of Monte Carlo samples to achieve a given error tolerance. We provide numerical examples to demonstrate the performance of the proposed method.« less

Family Structure and Adolescent Substance Use: An International Perspective.

PubMed

Hoffmann, John P

2017-11-10

Numerous studies indicate that family structure is a key correlate of adolescent substance use. Yet there are some important limitations to this research. Studies have been conducted mainly in the United States, with relatively few studies that have compared family structure and youth substance use across nations. There is also a lack of recognition of the complexity of family types prevalent in contemporary global society. Moreover, there remains a need to consider personal, interpersonal, and macro-level characteristics that may help account for the association between family structure and youth substance use. This study uses data from 37 countries to examine several models that purport to explain the association between family structure and substance use. The data are from the 2005-2006 WHO-sponsored Health Behaviour in School-Aged Children (HBSC) (n = 193,202). Multilevel models, including linear, probit, and structural equation models (SEMs), were used to test several hypotheses. The results suggest that time spent with friends largely accounted for the association between specific types of family structures and frequency of alcohol use and getting drunk, but that cannabis use was negatively associated with living with both biological parents irrespective of other factors.

Negative voltage modulated multi-level resistive switching by using a Cr/BaTiOx/TiN structure and quantum conductance through evidence of H2O2 sensing mechanism.

PubMed

Chakrabarti, Somsubhra; Ginnaram, Sreekanth; Jana, Surajit; Wu, Zong-Yi; Singh, Kanishk; Roy, Anisha; Kumar, Pankaj; Maikap, Siddheswar; Qiu, Jian-Tai; Cheng, Hsin-Ming; Tsai, Ling-Na; Chang, Ya-Ling; Mahapatra, Rajat; Yang, Jer-Ren

2017-07-05

Negative voltage modulated multi-level resistive switching with quantum conductance during staircase-type RESET and its transport characteristics in Cr/BaTiO x /TiN structure have been investigated for the first time. The as-deposited amorphous BaTiO x film has been confirmed by high-resolution transmission electron microscopy. X-ray photo-electron spectroscopy shows different oxidation states of Ba in the switching material, which is responsible for tunable more than 10 resistance states by varying negative stop voltage owing to slow decay value of RESET slope (217.39 mV/decade). Quantum conductance phenomenon has been observed in staircase RESET cycle of the memory devices. By inspecting the oxidation states of Ba + and Ba 2+ through measuring H 2 O 2 with a low concentration of 1 nM in electrolyte/BaTiO x /SiO 2 /p-Si structure, the switching mechanism of each HRS level as well as the multi-level phenomenon has been explained by gradual dissolution of oxygen vacancy filament. Along with negative stop voltage modulated multi-level, current compliance dependent multi-level has also been demonstrated and resistance ratio up to 2000 has been achieved even for a thin (<5 nm) switching material. By considering oxidation-reduction of the conducting filaments, the current-voltage switching curve has been simulated as well. Hence, multi-level resistive switching of Cr/BaTiO x /TiN structure implies the promising applications in high dense, multistate non-volatile memories in near future.

A Wideband Fast Multipole Method for the two-dimensional complex Helmholtz equation

NASA Astrophysics Data System (ADS)

Cho, Min Hyung; Cai, Wei

2010-12-01

A Wideband Fast Multipole Method (FMM) for the 2D Helmholtz equation is presented. It can evaluate the interactions between N particles governed by the fundamental solution of 2D complex Helmholtz equation in a fast manner for a wide range of complex wave number k, which was not easy with the original FMM due to the instability of the diagonalized conversion operator. This paper includes the description of theoretical backgrounds, the FMM algorithm, software structures, and some test runs. Program summaryProgram title: 2D-WFMM Catalogue identifier: AEHI_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEHI_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 4636 No. of bytes in distributed program, including test data, etc.: 82 582 Distribution format: tar.gz Programming language: C Computer: Any Operating system: Any operating system with gcc version 4.2 or newer Has the code been vectorized or parallelized?: Multi-core processors with shared memory RAM: Depending on the number of particles N and the wave number k Classification: 4.8, 4.12 External routines: OpenMP ( http://openmp.org/wp/) Nature of problem: Evaluate interaction between N particles governed by the fundamental solution of 2D Helmholtz equation with complex k. Solution method: Multilevel Fast Multipole Algorithm in a hierarchical quad-tree structure with cutoff level which combines low frequency method and high frequency method. Running time: Depending on the number of particles N, wave number k, and number of cores in CPU. CPU time increases as N log N.

Multiscale Multilevel Approach to Solution of Nanotechnology Problems

NASA Astrophysics Data System (ADS)

Polyakov, Sergey; Podryga, Viktoriia

2018-02-01

The paper is devoted to a multiscale multilevel approach for the solution of nanotechnology problems on supercomputer systems. The approach uses the combination of continuum mechanics models and the Newton dynamics for individual particles. This combination includes three scale levels: macroscopic, mesoscopic and microscopic. For gas-metal technical systems the following models are used. The quasihydrodynamic system of equations is used as a mathematical model at the macrolevel for gas and solid states. The system of Newton equations is used as a mathematical model at the mesoand microlevels; it is written for nanoparticles of the medium and larger particles moving in the medium. The numerical implementation of the approach is based on the method of splitting into physical processes. The quasihydrodynamic equations are solved by the finite volume method on grids of different types. The Newton equations of motion are solved by Verlet integration in each cell of the grid independently or in groups of connected cells. In the framework of the general methodology, four classes of algorithms and methods of their parallelization are provided. The parallelization uses the principles of geometric parallelism and the efficient partitioning of the computational domain. A special dynamic algorithm is used for load balancing the solvers. The testing of the developed approach was made by the example of the nitrogen outflow from a balloon with high pressure to a vacuum chamber through a micronozzle and a microchannel. The obtained results confirm the high efficiency of the developed methodology.

Promoting and Protecting Against Stigma in Assisted Living and Nursing Homes

PubMed Central

Zimmerman, Sheryl; Dobbs, Debra; Roth, Erin G.; Goldman, Susan; Peeples, Amanda D.; Wallace, Brandy

2016-01-01

Purpose of the Study: To determine the extent to which structures and processes of care in multilevel settings (independent living, assisted living, and nursing homes) result in stigma in assisted living and nursing homes. Design and Methods: Ethnographic in-depth interviews were conducted in 5 multilevel settings with 256 residents, families, and staff members. Qualitative analyses identified the themes that resulted when examining text describing either structures of care or processes of care in relation to 7 codes associated with stigma. Results: Four themes related to structures of care and stigma were identified, including the physical environment, case mix, staff training, and multilevel settings; five themes related to processes of care and stigma, including dining, independence, respect, privacy, and care provision. For each theme, examples were identified illustrating how structures and processes of care can potentially promote or protect against stigma. Implications: In no instance were examples or themes identified that suggested the staff intentionally promoted stigma; on the other hand, there was indication that some structures and processes were intentionally in place to protect against stigma. Perhaps the most important theme is the stigma related to multilevel settings, as it has the potential to reduce individuals’ likelihood to seek and accept necessary care. Results suggest specific recommendations to modify care and reduce stigma. PMID:24928555

The relationship between self-management abilities, quality of chronic care delivery, and wellbeing among patients with chronic obstructive pulmonary disease in The Netherlands

PubMed Central

Cramm, Jane Murray; Nieboer, Anna Petra

2013-01-01

Background This cross-sectional study aimed to identify the relationship between quality of chronic care delivery, self-management abilities, and wellbeing among patients with chronic obstructive pulmonary disease (COPD). Methods The study was conducted in 2012 and included 548 (out of 1303; 42% response rate) patients with COPD enrolled in a COPD care program in the region of Noord-Kennemerland in The Netherlands. We employed a multilevel random-effects model (548 patients nested in 47 healthcare practices) to investigate the relationship between quality of chronic care delivery, self-management abilities, and patients’ wellbeing. In the multilevel analyses we controlled for patients’ background characteristics and health behaviors. Results Multilevel analyses clearly showed a significant relationship between quality of chronic care delivery and wellbeing of patients with COPD (P ≤ 0.001). When self-management abilities were included in the equation while controlling for background characteristics, health behaviors, and quality of chronic care delivery, these abilities were found to have a strong positive relationship with patients’ wellbeing (P ≤ 0.001). Low educational level, single marital status, and physical exercise were not significantly associated with wellbeing when self-management abilities were included in the equation. Conclusion Self-management abilities and the quality of chronic care delivery are important for the wellbeing of patients with COPD. Furthermore, self-management abilities acted as mediators between wellbeing and low educational level, single status, and physical exercise among these patients. PMID:23641152

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

Ketterer, S.P.

This manual is designed as a comprehensive hands-on instructional manual for learning the T{sub E}X* computer typesetting program in a classroom environment. Each section presents a new concept in careful detail, concluding with an exercise (T{sub E}Xercise) to reinforce the learning of the concept. The manual introduces the novice T{sub E}X user to the program's basic command structure, along with the concepts of grouping, producing accents, making font changes, and generating mathematical symbols. The T{sub E}Xercises guide the new user in generating text containing footnotes, multilevel lists, and hanging indentations, as well as in magnifying text for viewgraphs. Once themore » basic text generation is defined, the more advanced topics of formatting math equations and tables are explained. A full range of math capabilities is presented --- beginning with simple one-line equations, progressing through complex numbered and aligned equations, and concluding with matrices. The sections on table generation present the basic concepts in T{sub E}X's table-formatting program and then build on them. The new user first learns to construct simple tables, and with careful explanations and guidance, learns to add one new table enhancement at a time. By the conclusion of these sections, the user can construct tables with horizontal and vertical rules and with column entries that are paragraphs. 1 ref.« less

The components of kin competition.

PubMed

Van Dyken, J David

2010-10-01

It is well known that competition among kin alters the rate and often the direction of evolution in subdivided populations. Yet much remains unclear about the ecological and demographic causes of kin competition, or what role life cycle plays in promoting or ameliorating its effects. Using the multilevel Price equation, I derive a general equation for evolution in structured populations under an arbitrary intensity of kin competition. This equation partitions the effects of selection and demography, and recovers numerous previous models as special cases. I quantify the degree of kin competition, α, which explicitly depends on life cycle. I show how life cycle and demographic assumptions can be incorporated into kin selection models via α, revealing life cycles that are more or less permissive of altruism. As an example, I give closed-form results for Hamilton's rule in a three-stage life cycle. Although results are sensitive to life cycle in general, I identify three demographic conditions that give life cycle invariant results. Under the infinite island model, α is a function of the scale of density regulation and dispersal rate, effectively disentangling these two phenomena. Population viscosity per se does not impede kin selection. © 2010 The Author(s). Journal compilation © 2010 The Society for the Study of Evolution.

A wideband fast multipole boundary element method for half-space/plane-symmetric acoustic wave problems

NASA Astrophysics Data System (ADS)

Zheng, Chang-Jun; Chen, Hai-Bo; Chen, Lei-Lei

2013-04-01

This paper presents a novel wideband fast multipole boundary element approach to 3D half-space/plane-symmetric acoustic wave problems. The half-space fundamental solution is employed in the boundary integral equations so that the tree structure required in the fast multipole algorithm is constructed for the boundary elements in the real domain only. Moreover, a set of symmetric relations between the multipole expansion coefficients of the real and image domains are derived, and the half-space fundamental solution is modified for the purpose of applying such relations to avoid calculating, translating and saving the multipole/local expansion coefficients of the image domain. The wideband adaptive multilevel fast multipole algorithm associated with the iterative solver GMRES is employed so that the present method is accurate and efficient for both lowand high-frequency acoustic wave problems. As for exterior acoustic problems, the Burton-Miller method is adopted to tackle the fictitious eigenfrequency problem involved in the conventional boundary integral equation method. Details on the implementation of the present method are described, and numerical examples are given to demonstrate its accuracy and efficiency.

Specifications of insilicoML 1.0: a multilevel biophysical model description language.

PubMed

Asai, Yoshiyuki; Suzuki, Yasuyuki; Kido, Yoshiyuki; Oka, Hideki; Heien, Eric; Nakanishi, Masao; Urai, Takahito; Hagihara, Kenichi; Kurachi, Yoshihisa; Nomura, Taishin

2008-12-01

An extensible markup language format, insilicoML (ISML), version 0.1, describing multi-level biophysical models has been developed and available in the public domain. ISML is fully compatible with CellML 1.0, a model description standard developed by the IUPS Physiome Project, for enhancing knowledge integration and model sharing. This article illustrates the new specifications of ISML 1.0 that largely extend the capability of ISML 0.1. ISML 1.0 can describe various types of mathematical models, including ordinary/partial differential/difference equations representing the dynamics of physiological functions and the geometry of living organisms underlying the functions. ISML 1.0 describes a model using a set of functional elements (modules) each of which can specify mathematical expressions of the functions. Structural and logical relationships between any two modules are specified by edges, which allow modular, hierarchical, and/or network representations of the model. The role of edge-relationships is enriched by key words in order for use in constructing a physiological ontology. The ontology is further improved by the traceability of history of the model's development and by linking between different ISML models stored in the model's database using meta-information. ISML 1.0 is designed to operate with a model database and integrated environments for model development and simulations for knowledge integration and discovery.

The Many Faces of Affect: A Multilevel Model of Drinking Frequency/Quantity and Alcohol Dependence Symptoms Among Young Adults

PubMed Central

Simons, Jeffrey S.; Wills, Thomas A.; Neal, Dan J.

2016-01-01

This research tested a multilevel structural equation model of associations between 3 aspects of affective functioning (state affect, trait affect, and affective lability) and 3 alcohol outcomes (likelihood of drinking, quantity on drinking days, and dependence symptoms) in a sample of 263 college students. Participants provided 49 days of experience sampling data over 1.3 years in a longitudinal burst design. Within-person results: At the daily level, positive affect was directly associated with greater likelihood and quantity of alcohol consumption. Daily negative affect was directly associated with higher consumption on drinking days and with higher dependence symptoms. Between-person direct effects: Affect lability was associated with higher trait negative, but not positive, affect. Trait positive affect was inversely associated with the proportion of drinking days, whereas negative affectivity predicted a greater proportion of drinking days. Affect lability exhibited a direct association with dependence symptoms. Between-person indirect effects: Trait positive affect was associated with fewer dependence symptoms via proportion of drinking days. Trait negative affect was associated with greater dependence symptoms via proportion of drinking days. The results distinguish relations of positive and negative affect to likelihood versus amount of drinking and state versus trait drinking outcomes, and highlight the importance of affect variability for predicting alcohol dependence symptoms. PMID:24933278

Stability of Boolean multilevel networks.

PubMed

Cozzo, Emanuele; Arenas, Alex; Moreno, Yamir

2012-09-01

The study of the interplay between the structure and dynamics of complex multilevel systems is a pressing challenge nowadays. In this paper, we use a semiannealed approximation to study the stability properties of random Boolean networks in multiplex (multilayered) graphs. Our main finding is that the multilevel structure provides a mechanism for the stabilization of the dynamics of the whole system even when individual layers work on the chaotic regime, therefore identifying new ways of feedback between the structure and the dynamics of these systems. Our results point out the need for a conceptual transition from the physics of single-layered networks to the physics of multiplex networks. Finally, the fact that the coupling modifies the phase diagram and the critical conditions of the isolated layers suggests that interdependency can be used as a control mechanism.

Integrated control/structure optimization by multilevel decomposition

NASA Technical Reports Server (NTRS)

Zeiler, Thomas A.; Gilbert, Michael G.

1990-01-01

A method for integrated control/structure optimization by multilevel decomposition is presented. It is shown that several previously reported methods were actually partial decompositions wherein only the control was decomposed into a subsystem design. One of these partially decomposed problems was selected as a benchmark example for comparison. The system is fully decomposed into structural and control subsystem designs and an improved design is produced. Theory, implementation, and results for the method are presented and compared with the benchmark example.

Design of shared unit-dose drug distribution network using multi-level particle swarm optimization.

PubMed

Chen, Linjie; Monteiro, Thibaud; Wang, Tao; Marcon, Eric

2018-03-01

Unit-dose drug distribution systems provide optimal choices in terms of medication security and efficiency for organizing the drug-use process in large hospitals. As small hospitals have to share such automatic systems for economic reasons, the structure of their logistic organization becomes a very sensitive issue. In the research reported here, we develop a generalized multi-level optimization method - multi-level particle swarm optimization (MLPSO) - to design a shared unit-dose drug distribution network. Structurally, the problem studied can be considered as a type of capacitated location-routing problem (CLRP) with new constraints related to specific production planning. This kind of problem implies that a multi-level optimization should be performed in order to minimize logistic operating costs. Our results show that with the proposed algorithm, a more suitable modeling framework, as well as computational time savings and better optimization performance are obtained than that reported in the literature on this subject.

Multilevel animal societies can emerge from cultural transmission

PubMed Central

Cantor, Maurício; Shoemaker, Lauren G.; Cabral, Reniel B.; Flores, César O.; Varga, Melinda; Whitehead, Hal

2015-01-01

Multilevel societies, containing hierarchically nested social levels, are remarkable social structures whose origins are unclear. The social relationships of sperm whales are organized in a multilevel society with an upper level composed of clans of individuals communicating using similar patterns of clicks (codas). Using agent-based models informed by an 18-year empirical study, we show that clans are unlikely products of stochastic processes (genetic or cultural drift) but likely originate from cultural transmission via biased social learning of codas. Distinct clusters of individuals with similar acoustic repertoires, mirroring the empirical clans, emerge when whales learn preferentially the most common codas (conformism) from behaviourally similar individuals (homophily). Cultural transmission seems key in the partitioning of sperm whales into sympatric clans. These findings suggest that processes similar to those that generate complex human cultures could not only be at play in non-human societies but also create multilevel social structures in the wild. PMID:26348688

Is biotechnology (more) acceptable when it enables a reduction in phytosanitary treatments? A European comparison of the acceptability of transgenesis and cisgenesis

PubMed Central

2017-01-01

Reduced pesticide use is one of the reasons given by Europeans for accepting new genetic engineering techniques. According to the advocates of these techniques, consumers are likely to embrace the application of cisgenesis to apple trees. In order to verify the acceptability of these techniques, we estimate a Bayesian multilevel structural equation model, which takes into account the multidimensional nature of acceptability and individual, national, and European effects, using data from the Eurobarometer 2010 73.1 on science. The results underline the persistence of clear differences between European countries and whilst showing considerable defiance, a relatively wider acceptability of vertical gene transfer as a means of reducing phytosanitary treatments, compared to horizontal transfer. PMID:28877215

Planarization of metal films for multilevel interconnects

DOEpatents

Tuckerman, D.B.

1985-06-24

In the fabrication of multilevel integrated circuits, each metal layer is planarized by heating to momentarily melt the layer. The layer is melted by sweeping lase pulses of suitable width, typically about 1 microsecond duration, over the layer in small increments. The planarization of each metal layer eliminates irregular and discontinuous conditions between successive layers. The planarization method is particularly applicable to circuits having ground or power planes and allows for multilevel interconnects. Dielectric layers can also be planarized to produce a fully planar multilevel interconnect structure. The method is useful for the fabrication of VLSI circuits, particularly for wafer-scale integration.

Planarization of metal films for multilevel interconnects

DOEpatents

Tuckerman, David B.

1987-01-01

In the fabrication of multilevel integrated circuits, each metal layer is anarized by heating to momentarily melt the layer. The layer is melted by sweeping laser pulses of suitable width, typically about 1 microsecond duration, over the layer in small increments. The planarization of each metal layer eliminates irregular and discontinuous conditions between successive layers. The planarization method is particularly applicable to circuits having ground or power planes and allows for multilevel interconnects. Dielectric layers can also be planarized to produce a fully planar multilevel interconnect structure. The method is useful for the fabrication of VLSI circuits, particularly for wafer-scale integration.

Planarization of metal films for multilevel interconnects

DOEpatents

Tuckerman, David B.

1989-01-01

In the fabrication of multilevel integrated circuits, each metal layer is anarized by heating to momentarily melt the layer. The layer is melted by sweeping laser pulses of suitable width, typically about 1 microsecond duration, over the layer in small increments. The planarization of each metal layer eliminates irregular and discontinuous conditions between successive layers. The planarization method is particularly applicable to circuits having ground or power planes and allows for multilevel interconnects. Dielectric layers can also be planarized to produce a fully planar multilevel interconnect structure. The method is useful for the fabrication of VLSI circuits, particularly for wafer-scale integration.

Planarization of metal films for multilevel interconnects

DOEpatents

Tuckerman, D.B.

1985-08-23

In the fabrication of multilevel integrated circuits, each metal layer is planarized by heating to momentarily melt the layer. The layer is melted by sweeping laser pulses of suitable width, typically about 1 microsecond duration, over the layer in small increments. The planarization of each metal layer eliminates irregular and discontinuous conditions between successive layers. The planarization method is particularly applicable to circuits having ground or power planes and allows for multilevel interconnects. Dielectric layers can also be planarized to produce a fully planar multilevel interconnect structure. The method is useful for the fabrication of VLSI circuits, particularly for wafer-scale integration.

Planarization of metal films for multilevel interconnects

DOEpatents

Tuckerman, D.B.

1989-03-21

In the fabrication of multilevel integrated circuits, each metal layer is planarized by heating to momentarily melt the layer. The layer is melted by sweeping laser pulses of suitable width, typically about 1 microsecond duration, over the layer in small increments. The planarization of each metal layer eliminates irregular and discontinuous conditions between successive layers. The planarization method is particularly applicable to circuits having ground or power planes and allows for multilevel interconnects. Dielectric layers can also be planarized to produce a fully planar multilevel interconnect structure. The method is useful for the fabrication of VLSI circuits, particularly for wafer-scale integration. 6 figs.

Multilevel Monte Carlo simulation of Coulomb collisions

DOE PAGES

Rosin, M. S.; Ricketson, L. F.; Dimits, A. M.; ...

2014-05-29

We present a new, for plasma physics, highly efficient multilevel Monte Carlo numerical method for simulating Coulomb collisions. The method separates and optimally minimizes the finite-timestep and finite-sampling errors inherent in the Langevin representation of the Landau–Fokker–Planck equation. It does so by combining multiple solutions to the underlying equations with varying numbers of timesteps. For a desired level of accuracy ε , the computational cost of the method is O(ε –2) or (ε –2(lnε) 2), depending on the underlying discretization, Milstein or Euler–Maruyama respectively. This is to be contrasted with a cost of O(ε –3) for direct simulation Monte Carlomore » or binary collision methods. We successfully demonstrate the method with a classic beam diffusion test case in 2D, making use of the Lévy area approximation for the correlated Milstein cross terms, and generating a computational saving of a factor of 100 for ε=10 –5. Lastly, we discuss the importance of the method for problems in which collisions constitute the computational rate limiting step, and its limitations.« less

Integrated control/structure optimization by multilevel decomposition

NASA Technical Reports Server (NTRS)

Zeiler, Thomas A.; Gilbert, Michael G.

1990-01-01

A method for integrated control/structure optimization by multilevel decomposition is presented. It is shown that several previously reported methods were actually partial decompositions wherein only the control was decomposed into a subsystem design. One of these partially decomposed problems was selected as a benchmark example for comparison. The present paper fully decomposes the system into structural and control subsystem designs and produces an improved design. Theory, implementation, and results for the method are presented and compared with the benchmark example.

Promoting and Protecting Against Stigma in Assisted Living and Nursing Homes.

PubMed

Zimmerman, Sheryl; Dobbs, Debra; Roth, Erin G; Goldman, Susan; Peeples, Amanda D; Wallace, Brandy

2016-06-01

To determine the extent to which structures and processes of care in multilevel settings (independent living, assisted living, and nursing homes) result in stigma in assisted living and nursing homes. Ethnographic in-depth interviews were conducted in 5 multilevel settings with 256 residents, families, and staff members. Qualitative analyses identified the themes that resulted when examining text describing either structures of care or processes of care in relation to 7 codes associated with stigma. Four themes related to structures of care and stigma were identified, including the physical environment, case mix, staff training, and multilevel settings; five themes related to processes of care and stigma, including dining, independence, respect, privacy, and care provision. For each theme, examples were identified illustrating how structures and processes of care can potentially promote or protect against stigma. In no instance were examples or themes identified that suggested the staff intentionally promoted stigma; on the other hand, there was indication that some structures and processes were intentionally in place to protect against stigma. Perhaps the most important theme is the stigma related to multilevel settings, as it has the potential to reduce individuals' likelihood to seek and accept necessary care. Results suggest specific recommendations to modify care and reduce stigma. © The Author 2014. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Multilevel filtering elliptic preconditioners

NASA Technical Reports Server (NTRS)

Kuo, C. C. Jay; Chan, Tony F.; Tong, Charles

1989-01-01

A class of preconditioners is presented for elliptic problems built on ideas borrowed from the digital filtering theory and implemented on a multilevel grid structure. They are designed to be both rapidly convergent and highly parallelizable. The digital filtering viewpoint allows the use of filter design techniques for constructing elliptic preconditioners and also provides an alternative framework for understanding several other recently proposed multilevel preconditioners. Numerical results are presented to assess the convergence behavior of the new methods and to compare them with other preconditioners of multilevel type, including the usual multigrid method as preconditioner, the hierarchical basis method and a recent method proposed by Bramble-Pasciak-Xu.

Planarization of metal films for multilevel interconnects by pulsed laser heating

DOEpatents

Tuckerman, David B.

1987-01-01

In the fabrication of multilevel integrated circuits, each metal layer is planarized by heating to momentarily melt the layer. The layer is melted by sweeping laser pulses of suitable width, typically about 1 microsecond duration, over the layer in small increments. The planarization of each metal layer eliminates irregular and discontinuous conditions between successive layers. The planarization method is particularly applicable to circuits having ground or power planes and allows for multilevel interconnects. Dielectric layers can also be planarized to produce a fully planar multilevel interconnect structure. The method is useful for the fabrication of VLSI circuits, particularly for wafer-scale integration.

Constraints on trait combinations explain climatic drivers of biodiversity: the importance of trait covariance in community assembly.

PubMed

Dwyer, John M; Laughlin, Daniel C

2017-07-01

Trade-offs maintain diversity and structure communities along environmental gradients. Theory indicates that if covariance among functional traits sets a limit on the number of viable trait combinations in a given environment, then communities with strong multidimensional trait constraints should exhibit low species diversity. We tested this prediction in winter annual plant assemblages along an aridity gradient using multilevel structural equation modelling. Univariate and multivariate functional diversity measures were poorly explained by aridity, and were surprisingly poor predictors of community richness. By contrast, the covariance between maximum height and seed mass strengthened along the aridity gradient, and was strongly associated with richness declines. Community richness had a positive effect on local neighbourhood richness, indicating that climate effects on trait covariance indirectly influence diversity at local scales. We present clear empirical evidence that declines in species richness along gradients of environmental stress can be due to increasing constraints on multidimensional phenotypes. © 2017 John Wiley & Sons Ltd/CNRS.

Multidisciplinary design optimization using multiobjective formulation techniques

NASA Technical Reports Server (NTRS)

Chattopadhyay, Aditi; Pagaldipti, Narayanan S.

1995-01-01

This report addresses the development of a multidisciplinary optimization procedure using an efficient semi-analytical sensitivity analysis technique and multilevel decomposition for the design of aerospace vehicles. A semi-analytical sensitivity analysis procedure is developed for calculating computational grid sensitivities and aerodynamic design sensitivities. Accuracy and efficiency of the sensitivity analysis procedure is established through comparison of the results with those obtained using a finite difference technique. The developed sensitivity analysis technique are then used within a multidisciplinary optimization procedure for designing aerospace vehicles. The optimization problem, with the integration of aerodynamics and structures, is decomposed into two levels. Optimization is performed for improved aerodynamic performance at the first level and improved structural performance at the second level. Aerodynamic analysis is performed by solving the three-dimensional parabolized Navier Stokes equations. A nonlinear programming technique and an approximate analysis procedure are used for optimization. The proceduredeveloped is applied to design the wing of a high speed aircraft. Results obtained show significant improvements in the aircraft aerodynamic and structural performance when compared to a reference or baseline configuration. The use of the semi-analytical sensitivity technique provides significant computational savings.

Development and application of optimum sensitivity analysis of structures

NASA Technical Reports Server (NTRS)

Barthelemy, J. F. M.; Hallauer, W. L., Jr.

1984-01-01

The research focused on developing an algorithm applying optimum sensitivity analysis for multilevel optimization. The research efforts have been devoted to assisting NASA Langley's Interdisciplinary Research Office (IRO) in the development of a mature methodology for a multilevel approach to the design of complex (large and multidisciplinary) engineering systems. An effort was undertaken to identify promising multilevel optimization algorithms. In the current reporting period, the computer program generating baseline single level solutions was completed and tested out.

On some variational acceleration techniques and related methods for local refinement

NASA Astrophysics Data System (ADS)

Teigland, Rune

1998-10-01

This paper shows that the well-known variational acceleration method described by Wachspress (E. Wachspress, Iterative Solution of Elliptic Systems and Applications to the Neutron Diffusion Equations of Reactor Physics, Prentice-Hall, Englewood Cliffs, NJ, 1966) and later generalized to multilevels (known as the additive correction multigrid method (B.R Huthchinson and G.D. Raithby, Numer. Heat Transf., 9, 511-537 (1986))) is similar to the FAC method of McCormick and Thomas (S.F McCormick and J.W. Thomas, Math. Comput., 46, 439-456 (1986)) and related multilevel methods. The performance of the method is demonstrated for some simple model problems using local refinement and suggestions for improving the performance of the method are given.

Analysis of aircraft tires via semianalytic finite elements

NASA Technical Reports Server (NTRS)

Noor, Ahmed K.; Kim, Kyun O.; Tanner, John A.

1990-01-01

A computational procedure is presented for the geometrically nonlinear analysis of aircraft tires. The tire was modeled by using a two-dimensional laminated anisotropic shell theory with the effects of variation in material and geometric parameters included. The four key elements of the procedure are: (1) semianalytic finite elements in which the shell variables are represented by Fourier series in the circumferential direction and piecewise polynomials in the meridional direction; (2) a mixed formulation with the fundamental unknowns consisting of strain parameters, stress-resultant parameters, and generalized displacements; (3) multilevel operator splitting to effect successive simplifications, and to uncouple the equations associated with different Fourier harmonics; and (4) multilevel iterative procedures and reduction techniques to generate the response of the shell.

Examining the Dynamic Structure of Daily Internalizing and Externalizing Behavior at Multiple Levels of Analysis

PubMed Central

Wright, Aidan G. C.; Beltz, Adriene M.; Gates, Kathleen M.; Molenaar, Peter C. M.; Simms, Leonard J.

2015-01-01

Psychiatric diagnostic covariation suggests that the underlying structure of psychopathology is not one of circumscribed disorders. Quantitative modeling of individual differences in diagnostic patterns has uncovered several broad domains of mental disorder liability, of which the Internalizing and Externalizing spectra have garnered the greatest support. These dimensions have generally been estimated from lifetime or past-year comorbidity patters, which are distal from the covariation of symptoms and maladaptive behavior that ebb and flow in daily life. In this study, structural models are applied to daily diary data (Median = 94 days) of maladaptive behaviors collected from a sample (N = 101) of individuals diagnosed with personality disorders (PDs). Using multilevel and unified structural equation modeling, between-person, within-person, and person-specific structures were estimated from 16 behaviors that are encompassed by the Internalizing and Externalizing spectra. At the between-person level (i.e., individual differences in average endorsement across days) we found support for a two-factor Internalizing–Externalizing model, which exhibits significant associations with corresponding diagnostic spectra. At the within-person level (i.e., dynamic covariation among daily behavior pooled across individuals) we found support for a more differentiated, four-factor, Negative Affect-Detachment-Hostility-Disinhibition structure. Finally, we demonstrate that the person-specific structures of associations between these four domains are highly idiosyncratic. PMID:26732546

On codes with multi-level error-correction capabilities

NASA Technical Reports Server (NTRS)

Lin, Shu

1987-01-01

In conventional coding for error control, all the information symbols of a message are regarded equally significant, and hence codes are devised to provide equal protection for each information symbol against channel errors. However, in some occasions, some information symbols in a message are more significant than the other symbols. As a result, it is desired to devise codes with multilevel error-correcting capabilities. Another situation where codes with multi-level error-correcting capabilities are desired is in broadcast communication systems. An m-user broadcast channel has one input and m outputs. The single input and each output form a component channel. The component channels may have different noise levels, and hence the messages transmitted over the component channels require different levels of protection against errors. Block codes with multi-level error-correcting capabilities are also known as unequal error protection (UEP) codes. Structural properties of these codes are derived. Based on these structural properties, two classes of UEP codes are constructed.

A new rational-based optimal design strategy of ship structure based on multi-level analysis and super-element modeling method

NASA Astrophysics Data System (ADS)

Sun, Li; Wang, Deyu

2011-09-01

A new multi-level analysis method of introducing the super-element modeling method, derived from the multi-level analysis method first proposed by O. F. Hughes, has been proposed in this paper to solve the problem of high time cost in adopting a rational-based optimal design method for ship structural design. Furthermore, the method was verified by its effective application in optimization of the mid-ship section of a container ship. A full 3-D FEM model of a ship, suffering static and quasi-static loads, was used as the analyzing object for evaluating the structural performance of the mid-ship module, including static strength and buckling performance. Research results reveal that this new method could substantially reduce the computational cost of the rational-based optimization problem without decreasing its accuracy, which increases the feasibility and economic efficiency of using a rational-based optimal design method in ship structural design.

On the application of multilevel modeling in environmental and ecological studies

USGS Publications Warehouse

Qian, Song S.; Cuffney, Thomas F.; Alameddine, Ibrahim; McMahon, Gerard; Reckhow, Kenneth H.

2010-01-01

This paper illustrates the advantages of a multilevel/hierarchical approach for predictive modeling, including flexibility of model formulation, explicitly accounting for hierarchical structure in the data, and the ability to predict the outcome of new cases. As a generalization of the classical approach, the multilevel modeling approach explicitly models the hierarchical structure in the data by considering both the within- and between-group variances leading to a partial pooling of data across all levels in the hierarchy. The modeling framework provides means for incorporating variables at different spatiotemporal scales. The examples used in this paper illustrate the iterative process of model fitting and evaluation, a process that can lead to improved understanding of the system being studied.

A Multilevel Conceptual Framework to Understand the Role of Food Insecurity on Antiretroviral Therapy Adherence in Low-Resource Settings: From Theory to Practice

PubMed Central

Masa, Rainier; Chowa, Gina

2018-01-01

The objective of this study was to describe a multilevel conceptual framework to understand the role of food insecurity on antiretroviral therapy adherence. The authors illustrated an example of how they used the multilevel framework to develop an intervention for poor people living with HIV in a rural and low-resource community. The framework incorporates intra-personal, interpersonal, and structural-level theories of understanding and changing health behaviors. The framework recognizes the role of personal, social, and environmental factors on cognition and behavior, with particular attention to ways in which treatment adherence is enabled or prevented by structural conditions, such as food insecurity. PMID:28368779

A multilevel control approach for a modular structured space platform

NASA Technical Reports Server (NTRS)

Chichester, F. D.; Borelli, M. T.

1981-01-01

A three axis mathematical representation of a modular assembled space platform consisting of interconnected discrete masses, including a deployable truss module, was derived for digital computer simulation. The platform attitude control system as developed to provide multilevel control utilizing the Gauss-Seidel second level formulation along with an extended form of linear quadratic regulator techniques. The objectives of the multilevel control are to decouple the space platform's spatial axes and to accommodate the modification of the platform's configuration for each of the decoupled axes.

Modelling the Evolution of Social Structure

PubMed Central

Sutcliffe, A. G.; Dunbar, R. I. M.; Wang, D.

2016-01-01

Although simple social structures are more common in animal societies, some taxa (mainly mammals) have complex, multi-level social systems, in which the levels reflect differential association. We develop a simulation model to explore the conditions under which multi-level social systems of this kind evolve. Our model focuses on the evolutionary trade-offs between foraging and social interaction, and explores the impact of alternative strategies for distributing social interaction, with fitness criteria for wellbeing, alliance formation, risk, stress and access to food resources that reward social strategies differentially. The results suggest that multi-level social structures characterised by a few strong relationships, more medium ties and large numbers of weak ties emerge only in a small part of the overall fitness landscape, namely where there are significant fitness benefits from wellbeing and alliance formation and there are high levels of social interaction. In contrast, ‘favour-the-few’ strategies are more competitive under a wide range of fitness conditions, including those producing homogeneous, single-level societies of the kind found in many birds and mammals. The simulations suggest that the development of complex, multi-level social structures of the kind found in many primates (including humans) depends on a capacity for high investment in social time, preferential social interaction strategies, high mortality risk and/or differential reproduction. These conditions are characteristic of only a few mammalian taxa. PMID:27427758

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…

Selective harmonic elimination strategy in eleven level inverter for PV system with unbalanced DC sources

NASA Astrophysics Data System (ADS)

Ghoudelbourk, Sihem.; Dib, D.; Meghni, B.; Zouli, M.

2017-02-01

The paper deals with the multilevel converters control strategy for photovoltaic system integrated in distribution grids. The objective of the proposed work is to design multilevel inverters for solar energy applications so as to reduce the Total Harmonic Distortion (THD) and to improve the power quality. The multilevel inverter power structure plays a vital role in every aspect of the power system. It is easier to produce a high-power, high-voltage inverter with the multilevel structure. The topologies of multilevel inverter have several advantages such as high output voltage, lower total harmonic distortion (THD) and reduction of voltage ratings of the power semiconductor switching devices. The proposed control strategy ensures an implementation of selective harmonic elimination (SHE) modulation for eleven levels. SHE is a very important and efficient strategy of eliminating selected harmonics by judicious selection of the firing angles of the inverter. Harmonics elimination technique eliminates the need of the expensive low pass filters in the system. Previous research considered that constant and equal DC sources with invariant behavior; however, this research extends earlier work to include variant DC sources, which are typical of lead-acid batteries when used in system PV. This Study also investigates methods to minimize the total harmonic distortion of the synthesized multilevel waveform and to help balance the battery voltage. The harmonic elimination method was used to eliminate selected lower dominant harmonics resulting from the inverter switching action.

Heat transfer analysis of skin during thermal therapy using thermal wave equation.

PubMed

Kashcooli, Meisam; Salimpour, Mohammad Reza; Shirani, Ebrahim

2017-02-01

Specifying exact geometry of vessel network and its effect on temperature distribution in living tissues is one of the most complicated problems of the bioheat field. In this paper, the effects of blood vessels on temperature distribution in a skin tissue subjected to various thermal therapy conditions are investigated. Present model consists of counter-current multilevel vessel network embedded in a three-dimensional triple-layered skin structure. Branching angles of vessels are calculated using the physiological principle of minimum work. Length and diameter ratios are specified using length doubling rule and Cube law, respectively. By solving continuity, momentum and energy equations for blood flow and Pennes and modified Pennes bioheat equations for the tissue, temperature distributions in the tissue are measured. Effects of considering modified Pennes bioheat equation are investigated, comprehensively. It is also observed that blood has an impressive role in temperature distribution of the tissue, especially at high temperatures. The effects of different parameters such as boundary conditions, relaxation time, thermal properties of skin, metabolism and pulse heat flux on temperature distribution are investigated. Tremendous effect of boundary condition type at the lower boundary is noted. It seems that neither insulation nor constant temperature at this boundary can completely describe the real physical phenomena. It is expected that real temperature at the lower levels is somewhat between two predicted values. The effect of temperature on the thermal properties of skin tissue is considered. It is shown that considering temperature dependent values for thermal conductivity is important in the temperature distribution estimation of skin tissue; however, the effect of temperature dependent values for specific heat capacity is negligible. It is seen that considering modified Pennes equation in processes with high heat flux during low times is significant. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multi-level adaptive finite element methods. 1: Variation problems

NASA Technical Reports Server (NTRS)

Brandt, A.

1979-01-01

A general numerical strategy for solving partial differential equations and other functional problems by cycling between coarser and finer levels of discretization is described. Optimal discretization schemes are provided together with very fast general solvers. It is described in terms of finite element discretizations of general nonlinear minimization problems. The basic processes (relaxation sweeps, fine-grid-to-coarse-grid transfers of residuals, coarse-to-fine interpolations of corrections) are directly and naturally determined by the objective functional and the sequence of approximation spaces. The natural processes, however, are not always optimal. Concrete examples are given and some new techniques are reviewed. Including the local truncation extrapolation and a multilevel procedure for inexpensively solving chains of many boundary value problems, such as those arising in the solution of time-dependent problems.

Multilevel Mixture Kalman Filter

NASA Astrophysics Data System (ADS)

Guo, Dong; Wang, Xiaodong; Chen, Rong

2004-12-01

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

Multi-level manual and autonomous control superposition for intelligent telerobot

NASA Technical Reports Server (NTRS)

Hirai, Shigeoki; Sato, T.

1989-01-01

Space telerobots are recognized to require cooperation with human operators in various ways. Multi-level manual and autonomous control superposition in telerobot task execution is described. The object model, the structured master-slave manipulation system, and the motion understanding system are proposed to realize the concept. The object model offers interfaces for task level and object level human intervention. The structured master-slave manipulation system offers interfaces for motion level human intervention. The motion understanding system maintains the consistency of the knowledge through all the levels which supports the robot autonomy while accepting the human intervention. The superposing execution of the teleoperational task at multi-levels realizes intuitive and robust task execution for wide variety of objects and in changeful environment. The performance of several examples of operating chemical apparatuses is shown.

Integrated aerodynamic/dynamic/structural optimization of helicopter rotor blades using multilevel decomposition

NASA Technical Reports Server (NTRS)

Walsh, Joanne L.; Young, Katherine C.; Pritchard, Jocelyn I.; Adelman, Howard M.; Mantay, Wayne R.

1995-01-01

This paper describes an integrated aerodynamic/dynamic/structural (IADS) optimization procedure for helicopter rotor blades. The procedure combines performance, dynamics, and structural analyses with a general-purpose optimizer using multilevel decomposition techniques. At the upper level, the structure is defined in terms of global quantities (stiffness, mass, and average strains). At the lower level, the structure is defined in terms of local quantities (detailed dimensions of the blade structure and stresses). The IADS procedure provides an optimization technique that is compatible with industrial design practices in which the aerodynamic and dynamic designs are performed at a global level and the structural design is carried out at a detailed level with considerable dialog and compromise among the aerodynamic, dynamic, and structural groups. The IADS procedure is demonstrated for several examples.

Multilevel decomposition approach to integrated aerodynamic/dynamic/structural optimization of helicopter rotor blades

NASA Technical Reports Server (NTRS)

Walsh, Joanne L.; Young, Katherine C.; Pritchard, Jocelyn I.; Adelman, Howard M.; Mantay, Wayne R.

1994-01-01

This paper describes an integrated aerodynamic, dynamic, and structural (IADS) optimization procedure for helicopter rotor blades. The procedure combines performance, dynamics, and structural analyses with a general purpose optimizer using multilevel decomposition techniques. At the upper level, the structure is defined in terms of local quantities (stiffnesses, mass, and average strains). At the lower level, the structure is defined in terms of local quantities (detailed dimensions of the blade structure and stresses). The IADS procedure provides an optimization technique that is compatible with industrial design practices in which the aerodynamic and dynamic design is performed at a global level and the structural design is carried out at a detailed level with considerable dialogue and compromise among the aerodynamic, dynamic, and structural groups. The IADS procedure is demonstrated for several cases.

