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.

The Impacts of 3-D Earth Structure on GIA-Induced Crustal Deformation and Future Sea-Level Change in the Antarctic

NASA Astrophysics Data System (ADS)

Powell, E. M.; Hay, C.; Latychev, K.; Gomez, N. A.; Mitrovica, J. X.

2016-12-01

Glacial Isostatic Adjustment (GIA) models used to constrain the extent of past ice sheets and viscoelastic Earth structure, or to correct geodetic and geological observables for ice age effects, generally only consider depth-dependent variations in Earth viscosity and lithospheric structure. A et al. [2013] argued that 3-D Earth structure could impact GIA observables in Antarctica, but concluded that the presence of such structure contributes less to GIA uncertainty than do differences in Antarctic deglaciation histories. New seismic and geological evidence, however, indicates the Antarctic is underlain by complex, high amplitude variability in viscoelastic structure, including a low viscosity zone (LVZ) under West Antarctica. Hay et al. [2016] showed that sea-level fingerprints of modern melting calculated using such Earth models differ from those based on elastic or 1-D viscoelastic Earth models within decades of melting. Our investigation is motivated by two questions: (1) How does 3-D Earth structure, especially this LVZ, impact observations of GIA-induced crustal deformation associated with the last deglaciation? (2) How will 3-D Earth structure affect predictions of future sea-level rise in Antarctica? We compute the gravitationally self-consistent sea level, uplift, and gravity changes using the finite volume treatment of Latychev et al. [2005]. We consider four viscoelastic Earth models: a global 1-D model; a regional, West Antarctic-like 1-D model; a 3-D model where the lithospheric thickness varies laterally; and a 3-D model where both viscosity and lithospheric thickness vary laterally. For our Last Glacial Maximum to present investigations we employ ICE6g [Peltier et al., 2015]. For our present-future investigations we consider a melt scenario consistent with GRACE satellite gravity derived solutions [Harig et al., 2015]. Our calculations indicate that predictions of crustal deformations due to both GIA and ongoing melting are strongly influenced by 3-D lithospheric thickness and viscosity structure. Future sea level change due to ongoing melting is primarily influenced by 3-D viscosity structure. We show that 1-D Earth models built using regional inferences of viscosity and lithospheric thickness do not accurately capture the variability introduced by 3-D Earth structure.

The Impacts of 3-D Earth Structure on GIA-Induced Crustal Deformation and Future Sea-Level Change in the Antarctic

NASA Astrophysics Data System (ADS)

Powell, E. M.; Hay, C.; Latychev, K.; Gomez, N. A.; Mitrovica, J. X.

2017-12-01

Glacial Isostatic Adjustment (GIA) models used to constrain the extent of past ice sheets and viscoelastic Earth structure, or to correct geodetic and geological observables for ice age effects, generally only consider depth-dependent variations in Earth viscosity and lithospheric structure. A et al. [2013] argued that 3-D Earth structure could impact GIA observables in Antarctica, but concluded that the presence of such structure contributes less to GIA uncertainty than do differences in Antarctic deglaciation histories. New seismic and geological evidence, however, indicates the Antarctic is underlain by complex, high amplitude variability in viscoelastic structure, including a low viscosity zone (LVZ) under West Antarctica. Hay et al. [2016] showed that sea-level fingerprints of modern melting calculated using such Earth models differ from those based on elastic or 1-D viscoelastic Earth models within decades of melting. Our investigation is motivated by two questions: (1) How does 3-D Earth structure, especially this LVZ, impact observations of GIA-induced crustal deformation associated with the last deglaciation? (2) How will 3-D Earth structure affect predictions of future sea-level rise in Antarctica? We compute the gravitationally self-consistent sea level, uplift, and gravity changes using the finite volume treatment of Latychev et al. [2005]. We consider four viscoelastic Earth models: a global 1-D model; a regional, West Antarctic-like 1-D model; a 3-D model where the lithospheric thickness varies laterally; and a 3-D model where both viscosity and lithospheric thickness vary laterally. For our Last Glacial Maximum to present investigations we employ ICE6g [Peltier et al., 2015]. For our present-future investigations we consider a melt scenario consistent with GRACE satellite gravity derived solutions [Harig et al., 2015]. Our calculations indicate that predictions of crustal deformations due to both GIA and ongoing melting are strongly influenced by 3-D lithospheric thickness and viscosity structure. Future sea level change due to ongoing melting is primarily influenced by 3-D viscosity structure. We show that 1-D Earth models built using regional inferences of viscosity and lithospheric thickness do not accurately capture the variability introduced by 3-D Earth structure.

A level set-based topology optimization method for simultaneous design of elastic structure and coupled acoustic cavity using a two-phase material model

NASA Astrophysics Data System (ADS)

Noguchi, Yuki; Yamamoto, Takashi; Yamada, Takayuki; Izui, Kazuhiro; Nishiwaki, Shinji

2017-09-01

This papers proposes a level set-based topology optimization method for the simultaneous design of acoustic and structural material distributions. In this study, we develop a two-phase material model that is a mixture of an elastic material and acoustic medium, to represent an elastic structure and an acoustic cavity by controlling a volume fraction parameter. In the proposed model, boundary conditions at the two-phase material boundaries are satisfied naturally, avoiding the need to express these boundaries explicitly. We formulate a topology optimization problem to minimize the sound pressure level using this two-phase material model and a level set-based method that obtains topologies free from grayscales. The topological derivative of the objective functional is approximately derived using a variational approach and the adjoint variable method and is utilized to update the level set function via a time evolutionary reaction-diffusion equation. Several numerical examples present optimal acoustic and structural topologies that minimize the sound pressure generated from a vibrating elastic structure.

Optical potentials for nuclear level structures and nucleon interactions data of tin isotopes based on the soft-rotator model

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

Lee, Jeong-Yeon; Hahn, Insik; Kim, Yeongduk

2009-06-15

The soft-rotator model is applied to self-consistent analyses of the nuclear level structures and the nucleon interaction data of the even-even Sn isotopes, {sup 116}Sn, {sup 118}Sn, {sup 120}Sn, and {sup 122}Sn. The model successfully describes low-lying collective levels of these isotopes, which exhibit neither typical rotational nor harmonic vibrational structures. The experimental nucleon interaction data--total neutron cross sections, proton reaction cross sections, and nucleon elastic and inelastic scattering data--are well described up to 200 MeV in a coupled-channels optical model approach. For the calculations, nuclear wave functions for the Sn isotopes are taken from the nonaxial soft-rotator model withmore » the model parameters adjusted to fit the measured low-lying collective level structures. We find that the {beta}{sub 2} and {beta}{sub 3} deformations for incident protons are larger than those for incident neutrons by {approx}15%, which is clear evidence of the deviation from the pure collective model for these isotopes.« less

Application of viscous and Iwan modal damping models to experimental measurements from bolted structures

DOE PAGES

Deaner, Brandon J.; Allen, Matthew S.; Starr, Michael James; ...