Final Report: Subcontract B623868 Algebraic Multigrid solvers for coupled PDE systems

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

Brannick, J.

The Pennsylvania State University (“Subcontractor”) continued to work on the design of algebraic multigrid solvers for coupled systems of partial differential equations (PDEs) arising in numerical modeling of various applications, with a main focus on solving the Dirac equation arising in Quantum Chromodynamics (QCD). The goal of the proposed work was to develop combined geometric and algebraic multilevel solvers that are robust and lend themselves to efficient implementation on massively parallel heterogeneous computers for these QCD systems. The research in these areas built on previous works, focusing on the following three topics: (1) the development of parallel full-multigrid (PFMG) andmore » non-Galerkin coarsening techniques in this frame work for solving the Wilson Dirac system; (2) the use of these same Wilson MG solvers for preconditioning the Overlap and Domain Wall formulations of the Dirac equation; and (3) the design and analysis of algebraic coarsening algorithms for coupled PDE systems including Stokes equation, Maxwell equation and linear elasticity.« less

Interviewer effects on non-response propensity in longitudinal surveys: a multilevel modelling approach

PubMed Central

Vassallo, Rebecca; Durrant, Gabriele B; Smith, Peter W F; Goldstein, Harvey

2015-01-01

The paper investigates two different multilevel approaches, the multilevel cross-classified and the multiple-membership models, for the analysis of interviewer effects on wave non-response in longitudinal surveys. The models proposed incorporate both interviewer and area effects to account for the non-hierarchical structure, the influence of potentially more than one interviewer across waves and possible confounding of area and interviewer effects arising from the non-random allocation of interviewers across areas. The methods are compared by using a data set: the UK Family and Children Survey. PMID:25598587

Theory and modelling of light-matter interactions in photonic crystal cavity systems coupled to quantum dot ensembles

NASA Astrophysics Data System (ADS)

Cartar, William K.

Photonic crystal microcavity quantum dot lasers show promise as high quality-factor, low threshold lasers, that can be integrated on-chip, with tunable room temperature opera- tions. However, such semiconductor microcavity lasers are notoriously difficult to model in a self-consistent way and are primarily modelled by simplified rate equation approxima- tions, typically fit to experimental data, which limits investigations of their optimization and fundamental light-matter interaction processes. Moreover, simple cavity mode optical theory and rate equations have recently been shown to fail in explaining lasing threshold trends in triangular lattice photonic crystal cavities as a function of cavity size, and the potential impact of fabrication disorder is not well understood. In this thesis, we develop a simple but powerful numerical scheme for modelling the quantum dot active layer used for lasing in these photonic crystal cavity structures, as an ensemble of randomly posi- tioned artificial two-level atoms. Each two-level atom is defined by optical Bloch equations solved by a quantum master equation that includes phenomenological pure dephasing and an incoherent pump rate that effectively models a multi-level gain system. Light-matter in- teractions of both passive and lasing structures are analyzed using simulation defined tools and post-simulation Green function techniques. We implement an active layer ensemble of up to 24,000 statistically unique quantum dots in photonic crystal cavity simulations, using a self-consistent finite-difference time-domain method. This method has the distinct advantage of capturing effects such as dipole-dipole coupling and radiative decay, without the need for any phenomenological terms, since the time-domain solution self-consistently captures these effects. Our analysis demonstrates a powerful ability to connect with recent experimental trends, while remaining completely general in its set-up; for example, we do not invoke common approximations such as the rotating-wave or slowly-varying envelope approximations, and solve dynamics with zero a priori knowledge.

Multilevel model of safety climate for furniture industries.

PubMed

Rodrigues, Matilde A; Arezes, Pedro M; Leão, Celina P

2015-01-01

Furniture companies can analyze their safety status using quantitative measures. However, the data needed are not always available and the number of accidents is under-reported. Safety climate scales may be an alternative. However, there are no validated Portuguese scales that account for the specific attributes of the furniture sector. The current study aims to develop and validate an instrument that uses a multilevel structure to measure the safety climate of the Portuguese furniture industry. The Safety Climate in Wood Industries (SCWI) model was developed and applied to the safety climate analysis using three different scales: organizational, group and individual. A multilevel exploratory factor analysis was performed to analyze the factorial structure. The studied companies' safety conditions were also analyzed. Different factorial structures were found between and within levels. In general, the results show the presence of a group-level safety climate. The scores of safety climates are directly and positively related to companies' safety conditions; the organizational scale is the one that best reflects the actual safety conditions. The SCWI instrument allows for the identification of different safety climates in groups that comprise the same furniture company and it seems to reflect those groups' safety conditions. The study also demonstrates the need for a multilevel analysis of the studied instrument.

Jet formation and equatorial superrotation in Jupiter's atmosphere: Numerical modelling using a new efficient parallel code

NASA Astrophysics Data System (ADS)

Rivier, Leonard Gilles

Using an efficient parallel code solving the primitive equations of atmospheric dynamics, the jet structure of a Jupiter like atmosphere is modeled. In the first part of this thesis, a parallel spectral code solving both the shallow water equations and the multi-level primitive equations of atmospheric dynamics is built. The implementation of this code called BOB is done so that it runs effectively on an inexpensive cluster of workstations. A one dimensional decomposition and transposition method insuring load balancing among processes is used. The Legendre transform is cache-blocked. A "compute on the fly" of the Legendre polynomials used in the spectral method produces a lower memory footprint and enables high resolution runs on relatively small memory machines. Performance studies are done using a cluster of workstations located at the National Center for Atmospheric Research (NCAR). BOB performances are compared to the parallel benchmark code PSTSWM and the dynamical core of NCAR's CCM3.6.6. In both cases, the comparison favors BOB. In the second part of this thesis, the primitive equation version of the code described in part I is used to study the formation of organized zonal jets and equatorial superrotation in a planetary atmosphere where the parameters are chosen to best model the upper atmosphere of Jupiter. Two levels are used in the vertical and only large scale forcing is present. The model is forced towards a baroclinically unstable flow, so that eddies are generated by baroclinic instability. We consider several types of forcing, acting on either the temperature or the momentum field. We show that only under very specific parametric conditions, zonally elongated structures form and persist resembling the jet structure observed near the cloud level top (1 bar) on Jupiter. We also study the effect of an equatorial heat source, meant to be a crude representation of the effect of the deep convective planetary interior onto the outer atmospheric layer. We show that such heat forcing is able to produce strong equatorial superrotating winds, one of the most striking feature of the Jovian circulation.

Multilevel geometry optimization

NASA Astrophysics Data System (ADS)

Rodgers, Jocelyn M.; Fast, Patton L.; Truhlar, Donald G.

2000-02-01

Geometry optimization has been carried out for three test molecules using six multilevel electronic structure methods, in particular Gaussian-2, Gaussian-3, multicoefficient G2, multicoefficient G3, and two multicoefficient correlation methods based on correlation-consistent basis sets. In the Gaussian-2 and Gaussian-3 methods, various levels are added and subtracted with unit coefficients, whereas the multicoefficient Gaussian-x methods involve noninteger parameters as coefficients. The multilevel optimizations drop the average error in the geometry (averaged over the 18 cases) by a factor of about two when compared to the single most expensive component of a given multilevel calculation, and in all 18 cases the accuracy of the atomization energy for the three test molecules improves; with an average improvement of 16.7 kcal/mol.

A multilevel layout algorithm for visualizing physical and genetic interaction networks, with emphasis on their modular organization.

PubMed

Tuikkala, Johannes; Vähämaa, Heidi; Salmela, Pekka; Nevalainen, Olli S; Aittokallio, Tero

2012-03-26

Graph drawing is an integral part of many systems biology studies, enabling visual exploration and mining of large-scale biological networks. While a number of layout algorithms are available in popular network analysis platforms, such as Cytoscape, it remains poorly understood how well their solutions reflect the underlying biological processes that give rise to the network connectivity structure. Moreover, visualizations obtained using conventional layout algorithms, such as those based on the force-directed drawing approach, may become uninformative when applied to larger networks with dense or clustered connectivity structure. We implemented a modified layout plug-in, named Multilevel Layout, which applies the conventional layout algorithms within a multilevel optimization framework to better capture the hierarchical modularity of many biological networks. Using a wide variety of real life biological networks, we carried out a systematic evaluation of the method in comparison with other layout algorithms in Cytoscape. The multilevel approach provided both biologically relevant and visually pleasant layout solutions in most network types, hence complementing the layout options available in Cytoscape. In particular, it could improve drawing of large-scale networks of yeast genetic interactions and human physical interactions. In more general terms, the biological evaluation framework developed here enables one to assess the layout solutions from any existing or future graph drawing algorithm as well as to optimize their performance for a given network type or structure. By making use of the multilevel modular organization when visualizing biological networks, together with the biological evaluation of the layout solutions, one can generate convenient visualizations for many network biology applications.

Multilevel Interventions: Study Design and Analysis Issues

PubMed Central

Gross, Cary P.; Zaslavsky, Alan M.; Taplin, Stephen H.

2012-01-01

Multilevel interventions, implemented at the individual, physician, clinic, health-care organization, and/or community level, increasingly are proposed and used in the belief that they will lead to more substantial and sustained changes in behaviors related to cancer prevention, detection, and treatment than would single-level interventions. It is important to understand how intervention components are related to patient outcomes and identify barriers to implementation. Designs that permit such assessments are uncommon, however. Thus, an important way of expanding our knowledge about multilevel interventions would be to assess the impact of interventions at different levels on patients as well as the independent and synergistic effects of influences from different levels. It also would be useful to assess the impact of interventions on outcomes at different levels. Multilevel interventions are much more expensive and complicated to implement and evaluate than are single-level interventions. Given how little evidence there is about the value of multilevel interventions, however, it is incumbent upon those arguing for this approach to do multilevel research that explicates the contributions that interventions at different levels make to the desired outcomes. Only then will we know whether multilevel interventions are better than more focused interventions and gain greater insights into the kinds of interventions that can be implemented effectively and efficiently to improve health and health care for individuals with cancer. This chapter reviews designs for assessing multilevel interventions and analytic ways of controlling for potentially confounding variables that can account for the complex structure of multilevel data. PMID:22623596

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…

Multilevel Factor Analyses of Family Data from the Hawai'i Family Study of Cognition

ERIC Educational Resources Information Center

McArdle, John J.; Hamagami, Fumiaki; Bautista, Randy; Onoye, Jane; Hishinuma, Earl S.; Prescott, Carol A.; Takeshita, Junji; Zonderman, Alan B.; Johnson, Ronald C.

2014-01-01

In this study, we reanalyzed the classic Hawai'i Family Study of Cognition (HFSC) data using contemporary multilevel modeling techniques. We used the HFSC baseline data ("N" = 6,579) and reexamined the factorial structure of 16 cognitive variables using confirmatory (restricted) measurement models in an explicit sequence. These models…

Multiple Imputation of Multilevel Missing Data-Rigor versus Simplicity

ERIC Educational Resources Information Center

Drechsler, Jörg

2015-01-01

Multiple imputation is widely accepted as the method of choice to address item-nonresponse in surveys. However, research on imputation strategies for the hierarchical structures that are typically found in the data in educational contexts is still limited. While a multilevel imputation model should be preferred from a theoretical point of view if…

"Using Power Tables to Compute Statistical Power in Multilevel Experimental Designs"

ERIC Educational Resources Information Center

Konstantopoulos, Spyros

2009-01-01

Power computations for one-level experimental designs that assume simple random samples are greatly facilitated by power tables such as those presented in Cohen's book about statistical power analysis. However, in education and the social sciences experimental designs have naturally nested structures and multilevel models are needed to compute the…

Distinguishing Continuous and Discrete Approaches to Multilevel Mixture IRT Models: A Model Comparison Perspective

ERIC Educational Resources Information Center

Zhu, Xiaoshu

2013-01-01

The current study introduced a general modeling framework, multilevel mixture IRT (MMIRT) which detects and describes characteristics of population heterogeneity, while accommodating the hierarchical data structure. In addition to introducing both continuous and discrete approaches to MMIRT, the main focus of the current study was to distinguish…

Efficiently Exploring Multilevel Data with Recursive Partitioning

ERIC Educational Resources Information Center

Martin, Daniel P.; von Oertzen, Timo; Rimm-Kaufman, Sara E.

2015-01-01

There is an increasing number of datasets with many participants, variables, or both, in education and other fields that often deal with large, multilevel data structures. Once initial confirmatory hypotheses are exhausted, it can be difficult to determine how best to explore the dataset to discover hidden relationships that could help to inform…

Two-bit multi-level phase change random access memory with a triple phase change material stack structure

NASA Astrophysics Data System (ADS)

Gyanathan, Ashvini; Yeo, Yee-Chia

2012-11-01

This work demonstrates a novel two-bit multi-level device structure comprising three phase change material (PCM) layers, separated by SiN thermal barrier layers. This triple PCM stack consisted of (from bottom to top), Ge2Sb2Te5 (GST), an ultrathin SiN barrier, nitrogen-doped GST, another ultrathin SiN barrier, and Ag0.5In0.5Sb3Te6. The PCM layers can selectively amorphize to form 4 different resistance levels ("00," "01," "10," and "11") using respective voltage pulses. Electrical characterization was extensively performed on these devices. Thermal analysis was also done to understand the physics behind the phase changing characteristics of the two-bit memory devices. The melting and crystallization temperatures of the PCMs play important roles in the power consumption of the multi-level devices. The electrical resistivities and thermal conductivities of the PCMs and the SiN thermal barrier are also crucial factors contributing to the phase changing behaviour of the PCMs in the two-bit multi-level PCRAM device.

Algebraic dynamic multilevel method for compositional flow in heterogeneous porous media

NASA Astrophysics Data System (ADS)

Cusini, Matteo; Fryer, Barnaby; van Kruijsdijk, Cor; Hajibeygi, Hadi

2018-02-01

This paper presents the algebraic dynamic multilevel method (ADM) for compositional flow in three dimensional heterogeneous porous media in presence of capillary and gravitational effects. As a significant advancement compared to the ADM for immiscible flows (Cusini et al., 2016) [33], here, mass conservation equations are solved along with k-value based thermodynamic equilibrium equations using a fully-implicit (FIM) coupling strategy. Two different fine-scale compositional formulations are considered: (1) the natural variables and (2) the overall-compositions formulation. At each Newton's iteration the fine-scale FIM Jacobian system is mapped to a dynamically defined (in space and time) multilevel nested grid. The appropriate grid resolution is chosen based on the contrast of user-defined fluid properties and on the presence of specific features (e.g., well source terms). Consistent mapping between different resolutions is performed by the means of sequences of restriction and prolongation operators. While finite-volume restriction operators are employed to ensure mass conservation at all resolutions, various prolongation operators are considered. In particular, different interpolation strategies can be used for the different primary variables, and multiscale basis functions are chosen as pressure interpolators so that fine scale heterogeneities are accurately accounted for across different resolutions. Several numerical experiments are conducted to analyse the accuracy, efficiency and robustness of the method for both 2D and 3D domains. Results show that ADM provides accurate solutions by employing only a fraction of the number of grid-cells employed in fine-scale simulations. As such, it presents a promising approach for large-scale simulations of multiphase flow in heterogeneous reservoirs with complex non-linear fluid physics.

Multi-level diffractive optics for single laser exposure fabrication of telecom-band diamond-like 3-dimensional photonic crystals.

PubMed

Chanda, Debashis; Abolghasemi, Ladan E; Haque, Moez; Ng, Mi Li; Herman, Peter R

2008-09-29

We present a novel multi-level diffractive optical element for diffractive optic near-field lithography based fabrication of large-area diamond-like photonic crystal structure in a single laser exposure step. A multi-level single-surface phase element was laser fabricated on a thin polymer film by two-photon polymerization. A quarter-period phase shift was designed into the phase elements to generate a 3D periodic intensity distribution of double basis diamond-like structure. Finite difference time domain calculation of near-field diffraction patterns and associated isointensity surfaces are corroborated by definitive demonstration of a diamond-like woodpile structure formed inside thick photoresist. A large number of layers provided a strong stopband in the telecom band that matched predictions of numerical band calculation. SEM and spectral observations indicate good structural uniformity over large exposure area that promises 3D photonic crystal devices with high optical quality for a wide range of motif shapes and symmetries. Optical sensing is demonstrated by spectral shifts of the Gamma-Zeta stopband under liquid emersion.

Theoretical and software considerations for general dynamic analysis using multilevel substructured models

NASA Technical Reports Server (NTRS)

Schmidt, R. J.; Dodds, R. H., Jr.

1985-01-01

The dynamic analysis of complex structural systems using the finite element method and multilevel substructured models is presented. The fixed-interface method is selected for substructure reduction because of its efficiency, accuracy, and adaptability to restart and reanalysis. This method is extended to reduction of substructures which are themselves composed of reduced substructures. The implementation and performance of the method in a general purpose software system is emphasized. Solution algorithms consistent with the chosen data structures are presented. It is demonstrated that successful finite element software requires the use of software executives to supplement the algorithmic language. The complexity of the implementation of restart and reanalysis porcedures illustrates the need for executive systems to support the noncomputational aspects of the software. It is shown that significant computational efficiencies can be achieved through proper use of substructuring and reduction technbiques without sacrificing solution accuracy. The restart and reanalysis capabilities and the flexible procedures for multilevel substructured modeling gives economical yet accurate analyses of complex structural systems.

Master equation theory applied to the redistribution of polarized radiation in the weak radiation field limit. IV. Application to the second solar spectrum of the Na I D1 and D2 lines

NASA Astrophysics Data System (ADS)

Bommier, Véronique

2016-06-01

Context. The spectrum of the linear polarization, which is formed by scattering and observed on the solar disk close to the limb, is very different from the intensity spectrum and thus able to provide new information, in particular about anisotropies in the solar surface plasma and magnetic fields. In addition, a large number of lines show far wing polarization structures assigned to partial redistribution (PRD), which we prefer to denote as Rayleigh/Raman scattering. The two-level or two-term atom approximation without any lower level polarization is insufficient for many lines. Aims: In the previous paper of this series, we presented our theory generalized to the multilevel and multiline atom and comprised of statistical equilibrium equations for the atomic density matrix elements and radiative transfer equation for the polarized radiation. The present paper is devoted to applying this theory to model the second solar spectrum of the Na I D1 and D2 lines. Methods: The solution method is iterative, of the lambda-iteration type. The usual acceleration techniques were considered or even applied, but we found these to be unsuccessful, in particular because of nonlinearity or large number of quantities determining the radiation at each depth. Results: The observed spectrum is qualitatively reproduced in line center, but the convergence is yet to be reached in the far wings and the observed spectrum is not totally reproduced there. Conclusions: We need to investigate noniterative resolution methods. The other limitation lies in the one-dimensional (1D) atmosphere model, which is unable to reproduce the intermittent matter structure formed of small loops or spicules in the chromosphere. This modeling is rough, but the computing time in the presence of hyperfine structure and PRD prevents us from envisaging a three-dimensional (3D) model at this instant.

A Multilevel Simultaneous Equations Model for Within-Cluster Dynamic Effects, with an Application to Reciprocal Parent-Child and Sibling Effects

ERIC Educational Resources Information Center

Steele, Fiona; Rasbash, Jon; Jenkins, Jennifer

2013-01-01

There has been substantial interest in the social and health sciences in the reciprocal causal influences that people in close relationships have on one another. Most research has considered reciprocal processes involving only 2 units, although many social relationships of interest occur within a larger group (e.g., families, work groups, peer…

Agent-based model with multi-level herding for complex financial systems

NASA Astrophysics Data System (ADS)

Chen, Jun-Jie; Tan, Lei; Zheng, Bo

2015-02-01

In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level.

Agent-based model with multi-level herding for complex financial systems

PubMed Central

Chen, Jun-Jie; Tan, Lei; Zheng, Bo

2015-01-01

In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level. PMID:25669427

On an efficient multilevel inverter assembly: structural savings and design optimisations

NASA Astrophysics Data System (ADS)

Choupan, Reza; Nazarpour, Daryoush; Golshannavaz, Sajjad

2018-01-01

This study puts forward an efficient unit cell to be taken in use in multilevel inverter assemblies. The proposed structure is in line with reductions in number of direct current (dc) voltage sources, insulated-gate bipolar transistors (IGBTs), gate driver circuits, installation area, and hence the implementation costs. Such structural savings do not sacrifice the technical performance of the proposed design wherein an increased number of output voltage levels is attained, interestingly. Targeting a techno-economic characteristic, the contemplated structure is included as the key unit of cascaded multilevel inverters. Such extensions require development of applicable design procedures. To this end, two efficient strategies are elaborated to determine the magnitudes of input dc voltage sources. As well, an optimisation process is developed to explore the optimal allocation of different parameters in overall performance of the proposed inverter. These parameters are investigated as the number of IGBTs, dc sources, diodes, and overall blocked voltage on switches. In the lights of these characteristics, a comprehensive analysis is established to compare the proposed design with the conventional and recently developed structures. Detailed simulation and experimental studies are conducted to assess the performance of the proposed design. The obtained results are discussed in depth.

Distal and proximal predictors of snacking at work: A daily-survey study.

PubMed

Sonnentag, Sabine; Pundt, Alexander; Venz, Laura

2017-02-01

This study aimed at examining predictors of healthy and unhealthy snacking at work. As proximal predictors we looked at food-choice motives (health motive, affect-regulation motive); as distal predictors we included organizational eating climate, emotional eating, and self-control demands at work. We collected daily survey data from 247 employees, over a period of 2 workweeks. Multilevel structural equation modeling showed that organizational eating climate predicted health as food-choice motive, whereas emotional eating and self-control demands predicted affect regulation as food-choice motive. The health motive, in turn, predicted consuming more fruits and more cereal bars and less sweet snacks; the affect-regulation motive predicted consuming more sweet snacks. Findings highlight the importance of a health-promoting eating climate within the organization and point to the potential harm of high self-control demands at work. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

The Role of School Principals in Shaping Children's Values.

PubMed

Berson, Yair; Oreg, Shaul

2016-12-01

Instilling values in children is among the cornerstones of every society. There is wide agreement that beyond academic teaching, schools play an important role in shaping schoolchildren's character, imparting in them values such as curiosity, achievement, benevolence, and citizenship. Despite the importance of this topic, we know very little about whether and how schools affect children's values. In this large-scale longitudinal study, we examined school principals' roles in the development of children's values. We hypothesized that relationships exist between principals' values and changes in children's values through the mediating effect of the school climate. To test our predictions, we collected data from 252 school principals, 3,658 teachers, and 49,401 schoolchildren. A multilevel structural-equation-modeling analysis yielded overall support for our hypotheses. These findings contribute to understanding the development of children's values and the far-reaching impact of leaders' values. They also demonstrate effects of schools on children beyond those on academic achievement.

Object-oriented biomedical system modelling--the language.

PubMed

Hakman, M; Groth, T

1999-11-01

The paper describes a new object-oriented biomedical continuous system modelling language (OOBSML). It is fully object-oriented and supports model inheritance, encapsulation, and model component instantiation and behaviour polymorphism. Besides the traditional differential and algebraic equation expressions the language includes also formal expressions for documenting models and defining model quantity types and quantity units. It supports explicit definition of model input-, output- and state quantities, model components and component connections. The OOBSML model compiler produces self-contained, independent, executable model components that can be instantiated and used within other OOBSML models and/or stored within model and model component libraries. In this way complex models can be structured as multilevel, multi-component model hierarchies. Technically the model components produced by the OOBSML compiler are executable computer code objects based on distributed object and object request broker technology. This paper includes both the language tutorial and the formal language syntax and semantic description.

Collective-efficacy as a mediator of the relationship of leaders' personality traits and team performance: A cross-level analysis.

PubMed

Li, Xiaoshan; Zhou, Mingjie; Zhao, Na; Zhang, Shanshan; Zhang, Jianxin

2015-06-01

The relationship between a leader's personality and his team's performance has been established in organisational research, but the underlying process and mechanism responsible for this effect have not been fully explored. Both the traditional multiple linear regression and the multilevel structural equation model approaches were used in this study to test a proposed mediating model of subordinates' perception of collective efficacy between leader personality and team performance. The results show that the team leader's extraversion and conscientiousness personality traits were related positively to both the team-average (individual) perception of collective efficacy and team performance, and the collective efficacy mediated the relationship of the leader's personality traits and team performance. This study also discusses how Chinese cultural elements play a role in such a mediating model. © 2014 International Union of Psychological Science.

Motivation Mediates the Perfectionism-Burnout Relationship: A Three-Wave Longitudinal Study With Junior Athletes.

PubMed

Madigan, Daniel J; Stoeber, Joachim; Passfield, Louis

2016-08-01

Perfectionism in sports has been shown to predict longitudinal changes in athlete burnout. What mediates these changes over time, however, is still unclear. Adopting a self-determination theory perspective and using a three-wave longitudinal design, the current study examined perfectionistic strivings, perfectionistic concerns, autonomous motivation, controlled motivation, and athlete burnout in 141 junior athletes (mean age = 17.3 years) over 6 months of active training. When multilevel structural equation modeling was employed to test a mediational model, a differential pattern of between- and within-person relationships emerged. Whereas autonomous motivation mediated the negative relationship that perfectionistic strivings had with burnout at the between- and within-person level, controlled motivation mediated the positive relationship that perfectionistic concerns had with burnout at the between-persons level only. The present findings suggest that differences in autonomous and controlled motivation explain why perfectionism predicts changes in athlete burnout over time.

Structural optimization by generalized, multilevel decomposition

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, J.; James, B. B.; Riley, M. F.

1985-01-01

The developments toward a general multilevel optimization capability and results for a three-level structural optimization are described. The method partitions a structure into a number of substructuring levels where each substructure corresponds to a subsystem in the general case of an engineering system. The method is illustrated by a portal framework that decomposes into individual beams. Each beam is a box that can be further decomposed into stiffened plates. Substructuring for this example spans three different levels: (1) the bottom level of finite elements representing the plates; (2) an intermediate level of beams treated as substructures; and (3) the top level for the assembled structure. The three-level case is now considered to be qualitatively complete.

Multi-level bandwidth efficient block modulation codes

NASA Technical Reports Server (NTRS)

Lin, Shu

1989-01-01

The multilevel technique is investigated for combining block coding and modulation. There are four parts. In the first part, a formulation is presented for signal sets on which modulation codes are to be constructed. Distance measures on a signal set are defined and their properties are developed. In the second part, a general formulation is presented for multilevel modulation codes in terms of component codes with appropriate Euclidean distances. The distance properties, Euclidean weight distribution and linear structure of multilevel modulation codes are investigated. In the third part, several specific methods for constructing multilevel block modulation codes with interdependency among component codes are proposed. Given a multilevel block modulation code C with no interdependency among the binary component codes, the proposed methods give a multilevel block modulation code C which has the same rate as C, a minimum squared Euclidean distance not less than that of code C, a trellis diagram with the same number of states as that of C and a smaller number of nearest neighbor codewords than that of C. In the last part, error performance of block modulation codes is analyzed for an AWGN channel based on soft-decision maximum likelihood decoding. Error probabilities of some specific codes are evaluated based on their Euclidean weight distributions and simulation results.

The relationship between multilevel models and non-parametric multilevel mixture models: Discrete approximation of intraclass correlation, random coefficient distributions, and residual heteroscedasticity.

PubMed

Rights, Jason D; Sterba, Sonya K

2016-11-01

Multilevel data structures are common in the social sciences. Often, such nested data are analysed with multilevel models (MLMs) in which heterogeneity between clusters is modelled by continuously distributed random intercepts and/or slopes. Alternatively, the non-parametric multilevel regression mixture model (NPMM) can accommodate the same nested data structures through discrete latent class variation. The purpose of this article is to delineate analytic relationships between NPMM and MLM parameters that are useful for understanding the indirect interpretation of the NPMM as a non-parametric approximation of the MLM, with relaxed distributional assumptions. We define how seven standard and non-standard MLM specifications can be indirectly approximated by particular NPMM specifications. We provide formulas showing how the NPMM can serve as an approximation of the MLM in terms of intraclass correlation, random coefficient means and (co)variances, heteroscedasticity of residuals at level 1, and heteroscedasticity of residuals at level 2. Further, we discuss how these relationships can be useful in practice. The specific relationships are illustrated with simulated graphical demonstrations, and direct and indirect interpretations of NPMM classes are contrasted. We provide an R function to aid in implementing and visualizing an indirect interpretation of NPMM classes. An empirical example is presented and future directions are discussed. © 2016 The British Psychological Society.

Multilevel modeling and panel data analysis in educational research (Case study: National examination data senior high school in West Java)

NASA Astrophysics Data System (ADS)

Zulvia, Pepi; Kurnia, Anang; Soleh, Agus M.

2017-03-01

Individual and environment are a hierarchical structure consist of units grouped at different levels. Hierarchical data structures are analyzed based on several levels, with the lowest level nested in the highest level. This modeling is commonly call multilevel modeling. Multilevel modeling is widely used in education research, for example, the average score of National Examination (UN). While in Indonesia UN for high school student is divided into natural science and social science. The purpose of this research is to develop multilevel and panel data modeling using linear mixed model on educational data. The first step is data exploration and identification relationships between independent and dependent variable by checking correlation coefficient and variance inflation factor (VIF). Furthermore, we use a simple model approach with highest level of the hierarchy (level-2) is regency/city while school is the lowest of hierarchy (level-1). The best model was determined by comparing goodness-of-fit and checking assumption from residual plots and predictions for each model. Our finding that for natural science and social science, the regression with random effects of regency/city and fixed effects of the time i.e multilevel model has better performance than the linear mixed model in explaining the variability of the dependent variable, which is the average scores of UN.

The social determinants of oral health: new approaches to conceptualizing and researching complex causal networks.

PubMed

Newton, J Timothy; Bower, Elizabeth J

2005-02-01

Oral epidemiological research into the social determinants of oral health has been limited by the absence of a theoretical framework which reflects the complexity of real life social processes and the network of causal pathways between social structure and oral health and disease. In the absence of such a framework, social determinants are treated as isolated risk factors, attributable to the individual, having a direct impact on oral health. There is little sense of how such factors interrelate over time and place and the pathways between the factors and oral health. Features of social life which impact on individuals' oral health but are not reducible to the individual remain under-researched. A conceptual framework informing mainstream epidemiological research into the social determinants of health is applied to oral epidemiology. The framework suggests complex causal pathways between social structure and health via interlinking material, psychosocial and behavioural pathways. Methodological implications for oral epidemiological research informed by the framework, such as the use of multilevel modelling, path analysis and structural equation modelling, combining qualitative and quantitative research methods, and collaborative research, are discussed. Copyright Blackwell Munksgaard, 2005.

Effects of unit empowerment and perceived support for professional nursing practice on unit effectiveness and individual nurse well-being: a time-lagged study.

PubMed

Spence Laschinger, Heather K; Nosko, Amanda; Wilk, Piotr; Finegan, Joan

2014-12-01

Recruitment and retention strategies have emphasized the importance of positive work environments that support professional nursing practice for sustaining the nursing workforce. Unit leadership that creates empowering workplace conditions plays a key role in establishing supportive practice environments that increase work effectiveness, and, ultimately, improves job satisfaction. To test a multi-level model examining the effect of both contextual and individual factors on individual nurse job satisfaction. At the unit level, structural empowerment and support for professional nursing practice (organizational resources) were hypothesized to be predictors of unit level effectiveness. At the individual level, core self-evaluation, and psychological empowerment (intrapersonal resources) were modeled as predictors of nurse job satisfaction one year later. Cross-level unit effects on individual nurses' job satisfaction were also examined. This study employed a longitudinal survey design with 545 staff nurses from 49 hospital units in Ontario, Canada. Participants completed a survey at two points in time (response rate of 40%) with standardized measures of the major study variables in the hypothesized model. Multilevel structural equation modeling was used to test the model. Nurses shared perceptions of structural empowerment on their units indirectly influenced their shared perceptions of unit effectiveness (Level 2) through perceived unit support for professional nursing practice, which in turn, had a significant positive direct effect on unit effectiveness (Level 2). Unit effectiveness was also strongly related to individual nurse job satisfaction one year later. At Level 1, higher core self-evaluation had a direct and indirect effect on job satisfaction through increased psychological empowerment. The results suggest that nurses' job satisfaction is influenced by a combination of individual and contextual factors demonstrating utility in considering both sources of nurses' satisfaction with their work in creating effective nursing work environments. Copyright © 2014 Elsevier Ltd. All rights reserved.

Multilevel Latent Class Analysis: An Application of Adolescent Smoking Typologies with Individual and Contextual Predictors

ERIC Educational Resources Information Center

Henry, Kimberly L.; Muthen, Bengt

2010-01-01

Latent class analysis (LCA) is a statistical method used to identify subtypes of related cases using a set of categorical or continuous observed variables. Traditional LCA assumes that observations are independent. However, multilevel data structures are common in social and behavioral research and alternative strategies are needed. In this…

Multilevel Confirmatory Factor Analysis of a Scale Measuring Interagency Collaboration of Children's Mental Health Agencies

ERIC Educational Resources Information Center

Dedrick, Robert F.; Greenbaum, Paul E.

2011-01-01

Multilevel confirmatory factor analysis was used to evaluate the factor structure underlying the 12-item, three-factor "Interagency Collaboration Activities Scale" (ICAS) at the informant level and at the agency level. Results from 378 professionals (104 administrators, 201 service providers, and 73 case managers) from 32 children's mental health…

Multilevel decomposition of complete vehicle configuration in a parallel computing environment

NASA Technical Reports Server (NTRS)

Bhatt, Vinay; Ragsdell, K. M.

1989-01-01

This research summarizes various approaches to multilevel decomposition to solve large structural problems. A linear decomposition scheme based on the Sobieski algorithm is selected as a vehicle for automated synthesis of a complete vehicle configuration in a parallel processing environment. The research is in a developmental state. Preliminary numerical results are presented for several example problems.

DIF Analysis with Multilevel Data: A Simulation Study Using the Latent Variable Approach

ERIC Educational Resources Information Center

Jin, Ying; Eason, Hershel

2016-01-01

The effects of mean ability difference (MAD) and short tests on the performance of various DIF methods have been studied extensively in previous simulation studies. Their effects, however, have not been studied under multilevel data structure. MAD was frequently observed in large-scale cross-country comparison studies where the primary sampling…

Examining the Influence of Campus Climate on Students' Time to Degree: A Multilevel Discrete-Time Survival Analysis

ERIC Educational Resources Information Center

Zhou, Ji; Castellanos, Michelle

2013-01-01

Utilizing longitudinal data of 3477 students from 28 institutions, we examine the effects of structural diversity and quality of interracial relation on students' persistence towards graduation within six years. We utilize multilevel discrete-time survival analysis to account for the longitudinal persistence patterns as well as the nested…

Macroeconomic Knowledge of Higher Education Students in Germany and Japan--A Multilevel Analysis of Contextual and Personal Effects

ERIC Educational Resources Information Center

Zlatkin-Troitschanskaia, Olga; Schmidt, Susanne; Brückner, Sebastian; Förster, Manuel; Yamaoka, Michio; Asano, Tadayoshi

2016-01-01

Recent trends towards harmonising and internationalising business and economics studies in higher education are affecting the structure and content of programmes and courses, and necessitate more transparent and comparable information on students' economic knowledge and skills. In this study, we examine by linear multilevel regression modelling…

Multilevel regression analyses to investigate the relationship between two variables over time: examining the longitudinal association between intrusion and avoidance.

PubMed

Suvak, Michael K; Walling, Sherry M; Iverson, Katherine M; Taft, Casey T; Resick, Patricia A

2009-12-01

Multilevel modeling is a powerful and flexible framework for analyzing nested data structures (e.g., repeated measures or longitudinal designs). The authors illustrate a series of multilevel regression procedures that can be used to elucidate the nature of the relationship between two variables across time. The goal is to help trauma researchers become more aware of the utility of multilevel modeling as a tool for increasing the field's understanding of posttraumatic adaptation. These procedures are demonstrated by examining the relationship between two posttraumatic symptoms, intrusion and avoidance, across five assessment points in a sample of rape and robbery survivors (n = 286). Results revealed that changes in intrusion were highly correlated with changes in avoidance over the 18-month posttrauma period.

Multilevel Factor Structure and Concurrent Validity of the Teacher Version of the Authoritative School Climate Survey.

PubMed

Huang, Francis L; Cornell, Dewey G; Konold, Timothy; Meyer, Joseph P; Lacey, Anna; Nekvasil, Erin K; Heilbrun, Anna; Shukla, Kathan D

2015-12-01

School climate is well recognized as an important influence on student behavior and adjustment to school, but there is a need for theory-guided measures that make use of teacher perspectives. Authoritative school climate theory hypothesizes that a positive school climate is characterized by high levels of disciplinary structure and student support. A teacher version of the Authoritative School Climate Survey (ASCS) was administered to a statewide sample of 9099 7th- and 8th-grade teachers from 366 schools. The study used exploratory and multilevel confirmatory factor analyses (MCFA) that accounted for the nested data structure and allowed for the modeling of the factor structures at 2 levels. Multilevel confirmatory factor analyses conducted on both an exploratory (N = 4422) and a confirmatory sample (N = 4677) showed good support for the factor structures investigated. Factor correlations at 2 levels indicated that schools with greater levels of disciplinary structure and student support had higher student engagement, less teasing and bullying, and lower student aggression toward teachers. The teacher version of the ASCS can be used to assess 2 key domains of school climate and associated measures of student engagement and aggression toward peers and teachers. © 2015, American School Health Association.

Quasi-periodic dynamics in system with multilevel pulse modulated control

NASA Astrophysics Data System (ADS)

Gol'tsov, Yu A.; Kizhuk, A. S.; Rubanov, V. G.

2018-03-01

In this paper, the authors describe the transitions from the regular periodic mode to quasiperiodicity that can be observed in a multilevel pulse-width modulated control system for a high-power heating unit. The behavior of such system can be described by a set of two coupled non-autonomous differential equations with discontinuous right-hand sides. The authors reduce the investigation of this system to the studying of a two-dimensional piecewise-smooth map. The authors demonstrate how a closed invariant curve associated with quasiperiodic dynamics can arise from a stable periodic motion through a border-collision bifurcation. The paper also considers a variety of interesting nonlinear phenomena, including phase-locking modes, the coexistence of several stable closed invariant curves, embedded one into the other and with their basins of attraction separated by intervening repelling closed curves.

Multilevel sequential Monte Carlo: Mean square error bounds under verifiable conditions

DOE PAGES

Del Moral, Pierre; Jasra, Ajay; Law, Kody J. H.

2017-01-09

We consider the multilevel sequential Monte Carlo (MLSMC) method of Beskos et al. (Stoch. Proc. Appl. [to appear]). This technique is designed to approximate expectations w.r.t. probability laws associated to a discretization. For instance, in the context of inverse problems, where one discretizes the solution of a partial differential equation. The MLSMC approach is especially useful when independent, coupled sampling is not possible. Beskos et al. show that for MLSMC the computational effort to achieve a given error, can be less than independent sampling. In this article we significantly weaken the assumptions of Beskos et al., extending the proofs tomore » non-compact state-spaces. The assumptions are based upon multiplicative drift conditions as in Kontoyiannis and Meyn (Electron. J. Probab. 10 [2005]: 61–123). The assumptions are verified for an example.« less

Multilevel sequential Monte Carlo: Mean square error bounds under verifiable conditions

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

Del Moral, Pierre; Jasra, Ajay; Law, Kody J. H.

We consider the multilevel sequential Monte Carlo (MLSMC) method of Beskos et al. (Stoch. Proc. Appl. [to appear]). This technique is designed to approximate expectations w.r.t. probability laws associated to a discretization. For instance, in the context of inverse problems, where one discretizes the solution of a partial differential equation. The MLSMC approach is especially useful when independent, coupled sampling is not possible. Beskos et al. show that for MLSMC the computational effort to achieve a given error, can be less than independent sampling. In this article we significantly weaken the assumptions of Beskos et al., extending the proofs tomore » non-compact state-spaces. The assumptions are based upon multiplicative drift conditions as in Kontoyiannis and Meyn (Electron. J. Probab. 10 [2005]: 61–123). The assumptions are verified for an example.« less

Editorial: Introduction to the Special Section on Causal Inference in Cross Sectional and Longitudinal Mediational Models

PubMed Central

West, Stephen G.

2016-01-01

Psychologists have long had interest in the processes through which antecedent variables produce their effects on the outcomes of ultimate interest (e.g., Wood-worth's Stimulus-Organism-Response model). Models involving such meditational processes have characterized many of the important psychological theories of the 20th century and continue to the present day. However, it was not until Judd and Kenny (1981) and Baron and Kenny (1986) combined ideas from experimental design and structural equation modeling that statistical methods for directly testing such models, now known as mediation analysis, began to be developed. Methodologists have improved these statistical methods, developing new, more efficient estimators for mediated effects. They have also extended mediation analysis to multilevel data structures, models involving multiple mediators, models in which interactions occur, and an array of noncontinuous outcome measures (see MacKinnon, 2008). This work nicely maps on to key questions of applied researchers and has led to an outpouring of research testing meditational models (As of August, 2011, Baron and Kenny's article has had over 24,000 citations according to Google Scholar). PMID:26736046

Design of convolutional tornado code

NASA Astrophysics Data System (ADS)

Zhou, Hui; Yang, Yao; Gao, Hongmin; Tan, Lu

2017-09-01

As a linear block code, the traditional tornado (tTN) code is inefficient in burst-erasure environment and its multi-level structure may lead to high encoding/decoding complexity. This paper presents a convolutional tornado (cTN) code which is able to improve the burst-erasure protection capability by applying the convolution property to the tTN code, and reduce computational complexity by abrogating the multi-level structure. The simulation results show that cTN code can provide a better packet loss protection performance with lower computation complexity than tTN code.

A multilevel layout algorithm for visualizing physical and genetic interaction networks, with emphasis on their modular organization

PubMed Central

2012-01-01

Background Graph drawing is an integral part of many systems biology studies, enabling visual exploration and mining of large-scale biological networks. While a number of layout algorithms are available in popular network analysis platforms, such as Cytoscape, it remains poorly understood how well their solutions reflect the underlying biological processes that give rise to the network connectivity structure. Moreover, visualizations obtained using conventional layout algorithms, such as those based on the force-directed drawing approach, may become uninformative when applied to larger networks with dense or clustered connectivity structure. Methods We implemented a modified layout plug-in, named Multilevel Layout, which applies the conventional layout algorithms within a multilevel optimization framework to better capture the hierarchical modularity of many biological networks. Using a wide variety of real life biological networks, we carried out a systematic evaluation of the method in comparison with other layout algorithms in Cytoscape. Results The multilevel approach provided both biologically relevant and visually pleasant layout solutions in most network types, hence complementing the layout options available in Cytoscape. In particular, it could improve drawing of large-scale networks of yeast genetic interactions and human physical interactions. In more general terms, the biological evaluation framework developed here enables one to assess the layout solutions from any existing or future graph drawing algorithm as well as to optimize their performance for a given network type or structure. Conclusions By making use of the multilevel modular organization when visualizing biological networks, together with the biological evaluation of the layout solutions, one can generate convenient visualizations for many network biology applications. PMID:22448851

A low-rank control variate for multilevel Monte Carlo simulation of high-dimensional uncertain systems

NASA Astrophysics Data System (ADS)

Fairbanks, Hillary R.; Doostan, Alireza; Ketelsen, Christian; Iaccarino, Gianluca

2017-07-01

Multilevel Monte Carlo (MLMC) is a recently proposed variation of Monte Carlo (MC) simulation that achieves variance reduction by simulating the governing equations on a series of spatial (or temporal) grids with increasing resolution. Instead of directly employing the fine grid solutions, MLMC estimates the expectation of the quantity of interest from the coarsest grid solutions as well as differences between each two consecutive grid solutions. When the differences corresponding to finer grids become smaller, hence less variable, fewer MC realizations of finer grid solutions are needed to compute the difference expectations, thus leading to a reduction in the overall work. This paper presents an extension of MLMC, referred to as multilevel control variates (MLCV), where a low-rank approximation to the solution on each grid, obtained primarily based on coarser grid solutions, is used as a control variate for estimating the expectations involved in MLMC. Cost estimates as well as numerical examples are presented to demonstrate the advantage of this new MLCV approach over the standard MLMC when the solution of interest admits a low-rank approximation and the cost of simulating finer grids grows fast.

Health behavior change models for HIV prevention and AIDS care: practical recommendations for a multi-level approach.

PubMed

Kaufman, Michelle R; Cornish, Flora; Zimmerman, Rick S; Johnson, Blair T

2014-08-15

Despite increasing recent emphasis on the social and structural determinants of HIV-related behavior, empirical research and interventions lag behind, partly because of the complexity of social-structural approaches. This article provides a comprehensive and practical review of the diverse literature on multi-level approaches to HIV-related behavior change in the interest of contributing to the ongoing shift to more holistic theory, research, and practice. It has the following specific aims: (1) to provide a comprehensive list of relevant variables/factors related to behavior change at all points on the individual-structural spectrum, (2) to map out and compare the characteristics of important recent multi-level models, (3) to reflect on the challenges of operating with such complex theoretical tools, and (4) to identify next steps and make actionable recommendations. Using a multi-level approach implies incorporating increasing numbers of variables and increasingly context-specific mechanisms, overall producing greater intricacies. We conclude with recommendations on how best to respond to this complexity, which include: using formative research and interdisciplinary collaboration to select the most appropriate levels and variables in a given context; measuring social and institutional variables at the appropriate level to ensure meaningful assessments of multiple levels are made; and conceptualizing intervention and research with reference to theoretical models and mechanisms to facilitate transferability, sustainability, and scalability.

Mathematical learning instruction and teacher motivation factors affecting science technology engineering and math (STEM) major choices in 4-year colleges and universities: Multilevel structural equation modeling

NASA Astrophysics Data System (ADS)

Lee, Ahlam

2011-12-01

Using the Educational Longitudinal Study of 2002/06, this study examined the effects of the selected mathematical learning and teacher motivation factors on graduates' science, technology, engineering, and math (STEM) related major choices in 4-year colleges and universities, as mediated by math performance and math self-efficacy. Using multilevel structural equation modeling, I analyzed: (1) the association between mathematical learning instruction factors (i.e., computer, individual, and lecture-based learning activities in mathematics) and students' STEM major choices in 4-year colleges and universities as mediated by math performance and math self-efficacy and (2) the association between school factor, teacher motivation and students' STEM major choices in 4-year colleges and universities via mediators of math performance and math self-efficacy. The results revealed that among the selected learning experience factors, computer-based learning activities in math classrooms yielded the most positive effects on math self-efficacy, which significantly predicted the increase in the proportion of students' STEM major choice as mediated by math self-efficacy. Further, when controlling for base-year math Item Response Theory (IRT) scores, a positive relationship between individual-based learning activities in math classrooms and the first follow-up math IRT scores emerged, which related to the high proportion of students' STEM major choices. The results also indicated that individual and lecture-based learning activities in math yielded positive effects on math self-efficacy, which related to STEM major choice. Concerning between-school levels, teacher motivation yielded positive effects on the first follow up math IRT score, when controlling for base year IRT score. The results from this study inform educators, parents, and policy makers on how mathematics instruction can improve student math performance and encourage more students to prepare for STEM careers. Students should receive all possible opportunities to use computers to enhance their math self-efficacy, be encouraged to review math materials, and concentrate on listening to math teachers' lectures. While all selected math-learning activities should be embraced in math instruction, computer and individual-based learning activities, which reflect student-driven learning, should be emphasized in the high school instruction. Likewise, students should be encouraged to frequently engage in individual-based learning activities to improve their math performance.

Fitting aerodynamic forces in the Laplace domain: An application of a nonlinear nongradient technique to multilevel constrained optimization

NASA Technical Reports Server (NTRS)

Tiffany, S. H.; Adams, W. M., Jr.

1984-01-01

A technique which employs both linear and nonlinear methods in a multilevel optimization structure to best approximate generalized unsteady aerodynamic forces for arbitrary motion is described. Optimum selection of free parameters is made in a rational function approximation of the aerodynamic forces in the Laplace domain such that a best fit is obtained, in a least squares sense, to tabular data for purely oscillatory motion. The multilevel structure and the corresponding formulation of the objective models are presented which separate the reduction of the fit error into linear and nonlinear problems, thus enabling the use of linear methods where practical. Certain equality and inequality constraints that may be imposed are identified; a brief description of the nongradient, nonlinear optimizer which is used is given; and results which illustrate application of the method are presented.

Multi-level structure in the large scale distribution of optically luminous galaxies

NASA Astrophysics Data System (ADS)

Deng, Xin-fa; Deng, Zu-gan; Liu, Yong-zhen

1992-04-01

Fractal dimensions in the large scale distribution of galaxies have been calculated with the method given by Wen et al. [1] Samples are taken from CfA redshift survey in northern and southern galactic [2] hemisphere in our analysis respectively. Results from these two regions are compared with each other. There are significant differences between the distributions in these two regions. However, our analyses do show some common features of the distributions in these two regions. All subsamples show multi-level fractal character distinctly. Combining it with the results from analyses of samples given by IRAS galaxies and results from samples given by redshift survey in pencil-beam fields, [3,4] we suggest that multi-level fractal structure is most likely to be a general and important character in the large scale distribution of galaxies. The possible implications of this character are discussed.

Examining the Rule of Thumb of Not Using Multilevel Modeling: The "Design Effect Smaller than Two" Rule

ERIC Educational Resources Information Center

Lai, Mark H. C.; Kwok, Oi-man

2015-01-01

Educational researchers commonly use the rule of thumb of "design effect smaller than 2" as the justification of not accounting for the multilevel or clustered structure in their data. The rule, however, has not yet been systematically studied in previous research. In the present study, we generated data from three different models…

The Effect of Small Sample Size on Two-Level Model Estimates: A Review and Illustration

ERIC Educational Resources Information Center

McNeish, Daniel M.; Stapleton, Laura M.

2016-01-01

Multilevel models are an increasingly popular method to analyze data that originate from a clustered or hierarchical structure. To effectively utilize multilevel models, one must have an adequately large number of clusters; otherwise, some model parameters will be estimated with bias. The goals for this paper are to (1) raise awareness of the…

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…

Multilevel multi-informant structure of the authoritative school climate survey.

PubMed

Konold, Timothy; Cornell, Dewey; Huang, Francis; Meyer, Patrick; Lacey, Anna; Nekvasil, Erin; Heilbrun, Anna; Shukla, Kathan

2014-09-01

The Authoritative School Climate Survey was designed to provide schools with a brief assessment of 2 key characteristics of school climate--disciplinary structure and student support--that are hypothesized to influence 2 important school climate outcomes--student engagement and prevalence of teasing and bullying in school. The factor structure of these 4 constructs was examined with exploratory and confirmatory factor analyses in a statewide sample of 39,364 students (Grades 7 and 8) attending 423 schools. Notably, the analyses used a multilevel structural approach to model the nesting of students in schools for purposes of evaluating factor structure, demonstrating convergent and concurrent validity and gauging the structural invariance of concurrent validity coefficients across gender. These findings provide schools with a core group of school climate measures guided by authoritative discipline theory. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Stress-Preventive Management Competencies, Psychosocial Work Environments, and Affective Well-Being: A Multilevel, Multisource Investigation.

PubMed

Toderi, Stefano; Balducci, Cristian

2018-02-26

The Management Competencies for Preventing and Reducing Stress at Work framework represents one of the few tailored models of leadership for work stress prevention purposes, but it has never been empirically evaluated. The aim of this study was to investigate whether supervisors' stress-preventive management competencies, as measured by the Stress Management Competencies Indicator Tool (SMCIT), are related to employees' affective well-being through psychosocial work environmental factors. To this end, multilevel structural equation modelling (MSEM) was developed and tested, including data provided by both supervisors and employees. Supervisors ( n = 84) self-assessed their stress-preventive management competencies (i.e., being respectful and responsible, managing and communicating existing and future work, reasoning and managing difficult situations, and managing the individual within the team) with a previously validated reduced version of the SMCIT. The supervised employees ( n = 584) rated job content (e.g., job demands) and work context (e.g., role clarity) psychosocial factors and their job-related affective well-being. Supervisors' job-related affective well-being was also included in the tested model. The results revealed that the stress-preventive competencies factor was related to employees' affective well-being through the psychosocial work environment only when the latter was operationalized by means of contextual work factors. Supervisors' affective well-being was related to their stress-preventive competencies, but it was not related to employees' affective well-being. We discuss the implications of the results obtained.

Relating Measurement Invariance, Cross-Level Invariance, and Multilevel Reliability.

PubMed

Jak, Suzanne; Jorgensen, Terrence D

2017-01-01

Data often have a nested, multilevel structure, for example when data are collected from children in classrooms. This kind of data complicate the evaluation of reliability and measurement invariance, because several properties can be evaluated at both the individual level and the cluster level, as well as across levels. For example, cross-level invariance implies equal factor loadings across levels, which is needed to give latent variables at the two levels a similar interpretation. Reliability at a specific level refers to the ratio of true score variance over total variance at that level. This paper aims to shine light on the relation between reliability, cross-level invariance, and strong factorial invariance across clusters in multilevel data. Specifically, we will illustrate how strong factorial invariance across clusters implies cross-level invariance and perfect reliability at the between level in multilevel factor models.

Hybrid massively parallel fast sweeping method for static Hamilton-Jacobi equations

NASA Astrophysics Data System (ADS)

Detrixhe, Miles; Gibou, Frédéric

2016-10-01

The fast sweeping method is a popular algorithm for solving a variety of static Hamilton-Jacobi equations. Fast sweeping algorithms for parallel computing have been developed, but are severely limited. In this work, we present a multilevel, hybrid parallel algorithm that combines the desirable traits of two distinct parallel methods. The fine and coarse grained components of the algorithm take advantage of heterogeneous computer architecture common in high performance computing facilities. We present the algorithm and demonstrate its effectiveness on a set of example problems including optimal control, dynamic games, and seismic wave propagation. We give results for convergence, parallel scaling, and show state-of-the-art speedup values for the fast sweeping method.

Convolutionless Nakajima-Zwanzig equations for stochastic analysis in nonlinear dynamical systems.

PubMed

Venturi, D; Karniadakis, G E

2014-06-08

Determining the statistical properties of stochastic nonlinear systems is of major interest across many disciplines. Currently, there are no general efficient methods to deal with this challenging problem that involves high dimensionality, low regularity and random frequencies. We propose a framework for stochastic analysis in nonlinear dynamical systems based on goal-oriented probability density function (PDF) methods. The key idea stems from techniques of irreversible statistical mechanics, and it relies on deriving evolution equations for the PDF of quantities of interest, e.g. functionals of the solution to systems of stochastic ordinary and partial differential equations. Such quantities could be low-dimensional objects in infinite dimensional phase spaces. We develop the goal-oriented PDF method in the context of the time-convolutionless Nakajima-Zwanzig-Mori formalism. We address the question of approximation of reduced-order density equations by multi-level coarse graining, perturbation series and operator cumulant resummation. Numerical examples are presented for stochastic resonance and stochastic advection-reaction problems.

Convolutionless Nakajima–Zwanzig equations for stochastic analysis in nonlinear dynamical systems

PubMed Central

Venturi, D.; Karniadakis, G. E.

2014-01-01

Determining the statistical properties of stochastic nonlinear systems is of major interest across many disciplines. Currently, there are no general efficient methods to deal with this challenging problem that involves high dimensionality, low regularity and random frequencies. We propose a framework for stochastic analysis in nonlinear dynamical systems based on goal-oriented probability density function (PDF) methods. The key idea stems from techniques of irreversible statistical mechanics, and it relies on deriving evolution equations for the PDF of quantities of interest, e.g. functionals of the solution to systems of stochastic ordinary and partial differential equations. Such quantities could be low-dimensional objects in infinite dimensional phase spaces. We develop the goal-oriented PDF method in the context of the time-convolutionless Nakajima–Zwanzig–Mori formalism. We address the question of approximation of reduced-order density equations by multi-level coarse graining, perturbation series and operator cumulant resummation. Numerical examples are presented for stochastic resonance and stochastic advection–reaction problems. PMID:24910519

A Social-Ecological Framework of Theory, Assessment, and Prevention of Suicide

PubMed Central

Cramer, Robert J.; Kapusta, Nestor D.

2017-01-01

The juxtaposition of increasing suicide rates with continued calls for suicide prevention efforts begs for new approaches. Grounded in the Centers for Disease Control and Prevention (CDC) framework for tackling health issues, this personal views work integrates relevant suicide risk/protective factor, assessment, and intervention/prevention literatures. Based on these components of suicide risk, we articulate a Social-Ecological Suicide Prevention Model (SESPM) which provides an integration of general and population-specific risk and protective factors. We also use this multi-level perspective to provide a structured approach to understanding current theories and intervention/prevention efforts concerning suicide. Following similar multi-level prevention efforts in interpersonal violence and Human Immunodeficiency Virus (HIV) domains, we offer recommendations for social-ecologically informed suicide prevention theory, training, research, assessment, and intervention programming. Although the SESPM calls for further empirical testing, it provides a suitable backdrop for tailoring of current prevention and intervention programs to population-specific needs. Moreover, the multi-level model shows promise to move suicide risk assessment forward (e.g., development of multi-level suicide risk algorithms or structured professional judgments instruments) to overcome current limitations in the field. Finally, we articulate a set of characteristics of social-ecologically based suicide prevention programs. These include the need to address risk and protective factors with the strongest degree of empirical support at each multi-level layer, incorporate a comprehensive program evaluation strategy, and use a variety of prevention techniques across levels of prevention. PMID:29062296

Modeling Learning in Doubly Multilevel Binary Longitudinal Data Using Generalized Linear Mixed Models: An Application to Measuring and Explaining Word Learning.

PubMed

Cho, Sun-Joo; Goodwin, Amanda P

2016-04-01

When word learning is supported by instruction in experimental studies for adolescents, word knowledge outcomes tend to be collected from complex data structure, such as multiple aspects of word knowledge, multilevel reader data, multilevel item data, longitudinal design, and multiple groups. This study illustrates how generalized linear mixed models can be used to measure and explain word learning for data having such complexity. Results from this application provide deeper understanding of word knowledge than could be attained from simpler models and show that word knowledge is multidimensional and depends on word characteristics and instructional contexts.

Real time selective harmonic minimization for multilevel inverters using genetic algorithm and artifical neural network angle generation

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

Filho, Faete J; Tolbert, Leon M; Ozpineci, Burak

2012-01-01

The work developed here proposes a methodology for calculating switching angles for varying DC sources in a multilevel cascaded H-bridges converter. In this approach the required fundamental is achieved, the lower harmonics are minimized, and the system can be implemented in real time with low memory requirements. Genetic algorithm (GA) is the stochastic search method to find the solution for the set of equations where the input voltages are the known variables and the switching angles are the unknown variables. With the dataset generated by GA, an artificial neural network (ANN) is trained to store the solutions without excessive memorymore » storage requirements. This trained ANN then senses the voltage of each cell and produces the switching angles in order to regulate the fundamental at 120 V and eliminate or minimize the low order harmonics while operating in real time.« less

Modeling and analysis of the space shuttle nose-gear tire with semianalytic finite elements

NASA Technical Reports Server (NTRS)

Kim, Kyun O.; Noor, Ahmed K.; Tanner, John A.

1990-01-01

A computational procedure is presented for the geometrically nonlinear analysis of aircraft tires. The Space Shuttle Orbiter nose gear tire was modeled by using a two-dimensional laminated anisotropic shell theory with the effects of variation in material and geometric parameters included. The four key elements of the procedure are: (1) semianalytic finite elements in which the shell variables are represented by Fourier series in the circumferential direction and piecewise polynominals in the meridional direction; (2) a mixed formulation with the fundamental unknowns consisting of strain parameters, stress-resultant parameters, and generalized displacements; (3) multilevel operator splitting to effect successive simplifications, and to uncouple the equations associated with different Fourier harmonics; and (4) multilevel iterative procedures and reduction techniques to generate the response of the shell. Numerical results of the Space Shuttle Orbiter nose gear tire model are compared with experimental measurements of the tire subjected to inflation loading.

Multilevel Iterative Methods in Nonlinear Computational Plasma Physics

NASA Astrophysics Data System (ADS)

Knoll, D. A.; Finn, J. M.

1997-11-01

Many applications in computational plasma physics involve the implicit numerical solution of coupled systems of nonlinear partial differential equations or integro-differential equations. Such problems arise in MHD, systems of Vlasov-Fokker-Planck equations, edge plasma fluid equations. We have been developing matrix-free Newton-Krylov algorithms for such problems and have applied these algorithms to the edge plasma fluid equations [1,2] and to the Vlasov-Fokker-Planck equation [3]. Recently we have found that with increasing grid refinement, the number of Krylov iterations required per Newton iteration has grown unmanageable [4]. This has led us to the study of multigrid methods as a means of preconditioning matrix-free Newton-Krylov methods. In this poster we will give details of the general multigrid preconditioned Newton-Krylov algorithm, as well as algorithm performance details on problems of interest in the areas of magnetohydrodynamics and edge plasma physics. Work supported by US DoE 1. Knoll and McHugh, J. Comput. Phys., 116, pg. 281 (1995) 2. Knoll and McHugh, Comput. Phys. Comm., 88, pg. 141 (1995) 3. Mousseau and Knoll, J. Comput. Phys. (1997) (to appear) 4. Knoll and McHugh, SIAM J. Sci. Comput. 19, (1998) (to appear)

Multi-Level Discourse Analysis in a Physics Teaching Methods Course from the Psychological Perspective of Activity Theory

ERIC Educational Resources Information Center

Vieira, Rodrigo Drumond; Kelly, Gregory J.

2014-01-01

In this paper, we present and apply a multi-level method for discourse analysis in science classrooms. This method is based on the structure of human activity (activity, actions, and operations) and it was applied to study a pre-service physics teacher methods course. We argue that such an approach, based on a cultural psychological perspective,…

Contextual effects and cancer outcomes in the United States: a systematic review of characteristics in multilevel analyses.

PubMed

Zahnd, Whitney E; McLafferty, Sara L

2017-11-01

There is increasing call for the utilization of multilevel modeling to explore the relationship between place-based contextual effects and cancer outcomes in the United States. To gain a better understanding of how contextual factors are being considered, we performed a systematic review. We reviewed studies published between January 1, 2002 and December 31, 2016 and assessed the following attributes: (1) contextual considerations such as geographic scale and contextual factors used; (2) methods used to quantify contextual factors; and (3) cancer type and outcomes. We searched PubMed, Scopus, and Web of Science and initially identified 1060 studies. One hundred twenty-two studies remained after exclusions. Most studies utilized a two-level structure; census tracts were the most commonly used geographic scale. Socioeconomic factors, health care access, racial/ethnic factors, and rural-urban status were the most common contextual factors addressed in multilevel models. Breast and colorectal cancers were the most common cancer types, and screening and staging were the most common outcomes assessed in these studies. Opportunities for future research include deriving contextual factors using more rigorous approaches, considering cross-classified structures and cross-level interactions, and using multilevel modeling to explore understudied cancers and outcomes. Copyright © 2017 Elsevier Inc. All rights reserved.

Displacement based multilevel structural optimization

NASA Technical Reports Server (NTRS)

Striz, Alfred G.

1995-01-01

Multidisciplinary design optimization (MDO) is expected to play a major role in the competitive transportation industries of tomorrow, i.e., in the design of aircraft and spacecraft, of high speed trains, boats, and automobiles. All of these vehicles require maximum performance at minimum weight to keep fuel consumption low and conserve resources. Here, MDO can deliver mathematically based design tools to create systems with optimum performance subject to the constraints of disciplines such as structures, aerodynamics, controls, etc. Although some applications of MDO are beginning to surface, the key to a widespread use of this technology lies in the improvement of its efficiency. This aspect is investigated here for the MDO subset of structural optimization, i.e., for the weight minimization of a given structure under size, strength, and displacement constraints. Specifically, finite element based multilevel optimization of structures (here, statically indeterminate trusses and beams for proof of concept) is performed. In the system level optimization, the design variables are the coefficients of assumed displacement functions, and the load unbalance resulting from the solution of the stiffness equations is minimized. Constraints are placed on the deflection amplitudes and the weight of the structure. In the subsystems level optimizations, the weight of each element is minimized under the action of stress constraints, with the cross sectional dimensions as design variables. This approach is expected to prove very efficient, especially for complex structures, since the design task is broken down into a large number of small and efficiently handled subtasks, each with only a small number of variables. This partitioning will also allow for the use of parallel computing, first, by sending the system and subsystems level computations to two different processors, ultimately, by performing all subsystems level optimizations in a massively parallel manner on separate processors. It is expected that the subsystems level optimizations can be further improved through the use of controlled growth, a method which reduces an optimization to a more efficient analysis with only a slight degradation in accuracy. The efficiency of all proposed techniques is being evaluated relative to the performance of the standard single level optimization approach where the complete structure is weight minimized under the action of all given constraints by one processor and to the performance of simultaneous analysis and design which combines analysis and optimization into a single step. It is expected that the present approach can be expanded to include additional structural constraints (buckling, free and forced vibration, etc.) or other disciplines (passive and active controls, aerodynamics, etc.) for true MDO.

A novel method for a multi-level hierarchical composite with brick-and-mortar structure

PubMed Central

Brandt, Kristina; Wolff, Michael F. H.; Salikov, Vitalij; Heinrich, Stefan; Schneider, Gerold A.

2013-01-01

The fascination for hierarchically structured hard tissues such as enamel or nacre arises from their unique structure-properties-relationship. During the last decades this numerously motivated the synthesis of composites, mimicking the brick-and-mortar structure of nacre. However, there is still a lack in synthetic engineering materials displaying a true hierarchical structure. Here, we present a novel multi-step processing route for anisotropic 2-level hierarchical composites by combining different coating techniques on different length scales. It comprises polymer-encapsulated ceramic particles as building blocks for the first level, followed by spouted bed spray granulation for a second level, and finally directional hot pressing to anisotropically consolidate the composite. The microstructure achieved reveals a brick-and-mortar hierarchical structure with distinct, however not yet optimized mechanical properties on each level. It opens up a completely new processing route for the synthesis of multi-level hierarchically structured composites, giving prospects to multi-functional structure-properties relationships. PMID:23900554

A novel method for a multi-level hierarchical composite with brick-and-mortar structure.

PubMed

Brandt, Kristina; Wolff, Michael F H; Salikov, Vitalij; Heinrich, Stefan; Schneider, Gerold A

2013-01-01

The fascination for hierarchically structured hard tissues such as enamel or nacre arises from their unique structure-properties-relationship. During the last decades this numerously motivated the synthesis of composites, mimicking the brick-and-mortar structure of nacre. However, there is still a lack in synthetic engineering materials displaying a true hierarchical structure. Here, we present a novel multi-step processing route for anisotropic 2-level hierarchical composites by combining different coating techniques on different length scales. It comprises polymer-encapsulated ceramic particles as building blocks for the first level, followed by spouted bed spray granulation for a second level, and finally directional hot pressing to anisotropically consolidate the composite. The microstructure achieved reveals a brick-and-mortar hierarchical structure with distinct, however not yet optimized mechanical properties on each level. It opens up a completely new processing route for the synthesis of multi-level hierarchically structured composites, giving prospects to multi-functional structure-properties relationships.

A novel method for a multi-level hierarchical composite with brick-and-mortar structure

NASA Astrophysics Data System (ADS)

Brandt, Kristina; Wolff, Michael F. H.; Salikov, Vitalij; Heinrich, Stefan; Schneider, Gerold A.

2013-07-01

The fascination for hierarchically structured hard tissues such as enamel or nacre arises from their unique structure-properties-relationship. During the last decades this numerously motivated the synthesis of composites, mimicking the brick-and-mortar structure of nacre. However, there is still a lack in synthetic engineering materials displaying a true hierarchical structure. Here, we present a novel multi-step processing route for anisotropic 2-level hierarchical composites by combining different coating techniques on different length scales. It comprises polymer-encapsulated ceramic particles as building blocks for the first level, followed by spouted bed spray granulation for a second level, and finally directional hot pressing to anisotropically consolidate the composite. The microstructure achieved reveals a brick-and-mortar hierarchical structure with distinct, however not yet optimized mechanical properties on each level. It opens up a completely new processing route for the synthesis of multi-level hierarchically structured composites, giving prospects to multi-functional structure-properties relationships.

On the non-linear spectroscopy including saturated absorption and four-wave mixing in two and multi-level atoms: a computational study

NASA Astrophysics Data System (ADS)

Patel, M.; De Jager, G.; Nkosi, Z.; Wyngaard, A.; Govender, K.

2017-10-01

In this paper we report on the study of two and multi-level atoms interacting with multiple laser beams. The semi-classical approach is used to describe the system in which the atoms are treated quantum mechanically via the density matrix operator, while the laser beams are treated classically using Maxwells equations. We present results of a two level atom interacting with single and multiple laser beams and demonstrate Rabi oscillations between the levels. The effects of laser modulation on the dynamics of the atom (atomic populations and coherences) are examined by solving the optical Bloch equations. Plots of the density matrix elements as a function of time are presented for various parameters such as laser intensity, detuning, modulation etc. In addition, phase-space plots and Fourier analysis of the density matrix elements are provided. The atomic polarization, estimated from the coherence terms of the density matrix elements, is used in the numerical solution of Maxwells equations to determine the behaviour of the laser beams as they propagate through the atomic ensemble. The effects of saturation and hole-burning are demonstrated in the case of two counter propagating beams with one being a strong beam and the other being very weak. The above work is extended to include four-wave mixing in four level atoms in a diamond configuration. Two co-propagating beams of different wavelengths drive the atoms from a ground state |1〉 to an excited state |3〉 via an intermediate state |2〉. The atoms then move back to the ground state via another intermediate state |4〉, resulting in the generation of two additional correlated photon beams. The characteristics of these additional photons are studied.

Networks of Food Sharing Reveal the Functional Significance of Multilevel Sociality in Two Hunter-Gatherer Groups.

PubMed

Dyble, Mark; Thompson, James; Smith, Daniel; Salali, Gul Deniz; Chaudhary, Nikhil; Page, Abigail E; Vinicuis, Lucio; Mace, Ruth; Migliano, Andrea Bamberg

2016-08-08

Like many other mammalian and primate societies [1-4], humans are said to live in multilevel social groups, with individuals situated in a series of hierarchically structured sub-groups [5, 6]. Although this multilevel social organization has been described among contemporary hunter-gatherers [5], questions remain as to the benefits that individuals derive from living in such groups. Here, we show that food sharing among two populations of contemporary hunter-gatherers-the Palanan Agta (Philippines) and Mbendjele BaYaka (Republic of Congo)-reveals similar multilevel social structures, with individuals situated in households, within sharing clusters of 3-4 households, within the wider residential camps, which vary in size. We suggest that these groupings serve to facilitate inter-sexual provisioning, kin provisioning, and risk reduction reciprocity, three levels of cooperation argued to be fundamental in human societies [7, 8]. Humans have a suite of derived life history characteristics including a long childhood and short inter-birth intervals that make offspring energetically demanding [9] and have moved to a dietary niche that often involves the exploitation of difficult to acquire foods with highly variable return rates [10-12]. This means that human foragers face both day-to-day and more long-term energetic deficits that conspire to make humans energetically interdependent. We suggest that a multilevel social organization allows individuals access to both the food sharing partners required to buffer themselves against energetic shortfalls and the cooperative partners required for skill-based tasks such as cooperative foraging. Copyright © 2016 Elsevier Ltd. All rights reserved.

Hybrid massively parallel fast sweeping method for static Hamilton–Jacobi equations

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

Detrixhe, Miles, E-mail: mdetrixhe@engineering.ucsb.edu; University of California Santa Barbara, Santa Barbara, CA, 93106; Gibou, Frédéric, E-mail: fgibou@engineering.ucsb.edu

The fast sweeping method is a popular algorithm for solving a variety of static Hamilton–Jacobi equations. Fast sweeping algorithms for parallel computing have been developed, but are severely limited. In this work, we present a multilevel, hybrid parallel algorithm that combines the desirable traits of two distinct parallel methods. The fine and coarse grained components of the algorithm take advantage of heterogeneous computer architecture common in high performance computing facilities. We present the algorithm and demonstrate its effectiveness on a set of example problems including optimal control, dynamic games, and seismic wave propagation. We give results for convergence, parallel scaling,more » and show state-of-the-art speedup values for the fast sweeping method.« less

Modeling Intraindividual Dynamics Using Stochastic Differential Equations: Age Differences in Affect Regulation.

PubMed

Wood, Julie; Oravecz, Zita; Vogel, Nina; Benson, Lizbeth; Chow, Sy-Miin; Cole, Pamela; Conroy, David E; Pincus, Aaron L; Ram, Nilam

2017-12-15

Life-span theories of aging suggest improvements and decrements in individuals' ability to regulate affect. Dynamic process models, with intensive longitudinal data, provide new opportunities to articulate specific theories about individual differences in intraindividual dynamics. This paper illustrates a method for operationalizing affect dynamics using a multilevel stochastic differential equation (SDE) model, and examines how those dynamics differ with age and trait-level tendencies to deploy emotion regulation strategies (reappraisal and suppression). Univariate multilevel SDE models, estimated in a Bayesian framework, were fit to 21 days of ecological momentary assessments of affect valence and arousal (average 6.93/day, SD = 1.89) obtained from 150 adults (age 18-89 years)-specifically capturing temporal dynamics of individuals' core affect in terms of attractor point, reactivity to biopsychosocial (BPS) inputs, and attractor strength. Older age was associated with higher arousal attractor point and less BPS-related reactivity. Greater use of reappraisal was associated with lower valence attractor point. Intraindividual variability in regulation strategy use was associated with greater BPS-related reactivity and attractor strength, but in different ways for valence and arousal. The results highlight the utility of SDE models for studying affect dynamics and informing theoretical predictions about how intraindividual dynamics change over the life course. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Assessment of Material Solutions of Multi-level Garage Structure Within Integrated Life Cycle Design Process

NASA Astrophysics Data System (ADS)

Wałach, Daniel; Sagan, Joanna; Gicala, Magdalena

2017-10-01

The paper presents an environmental and economic analysis of the material solutions of multi-level garage. The construction project approach considered reinforced concrete structure under conditions of use of ordinary concrete and high-performance concrete (HPC). Using of HPC allowed to significant reduction of reinforcement steel, mainly in compression elements (columns) in the construction of the object. The analysis includes elements of the methodology of integrated lice cycle design (ILCD). By making multi-criteria analysis based on established weight of the economic and environmental parameters, three solutions have been evaluated and compared within phase of material production (information modules A1-A3).

Two alternative ways for solving the coordination problem in multilevel optimization

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, Jaroslaw

1991-01-01

Two techniques for formulating the coupling between levels in multilevel optimization by linear decomposition, proposed as improvements over the original formulation, now several years old, that relied on explicit equality constraints which were shown by application experience as occasionally causing numerical difficulties. The two new techniques represent the coupling without using explicit equality constraints, thus avoiding the above diffuculties and also reducing computational cost of the procedure. The old and new formulations are presented in detail and illustrated by an example of a structural optimization. A generic version of the improved algorithm is also developed for applications to multidisciplinary systems not limited to structures.

Structural optimization by multilevel decomposition

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, J.; James, B.; Dovi, A.

1983-01-01

A method is described for decomposing an optimization problem into a set of subproblems and a coordination problem which preserves coupling between the subproblems. The method is introduced as a special case of multilevel, multidisciplinary system optimization and its algorithm is fully described for two level optimization for structures assembled of finite elements of arbitrary type. Numerical results are given for an example of a framework to show that the decomposition method converges and yields results comparable to those obtained without decomposition. It is pointed out that optimization by decomposition should reduce the design time by allowing groups of engineers, using different computers to work concurrently on the same large problem.

Structural synthesis: Precursor and catalyst

NASA Technical Reports Server (NTRS)

Schmit, L. A.

1984-01-01

More than twenty five years have elapsed since it was recognized that a rather general class of structural design optimization tasks could be properly posed as an inequality constrained minimization problem. It is suggested that, independent of primary discipline area, it will be useful to think about: (1) posing design problems in terms of an objective function and inequality constraints; (2) generating design oriented approximate analysis methods (giving special attention to behavior sensitivity analysis); (3) distinguishing between decisions that lead to an analysis model and those that lead to a design model; (4) finding ways to generate a sequence of approximate design optimization problems that capture the essential characteristics of the primary problem, while still having an explicit algebraic form that is matched to one or more of the established optimization algorithms; (5) examining the potential of optimum design sensitivity analysis to facilitate quantitative trade-off studies as well as participation in multilevel design activities. It should be kept in mind that multilevel methods are inherently well suited to a parallel mode of operation in computer terms or to a division of labor between task groups in organizational terms. Based on structural experience with multilevel methods general guidelines are suggested.

A longitudinal multilevel CFA-MTMM model for interchangeable and structurally different methods

PubMed Central

Koch, Tobias; Schultze, Martin; Eid, Michael; Geiser, Christian

2014-01-01

One of the key interests in the social sciences is the investigation of change and stability of a given attribute. Although numerous models have been proposed in the past for analyzing longitudinal data including multilevel and/or latent variable modeling approaches, only few modeling approaches have been developed for studying the construct validity in longitudinal multitrait-multimethod (MTMM) measurement designs. The aim of the present study was to extend the spectrum of current longitudinal modeling approaches for MTMM analysis. Specifically, a new longitudinal multilevel CFA-MTMM model for measurement designs with structurally different and interchangeable methods (called Latent-State-Combination-Of-Methods model, LS-COM) is presented. Interchangeable methods are methods that are randomly sampled from a set of equivalent methods (e.g., multiple student ratings for teaching quality), whereas structurally different methods are methods that cannot be easily replaced by one another (e.g., teacher, self-ratings, principle ratings). Results of a simulation study indicate that the parameters and standard errors in the LS-COM model are well recovered even in conditions with only five observations per estimated model parameter. The advantages and limitations of the LS-COM model relative to other longitudinal MTMM modeling approaches are discussed. PMID:24860515

A Multilevel Gamma-Clustering Layout Algorithm for Visualization of Biological Networks

PubMed Central

Hruz, Tomas; Lucas, Christoph; Laule, Oliver; Zimmermann, Philip

2013-01-01

Visualization of large complex networks has become an indispensable part of systems biology, where organisms need to be considered as one complex system. The visualization of the corresponding network is challenging due to the size and density of edges. In many cases, the use of standard visualization algorithms can lead to high running times and poorly readable visualizations due to many edge crossings. We suggest an approach that analyzes the structure of the graph first and then generates a new graph which contains specific semantic symbols for regular substructures like dense clusters. We propose a multilevel gamma-clustering layout visualization algorithm (MLGA) which proceeds in three subsequent steps: (i) a multilevel γ-clustering is used to identify the structure of the underlying network, (ii) the network is transformed to a tree, and (iii) finally, the resulting tree which shows the network structure is drawn using a variation of a force-directed algorithm. The algorithm has a potential to visualize very large networks because it uses modern clustering heuristics which are optimized for large graphs. Moreover, most of the edges are removed from the visual representation which allows keeping the overview over complex graphs with dense subgraphs. PMID:23864855

Volatility, house edge and prize structure of gambling games.

PubMed

Turner, Nigel E

2011-12-01

This study used simulations to examine the effect of prize structure on the outcome volatility and the number of winners of various game configurations. The two most common prize structures found in gambling games are even money payoff games (bet $1; win $2) found on most table games and multilevel prizes structures found in gambling machine games. Simulations were set up to examine the effect of prize structure on the long-term outcomes of these games. Eight different prize structures were compared in terms of the number of winners and volatility. It was found that the standard table game and commercial gambling machines produced fairly high numbers of short term winners (1 h), but few long term winners (50 h). It was found that the typical even money game set up produced the lowest level of volatility. Of the multilevel prize structures examined, the three simulations based on commercial gambling machines were the least volatile. The results are examined in terms of the pragmatics of game design.

The art of spacecraft design: A multidisciplinary challenge

NASA Technical Reports Server (NTRS)

Abdi, F.; Ide, H.; Levine, M.; Austel, L.

1989-01-01

Actual design turn-around time has become shorter due to the use of optimization techniques which have been introduced into the design process. It seems that what, how and when to use these optimization techniques may be the key factor for future aircraft engineering operations. Another important aspect of this technique is that complex physical phenomena can be modeled by a simple mathematical equation. The new powerful multilevel methodology reduces time-consuming analysis significantly while maintaining the coupling effects. This simultaneous analysis method stems from the implicit function theorem and system sensitivity derivatives of input variables. Use of the Taylor's series expansion and finite differencing technique for sensitivity derivatives in each discipline makes this approach unique for screening dominant variables from nondominant variables. In this study, the current Computational Fluid Dynamics (CFD) aerodynamic and sensitivity derivative/optimization techniques are applied for a simple cone-type forebody of a high-speed vehicle configuration to understand basic aerodynamic/structure interaction in a hypersonic flight condition.

Investing in communities: evaluating the added value of community mobilization on HIV prevention outcomes among FSWs in India.

PubMed

Kuhlmann, Anne Sebert; Galavotti, Christine; Hastings, Philip; Narayanan, Pradeep; Saggurti, Niranjan

2014-04-01

Community mobilization often requires greater time and resource investments than typical interventions, yet few evaluations exist to justify these investments. We evaluated the added benefit of community mobilization on HIV prevention outcomes among female sex workers (FSWs) using a composite measure of volunteer participation in program committees by FSWs. After adjusting for treatment propensity, we used multilevel structural equation modeling (MSEM) to test our program theory. We hypothesized that stronger community mobilization would be associated with increased levels of consistent condom use and with increased levels of perceived fairness, mediated by psychosocial processes. Community mobilization had an indirect effect on consistent condom use mediated through social cohesion and an indirect effect on perceived fairness mediated by collective efficacy. Our results suggest higher levels of community mobilization help improve condom use and reduce perceived discrimination beyond the effects of the core HIV intervention program. We recommend further testing of this model.

Computational Study of Near-limit Propagation of Detonation in Hydrogen-air Mixtures

NASA Technical Reports Server (NTRS)

Yungster, S.; Radhakrishnan, K.

2002-01-01

A computational investigation of the near-limit propagation of detonation in lean and rich hydrogen-air mixtures is presented. The calculations were carried out over an equivalence ratio range of 0.4 to 5.0, pressures ranging from 0.2 bar to 1.0 bar and ambient initial temperature. The computations involved solution of the one-dimensional Euler equations with detailed finite-rate chemistry. The numerical method is based on a second-order spatially accurate total-variation-diminishing (TVD) scheme, and a point implicit, first-order-accurate, time marching algorithm. The hydrogen-air combustion was modeled with a 9-species, 19-step reaction mechanism. A multi-level, dynamically adaptive grid was utilized in order to resolve the structure of the detonation. The results of the computations indicate that when hydrogen concentrations are reduced below certain levels, the detonation wave switches from a high-frequency, low amplitude oscillation mode to a low frequency mode exhibiting large fluctuations in the detonation wave speed; that is, a 'galloping' propagation mode is established.

Differential investments and opportunities: How do neighborhood conditions moderate the relationship between perceived housing discrimination and social capital?

PubMed

Yang, Tse-Chuan; Chen, I-Chien; Kim, Seulki; Choi, Seung-Won

2018-05-01

Though the adverse consequences of perceived housing discrimination have been documented, little is known about whether such experience undermines one's social capital in a neighborhood and even less is about whether and how this relationship is altered by neighborhood features. We proposed a framework that simultaneously considers within-individual and between-neighborhood processes. We applied multilevel structural equation models to data from Philadelphia (n = 9987) and found that (a) perceived housing discrimination was negatively associated with one's social capital even after other confounders were considered, (b) this negative association could be partly explained by the proliferated daily stress and anxiety mechanisms, (c) differential exposures to neighborhood social disadvantage accounted for the variation in social capital across neighborhoods, and (d) the adverse association between perceived housing discrimination and social capital could be attenuated by neighborhood stability. The findings suggested that appropriate interventions should buffer the negative association of perceived housing discrimination with social capital. Copyright © 2018 Elsevier Inc. All rights reserved.

ANCOVA Versus CHANGE From Baseline in Nonrandomized Studies: The Difference.

PubMed

van Breukelen, Gerard J P

2013-11-01

The pretest-posttest control group design can be analyzed with the posttest as dependent variable and the pretest as covariate (ANCOVA) or with the difference between posttest and pretest as dependent variable (CHANGE). These 2 methods can give contradictory results if groups differ at pretest, a phenomenon that is known as Lord's paradox. Literature claims that ANCOVA is preferable if treatment assignment is based on randomization or on the pretest and questionable for preexisting groups. Some literature suggests that Lord's paradox has to do with measurement error in the pretest. This article shows two new things: First, the claims are confirmed by proving the mathematical equivalence of ANCOVA to a repeated measures model without group effect at pretest. Second, correction for measurement error in the pretest is shown to lead back to ANCOVA or to CHANGE, depending on the assumed absence or presence of a true group difference at pretest. These two new theoretical results are illustrated with multilevel (mixed) regression and structural equation modeling of data from two studies.

Relationships between drinking onset, alcohol use intensity, and nighttime risk behaviors in a college bar district.

PubMed

Thombs, Dennis L; O'Mara, Ryan; Tobler, Amy L; Wagenaar, Alexander C; Clapp, John D

2009-01-01

To identify antecedents of risk behavior events in college bar patrons. In this nighttime field study, self-report data and alcohol intoxication readings were collected from patrons immediately upon exiting bars (n = 618). Multilevel structural equation modeling revealed positive associations between age of drinking onset and both alcohol use intensity in the past year and recent bar-going frequency. In turn, alcohol use intensity in the past year was positively associated with bar-going frequency and intoxication at bar exit. An association between drinking onset and bar-going frequency was mediated by alcohol use intensity in the past year. Discernable paths from age of drinking onset to monthly bar-going frequency and intoxication level after leaving a bar can be identified. The results highlight the critical role of drinking onset in development of college student alcohol abuse. Research is needed to determine whether college bars are environmental pathogens mediating between genetic risk factors and patron risk behavior.

Organizational Climate Partially Mediates the Effect of Culture on Work Attitudes and Staff Turnover in Mental Health Services

PubMed Central

Aarons, Gregory A.; Sawitzky, Angelina C.