2015-01-20

Measurements are presented from a two-beam structure with several bolted interfaces in order to characterize the nonlinear damping introduced by the joints. The measurements (all at force levels below macroslip) reveal that each underlying mode of the structure is well approximated by a single degree-of-freedom (SDOF) system with a nonlinear mechanical joint. At low enough force levels, the measurements show dissipation that scales as the second power of the applied force, agreeing with theory for a linear viscously damped system. This is attributed to linear viscous behavior of the material and/or damping provided by the support structure. At larger forcemore » levels, the damping is observed to behave nonlinearly, suggesting that damping from the mechanical joints is dominant. A model is presented that captures these effects, consisting of a spring and viscous damping element in parallel with a four-parameter Iwan model. As a result, the parameters of this model are identified for each mode of the structure and comparisons suggest that the model captures the stiffness and damping accurately over a range of forcing levels.« less

Constrained Maximum Likelihood Estimation for Two-Level Mean and Covariance Structure Models

ERIC Educational Resources Information Center

Bentler, Peter M.; Liang, Jiajuan; Tang, Man-Lai; Yuan, Ke-Hai

2011-01-01

Maximum likelihood is commonly used for the estimation of model parameters in the analysis of two-level structural equation models. Constraints on model parameters could be encountered in some situations such as equal factor loadings for different factors. Linear constraints are the most common ones and they are relatively easy to handle in…

A Bayesian Approach for Analyzing Longitudinal Structural Equation Models

ERIC Educational Resources Information Center

Song, Xin-Yuan; Lu, Zhao-Hua; Hser, Yih-Ing; Lee, Sik-Yum

2011-01-01

This article considers a Bayesian approach for analyzing a longitudinal 2-level nonlinear structural equation model with covariates, and mixed continuous and ordered categorical variables. The first-level model is formulated for measures taken at each time point nested within individuals for investigating their characteristics that are dynamically…

Image/video understanding systems based on network-symbolic models

NASA Astrophysics Data System (ADS)

Kuvich, Gary

2004-03-01

Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolve ambiguity and uncertainty via feedback projections, and provide image understanding that is an interpretation of visual information in terms of such knowledge models. Computer simulation models are built on the basis of graphs/networks. The ability of human brain to emulate similar graph/network models is found. Symbols, predicates and grammars naturally emerge in such networks, and logic is simply a way of restructuring such models. Brain analyzes an image as a graph-type relational structure created via multilevel hierarchical compression of visual information. Primary areas provide active fusion of image features on a spatial grid-like structure, where nodes are cortical columns. Spatial logic and topology naturally present in such structures. Mid-level vision processes like perceptual grouping, separation of figure from ground, are special kinds of network transformations. They convert primary image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena are results of such analysis. Composition of network-symbolic models combines learning, classification, and analogy together with higher-level model-based reasoning into a single framework, and it works similar to frames and agents. Computational intelligence methods transform images into model-based knowledge representation. Based on such principles, an Image/Video Understanding system can convert images into the knowledge models, and resolve uncertainty and ambiguity. This allows creating intelligent computer vision systems for design and manufacturing.

A Systematic Approach for Identifying Level-1 Error Covariance Structures in Latent Growth Modeling

ERIC Educational Resources Information Center

Ding, Cherng G.; Jane, Ten-Der; Wu, Chiu-Hui; Lin, Hang-Rung; Shen, Chih-Kang

2017-01-01

It has been pointed out in the literature that misspecification of the level-1 error covariance structure in latent growth modeling (LGM) has detrimental impacts on the inferences about growth parameters. Since correct covariance structure is difficult to specify by theory, the identification needs to rely on a specification search, which,…

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.

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

Model Updating of Complex Structures Using the Combination of Component Mode Synthesis and Kriging Predictor

PubMed Central

Li, Yan; Wang, Dejun; Zhang, Shaoyi

2014-01-01

Updating the structural model of complex structures is time-consuming due to the large size of the finite element model (FEM). Using conventional methods for these cases is computationally expensive or even impossible. A two-level method, which combined the Kriging predictor and the component mode synthesis (CMS) technique, was proposed to ensure the successful implementing of FEM updating of large-scale structures. In the first level, the CMS was applied to build a reasonable condensed FEM of complex structures. In the second level, the Kriging predictor that was deemed as a surrogate FEM in structural dynamics was generated based on the condensed FEM. Some key issues of the application of the metamodel (surrogate FEM) to FEM updating were also discussed. Finally, the effectiveness of the proposed method was demonstrated by updating the FEM of a real arch bridge with the measured modal parameters. PMID:24634612

Multilayer network of language: A unified framework for structural analysis of linguistic subsystems

NASA Astrophysics Data System (ADS)

Martinčić-Ipšić, Sanda; Margan, Domagoj; Meštrović, Ana

2016-09-01

Recently, the focus of complex networks' research has shifted from the analysis of isolated properties of a system toward a more realistic modeling of multiple phenomena - multilayer networks. Motivated by the prosperity of multilayer approach in social, transport or trade systems, we introduce the multilayer networks for language. The multilayer network of language is a unified framework for modeling linguistic subsystems and their structural properties enabling the exploration of their mutual interactions. Various aspects of natural language systems can be represented as complex networks, whose vertices depict linguistic units, while links model their relations. The multilayer network of language is defined by three aspects: the network construction principle, the linguistic subsystem and the language of interest. More precisely, we construct a word-level (syntax and co-occurrence) and a subword-level (syllables and graphemes) network layers, from four variations of original text (in the modeled language). The analysis and comparison of layers at the word and subword-levels are employed in order to determine the mechanism of the structural influences between linguistic units and subsystems. The obtained results suggest that there are substantial differences between the networks' structures of different language subsystems, which are hidden during the exploration of an isolated layer. The word-level layers share structural properties regardless of the language (e.g. Croatian or English), while the syllabic subword-level expresses more language dependent structural properties. The preserved weighted overlap quantifies the similarity of word-level layers in weighted and directed networks. Moreover, the analysis of motifs reveals a close topological structure of the syntactic and syllabic layers for both languages. The findings corroborate that the multilayer network framework is a powerful, consistent and systematic approach to model several linguistic subsystems simultaneously and hence to provide a more unified view on language.

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.

Computational Modeling of Airway and Pulmonary Vascular Structure and Function: Development of a “Lung Physiome”

PubMed Central

Tawhai, M. H.; Clark, A. R.; Donovan, G. M.; Burrowes, K. S.

2011-01-01

Computational models of lung structure and function necessarily span multiple spatial and temporal scales, i.e., dynamic molecular interactions give rise to whole organ function, and the link between these scales cannot be fully understood if only molecular or organ-level function is considered. Here, we review progress in constructing multiscale finite element models of lung structure and function that are aimed at providing a computational framework for bridging the spatial scales from molecular to whole organ. These include structural models of the intact lung, embedded models of the pulmonary airways that couple to model lung tissue, and models of the pulmonary vasculature that account for distinct structural differences at the extra- and intra-acinar levels. Biophysically based functional models for tissue deformation, pulmonary blood flow, and airway bronchoconstriction are also described. The development of these advanced multiscale models has led to a better understanding of complex physiological mechanisms that govern regional lung perfusion and emergent heterogeneity during bronchoconstriction. PMID:22011236

Epistemological beliefs of physics undergraduate and graduate students and faculty in the context of a well-structured and an ill-structured problem

NASA Astrophysics Data System (ADS)

Mercan, Fatih C.