2006-01-01

Staff turnover in mental health service organizations is an ongoing problem with implications for staff morale, productivity, organizational effectiveness, and implementation of innovation. Recent studies in public sector services have examined the impact of organizational culture and climate on work attitudes (i.e., job satisfaction and organizational commitment) and, ultimately, staff turnover. However, mediational models of the impact of culture and climate on work attitudes have not been examined. The present study examined full and partial mediation models of the effects of culture and climate on work attitudes and the subsequent impact of work attitudes on staff turnover. Multilevel structural equation models supported a partial mediation model in which organizational culture had both direct influence on work attitudes and indirect influence through organizational climate. Work attitudes significantly predicted one-year staff turnover rates. These findings support the contention that both culture and climate impact work attitudes and subsequent staff turnover. PMID:16544205

Gender inequality and the use of maternal healthcare services in rural sub-Saharan Africa.

PubMed

Adjiwanou, Vissého; LeGrand, Thomas

2014-09-01

In this study, we measure gender inequality both at individual level by women׳s household decision-making and at contextual level by permissive gender norms associated with tolerance of violence against women and assess their impact on maternal healthcare services utilisation in rural Africa. We apply multilevel structural equation modelling to Demographic and Health Survey (DHS) data from Ghana, Kenya, Tanzania and Uganda to gain better measure and effect of the gender norms construct. The results show that women in Ghana and Uganda, who live in areas where gender norms are relatively tolerant of violence against women, are less likely to use skilled birth attendants and timely antenatal care. In Tanzania, women who live in this type of environment are less likely to attend four or more antenatal visits. In contrast, the effects of a woman׳s decision-making authority on maternal health service use are less pronounced in the same countries. Copyright © 2014 Elsevier Ltd. All rights reserved.

Reciprocal Relations between Work-Related Authenticity and Intrinsic Motivation, Work Ability and Depressivity: A Two-Wave Study.

PubMed

Emmerich, Astrid I; Rigotti, Thomas

2017-01-01

This study investigates the role of context-specific authenticity at work for work-related outcomes (intrinsic motivation, work ability) and depressivity. Furthermore reciprocal relations between work-related authenticity and healthy psychological functioning are investigated. Longitudinal data from 1,243 employees from 63 subsidiaries of a non-profit organization in the social sector were analyzed using multilevel structural equation modeling. Work-related authenticity at T1 predicted work ability and depressivity, but not intrinsic motivation at T2, about 6 months later. Work-related authenticity at T2 was predicted by intrinsic motivation and depressivity, but not by work ability at T1. We conclude that work-related authenticity and healthy psychological functioning are positively reinforcing each other. Thus, enabling employees to be authentic supposedly increases their well-being and is a pivotal opportunity for organizations to foster health and performance-related indicators like work ability and prevent negative health indicators like depressivity. At the same time, authenticity of employees can be fostered through workplace health promotion.

Organizational climate partially mediates the effect of culture on work attitudes and staff turnover in mental health services.

PubMed

Aarons, Gregory A; Sawitzky, Angelina C

2006-05-01

Staff turnover in mental health service organizations is an ongoing problem with implications for staff morale, productivity, organizational effectiveness, and implementation of innovation. Recent studies in public sector services have examined the impact of organizational culture and climate on work attitudes (i.e., job satisfaction and organizational commitment) and, ultimately, staff turnover. However, mediational models of the impact of culture and climate on work attitudes have not been examined. The present study examined full and partial mediation models of the effects of culture and climate on work attitudes and the subsequent impact of work attitudes on staff turnover. Multilevel structural equation models supported a partial mediation model in which organizational culture had both direct influence on work attitudes and indirect influence through organizational climate. Work attitudes significantly predicted one-year staff turnover rates. These findings support the contention that both culture and climate impact work attitudes and subsequent staff turnover.

Rapid earthquake hazard and loss assessment for Euro-Mediterranean region

NASA Astrophysics Data System (ADS)

Erdik, Mustafa; Sesetyan, Karin; Demircioglu, Mine; Hancilar, Ufuk; Zulfikar, Can; Cakti, Eser; Kamer, Yaver; Yenidogan, Cem; Tuzun, Cuneyt; Cagnan, Zehra; Harmandar, Ebru

2010-10-01

The almost-real time estimation of ground shaking and losses after a major earthquake in the Euro-Mediterranean region was performed in the framework of the Joint Research Activity 3 (JRA-3) component of the EU FP6 Project entitled "Network of Research Infra-structures for European Seismology, NERIES". This project consists of finding the most likely location of the earthquake source by estimating the fault rupture parameters on the basis of rapid inversion of data from on-line regional broadband stations. It also includes an estimation of the spatial distribution of selected site-specific ground motion parameters at engineering bedrock through region-specific ground motion prediction equations (GMPEs) or physical simulation of ground motion. By using the Earthquake Loss Estimation Routine (ELER) software, the multi-level methodology developed for real time estimation of losses is capable of incorporating regional variability and sources of uncertainty stemming from GMPEs, fault finiteness, site modifications, inventory of physical and social elements subjected to earthquake hazard and the associated vulnerability relationships.

A scalable nonlinear fluid-structure interaction solver based on a Schwarz preconditioner with isogeometric unstructured coarse spaces in 3D

NASA Astrophysics Data System (ADS)

Kong, Fande; Cai, Xiao-Chuan

2017-07-01

Nonlinear fluid-structure interaction (FSI) problems on unstructured meshes in 3D appear in many applications in science and engineering, such as vibration analysis of aircrafts and patient-specific diagnosis of cardiovascular diseases. In this work, we develop a highly scalable, parallel algorithmic and software framework for FSI problems consisting of a nonlinear fluid system and a nonlinear solid system, that are coupled monolithically. The FSI system is discretized by a stabilized finite element method in space and a fully implicit backward difference scheme in time. To solve the large, sparse system of nonlinear algebraic equations at each time step, we propose an inexact Newton-Krylov method together with a multilevel, smoothed Schwarz preconditioner with isogeometric coarse meshes generated by a geometry preserving coarsening algorithm. Here "geometry" includes the boundary of the computational domain and the wet interface between the fluid and the solid. We show numerically that the proposed algorithm and implementation are highly scalable in terms of the number of linear and nonlinear iterations and the total compute time on a supercomputer with more than 10,000 processor cores for several problems with hundreds of millions of unknowns.

A scalable nonlinear fluid–structure interaction solver based on a Schwarz preconditioner with isogeometric unstructured coarse spaces in 3D

DOE PAGES

Kong, Fande; Cai, Xiao-Chuan

2017-03-24

Nonlinear fluid-structure interaction (FSI) problems on unstructured meshes in 3D appear many applications in science and engineering, such as vibration analysis of aircrafts and patient-specific diagnosis of cardiovascular diseases. In this work, we develop a highly scalable, parallel algorithmic and software framework for FSI problems consisting of a nonlinear fluid system and a nonlinear solid system, that are coupled monolithically. The FSI system is discretized by a stabilized finite element method in space and a fully implicit backward difference scheme in time. To solve the large, sparse system of nonlinear algebraic equations at each time step, we propose an inexactmore » Newton-Krylov method together with a multilevel, smoothed Schwarz preconditioner with isogeometric coarse meshes generated by a geometry preserving coarsening algorithm. Here ''geometry'' includes the boundary of the computational domain and the wet interface between the fluid and the solid. We show numerically that the proposed algorithm and implementation are highly scalable in terms of the number of linear and nonlinear iterations and the total compute time on a supercomputer with more than 10,000 processor cores for several problems with hundreds of millions of unknowns.« less

Robotic intelligence kernel

DOEpatents

Bruemmer, David J [Idaho Falls, ID

2009-11-17

A robot platform includes perceptors, locomotors, and a system controller. The system controller executes a robot intelligence kernel (RIK) that includes a multi-level architecture and a dynamic autonomy structure. The multi-level architecture includes a robot behavior level for defining robot behaviors, that incorporate robot attributes and a cognitive level for defining conduct modules that blend an adaptive interaction between predefined decision functions and the robot behaviors. The dynamic autonomy structure is configured for modifying a transaction capacity between an operator intervention and a robot initiative and may include multiple levels with at least a teleoperation mode configured to maximize the operator intervention and minimize the robot initiative and an autonomous mode configured to minimize the operator intervention and maximize the robot initiative. Within the RIK at least the cognitive level includes the dynamic autonomy structure.

Habit, custom, and power: a multi-level theory of population health.

PubMed

Zimmerman, Frederick J

2013-03-01

In multi-level theory, individual behavior flows from cognitive habits, either directly through social referencing, rules of thumb, or automatic behaviors; or indirectly through the shaping of rationality itself by framing or heuristics. Although behavior does not arise from individually rational optimization, it generally appears to be rational, because the cognitive habits that guide behavior evolve toward optimality. However, power imbalances shaped by particular social, political, and economic structures can distort this evolution, leading to individual behavior that fails to maximize individual or social well-being. Replacing the dominant rational-choice paradigm with a multi-level theoretical paradigm involving habit, custom, and power will enable public health to engage in rigorous new areas of research. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multilevel sparse functional principal component analysis.

PubMed

Di, Chongzhi; Crainiceanu, Ciprian M; Jank, Wolfgang S

2014-01-29

We consider analysis of sparsely sampled multilevel functional data, where the basic observational unit is a function and data have a natural hierarchy of basic units. An example is when functions are recorded at multiple visits for each subject. Multilevel functional principal component analysis (MFPCA; Di et al. 2009) was proposed for such data when functions are densely recorded. Here we consider the case when functions are sparsely sampled and may contain only a few observations per function. We exploit the multilevel structure of covariance operators and achieve data reduction by principal component decompositions at both between and within subject levels. We address inherent methodological differences in the sparse sampling context to: 1) estimate the covariance operators; 2) estimate the functional principal component scores; 3) predict the underlying curves. Through simulations the proposed method is able to discover dominating modes of variations and reconstruct underlying curves well even in sparse settings. Our approach is illustrated by two applications, the Sleep Heart Health Study and eBay auctions.

Residual Structures in Latent Growth Curve Modeling

ERIC Educational Resources Information Center

Grimm, Kevin J.; Widaman, Keith F.

2010-01-01

Several alternatives are available for specifying the residual structure in latent growth curve modeling. Two specifications involve uncorrelated residuals and represent the most commonly used residual structures. The first, building on repeated measures analysis of variance and common specifications in multilevel models, forces residual variances…

Probabilistic Multi-Scale, Multi-Level, Multi-Disciplinary Analysis and Optimization of Engine Structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Abumeri, Galib H.

2000-01-01

Aircraft engines are assemblies of dynamically interacting components. Engine updates to keep present aircraft flying safely and engines for new aircraft are progressively required to operate in more demanding technological and environmental requirements. Designs to effectively meet those requirements are necessarily collections of multi-scale, multi-level, multi-disciplinary analysis and optimization methods and probabilistic methods are necessary to quantify respective uncertainties. These types of methods are the only ones that can formally evaluate advanced composite designs which satisfy those progressively demanding requirements while assuring minimum cost, maximum reliability and maximum durability. Recent research activities at NASA Glenn Research Center have focused on developing multi-scale, multi-level, multidisciplinary analysis and optimization methods. Multi-scale refers to formal methods which describe complex material behavior metal or composite; multi-level refers to integration of participating disciplines to describe a structural response at the scale of interest; multidisciplinary refers to open-ended for various existing and yet to be developed discipline constructs required to formally predict/describe a structural response in engine operating environments. For example, these include but are not limited to: multi-factor models for material behavior, multi-scale composite mechanics, general purpose structural analysis, progressive structural fracture for evaluating durability and integrity, noise and acoustic fatigue, emission requirements, hot fluid mechanics, heat-transfer and probabilistic simulations. Many of these, as well as others, are encompassed in an integrated computer code identified as Engine Structures Technology Benefits Estimator (EST/BEST) or Multi-faceted/Engine Structures Optimization (MP/ESTOP). The discipline modules integrated in MP/ESTOP include: engine cycle (thermodynamics), engine weights, internal fluid mechanics, cost, mission and coupled structural/thermal, various composite property simulators and probabilistic methods to evaluate uncertainty effects (scatter ranges) in all the design parameters. The objective of the proposed paper is to briefly describe a multi-faceted design analysis and optimization capability for coupled multi-discipline engine structures optimization. Results are presented for engine and aircraft type metrics to illustrate the versatility of that capability. Results are also presented for reliability, noise and fatigue to illustrate its inclusiveness. For example, replacing metal rotors with composites reduces the engine weight by 20 percent, 15 percent noise reduction, and an order of magnitude improvement in reliability. Composite designs exist to increase fatigue life by at least two orders of magnitude compared to state-of-the-art metals.

Hierarchically Parallelized Constrained Nonlinear Solvers with Automated Substructuring

NASA Technical Reports Server (NTRS)

Padovan, Joe; Kwang, Abel

1994-01-01

This paper develops a parallelizable multilevel multiple constrained nonlinear equation solver. The substructuring process is automated to yield appropriately balanced partitioning of each succeeding level. Due to the generality of the procedure,_sequential, as well as partially and fully parallel environments can be handled. This includes both single and multiprocessor assignment per individual partition. Several benchmark examples are presented. These illustrate the robustness of the procedure as well as its capability to yield significant reductions in memory utilization and calculational effort due both to updating and inversion.

Relations of alpine plant communities across environmental gradients: Multilevel versus multiscale analyses

USGS Publications Warehouse

Malanson, George P.; Zimmerman, Dale L.; Kinney, Mitch; Fagre, Daniel B.

2017-01-01

Alpine plant communities vary, and their environmental covariates could influence their response to climate change. A single multilevel model of how alpine plant community composition is determined by hierarchical relations is compared to a separate examination of those relations at different scales. Nonmetric multidimensional scaling of species cover for plots in four regions across the Rocky Mountains created dependent variables. Climate variables are derived for the four regions from interpolated data. Plot environmental variables are measured directly and the presence of thirty-seven site characteristics is recorded and used to create additional independent variables. Multilevel and best subsets regressions are used to determine the strength of the hypothesized relations. The ordinations indicate structure in the assembly of plant communities. The multilevel analyses, although revealing significant relations, provide little explanation; of the site variables, those related to site microclimate are most important. In multiscale analyses (whole and separate regions), different variables are better explanations within the different regions. This result indicates weak environmental niche control of community composition. The weak relations of the structure in the patterns of species association to the environment indicates that either alpine vegetation represents a case of the neutral theory of biogeography being a valid explanation or that it represents disequilibrium conditions. The implications of neutral theory and disequilibrium explanations are similar: Response to climate change will be difficult to quantify above equilibrium background turnover.

Significance tests for functional data with complex dependence structure.

PubMed

Staicu, Ana-Maria; Lahiri, Soumen N; Carroll, Raymond J

2015-01-01

We propose an L 2 -norm based global testing procedure for the null hypothesis that multiple group mean functions are equal, for functional data with complex dependence structure. Specifically, we consider the setting of functional data with a multilevel structure of the form groups-clusters or subjects-units, where the unit-level profiles are spatially correlated within the cluster, and the cluster-level data are independent. Orthogonal series expansions are used to approximate the group mean functions and the test statistic is estimated using the basis coefficients. The asymptotic null distribution of the test statistic is developed, under mild regularity conditions. To our knowledge this is the first work that studies hypothesis testing, when data have such complex multilevel functional and spatial structure. Two small-sample alternatives, including a novel block bootstrap for functional data, are proposed, and their performance is examined in simulation studies. The paper concludes with an illustration of a motivating experiment.

Fundamental physics issues of multilevel logic in developing a parallel processor.

NASA Astrophysics Data System (ADS)

Bandyopadhyay, Anirban; Miki, Kazushi

2007-06-01

In the last century, On and Off physical switches, were equated with two decisions 0 and 1 to express every information in terms of binary digits and physically realize it in terms of switches connected in a circuit. Apart from memory-density increase significantly, more possible choices in particular space enables pattern-logic a reality, and manipulation of pattern would allow controlling logic, generating a new kind of processor. Neumann's computer is based on sequential logic, processing bits one by one. But as pattern-logic is generated on a surface, viewing whole pattern at a time is a truly parallel processing. Following Neumann's and Shannons fundamental thermodynamical approaches we have built compatible model based on series of single molecule based multibit logic systems of 4-12 bits in an UHV-STM. On their monolayer multilevel communication and pattern formation is experimentally verified. Furthermore, the developed intelligent monolayer is trained by Artificial Neural Network. Therefore fundamental weak interactions for the building of truly parallel processor are explored here physically and theoretically.

Cascaded Quadruple Active Bridge Structures for Multilevel DC to Three-Phase AC Conversion

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

Johnson, Brian B; Achanta, Prasanta K; Maksimovic, Dragan

This paper introduces a multilevel architecture comprised of interconnected dc to three-phase ac converter units. To enable series connected operation, each converter unit contains a quadruple active bridge (QAB) converter that provides isolation between the dc side and each of the three ac sides. Since each converter unit transfers dc-side power as constant balanced three-phase power on the ac side, this implies instantaneous input-output power balance and allows elimination of bulk capacitive energy storage. In addition to minimizing required capacitance, the proposed approach simultaneously enables simplified dc-link controllers amenable to decentralized implementation, supports bidirectional power transfer, and exhibits a modularmore » structure to enhance scalability. Isolation provided by the QAB allows a wide range of electrical configurations among multiple units in various dc-ac, ac-dc or ac-ac applications. In this paper, the focus is on series connections on the ac side to emphasize multilevel operation, and the approach is experimentally validated in a dc-ac system containing two cascaded converter units.« less

Multilevel perspective on high-order harmonic generation in solids

NASA Astrophysics Data System (ADS)

Wu, Mengxi; Browne, Dana A.; Schafer, Kenneth J.; Gaarde, Mette B.

2016-12-01

We investigate high-order harmonic generation in a solid, modeled as a multilevel system dressed by a strong infrared laser field. We show that the cutoff energies and the relative strengths of the multiple plateaus that emerge in the harmonic spectrum can be understood both qualitatively and quantitatively by considering a combination of adiabatic and diabatic processes driven by the strong field. Such a model was recently used to interpret the multiple plateaus exhibited in harmonic spectra generated by solid argon and krypton [G. Ndabashimiye et al., Nature 534, 520 (2016), 10.1038/nature17660]. We also show that when the multilevel system originates from the Bloch state at the Γ point of the band structure, the laser-dressed states are equivalent to the Houston states [J. B. Krieger and G. J. Iafrate, Phys. Rev. B 33, 5494 (1986), 10.1103/PhysRevB.33.5494] and will therefore map out the band structure away from the Γ point as the laser field increases. This leads to a semiclassical three-step picture in momentum space that describes the high-order harmonic generation process in a solid.

Context matters: the impact of unit leadership and empowerment on nurses' organizational commitment.

PubMed

Laschinger, Heather K Spence; Finegan, Joan; Wilk, Piotr

2009-05-01

The aim of this study was to test a multilevel model linking unit-level leader-member exchange quality and structural empowerment to nurses' psychological empowerment and organizational commitment at the individual level of analysis. Few studies have examined the contextual effects of unit leadership on individual nurse outcomes. Workplace empowerment has been related to retention outcomes such as organizational commitment in several studies, but few have studied the impact of specific unit characteristics within which nurses work on these outcomes. We surveyed 3,156 nurses in 217 hospital units to test the multilevel model. A multilevel path analysis revealed significant individual and contextual effects on nurses' organizational commitment. Both unit-level leader-member exchange quality and structural empowerment had significant direct effects on individual-level psychological empowerment and organizational commitment. Psychological empowerment mediated the relationship between core self-evaluations and organizational commitment at the individual level of analysis. The contextual effects of positive supervisor relationships and their influence on empowering working conditions at the unit level and, subsequently, nurses' organizational commitment highlight the importance of leadership for creating conditions that result in a committed nursing workforce.

Establishing a Mathematical Equations and Improving the Production of L-tert-Leucine by Uniform Design and Regression Analysis.

PubMed

Jiang, Wei; Xu, Chao-Zhen; Jiang, Si-Zhi; Zhang, Tang-Duo; Wang, Shi-Zhen; Fang, Bai-Shan

2017-04-01

L-tert-Leucine (L-Tle) and its derivatives are extensively used as crucial building blocks for chiral auxiliaries, pharmaceutically active ingredients, and ligands. Combining with formate dehydrogenase (FDH) for regenerating the expensive coenzyme NADH, leucine dehydrogenase (LeuDH) is continually used for synthesizing L-Tle from α-keto acid. A multilevel factorial experimental design was executed for research of this system. In this work, an efficient optimization method for improving the productivity of L-Tle was developed. And the mathematical model between different fermentation conditions and L-Tle yield was also determined in the form of the equation by using uniform design and regression analysis. The multivariate regression equation was conveniently implemented in water, with a space time yield of 505.9 g L -1  day -1 and an enantiomeric excess value of >99 %. These results demonstrated that this method might become an ideal protocol for industrial production of chiral compounds and unnatural amino acids such as chiral drug intermediates.

A new exact method for line radiative transfer

NASA Astrophysics Data System (ADS)

Elitzur, Moshe; Asensio Ramos, Andrés

2006-01-01

We present a new method, the coupled escape probability (CEP), for exact calculation of line emission from multi-level systems, solving only algebraic equations for the level populations. The CEP formulation of the classical two-level problem is a set of linear equations, and we uncover an exact analytic expression for the emission from two-level optically thick sources that holds as long as they are in the `effectively thin' regime. In a comparative study of a number of standard problems, the CEP method outperformed the leading line transfer methods by substantial margins. The algebraic equations employed by our new method are already incorporated in numerous codes based on the escape probability approximation. All that is required for an exact solution with these existing codes is to augment the expression for the escape probability with simple zone-coupling terms. As an application, we find that standard escape probability calculations generally produce the correct cooling emission by the CII 158-μm line but not by the 3P lines of OI.

Care pathways across the primary-hospital care continuum: using the multi-level framework in explaining care coordination

PubMed Central

2013-01-01

Background Care pathways are widely used in hospitals for a structured and detailed planning of the care process. There is a growing interest in extending care pathways into primary care to improve quality of care by increasing care coordination. Evidence is sparse about the relationship between care pathways and care coordination. The multi-level framework explores care coordination across organizations and states that (inter)organizational mechanisms have an effect on the relationships between healthcare professionals, resulting in quality and efficiency of care. The aim of this study was to assess the extent to which care pathways support or create elements of the multi-level framework necessary to improve care coordination across the primary - hospital care continuum. Methods This study is an in-depth analysis of five existing local community projects located in four different regions in Flanders (Belgium) to determine whether the available empirical evidence supported or refuted the theoretical expectations from the multi-level framework. Data were gathered using mixed methods, including structured face-to-face interviews, participant observations, documentation and a focus group. Multiple cases were analyzed performing a cross case synthesis to strengthen the results. Results The development of a care pathway across the primary-hospital care continuum, supported by a step-by-step scenario, led to the use of existing and newly constructed structures, data monitoring and the development of information tools. The construction and use of these inter-organizational mechanisms had a positive effect on exchanging information, formulating and sharing goals, defining and knowing each other’s roles, expectations and competences and building qualitative relationships. Conclusion Care pathways across the primary-hospital care continuum enhance the components of care coordination. PMID:23919518

Care pathways across the primary-hospital care continuum: using the multi-level framework in explaining care coordination.

PubMed

Van Houdt, Sabine; Heyrman, Jan; Vanhaecht, Kris; Sermeus, Walter; De Lepeleire, Jan

2013-08-06

Care pathways are widely used in hospitals for a structured and detailed planning of the care process. There is a growing interest in extending care pathways into primary care to improve quality of care by increasing care coordination. Evidence is sparse about the relationship between care pathways and care coordination.The multi-level framework explores care coordination across organizations and states that (inter)organizational mechanisms have an effect on the relationships between healthcare professionals, resulting in quality and efficiency of care.The aim of this study was to assess the extent to which care pathways support or create elements of the multi-level framework necessary to improve care coordination across the primary-hospital care continuum. This study is an in-depth analysis of five existing local community projects located in four different regions in Flanders (Belgium) to determine whether the available empirical evidence supported or refuted the theoretical expectations from the multi-level framework. Data were gathered using mixed methods, including structured face-to-face interviews, participant observations, documentation and a focus group. Multiple cases were analyzed performing a cross case synthesis to strengthen the results. The development of a care pathway across the primary-hospital care continuum, supported by a step-by-step scenario, led to the use of existing and newly constructed structures, data monitoring and the development of information tools. The construction and use of these inter-organizational mechanisms had a positive effect on exchanging information, formulating and sharing goals, defining and knowing each other's roles, expectations and competences and building qualitative relationships. Care pathways across the primary-hospital care continuum enhance the components of care coordination.

Multi-level tree analysis of pulmonary artery/vein trees in non-contrast CT images

NASA Astrophysics Data System (ADS)

Gao, Zhiyun; Grout, Randall W.; Hoffman, Eric A.; Saha, Punam K.

2012-02-01

Diseases like pulmonary embolism and pulmonary hypertension are associated with vascular dystrophy. Identifying such pulmonary artery/vein (A/V) tree dystrophy in terms of quantitative measures via CT imaging significantly facilitates early detection of disease or a treatment monitoring process. A tree structure, consisting of nodes and connected arcs, linked to the volumetric representation allows multi-level geometric and volumetric analysis of A/V trees. Here, a new theory and method is presented to generate multi-level A/V tree representation of volumetric data and to compute quantitative measures of A/V tree geometry and topology at various tree hierarchies. The new method is primarily designed on arc skeleton computation followed by a tree construction based topologic and geometric analysis of the skeleton. The method starts with a volumetric A/V representation as input and generates its topologic and multi-level volumetric tree representations long with different multi-level morphometric measures. A new recursive merging and pruning algorithms are introduced to detect bad junctions and noisy branches often associated with digital geometric and topologic analysis. Also, a new notion of shortest axial path is introduced to improve the skeletal arc joining two junctions. The accuracy of the multi-level tree analysis algorithm has been evaluated using computer generated phantoms and pulmonary CT images of a pig vessel cast phantom while the reproducibility of method is evaluated using multi-user A/V separation of in vivo contrast-enhanced CT images of a pig lung at different respiratory volumes.

The median hazard ratio: a useful measure of variance and general contextual effects in multilevel survival analysis.

PubMed

Austin, Peter C; Wagner, Philippe; Merlo, Juan

2017-03-15

Multilevel data occurs frequently in many research areas like health services research and epidemiology. A suitable way to analyze such data is through the use of multilevel regression models (MLRM). MLRM incorporate cluster-specific random effects which allow one to partition the total individual variance into between-cluster variation and between-individual variation. Statistically, MLRM account for the dependency of the data within clusters and provide correct estimates of uncertainty around regression coefficients. Substantively, the magnitude of the effect of clustering provides a measure of the General Contextual Effect (GCE). When outcomes are binary, the GCE can also be quantified by measures of heterogeneity like the Median Odds Ratio (MOR) calculated from a multilevel logistic regression model. Time-to-event outcomes within a multilevel structure occur commonly in epidemiological and medical research. However, the Median Hazard Ratio (MHR) that corresponds to the MOR in multilevel (i.e., 'frailty') Cox proportional hazards regression is rarely used. Analogously to the MOR, the MHR is the median relative change in the hazard of the occurrence of the outcome when comparing identical subjects from two randomly selected different clusters that are ordered by risk. We illustrate the application and interpretation of the MHR in a case study analyzing the hazard of mortality in patients hospitalized for acute myocardial infarction at hospitals in Ontario, Canada. We provide R code for computing the MHR. The MHR is a useful and intuitive measure for expressing cluster heterogeneity in the outcome and, thereby, estimating general contextual effects in multilevel survival analysis. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

The median hazard ratio: a useful measure of variance and general contextual effects in multilevel survival analysis

PubMed Central

Wagner, Philippe; Merlo, Juan

2016-01-01

Multilevel data occurs frequently in many research areas like health services research and epidemiology. A suitable way to analyze such data is through the use of multilevel regression models (MLRM). MLRM incorporate cluster‐specific random effects which allow one to partition the total individual variance into between‐cluster variation and between‐individual variation. Statistically, MLRM account for the dependency of the data within clusters and provide correct estimates of uncertainty around regression coefficients. Substantively, the magnitude of the effect of clustering provides a measure of the General Contextual Effect (GCE). When outcomes are binary, the GCE can also be quantified by measures of heterogeneity like the Median Odds Ratio (MOR) calculated from a multilevel logistic regression model. Time‐to‐event outcomes within a multilevel structure occur commonly in epidemiological and medical research. However, the Median Hazard Ratio (MHR) that corresponds to the MOR in multilevel (i.e., ‘frailty’) Cox proportional hazards regression is rarely used. Analogously to the MOR, the MHR is the median relative change in the hazard of the occurrence of the outcome when comparing identical subjects from two randomly selected different clusters that are ordered by risk. We illustrate the application and interpretation of the MHR in a case study analyzing the hazard of mortality in patients hospitalized for acute myocardial infarction at hospitals in Ontario, Canada. We provide R code for computing the MHR. The MHR is a useful and intuitive measure for expressing cluster heterogeneity in the outcome and, thereby, estimating general contextual effects in multilevel survival analysis. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:27885709

Spatial Random Effects Survival Models to Assess Geographical Inequalities in Dengue Fever Using Bayesian Approach: a Case Study

NASA Astrophysics Data System (ADS)

Astuti Thamrin, Sri; Taufik, Irfan

2018-03-01

Dengue haemorrhagic fever (DHF) is an infectious disease caused by dengue virus. The increasing number of people with DHF disease correlates with the neighbourhood, for example sub-districts, and the characteristics of the sub-districts are formed from individuals who are domiciled in the sub-districts. Data containing individuals and sub-districts is a hierarchical data structure, called multilevel analysis. Frequently encountered response variable of the data is the time until an event occurs. Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in DHF survival. Using a case study approach, we report on the implications of using multilevel with spatial survival models to study geographical inequalities in all cause survival.

Negative differential resistance effect induced by metal ion implantation in SiO2 film for multilevel RRAM application

NASA Astrophysics Data System (ADS)

Wu, Facai; Si, Shuyao; Shi, Tuo; Zhao, Xiaolong; Liu, Qi; Liao, Lei; Lv, Hangbing; Long, Shibing; Liu, Ming

2018-02-01

Pt/SiO2:metal nanoparticles/Pt sandwich structure is fabricated with the method of metal ion (Ag) implantation. The device exhibits multilevel storage with appropriate R off/R on ratio, good endurance and retention properties. Based on transmission electron microscopy and energy dispersive spectrometer analysis, we confirm that Pt nanoparticles are spurted into SiO2 film from Pt bottom electrode by Ag implantation; during electroforming, the local electric field can be enhanced by these Pt nanoparticles, meanwhile the Ag nanoparticles constantly migrate toward the Pt nanoparticles. The implantation induced nanoparticles act as trap sites in the resistive switching layer and play critical roles in the multilevel storage, which is evidenced by the negative differential resistance effect in the current-voltage (I-V) measurements.

Who will volunteer? Analysing individual and structural factors of volunteering in Swiss sports clubs.

PubMed

Schlesinger, Torsten; Nagel, Siegfried

2013-01-01

This article analyses the conditions influencing volunteering in sports clubs. It focuses not only on individual characteristics of volunteers but also on the corresponding structural conditions of sports clubs. It proposes a model of voluntary work in sports clubs based on economic behaviour theory. The influences of both the individual and context levels on the decision to engage in voluntary work are estimated in different multilevel models. Results of these multilevel analyses indicate that volunteering is not just an outcome of individual characteristics such as lower workloads, higher income, children belonging to the sports club, longer club memberships, or a strong commitment to the club. It is also influenced by club-specific structural conditions; volunteering is more probable in rural sports clubs whereas growth-oriented goals in clubs have a destabilising effect.

On multilevel RBF collocation to solve nonlinear PDEs arising from endogenous stochastic volatility models

NASA Astrophysics Data System (ADS)

Bastani, Ali Foroush; Dastgerdi, Maryam Vahid; Mighani, Abolfazl

2018-06-01

The main aim of this paper is the analytical and numerical study of a time-dependent second-order nonlinear partial differential equation (PDE) arising from the endogenous stochastic volatility model, introduced in [Bensoussan, A., Crouhy, M. and Galai, D., Stochastic equity volatility related to the leverage effect (I): equity volatility behavior. Applied Mathematical Finance, 1, 63-85, 1994]. As the first step, we derive a consistent set of initial and boundary conditions to complement the PDE, when the firm is financed by equity and debt. In the sequel, we propose a Newton-based iteration scheme for nonlinear parabolic PDEs which is an extension of a method for solving elliptic partial differential equations introduced in [Fasshauer, G. E., Newton iteration with multiquadrics for the solution of nonlinear PDEs. Computers and Mathematics with Applications, 43, 423-438, 2002]. The scheme is based on multilevel collocation using radial basis functions (RBFs) to solve the resulting locally linearized elliptic PDEs obtained at each level of the Newton iteration. We show the effectiveness of the resulting framework by solving a prototypical example from the field and compare the results with those obtained from three different techniques: (1) a finite difference discretization; (2) a naive RBF collocation and (3) a benchmark approximation, introduced for the first time in this paper. The numerical results confirm the robustness, higher convergence rate and good stability properties of the proposed scheme compared to other alternatives. We also comment on some possible research directions in this field.

How to compare cross-lagged associations in a multilevel autoregressive model.

PubMed

Schuurman, Noémi K; Ferrer, Emilio; de Boer-Sonnenschein, Mieke; Hamaker, Ellen L

2016-06-01

By modeling variables over time it is possible to investigate the Granger-causal cross-lagged associations between variables. By comparing the standardized cross-lagged coefficients, the relative strength of these associations can be evaluated in order to determine important driving forces in the dynamic system. The aim of this study was twofold: first, to illustrate the added value of a multilevel multivariate autoregressive modeling approach for investigating these associations over more traditional techniques; and second, to discuss how the coefficients of the multilevel autoregressive model should be standardized for comparing the strength of the cross-lagged associations. The hierarchical structure of multilevel multivariate autoregressive models complicates standardization, because subject-based statistics or group-based statistics can be used to standardize the coefficients, and each method may result in different conclusions. We argue that in order to make a meaningful comparison of the strength of the cross-lagged associations, the coefficients should be standardized within persons. We further illustrate the bivariate multilevel autoregressive model and the standardization of the coefficients, and we show that disregarding individual differences in dynamics can prove misleading, by means of an empirical example on experienced competence and exhaustion in persons diagnosed with burnout. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Demographic, clinical, lifestyle-related, and social-cognitive correlates of physical activity in head and neck cancer survivors.

PubMed

Buffart, Laurien M; de Bree, Remco; Altena, Martine; van der Werff, Sophie; Drossaert, Constance H C; Speksnijder, Caroline M; van den Brekel, Michiel W; Jager-Wittenaar, Harriët; Aaronson, Neil K; Stuiver, Martijn M

2018-05-01

The purpose of the study is to identify demographic, clinical, lifestyle-related, and social-cognitive correlates of physical activity (PA) intention and behavior in head and neck cancer (HNC) survivors using the theory of planned behavior (TPB). Data from two cross-sectional studies on correlates of PA in HNC survivors were pooled. Both studies used self-reports to assess PA and social-cognitive correlates. Potential correlates were collected via self-report or medical records. Univariable and multivariable multilevel linear mixed-effects models were built to identify correlates of PA intention and PA behavior (Z scores). Structural equation model analyses were conducted to study the full TPB model in one analysis, taking into account relevant covariates. In total, 416 HNC survivors were surveyed. Their mean (SD) age was 66.6 (9.4) years; 64% were men, and 78% were diagnosed with laryngeal cancer. The structural equation model showed that PA intention was significantly higher in HNC survivors with a history of exercising, who had a more positive attitude, subjective norm, and perceived behavioral control. Patients with higher PA intention, higher PBC, a lower age, and without unintentional weight loss or comorbidities had higher PA behavior. The model explained 22.9% of the variance in PA intention and 16.1% of the variance in PA behavior. Despite significant pathways of the TPB model, the large proportion variance in PA intention and behavior remaining unexplained suggests the need for better PA behavior (change) models to guide the development of PA promotion programs, particularly for the elderly. Such programs should be tailored to comorbidities and nutritional status.

ML 3.0 smoothed aggregation user's guide.

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

Sala, Marzio; Hu, Jonathan Joseph; Tuminaro, Raymond Stephen

2004-05-01

ML is a multigrid preconditioning package intended to solve linear systems of equations Az = b where A is a user supplied n x n sparse matrix, b is a user supplied vector of length n and x is a vector of length n to be computed. ML should be used on large sparse linear systems arising from partial differential equation (PDE) discretizations. While technically any linear system can be considered, ML should be used on linear systems that correspond to things that work well with multigrid methods (e.g. elliptic PDEs). ML can be used as a stand-alone package ormore » to generate preconditioners for a traditional iterative solver package (e.g. Krylov methods). We have supplied support for working with the AZTEC 2.1 and AZTECOO iterative package [15]. However, other solvers can be used by supplying a few functions. This document describes one specific algebraic multigrid approach: smoothed aggregation. This approach is used within several specialized multigrid methods: one for the eddy current formulation for Maxwell's equations, and a multilevel and domain decomposition method for symmetric and non-symmetric systems of equations (like elliptic equations, or compressible and incompressible fluid dynamics problems). Other methods exist within ML but are not described in this document. Examples are given illustrating the problem definition and exercising multigrid options.« less

ML 3.1 smoothed aggregation user's guide.

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

Sala, Marzio; Hu, Jonathan Joseph; Tuminaro, Raymond Stephen

2004-10-01

ML is a multigrid preconditioning package intended to solve linear systems of equations Ax = b where A is a user supplied n x n sparse matrix, b is a user supplied vector of length n and x is a vector of length n to be computed. ML should be used on large sparse linear systems arising from partial differential equation (PDE) discretizations. While technically any linear system can be considered, ML should be used on linear systems that correspond to things that work well with multigrid methods (e.g. elliptic PDEs). ML can be used as a stand-alone package ormore » to generate preconditioners for a traditional iterative solver package (e.g. Krylov methods). We have supplied support for working with the Aztec 2.1 and AztecOO iterative package [16]. However, other solvers can be used by supplying a few functions. This document describes one specific algebraic multigrid approach: smoothed aggregation. This approach is used within several specialized multigrid methods: one for the eddy current formulation for Maxwell's equations, and a multilevel and domain decomposition method for symmetric and nonsymmetric systems of equations (like elliptic equations, or compressible and incompressible fluid dynamics problems). Other methods exist within ML but are not described in this document. Examples are given illustrating the problem definition and exercising multigrid options.« less

A Semi-Implicit, Three-Dimensional Model for Estuarine Circulation

USGS Publications Warehouse

Smith, Peter E.

2006-01-01

A semi-implicit, finite-difference method for the numerical solution of the three-dimensional equations for circulation in estuaries is presented and tested. The method uses a three-time-level, leapfrog-trapezoidal scheme that is essentially second-order accurate in the spatial and temporal numerical approximations. The three-time-level scheme is shown to be preferred over a two-time-level scheme, especially for problems with strong nonlinearities. The stability of the semi-implicit scheme is free from any time-step limitation related to the terms describing vertical diffusion and the propagation of the surface gravity waves. The scheme does not rely on any form of vertical/horizontal mode-splitting to treat the vertical diffusion implicitly. At each time step, the numerical method uses a double-sweep method to transform a large number of small tridiagonal equation systems and then uses the preconditioned conjugate-gradient method to solve a single, large, five-diagonal equation system for the water surface elevation. The governing equations for the multi-level scheme are prepared in a conservative form by integrating them over the height of each horizontal layer. The layer-integrated volumetric transports replace velocities as the dependent variables so that the depth-integrated continuity equation that is used in the solution for the water surface elevation is linear. Volumetric transports are computed explicitly from the momentum equations. The resulting method is mass conservative, efficient, and numerically accurate.

An object-oriented approach for parallel self adaptive mesh refinement on block structured grids

NASA Technical Reports Server (NTRS)

Lemke, Max; Witsch, Kristian; Quinlan, Daniel

1993-01-01

Self-adaptive mesh refinement dynamically matches the computational demands of a solver for partial differential equations to the activity in the application's domain. In this paper we present two C++ class libraries, P++ and AMR++, which significantly simplify the development of sophisticated adaptive mesh refinement codes on (massively) parallel distributed memory architectures. The development is based on our previous research in this area. The C++ class libraries provide abstractions to separate the issues of developing parallel adaptive mesh refinement applications into those of parallelism, abstracted by P++, and adaptive mesh refinement, abstracted by AMR++. P++ is a parallel array class library to permit efficient development of architecture independent codes for structured grid applications, and AMR++ provides support for self-adaptive mesh refinement on block-structured grids of rectangular non-overlapping blocks. Using these libraries, the application programmers' work is greatly simplified to primarily specifying the serial single grid application and obtaining the parallel and self-adaptive mesh refinement code with minimal effort. Initial results for simple singular perturbation problems solved by self-adaptive multilevel techniques (FAC, AFAC), being implemented on the basis of prototypes of the P++/AMR++ environment, are presented. Singular perturbation problems frequently arise in large applications, e.g. in the area of computational fluid dynamics. They usually have solutions with layers which require adaptive mesh refinement and fast basic solvers in order to be resolved efficiently.

Multilevel control of the metastable states in a manganite film

NASA Astrophysics Data System (ADS)

Jin, Feng; Feng, Qiyuan; Guo, Zhuang; Lan, Da; Chen, Binbin; Xu, Haoran; Wang, Ze; Wang, Lingfei; Gao, Guanyin; Chen, Feng; Lu, Qingyou; Wu, Wenbin

2017-06-01

For high density memory applications, the dynamic switching between multilevel resistance states per cell is highly desirable, and for oxide-based memory devices, the multistate operation has been actively explored. We have previously shown that for La2/3Ca1/3MnO3 films, the antiferromagnetic charge-ordered-insulator (COI) phase can be induced via the anisotropic epitaxial strain, and it competes with the doping-determined ferromagnetic-metal (FMM) ground state in a wide temperature range. Here, we show that for the phase competitions, in various magnetic fields and/or thermal cycling, the reappearance of the COI phase and thus the resistance and magnetization can be manipulated and quantified in a multilevel manner at lower temperatures. Furthermore, by using a high-field magnetic force microscope, we image the COI/FMM domain structures in accordance with the transport measurements, and find that the evolving domains or the phase fraction ratios do underline the metastability of the reappeared COI droplets, possibly protected by the energy barriers due to accommodation strain. These results may add new insights into the design and fabrication of future multilevel memory cells.

Empowerment and performance of managers and subordinates in elderly care: A longitudinal and multilevel study.

PubMed

Hagerman, Heidi; Högberg, Hans; Skytt, Bernice; Wadensten, Barbro; Engström, Maria

2017-11-01

To investigate relationships between first-line managers' ratings of structural and psychological empowerment, and the subordinates' ratings of structural empowerment, as well as their ratings of the managers' leadership-management performance. Work situations in elderly care are complex. To date, few studies have used a longitudinal, correlational and multilevel design to study the working life of subordinates and managers. In five Swedish municipalities, questionnaires were answered twice during 2010-12 by 56 first-line managers and 769 subordinates working in nursing homes or home-help services. First-line managers' empowerment at Time 1 partially predicted subordinate's structural empowerment and ratings of their managers' leadership-management performance at Time 2. Changes over time partially revealed that the more access managers had to structural empowerment, i.e. increase over time, the higher the ratings were for structural empowerment and managerial leadership-management performance among subordinates. Findings strengthen research and theoretical suggestions linking first-line managers' structural empowerment to their subordinates' structural empowerment and ratings of their manager's leadership-management performance. Managers with high access to structural empowerment are more likely to provide subordinates access to structural empowerment. © 2017 The Authors. Journal of Nursing Management Published by John Wiley & Sons Ltd.

Multi-level damage identification with response reconstruction

NASA Astrophysics Data System (ADS)

Zhang, Chao-Dong; Xu, You-Lin

2017-10-01

Damage identification through finite element (FE) model updating usually forms an inverse problem. Solving the inverse identification problem for complex civil structures is very challenging since the dimension of potential damage parameters in a complex civil structure is often very large. Aside from enormous computation efforts needed in iterative updating, the ill-condition and non-global identifiability features of the inverse problem probably hinder the realization of model updating based damage identification for large civil structures. Following a divide-and-conquer strategy, a multi-level damage identification method is proposed in this paper. The entire structure is decomposed into several manageable substructures and each substructure is further condensed as a macro element using the component mode synthesis (CMS) technique. The damage identification is performed at two levels: the first is at macro element level to locate the potentially damaged region and the second is over the suspicious substructures to further locate as well as quantify the damage severity. In each level's identification, the damage searching space over which model updating is performed is notably narrowed down, not only reducing the computation amount but also increasing the damage identifiability. Besides, the Kalman filter-based response reconstruction is performed at the second level to reconstruct the response of the suspicious substructure for exact damage quantification. Numerical studies and laboratory tests are both conducted on a simply supported overhanging steel beam for conceptual verification. The results demonstrate that the proposed multi-level damage identification via response reconstruction does improve the identification accuracy of damage localization and quantization considerably.

Multilevel Multi-Informant Structure of the Authoritative School Climate Survey

ERIC Educational Resources Information Center

Konold, Timothy; Cornell, Dewey; Huang, Francis; Meyer, Patrick; Lacey, Anna; Nekvasil, Erin; Heilbrun, Anna; Shukla, Kathan

2014-01-01

The Authoritative School Climate Survey was designed to provide schools with a brief assessment of 2 key characteristics of school climate--disciplinary structure and student support--that are hypothesized to influence 2 important school climate outcomes--student engagement and prevalence of teasing and bullying in school. The factor structure of…

Multilevel Safety Climate and Safety Performance in the Construction Industry: Development and Validation of a Top-Down Mechanism

PubMed Central

Gao, Ran; Chan, Albert P.C.; Utama, Wahyudi P.; Zahoor, Hafiz

2016-01-01

The character of construction projects exposes front-line workers to dangers and accidents. Safety climate has been confirmed to be a predictor of safety performance in the construction industry. This study aims to explore the underlying mechanisms of the relationship between multilevel safety climate and safety performance. An integrated model was developed to study how particular safety climate factors of one level affect those of other levels, and then affect safety performance from the top down. A questionnaire survey was administered on six construction sites in Vietnam. A total of 1030 valid questionnaires were collected from this survey. Approximately half of the data were used to conduct exploratory factor analysis (EFA) and the remaining data were submitted to structural equation modeling (SEM). Top management commitment (TMC) and supervisors’ expectation (SE) were identified as factors to represent organizational safety climate (OSC) and supervisor safety climate (SSC), respectively, and coworkers’ caring and communication (CCC) and coworkers’ role models (CRM) were identified as factors to denote coworker safety climate (CSC). SEM results show that OSC factor is positively related to SSC factor and CSC factors significantly. SSC factor could partially mediate the relationship between OSC factor and CSC factors, as well as the relationship between OSC factor and safety performance. CSC factors partially mediate the relationship between OSC factor and safety performance, and the relationship between SSC factor and safety performance. The findings imply that a positive safety culture should be established both at the organizational level and the group level. Efforts from all top management, supervisors, and coworkers should be provided to improve safety performance in the construction industry. PMID:27834823

Efficient Broadband Simulation of Fluid-Structure Coupling for Membrane-Type Acoustic Transducer Arrays Using the Multilevel Fast Multipole Algorithm.

PubMed

Shieh, Bernard; Sabra, Karim G; Degertekin, F Levent

2016-11-01

A boundary element model provides great flexibility for the simulation of membrane-type micromachined ultrasonic transducers (MUTs) in terms of membrane shape, actuating mechanism, and array layout. Acoustic crosstalk is accounted for through a mutual impedance matrix that captures the primary crosstalk mechanism of dispersive-guided modes generated at the fluid-solid interface. However, finding the solution to the fully populated boundary element matrix equation using standard techniques requires computation time and memory usage that scales by the cube and by the square of the number of nodes, respectively, limiting simulation to a small number of membranes. We implement a solver with improved speed and efficiency through the application of a multilevel fast multipole algorithm (FMA). By approximating the fields of collections of nodes using multipole expansions of the free-space Green's function, an FMA solver can enable the simulation of hundreds of thousands of nodes while incurring an approximation error that is controllable. Convergence is drastically improved using a problem-specific block-diagonal preconditioner. We demonstrate the solver's capabilities by simulating a 32-element 7-MHz 1-D capacitive MUT (CMUT) phased array with 2880 membranes. The array is simulated using 233280 nodes for a very wide frequency band up to 50 MHz. For a simulation with 15210 nodes, the FMA solver performed ten times faster and used 32 times less memory than a standard solver based on LU decomposition. We investigate the effects of mesh density and phasing on the predicted array response and find that it is necessary to use about seven nodes over the width of the membrane to observe convergence of the solution-even below the first membrane resonance frequency-due to the influence of higher order membrane modes.

Multilevel Safety Climate and Safety Performance in the Construction Industry: Development and Validation of a Top-Down Mechanism.

PubMed

Gao, Ran; Chan, Albert P C; Utama, Wahyudi P; Zahoor, Hafiz

2016-11-08

The character of construction projects exposes front-line workers to dangers and accidents. Safety climate has been confirmed to be a predictor of safety performance in the construction industry. This study aims to explore the underlying mechanisms of the relationship between multilevel safety climate and safety performance. An integrated model was developed to study how particular safety climate factors of one level affect those of other levels, and then affect safety performance from the top down. A questionnaire survey was administered on six construction sites in Vietnam. A total of 1030 valid questionnaires were collected from this survey. Approximately half of the data were used to conduct exploratory factor analysis (EFA) and the remaining data were submitted to structural equation modeling (SEM). Top management commitment (TMC) and supervisors' expectation (SE) were identified as factors to represent organizational safety climate (OSC) and supervisor safety climate (SSC), respectively, and coworkers' caring and communication (CCC) and coworkers' role models (CRM) were identified as factors to denote coworker safety climate (CSC). SEM results show that OSC factor is positively related to SSC factor and CSC factors significantly. SSC factor could partially mediate the relationship between OSC factor and CSC factors, as well as the relationship between OSC factor and safety performance. CSC factors partially mediate the relationship between OSC factor and safety performance, and the relationship between SSC factor and safety performance. The findings imply that a positive safety culture should be established both at the organizational level and the group level. Efforts from all top management, supervisors, and coworkers should be provided to improve safety performance in the construction industry.

A Structural Equation Model of HIV-Related Stigma, Racial Discrimination, Housing Insecurity and Wellbeing among African and Caribbean Black Women Living with HIV in Ontario, Canada

PubMed Central

Logie, Carmen H.; Jenkinson, Jesse I. R.; Earnshaw, Valerie; Tharao, Wangari; Loutfy, Mona R.

2016-01-01

African and Caribbean Black women in Canada have new HIV infection rates 7 times higher than their white counterparts. This overrepresentation is situated in structural contexts of inequities that result in social, economic and health disparities among African and Caribbean Black populations. Economic insecurity is a distal driver of HIV vulnerability, reducing access to HIV testing, prevention and care. Less is known about how economic insecurity indicators, such as housing security, continue to influence the lives of women living with HIV following HIV-positive diagnoses. The aim of this study was to test a conceptual model of the pathways linking HIV-related stigma, racial discrimination, housing insecurity, and wellbeing (depression, social support, self-rated health). We implemented a cross-sectional survey with African and Caribbean Black women living with HIV in 5 Ontario cities, and included 157 participants with complete data in the analyses. We conducted structural equation modeling using maximum likelihood estimation to evaluate the hypothesized conceptual model. One-fifth (22.5%; n = 39) of participants reported housing insecurity. As hypothesized, racial discrimination had significant direct effects on: HIV-related stigma, depression and social support, and an indirect effect on self-rated health via HIV-related stigma. HIV-related stigma and housing insecurity had direct effects on depression and social support, and HIV-related stigma had a direct effect on self-rated health. The model fit the data well: χ2 (45, n = 154) = 54.28, p = 0.387; CFI = 0.997; TLI = 0.996; RMSEA = 0.016. Findings highlight the need to address housing insecurity and intersecting forms of stigma and discrimination among African and Caribbean Black women living with HIV. Understanding the complex relationships between housing insecurity, HIV-related stigma, racial discrimination, and wellbeing can inform multi-level interventions to reduce stigma and enhance health. PMID:27669510

Effect of electron-electron scattering on the conductance of a quantum wire studied with the Boltzman transport equation

NASA Astrophysics Data System (ADS)

Lyo, S. K.; Huang, Danhong

2006-05-01

Electron-electron scattering conserves total momentum and does not dissipate momentum directly in a low-density system where the umklapp process is forbidden. However, it can still affect the conductance through the energy relaxation of the electrons. We show here that this effect can be studied with arbitrary accuracy in a multisublevel one-dimensional (1D) single quantum wire system in the presence of roughness and phonon scattering using a formally exact solution of the Boltzmann transport equation. The intrasubband electron-electron scattering is found to yield no net effect on the transport of electrons in 1D with only one sublevel occupied. For a system with a multilevel occupation, however, we find a significant effect of intersublevel electron-electron scattering on the temperature and density dependence of the resistance at low temperatures.

A multilevel analysis of the effects of the Practice Environment Scale of the Nursing Work Index on nurse outcomes.

PubMed

Gabriel, Allison S; Erickson, Rebecca J; Moran, Christina M; Diefendorff, James M; Bromley, Gail E

2013-12-01

Few researchers have examined how the components of the Practice Environment Scale of the Nursing Work Index (PES-NWI) relate to nurses' well-being at multiple organizational levels. The objective of the study was to perform a multilevel assessment of the relationships of the PES-NWI subscales with three nurse outcomes: job satisfaction, emotional exhaustion, and turnover intentions. Additionally, we tested the multilevel factor structure of the PES-NWI. In a sample of 699 full-time registered nurses in 79 units and 9 branches of a hospital system, relationships of the NWI with nurse outcomes were fairly consistent across levels of analysis. However, subscales contributed differently to the three outcomes, demonstrating the complexity of environmental influences on nurses' work experience. © 2013 Wiley Periodicals, Inc.

"Rebuilding our community": hearing silenced voices on Aboriginal youth suicide.

PubMed

Walls, Melissa L; Hautala, Dane; Hurley, Jenna

2014-02-01

This paper brings forth the voices of adult Aboriginal First Nations community members who gathered in focus groups to discuss the problem of youth suicide on their reserves. Our approach emphasizes multilevel (e.g., individual, family, and broader ecological systems) factors viewed by participants as relevant to youth suicide. Wheaton's conceptualization of stressors and Evans-Campbell's multilevel classification of the impacts of historical trauma are used as theoretical and analytic guides. Thematic analysis of qualitative data transcripts revealed a highly complex intersection of stressors, traumas, and social problems seen by community members as underlying mechanisms influencing heightened levels of Aboriginal youth suicidality. Our multilevel coding approach revealed that suicidal behaviors were described by community members largely as a problem with deep historical and contemporary structural roots, as opposed to being viewed as individualized pathology.

How Structure Shapes Dynamics: Knowledge Development in Wikipedia - A Network Multilevel Modeling Approach

PubMed Central

Halatchliyski, Iassen; Cress, Ulrike

2014-01-01

Using a longitudinal network analysis approach, we investigate the structural development of the knowledge base of Wikipedia in order to explain the appearance of new knowledge. The data consists of the articles in two adjacent knowledge domains: psychology and education. We analyze the development of networks of knowledge consisting of interlinked articles at seven snapshots from 2006 to 2012 with an interval of one year between them. Longitudinal data on the topological position of each article in the networks is used to model the appearance of new knowledge over time. Thus, the structural dimension of knowledge is related to its dynamics. Using multilevel modeling as well as eigenvector and betweenness measures, we explain the significance of pivotal articles that are either central within one of the knowledge domains or boundary-crossing between the two domains at a given point in time for the future development of new knowledge in the knowledge base. PMID:25365319

A novel multi-level IC-compatible surface microfabrication technology for MEMS with independently controlled lateral and vertical submicron transduction gaps

NASA Astrophysics Data System (ADS)

Cicek, Paul-Vahe; Elsayed, Mohannad; Nabki, Frederic; El-Gamal, Mourad

2017-11-01

An above-IC compatible multi-level MEMS surface microfabrication technology based on a silicon carbide structural layer is presented. The fabrication process flow provides optimal electrostatic transduction by allowing the creation of independently controlled submicron vertical and lateral gaps without the need for high resolution lithography. Adopting silicon carbide as the structural material, the technology ensures material, chemical and thermal compatibility with modern semiconductor nodes, reporting the lowest peak processing temperature (i.e. 200 °C) of all comparable works. This makes this process ideally suited for integrating capacitive-based MEMS directly above standard CMOS substrates. Process flow design and optimization are presented in the context of bulk-mode disk resonators, devices that are shown to exhibit improved performance with respect to previous generation flexural beam resonators, and that represent relatively complex MEMS structures. The impact of impending improvements to the fabrication technology is discussed.

Dark channels in resonant tunneling transport through artificial atoms.

PubMed

Vaz, Eduardo; Kyriakidis, Jordan

2008-07-14

We investigate sequential tunneling through a multilevel quantum dot confining multiple electrons in the regime where several channels are available for transport within the bias window. By analyzing solutions to the master equations of the reduced density matrix, we give general conditions on when the presence of a second transport channel in the bias window quenches transport through the quantum dot. These conditions are in terms of distinct tunneling anisotropies which may aid in explaining the occurrence of negative differential conductance in quantum dots in the nonlinear regime.

A Structural Modeling Approach to a Multilevel Random Coefficients Model.

ERIC Educational Resources Information Center

Rovine, Michael J.; Molenaar, Peter C. M.

2000-01-01

Presents a method for estimating the random coefficients model using covariance structure modeling and allowing one to estimate both fixed and random effects. The method is applied to real and simulated data, including marriage data from J. Belsky and M. Rovine (1990). (SLD)

Emitter signal separation method based on multi-level digital channelization

NASA Astrophysics Data System (ADS)

Han, Xun; Ping, Yifan; Wang, Sujun; Feng, Ying; Kuang, Yin; Yang, Xinquan

2018-02-01

To solve the problem of emitter separation under complex electromagnetic environment, a signal separation method based on multi-level digital channelization is proposed in this paper. A two-level structure which can divide signal into different channel is designed first, after that, the peaks of different channels are tracked using the track filter and the coincident signals in time domain are separated in time-frequency domain. Finally, the time domain waveforms of different signals are acquired by reverse transformation. The validness of the proposed method is proved by experiment.

Near-Edge X-ray Absorption Fine Structure within Multilevel Coupled Cluster Theory.

PubMed

Myhre, Rolf H; Coriani, Sonia; Koch, Henrik

2016-06-14

Core excited states are challenging to calculate, mainly because they are embedded in a manifold of high-energy valence-excited states. However, their locality makes their determination ideal for local correlation methods. In this paper, we demonstrate the performance of multilevel coupled cluster theory in computing core spectra both within the core-valence separated and the asymmetric Lanczos implementations of coupled cluster linear response theory. We also propose a visualization tool to analyze the excitations using the difference between the ground-state and excited-state electron densities.

Structure and Stability of One-Dimensional Detonations in Ethylene-Air Mixtures

NASA Technical Reports Server (NTRS)

Yungster, S.; Radhakrishnan, K.; Perkins, High D. (Technical Monitor)

2003-01-01

The propagation of one-dimensional detonations in ethylene-air mixtures is investigated numerically by solving the one-dimensional Euler equations with detailed finite-rate chemistry. The numerical method is based on a second-order spatially accurate total-variation-diminishing scheme and a point implicit, first-order-accurate, time marching algorithm. The ethylene-air combustion is modeled with a 20-species, 36-step reaction mechanism. A multi-level, dynamically adaptive grid is utilized, in order to resolve the structure of the detonation. Parametric studies over an equivalence ratio range of 0.5 less than phi less than 3 for different initial pressures and degrees of detonation overdrive demonstrate that the detonation is unstable for low degrees of overdrive, but the dynamics of wave propagation varies with fuel-air equivalence ratio. For equivalence ratios less than approximately 1.2 the detonation exhibits a short-period oscillatory mode, characterized by high-frequency, low-amplitude waves. Richer mixtures (phi greater than 1.2) exhibit a low-frequency mode that includes large fluctuations in the detonation wave speed; that is, a galloping propagation mode is established. At high degrees of overdrive, stable detonation wave propagation is obtained. A modified McVey-Toong short-period wave-interaction theory is in excellent agreement with the numerical simulations.

Impact of roadway geometric features on crash severity on rural two-lane highways.

PubMed

Haghighi, Nima; Liu, Xiaoyue Cathy; Zhang, Guohui; Porter, Richard J

2018-02-01

This study examines the impact of a wide range of roadway geometric features on the severity outcomes of crashes occurred on rural two-lane highways. We argue that crash data have a hierarchical structure which needs to be addressed in modeling procedure. Moreover, most of previous studies ignored the impact of geometric features on crash types when developing crash severity models. We hypothesis that geometric features are more likely to determine crash type, and crash type together with other occupant, environmental and vehicle characteristics determine crash severity outcome. This paper presents an application of multilevel models to successfully capture both hierarchical structure of crash data and indirect impact of geometric features on crash severity. Using data collected in Illinois from 2007 to 2009, multilevel ordered logit model is developed to quantify the impact of geometric features and environmental conditions on crash severity outcome. Analysis results revealed that there is a significant variation in severity outcomes of crashes occurred across segments which verifies the presence of hierarchical structure. Lower risk of severe crashes is found to be associated with the presence of 10-ft lane and/or narrow shoulders, lower roadside hazard rate, higher driveway density, longer barrier length, and shorter barrier offset. The developed multilevel model offers greater consistency with data generating mechanism and can be utilized to evaluate safety effects of geometric design improvement projects. Published by Elsevier Ltd.

Exploring the impact of different multi-level measures of physician communities in patient-centric care networks on healthcare outcomes: A multi-level regression approach.

PubMed

Uddin, Shahadat

2016-02-04

A patient-centric care network can be defined as a network among a group of healthcare professionals who provide treatments to common patients. Various multi-level attributes of the members of this network have substantial influence to its perceived level of performance. In order to assess the impact different multi-level attributes of patient-centric care networks on healthcare outcomes, this study first captured patient-centric care networks for 85 hospitals using health insurance claim dataset. From these networks, this study then constructed physician collaboration networks based on the concept of patient-sharing network among physicians. A multi-level regression model was then developed to explore the impact of different attributes that are organised at two levels on hospitalisation cost and hospital length of stay. For Level-1 model, the average visit per physician significantly predicted both hospitalisation cost and hospital length of stay. The number of different physicians significantly predicted only the hospitalisation cost, which has significantly been moderated by age, gender and Comorbidity score of patients. All Level-1 findings showed significance variance across physician collaboration networks having different community structure and density. These findings could be utilised as a reflective measure by healthcare decision makers. Moreover, healthcare managers could consider them in developing effective healthcare environments.

Multilevel and sex-specific selection on competitive traits in North American red squirrels.

PubMed

Fisher, David N; Boutin, Stan; Dantzer, Ben; Humphries, Murray M; Lane, Jeffrey E; McAdam, Andrew G

2017-07-01

Individuals often interact more closely with some members of the population (e.g., offspring, siblings, or group members) than they do with other individuals. This structuring of interactions can lead to multilevel natural selection, where traits expressed at the group-level influence fitness alongside individual-level traits. Such multilevel selection can alter evolutionary trajectories, yet is rarely quantified in the wild, especially for species that do not interact in clearly demarcated groups. We quantified multilevel natural selection on two traits, postnatal growth rate and birth date, in a population of North American red squirrels (Tamiasciurus hudsonicus). The strongest level of selection was typically within-acoustic social neighborhoods (within 130 m of the nest), where growing faster and being born earlier than nearby litters was key, while selection on growth rate was also apparent both within-litters and within-study areas. Higher population densities increased the strength of selection for earlier breeding, but did not influence selection on growth rates. Females experienced especially strong selection on growth rate at the within-litter level, possibly linked to the biased bequeathal of the maternal territory to daughters. Our results demonstrate the importance of considering multilevel and sex-specific selection in wild species, including those that are territorial and sexually monomorphic. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Bridging the gap between biologic, individual, and macroenvironmental factors in cancer: a multilevel approach.

PubMed

Lynch, Shannon M; Rebbeck, Timothy R

2013-04-01

To address the complex nature of cancer occurrence and outcomes, approaches have been developed to simultaneously assess the role of two or more etiologic agents within hierarchical levels including the: (i) macroenvironment level (e.g., health care policy, neighborhood, or family structure); (ii) individual level (e.g., behaviors, carcinogenic exposures, socioeconomic factors, and psychologic responses); and (iii) biologic level (e.g., cellular biomarkers and inherited susceptibility variants). Prior multilevel approaches tend to focus on social and environmental hypotheses, and are thus limited in their ability to integrate biologic factors into a multilevel framework. This limited integration may be related to the limited translation of research findings into the clinic. We propose a "Multi-level Biologic and Social Integrative Construct" (MBASIC) to integrate macroenvironment and individual factors with biology. The goal of this framework is to help researchers identify relationships among factors that may be involved in the multifactorial, complex nature of cancer etiology, to aid in appropriate study design, to guide the development of statistical or mechanistic models to study these relationships, and to position the results of these studies for improved intervention, translation, and implementation. MBASIC allows researchers from diverse fields to develop hypotheses of interest under a common conceptual framework, to guide transdisciplinary collaborations, and to optimize the value of multilevel studies for clinical and public health activities.

Multi-level storage and ultra-high speed of superlattice-like Ge50Te50/Ge8Sb92 thin film for phase-change memory application.

PubMed

Wu, Weihua; Chen, Shiyu; Zhai, Jiwei; Liu, Xinyi; Lai, Tianshu; Song, Sannian; Song, Zhitang

2017-10-06

Superlattice-like Ge 50 Te 50 /Ge 8 Sb 92 (SLL GT/GS) thin film was systematically investigated for multi-level storage and ultra-fast switching phase-change memory application. In situ resistance measurement indicates that SLL GT/GS thin film exhibits two distinct resistance steps with elevated temperature. The thermal stability of the amorphous state and intermediate state were evaluated with the Kissinger and Arrhenius plots. The phase-structure evolution revealed that the amorphous SLL GT/GS thin film crystallized into rhombohedral Sb phase first, then the rhombohedral GeTe phase. The microstructure, layered structure, and interface stability of SLL GT/GS thin film was confirmed by using transmission electron microscopy. The transition speed of crystallization and amorphization was measured by the picosecond laser pump-probe system. The volume variation during the crystallization was obtained from x-ray reflectivity. Phase-change memory (PCM) cells based on SLL GT/GS thin film were fabricated to verify the multi-level switching under an electrical pulse as short as 30 ns. These results illustrate that the SLL GT/GS thin film has great potentiality in high-density and high-speed PCM applications.

Building Collaborative Structures for Teachers' Autonomy and Self-Efficacy: The Mediating Role of Participative Management and Learning Culture

ERIC Educational Resources Information Center

Lu, Jiafang; Jiang, Xinhui; Yu, Huen; Li, Dongyu

2015-01-01

This study focused on the collaborative structure-building behavior of school principals and examined how such behavior affects teacher empowerment. More important, it tested the mediating effects of participative management and learning culture. By collecting nested data from 104 schools in Hong Kong and adopting multilevel structural equation…

Reciprocal Relations between Work-Related Authenticity and Intrinsic Motivation, Work Ability and Depressivity: A Two-Wave Study

PubMed Central

Emmerich, Astrid I.; Rigotti, Thomas

2017-01-01

This study investigates the role of context-specific authenticity at work for work-related outcomes (intrinsic motivation, work ability) and depressivity. Furthermore reciprocal relations between work-related authenticity and healthy psychological functioning are investigated. Longitudinal data from 1,243 employees from 63 subsidiaries of a non-profit organization in the social sector were analyzed using multilevel structural equation modeling. Work-related authenticity at T1 predicted work ability and depressivity, but not intrinsic motivation at T2, about 6 months later. Work-related authenticity at T2 was predicted by intrinsic motivation and depressivity, but not by work ability at T1. We conclude that work-related authenticity and healthy psychological functioning are positively reinforcing each other. Thus, enabling employees to be authentic supposedly increases their well-being and is a pivotal opportunity for organizations to foster health and performance-related indicators like work ability and prevent negative health indicators like depressivity. At the same time, authenticity of employees can be fostered through workplace health promotion. PMID:28316581

Impacts of family and community violence exposure on child coping and mental health.

PubMed

Mohammad, Esror Tamim; Shapiro, Ester R; Wainwright, Laurel D; Carter, Alice S

2015-02-01

An ecological stress process model was employed to explore relations between children's exposures to family and community violence and child mental health, and emotionally-regulated coping (ERC) as a protective factor among Latino, European-American, and African-American school-aged children (n = 91; girls, n = 50[54 %]) living in single-parent families who were either homeless and residing in emergency shelters or housed but living in poverty. Mothers reported domestic violence experiences and their child's history of physical/sexual abuse, community violence exposures, and mental health. Children reported on exposure to community violence, internalizing symptoms, and coping. The mental health impacts of multi-level violence exposures and ERC as a moderator of associations between violence exposures and child mental health was tested with structural equation modeling. Family abuse was uniquely associated with PTSD, and community violence with anxiety and aggression. Latent interaction tests revealed that ERC moderated relations between family abuse and anxiety, aggression and PTSD. Emotionally-regulated coping appears to play a protective role for children's mental health in contexts of violence exposure, offering opportunities for intervention and prevention.

Relationships between racial-ethnic identity, self-esteem and in-group attitudes among First Nation children.

PubMed

Corenblum, Barry

2014-03-01

Positive in-group distinctiveness has been associated with self-esteem increases among adolescents and adults. To examine whether in-group biases are associated with self-esteem enhancement among minority group children, Native Canadian children (N = 414, 209 female) age 6-11 completed each year for 5 years, measures assessing their level of concrete operational thought, racial-ethnic identity, racial-ethnic centrality, implicit and explicit self-esteem, and implicit and explicit in-group attitudes. According to cognitive developmental theory, increases in the level of concrete operational thought will predict increases in racial-ethnic identity, and increases in identity should, in turn, predict more favorable in-group attitudes. Social identity theory predicts that more favorable in-group attitudes should predict increases in self-esteem. Multi-level structural equation modelling revealed support for these hypotheses. Cognitively mature children who identify closely with their group enhanced their level of self-esteem by positively differentiating between group members on dimensions that favor their group. Limitations of the present study and suggestions for future studies are also presented.

Dispositional and Situational Avoidance and Approach as Predictors of Physical Symptom Bother Following Breast Cancer Diagnosis

PubMed Central

Bauer, Margaret R.; Harris, Lauren N.; Wiley, Joshua F.; Crespi, Catherine M.; Krull, Jennifer L.; Weihs, Karen L.; Stanton, Annette L.

2016-01-01

Background Few studies examine whether dispositional approach and avoidance coping and stressor-specific coping strategies differentially predict physical adjustment to cancer-related stress. Purpose This study examines dispositional and situational avoidance and approach coping as unique predictors of the bother women experience from physical symptoms after breast cancer treatment, as well as whether situational coping mediates the prediction of bother from physical symptoms by dispositional coping. Method Breast cancer patients (N=460) diagnosed within the past 3 months completed self-report measures of dispositional coping at study entry and of situational coping and bother from physical symptoms every 6 weeks through 6 months. Results In multilevel structural equation modeling analyses, both dispositional and situational avoidance predict greater symptom bother. Dispositional, but not situational, approach predicts less symptom bother. Supporting mediation models, dispositional avoidance predicts more symptom bother indirectly through greater situational avoidance. Dispositional approach predicts less symptom bother through less situational avoidance. Conclusion Psychosocial interventions to reduce cancer-related avoidance coping are warranted for cancer survivors who are high in dispositional avoidance and/or low in dispositional approach. PMID:26769023

Dispositional and Situational Avoidance and Approach as Predictors of Physical Symptom Bother Following Breast Cancer Diagnosis.

PubMed

Bauer, Margaret R; Harris, Lauren N; Wiley, Joshua F; Crespi, Catherine M; Krull, Jennifer L; Weihs, Karen L; Stanton, Annette L

2016-06-01

Few studies examine whether dispositional approach and avoidance coping and stressor-specific coping strategies differentially predict physical adjustment to cancer-related stress. This study examines dispositional and situational avoidance and approach coping as unique predictors of the bother women experience from physical symptoms after breast cancer treatment, as well as whether situational coping mediates the prediction of bother from physical symptoms by dispositional coping. Breast cancer patients (N = 460) diagnosed within the past 3 months completed self-report measures of dispositional coping at study entry and of situational coping and bother from physical symptoms every 6 weeks through 6 months. In multilevel structural equation modeling analyses, both dispositional and situational avoidance predict greater symptom bother. Dispositional, but not situational, approach predicts less symptom bother. Supporting mediation models, dispositional avoidance predicts more symptom bother indirectly through greater situational avoidance. Dispositional approach predicts less symptom bother through less situational avoidance. Psychosocial interventions to reduce cancer-related avoidance coping are warranted for cancer survivors who are high in dispositional avoidance and/or low in dispositional approach.

Synergistic Effects of Expectancy and Value on Homework Engagement: The Case for a Within-Person Perspective.

PubMed

Nagengast, Benjamin; Trautwein, Ulrich; Kelava, Augustin; Lüdtke, Oliver

2013-05-01

Historically, expectancy-value models of motivation assumed a synergistic relation between expectancy and value: motivation is high only when both expectancy and value are high. Motivational processes were studied from a within-person perspective, with expectancies and values being assessed or experimentally manipulated across multiple domains and the focus being placed on intraindividual differences. In contrast, contemporary expectancy-value models in educational psychology concentrate almost exclusively on linear effects of expectancy and value on motivational outcomes, with a focus on between-person differences. Recent advances in latent variable methodology allow both issues to be addressed in observational studies. Using the expectancy-value model of homework motivation as a theoretical framework, this study estimated multilevel structural equation models with latent interactions in a sample of 511 secondary school students and found synergistic effects between domain-specific homework expectancy and homework value in predicting homework engagement in 6 subjects. This approach not only brings the "×" back into expectancy-value theory but also reestablishes the within-person perspective as the appropriate level of analysis for latent expectancy-value models.

Developing the formula for state subsidies for health care in Finland.

PubMed

Häkkinen, Unto; Järvelin, Jutta

2004-01-01

The aim was to generate a research-based proposal for a new subsidy formula for municipal healthcare services in Finland. Small-area data on potential need variables, supply of and access to services, and age-, sex- and case-mix-standardised service utilisation per capita were used. Utilisation was regressed in order to identify need variables and the cost weights for the selected need variables were subsequently derived using various multilevel models and structural equation methods. The variables selected for the subsidy formula were as follows: age- and sex-standardised mortality (age under 65 years) and income for outpatient primary health services; age- and sex-standardised mortality (all ages) and index of overcrowded housing for elderly care and long-term inpatient care; index of disability pensions for those aged 15-55 years and migration for specialised non-psychiatric care; and index of living alone and income for psychiatric care. Decisions on the amount of state subsidies can be divided into three stages, of which the first two are mainly political and the third is based on the results of this study.

Does Drinking to Cope Explain Links Between Emotion-Driven Impulse Control Difficulties and Hazardous Drinking? A Longitudinal Test

PubMed Central

Watkins, Laura E.; Franz, Molly R.; DiLillo, David; Gratz, Kim L.; Messman-Moore, Terri L.

2016-01-01

Difficulty controlling impulsive behaviors when experiencing negative emotions is a prominent risk factor for hazardous alcohol use, and prior research suggests that drinking to cope may mediate this association. The present study examines this possibility prospectively in a sample of 490 young adult women between the ages of 18 and 25. Participants completed measures of emotion-driven impulse control difficulties, drinking to cope, and hazardous alcohol use at six time points over the course of approximately 20 months (i.e., one assessment every four months). Multilevel structural equation modeling revealed that drinking to cope fully mediated the relationship between emotion-driven impulse control difficulties and hazardous alcohol use when examining these relationships between individuals and partially mediated this relation when examining these relationships within individuals. These findings suggest that drinking to cope is a key mechanism in the relationship between emotion-driven impulse control difficulties and hazardous drinking. Results highlight the importance of targeting both emotion dysregulation and drinking to cope when treating young women for alcohol use problems. PMID:26502334

A multilevel simultaneous equations model for within-cluster dynamic effects, with an application to reciprocal parent-child and sibling effects.

PubMed

Steele, Fiona; Rasbash, Jon; Jenkins, Jennifer

2013-03-01

There has been substantial interest in the social and health sciences in the reciprocal causal influences that people in close relationships have on one another. Most research has considered reciprocal processes involving only 2 units, although many social relationships of interest occur within a larger group (e.g., families, work groups, peer groups, classrooms). This article presents a general longitudinal multilevel modeling framework for the simultaneous estimation of reciprocal relationships among individuals with unique roles operating in a social group. We use family data for illustrative purposes, but the model is generalizable to any social group in which measurements of individuals in the social group occur over time, individuals have unique roles, and clustering of the data is evident. We allow for the possibility that the outcomes of family members are influenced by a common set of unmeasured family characteristics. The multilevel model we propose allows for residual variation in the outcomes of parents and children at the occasion, individual, and family levels and residual correlation between parents and children due to the unmeasured shared environment, genetic factors, and shared measurement. Another advantage of this method over approaches used in previous family research is it can handle mixed family sizes. The method is illustrated in an analysis of maternal depression and child delinquency using data from the Avon Brothers and Sisters Study. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Measurement and structural relations of an authoritative school climate model: A multi-level latent variable investigation.

PubMed

Konold, Timothy R; Cornell, Dewey

2015-12-01

This study tested a conceptual model of school climate in which two key elements of an authoritative school, structure and support variables, are associated with student engagement in school and lower levels of peer aggression. Multilevel multivariate structural modeling was conducted in a statewide sample of 48,027 students in 323 public high schools who completed the Authoritative School Climate Survey. As hypothesized, two measures of structure (Disciplinary Structure and Academic Expectations) and two measures of support (Respect for Students and Willingness to Seek Help) were associated with higher student engagement (Affective Engagement and Cognitive Engagement) and lower peer aggression (Prevalence of Teasing and Bullying) on both student and school levels of analysis, controlling for the effects of school demographics (school size, percentage of minority students, and percentage of low income students). These results support the extension of authoritative school climate model to high school and guide further research on the conditions for a positive school climate. Copyright © 2015 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

The cultural production of health inequalities: a cross-sectional, multilevel examination of 52 countries.

PubMed

Mansyur, Carol Leler; Amick, Benjamin C; Harrist, Ronald B; Franzini, Luisa; Roberts, Robert E

2009-01-01

In a 2001 report, the U.S. National Institutes of Health called for more integration of the social sciences into health-related research, including research guided by theories and methods that take social and cultural systems into consideration. Based on a theoretical framework that integrates Hofstede's cultural dimensions with sociological theory, the authors used multilevel modeling to explore the association of culture with structural inequality and health disparities. Their results support the idea that cultural dimensions and social structure, along with economic development, may account for much of the cross-national variation in the distribution of health inequalities. Sensitivity tests also suggest that an interaction between culture and social structure may confound the relationship between income inequality and health. It is necessary to identify important cultural and social structural characteristics before we can achieve an understanding of the complex, dynamic systems that affect health, and develop culturally sensitive interventions and policies. This study takes a step toward identifying some of the relevant cultural and structural influences. More research is needed to explore the pathways leading from the sociocultural environment to health inequalities.

Examining Brain Morphometry Associated with Self-Esteem in Young Adults Using Multilevel-ROI-Features-Based Classification Method

PubMed Central

Peng, Bo; Lu, Jieru; Saxena, Aditya; Zhou, Zhiyong; Zhang, Tao; Wang, Suhong; Dai, Yakang

2017-01-01

Purpose: This study is to exam self-esteem related brain morphometry on brain magnetic resonance (MR) images using multilevel-features-based classification method. Method: The multilevel region of interest (ROI) features consist of two types of features: (i) ROI features, which include gray matter volume, white matter volume, cerebrospinal fluid volume, cortical thickness, and cortical surface area, and (ii) similarity features, which are based on similarity calculation of cortical thickness between ROIs. For each feature type, a hybrid feature selection method, comprising of filter-based and wrapper-based algorithms, is used to select the most discriminating features. ROI features and similarity features are integrated by using multi-kernel support vector machines (SVMs) with appropriate weighting factor. Results: The classification performance is improved by using multilevel ROI features with an accuracy of 96.66%, a specificity of 96.62%, and a sensitivity of 95.67%. The most discriminating ROI features that are related to self-esteem spread over occipital lobe, frontal lobe, parietal lobe, limbic lobe, temporal lobe, and central region, mainly involving white matter and cortical thickness. The most discriminating similarity features are distributed in both the right and left hemisphere, including frontal lobe, occipital lobe, limbic lobe, parietal lobe, and central region, which conveys information of structural connections between different brain regions. Conclusion: By using ROI features and similarity features to exam self-esteem related brain morphometry, this paper provides a pilot evidence that self-esteem is linked to specific ROIs and structural connections between different brain regions. PMID:28588470

Examining Brain Morphometry Associated with Self-Esteem in Young Adults Using Multilevel-ROI-Features-Based Classification Method.

PubMed

Peng, Bo; Lu, Jieru; Saxena, Aditya; Zhou, Zhiyong; Zhang, Tao; Wang, Suhong; Dai, Yakang

2017-01-01

Purpose: This study is to exam self-esteem related brain morphometry on brain magnetic resonance (MR) images using multilevel-features-based classification method. Method: The multilevel region of interest (ROI) features consist of two types of features: (i) ROI features, which include gray matter volume, white matter volume, cerebrospinal fluid volume, cortical thickness, and cortical surface area, and (ii) similarity features, which are based on similarity calculation of cortical thickness between ROIs. For each feature type, a hybrid feature selection method, comprising of filter-based and wrapper-based algorithms, is used to select the most discriminating features. ROI features and similarity features are integrated by using multi-kernel support vector machines (SVMs) with appropriate weighting factor. Results: The classification performance is improved by using multilevel ROI features with an accuracy of 96.66%, a specificity of 96.62%, and a sensitivity of 95.67%. The most discriminating ROI features that are related to self-esteem spread over occipital lobe, frontal lobe, parietal lobe, limbic lobe, temporal lobe, and central region, mainly involving white matter and cortical thickness. The most discriminating similarity features are distributed in both the right and left hemisphere, including frontal lobe, occipital lobe, limbic lobe, parietal lobe, and central region, which conveys information of structural connections between different brain regions. Conclusion: By using ROI features and similarity features to exam self-esteem related brain morphometry, this paper provides a pilot evidence that self-esteem is linked to specific ROIs and structural connections between different brain regions.

Ambulant children with spastic cerebral palsy and their parents' perceptions and expectations prior to multilevel surgery.

PubMed

Capjon, Hilde; Bjørk, Ida Torunn

2010-01-01

This study explores the pre-operative situation of children accepted for multilevel surgery for cerebral palsy (CP) and their parents. Eight ambulatory children with varied severity of spastic CP and their parents were included. Qualitative, semi-structured interviews were carried out separately with the children and parents. Everyday life of the children and their parents was vulnerable. The degree to which children strived for social acceptance and normality increased their pain. Deteriorating physical capacity resulted in pain and fatigue and was the parents' and children's main motivation for the operation. Although the parents were ambivalent to the operation they mediated hope and cautious optimism about a better life for their children. Parents' and children's experiences imply the need for improvements to ensure facilitation for disabled children in schools and all levels of the health service, equality of communication and awareness-raising in the pre-operative phase of multilevel surgery.

Multiplex lithography for multilevel multiscale architectures and its application to polymer electrolyte membrane fuel cell

NASA Astrophysics Data System (ADS)

Cho, Hyesung; Moon Kim, Sang; Sik Kang, Yun; Kim, Junsoo; Jang, Segeun; Kim, Minhyoung; Park, Hyunchul; Won Bang, Jung; Seo, Soonmin; Suh, Kahp-Yang; Sung, Yung-Eun; Choi, Mansoo

2015-09-01

The production of multiscale architectures is of significant interest in materials science, and the integration of those structures could provide a breakthrough for various applications. Here we report a simple yet versatile strategy that allows for the LEGO-like integrations of microscale membranes by quantitatively controlling the oxygen inhibition effects of ultraviolet-curable materials, leading to multilevel multiscale architectures. The spatial control of oxygen concentration induces different curing contrasts in a resin allowing the selective imprinting and bonding at different sides of a membrane, which enables LEGO-like integration together with the multiscale pattern formation. Utilizing the method, the multilevel multiscale Nafion membranes are prepared and applied to polymer electrolyte membrane fuel cell. Our multiscale membrane fuel cell demonstrates significant enhancement of performance while ensuring mechanical robustness. The performance enhancement is caused by the combined effect of the decrease of membrane resistance and the increase of the electrochemical active surface area.

Deaf capital: an exploration of the relationship between stigma and value in deaf multilevel marketing participation in Urban India.

PubMed

Friedner, Michele

2014-12-01

This article ethnographically examines how some deaf people in urban India have begun to orient themselves toward the future by participating in multilevel marketing businesses. In the absence of other structural possibilities for deaf future-making, deaf Indians have turned to such businesses in search of social, economic, and moral livelihood. This article analyzes participation in one particular business and asks how participating within the business both enables and disables the cultivation of specific ideas of development. Particular attention is devoted to exploring the multiple registers of the concept of "deaf development" and how such development may be cultivated through multilevel marketing businesses. This article aims to make a critical intervention in medical anthropology studies of disability by arguing that disability (or in this case deafness) can function as a source of value, therefore highlighting tensions between stigma and value. © 2014 by the American Anthropological Association.

Review of Issues About Classical Change Scores: A Multilevel Modeling Perspective on Some Enduring Beliefs.

PubMed

Gu, Zhengguo; Emons, Wilco H M; Sijtsma, Klaas

2018-04-30

Change scores obtained in pretest-posttest designs are important for evaluating treatment effectiveness and for assessing change of individual test scores in psychological research. However, over the years the use of change scores has raised much controversy. In this article, from a multilevel perspective, we provide a structured treatise on several persistent negative beliefs about change scores and show that these beliefs originated from the confounding of the effects of within-person change on change-score reliability and between-person change differences. We argue that psychometric properties of change scores, such as reliability and measurement precision, should be treated at suitable levels within a multilevel framework. We show that, if examined at the suitable levels with such a framework, the negative beliefs about change scores can be renounced convincingly. Finally, we summarize the conclusions about change scores to dispel the myths and to promote the potential and practical usefulness of change scores.