This study examines epistemological beliefs of physics undergraduate and graduate students and faculty in the context of solving a well-structured and an ill-structured problem. The data collection consisted of a think aloud problem solving session followed by a semi-structured interview conducted with 50 participants, 10 participants at freshmen, seniors, masters, PhD, and faculty levels. The data analysis involved (a) identification of the range of beliefs about knowledge in the context of the well-structured and the ill-structured problem solving, (b) construction of a framework that unites the individual beliefs identified in each problem context under the same conceptual base, and (c) comparisons of the problem contexts and expertise level groups using the framework. The results of the comparison of the contexts of the well-structured and the ill-structured problem showed that (a) authoritative beliefs about knowledge were expressed in the well-structured problem context, (b) relativistic and religious beliefs about knowledge were expressed in the ill-structured problem context, and (c) rational, empirical, modeling beliefs about knowledge were expressed in both problem contexts. The results of the comparison of the expertise level groups showed that (a) undergraduates expressed authoritative beliefs about knowledge more than graduate students and faculty did not express authoritative beliefs, (b) faculty expressed modeling beliefs about knowledge more than graduate students and undergraduates did not express modeling beliefs, and (c) there were no differences in rational, empirical, experiential, relativistic, and religious beliefs about knowledge among the expertise level groups. As the expertise level increased the number of participants who expressed authoritative beliefs about knowledge decreased and the number of participants who expressed modeling based beliefs about knowledge increased. The results of this study implied that existing developmental and cognitive models of personal epistemology can explain personal epistemology in physics to a limited extent, however, these models cannot adequately account for the variation of epistemological beliefs across problem contexts. Modeling beliefs about knowledge emerged as a part of personal epistemology and an indicator of epistemological sophistication, which do not develop until extensive experience in the field. Based on these findings, the researcher recommended providing opportunities for practicing model construction for students.

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…

Strategy for the management of substance use disorders in the State of Punjab: Developing a structural model of state-level de-addiction services in the health sector (the “Punjab model”)

PubMed Central

Basu, Debasish; Avasthi, Ajit

2015-01-01

Background: Substance use disorders are believed to have become rampant in the State of Punjab, causing substantive loss to the person, the family, the society, and the state. The situation is likely to worsen further if a structured, government-level, state-wide de-addiction service is not put into place. Aims: The aim was to describe a comprehensive structural model of de-addiction service in the State of Punjab (the “Pyramid model” or “Punjab model”), which is primarily concerned with demand reduction, particularly that part which is concerned with identification, treatment, and aftercare of substance users. Materials and Methods: At the behest of the Punjab Government, this model was developed by the authors after a detailed study of the current scenario, critical and exhaustive look at the existing guidelines, policies, books, web resources, government documents, and the like in this area, a check of the ground reality in terms of existing infrastructural and manpower resources, and keeping pragmatism and practicability in mind. Several rounds of meetings with the government officials and other important stakeholders helped to refine the model further. Results: Our model envisages structural innovation and renovations within the existing state healthcare infrastructure. We formulated a “Pyramid model,” later renamed as “Punjab model,” where there is a broad community base for early identification and outpatient level treatment at the primary care level, both outpatient and inpatient care at the secondary care level, and comprehensive management for more difficult cases at the tertiary care level. A separate de-addiction system for the prisons was also developed. Each of these structural elements was described and refined in details, with the aim of uniform, standardized, and easily accessible care across the state. Conclusions: If the “Punjab model” succeeds, it can provide useful models for other states or even at the national level. PMID:25657452

Viking Mars lander 1975 dynamic test model/orbiter developmental test model forced vibration test

NASA Technical Reports Server (NTRS)

Fortenberry, J.; Brownlee, G. R.

1974-01-01

The Viking Mars Lander 1975 dynamic test model and orbiter developmental test model were subjected to forced vibration sine tests. Flight acceptance (FA) and type approval (TA) test levels were applied to the spacecraft structure in a longitudinal test configuration using a 133,440-N (30,000-lb) force shaker. Testing in the two lateral axes (X, Y) was performed at lower levels using four 667-N (150-lb) force shakers. Forced vibration qualification (TA) test levels were successfully imposed on the spacecraft at frequencies down to 10 Hz. Measured responses showed the same character as analytical predictions, and correlation was reasonably good. Because of control system test tolerances, orbiter primary structure generally did not reach the design load limits attained in earlier static testing. A post-test examination of critical orbiter structure disclosed no apparent damage to the structure as a result of the test environment.

Construct validity of the Moral Development Scale for Professionals (MDSP).

PubMed

Söderhamn, Olle; Bjørnestad, John Olav; Skisland, Anne; Cliffordson, Christina

2011-01-01

The aim of this study was to investigate the construct validity of the Moral Development Scale for Professionals (MDSP) using structural equation modeling. The instrument is a 12-item self-report instrument, developed in the Scandinavian cultural context and based on Kohlberg's theory. A hypothesized simplex structure model underlying the MDSP was tested through structural equation modeling. Validity was also tested as the proportion of respondents older than 20 years that reached the highest moral level, which according to the theory should be small. A convenience sample of 339 nursing students with a mean age of 25.3 years participated. Results confirmed the simplex model structure, indicating that MDSP reflects a moral construct empirically organized from low to high. A minority of respondents >20 years of age (13.5%) scored more than 80% on the highest moral level. The findings support the construct validity of the MDSP and the stages and levels in Kohlberg's theory.

Development of structural and material clavicle response corridors under axial compression and three point bending loading for clavicle finite element model validation.

PubMed

Zhang, Qi; Kindig, Matthew; Li, Zuoping; Crandall, Jeff R; Kerrigan, Jason R

2014-08-22

Clavicle injuries were frequently observed in automotive side and frontal crashes. Finite element (FE) models have been developed to understand the injury mechanism, although no clavicle loading response corridors yet exist in the literature to ensure the model response biofidelity. Moreover, the typically developed structural level (e.g., force-deflection) response corridors were shown to be insufficient for verifying the injury prediction capacity of FE model, which usually is based on strain related injury criteria. Therefore, the purpose of this study is to develop both the structural (force vs deflection) and material level (strain vs force) clavicle response corridors for validating FE models for injury risk modeling. 20 Clavicles were loaded to failure under loading conditions representative of side and frontal crashes respectively, half of which in axial compression, and the other half in three point bending. Both structural and material response corridors were developed for each loading condition. FE model that can accurately predict structural response and strain level provides a more useful tool in injury risk modeling and prediction. The corridor development method in this study could also be extended to develop corridors for other components of the human body. Copyright © 2014 Elsevier Ltd. All rights reserved.

Hydraulic modeling of flow impact on bridge structures: a case study on Citarum bridge

NASA Astrophysics Data System (ADS)

Siregar, R. I.

2018-02-01

Flood waves because of the rapid catchment response to high intense rainfall, breaches of flood defenses may induce huge impact forces on structures, causing structural damage or even failures. Overflowing stream that passes over the bridge, it means to discharge flood water level is smaller than the capacity of the river flow. In this study, the researches present the methodological approach of flood modeling on bridge structures. The amount of force that obtained because of the hydrostatic pressure received by the bridge at the time of the flood caused the bridge structure disrupted. This paper presents simulation of flow impact on bridge structures with some event flood conditions. Estimating the hydrostatic pressure developed new model components, to quantify the flow impact on structures. Flow parameters applied the model for analyzing, such as discharge, velocity, and water level or head that effect of bridge structures. The simulation will illustrate the capability of bridge structures with some event flood river and observe the behavior of the flow that occurred during the flood. Hydraulic flood modeling use HEC-RAS for simulation. This modeling will describe the impact on bridge structures. Based on the above modelling resulted, in 2008 has flood effect more than other years on the Citarum Bridge, because its flow overflow on the bridge.