“Rebuilding our community”: Hearing silenced voices on Aboriginal youth suicide

PubMed Central

Walls, Melissa L.; Hautala, Dane; Hurley, Jenna

2014-01-01

This paper brings forth the voices of adult Aboriginal First Nations community members who gathered in focus groups to discuss the problem of youth suicide on their reserves. Our approach emphasizes multilevel (e.g., individual, family, and broader ecological systems) factors viewed by participants as relevant to youth suicide. Wheaton’s conceptualization of stressors (1994; 1999) and Evans-Campbell’s (2008) multilevel classification of the impacts of historical trauma are used as theoretical and analytic guides. Thematic analysis of qualitative data transcripts revealed a highly complex intersection of stressors, traumas, and social problems seen by community members as underlying mechanisms influencing heightened levels of Aboriginal youth suicidality. Our multilevel coding approach revealed that suicidal behaviors were described by community members largely as a problem with deep historical and contemporary structural roots as opposed to being viewed as individualized pathology. PMID:24097414

Updated User's Guide for Sammy: Multilevel R-Matrix Fits to Neutron Data Using Bayes' Equations

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

Larson, Nancy M

2008-10-01

In 1980 the multilevel multichannel R-matrix code SAMMY was released for use in analysis of neutron-induced cross section data at the Oak Ridge Electron Linear Accelerator. Since that time, SAMMY has evolved to the point where it is now in use around the world for analysis of many different types of data. SAMMY is not limited to incident neutrons but can also be used for incident protons, alpha particles, or other charged particles; likewise, Coulomb exit hannels can be included. Corrections for a wide variety of experimental conditions are available in the code: Doppler and resolution broadening, multiple-scattering corrections formore » capture or reaction yields, normalizations and backgrounds, to name but a few. The fitting procedure is Bayes' method, and data and parameter covariance matrices are properly treated within the code. Pre- and post-processing capabilities are also available, including (but not limited to) connections with the Evaluated Nuclear Data Files. Though originally designed for use in the resolved resonance region, SAMMY also includes a treatment for data analysis in the unresolved resonance region.« less

Student Perceptions of Classroom Achievement Goal Structure: Is It Appropriate to Aggregate?

ERIC Educational Resources Information Center

Lam, Arena C.; Ruzek, Erik A.; Schenke, Katerina; Conley, AnneMarie M.; Karabenick, Stuart A.

2015-01-01

Student reports are a common approach to characterizing how students experience their classrooms. We used a recently developed method--multilevel confirmatory factor analysis--to determine whether commonly employed measures of achievement goal structure constructs (mastery and performance) typically verified at the student level can be verified at…

The Structure of Women's Employment in Comparative Perspective

ERIC Educational Resources Information Center

Pettit, Becky; Hook, Jennifer Lynn

2005-01-01

In this paper we analyze social survey data from 19 countries using multi-level modeling methods in an effort to synthesize structural and institutional accounts for variation in women's employment. Observed demographic characteristics show much consistency in their relationship to women's employment across countries, yet there is significant…

Final Report - Subcontract B623760

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

Bank, R.

2017-11-17

During my visit to LLNL during July 17{27, 2017, I worked on linear system solvers. The two level hierarchical solver that initiated our study was developed to solve linear systems arising from hp adaptive finite element calculations, and is implemented in the PLTMG software package, version 12. This preconditioner typically requires 3-20% of the space used by the stiffness matrix for higher order elements. It has multigrid like convergence rates for a wide variety of PDEs (self-adjoint positive de nite elliptic equations, convection dominated convection-diffusion equations, and highly indefinite Helmholtz equations, among others). The convergence rate is not independent ofmore » the polynomial degree p as p ! 1, but but remains strong for p 9, which is the highest polynomial degree allowed in PLTMG, due to limitations of the numerical quadrature rules implemented in the software package. A more complete description of the method and some numerical experiments illustrating its effectiveness appear in. Like traditional geometric multilevel methods, this scheme relies on knowledge of the underlying finite element space in order to construct the smoother and the coarse grid correction.« less

The solution of radiative transfer problems in molecular bands without the LTE assumption by accelerated lambda iteration methods

NASA Technical Reports Server (NTRS)

Kutepov, A. A.; Kunze, D.; Hummer, D. G.; Rybicki, G. B.

1991-01-01

An iterative method based on the use of approximate transfer operators, which was designed initially to solve multilevel NLTE line formation problems in stellar atmospheres, is adapted and applied to the solution of the NLTE molecular band radiative transfer in planetary atmospheres. The matrices to be constructed and inverted are much smaller than those used in the traditional Curtis matrix technique, which makes possible the treatment of more realistic problems using relatively small computers. This technique converges much more rapidly than straightforward iteration between the transfer equation and the equations of statistical equilibrium. A test application of this new technique to the solution of NLTE radiative transfer problems for optically thick and thin bands (the 4.3 micron CO2 band in the Venusian atmosphere and the 4.7 and 2.3 micron CO bands in the earth's atmosphere) is described.

Parallel multigrid smoothing: polynomial versus Gauss-Seidel

NASA Astrophysics Data System (ADS)

Adams, Mark; Brezina, Marian; Hu, Jonathan; Tuminaro, Ray

2003-07-01

Gauss-Seidel is often the smoother of choice within multigrid applications. In the context of unstructured meshes, however, maintaining good parallel efficiency is difficult with multiplicative iterative methods such as Gauss-Seidel. This leads us to consider alternative smoothers. We discuss the computational advantages of polynomial smoothers within parallel multigrid algorithms for positive definite symmetric systems. Two particular polynomials are considered: Chebyshev and a multilevel specific polynomial. The advantages of polynomial smoothing over traditional smoothers such as Gauss-Seidel are illustrated on several applications: Poisson's equation, thin-body elasticity, and eddy current approximations to Maxwell's equations. While parallelizing the Gauss-Seidel method typically involves a compromise between a scalable convergence rate and maintaining high flop rates, polynomial smoothers achieve parallel scalable multigrid convergence rates without sacrificing flop rates. We show that, although parallel computers are the main motivation, polynomial smoothers are often surprisingly competitive with Gauss-Seidel smoothers on serial machines.

Innovative Composite Structure Design for Blast Protection

DTIC Science & Technology

2007-01-01

2007-01-0483 Innovative Composite Structure Design for Blast Protection Dongying Jiang, Yuanyuan Liu MKP Structural Design Associates, Inc...protect vehicle and occupants against various explosives. The multi-level and multi-scenario blast simulation and design system integrates three major...numerical simulation of a BTR composite under a blast event. The developed blast simulation and design system will enable the prediction, design, and

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,…

Individual-level socioeconomic status and community-level inequality as determinants of stigma towards persons living with HIV who inject drugs in Thai Nguyen, Vietnam.

PubMed

Lim, Travis; Zelaya, Carla; Latkin, Carl; Quan, Vu Minh; Frangakis, Constantine; Ha, Tran Viet; Minh, Nguyen Le; Go, Vivian

2013-11-13

HIV infection may be affected by multiple complex socioeconomic status (SES) factors, especially individual socioeconomic disadvantage and community-level inequality. At the same time, stigma towards HIV and marginalized groups has exacerbated persistent concentrated epidemics among key populations, such as persons who inject drugs (PWID) in Vietnam. Stigma researchers argue that stigma fundamentally depends on the existence of economic power differences in a community. In rapidly growing economies like Vietnam, the increasing gap in income and education levels, as well as an individual's absolute income and education, may create social conditions that facilitate stigma related to injecting drug use and HIV. A cross-sectional baseline survey assessing different types of stigma and key socioeconomic characteristics was administered to 1674 PWID and 1349 community members living in physical proximity throughout the 32 communes in Thai Nguyen province, Vietnam. We created four stigma scales, including HIV-related and drug-related stigma reported by both PWID and community members. We then used ecologic Spearman's correlation, ordinary least-squares regression and multi-level generalized estimating equations to examine community-level inequality associations, individual-level SES associations and multi-level SES associations with different types of stigma, respectively. There was little urban-rural difference in stigma among communes. Higher income inequality was marginally associated with drug-related stigma reported by community members (p=0.087), and higher education inequality was significantly associated with higher HIV-related stigma reported by both PWID and community members (p<0.05). For individuals, higher education was significantly associated with lower stigma (HIV and drug related) reported by both PWID and community members. Part-time employed PWID reported more experiences and perceptions of drug-related stigma, while conversely unemployed community members reported enacting lower drug-related stigma. Multi-level analysis revealed that the relationship between education inequality and HIV-related stigma is superseded by the effect of individual-level education. The results of the study confirm that socioeconomic factors at both the individual level and community level affect different types of stigma in different ways. Attention should be paid to these differences when planning structural or educational interventions to reduce stigma, and additional research should investigate the mechanisms with which SES and inequality affect social relationships and, in turn, stigma.

Individual-level socioeconomic status and community-level inequality as determinants of stigma towards persons living with HIV who inject drugs in Thai Nguyen, Vietnam

PubMed Central

Lim, Travis; Zelaya, Carla; Latkin, Carl; Quan, Vu Minh; Frangakis, Constantine; Ha, Tran Viet; Minh, Nguyen Le; Go, Vivian

2013-01-01

Introduction HIV infection may be affected by multiple complex socioeconomic status (SES) factors, especially individual socioeconomic disadvantage and community-level inequality. At the same time, stigma towards HIV and marginalized groups has exacerbated persistent concentrated epidemics among key populations, such as persons who inject drugs (PWID) in Vietnam. Stigma researchers argue that stigma fundamentally depends on the existence of economic power differences in a community. In rapidly growing economies like Vietnam, the increasing gap in income and education levels, as well as an individual's absolute income and education, may create social conditions that facilitate stigma related to injecting drug use and HIV. Methods A cross-sectional baseline survey assessing different types of stigma and key socioeconomic characteristics was administered to 1674 PWID and 1349 community members living in physical proximity throughout the 32 communes in Thai Nguyen province, Vietnam. We created four stigma scales, including HIV-related and drug-related stigma reported by both PWID and community members. We then used ecologic Spearman's correlation, ordinary least-squares regression and multi-level generalized estimating equations to examine community-level inequality associations, individual-level SES associations and multi-level SES associations with different types of stigma, respectively. Results There was little urban–rural difference in stigma among communes. Higher income inequality was marginally associated with drug-related stigma reported by community members (p=0.087), and higher education inequality was significantly associated with higher HIV-related stigma reported by both PWID and community members (p<0.05). For individuals, higher education was significantly associated with lower stigma (HIV and drug related) reported by both PWID and community members. Part-time employed PWID reported more experiences and perceptions of drug-related stigma, while conversely unemployed community members reported enacting lower drug-related stigma. Multi-level analysis revealed that the relationship between education inequality and HIV-related stigma is superseded by the effect of individual-level education. Conclusions The results of the study confirm that socioeconomic factors at both the individual level and community level affect different types of stigma in different ways. Attention should be paid to these differences when planning structural or educational interventions to reduce stigma, and additional research should investigate the mechanisms with which SES and inequality affect social relationships and, in turn, stigma. PMID:24242257

Development of an efficient multigrid method for the NEM form of the multigroup neutron diffusion equation

NASA Astrophysics Data System (ADS)

Al-Chalabi, Rifat M. Khalil

1997-09-01

Development of an improvement to the computational efficiency of the existing nested iterative solution strategy of the Nodal Exapansion Method (NEM) nodal based neutron diffusion code NESTLE is presented. The improvement in the solution strategy is the result of developing a multilevel acceleration scheme that does not suffer from the numerical stalling associated with a number of iterative solution methods. The acceleration scheme is based on the multigrid method, which is specifically adapted for incorporation into the NEM nonlinear iterative strategy. This scheme optimizes the computational interplay between the spatial discretization and the NEM nonlinear iterative solution process through the use of the multigrid method. The combination of the NEM nodal method, calculation of the homogenized, neutron nodal balance coefficients (i.e. restriction operator), efficient underlying smoothing algorithm (power method of NESTLE), and the finer mesh reconstruction algorithm (i.e. prolongation operator), all operating on a sequence of coarser spatial nodes, constitutes the multilevel acceleration scheme employed in this research. Two implementations of the multigrid method into the NESTLE code were examined; the Imbedded NEM Strategy and the Imbedded CMFD Strategy. The main difference in implementation between the two methods is that in the Imbedded NEM Strategy, the NEM solution is required at every MG level. Numerical tests have shown that the Imbedded NEM Strategy suffers from divergence at coarse- grid levels, hence all the results for the different benchmarks presented here were obtained using the Imbedded CMFD Strategy. The novelties in the developed MG method are as follows: the formulation of the restriction and prolongation operators, and the selection of the relaxation method. The restriction operator utilizes a variation of the reactor physics, consistent homogenization technique. The prolongation operator is based upon a variant of the pin power reconstruction methodology. The relaxation method, which is the power method, utilizes a constant coefficient matrix within the NEM non-linear iterative strategy. The choice of the MG nesting within the nested iterative strategy enables the incorporation of other non-linear effects with no additional coding effort. In addition, if an eigenvalue problem is being solved, it remains an eigenvalue problem at all grid levels, simplifying coding implementation. The merit of the developed MG method was tested by incorporating it into the NESTLE iterative solver, and employing it to solve four different benchmark problems. In addition to the base cases, three different sensitivity studies are performed, examining the effects of number of MG levels, homogenized coupling coefficients correction (i.e. restriction operator), and fine-mesh reconstruction algorithm (i.e. prolongation operator). The multilevel acceleration scheme developed in this research provides the foundation for developing adaptive multilevel acceleration methods for steady-state and transient NEM nodal neutron diffusion equations. (Abstract shortened by UMI.)

Integrated structure/control design - Present methodology and future opportunities

NASA Technical Reports Server (NTRS)

Weisshaar, T. A.; Newsom, J. R.; Zeiler, T. A.; Gilbert, M. G.

1986-01-01

Attention is given to current methodology applied to the integration of the optimal design process for structures and controls. Multilevel linear decomposition techniques proved to be most effective in organizing the computational efforts necessary for ISCD (integrated structures and control design) tasks. With the development of large orbiting space structures and actively controlled, high performance aircraft, there will be more situations in which this concept can be applied.

The Impact of Partial Measurement Invariance on Testing Moderation for Single and Multi-Level Data

PubMed Central

Hsiao, Yu-Yu; Lai, Mark H. C.

2018-01-01

Moderation effect is a commonly used concept in the field of social and behavioral science. Several studies regarding the implication of moderation effects have been done; however, little is known about how partial measurement invariance influences the properties of tests for moderation effects when categorical moderators were used. Additionally, whether the impact is the same across single and multilevel data is still unknown. Hence, the purpose of the present study is twofold: (a) To investigate the performance of the moderation test in single-level studies when measurement invariance does not hold; (b) To examine whether unique features of multilevel data, such as intraclass correlation (ICC) and number of clusters, influence the effect of measurement non-invariance on the performance of tests for moderation. Simulation results indicated that falsely assuming measurement invariance lead to biased estimates, inflated Type I error rates, and more gain or more loss in power (depends on simulation conditions) for the test of moderation effects. Such patterns were more salient as sample size and the number of non-invariant items increase for both single- and multi-level data. With multilevel data, the cluster size seemed to have a larger impact than the number of clusters when falsely assuming measurement invariance in the moderation estimation. ICC was trivially related to the moderation estimates. Overall, when testing moderation effects with categorical moderators, employing a model that accounts for the measurement (non)invariance structure of the predictor and/or the outcome is recommended. PMID:29867692

The Impact of Partial Measurement Invariance on Testing Moderation for Single and Multi-Level Data.

PubMed

Hsiao, Yu-Yu; Lai, Mark H C

2018-01-01

Moderation effect is a commonly used concept in the field of social and behavioral science. Several studies regarding the implication of moderation effects have been done; however, little is known about how partial measurement invariance influences the properties of tests for moderation effects when categorical moderators were used. Additionally, whether the impact is the same across single and multilevel data is still unknown. Hence, the purpose of the present study is twofold: (a) To investigate the performance of the moderation test in single-level studies when measurement invariance does not hold; (b) To examine whether unique features of multilevel data, such as intraclass correlation (ICC) and number of clusters, influence the effect of measurement non-invariance on the performance of tests for moderation. Simulation results indicated that falsely assuming measurement invariance lead to biased estimates, inflated Type I error rates, and more gain or more loss in power (depends on simulation conditions) for the test of moderation effects. Such patterns were more salient as sample size and the number of non-invariant items increase for both single- and multi-level data. With multilevel data, the cluster size seemed to have a larger impact than the number of clusters when falsely assuming measurement invariance in the moderation estimation. ICC was trivially related to the moderation estimates. Overall, when testing moderation effects with categorical moderators, employing a model that accounts for the measurement (non)invariance structure of the predictor and/or the outcome is recommended.

Interdisciplinary optimum design. [of aerospace structures

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, Jaroslaw; Haftka, Raphael T.

1986-01-01

Problems related to interdisciplinary interactions in the design of a complex engineering systems are examined with reference to aerospace applications. The interdisciplinary optimization problems examined include those dealing with controls and structures, materials and structures, control and stability, structure and aerodynamics, and structure and thermodynamics. The discussion is illustrated by the following specific applications: integrated aerodynamic/structural optimization of glider wing; optimization of an antenna parabolic dish structure for minimum weight and prescribed emitted signal gain; and a multilevel optimization study of a transport aircraft.

Cantilevered multilevel LIGA devices and methods

DOEpatents

Morales, Alfredo Martin; Domeier, Linda A.

2002-01-01

In the formation of multilevel LIGA microstructures, a preformed sheet of photoresist material, such as polymethylmethacrylate (PMMA) is patterned by exposure through a mask to radiation, such as X-rays, and developed using a developer to remove the exposed photoresist material. A first microstructure is then formed by electroplating metal into the areas from which the photoresist has been removed. Additional levels of microstructure are added to the initial microstructure by covering the first microstructure with a conductive polymer, machining the conductive polymer layer to reveal the surface of the first microstructure, sealing the conductive polymer and surface of the first microstructure with a metal layer, and then forming the second level of structure on top of the first level structure. In such a manner, multiple layers of microstructure can be built up to allow complex cantilevered microstructures to be formed.

A Model of Adding Relations in Multi-levels to a Formal Organization Structure with Two Subordinates

NASA Astrophysics Data System (ADS)

Sawada, Kiyoshi; Amano, Kazuyuki

2009-10-01

This paper proposes a model of adding relations in multi-levels to a formal organization structure with two subordinates such that the communication of information between every member in the organization becomes the most efficient. When edges between every pair of nodes with the same depth in L (L = 1, 2, …, H) levels are added to a complete binary tree of height H, an optimal set of depths {N1, N2, …, NL} (H⩾N1>N2> …>NL⩾1) is obtained by maximizing the total shortening path length which is the sum of shortening lengths of shortest paths between every pair of all nodes in the complete binary tree. It is shown that {N1, N2, …, NL}* = {H, H-1, …, H-L+1}.

A mixed integer bi-level DEA model for bank branch performance evaluation by Stackelberg approach

NASA Astrophysics Data System (ADS)

Shafiee, Morteza; Lotfi, Farhad Hosseinzadeh; Saleh, Hilda; Ghaderi, Mehdi

2016-03-01

One of the most complicated decision making problems for managers is the evaluation of bank performance, which involves various criteria. There are many studies about bank efficiency evaluation by network DEA in the literature review. These studies do not focus on multi-level network. Wu (Eur J Oper Res 207:856-864, 2010) proposed a bi-level structure for cost efficiency at the first time. In this model, multi-level programming and cost efficiency were used. He used a nonlinear programming to solve the model. In this paper, we have focused on multi-level structure and proposed a bi-level DEA model. We then used a liner programming to solve our model. In other hand, we significantly improved the way to achieve the optimum solution in comparison with the work by Wu (2010) by converting the NP-hard nonlinear programing into a mixed integer linear programming. This study uses a bi-level programming data envelopment analysis model that embodies internal structure with Stackelberg-game relationships to evaluate the performance of banking chain. The perspective of decentralized decisions is taken in this paper to cope with complex interactions in banking chain. The results derived from bi-level programming DEA can provide valuable insights and detailed information for managers to help them evaluate the performance of the banking chain as a whole using Stackelberg-game relationships. Finally, this model was applied in the Iranian bank to evaluate cost efficiency.

Multilevel social structure and diet shape the gut microbiota of the gelada monkey, the only grazing primate.

PubMed

Trosvik, Pål; de Muinck, Eric J; Rueness, Eli K; Fashing, Peter J; Beierschmitt, Evan C; Callingham, Kadie R; Kraus, Jacob B; Trew, Thomas H; Moges, Amera; Mekonnen, Addisu; Venkataraman, Vivek V; Nguyen, Nga

2018-05-05

The gelada monkey (Theropithecus gelada), endemic to the Ethiopian highlands, is the only graminivorous primate, i.e., it feeds mainly on grasses and sedges. In spite of known dental, manual, and locomotor adaptations, the intestinal anatomy of geladas is similar to that of other primates. We currently lack a clear understanding of the adaptations in digestive physiology necessary for this species to subsist on a graminoid-based diet, but digestion in other graminivores, such as ruminants, relies heavily on the microbial community residing in the gastrointestinal (GI) system. Furthermore, geladas form complex, multilevel societies, making them a suitable system for investigating links between sociality and the GI microbiota. Here, we explore the gastrointestinal microbiota of gelada monkeys inhabiting an intact ecosystem and document how factors like multilevel social structure and seasonal changes in diet shape the GI microbiota. We compare the gelada GI microbiota to those of other primate species, reporting a gradient from geladas to herbivorous specialist monkeys to dietary generalist monkeys and lastly humans, the ultimate ecological generalists. We also compare the microbiotas of the gelada GI tract and the sheep rumen, finding that geladas are highly enriched for cellulolytic bacteria associated with ruminant digestion, relative to other primates. This study represents the first analysis of the gelada GI microbiota, providing insights into the adaptations underlying graminivory in a primate. Our results also highlight the role of social organization in structuring the GI microbiota within a society of wild animals.

3D Multi-Level Non-LTE Radiative Transfer for the CO Molecule

NASA Astrophysics Data System (ADS)

Berkner, A.; Schweitzer, A.; Hauschildt, P. H.

2015-01-01

The photospheres of cool stars are both rich in molecules and an environment where the assumption of LTE can not be upheld under all circumstances. Unfortunately, detailed 3D non-LTE calculations involving molecules are hardly feasible with current computers. For this reason, we present our implementation of the super level technique, in which molecular levels are combined into super levels, to reduce the number of unknowns in the rate equations and, thus, the computational effort and memory requirements involved, and show the results of our first tests against the 1D implementation of the same method.

Fully implicit moving mesh adaptive algorithm

NASA Astrophysics Data System (ADS)

Chacon, Luis

2005-10-01

In many problems of interest, the numerical modeler is faced with the challenge of dealing with multiple time and length scales. The former is best dealt with with fully implicit methods, which are able to step over fast frequencies to resolve the dynamical time scale of interest. The latter requires grid adaptivity for efficiency. Moving-mesh grid adaptive methods are attractive because they can be designed to minimize the numerical error for a given resolution. However, the required grid governing equations are typically very nonlinear and stiff, and of considerably difficult numerical treatment. Not surprisingly, fully coupled, implicit approaches where the grid and the physics equations are solved simultaneously are rare in the literature, and circumscribed to 1D geometries. In this study, we present a fully implicit algorithm for moving mesh methods that is feasible for multidimensional geometries. A crucial element is the development of an effective multilevel treatment of the grid equation.ootnotetextL. Chac'on, G. Lapenta, A fully implicit, nonlinear adaptive grid strategy, J. Comput. Phys., accepted (2005) We will show that such an approach is competitive vs. uniform grids both from the accuracy (due to adaptivity) and the efficiency standpoints. Results for a variety of models 1D and 2D geometries, including nonlinear diffusion, radiation-diffusion, Burgers equation, and gas dynamics will be presented.

Model Selection with the Linear Mixed Model for Longitudinal Data

ERIC Educational Resources Information Center

Ryoo, Ji Hoon

2011-01-01

Model building or model selection with linear mixed models (LMMs) is complicated by the presence of both fixed effects and random effects. The fixed effects structure and random effects structure are codependent, so selection of one influences the other. Most presentations of LMM in psychology and education are based on a multilevel or…

Micro structure processing on plastics by accelerated hydrogen molecular ions

NASA Astrophysics Data System (ADS)

Hayashi, H.; Hayakawa, S.; Nishikawa, H.

2017-08-01

A proton has 1836 times the mass of an electron and is the lightest nucleus to be used for accelerator in material modification. We can setup accelerator with the lowest acceleration voltage. It is preferable characteristics of Proton Beam Writer (PBW) for industrial applications. On the contrary ;proton; has the lowest charge among all nuclei and the potential impact to material is lowest. The object of this research is to improve productivity of the PBW for industry application focusing on hydrogen molecular ions. These ions are generated in the same ion source by ionizing hydrogen molecule. There is no specific ion source requested and it is suitable for industrial use. We demonstrated three dimensional (3D) multilevel micro structures on polyester base FPC (Flexible Printed Circuits) using proton, H2+ and H3+. The reactivity of hydrogen molecular ions is much higher than that of proton and coincident with the level of expectation. We can apply this result to make micro devices of 3D multilevel structures on FPC.

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.

Multilevel Models for Intensive Longitudinal Data with Heterogeneous Autoregressive Errors: The Effect of Misspecification and Correction with Cholesky Transformation

PubMed Central

Jahng, Seungmin; Wood, Phillip K.

2017-01-01

Intensive longitudinal studies, such as ecological momentary assessment studies using electronic diaries, are gaining popularity across many areas of psychology. Multilevel models (MLMs) are most widely used analytical tools for intensive longitudinal data (ILD). Although ILD often have individually distinct patterns of serial correlation of measures over time, inferences of the fixed effects, and random components in MLMs are made under the assumption that all variance and autocovariance components are homogenous across individuals. In the present study, we introduced a multilevel model with Cholesky transformation to model ILD with individually heterogeneous covariance structure. In addition, the performance of the transformation method and the effects of misspecification of heterogeneous covariance structure were investigated through a Monte Carlo simulation. We found that, if individually heterogeneous covariances are incorrectly assumed as homogenous independent or homogenous autoregressive, MLMs produce highly biased estimates of the variance of random intercepts and the standard errors of the fixed intercept and the fixed effect of a level 2 covariate when the average autocorrelation is high. For intensive longitudinal data with individual specific residual covariance, the suggested transformation method showed lower bias in those estimates than the misspecified models when the number of repeated observations within individuals is 50 or more. PMID:28286490

Within-Year Changes of Lesson Structure: An Exploration of Pedagogical Functions of Lessons by Means of Multilevel Growth Curve Modelling in Indonesia

ERIC Educational Resources Information Center

Maulana, Ridwan; Opdenakker, Marie-Christine; den Brok, Perry

2015-01-01

Teaching is undoubtedly complex and the complexity of classroom practice implies that the structure of lessons making up teaching may differ and subject to change over time. The aims of this study were to investigate changes in observed lesson structure, and explore the effects of several teacher and contextual characteristics on differences in…

Migration and HIV prevention programmes: linking structural factors, culture, and individual behaviour--an Israeli experience.

PubMed

Soskolne, Varda; Shtarkshall, Ronny A

2002-10-01

Migration is one of the structural factors associated with HIV infections, but the dynamic and complex role of migrant situations as determinants of HIV-related vulnerability is still a major issue for social science research. Moreover, interventions to address the specific structural and contextual factors inherent in this association are limited and many do not take into account the cultural components. This paper presents a multi-level framework for analysis of the links between migration and HIV. It includes the association of migration with structural macro factors-lower socio-economic status and limited power in the new society; intermediate structural factors-limited social capital and bi-directional interaction of cultural norms; and individual-level factors-stressors unique to the migration context, depleted psychosocial resources, loss of cultural beliefs and low use of health services. All these factors affect risky sexual behaviour and transmission of HIV. The paper utilises those elements of the framework that are relevant to the specific needs of immigrant populations from the former Soviet Union and from Ethiopia in Israel. We demonstrate their application to integrated, multi-level HIV prevention interventions and propose several special principles for development of migration-related HIV prevention programmes.

Detection and localization of damage using empirical mode decomposition and multilevel support vector machine

NASA Astrophysics Data System (ADS)

Dushyanth, N. D.; Suma, M. N.; Latte, Mrityanjaya V.

2016-03-01

Damage in the structure may raise a significant amount of maintenance cost and serious safety problems. Hence detection of the damage at its early stage is of prime importance. The main contribution pursued in this investigation is to propose a generic optimal methodology to improve the accuracy of positioning of the flaw in a structure. This novel approach involves a two-step process. The first step essentially aims at extracting the damage-sensitive features from the received signal, and these extracted features are often termed the damage index or damage indices, serving as an indicator to know whether the damage is present or not. In particular, a multilevel SVM (support vector machine) plays a vital role in the distinction of faulty and healthy structures. Formerly, when a structure is unveiled as a damaged structure, in the subsequent step, the position of the damage is identified using Hilbert-Huang transform. The proposed algorithm has been evaluated in both simulation and experimental tests on a 6061 aluminum plate with dimensions 300 mm × 300 mm × 5 mm which accordingly yield considerable improvement in the accuracy of estimating the position of the flaw.

Multilevel Spatial Structure Impacts on the Pollination Services of Comarum palustre (Rosaceae)

PubMed Central

Somme, Laurent; Mayer, Carolin; Jacquemart, Anne-Laure

2014-01-01

Habitat destruction and fragmentation accelerate pollinator decline, consequently disrupting ecosystem processes such as pollination. To date, the impacts of multilevel spatial structure on pollination services have rarely been addressed. We focused on the effects of population spatial structure on the pollination services of Comarum palustre at three levels (i.e. within-population, between-populations and landscape). For three years, we investigated 14 Belgian populations, which differed in their within-population flower density, population surface, closure (i.e. proportion of the population edge that consisted of woody elements) and isolation (i.e. percentage of woody area cover within a 500 m radius from the population centre). We tested whether these spatial characteristics impact on pollinator abundance and visitation rate and thus, reproductive success of C. palustre. Insects were observed in 15 randomly-chosen plots in each population. We tested for pollen limitation with supplemental hand-cross pollination. Bumble bees and solitary bees were the major pollinators through all populations. Within populations, plots with high flower densities attracted high numbers of bumble bees and other insects. High bumble bee and solitary bee abundance was observed in populations presenting high proportions of woody edges and in populations within landscapes presenting high proportions of woody areas. Seed set resulting from open pollination varied with bumble bee and solitary bee visitation rate, leading to increased pollen limitation when pollinators were scarce. Since the reproductive success depended on the visitation rate of the main pollinators, which depended on multilevel spatial structure, wetland management plans should pay special attention to favour a mosaic of biotopes, including nesting sites and food resources for insects. This study particularly supports the relevance of a mix wetlands and woody habitats to bees. PMID:24915450

Multilevel spatial structure impacts on the pollination services of Comarum palustre (Rosaceae).

PubMed

Somme, Laurent; Mayer, Carolin; Jacquemart, Anne-Laure

2014-01-01

Habitat destruction and fragmentation accelerate pollinator decline, consequently disrupting ecosystem processes such as pollination. To date, the impacts of multilevel spatial structure on pollination services have rarely been addressed. We focused on the effects of population spatial structure on the pollination services of Comarum palustre at three levels (i.e. within-population, between-populations and landscape). For three years, we investigated 14 Belgian populations, which differed in their within-population flower density, population surface, closure (i.e. proportion of the population edge that consisted of woody elements) and isolation (i.e. percentage of woody area cover within a 500 m radius from the population centre). We tested whether these spatial characteristics impact on pollinator abundance and visitation rate and thus, reproductive success of C. palustre. Insects were observed in 15 randomly-chosen plots in each population. We tested for pollen limitation with supplemental hand-cross pollination. Bumble bees and solitary bees were the major pollinators through all populations. Within populations, plots with high flower densities attracted high numbers of bumble bees and other insects. High bumble bee and solitary bee abundance was observed in populations presenting high proportions of woody edges and in populations within landscapes presenting high proportions of woody areas. Seed set resulting from open pollination varied with bumble bee and solitary bee visitation rate, leading to increased pollen limitation when pollinators were scarce. Since the reproductive success depended on the visitation rate of the main pollinators, which depended on multilevel spatial structure, wetland management plans should pay special attention to favour a mosaic of biotopes, including nesting sites and food resources for insects. This study particularly supports the relevance of a mix wetlands and woody habitats to bees.

Multilevel Optimization Framework for Hierarchical Stiffened Shells Accelerated by Adaptive Equivalent Strategy

NASA Astrophysics Data System (ADS)

Wang, Bo; Tian, Kuo; Zhao, Haixin; Hao, Peng; Zhu, Tianyu; Zhang, Ke; Ma, Yunlong

2017-06-01

In order to improve the post-buckling optimization efficiency of hierarchical stiffened shells, a multilevel optimization framework accelerated by adaptive equivalent strategy is presented in this paper. Firstly, the Numerical-based Smeared Stiffener Method (NSSM) for hierarchical stiffened shells is derived by means of the numerical implementation of asymptotic homogenization (NIAH) method. Based on the NSSM, a reasonable adaptive equivalent strategy for hierarchical stiffened shells is developed from the concept of hierarchy reduction. Its core idea is to self-adaptively decide which hierarchy of the structure should be equivalent according to the critical buckling mode rapidly predicted by NSSM. Compared with the detailed model, the high prediction accuracy and efficiency of the proposed model is highlighted. On the basis of this adaptive equivalent model, a multilevel optimization framework is then established by decomposing the complex entire optimization process into major-stiffener-level and minor-stiffener-level sub-optimizations, during which Fixed Point Iteration (FPI) is employed to accelerate convergence. Finally, the illustrative examples of the multilevel framework is carried out to demonstrate its efficiency and effectiveness to search for the global optimum result by contrast with the single-level optimization method. Remarkably, the high efficiency and flexibility of the adaptive equivalent strategy is indicated by compared with the single equivalent strategy.

Soft-assembled Multilevel Dynamics of Tactical Behaviors in Soccer

PubMed Central

Ric, Angel; Torrents, Carlota; Gonçalves, Bruno; Sampaio, Jaime; Hristovski, Robert

2016-01-01

This study aimed to identify the tactical patterns and the timescales of variables during a soccer match, allowing understanding the multilevel organization of tactical behaviors, and to determine the similarity of patterns performed by different groups of teammates during the first and second halves. Positional data from 20 professional male soccer players from the same team were collected using high frequency global positioning systems (5 Hz). Twenty-nine categories of tactical behaviors were determined from eight positioning-derived variables creating multivariate binary (Boolean) time-series matrices. Hierarchical principal component analysis (PCA) was used to identify the multilevel structure of tactical behaviors. The sequential reduction of each set level of principal components revealed a sole principal component as the slowest collective variable, forming the global basin of attraction of tactical patterns during each half of the match. In addition, the mean dwell time of each positioning-derived variable helped to understand the multilevel organization of collective tactical behavior during a soccer match. This approach warrants further investigations to analyze the influence of task constraints on the emergence of tactical behavior. Furthermore, PCA can help coaches to design representative training tasks according to those tactical patterns captured during match competitions and to compare them depending on situational variables. PMID:27761120

Simultaneous observations of electromagnetically induced transparency (EIT) and absorption (EIA) in a multi-level V-type system of 87Rb and theoretical simulation of the observed spectra using a multi-mode approach

NASA Astrophysics Data System (ADS)

Das, Bankim Chandra; Bhattacharyya, Dipankar; Das, Arpita; Chakrabarti, Shrabana; De, Sankar

2016-12-01

We report here simultaneous experimental observation of Electromagnetically Induced Transparency (EIT) and Electromagnetically Induced Absorption (EIA) in a multi-level V-type system in D2 transition of 87Rb, i.e., F =2 →F' with a strong pump and a weak probe beam. We studied the probe spectrum by locking the probe beam to the transition F =2 →F'=2 while the pump is scanned from F =2 →F' . EIA is observed for the open transition (F =2 →F'=2 ) whereas EIT is observed in the closed transition (F =2 →F'=3 ). Sub natural line-width is observed for the EIA. To simulate the observed spectra theoretically, Liouville equation for the three-level V-type system is solved analytically with a multi-mode approach for the density matrix elements. We assumed both the pump and the probe beams can couple the excited states. A multi-mode approach for the coherence terms facilitates the study of all the frequency contributions due to the pump and the probe fields. Since the terms contain higher harmonics of the pump and the probe frequencies, we expressed them in Fourier transformed forms. To simulate the probe spectrum, we have solved inhomogeneous difference equations for the coherence terms using the Green's function technique and continued fraction theory. The experimental line-widths of the EIT and the EIA are compared with our theoretical model. Our system can be useful in optical switching applications as it can be precisely tuned to render the medium opaque and transparent simultaneously.

Simultaneous observations of electromagnetically induced transparency (EIT) and absorption (EIA) in a multi-level V-type system of 87Rb and theoretical simulation of the observed spectra using a multi-mode approach.

PubMed

Das, Bankim Chandra; Bhattacharyya, Dipankar; Das, Arpita; Chakrabarti, Shrabana; De, Sankar

2016-12-14

We report here simultaneous experimental observation of Electromagnetically Induced Transparency (EIT) and Electromagnetically Induced Absorption (EIA) in a multi-level V-type system in D 2 transition of Rb87, i.e., F=2→F ' with a strong pump and a weak probe beam. We studied the probe spectrum by locking the probe beam to the transition F=2→F ' =2 while the pump is scanned from F=2→F ' . EIA is observed for the open transition (F=2→F ' =2) whereas EIT is observed in the closed transition (F=2→F ' =3). Sub natural line-width is observed for the EIA. To simulate the observed spectra theoretically, Liouville equation for the three-level V-type system is solved analytically with a multi-mode approach for the density matrix elements. We assumed both the pump and the probe beams can couple the excited states. A multi-mode approach for the coherence terms facilitates the study of all the frequency contributions due to the pump and the probe fields. Since the terms contain higher harmonics of the pump and the probe frequencies, we expressed them in Fourier transformed forms. To simulate the probe spectrum, we have solved inhomogeneous difference equations for the coherence terms using the Green's function technique and continued fraction theory. The experimental line-widths of the EIT and the EIA are compared with our theoretical model. Our system can be useful in optical switching applications as it can be precisely tuned to render the medium opaque and transparent simultaneously.

Family Structure and Child Mortality in Sub-Saharan Africa: Cross-National Effects of Polygyny

ERIC Educational Resources Information Center

Omariba, D. Walter Rasugu; Boyle, Michael H.

2007-01-01

This study applies multilevel logistic regression to Demographic and Health Survey data from 22 sub-Saharan African countries to examine whether the relationship between child mortality and family structure, with a specific emphasis on polygyny, varies cross-nationally and over time. Hypotheses were developed on the basis of competing theories on…

Multilevel Factor Structure and Concurrent Validity of the Teacher Version of the Authoritative School Climate Survey

ERIC Educational Resources Information Center

Huang, Francis L.; Cornell, Dewey G.; Konold, Timothy; Meyer, Joseph P.; Lacey, Anna; Nekvasil, Erin K.; Heilbrun, Anna; Shukla, Kathan D.

2015-01-01

Background: School climate is well recognized as an important influence on student behavior and adjustment to school, but there is a need for theory-guided measures that make use of teacher perspectives. Authoritative school climate theory hypothesizes that a positive school climate is characterized by high levels of disciplinary structure and…

Coexistence of diode-like volatile and multilevel nonvolatile resistive switching in a ZrO2/TiO2 stack structure.

PubMed

Li, Yingtao; Yuan, Peng; Fu, Liping; Li, Rongrong; Gao, Xiaoping; Tao, Chunlan

2015-10-02

Diode-like volatile resistive switching as well as nonvolatile resistive switching behaviors in a Cu/ZrO₂/TiO₂/Ti stack are investigated. Depending on the current compliance during the electroforming process, either volatile resistive switching or nonvolatile resistive switching is observed. With a lower current compliance (<10 μA), the Cu/ZrO₂/TiO₂/Ti device exhibits diode-like volatile resistive switching with a rectifying ratio over 10(6). The permanent transition from volatile to nonvolatile resistive switching can be obtained by applying a higher current compliance of 100 μA. Furthermore, by using different reset voltages, the Cu/ZrO₂/TiO₂/Ti device exhibits multilevel memory characteristics with high uniformity. The coexistence of nonvolatile multilevel memory and diode-like volatile resistive switching behaviors in the same Cu/ZrO₂/TiO₂/Ti device opens areas of applications in high-density storage, logic circuits, neural networks, and passive crossbar memory selectors.

A multilevel model for comorbid outcomes: obesity and diabetes in the US.

PubMed

Congdon, Peter

2010-02-01

Multilevel models are overwhelmingly applied to single health outcomes, but when two or more health conditions are closely related, it is important that contextual variation in their joint prevalence (e.g., variations over different geographic settings) is considered. A multinomial multilevel logit regression approach for analysing joint prevalence is proposed here that includes subject level risk factors (e.g., age, race, education) while also taking account of geographic context. Data from a US population health survey (the 2007 Behavioral Risk Factor Surveillance System or BRFSS) are used to illustrate the method, with a six category multinomial outcome defined by diabetic status and weight category (obese, overweight, normal). The influence of geographic context is partly represented by known geographic variables (e.g., county poverty), and partly by a model for latent area influences. In particular, a shared latent variable (common factor) approach is proposed to measure the impact of unobserved area influences on joint weight and diabetes status, with the latent variable being spatially structured to reflect geographic clustering in risk.

Multiplex lithography for multilevel multiscale architectures and its application to polymer electrolyte membrane fuel cell

PubMed Central

Cho, Hyesung; Moon Kim, Sang; Sik Kang, Yun; Kim, Junsoo; Jang, Segeun; Kim, Minhyoung; Park, Hyunchul; Won Bang, Jung; Seo, Soonmin; Suh, Kahp-Yang; Sung, Yung-Eun; Choi, Mansoo

2015-01-01

The production of multiscale architectures is of significant interest in materials science, and the integration of those structures could provide a breakthrough for various applications. Here we report a simple yet versatile strategy that allows for the LEGO-like integrations of microscale membranes by quantitatively controlling the oxygen inhibition effects of ultraviolet-curable materials, leading to multilevel multiscale architectures. The spatial control of oxygen concentration induces different curing contrasts in a resin allowing the selective imprinting and bonding at different sides of a membrane, which enables LEGO-like integration together with the multiscale pattern formation. Utilizing the method, the multilevel multiscale Nafion membranes are prepared and applied to polymer electrolyte membrane fuel cell. Our multiscale membrane fuel cell demonstrates significant enhancement of performance while ensuring mechanical robustness. The performance enhancement is caused by the combined effect of the decrease of membrane resistance and the increase of the electrochemical active surface area. PMID:26412619

Multilevel Correlates of Satisfaction with Neighborhood Availability of Fresh Fruits and Vegetables

PubMed Central

Zenk, Shannon N.; Schulz, Amy J.; Lachance, Laurie L.; Mentz, Graciela; Kannan, Srimathi; Ridella, William; Galea, Sandro

2009-01-01

Background Little is known about influences on perceptions of neighborhood food environments, despite their relevance for food-shopping behaviors and food choices. Purpose This study examined relationships between multilevel factors (neighborhood structure, independently observed neighborhood food environment, individual socioeconomic position) and satisfaction with neighborhood availability of fruits and vegetables. Methods The multilevel regression analysis drew on data from a community survey of urban adults, in-person audit and mapping of food stores, and the 2000 Census. Results Satisfaction with neighborhood availability of fruits and vegetables was lower in neighborhoods that were further from a supermarket and that had proportionately more African-American residents. Neighborhood poverty and independently observed neighborhood fruit and vegetable characteristics (variety, prices, quality) were not associated with satisfaction. Individual education modified relationships between neighborhood availability of smaller food stores (small grocery stores, convenience stores, liquor stores) and satisfaction. Conclusions Individual-level and neighborhood-level factors affect perceptions of neighborhood food environments. PMID:19809859

Maisotsenko cycle applications in multi-stage ejector recycling module for chemical production

NASA Astrophysics Data System (ADS)

Levchenko, D. O.; Artyukhov, A. E.; Yurko, I. V.

2017-08-01

The article is devoted to the theoretical bases of multistage (multi-level) utilization modules as part of chemical plants (on the example of the technological line for obtaining nitrogen fertilizers). The possibility of recycling production waste (ammonia vapors, dust and substandard nitrogen fertilizers) using ejection devices and waste heat using Maisotsenko cycle technology (Maisotsenko heat and mass exchanger (HMX), Maisotsenko power cycles and recuperators, etc.) is substantiated. The principle of operation of studied recycling module and prospects for its implementation are presented. An improved technological scheme for obtaining granular fertilizers and granules with porous structure with multistage (multi-level) recycling module is proposed.

Child Abuse, Risk in Male Partner Selection, and Intimate Partner Violence Victimization of Women of the European Union.

PubMed

Herrero, Juan; Torres, Andrea; Rodríguez, Francisco J

2018-06-05

The revictimization of women during the life cycle has attracted the interest of many researchers in recent years. In this study, we examined the relationship between the experience of child abuse and the subsequent victimization by a male partner in adulthood. Specifically, we proposed that childhood abuse experiences negatively affect the development of healthy interpersonal relationships in adulthood. Thus, some female victims of child abuse are more likely to select potentially abusive intimate male partners. Data from 23,863 heterosexual women from the 28 countries of the European Union who were living with their partners at the time of the study were used. We investigated the association between child abuse, partner's adherence to traditional gender roles, and general violence and intimate partner violence (IPV) against women. Multilevel structural equation modeling (MSEM) results indicated that child abuse is positively related to the partner's traditional gender role and general violence, which in turn predict IPV. Countries' level of human development was found to affect this process. We found support for the hypothesis that child abuse is related to IPV partially because it influences partner selection in adulthood. Thus, when they become adults, girls abused in childhood tend to select partners who are either traditional or generally violent. There is a persistent influence of social structural conditions (i.e., country's human development) throughout this process.

Multi-level Discourse Analysis in a Physics Teaching Methods Course from the Psychological Perspective of Activity Theory

NASA Astrophysics Data System (ADS)

Vieira, Rodrigo Drumond; Kelly, Gregory J.

2014-11-01

In this paper, we present and apply a multi-level method for discourse analysis in science classrooms. This method is based on the structure of human activity (activity, actions, and operations) and it was applied to study a pre-service physics teacher methods course. We argue that such an approach, based on a cultural psychological perspective, affords opportunities for analysts to perform a theoretically based detailed analysis of discourse events. Along with the presentation of analysis, we show and discuss how the articulation of different levels offers interpretative criteria for analyzing instructional conversations. We synthesize the results into a model for a teacher's practice and discuss the implications and possibilities of this approach for the field of discourse analysis in science classrooms. Finally, we reflect on how the development of teachers' understanding of their activity structures can contribute to forms of progressive discourse of science education.

Are ethnic and gender specific equations needed to derive fat free mass from bioelectrical impedance in children of South asian, black african-Caribbean and white European origin? Results of the assessment of body composition in children study.

PubMed

Nightingale, Claire M; Rudnicka, Alicja R; Owen, Christopher G; Donin, Angela S; Newton, Sian L; Furness, Cheryl A; Howard, Emma L; Gillings, Rachel D; Wells, Jonathan C K; Cook, Derek G; Whincup, Peter H

2013-01-01

Bioelectrical impedance analysis (BIA) is a potentially valuable method for assessing lean mass and body fat levels in children from different ethnic groups. We examined the need for ethnic- and gender-specific equations for estimating fat free mass (FFM) from BIA in children from different ethnic groups and examined their effects on the assessment of ethnic differences in body fat. Cross-sectional study of children aged 8-10 years in London Primary schools including 325 South Asians, 250 black African-Caribbeans and 289 white Europeans with measurements of height, weight and arm-leg impedance (Z; Bodystat 1500). Total body water was estimated from deuterium dilution and converted to FFM. Multilevel models were used to derive three types of equation {A: FFM = linear combination(height+weight+Z); B: FFM = linear combination(height(2)/Z); C: FFM = linear combination(height(2)/Z+weight)}. Ethnicity and gender were important predictors of FFM and improved model fit in all equations. The models of best fit were ethnicity and gender specific versions of equation A, followed by equation C; these provided accurate assessments of ethnic differences in FFM and FM. In contrast, the use of generic equations led to underestimation of both the negative South Asian-white European FFM difference and the positive black African-Caribbean-white European FFM difference (by 0.53 kg and by 0.73 kg respectively for equation A). The use of generic equations underestimated the positive South Asian-white European difference in fat mass (FM) and overestimated the positive black African-Caribbean-white European difference in FM (by 4.7% and 10.1% respectively for equation A). Consistent results were observed when the equations were applied to a large external data set. Ethnic- and gender-specific equations for predicting FFM from BIA provide better estimates of ethnic differences in FFM and FM in children, while generic equations can misrepresent these ethnic differences.

Are Ethnic and Gender Specific Equations Needed to Derive Fat Free Mass from Bioelectrical Impedance in Children of South Asian, Black African-Caribbean and White European Origin? Results of the Assessment of Body Composition in Children Study

PubMed Central

Nightingale, Claire M.; Rudnicka, Alicja R.; Owen, Christopher G.; Donin, Angela S.; Newton, Sian L.; Furness, Cheryl A.; Howard, Emma L.; Gillings, Rachel D.; Wells, Jonathan C. K.; Cook, Derek G.; Whincup, Peter H.

2013-01-01

Background Bioelectrical impedance analysis (BIA) is a potentially valuable method for assessing lean mass and body fat levels in children from different ethnic groups. We examined the need for ethnic- and gender-specific equations for estimating fat free mass (FFM) from BIA in children from different ethnic groups and examined their effects on the assessment of ethnic differences in body fat. Methods Cross-sectional study of children aged 8–10 years in London Primary schools including 325 South Asians, 250 black African-Caribbeans and 289 white Europeans with measurements of height, weight and arm-leg impedance (Z; Bodystat 1500). Total body water was estimated from deuterium dilution and converted to FFM. Multilevel models were used to derive three types of equation {A: FFM = linear combination(height+weight+Z); B: FFM = linear combination(height2/Z); C: FFM = linear combination(height2/Z+weight)}. Results Ethnicity and gender were important predictors of FFM and improved model fit in all equations. The models of best fit were ethnicity and gender specific versions of equation A, followed by equation C; these provided accurate assessments of ethnic differences in FFM and FM. In contrast, the use of generic equations led to underestimation of both the negative South Asian-white European FFM difference and the positive black African-Caribbean-white European FFM difference (by 0.53 kg and by 0.73 kg respectively for equation A). The use of generic equations underestimated the positive South Asian-white European difference in fat mass (FM) and overestimated the positive black African-Caribbean-white European difference in FM (by 4.7% and 10.1% respectively for equation A). Consistent results were observed when the equations were applied to a large external data set. Conclusions Ethnic- and gender-specific equations for predicting FFM from BIA provide better estimates of ethnic differences in FFM and FM in children, while generic equations can misrepresent these ethnic differences. PMID:24204625

Abriendo Puertas: Feasibility and Effectiveness a Multi-Level Intervention to Improve HIV Outcomes Among Female Sex Workers Living with HIV in the Dominican Republic.

PubMed

Kerrigan, Deanna; Barrington, Clare; Donastorg, Yeycy; Perez, Martha; Galai, Noya

2016-09-01

Female sex workers (FSW) are disproportionately affected by HIV. Yet, few interventions address the needs of FSW living with HIV. We developed a multi-level intervention, Abriendo Puertas (Opening Doors), and assessed its feasibility and effectiveness among a cohort of 250 FSW living with HIV in the Dominican Republic. We conducted socio-behavioral surveys and sexually transmitted infection and viral load testing at baseline and 10-month follow-up. We assessed changes in protected sex and adherence to antiretroviral therapy (ART) with logistic regression using generalized estimating equations. Significant pre-post intervention changes were documented for adherence (72-89 %; p < 0.001) and protected sex (71-81 %; p < 0.002). Higher intervention exposure was significantly associated with changes in adherence (AOR 2.42; 95 % CI 1.23-4.51) and protected sex (AOR 1.76; 95 % CI 1.09-2.84). Illicit drug use was negatively associated with both ART adherence and protected sex. Abriendo Puertas is feasible and effective in improving behavioral HIV outcomes in FSW living with HIV.

New Bandwidth Efficient Parallel Concatenated Coding Schemes

NASA Technical Reports Server (NTRS)

Denedetto, S.; Divsalar, D.; Montorsi, G.; Pollara, F.

1996-01-01

We propose a new solution to parallel concatenation of trellis codes with multilevel amplitude/phase modulations and a suitable iterative decoding structure. Examples are given for throughputs 2 bits/sec/Hz with 8PSK and 16QAM signal constellations.

The effect of quality of overtime work on nurses' mental health and work engagement.

PubMed

Watanabe, Mayumi; Yamauchi, Keita

2018-04-23

Recent research has suggested that the reasons why nurses work overtime hours exert differential effects on the overall impact of the work. This study aimed to clarify why nurses work overtime, and whether well-being effects differed by reason, at both the ward and individual level. Participants were 1,075 permanent nurses from 54 wards. Overtime reasons' distribution and impact on nurses were examined by a multilevel structural equation modelling approach. Nurses typically worked overtime due to a pressure to conform, high workload and to enhance self-development. Involuntary overtime work demonstrated a detrimental effect on mental health and work engagement at both the ward and individual level, whereas voluntary overtime work exerted a beneficial effect on well-being. The distribution and impact of overtime work differed by the reasons for working the overtime. These results suggest the importance of assessing the reasons for overtime, aside from the length of overtime hours. When trying to reduce overtime work, hospital managers and nurse managers need to advance the plan by ward as a whole, and also carefully assess the reasons for overtime. © 2018 John Wiley & Sons Ltd.

Multitrophic functional diversity predicts ecosystem functioning in experimental assemblages of estuarine consumers.

PubMed

Lefcheck, Jonathan S; Duffy, J Emmett

2015-11-01

The use of functional traits to explain how biodiversity affects ecosystem functioning has attracted intense interest, yet few studies have a priori altered functional diversity, especially in multitrophic communities. Here, we manipulated multivariate functional diversity of estuarine grazers and predators within multiple levels of species richness to test how species richness and functional diversity predicted ecosystem functioning in a multitrophic food web. Community functional diversity was a better predictor than species richness for the majority of ecosystem properties, based on generalized linear mixed-effects models. Combining inferences from eight traits into a single multivariate index increased prediction accuracy of these models relative to any individual trait. Structural equation modeling revealed that functional diversity of both grazers and predators was important in driving final biomass within trophic levels, with stronger effects observed for predators. We also show that different species drove different ecosystem responses, with evidence for both sampling effects and complementarity. Our study extends experimental investigations of functional trait diversity to a multilevel food web, and demonstrates that functional diversity can be more accurate and effective than species richness in predicting community biomass in a food web context.

School environments and obesity: The mediating role of personal stress.

PubMed

Milam, Adam J; Jones, Chandria D; Debnam, Katrina J; Bradshaw, Catherine P

2017-01-01

Youth spend a large amount of time in the school environment. Given the multiple influences of teachers, peers, and food and physical activity options, youth are likely to experience stressors that can influence their weight. This study examines the association between school climate and weight status. Students ( n = 28,582; 58 schools) completed an online, anonymous school climate survey as part of the Maryland Safe and Supportive Schools Project. Multilevel structural equation modeling was used to explore the association between school climate, personal stress, and obesity. Analyses were stratified by gender. At the individual level, poor school climate (bullying, physical safety, and lack of whole-school connectedness) was associated with an increased likelihood of being overweight among females ( β =.115, p = .019) but not males ( β = .138; p =.244), after controlling for age, race, and physical activity. There was no association between school climate at the school level and being overweight among males or females. A second model included stress as a potential mediator; stress attenuated the relationship between poor school-related climate and being overweight ( β = .039; p = .048) among females. Findings suggest that stress related to school climate can play a role in the health and weight status of youth.

Inequality matters: classroom status hierarchy and adolescents' bullying.

PubMed

Garandeau, Claire F; Lee, Ihno A; Salmivalli, Christina

2014-07-01

The natural emergence of status hierarchies in adolescent peer groups has long been assumed to help prevent future intragroup aggression. However, clear evidence of this beneficial influence is lacking. In fact, few studies have examined between-group differences in the degree of status hierarchy (defined as within-group variation in individual status) and how they are related to bullying, a widespread form of aggression in schools. Data from 11,296 eighth- and ninth-graders (mean age = 14.57, 50.6 % female) from 583 classes in 71 schools were used to determine the direction of the association between classroom degree of status hierarchy and bullying behaviors, and to investigate prospective relationships between these two variables over a 6-month period. Multilevel structural equation modeling analyses showed that higher levels of classroom status hierarchy were concurrently associated with higher levels of bullying at the end of the school year. Higher hierarchy in the middle of the school year predicted higher bullying later in the year. No evidence was found to indicate that initial bullying predicted future hierarchy. These findings highlight the importance of a shared balance of power in the classroom for the prevention of bullying among adolescents.

Polarization effects in the interaction between multi-level atoms and two optical fields

NASA Astrophysics Data System (ADS)

Colín-Rodríguez, R.; Flores-Mijangos, J.; Hernández-Gómez, S.; Jáuregui, R.; López-Hernández, O.; Mojica-Casique, C.; Ponciano-Ojeda, F.; Ramírez-Martínez, F.; Sahagún, D.; Volke-Sepúlveda, K.; Jiménez-Mier, J.

2015-06-01

Polarized velocity selective spectra for rubidium atoms in a room temperature cell are presented. The experiments were performed in the lambda configuration (D2 manifold) and in the 5s\\to 5{{p}3/2}\\to 5{{d}j} ladder configuration. For the lambda configuration the effect of the probe beam intensity in the absorption and polarization spectra are compared with results of a rate equation approximation. Good overall agreement between experiment and theory is found. The results indicate different saturation rates for each of the atomic transitions. Distinctive polarization signals with hyperfine-resolved components are found for the ladder 5{{d}3/2} and 5{{d}5/2} upper states. Fluorescence detection of the 420 nm that results from the second step in the cascade decay 5{{d}j}\\to 6{{p}{{j\\prime }}}\\to 5s was used in the ladder experiments. This fluorescence was also used for the detection of the 5{{p}3/2}\\to 6{{p}3/2} electric dipole forbidden transition in atomic rubidium that occurs at 911 nm. The 6{{p}3/2} hyperfine structure was resolved in this continuous wave, non-dipole excitation.

Cellular Gauge Symmetry and the Li Organization Principle: A Mathematical Addendum. Quantifying energetic dynamics in physical and biological systems through a simple geometric tool and geodetic curves.

PubMed

Yurkin, Alexander; Tozzi, Arturo; Peters, James F; Marijuán, Pedro C

2017-12-01

The present Addendum complements the accompanying paper "Cellular Gauge Symmetry and the Li Organization Principle"; it illustrates a recently-developed geometrical physical model able to assess electronic movements and energetic paths in atomic shells. The model describes a multi-level system of circular, wavy and zigzag paths which can be projected onto a horizontal tape. This model ushers in a visual interpretation of the distribution of atomic electrons' energy levels and the corresponding quantum numbers through rather simple tools, such as compasses, rulers and straightforward calculations. Here we show how this geometrical model, with the due corrections, among them the use of geodetic curves, might be able to describe and quantify the structure and the temporal development of countless physical and biological systems, from Langevin equations for random paths, to symmetry breaks occurring ubiquitously in physical and biological phenomena, to the relationships among different frequencies of EEG electric spikes. Therefore, in our work we explore the possible association of binomial distribution and geodetic curves configuring a uniform approach for the research of natural phenomena, in biology, medicine or the neurosciences. Copyright © 2017 Elsevier Ltd. All rights reserved.

Promoting children's learning and development in conflict-affected countries: Testing change process in the Democratic Republic of the Congo.

PubMed

Aber, J Lawrence; Tubbs, Carly; Torrente, Catalina; Halpin, Peter F; Johnston, Brian; Starkey, Leighann; Shivshanker, Anjuli; Annan, Jeannie; Seidman, Edward; Wolf, Sharon

2017-02-01

Improving children's learning and development in conflict-affected countries is critically important for breaking the intergenerational transmission of violence and poverty. Yet there is currently a stunning lack of rigorous evidence as to whether and how programs to improve learning and development in conflict-affected countries actually work to bolster children's academic learning and socioemotional development. This study tests a theory of change derived from the fields of developmental psychopathology and social ecology about how a school-based universal socioemotional learning program, the International Rescue Committee's Learning to Read in a Healing Classroom (LRHC), impacts children's learning and development. The study was implemented in three conflict-affected provinces of the Democratic Republic of the Congo and employed a cluster-randomized waitlist control design to estimate impact. Using multilevel structural equation modeling techniques, we found support for the central pathways in the LRHC theory of change. Specifically, we found that LRHC differentially impacted dimensions of the quality of the school and classroom environment at the end of the first year of the intervention, and that in turn these dimensions of quality were differentially associated with child academic and socioemotional outcomes. Future implications and directions are discussed.

The Role of Stress and Spirituality in Adolescent Substance Use.

PubMed

Debnam, Katrina; Milam, Adam J; Furr-Holden, C Debra; Bradshaw, Catherine

2016-05-11

Substance use can occur as a result of coping with stress. Within the school context, youth are exposed to stressors related to school achievement and peer-relationships. Protective factors, such as spirituality, may moderate adolescents' engagement in substance use. The current study investigated the role of spirituality in the association between stress and substance use, in an effort to test the hypothesis that spirituality moderates the association between stress and substance use. This study used data from youth in grades 6-8 attending 40 parochial private schools. A total of 5,217 students participated in the web-based survey administered in Spring 2013. Multilevel structural equation models were used to examine the association between stress, spirituality, and substance use, while accounting for the nested nature of the data (i.e., students within schools). Higher stress was significantly associated with increased alcohol, tobacco, and other drug use among youth (b =.306, p <.001). In addition, lower spiritual beliefs were associated with greater substance use (b =.349, p <.001). Spiritual beliefs did not moderate the relationship between stress and substance use. Implications for increasing students' adaptive coping when confronted with school-related stressors and the role of school climate are discussed.

Using multiple group modeling to test moderators in meta-analysis.

PubMed

Schoemann, Alexander M

2016-12-01

Meta-analysis is a popular and flexible analysis that can be fit in many modeling frameworks. Two methods of fitting meta-analyses that are growing in popularity are structural equation modeling (SEM) and multilevel modeling (MLM). By using SEM or MLM to fit a meta-analysis researchers have access to powerful techniques associated with SEM and MLM. This paper details how to use one such technique, multiple group analysis, to test categorical moderators in meta-analysis. In a multiple group meta-analysis a model is fit to each level of the moderator simultaneously. By constraining parameters across groups any model parameter can be tested for equality. Using multiple groups to test for moderators is especially relevant in random-effects meta-analysis where both the mean and the between studies variance of the effect size may be compared across groups. A simulation study and the analysis of a real data set are used to illustrate multiple group modeling with both SEM and MLM. Issues related to multiple group meta-analysis and future directions for research are discussed. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A multi-level qualitative analysis of Telehomecare in Ontario: challenges and opportunities.

PubMed

Hunting, Gemma; Shahid, Nida; Sahakyan, Yeva; Fan, Iris; Moneypenny, Crystal R; Stanimirovic, Aleksandra; North, Taylor; Petrosyan, Yelena; Krahn, Murray D; Rac, Valeria E

2015-12-09

Despite research demonstrating the potential effectiveness of Telehomecare for people with Chronic Obstructive Pulmonary Disease and Heart Failure, broad-scale comprehensive evaluations are lacking. This article discusses the qualitative component of a mixed-method program evaluation of Telehomecare in Ontario, Canada. The objective of the qualitative component was to explore the multi-level factors and processes which facilitate or impede the implementation and adoption of the program across three regions where it was first implemented. The study employs a multi-level framework as a conceptual guide to explore the facilitators and barriers to Telehomecare implementation and adoption across five levels: technology, patients, providers, organizations, and structures. In-depth semi-structured interviews and ethnographic observations with program stakeholders, as well as a Telehomecare document review were used to elicit key themes. Study participants (n = 89) included patients and/or informal caregivers (n = 39), health care providers (n = 23), technicians (n = 2), administrators (n = 12), and decision makers (n = 13) across three different Local Health Integration Networks in Ontario. Key facilitators to Telehomecare implementation and adoption at each level of the multi-level framework included: user-friendliness of Telehomecare technology, patient motivation to participate in the program, support for Telehomecare providers, the integration of Telehomecare into broader health service provision, and comprehensive program evaluation. Key barriers included: access-related issues to using the technology, patient language (if not English or French), Telehomecare provider time limitations, gaps in health care provision for patients, and structural barriers to patient participation related to geography and social location. Though Telehomecare has the potential to positively impact patient lives and strengthen models of health care provision, a number of key challenges remain. As such, further implementation and expansion of Telehomecare must involve continuous assessments of what is working and not working with all stakeholders. Increased dialogue, evaluation, and knowledge translation within and across regions to understand the contextual factors influencing Telehomecare implementation and adoption is required. This can inform decision-making that better reflects and addresses the needs of all program stakeholders.

Meros Preconditioner Package

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

2004-04-01

Meros uses the compositional, aggregation, and overload operator capabilities of TSF to provide an object-oriented package providing segregated/block preconditioners for linear systems related to fully-coupled Navier-Stokes problems. This class of preconditioners exploits the special properties of these problems to segregate the equations and use multi-level preconditioners (through ML) on the matrix sub-blocks. Several preconditioners are provided, including the Fp and BFB preconditioners of Kay & Loghin and Silvester, Elman, Kay & Wathen. The overall performance and scalability of these preconditioners approaches that of multigrid for certain types of problems. Meros also provides more traditional pressure projection methods including SIMPLE andmore » SIMPLEC.« less

Multilevel models for cost-effectiveness analyses that use cluster randomised trial data: An approach to model choice.

PubMed

Ng, Edmond S-W; Diaz-Ordaz, Karla; Grieve, Richard; Nixon, Richard M; Thompson, Simon G; Carpenter, James R

2016-10-01

Multilevel models provide a flexible modelling framework for cost-effectiveness analyses that use cluster randomised trial data. However, there is a lack of guidance on how to choose the most appropriate multilevel models. This paper illustrates an approach for deciding what level of model complexity is warranted; in particular how best to accommodate complex variance-covariance structures, right-skewed costs and missing data. Our proposed models differ according to whether or not they allow individual-level variances and correlations to differ across treatment arms or clusters and by the assumed cost distribution (Normal, Gamma, Inverse Gaussian). The models are fitted by Markov chain Monte Carlo methods. Our approach to model choice is based on four main criteria: the characteristics of the data, model pre-specification informed by the previous literature, diagnostic plots and assessment of model appropriateness. This is illustrated by re-analysing a previous cost-effectiveness analysis that uses data from a cluster randomised trial. We find that the most useful criterion for model choice was the deviance information criterion, which distinguishes amongst models with alternative variance-covariance structures, as well as between those with different cost distributions. This strategy for model choice can help cost-effectiveness analyses provide reliable inferences for policy-making when using cluster trials, including those with missing data. © The Author(s) 2013.

Ion Elevators and Escalators in Multilevel Structures for Lossless Ion Manipulations

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

Ibrahim, Yehia M.; Hamid, Ahmed M.; Cox, Jonathan T.

2017-01-19

We describe two approaches based upon ion ‘elevator’ and ‘escalator’ components that allow moving ions to different levels in structures for lossless ion manipulations (SLIM). Guided by ion motion simulations we designed elevator and escalator components providing essentially lossless transmission in multi-level designs based upon ion current measurements. The ion elevator design allowed ions to efficiently bridge a 4 mm gap between levels. The component was integrated in a SLIM and coupled to a QTOF mass spectrometer using an ion funnel interface to evaluate the m/z range transmitted as compared to transmission within a level (e.g. in a linear section).more » Mass spectra for singly-charged ions of m/z 600-2700 produced similar mass spectra for both elevator and straight (linear motion) components. In the ion escalator design, traveling waves (TW) were utilized to transport ions efficiently between two SLIM levels. Ion current measurements and ion mobility (IM) spectrometry analysis illustrated that ions can be transported between TW-SLIM levels with no significant loss of either ions or IM resolution. These developments provide a path for the development of multilevel designs providing e.g. much longer IM path lengths, more compact designs, and the implementation of much more complex SLIM devices in which e.g. different levels may operate at different temperatures or with different gases.« less

Family structure and posttraumatic stress reactions: a longitudinal study using multilevel analyses

PubMed Central

2011-01-01

Background There is limited research on the relevance of family structures to the development and maintenance of posttraumatic stress following disasters. We longitudinally studied the effects of marital and parental statuses on posttraumatic stress reactions after the 2004 Southeast Asian tsunami and whether persons in the same households had more shared stress reactions than others. Method The study included a tourist population of 641 Norwegian adult citizens, many of them from families with children. We measured posttraumatic stress symptoms with the Impact of Event Scale-Revised at 6 months and 2 years post-disaster. Analyses included multilevel methods with mixed effects models. Results Results showed that neither marital nor parental status was significantly related to posttraumatic stress. At both assessments, adults living in the same household reported levels of posttraumatic stress that were more similar to one another than adults who were not living together. Between households, disaster experiences were closely related to the variance in posttraumatic stress symptom levels at both assessments. Within households, however, disaster experiences were less related to the variance in symptom level at 2 years than at 6 months. Conclusions These results indicate that adult household members may influence one another's posttraumatic stress reactions as well as their interpretations of the disaster experiences over time. Our findings suggest that multilevel methods may provide important information about family processes after disasters. PMID:22171549

Experimental study and numerical simulation on the structural and mechanical properties of Typha leaves through multimodal microscopy approaches.

PubMed

Liu, Jingjing; Zhang, Zhihui; Yu, Zhenglei; Liang, Yunhong; Li, Xiujuan; Ren, Luquan

2018-01-01

The Typha leaf, with special multi-level structure, low density and excellent mechanical properties, is an ideal bionic prototype utilized for lightweight design. In order to further study the relationship between the structure and mechanical properties, the three-dimensional macroscopic morphology of Typha leaves was characterized by micro computed tomography (Micro-CT) and its internal microstructure was observed by scanning electron microscopy (SEM). The combination of experimental and computational research was carried out in this paper, to reveal and verify the effect of multi-level structure on the mechanical properties. A universal testing machine and a self-developed mechanical testing apparatus with high precision and low load were used to measure the mechanical properties of the axial compression and lateral bending of the leaves, respectively. Three models with different internal structures were established based on the above-mentioned three-dimensional morphologies. The result demonstrated that the structure of partitions and diaphragms within the Typha leaf could form a reinforcement ribs structure which could provide multiple load paths and make the process of compression and bending difficult. The further nonlinear finite element analysis through LS-DYNA proved that internal structure could improve the ability of the models to resist compression and deformation. The investigation can be the reference for lightweight thin-walled structure design and inspire the application of the bionic structural materials. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multilevel Factor Structure, Concurrent Validity, and Test-Retest Reliability of the High School Teacher Version of the Authoritative School Climate Survey

ERIC Educational Resources Information Center

Huang, Francis L.; Cornell, Dewey G.

2016-01-01

Although school climate has long been recognized as an important factor in the school improvement process, there are few psychometrically supported measures based on teacher perspectives. The current study replicated and extended the factor structure, concurrent validity, and test-retest reliability of the teacher version of the Authoritative…

76 FR 14959 - Fall Creek Hydro, LLC; Notice of Application Tendered for Filing With the Commission and...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-18

... facilities: (1) An intake structure located on the face of the Corps dam and installed directly above one of the existing intake structures; (2) two 8-foot-diameter by 110-foot-long steel penstocks that would..., among other things, Eicher fish screens, steel pipes, multi-level release ports, open channels, a fish...

Fully implicit moving mesh adaptive algorithm

NASA Astrophysics Data System (ADS)

Serazio, C.; Chacon, L.; Lapenta, G.

2006-10-01

In many problems of interest, the numerical modeler is faced with the challenge of dealing with multiple time and length scales. The former is best dealt with with fully implicit methods, which are able to step over fast frequencies to resolve the dynamical time scale of interest. The latter requires grid adaptivity for efficiency. Moving-mesh grid adaptive methods are attractive because they can be designed to minimize the numerical error for a given resolution. However, the required grid governing equations are typically very nonlinear and stiff, and of considerably difficult numerical treatment. Not surprisingly, fully coupled, implicit approaches where the grid and the physics equations are solved simultaneously are rare in the literature, and circumscribed to 1D geometries. In this study, we present a fully implicit algorithm for moving mesh methods that is feasible for multidimensional geometries. Crucial elements are the development of an effective multilevel treatment of the grid equation, and a robust, rigorous error estimator. For the latter, we explore the effectiveness of a coarse grid correction error estimator, which faithfully reproduces spatial truncation errors for conservative equations. We will show that the moving mesh approach is competitive vs. uniform grids both in accuracy (due to adaptivity) and efficiency. Results for a variety of models 1D and 2D geometries will be presented. L. Chac'on, G. Lapenta, J. Comput. Phys., 212 (2), 703 (2006) G. Lapenta, L. Chac'on, J. Comput. Phys., accepted (2006)

Multilevel covariance regression with correlated random effects in the mean and variance structure.

PubMed

Quintero, Adrian; Lesaffre, Emmanuel

2017-09-01

Multivariate regression methods generally assume a constant covariance matrix for the observations. In case a heteroscedastic model is needed, the parametric and nonparametric covariance regression approaches can be restrictive in the literature. We propose a multilevel regression model for the mean and covariance structure, including random intercepts in both components and allowing for correlation between them. The implied conditional covariance function can be different across clusters as a result of the random effect in the variance structure. In addition, allowing for correlation between the random intercepts in the mean and covariance makes the model convenient for skewedly distributed responses. Furthermore, it permits us to analyse directly the relation between the mean response level and the variability in each cluster. Parameter estimation is carried out via Gibbs sampling. We compare the performance of our model to other covariance modelling approaches in a simulation study. Finally, the proposed model is applied to the RN4CAST dataset to identify the variables that impact burnout of nurses in Belgium. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Model Comparison of Bayesian Semiparametric and Parametric Structural Equation Models

ERIC Educational Resources Information Center

Song, Xin-Yuan; Xia, Ye-Mao; Pan, Jun-Hao; Lee, Sik-Yum

2011-01-01

Structural equation models have wide applications. One of the most important issues in analyzing structural equation models is model comparison. This article proposes a Bayesian model comparison statistic, namely the "L[subscript nu]"-measure for both semiparametric and parametric structural equation models. For illustration purposes, we consider…

Applying Meta-Analysis to Structural Equation Modeling

ERIC Educational Resources Information Center

Hedges, Larry V.

2016-01-01

Structural equation models play an important role in the social sciences. Consequently, there is an increasing use of meta-analytic methods to combine evidence from studies that estimate the parameters of structural equation models. Two approaches are used to combine evidence from structural equation models: A direct approach that combines…

Cloud/climate sensitivity experiments

NASA Technical Reports Server (NTRS)

Roads, J. O.; Vallis, G. K.; Remer, L.

1982-01-01

A study of the relationships between large-scale cloud fields and large scale circulation patterns is presented. The basic tool is a multi-level numerical model comprising conservation equations for temperature, water vapor and cloud water and appropriate parameterizations for evaporation, condensation, precipitation and radiative feedbacks. Incorporating an equation for cloud water in a large-scale model is somewhat novel and allows the formation and advection of clouds to be treated explicitly. The model is run on a two-dimensional, vertical-horizontal grid with constant winds. It is shown that cloud cover increases with decreased eddy vertical velocity, decreased horizontal advection, decreased atmospheric temperature, increased surface temperature, and decreased precipitation efficiency. The cloud field is found to be well correlated with the relative humidity field except at the highest levels. When radiative feedbacks are incorporated and the temperature increased by increasing CO2 content, cloud amounts decrease at upper-levels or equivalently cloud top height falls. This reduces the temperature response, especially at upper levels, compared with an experiment in which cloud cover is fixed.

Bioinspired Functional Materials

DOE PAGES

Zheng, Yongmei; Wang, Jingxia; Hou, Yongping; ...

2014-11-25

This special issue is focused on the nanoscale or micro-/nanoscale structures similar to the biological features in multilevels or hierarchy and so on. Research by mimicking biological systems has shown more impact on many applications due to the well-designed micro-/nanostructures inspired from the biological surfaces or interfaces; therefore, the materials may achieve the fascinating functionality. In conclusion, the bioinspired functional materials may be fabricated by developing novel technology or methods such as synthesis, self-assembly, and soft lithography at micro- or nanolevel or multilevels and, in addition, the multidisciplinary procedures of physical or chemical methods and nanotechnology to mimic the biologicalmore » multiscale micro-/nanostructures onto one-/two-dimensional surface materials.« less

Multi-Hamiltonian structure of the Born-Infeld equation

NASA Astrophysics Data System (ADS)

Arik, Metin; Neyzi, Fahrünisa; Nutku, Yavuz; Olver, Peter J.; Verosky, John M.

1989-06-01

The multi-Hamiltonian structure, conservation laws, and higher order symmetries for the Born-Infeld equation are exhibited. A new transformation of the Born-Infeld equation to the equations of a Chaplygin gas is presented and explored. The Born-Infeld equation is distinguished among two-dimensional hyperbolic systems by its wealth of such multi-Hamiltonian structures.

Multi-level Bayesian safety analysis with unprocessed Automatic Vehicle Identification data for an urban expressway.

PubMed

Shi, Qi; Abdel-Aty, Mohamed; Yu, Rongjie

2016-03-01

In traffic safety studies, crash frequency modeling of total crashes is the cornerstone before proceeding to more detailed safety evaluation. The relationship between crash occurrence and factors such as traffic flow and roadway geometric characteristics has been extensively explored for a better understanding of crash mechanisms. In this study, a multi-level Bayesian framework has been developed in an effort to identify the crash contributing factors on an urban expressway in the Central Florida area. Two types of traffic data from the Automatic Vehicle Identification system, which are the processed data capped at speed limit and the unprocessed data retaining the original speed were incorporated in the analysis along with road geometric information. The model framework was proposed to account for the hierarchical data structure and the heterogeneity among the traffic and roadway geometric data. Multi-level and random parameters models were constructed and compared with the Negative Binomial model under the Bayesian inference framework. Results showed that the unprocessed traffic data was superior. Both multi-level models and random parameters models outperformed the Negative Binomial model and the models with random parameters achieved the best model fitting. The contributing factors identified imply that on the urban expressway lower speed and higher speed variation could significantly increase the crash likelihood. Other geometric factors were significant including auxiliary lanes and horizontal curvature. Copyright © 2015 Elsevier Ltd. All rights reserved.

The use of simple reparameterizations to improve the efficiency of Markov chain Monte Carlo estimation for multilevel models with applications to discrete time survival models.

PubMed

Browne, William J; Steele, Fiona; Golalizadeh, Mousa; Green, Martin J

2009-06-01

We consider the application of Markov chain Monte Carlo (MCMC) estimation methods to random-effects models and in particular the family of discrete time survival models. Survival models can be used in many situations in the medical and social sciences and we illustrate their use through two examples that differ in terms of both substantive area and data structure. A multilevel discrete time survival analysis involves expanding the data set so that the model can be cast as a standard multilevel binary response model. For such models it has been shown that MCMC methods have advantages in terms of reducing estimate bias. However, the data expansion results in very large data sets for which MCMC estimation is often slow and can produce chains that exhibit poor mixing. Any way of improving the mixing will result in both speeding up the methods and more confidence in the estimates that are produced. The MCMC methodological literature is full of alternative algorithms designed to improve mixing of chains and we describe three reparameterization techniques that are easy to implement in available software. We consider two examples of multilevel survival analysis: incidence of mastitis in dairy cattle and contraceptive use dynamics in Indonesia. For each application we show where the reparameterization techniques can be used and assess their performance.

Random-Effects Models for Meta-Analytic Structural Equation Modeling: Review, Issues, and Illustrations

ERIC Educational Resources Information Center

Cheung, Mike W.-L.; Cheung, Shu Fai

2016-01-01

Meta-analytic structural equation modeling (MASEM) combines the techniques of meta-analysis and structural equation modeling for the purpose of synthesizing correlation or covariance matrices and fitting structural equation models on the pooled correlation or covariance matrix. Both fixed-effects and random-effects models can be defined in MASEM.…

A Performance Comparison of the Parallel Preconditioners for Iterative Methods for Large Sparse Linear Systems Arising from Partial Differential Equations on Structured Grids

NASA Astrophysics Data System (ADS)

Ma, Sangback

In this paper we compare various parallel preconditioners such as Point-SSOR (Symmetric Successive OverRelaxation), ILU(0) (Incomplete LU) in the Wavefront ordering, ILU(0) in the Multi-color ordering, Multi-Color Block SOR (Successive OverRelaxation), SPAI (SParse Approximate Inverse) and pARMS (Parallel Algebraic Recursive Multilevel Solver) for solving large sparse linear systems arising from two-dimensional PDE (Partial Differential Equation)s on structured grids. Point-SSOR is well-known, and ILU(0) is one of the most popular preconditioner, but it is inherently serial. ILU(0) in the Wavefront ordering maximizes the parallelism in the natural order, but the lengths of the wave-fronts are often nonuniform. ILU(0) in the Multi-color ordering is a simple way of achieving a parallelism of the order N, where N is the order of the matrix, but its convergence rate often deteriorates as compared to that of natural ordering. We have chosen the Multi-Color Block SOR preconditioner combined with direct sparse matrix solver, since for the Laplacian matrix the SOR method is known to have a nondeteriorating rate of convergence when used with the Multi-Color ordering. By using block version we expect to minimize the interprocessor communications. SPAI computes the sparse approximate inverse directly by least squares method. Finally, ARMS is a preconditioner recursively exploiting the concept of independent sets and pARMS is the parallel version of ARMS. Experiments were conducted for the Finite Difference and Finite Element discretizations of five two-dimensional PDEs with large meshsizes up to a million on an IBM p595 machine with distributed memory. Our matrices are real positive, i. e., their real parts of the eigenvalues are positive. We have used GMRES(m) as our outer iterative method, so that the convergence of GMRES(m) for our test matrices are mathematically guaranteed. Interprocessor communications were done using MPI (Message Passing Interface) primitives. The results show that in general ILU(0) in the Multi-Color ordering ahd ILU(0) in the Wavefront ordering outperform the other methods but for symmetric and nearly symmetric 5-point matrices Multi-Color Block SOR gives the best performance, except for a few cases with a small number of processors.

A Multilevel Investigation of Neighborhood Effects on Parental Warmth

ERIC Educational Resources Information Center

Tendulkar, Shalini A.; Buka, Stephen; Dunn, Erin C.; Subramanian, S. V.; Koenen, Karestan C.

2010-01-01

Although researchers recognize that social contexts shape parenting behaviors, the relationship between neighborhood environment and parenting remains poorly understood. To address this gap, we investigated the associations between compositional and contextual (structural, social, and safety) characteristics of neighborhoods and parental warmth.…

Uncertainty quantification and validation of 3D lattice scaffolds for computer-aided biomedical applications.

PubMed

Gorguluarslan, Recep M; Choi, Seung-Kyum; Saldana, Christopher J

2017-07-01

A methodology is proposed for uncertainty quantification and validation to accurately predict the mechanical response of lattice structures used in the design of scaffolds. Effective structural properties of the scaffolds are characterized using a developed multi-level stochastic upscaling process that propagates the quantified uncertainties at strut level to the lattice structure level. To obtain realistic simulation models for the stochastic upscaling process and minimize the experimental cost, high-resolution finite element models of individual struts were reconstructed from the micro-CT scan images of lattice structures which are fabricated by selective laser melting. The upscaling method facilitates the process of determining homogenized strut properties to reduce the computational cost of the detailed simulation model for the scaffold. Bayesian Information Criterion is utilized to quantify the uncertainties with parametric distributions based on the statistical data obtained from the reconstructed strut models. A systematic validation approach that can minimize the experimental cost is also developed to assess the predictive capability of the stochastic upscaling method used at the strut level and lattice structure level. In comparison with physical compression test results, the proposed methodology of linking the uncertainty quantification with the multi-level stochastic upscaling method enabled an accurate prediction of the elastic behavior of the lattice structure with minimal experimental cost by accounting for the uncertainties induced by the additive manufacturing process. Copyright © 2017 Elsevier Ltd. All rights reserved.

The socio-genetics of a complex society: female gelada relatedness patterns mirror association patterns in a multilevel society.

PubMed

Snyder-Mackler, Noah; Alberts, Susan C; Bergman, Thore J

2014-12-01

Multilevel societies with fission-fusion dynamics--arguably the most complex animal societies--are defined by two or more nested levels of organization. The core of these societies are modular social units that regularly fission and fuse with one another. Despite convergent evolution in disparate taxa, we know strikingly little about how such societies form and how fitness benefits operate. Understanding the kinship structure of complex societies could inform us about the origins of the social structure as well as about the potential for individuals in these societies to accrue indirect fitness benefits. Here, we combined genetic and behavioural data on geladas (Theropithecus gelada), an Old World Monkey, to complete the most comprehensive socio-genetic analysis of a multilevel society to date. In geladas, individuals in the core social 'units', associate at different frequencies to form 'teams', 'bands' and, the largest aggregations, 'communities'. Units were composed of closely related females, and females remained with their close kin during permanent fissions of units. Interestingly, female-female relatedness also significantly predicted between-unit, between-team and between-band association patterns, while male-male relatedness did not. Thus, it is likely that the socio-genetic structure of gelada society results from females maintaining associations with their female relatives during successive unit fissions--possibly in an attempt to balance the direct and indirect fitness benefits of group living. Overall, the persistence of associations among related females across generations appears to drive the formation of higher levels of gelada society, suggesting that females seek kin for inclusive fitness benefits at multiple levels of gelada society. © 2014 John Wiley & Sons Ltd.