Wrinkling reduction of membrane structure by trimming edges

NASA Astrophysics Data System (ADS)

Liu, Mingjun; Huang, Jin; Liu, Mingyue

2017-05-01

Thin membranes have negligible bending stiffness, compressive stresses inevitably lead to wrinkling. Therefore, it is important to keep the surface of membrane structures flat in order to guarantee high precision. Edge-trimming is an effective method to passively diminish wrinkles, however a key difficulty in this process is the determination of the optimal trimming level. In this paper, regular polygonal membrane structures subjected to equal radial forces were analyzed, and a new stress field distribution model for arc-edge square membrane structure was proposed to predict the optimal trimming level. This model is simple and applicable to any polygonal membrane structures. Comparison among the results of the finite element analysis, and the experimental and analytical results showed that the proposed model accurately described the stress field distribution and guaranteed that there are no wrinkles appear inside the effective inscribed circle region for the optimal trimming level.

Topsoil structure stability in a restored floodplain: Impacts of fluctuating water levels, soil parameters and ecosystem engineers.

PubMed

Schomburg, A; Schilling, O S; Guenat, C; Schirmer, M; Le Bayon, R C; Brunner, P

2018-10-15

Ecosystem services provided by floodplains are strongly controlled by the structural stability of soils. The development of a stable structure in floodplain soils is affected by a complex and poorly understood interplay of hydrological, physico-chemical and biological processes. This paper aims at analysing relations between fluctuating groundwater levels, soil physico-chemical and biological parameters on soil structure stability in a restored floodplain. Water level fluctuations in the soil are modelled using a numerical surface-water-groundwater flow model and correlated to soil physico-chemical parameters and abundances of plants and earthworms. Causal relations and multiple interactions between the investigated parameters are tested through structural equation modelling (SEM). Fluctuating water levels in the soil did not directly affect the topsoil structure stability, but indirectly through affecting plant roots and soil parameters that in turn determine topsoil structure stability. These relations remain significant for mean annual days of complete and partial (>25%) water saturation. Ecosystem functioning of a restored floodplain might already be affected by the fluctuation of groundwater levels alone, and not only through complete flooding by surface water during a flood period. Surprisingly, abundances of earthworms did not show any relation to other variables in the SEM. These findings emphasise that earthworms have efficiently adapted to periodic stress and harsh environmental conditions. Variability of the topsoil structure stability is thus stronger driven by the influence of fluctuating water levels on plants than by the abundance of earthworms. This knowledge about the functional network of soil engineering organisms, soil parameters and fluctuating water levels and how they affect soil structural stability is of fundamental importance to define management strategies of near-natural or restored floodplains in the future. Copyright © 2018 Elsevier B.V. All rights reserved.

Multi-level analysis in information systems research: the case of enterprise resource planning system usage in China

NASA Astrophysics Data System (ADS)

Sun, Yuan; Bhattacherjee, Anol

2011-11-01

Information technology (IT) usage within organisations is a multi-level phenomenon that is influenced by individual-level and organisational-level variables. Yet, current theories, such as the unified theory of acceptance and use of technology, describe IT usage as solely an individual-level phenomenon. This article postulates a model of organisational IT usage that integrates salient organisational-level variables such as user training, top management support and technical support within an individual-level model to postulate a multi-level model of IT usage. The multi-level model was then empirically validated using multi-level data collected from 128 end users and 26 managers in 26 firms in China regarding their use of enterprise resource planning systems and analysed using the multi-level structural equation modelling (MSEM) technique. We demonstrate the utility of MSEM analysis of multi-level data relative to the more common structural equation modelling analysis of single-level data and show how single-level data can be aggregated to approximate multi-level analysis when multi-level data collection is not possible. We hope that this article will motivate future scholars to employ multi-level data and multi-level analysis for understanding organisational phenomena that are truly multi-level in nature.

Measuring Moisture Levels in Graphite Epoxy Composite Sandwich Structures

NASA Technical Reports Server (NTRS)

Nurge, Mark; Youngquist, Robert; Starr, Stanley

2011-01-01

Graphite epoxy composite (GEC) materials are used in the construction of rocket fairings, nose cones, interstage adapters, and heat shields due to their high strength and light weight. However, they absorb moisture depending on the environmental conditions they are exposed to prior to launch. Too much moisture absorption can become a problem when temperature and pressure changes experienced during launch cause the water to vaporize. The rapid state change of the water can result in structural failure of the material. In addition, heat and moisture combine to weaken GEC structures. Diffusion models that predict the total accumulated moisture content based on the environmental conditions are one accepted method of determining if the material strength has been reduced to an unacceptable level. However, there currently doesn t exist any field measurement technique to estimate the actual moisture content of a composite structure. A multi-layer diffusion model was constructed with Mathematica to predict moisture absorption and desorption from the GEC sandwich structure. This model is used in conjunction with relative humidity/temperature sensors both on the inside and outside of the material to determine the moisture levels in the structure. Because the core materials have much higher diffusivity than the face sheets, a single relative humidity measurement will accurately reflect the moisture levels in the core. When combined with an external relative humidity measurement, the model can be used to determine the moisture levels in the face sheets. Since diffusion is temperaturedependent, the temperature measurements are used to determine the diffusivity of the face sheets for the model computations.

Modeling complexes of modeled proteins.

PubMed

Anishchenko, Ivan; Kundrotas, Petras J; Vakser, Ilya A

2017-03-01

Structural characterization of proteins is essential for understanding life processes at the molecular level. However, only a fraction of known proteins have experimentally determined structures. This fraction is even smaller for protein-protein complexes. Thus, structural modeling of protein-protein interactions (docking) primarily has to rely on modeled structures of the individual proteins, which typically are less accurate than the experimentally determined ones. Such "double" modeling is the Grand Challenge of structural reconstruction of the interactome. Yet it remains so far largely untested in a systematic way. We present a comprehensive validation of template-based and free docking on a set of 165 complexes, where each protein model has six levels of structural accuracy, from 1 to 6 Å C α RMSD. Many template-based docking predictions fall into acceptable quality category, according to the CAPRI criteria, even for highly inaccurate proteins (5-6 Å RMSD), although the number of such models (and, consequently, the docking success rate) drops significantly for models with RMSD > 4 Å. The results show that the existing docking methodologies can be successfully applied to protein models with a broad range of structural accuracy, and the template-based docking is much less sensitive to inaccuracies of protein models than the free docking. Proteins 2017; 85:470-478. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Scale separation for multi-scale modeling of free-surface and two-phase flows with the conservative sharp interface method

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

Han, L.H., E-mail: Luhui.Han@tum.de; Hu, X.Y., E-mail: Xiangyu.Hu@tum.de; Adams, N.A., E-mail: Nikolaus.Adams@tum.de

In this paper we present a scale separation approach for multi-scale modeling of free-surface and two-phase flows with complex interface evolution. By performing a stimulus-response operation on the level-set function representing the interface, separation of resolvable and non-resolvable interface scales is achieved efficiently. Uniform positive and negative shifts of the level-set function are used to determine non-resolvable interface structures. Non-resolved interface structures are separated from the resolved ones and can be treated by a mixing model or a Lagrangian-particle model in order to preserve mass. Resolved interface structures are treated by the conservative sharp-interface model. Since the proposed scale separationmore » approach does not rely on topological information, unlike in previous work, it can be implemented in a straightforward fashion into a given level set based interface model. A number of two- and three-dimensional numerical tests demonstrate that the proposed method is able to cope with complex interface variations accurately and significantly increases robustness against underresolved interface structures.« less

Exploring Solid-State Structure and Physical Properties: A Molecular and Crystal Model Exercise

ERIC Educational Resources Information Center

Bindel, Thomas H.

2008-01-01

A crystal model laboratory exercise is presented that allows students to examine relations among the microscopic-macroscopic-symbolic levels, using crystalline mineral samples and corresponding crystal models. Students explore the relationship between solid-state structure and crystal form. Other structure-property relationships are explored. The…

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.

The interplay of structure and agency in health promotion: integrating a concept of structural change and the policy dimension into a multi-level model and applying it to health promotion principles and practice.

PubMed

Rütten, Alfred; Gelius, Peter

2011-10-01

The recent debate in public health about the "inequality paradox" mirrors a long-standing dispute between proponents of structuralist approaches and advocates of action theory. Both views are genuine perspectives of health promotion, but so far they have not been adequately linked by health promotion theory. Using Anthony Giddens's concepts of structure and agency seems promising, but his theory has a number of shortcomings that need to be amended if it is to be applied successfully to health promotion. After briefly assessing Giddens's theory of structuration, this paper proposes to add to it both the concept of structural change as proposed by William Sewell and the policy dimension as described by Elinor Ostrom in her distinction between "operational" and "collective choice" level. On this basis, a multi-level model of the interaction of structure and agency in health promotion is proposed. This model is then connected to central claims of the Ottawa Charter, i.e. "build healthy public policy", "create supportive environments", "strengthen community actions", and "develop personal skills". A case study from a local-level health promotion project in Germany is used to illustrate the explanatory power of the model, showing how interaction between structure and agency on the operational and on the collective choice level led to the establishment of women-only hours at the municipal indoor swimming pool as well as to increased physical activity levels and improved general self-efficacy among members of the target group. Copyright © 2011 Elsevier Ltd. All rights reserved.

Modeling Techniques for Shipboard Manning: A Review and Plan for Development

DTIC Science & Technology

1993-02-01

manning levels. Once manning models have been created, experiments can be conducted to show how changes in the manning structure might affect ship safety...these predictions, users of the manning models can evaluate how changes in crew configurations, manning levels, and voyage profiles affect ship safety...mitigate emergency situations would provide crucial information on how changes in manning structure would affect overall ship safety. Like emergency

Numerical damage models using a structural approach: application in bones and ligaments

NASA Astrophysics Data System (ADS)

Arnoux, P. J.; Bonnoit, J.; Chabrand, P.; Jean, M.; Pithioux, M.

2002-01-01

The purpose of the present study was to apply knowledge of structural properties to perform numerical simulations with models of bones and knee ligaments exposed to dynamic tensile loading leading to tissue damage. Compact bones and knee ligaments exhibit the same geometrical pattern in their different levels of structural hierarchy from the tropocollagen molecule to the fibre. Nevertheless, their mechanical behaviours differ considerably at the fibril level. These differences are due to the contribution of the joints in the microfibril-fibril-fibre assembly and to the mechanical properties of the structural components. Two finite element models of the fibrous bone and ligament structure were used to describe damage in terms of elastoplastic laws or joint decohesion processes.

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.

Challenges in structural approaches to cell modeling

PubMed Central

Im, Wonpil; Liang, Jie; Olson, Arthur; Zhou, Huan-Xiang; Vajda, Sandor; Vakser, Ilya A.

2016-01-01

Computational modeling is essential for structural characterization of biomolecular mechanisms across the broad spectrum of scales. Adequate understanding of biomolecular mechanisms inherently involves our ability to model them. Structural modeling of individual biomolecules and their interactions has been rapidly progressing. However, in terms of the broader picture, the focus is shifting toward larger systems, up to the level of a cell. Such modeling involves a more dynamic and realistic representation of the interactomes in vivo, in a crowded cellular environment, as well as membranes and membrane proteins, and other cellular components. Structural modeling of a cell complements computational approaches to cellular mechanisms based on differential equations, graph models, and other techniques to model biological networks, imaging data, etc. Structural modeling along with other computational and experimental approaches will provide a fundamental understanding of life at the molecular level and lead to important applications to biology and medicine. A cross section of diverse approaches presented in this review illustrates the developing shift from the structural modeling of individual molecules to that of cell biology. Studies in several related areas are covered: biological networks; automated construction of three-dimensional cell models using experimental data; modeling of protein complexes; prediction of non-specific and transient protein interactions; thermodynamic and kinetic effects of crowding; cellular membrane modeling; and modeling of chromosomes. The review presents an expert opinion on the current state-of-the-art in these various aspects of structural modeling in cellular biology, and the prospects of future developments in this emerging field. PMID:27255863

Aircraft Structural Mass Property Prediction Using Conceptual-Level Structural Analysis

NASA Technical Reports Server (NTRS)

Sexstone, Matthew G.

1998-01-01

This paper describes a methodology that extends the use of the Equivalent LAminated Plate Solution (ELAPS) structural analysis code from conceptual-level aircraft structural analysis to conceptual-level aircraft mass property analysis. Mass property analysis in aircraft structures has historically depended upon parametric weight equations at the conceptual design level and Finite Element Analysis (FEA) at the detailed design level. ELAPS allows for the modeling of detailed geometry, metallic and composite materials, and non-structural mass coupled with analytical structural sizing to produce high-fidelity mass property analyses representing fully configured vehicles early in the design process. This capability is especially valuable for unusual configuration and advanced concept development where existing parametric weight equations are inapplicable and FEA is too time consuming for conceptual design. This paper contrasts the use of ELAPS relative to empirical weight equations and FEA. ELAPS modeling techniques are described and the ELAPS-based mass property analysis process is detailed. Examples of mass property stochastic calculations produced during a recent systems study are provided. This study involved the analysis of three remotely piloted aircraft required to carry scientific payloads to very high altitudes at subsonic speeds. Due to the extreme nature of this high-altitude flight regime, few existing vehicle designs are available for use in performance and weight prediction. ELAPS was employed within a concurrent engineering analysis process that simultaneously produces aerodynamic, structural, and static aeroelastic results for input to aircraft performance analyses. The ELAPS models produced for each concept were also used to provide stochastic analyses of wing structural mass properties. The results of this effort indicate that ELAPS is an efficient means to conduct multidisciplinary trade studies at the conceptual design level.

Aircraft Structural Mass Property Prediction Using Conceptual-Level Structural Analysis

NASA Technical Reports Server (NTRS)

Sexstone, Matthew G.