Hybrid Artificial Root Foraging Optimizer Based Multilevel Threshold for Image Segmentation

PubMed Central

Liu, Yang; Liu, Junfei

2016-01-01

This paper proposes a new plant-inspired optimization algorithm for multilevel threshold image segmentation, namely, hybrid artificial root foraging optimizer (HARFO), which essentially mimics the iterative root foraging behaviors. In this algorithm the new growth operators of branching, regrowing, and shrinkage are initially designed to optimize continuous space search by combining root-to-root communication and coevolution mechanism. With the auxin-regulated scheme, various root growth operators are guided systematically. With root-to-root communication, individuals exchange information in different efficient topologies, which essentially improve the exploration ability. With coevolution mechanism, the hierarchical spatial population driven by evolutionary pressure of multiple subpopulations is structured, which ensure that the diversity of root population is well maintained. The comparative results on a suit of benchmarks show the superiority of the proposed algorithm. Finally, the proposed HARFO algorithm is applied to handle the complex image segmentation problem based on multilevel threshold. Computational results of this approach on a set of tested images show the outperformance of the proposed algorithm in terms of optimization accuracy computation efficiency. PMID:27725826

Hybrid Artificial Root Foraging Optimizer Based Multilevel Threshold for Image Segmentation.

PubMed

Liu, Yang; Liu, Junfei; Tian, Liwei; Ma, Lianbo

2016-01-01

This paper proposes a new plant-inspired optimization algorithm for multilevel threshold image segmentation, namely, hybrid artificial root foraging optimizer (HARFO), which essentially mimics the iterative root foraging behaviors. In this algorithm the new growth operators of branching, regrowing, and shrinkage are initially designed to optimize continuous space search by combining root-to-root communication and coevolution mechanism. With the auxin-regulated scheme, various root growth operators are guided systematically. With root-to-root communication, individuals exchange information in different efficient topologies, which essentially improve the exploration ability. With coevolution mechanism, the hierarchical spatial population driven by evolutionary pressure of multiple subpopulations is structured, which ensure that the diversity of root population is well maintained. The comparative results on a suit of benchmarks show the superiority of the proposed algorithm. Finally, the proposed HARFO algorithm is applied to handle the complex image segmentation problem based on multilevel threshold. Computational results of this approach on a set of tested images show the outperformance of the proposed algorithm in terms of optimization accuracy computation efficiency.

The design of composite monitoring scheme for multilevel information in crop early diseases

NASA Astrophysics Data System (ADS)

Zhang, Yan; Meng, Qinglong; Shang, Jing

2018-02-01

It is difficult to monitor and predict the crops early diseases in that the crop disease monitoring is usually monitored by visible light images and the availabilities in early warning are poor at present. The features of common nondestructive testing technology applied to the crop diseases were analyzed in this paper. Based on the changeable characteristics of the virus from the incubation period to the onset period of crop activities, the multilevel composite information monitoring scheme were designed by applying infrared thermal imaging, visible near infrared hyperspectral imaging, micro-imaging technology to the monitoring of multilevel information of crop disease infection comprehensively. The early warning process and key monitoring parameters of compound monitoring scheme are given by taking the temperature, color, structure and texture of crops as the key monitoring characteristics of disease. With overcoming the deficiency that the conventional monitoring scheme is only suitable for the observation of diseases with naked eyes, the monitoring and early warning of the incubation and early onset of the infection crops can be realized by the composite monitoring program as mentioned in this paper.

A Multilevel Model for Comorbid Outcomes: Obesity and Diabetes in the US

PubMed Central

Congdon, Peter

2010-01-01

Multilevel models are overwhelmingly applied to single health outcomes, but when two or more health conditions are closely related, it is important that contextual variation in their joint prevalence (e.g., variations over different geographic settings) is considered. A multinomial multilevel logit regression approach for analysing joint prevalence is proposed here that includes subject level risk factors (e.g., age, race, education) while also taking account of geographic context. Data from a US population health survey (the 2007 Behavioral Risk Factor Surveillance System or BRFSS) are used to illustrate the method, with a six category multinomial outcome defined by diabetic status and weight category (obese, overweight, normal). The influence of geographic context is partly represented by known geographic variables (e.g., county poverty), and partly by a model for latent area influences. In particular, a shared latent variable (common factor) approach is proposed to measure the impact of unobserved area influences on joint weight and diabetes status, with the latent variable being spatially structured to reflect geographic clustering in risk. PMID:20616977

Stakeholder conceptualisation of multi-level HIV and AIDS determinants in a Black epicentre.

PubMed

Brawner, Bridgette M; Reason, Janaiya L; Hanlon, Kelsey; Guthrie, Barbara; Schensul, Jean J

2017-09-01

HIV has reached epidemic proportions among African Americans in the USA but certain urban contexts appear to experience a disproportionate disease burden. Geographic information systems mapping in Philadelphia indicates increased HIV incidence and prevalence in predominantly Black census tracts, with major differences across adjacent communities. What factors shape these geographic HIV disparities among Black Philadelphians? This descriptive study was designed to refine and validate a conceptual model developed to better understand multi-level determinants of HIV-related risk among Black Philadelphians. We used an expanded ecological approach to elicit reflective perceptions from administrators, direct service providers and community members about individual, social and structural factors that interact to protect against or increase the risk for acquiring HIV within their community. Gender equity, social capital and positive cultural mores (e.g., monogamy, abstinence) were seen as the main protective factors. Historical negative contributory influences of racial residential segregation, poverty and incarceration were among the most salient risk factors. This study was a critical next step toward initiating theory-based, multi-level community-based HIV prevention initiatives.

A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking

PubMed Central

Gilbert, David

2016-01-01

Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour, the Xenopus laevis cell cycle and the acute inflammation of the gut and lung. Our methodology and software will enable computational biologists to efficiently develop reliable multilevel computational models of biological systems. PMID:27187178

A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking.

PubMed

Pârvu, Ovidiu; Gilbert, David

2016-01-01

Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour, the Xenopus laevis cell cycle and the acute inflammation of the gut and lung. Our methodology and software will enable computational biologists to efficiently develop reliable multilevel computational models of biological systems.

Multilevel Interventions: Measurement and Measures

PubMed Central

Charns, Martin P.; Alligood, Elaine C.; Benzer, Justin K.; Burgess, James F.; Mcintosh, Nathalie M.; Burness, Allison; Partin, Melissa R.; Clauser, Steven B.

2012-01-01

Background Multilevel intervention research holds the promise of more accurately representing real-life situations and, thus, with proper research design and measurement approaches, facilitating effective and efficient resolution of health-care system challenges. However, taking a multilevel approach to cancer care interventions creates both measurement challenges and opportunities. Methods One-thousand seventy two cancer care articles from 2005 to 2010 were reviewed to examine the state of measurement in the multilevel intervention cancer care literature. Ultimately, 234 multilevel articles, 40 involving cancer care interventions, were identified. Additionally, literature from health services, social psychology, and organizational behavior was reviewed to identify measures that might be useful in multilevel intervention research. Results The vast majority of measures used in multilevel cancer intervention studies were individual level measures. Group-, organization-, and community-level measures were rarely used. Discussion of the independence, validity, and reliability of measures was scant. Discussion Measurement issues may be especially complex when conducting multilevel intervention research. Measurement considerations that are associated with multilevel intervention research include those related to independence, reliability, validity, sample size, and power. Furthermore, multilevel intervention research requires identification of key constructs and measures by level and consideration of interactions within and across levels. Thus, multilevel intervention research benefits from thoughtful theory-driven planning and design, an interdisciplinary approach, and mixed methods measurement and analysis. PMID:22623598

Multi-Hamiltonian structure of equations of hydrodynamic type

NASA Astrophysics Data System (ADS)

Gümral, H.; Nutku, Y.

1990-11-01

The discussion of the Hamiltonian structure of two-component equations of hydrodynamic type is completed by presenting the Hamiltonian operators for Euler's equation governing the motion of plane sound waves of finite amplitude and another quasilinear second-order wave equation. There exists a doubly infinite family of conserved Hamiltonians for the equations of gas dynamics that degenerate into one, namely, the Benney sequence, for shallow-water waves. Infinite sequences of conserved quantities for these equations are also presented. In the case of multicomponent equations of hydrodynamic type, it is shown, that Kodama's generalization of the shallow-water equations admits bi-Hamiltonian structure.

Multi-level of Fidelity Multi-Disciplinary Design Optimization of Small, Solid-Propellant Launch Vehicles

NASA Astrophysics Data System (ADS)

Roshanian, Jafar; Jodei, Jahangir; Mirshams, Mehran; Ebrahimi, Reza; Mirzaee, Masood

A new automated multi-level of fidelity Multi-Disciplinary Design Optimization (MDO) methodology has been developed at the MDO Laboratory of K.N. Toosi University of Technology. This paper explains a new design approach by formulation of developed disciplinary modules. A conceptual design for a small, solid-propellant launch vehicle was considered at two levels of fidelity structure. Low and medium level of fidelity disciplinary codes were developed and linked. Appropriate design and analysis codes were defined according to their effect on the conceptual design process. Simultaneous optimization of the launch vehicle was performed at the discipline level and system level. Propulsion, aerodynamics, structure and trajectory disciplinary codes were used. To reach the minimum launch weight, the Low LoF code first searches the whole design space to achieve the mission requirements. Then the medium LoF code receives the output of the low LoF and gives a value near the optimum launch weight with more details and higher fidelity.

Evolution of cooperation in multilevel public goods games with community structures

NASA Astrophysics Data System (ADS)

Wang, Jing; Wu, Bin; Ho, Daniel W. C.; Wang, Long

2011-03-01

In a community-structured population, public goods games (PGG) occur both within and between communities. Such type of PGG is referred as multilevel public goods games (MPGG). We propose a minimalist evolutionary model of the MPGG and analytically study the evolution of cooperation. We demonstrate that in the case of sufficiently large community size and community number, if the imitation strength within community is weak, i.e., an individual imitates another one in the same community almost randomly, cooperation as well as punishment are more abundant than defection in the long run; if the imitation strength between communities is strong, i.e., the more successful strategy in two individuals from distinct communities is always imitated, cooperation and punishment are also more abundant. However, when both of the two imitation intensities are strong, defection becomes the most abundant strategy in the population. Our model provides insight into the investigation of the large-scale cooperation in public social dilemma among contemporary communities.

Reading and spelling skills in German third graders: Examining the role of student and context characteristics.

PubMed

von Suchodoletz, Antje; Larsen, Ross A A; Gunzenhauser, Catherine; Fäsche, Anika

2015-12-01

Educational processes and outcomes are influenced by a multitude of factors, including individual and contextual characteristics. Recently, studies have demonstrated that student and context characteristics may produce unique and cumulative effects on educational outcomes. The study aimed to investigate (1) the relative contribution of student, classroom, and school characteristics to reading fluency and orthographic spelling, (2) the relative contribution of specific predictors to reading fluency and orthographic spelling within the sets of student, classroom, and school characteristics, and (3) whether the contribution of student, classroom, and school characteristics differs for reading fluency and orthographic spelling. Participants were 789 German third-grade students from 56 classrooms in 34 schools. Students completed an intelligence test and a questionnaire assessing self-control. Reading fluency and orthographic spelling performance were assessed using standardized achievement tests. Multilevel structural equation modelling was used to control for the hierarchical structure of educational data. Variances in students' reading and spelling skills were in large part explained by student characteristics (>90%). Classroom and school characteristics yielded little variance. Student-level intelligence and self-control were significantly related to reading fluency. For orthographic spelling, student-level intelligence and self-control, class-average intelligence, and, at the school level, the socio-economic status of the school's neighbourhood were significant predictors. Future research needs to investigate relevant classroom and school factors that may directly and indirectly relate to academic outcomes. © 2015 The British Psychological Society.

Prenatal smoking exposure and offspring stress coping in late adolescence: no causal link.

PubMed

Kuja-Halkola, Ralf; D'Onofrio, Brian M; Iliadou, Anastasia N; Långström, Niklas; Lichtenstein, Paul

2010-12-01

In utero exposure to tobacco smoking has been suggested to cause persistent alterations in cognitive functioning. We examined if mothers' smoking during pregnancy (SDP) is associated with long-term impairment in offspring stress coping and the causal mechanism behind a possible link. We used a large cohort (n = 187,106) of young males in Sweden (mean age = 18.2 years), who underwent a semi-structured psychological assessment in 1997-2006, including an evaluation of stress coping ability, as part of the compulsory military conscript examination. We compared differentially exposed siblings within nuclear families and cousins in extended families and used multilevel structural equation models to disentangle genetic from environmental contributions to the association between SDP and stress coping. SDP and offspring stress coping was moderately strongly associated when comparing unrelated individuals [regression coefficient (b) = -0.38 on a nine-point scale; 95% confidence interval (CI) -0.40 to -0.36, P < 0.0001]. In contrast, it disappeared when siblings were compared (b = 0.11; 95% CI -0.01 to 0.23, P = 0.071). This familial confounding was entirely due to genetic influences. SDP is an established risk factor for pregnancy- and birth-related complications. However, we found no long-term effect of SDP on offspring stress coping. Rather, the observed association was due to familial confounding of genetic origin; women prone to SDP also transmit genes to their children that are associated with poorer coping with stress.

The biophysical properties of the aorta are altered following Kawasaki disease.

PubMed

Vaujois, Laurence; Dallaire, Frédéric; Maurice, Roch L; Fournier, Anne; Houde, Christine; Thérien, Johanne; Cartwright, Daniel; Dahdah, Nagib

2013-12-01

The long-term sequelae of Kawasaki disease (KD) are based on the coronary complications. Because KD causes generalized vasculitis, with documented aneurysms in the femoral, iliac, renal, axillary, and brachial arteries, the aim of this study was to assess the biophysical properties of the aorta (BPA) after KD. The BPA are biometric measurements representing vascular structural and dynamic changes in response to cardiac work. Anthropometric and echocardiographic measurements of the aorta in a series of patients with KD were compared with those of healthy subjects. The BPA were calculated noninvasively by extrapolating previously validated equations that were conceived for invasive measurements. Because BPA vary with body habitus, control subjects were used to normalize BPA parameters for height to compute BPA Z-score equations. Between June 2007 and February 2010, BPA were recorded in 57 patients with KD >1 year after the onset of the disease, 45 without and 12 with coronary artery sequelae. The mean intervals between the acute onset of KD and enrollment were 10.0 ± 5.0 and 5.8 ± 4.5 years for patients with and without coronary artery sequelae, respectively (P = .008). Patients with KD with coronary artery sequelae had significantly altered Z scores of aortic diameter modulation, Peterson's elastic modulus, and β stiffness index (P = .001-.016). Patients with KD without coronary artery sequelae also exhibited altered elasticity, stiffness, and pulse-wave velocity (P = .001-.026). Altered BPA after KD are detectible despite apparent resolution of acute vasculitis. Future directions toward determining multilevel and multilayer vascular impact, including vascular autonomous homeostasis, require thorough investigation. Copyright © 2013 American Society of Echocardiography. Published by Mosby, Inc. All rights reserved.

Social support and social strain among husbands and wives: a multilevel analysis.

PubMed

DeLongis, Anita; Capreol, Martha; Holtzman, Susan; O'Brien, Tess; Campbell, Jennifer

2004-09-01

In response to recent calls in the literature for within-person examinations of social support processes over time, this study explores the relationships of spousal support, spousal strain, and well-being among husbands and wives, both within the same day and across days. Eighty-three couples were interviewed and completed a structured diary twice daily for 1 week. The results of multilevel hierarchical modeling suggest that both spousal support and spousal strain made significant, independent contributions to concurrent negative affect, although only spousal support was a significant predictor of next-day negative affect. Spousal strain interacted with spousal support to predict next-day negative affect. Direct and moderating effects of perceived marital adjustment on negative affect were discussed. Copyright 2004 American Psychological Association

A multilevel approach to the relationship between birth order and intelligence.

PubMed

Wichman, Aaron L; Rodgers, Joseph Lee; MacCallum, Robert C

2006-01-01

Many studies show relationships between birth order and intelligence but use cross-sectional designs or manifest other threats to internal validity. Multilevel analyses with a control variable show that when these threats are removed, two major results emerge: (a) birth order has no significant influence on children's intelligence and (b) earlier reported birth order effects on intelligence are attributable to factors that vary between, not within, families. Analyses on 7- to 8 - and 13- to 14-year-old children from the National Longitudinal Survey of Youth support these conclusions. When hierarchical data structures, age variance of children, and within-family versus between-family variance sources are taken into account, previous research is seen in a new light.

Topology of Collisionless Relaxation

NASA Astrophysics Data System (ADS)

Pakter, Renato; Levin, Yan

2013-04-01

Using extensive molecular dynamics simulations we explore the fine-grained phase space structure of systems with long-range interactions. We find that if the initial phase space particle distribution has no holes, the final stationary distribution will also contain a compact simply connected region. The microscopic holes created by the filamentation of the initial distribution function are always restricted to the outer regions of the phase space. In general, for complex multilevel distributions it is very difficult to a priori predict the final stationary state without solving the full dynamical evolution. However, we show that, for multilevel initial distributions satisfying a generalized virial condition, it is possible to predict the particle distribution in the final stationary state using Casimir invariants of the Vlasov dynamics.

Linear and nonlinear spectroscopy from quantum master equations.

PubMed

Fetherolf, Jonathan H; Berkelbach, Timothy C

2017-12-28

We investigate the accuracy of the second-order time-convolutionless (TCL2) quantum master equation for the calculation of linear and nonlinear spectroscopies of multichromophore systems. We show that even for systems with non-adiabatic coupling, the TCL2 master equation predicts linear absorption spectra that are accurate over an extremely broad range of parameters and well beyond what would be expected based on the perturbative nature of the approach; non-equilibrium population dynamics calculated with TCL2 for identical parameters are significantly less accurate. For third-order (two-dimensional) spectroscopy, the importance of population dynamics and the violation of the so-called quantum regression theorem degrade the accuracy of TCL2 dynamics. To correct these failures, we combine the TCL2 approach with a classical ensemble sampling of slow microscopic bath degrees of freedom, leading to an efficient hybrid quantum-classical scheme that displays excellent accuracy over a wide range of parameters. In the spectroscopic setting, the success of such a hybrid scheme can be understood through its separate treatment of homogeneous and inhomogeneous broadening. Importantly, the presented approach has the computational scaling of TCL2, with the modest addition of an embarrassingly parallel prefactor associated with ensemble sampling. The presented approach can be understood as a generalized inhomogeneous cumulant expansion technique, capable of treating multilevel systems with non-adiabatic dynamics.

Linear and nonlinear spectroscopy from quantum master equations

NASA Astrophysics Data System (ADS)

Fetherolf, Jonathan H.; Berkelbach, Timothy C.

2017-12-01

We investigate the accuracy of the second-order time-convolutionless (TCL2) quantum master equation for the calculation of linear and nonlinear spectroscopies of multichromophore systems. We show that even for systems with non-adiabatic coupling, the TCL2 master equation predicts linear absorption spectra that are accurate over an extremely broad range of parameters and well beyond what would be expected based on the perturbative nature of the approach; non-equilibrium population dynamics calculated with TCL2 for identical parameters are significantly less accurate. For third-order (two-dimensional) spectroscopy, the importance of population dynamics and the violation of the so-called quantum regression theorem degrade the accuracy of TCL2 dynamics. To correct these failures, we combine the TCL2 approach with a classical ensemble sampling of slow microscopic bath degrees of freedom, leading to an efficient hybrid quantum-classical scheme that displays excellent accuracy over a wide range of parameters. In the spectroscopic setting, the success of such a hybrid scheme can be understood through its separate treatment of homogeneous and inhomogeneous broadening. Importantly, the presented approach has the computational scaling of TCL2, with the modest addition of an embarrassingly parallel prefactor associated with ensemble sampling. The presented approach can be understood as a generalized inhomogeneous cumulant expansion technique, capable of treating multilevel systems with non-adiabatic dynamics.

Multilevel sequential Monte Carlo samplers

DOE PAGES

Beskos, Alexandros; Jasra, Ajay; Law, Kody; ...

2016-08-24

Here, we study the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods and leading to a discretisation bias, with the step-size level h L. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretisation levelsmore » $${\\infty}$$ >h 0>h 1 ...>h L. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence of probability distributions. A sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. In conclusion, it is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context.« less

Coupled superconducting qudit-resonator system: Energy spectrum, state population, and state transition under microwave drive

NASA Astrophysics Data System (ADS)

Liu, W. Y.; Xu, H. K.; Su, F. F.; Li, Z. Y.; Tian, Ye; Han, Siyuan; Zhao, S. P.

2018-03-01

Superconducting quantum multilevel systems coupled to resonators have recently been considered in some applications such as microwave lasing and high-fidelity quantum logical gates. In this work, using an rf-SQUID type phase qudit coupled to a microwave coplanar waveguide resonator, we study both theoretically and experimentally the energy spectrum of the system when the qudit level spacings are varied around the resonator frequency by changing the magnetic flux applied to the qudit loop. We show that the experimental result can be well described by a theoretical model that extends from the usual two-level Jaynes-Cummings system to the present four-level system. It is also shown that due to the small anharmonicity of the phase device a simplified model capturing the leading state interactions fits the experimental spectra very well. Furthermore we use the Lindblad master equation containing various relaxation and dephasing processes to calculate the level populations in the simpler qutrit-resonator system, which allows a clear understanding of the dynamics of the system under the microwave drive. Our results help to better understand and perform the experiments of coupled multilevel and resonator systems and can be applied in the case of transmon or Xmon qudits having similar anharmonicity to the present phase device.

The Variance of Intraclass Correlations in Three- and Four-Level Models

ERIC Educational Resources Information Center

Hedges, Larry V.; Hedberg, E. C.; Kuyper, Arend M.

2012-01-01

Intraclass correlations are used to summarize the variance decomposition in populations with multilevel hierarchical structure. There has recently been considerable interest in estimating intraclass correlations from surveys or designed experiments to provide design parameters for planning future large-scale randomized experiments. The large…

The Variance of Intraclass Correlations in Three and Four Level

ERIC Educational Resources Information Center

Hedges, Larry V.; Hedberg, Eric C.; Kuyper, Arend M.

2012-01-01

Intraclass correlations are used to summarize the variance decomposition in popula- tions with multilevel hierarchical structure. There has recently been considerable interest in estimating intraclass correlations from surveys or designed experiments to provide design parameters for planning future large-scale randomized experiments. The large…

Bullying Victims' Perceptions of Classroom Interaction

ERIC Educational Resources Information Center

Havik, Trude

2017-01-01

This study investigated bullying victims' perceptions of their teachers' support and monitoring when controlling for level of mental health problems, peer relationships, gender, and grade level. Given the nested structure of the data, multilevel analyses were employed to examine these associations. The quality of classroom interaction is highly…

Bayesian Analysis of Structural Equation Models with Nonlinear Covariates and Latent Variables

ERIC Educational Resources Information Center

Song, Xin-Yuan; Lee, Sik-Yum

2006-01-01

In this article, we formulate a nonlinear structural equation model (SEM) that can accommodate covariates in the measurement equation and nonlinear terms of covariates and exogenous latent variables in the structural equation. The covariates can come from continuous or discrete distributions. A Bayesian approach is developed to analyze the…

Improvement of multi-level resistive switching characteristics in solution-processed AlO x -based non-volatile resistive memory using microwave irradiation

NASA Astrophysics Data System (ADS)

Kim, Seung-Tae; Cho, Won-Ju

2018-01-01

We fabricated a resistive random access memory (ReRAM) device on a Ti/AlO x /Pt structure with solution-processed AlO x switching layer using microwave irradiation (MWI), and demonstrated multi-level cell (MLC) operation. To investigate the effect of MWI power on the MLC characteristics, post-deposition annealing was performed at 600-3000 W after AlO x switching layer deposition, and the MLC operation was compared with as-deposited (as-dep) and conventional thermally annealing (CTA) treated devices. All solution-processed AlO x -based ReRAM devices exhibited bipolar resistive switching (BRS) behavior. We found that these devices have four-resistance states (2 bits) of MLC operation according to the modulation of the high-resistance state (HRSs) through reset voltage control. Particularly, compared to the as-dep and CTA ReRAM devices, the MWI-treated ReRAM devices showed a significant increase in the memory window and stable endurance for multi-level operation. Moreover, as the MWI power increased, excellent MLC characteristics were exhibited because the resistance ratio between each resistance state was increased. In addition, it exhibited reliable retention characteristics without deterioration at 25 °C and 85 °C for 10 000 s. Finally, the relationship between the chemical characteristics of the solution-processed AlO x switching layer and BRS-based multi-level operation according to the annealing method and MWI power was investigated using x-ray photoelectron spectroscopy.

Design of mulitlevel OLF approach ("V"-shaped decompressive laminoplasty) based on 3D printing technology.

PubMed

Ling, Qinjie; He, Erxing; Ouyang, Hanbin; Guo, Jing; Yin, Zhixun; Huang, Wenhua

2017-07-27

To introduce a new surgical approach to the multilevel ossification of the ligamentum flavum (OLF) aided by three-dimensional (3D) printing technology. A multilevel OLF patient (male, 66 years) was scanned using computed tomography (CT). His saved DICOM format data were inputted to the Mimics14.0 3D reconstruction software (Materialise, Belgium). The resulting 3D model was used to observe the anatomical features of the multilevel OLF area and to design the surgical approach. At the base of the spinous process, two channels were created using an osteotomy bilaterally to create a "V" shape to remove the bone ligamentous complex (BLC). The decompressive laminoplasty using mini-plate fixation was simulated with the computer. The physical model was manufactured using 3D printing technology. The patient was subsequently treated using the designed surgery. The operation was completed successfully without any complications. The operative time was 90 min, and blood loss was 200 ml. One month after the operation, neurologic function was recovered well, and the JOA score was improved from 6 preoperatively to 10. Postoperative CT scanning showed that the OLF was totally removed, and the replanted BLC had not subsided. 3D printing technology is an effective, reliable, and minimally invasive method to design operations. The technique can be an option for multilevel OLF surgical treatment. This can provide sufficient decompression with minimum damage to the spine and other intact anatomical structures.

Prolongation structures of nonlinear evolution equations

NASA Technical Reports Server (NTRS)

Wahlquist, H. D.; Estabrook, F. B.

1975-01-01

A technique is developed for systematically deriving a 'prolongation structure' - a set of interrelated potentials and pseudopotentials - for nonlinear partial differential equations in two independent variables. When this is applied to the Korteweg-de Vries equation, a new infinite set of conserved quantities is obtained. Known solution techniques are shown to result from the discovery of such a structure: related partial differential equations for the potential functions, linear 'inverse scattering' equations for auxiliary functions, Backlund transformations. Generalizations of these techniques will result from the use of irreducible matrix representations of the prolongation structure.

Multilevel Model Prediction

ERIC Educational Resources Information Center

Frees, Edward W.; Kim, Jee-Seon

2006-01-01

Multilevel models are proven tools in social research for modeling complex, hierarchical systems. In multilevel modeling, statistical inference is based largely on quantification of random variables. This paper distinguishes among three types of random variables in multilevel modeling--model disturbances, random coefficients, and future response…

A multilevel preconditioner for domain decomposition boundary systems

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

Bramble, J.H.; Pasciak, J.E.; Xu, Jinchao.

1991-12-11

In this note, we consider multilevel preconditioning of the reduced boundary systems which arise in non-overlapping domain decomposition methods. It will be shown that the resulting preconditioned systems have condition numbers which be bounded in the case of multilevel spaces on the whole domain and grow at most proportional to the number of levels in the case of multilevel boundary spaces without multilevel extensions into the interior.

3D spine reconstruction of postoperative patients from multi-level manifold ensembles.

PubMed

Kadoury, Samuel; Labelle, Hubert; Parent, Stefan

2014-01-01

The quantitative assessment of surgical outcomes using personalized anatomical models is an essential task for the treatment of spinal deformities such as adolescent idiopathic scoliosis. However an accurate 3D reconstruction of the spine from postoperative X-ray images remains challenging due to presence of instrumentation (metallic rods and screws) occluding vertebrae on the spine. In this paper, we formulate the reconstruction problem as an optimization over a manifold of articulated spine shapes learned from pathological training data. The manifold itself is represented using a novel data structure, a multi-level manifold ensemble, which contains links between nodes in a single hierarchical structure, as well as links between different hierarchies, representing overlapping partitions. We show that this data structure allows both efficient localization and navigation on the manifold, for on-the-fly building of local nonlinear models (manifold charting). Our reconstruction framework was tested on pre- and postoperative X-ray datasets from patients who underwent spinal surgery. Compared to manual ground-truth, our method achieves a 3D reconstruction accuracy of 2.37 +/- 0.85 mm for postoperative spine models and can deal with severe cases of scoliosis.

Structural Equation Modeling of Multivariate Time Series

ERIC Educational Resources Information Center

du Toit, Stephen H. C.; Browne, Michael W.

2007-01-01

The covariance structure of a vector autoregressive process with moving average residuals (VARMA) is derived. It differs from other available expressions for the covariance function of a stationary VARMA process and is compatible with current structural equation methodology. Structural equation modeling programs, such as LISREL, may therefore be…

Alternative bi-Hamiltonian structures for WDVV equations of associativity

NASA Astrophysics Data System (ADS)

Kalayci, J.; Nutku, Y.

1998-01-01

The WDVV equations of associativity in two-dimensional topological field theory are completely integrable third-order Monge-Ampère equations which admit bi-Hamiltonian structure. The time variable plays a distinguished role in the discussion of Hamiltonian structure, whereas in the theory of WDVV equations none of the independent variables merits such a distinction. WDVV equations admit very different alternative Hamiltonian structures under different possible choices of the time variable, but all these various Hamiltonian formulations can be brought together in the framework of the covariant theory of symplectic structure. They can be identified as different components of the covariant Witten-Zuckerman symplectic 2-form current density where a variational formulation of the WDVV equation that leads to the Hamiltonian operator through the Dirac bracket is available.

Re-Imagining Archival Display: Creating User-Friendly Finding Aids

ERIC Educational Resources Information Center

Daines, J. Gordon, III; Nimer, Cory L.

2011-01-01

This article examines how finding aids are structured and delivered, considering alternative approaches. It suggests that single-level displays, those that present a single component of a multilevel description to users at a time, have the potential to transform the delivery and display of collection information while improving the user…

Exploring Pattern of Socialisation Conditions and Human Development by Nonlinear Multivariate Analysis.

ERIC Educational Resources Information Center

Grundmann, Matthias

Following the assumptions of ecological socialization research, adequate analysis of socialization conditions must take into account the multilevel and multivariate structure of social factors that impact on human development. This statement implies that complex models of family configurations or of socialization factors are needed to explain the…

Race, Sex, and Discrimination in School Settings: A Multilevel Analysis of Associations with Delinquency

ERIC Educational Resources Information Center

Chambers, Brittany D.; Erausquin, Jennifer Toller

2018-01-01

Background: Adolescence is a critical phase of development and experimentation with delinquent behaviors. There is a growing body of literature exploring individual and structural impacts of discrimination on health outcomes and delinquent behaviors. However, there is limited research assessing how school diversity and discrimination impact…

Multilevel Design of School Effectiveness Studies in Sub-Saharan Africa

ERIC Educational Resources Information Center

Kelcey, Ben; Shen, Zuchao

2016-01-01

School-based improvement programs represent a core strategy in improving education because they can leverage pre-existing social and organizational structures to promote coordinated and comprehensive change across multiple facets of schooling. School-based programs are generally designed to be implemented by intact schools/districts, frequently…

Dimensions of Cultural Differences: Pancultural, ETIC/EMIC, and Ecological Approaches

ERIC Educational Resources Information Center

Stankov, Lazar; Lee, Jihyun

2009-01-01

We investigated the factorial structure of four major domains in social psychology (personality traits, social attitudes, values, and social norms) with an emphasis on cross-cultural differences. Three distinctive approaches--pancultural, multigroup, and multilevel--were applied to the data based on 22 measures that were collected from 2029…

Optimal Design for Regression Discontinuity Studies with Clustering

ERIC Educational Resources Information Center

Rhoads, Christopher; Dye, Charles

2014-01-01

Recent years have seen an increased interest in quantitative educational research studies that use random assignment (RA) to evaluate the causal impacts of educational interventions (Angrist, 2004). The multi-level structure of the public education system in the United States often leads to experimental designs where naturally occurring clusters…

Optimal Design for Two-Level Random Assignment and Regression Discontinuity Studies

ERIC Educational Resources Information Center

Rhoads, Christopher H.; Dye, Charles

2016-01-01

An important concern when planning research studies is to obtain maximum precision of an estimate of a treatment effect given a budget constraint. When research designs have a "multilevel" or "hierarchical" structure changes in sample size at different levels of the design will impact precision differently. Furthermore, there…

Factors Underlying Contextual Variations in the Structure of the Self: Differences Related to SES, Gender, Culture, and "Majority/Nonmajority" Status during Early Adolescence

ERIC Educational Resources Information Center

Santo, Jonathan Bruce; Bukowski, William M.; Stella-Lopez, Luz; Carmago, Gina; Mayman, Shari B.; Adams, Ryan E.

2013-01-01

Multilevel modeling was used to examine contextual variations in the structure of the "self" in a sample of 918 lower- and upper-middle class early adolescents (M age = 10.37 years, SD = 1.19) from a "majority" cultural context (i.e., Barranquilla in the Caribbean region of Colombia) and a "nonmajority" context (i.e.,…

Hamiltonian structure of the Lotka-Volterra equations

NASA Astrophysics Data System (ADS)

Nutku, Y.

1990-03-01

The Lotka-Volterra equations governing predator-prey relations are shown to admit Hamiltonian structure with respect to a generalized Poisson bracket. These equations provide an example of a system for which the naive criterion for the existence of Hamiltonian structure fails. We show further that there is a three-component generalization of the Lotka-Volterra equations which is a bi-Hamiltonian system.

Behavioral and neuronal determinants of negative reciprocity in the ultimatum game

PubMed Central

Hildebrandt, Andrea; Wilhelm, Oliver; Sommer, Werner

2016-01-01

The rejection of unfair offers in the ultimatum game (UG) indicates negative reciprocity. The model of strong reciprocity claims that negative reciprocity reflects prosociality because the rejecting individual is sacrificing resources in order to punish unfair behavior. However, a recent study found that the rejection rate of unfair offers is linked to assertiveness (status defense model). To pursue the question what drives negative reciprocity, the present study investigated individual differences in the rejection of unfair offers along with their behavioral and neuronal determinants. We measured fairness preferences and event-related potentials (ERP) in 200 healthy participants playing a computerized version of the UG with pictures of unfair and fair proposers. Structural equation modeling (SEM) on the behavioral data corroborated both the strong reciprocity and the status defense models of human cooperation: Not only more prosocial but also more assertive individuals were more likely to show negative reciprocity by rejecting unfair offers. Experimental ERP results confirmed the feedback negativity (FN) as a neural signature of fairness processing. Multilevel SEM of brain–behavior relationships revealed that negative reciprocity was significantly associated with individual differences in FN amplitudes in response to proposers. Our results confirm stable individual differences in fairness processing at the behavioral and neuronal level. PMID:27261490

Going the extra mile and feeling energized: An enrichment perspective of organizational citizenship behaviors.

PubMed

Lam, Chak Fu; Wan, Wylie H; Roussin, Christopher J

2016-03-01

Scholars have voiced concerns about the potential dark side of Organizational Citizenship Behavior (OCB), arguing that OCB consumes energy, which contributes to a depletion of personal resources and results in poorer well-being. Drawing from research on the meaningfulness of work, we propose a pattern opposite to depletion: that OCB enhances energy, which contributes to an enrichment of personal resources and results in better well-being. This idea was tested over the course of a workweek with 224 day-level ratings from 67 employees and 30 managers working in a service management firm. Three-level hierarchical linear modeling indicated that supervisor-rated daily OCB was positively associated with employees' vigor at the end of the workday, and multilevel structural equation modeling analyses showed that this relationship was mediated by meaningfulness of work. Moreover, we found that the association between OCB and work meaningfulness was stronger for employees with greater role ambiguity. Exploratory analyses revealed that daily in-role performance and daily OCB interacted to predict meaningfulness of work, such that the association between daily OCB and meaningfulness of work was more prominent among those who exhibited high levels of daily in-role performance. We discuss implications of these findings, limitations, and directions for future research. (c) 2016 APA, all rights reserved).

Multiscale modeling of fluid flow and mass transport

NASA Astrophysics Data System (ADS)

Masuoka, K.; Yamamoto, H.; Bijeljic, B.; Lin, Q.; Blunt, M. J.

2017-12-01

In recent years, there are some reports on a simulation of fluid flow in pore spaces of rocks using Navier-Stokes equations. These studies mostly adopt a X-ray CT to create 3-D numerical grids of the pores in micro-scale. However, results may be of low accuracy when the rock has a large pore size distribution, because pores, whose size is smaller than resolution of the X-ray CT may be neglected. We recently found out by tracer tests in a laboratory using a brine saturated Ryukyu limestone and inject fresh water that a decrease of chloride concentration took longer time. This phenomenon can be explained due to weak connectivity of the porous networks. Therefore, it is important to simulate entire pore spaces even those of very small sizes in which diffusion is dominant. We have developed a new methodology for multi-level modeling for pore scale fluid flow in porous media. The approach is to combine pore-scale analysis with Darcy-flow analysis using two types of X-ray CT images in different resolutions. Results of the numerical simulations showed a close match with the experimental results. The proposed methodology is an enhancement for analyzing mass transport and flow phenomena in rocks with complicated pore structure.

School environments and obesity: The mediating role of personal stress

PubMed Central

Milam, Adam J.; Jones, Chandria D.; Debnam, Katrina J.; Bradshaw, Catherine P.

2018-01-01

Background Youth spend a large amount of time in the school environment. Given the multiple influences of teachers, peers, and food and physical activity options, youth are likely to experience stressors that can influence their weight. This study examines the association between school climate and weight status. Method Students (n = 28,582; 58 schools) completed an online, anonymous school climate survey as part of the Maryland Safe and Supportive Schools Project. Multilevel structural equation modeling was used to explore the association between school climate, personal stress, and obesity. Analyses were stratified by gender. Results At the individual level, poor school climate (bullying, physical safety, and lack of whole-school connectedness) was associated with an increased likelihood of being overweight among females (β =.115, p = .019) but not males (β = .138; p =.244), after controlling for age, race, and physical activity. There was no association between school climate at the school level and being overweight among males or females. A second model included stress as a potential mediator; stress attenuated the relationship between poor school-related climate and being overweight (β = .039; p = .048) among females. Conclusion Findings suggest that stress related to school climate can play a role in the health and weight status of youth. PMID:29731524

Examining classroom influences on student perceptions of school climate: the role of classroom management and exclusionary discipline strategies.

PubMed

Mitchell, Mary M; Bradshaw, Catherine P

2013-10-01

There is growing emphasis on the use of positive behavior supports rather than exclusionary discipline strategies to promote a positive classroom environment. Yet, there has been limited research examining the association between these two different approaches to classroom management and students' perceptions of school climate. Data from 1902 students within 93 classrooms that were nested within 37 elementary schools were examined using multilevel structural equation modeling procedures to investigate the association between two different classroom management strategies (i.e., exclusionary discipline strategies and the use of positive behavior supports) and student ratings of school climate (i.e., fairness, order and discipline, student-teacher relationship, and academic motivation). The analyses indicated that greater use of exclusionary discipline strategies was associated with lower order and discipline scores, whereas greater use of classroom-based positive behavior supports was associated with higher scores on order and discipline, fairness, and student-teacher relationship. These findings suggest that pre-service training and professional development activities should promote teachers' use of positive behavior support strategies and encourage reduced reliance on exclusionary discipline strategies in order to enhance the school climate and conditions for learning. Copyright © 2013 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Newcomer adjustment: Examining the role of managers' perception of newcomer proactive behavior during organizational socialization.

PubMed

Ellis, Allison M; Nifadkar, Sushil S; Bauer, Talya N; Erdogan, Berrin

2017-06-01

Separate streams of organizational socialization research have recognized the importance of (a) newcomer proactivity and (b) manager support in facilitating newcomer adjustment. However, extant research has largely focused on the newcomers' experience, leaving the perspectives of managers during socialization relatively unexplored-a theoretical gap that has implications both for newcomer adjustment and manager-newcomer interactions that may serve as a basis for future relationship development. Drawing from the "interlocked" employee behavior argument of Weick (1979), we propose that managers' perception of newcomers' proactive behaviors are associated with concordant manager behaviors, which, in turn, support newcomer adjustment. Further, we investigate a cognitive mechanism-managers' evaluation of newcomers' commitment to adjust-which we expect underlies the proposed relationship between newcomers' proactive behaviors and managers' supportive behaviors. Using a time-lagged, 4-phase data collection of a sample of new software engineers in India and their managers, we were able to test our hypothesized model as well as rule out alternative explanations via multilevel structural equation modeling. Results broadly supported our model even after controlling for manager-newcomer social exchange relationship, proactive personalities of both newcomers and managers, and potential effects of coworker information providing. The implications of our findings for theory and practice are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Longitudinal Linkages among Parent-Child Acculturation Discrepancy, Parenting, Parent-Child Sense of Alienation, and Adolescent Adjustment in Chinese Immigrant Families

PubMed Central

Kim, Su Yeong; Chen, Qi; Wang, Yijie; Shen, Yishan; Orozco-Lapray, Diana

2012-01-01

Parent-child acculturation discrepancy is a risk factor in the development of children in immigrant families. Using a longitudinal sample of Chinese immigrant families, the current study examined how unsupportive parenting and parent-child sense of alienation sequentially mediate the relationship between parent-child acculturation discrepancy and child adjustment during early and middle adolescence. Acculturation discrepancy scores were created using multilevel modeling to take into account the interdependence among family members. Structural equation models showed that, during early adolescence, parent-child American orientation discrepancy is related to parents’ use of unsupportive parenting practices; parents’ use of unsupportive parenting is related to increased sense of alienation between parents and children, which in turn is related to more depressive symptoms and lower academic performance in Chinese American adolescents. These patterns of negative adjustment established in early adolescence persist into middle adolescence. This mediating effect is more apparent among father-adolescent dyads than among mother-adolescent dyads. In contrast, parent-child Chinese orientation discrepancy does not demonstrate a significant direct or indirect effect on adolescent adjustment, either concurrently or longitudinally. The current findings suggest that early adolescence is more susceptible to the negative effects of parent-child acculturation discrepancy; they also underscore the importance of fathering in Chinese immigrant families. PMID:22799587

A test of basic psychological needs theory in young soccer players: time-lagged design at the individual and team levels.

PubMed

González, L; Tomás, I; Castillo, I; Duda, J L; Balaguer, I

2017-11-01

Within the framework of basic psychological needs theory (Deci & Ryan, 2000), multilevel structural equation modeling (MSEM) with a time-lagged design was used to test a mediation model examining the relationship between perceptions of coaches' interpersonal styles (autonomy supportive and controlling), athletes' basic psychological needs (satisfaction and thwarting), and indicators of well-being (subjective vitality) and ill-being (burnout), estimating separately between and within effects. The participants were 597 Spanish male soccer players aged between 11 and 14 years (M = 12.57, SD = 0.54) from 40 teams who completed a questionnaire package at two time points in a competitive season. Results revealed that at the individual level, athletes' perceptions of autonomy support positively predicted athletes' need satisfaction (autonomy, competence, and relatedness), whereas athletes' perceptions of controlling style positively predicted athletes' need thwarting (autonomy, competence, and relatedness). In turn, all three athletes' need satisfaction dimensions predicted athletes' subjective vitality and burnout (positively and negatively, respectively), whereas competence thwarting negatively predicted subjective vitality and competence and relatedness positively predicted burnout. At the team level, team perceptions of autonomy supportive style positively predicted team autonomy and relatedness satisfaction. Mediation effects only appeared at the individual level. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.