1998-01-01

This paper describes a methodology that extends the use of the Equivalent LAminated Plate Solution (ELAPS) structural analysis code from conceptual-level aircraft structural analysis to conceptual-level aircraft mass property analysis. Mass property analysis in aircraft structures has historically depended upon parametric weight equations at the conceptual design level and Finite Element Analysis (FEA) at the detailed design level ELAPS allows for the modeling of detailed geometry, metallic and composite materials, and non-structural mass coupled with analytical structural sizing to produce high-fidelity mass property analyses representing fully configured vehicles early in the design process. This capability is especially valuable for unusual configuration and advanced concept development where existing parametric weight equations are inapplicable and FEA is too time consuming for conceptual design. This paper contrasts the use of ELAPS relative to empirical weight equations and FEA. ELAPS modeling techniques are described and the ELAPS-based mass property analysis process is detailed Examples of mass property stochastic calculations produced during a recent systems study are provided This study involved the analysis of three remotely piloted aircraft required to carry scientific payloads to very high altitudes at subsonic speeds. Due to the extreme nature of this high-altitude flight regime,few existing vehicle designs are available for use in performance and weight prediction. ELAPS was employed within a concurrent engineering analysis process that simultaneously produces aerodynamic, structural, and static aeroelastic results for input to aircraft performance analyses. The ELAPS models produced for each concept were also used to provide stochastic analyses of wing structural mass properties. The results of this effort indicate that ELAPS is an efficient means to conduct multidisciplinary trade studies at the conceptual design level.

Towards a virtual lung: multi-scale, multi-physics modelling of the pulmonary system.

PubMed

Burrowes, K S; Swan, A J; Warren, N J; Tawhai, M H

2008-09-28

The essential function of the lung, gas exchange, is dependent on adequate matching of ventilation and perfusion, where air and blood are delivered through complex branching systems exposed to regionally varying transpulmonary and transmural pressures. Structure and function in the lung are intimately related, yet computational models in pulmonary physiology usually simplify or neglect structure. The geometries of the airway and vascular systems and their interaction with parenchymal tissue have an important bearing on regional distributions of air and blood, and therefore on whole lung gas exchange, but this has not yet been addressed by modelling studies. Models for gas exchange have typically incorporated considerable detail at the level of chemical reactions, with little thought for the influence of structure. To date, relatively little attention has been paid to modelling at the cellular or subcellular level in the lung, or to linking information from the protein structure/interaction and cellular levels to the operation of the whole lung. We review previous work in developing anatomically based models of the lung, airways, parenchyma and pulmonary vasculature, and some functional studies in which these models have been used. Models for gas exchange at several spatial scales are briefly reviewed, and the challenges and benefits from modelling cellular function in the lung are discussed.

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…

Construct validity of the Moral Development Scale for Professionals (MDSP)

PubMed Central

Söderhamn, Olle; Bjørnestad, John Olav; Skisland, Anne; Cliffordson, Christina

2011-01-01

The aim of this study was to investigate the construct validity of the Moral Development Scale for Professionals (MDSP) using structural equation modeling. The instrument is a 12-item self-report instrument, developed in the Scandinavian cultural context and based on Kohlberg’s theory. A hypothesized simplex structure model underlying the MDSP was tested through structural equation modeling. Validity was also tested as the proportion of respondents older than 20 years that reached the highest moral level, which according to the theory should be small. A convenience sample of 339 nursing students with a mean age of 25.3 years participated. Results confirmed the simplex model structure, indicating that MDSP reflects a moral construct empirically organized from low to high. A minority of respondents >20 years of age (13.5%) scored more than 80% on the highest moral level. The findings support the construct validity of the MDSP and the stages and levels in Kohlberg’s theory. PMID:21655343

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

Ising model with conserved magnetization on the human connectome: Implications on the relation structure-function in wakefulness and anesthesia

NASA Astrophysics Data System (ADS)

Stramaglia, S.; Pellicoro, M.; Angelini, L.; Amico, E.; Aerts, H.; Cortés, J. M.; Laureys, S.; Marinazzo, D.

2017-04-01

Dynamical models implemented on the large scale architecture of the human brain may shed light on how a function arises from the underlying structure. This is the case notably for simple abstract models, such as the Ising model. We compare the spin correlations of the Ising model and the empirical functional brain correlations, both at the single link level and at the modular level, and show that their match increases at the modular level in anesthesia, in line with recent results and theories. Moreover, we show that at the peak of the specific heat (the critical state), the spin correlations are minimally shaped by the underlying structural network, explaining how the best match between the structure and function is obtained at the onset of criticality, as previously observed. These findings confirm that brain dynamics under anesthesia shows a departure from criticality and could open the way to novel perspectives when the conserved magnetization is interpreted in terms of a homeostatic principle imposed to neural activity.

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

Zhu Qin, E-mail: zhuqin@fudan.edu.cn; Peng Xizhe, E-mail: xzpeng@fudan.edu.cn

This study examines the impacts of population size, population structure, and consumption level on carbon emissions in China from 1978 to 2008. To this end, we expanded the stochastic impacts by regression on population, affluence, and technology model and used the ridge regression method, which overcomes the negative influences of multicollinearity among independent variables under acceptable bias. Results reveal that changes in consumption level and population structure were the major impact factors, not changes in population size. Consumption level and carbon emissions were highly correlated. In terms of population structure, urbanization, population age, and household size had distinct effects onmore » carbon emissions. Urbanization increased carbon emissions, while the effect of age acted primarily through the expansion of the labor force and consequent overall economic growth. Shrinking household size increased residential consumption, resulting in higher carbon emissions. Households, rather than individuals, are a more reasonable explanation for the demographic impact on carbon emissions. Potential social policies for low carbon development are also discussed. - Highlights: Black-Right-Pointing-Pointer We examine the impacts of population change on carbon emissions in China. Black-Right-Pointing-Pointer We expand the STIRPAT model by containing population structure factors in the model. Black-Right-Pointing-Pointer The population structure includes age structure, urbanization level, and household size. Black-Right-Pointing-Pointer The ridge regression method is used to estimate the model with multicollinearity. Black-Right-Pointing-Pointer The population structure plays a more important role compared with the population size.« less

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

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

A dynamic social systems model for considering structural factors in HIV prevention and detection

PubMed Central

Latkin, Carl; Weeks, Margaret; Glasman, Laura; Galletly, Carol; Albarracin, Dolores

2010-01-01

We present a model for HIV-related behaviors that emphasizes the dynamic and social nature of the structural factors that influence HIV prevention and detection. Key structural dimensions of the model include resources, science and technology, formal social control, informal social influences and control, social interconnectedness, and settings. These six dimensions can be conceptualized on macro, meso, and micro levels. Given the inherent complexity of structural factors and their interrelatedness, HIV prevention interventions may focus on different levels and dimensions. We employ a systems perspective to describe the interconnected and dynamic processes of change among social systems and their components. The topics of HIV testing and safer injection facilities are analyzed using this structural framework. Finally, we discuss methodological issues in the development and evaluation of structural interventions for HIV prevention and detection. PMID:20838871

Edible oil structures at low and intermediate concentrations. II. Ultra-small angle X-ray scattering of in situ tristearin solids in triolein

NASA Astrophysics Data System (ADS)

Peyronel, Fernanda; Ilavsky, Jan; Mazzanti, Gianfranco; Marangoni, Alejandro G.; Pink, David A.

2013-12-01

Ultra-small angle X-ray scattering has been used for the first time to elucidate, in situ, the aggregation structure of a model edible oil system. The three-dimensional nano- to micro-structure of tristearin solid particles in triolein solvent was investigated using 5, 10, 15, and 20% solids. Three different sample preparation procedures were investigated: two slow cooling rates of 0.5°/min, case 1 (22 days of storage at room temperature) and case 2 (no storage), and one fast cooling of 30°/min, case 3 (no storage). The length scale investigated, by using the Bonse-Hart camera at beamline ID-15D at the Advanced Photon Source, Argonne National Laboratory, covered the range from 300 Å to 10 μm. The unified fit and the Guinier-Porod models in the Irena software were used to fit the data. The former was used to fit 3 structural levels. Level 1 structures showed that the primary scatterers were essentially 2-dimensional objects for the three cases. The scatterers possessed lateral dimensions between 1000 and 4300 Å. This is consistent with the sizes of crystalline nanoplatelets present which were observed using cryo-TEM. Level 2 structures were aggregates possessing radii of gyration, Rg2 between 1800 Å and 12000 Å and fractal dimensions of either D2=1 for case 3 or 1.8≤D2≤2.1 for case 1 and case 2. D2 = 1 is consistent with unaggregated 1-dimensional objects. 1.8 ≤ D2 ≤ 2.1 is consistent with these 1-dimensional objects (below) forming structures characteristic of diffusion or reaction limited cluster-cluster aggregation. Level 3 structures showed that the spatial distribution of the level 2 structures was uniform, on the average, for case 1, with fractal dimension D3≈3 while for case 2 and case 3 the fractal dimension was D3≈2.2, which suggested that the large-scale distribution had not come to equilibrium. The Guinier-Porod model showed that the structures giving rise to the aggregates with a fractal dimension given by D2 in the unified fit level 2 model were cylinders described by the parameter s ≈1 in the Guinier-Porod model. The size of the base of these cylinders was in agreement with the cryo-TEM observations as well as with the results of the level 1 unified fit model. By estimating the size of the nanoplatelets and understanding the structures formed via their aggregation, it will be possible to engineer novel lipids systems that embody desired functional characteristics.

Multiple scales of patchiness and patch structure: a hierarchical framework for the study of heterogeneity

USGS Publications Warehouse

Kotliar, Natasha B.; Wiens, John A.

1990-01-01

We develop a hierarchical model of heterogeneity that provides a framework for classifying patch structure across a range of scales. Patches at lower levels in the hierarchy are more simplistic and correspond to the traditional view of patches. At levels approaching the upper bounds of the hierarchy the internal structure becomes more heterogeneous and boundaries more ambiguous. At each level in the hierarchy, patch structure will be influenced by both contrast among patches as well as the degree of aggregation of patches at lower levels in the hierarchy. We apply this model to foraging theory, but it has wider applications as in the study of habitat selection, population dynamics, and habitat fragmentation. It may also be useful in expanding the realm of landscape ecology beyond the current focus on anthropocentric scales.

Effective field model of roughness in magnetic nano-structures

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

Lepadatu, Serban, E-mail: SLepadatu@uclan.ac.uk

2015-12-28

An effective field model is introduced here within the micromagnetics formulation, to study roughness in magnetic structures, by considering sub-exchange length roughness levels as a perturbation on a smooth structure. This allows the roughness contribution to be separated, which is found to give rise to an effective configurational anisotropy for both edge and surface roughness, and accurately model its effects with fine control over the roughness depth without the explicit need to refine the computational cell size to accommodate the roughness profile. The model is validated by comparisons with directly roughened structures for a series of magnetization switching and domainmore » wall velocity simulations and found to be in excellent agreement for roughness levels up to the exchange length. The model is further applied to vortex domain wall velocity simulations with surface roughness, which is shown to significantly modify domain wall movement and result in dynamic pinning and stochastic creep effects.« less

Student perception and conceptual development as represented by student mental models of atomic structure

NASA Astrophysics Data System (ADS)

Park, Eun Jung

The nature of matter based upon atomic theory is a principal concept in science; hence, how to teach and how to learn about atoms is an important subject for science education. To this end, this study explored student perceptions of atomic structure and how students learn about this concept by analyzing student mental models of atomic structure. Changes in student mental models serve as a valuable resource for comprehending student conceptual development. Data was collected from students who were taking the introductory chemistry course. Responses to course examinations, pre- and post-questionnaires, and pre- and post-interviews were used to analyze student mental models of atomic structure. First, this study reveals that conceptual development can be achieved, either by elevating mental models toward higher levels of understanding or by developing a single mental model. This study reinforces the importance of higher-order thinking skills to enable students to relate concepts in order to construct a target model of atomic structure. Second, Bohr's orbital structure seems to have had a strong influence on student perceptions of atomic structure. With regard to this finding, this study suggests that it is instructionally important to teach the concept of "orbitals" related to "quantum theory." Third, there were relatively few students who had developed understanding at the level of the target model, which required student understanding of the basic ideas of quantum theory. This study suggests that the understanding of atomic structure based on the idea of quantum theory is both important and difficult. Fourth, this study included different student assessments comprised of course examinations, questionnaires, and interviews. Each assessment can be used to gather information to map out student mental models. Fifth, in the comparison of the pre- and post-interview responses, this study showed that high achieving students moved toward more improved models or to advanced levels of understanding. The analysis of mental models in this study has provided information describing student understanding of the nature and structure of an atom. In addition to an assessment of student cognition, information produced from this study can serve as an important resource for curriculum development, teacher education, and instruction.

Challenges in structural approaches to cell modeling.

PubMed

Im, Wonpil; Liang, Jie; Olson, Arthur; Zhou, Huan-Xiang; Vajda, Sandor; Vakser, Ilya A

2016-07-31

Computational modeling is essential for structural characterization of biomolecular mechanisms across the broad spectrum of scales. Adequate understanding of biomolecular mechanisms inherently involves our ability to model them. Structural modeling of individual biomolecules and their interactions has been rapidly progressing. However, in terms of the broader picture, the focus is shifting toward larger systems, up to the level of a cell. Such modeling involves a more dynamic and realistic representation of the interactomes in vivo, in a crowded cellular environment, as well as membranes and membrane proteins, and other cellular components. Structural modeling of a cell complements computational approaches to cellular mechanisms based on differential equations, graph models, and other techniques to model biological networks, imaging data, etc. Structural modeling along with other computational and experimental approaches will provide a fundamental understanding of life at the molecular level and lead to important applications to biology and medicine. A cross section of diverse approaches presented in this review illustrates the developing shift from the structural modeling of individual molecules to that of cell biology. Studies in several related areas are covered: biological networks; automated construction of three-dimensional cell models using experimental data; modeling of protein complexes; prediction of non-specific and transient protein interactions; thermodynamic and kinetic effects of crowding; cellular membrane modeling; and modeling of chromosomes. The review presents an expert opinion on the current state-of-the-art in these various aspects of structural modeling in cellular biology, and the prospects of future developments in this emerging field. Copyright © 2016 Elsevier Ltd. All rights reserved.

Biology Students’ Initial Mental Model about Microorganism

NASA Astrophysics Data System (ADS)

Hamdiyati, Y.; Sudargo, F.; Redjeki, S.; Fitriani, A.

2017-02-01

The purpose of this study was to identify biology students’ initial mental model about microorganism. This research used descriptive method with 32 sixth semester biology students at Biology Education Departement-Universitas Pendidikan Indonesia as its respondents. Data was taken at the beginning of the 6th semester before respondents endure microbiology course. Instrument used to assess mental model was drawing-writing test in which it contains concepts such as structure of bacteria, archaea, virus, and fungi. Students were asked to describe their imagination about the structure of microorganisms and subsequently asked to explain the structure of microorganisms in writing through open-ended questions. Students’ response was then compared to scientists or experts’ mental models as the targeted mental model. Student mental models were categorized into five levels (levels 1-5), namely “there is no drawing/writing,” “wrong or irrelevant drawing/writing of question,” “partially correct drawing/writing,” “the drawing/writing that has some deficiencies,” and “completely correct and complete drawing/writing.” Results showed that the level of mental models through drawing or writing about the four concepts were varied. The highest level of mental models through drawing (D5) was found in the concept of bacteria, while the highest level of mental models through writing (W3) was found in the concept of bacteria, virus, and fungi. Mental model levels most commonly found in each concept through drawing-writing tests (D/W) were bacteria (D2/W2), Archaea (D1/W1 and D2/W2), virus (D3/W3), and fungi (D2/W1). From these results it is advisable to improve lectures and assessment strategy to enhance or complement students’ mental models about microorganisms.

Epidemics in adaptive networks with community structure

NASA Astrophysics Data System (ADS)

Shaw, Leah; Tunc, Ilker

2010-03-01

Models for epidemic spread on static social networks do not account for changes in individuals' social interactions. Recent studies of adaptive networks have modeled avoidance behavior, as non-infected individuals try to avoid contact with infectives. Such models have not generally included realistic social structure. Here we study epidemic spread on an adaptive network with community structure. We model the effect of heterogeneous communities on infection levels and epidemic extinction. We also show how an epidemic can alter the community structure.

Methods to assess an exercise intervention trial based on 3-level functional data.

PubMed

Li, Haocheng; Kozey Keadle, Sarah; Staudenmayer, John; Assaad, Houssein; Huang, Jianhua Z; Carroll, Raymond J

2015-10-01

Motivated by data recording the effects of an exercise intervention on subjects' physical activity over time, we develop a model to assess the effects of a treatment when the data are functional with 3 levels (subjects, weeks and days in our application) and possibly incomplete. We develop a model with 3-level mean structure effects, all stratified by treatment and subject random effects, including a general subject effect and nested effects for the 3 levels. The mean and random structures are specified as smooth curves measured at various time points. The association structure of the 3-level data is induced through the random curves, which are summarized using a few important principal components. We use penalized splines to model the mean curves and the principal component curves, and cast the proposed model into a mixed effects model framework for model fitting, prediction and inference. We develop an algorithm to fit the model iteratively with the Expectation/Conditional Maximization Either (ECME) version of the EM algorithm and eigenvalue decompositions. Selection of the number of principal components and handling incomplete data issues are incorporated into the algorithm. The performance of the Wald-type hypothesis test is also discussed. The method is applied to the physical activity data and evaluated empirically by a simulation study. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Engine Structures Modeling Software System (ESMOSS)

NASA Technical Reports Server (NTRS)

1991-01-01

Engine Structures Modeling Software System (ESMOSS) is the development of a specialized software system for the construction of geometric descriptive and discrete analytical models of engine parts, components, and substructures which can be transferred to finite element analysis programs such as NASTRAN. The NASA Lewis Engine Structures Program is concerned with the development of technology for the rational structural design and analysis of advanced gas turbine engines with emphasis on advanced structural analysis, structural dynamics, structural aspects of aeroelasticity, and life prediction. Fundamental and common to all of these developments is the need for geometric and analytical model descriptions at various engine assembly levels which are generated using ESMOSS.

Structural models used in real-time biosurveillance outbreak detection and outbreak curve isolation from noisy background morbidity levels

PubMed Central

Cheng, Karen Elizabeth; Crary, David J; Ray, Jaideep; Safta, Cosmin

2013-01-01

Objective We discuss the use of structural models for the analysis of biosurveillance related data. Methods and results Using a combination of real and simulated data, we have constructed a data set that represents a plausible time series resulting from surveillance of a large scale bioterrorist anthrax attack in Miami. We discuss the performance of anomaly detection with structural models for these data using receiver operating characteristic (ROC) and activity monitoring operating characteristic (AMOC) analysis. In addition, we show that these techniques provide a method for predicting the level of the outbreak valid for approximately 2 weeks, post-alarm. Conclusions Structural models provide an effective tool for the analysis of biosurveillance data, in particular for time series with noisy, non-stationary background and missing data. PMID:23037798

Structural hierarchy of autism spectrum disorder symptoms: an integrative framework.

PubMed

Kim, Hyunsik; Keifer, Cara M; Rodriguez-Seijas, Craig; Eaton, Nicholas R; Lerner, Matthew D; Gadow, Kenneth D

2018-01-01

In an attempt to resolve questions regarding the symptom classification of autism spectrum disorder (ASD), previous research generally aimed to demonstrate superiority of one model over another. Rather than adjudicating which model may be optimal, we propose an alternative approach that integrates competing models using Goldberg's bass-ackwards method, providing a comprehensive understanding of the underlying symptom structure of ASD. The study sample comprised 3,825 individuals, consecutive referrals to a university hospital developmental disabilities specialty clinic or a child psychiatry outpatient clinic. This study analyzed DSM-IV-referenced ASD symptom statements from parent and teacher versions of the Child and Adolescent Symptom Inventory-4R. A series of exploratory structural equation models was conducted in order to produce interpretable latent factors that account for multivariate covariance. Results indicated that ASD symptoms were structured into an interpretable hierarchy across multiple informants. This hierarchy includes five levels; key features of ASD bifurcate into different constructs with increasing specificity. This is the first study to examine an underlying structural hierarchy of ASD symptomatology using the bass-ackwards method. This hierarchy demonstrates how core features of ASD relate at differing levels of resolution, providing a model for conceptualizing ASD heterogeneity and a structure for integrating divergent theories of cognitive processes and behavioral features that define the disorder. These findings suggest that a more coherent and complete understanding of the structure of ASD symptoms may be reflected in a metastructure rather than at one level of resolution. © 2017 Association for Child and Adolescent Mental Health.

New model framework and structure and the commonality evaluation model. [concerning unmanned spacecraft projects

NASA Technical Reports Server (NTRS)

1977-01-01

The development of a framework and structure for shuttle era unmanned spacecraft projects and the development of a commonality evaluation model is documented. The methodology developed for model utilization in performing cost trades and comparative evaluations for commonality studies is discussed. The model framework consists of categories of activities associated with the spacecraft system's development process. The model structure describes the physical elements to be treated as separate identifiable entities. Cost estimating relationships for subsystem and program-level components were calculated.

A coordination theory for intelligent machines

NASA Technical Reports Server (NTRS)

Wang, Fei-Yue; Saridis, George N.

1990-01-01

A formal model for the coordination level of intelligent machines is established. The framework of the coordination level investigated consists of one dispatcher and a number of coordinators. The model called coordination structure has been used to describe analytically the information structure and information flow for the coordination activities in the coordination level. Specifically, the coordination structure offers a formalism to (1) describe the task translation of the dispatcher and coordinators; (2) represent the individual process within the dispatcher and coordinators; (3) specify the cooperation and connection among the dispatcher and coordinators; (4) perform the process analysis and evaluation; and (5) provide a control and communication mechanism for the real-time monitor or simulation of the coordination process. A simple procedure for the task scheduling in the coordination structure is presented. The task translation is achieved by a stochastic learning algorithm. The learning process is measured with entropy and its convergence is guaranteed. Finally, a case study of the coordination structure with three coordinators and one dispatcher for a simple intelligent manipulator system illustrates the proposed model and the simulation of the task processes performed on the model verifies the soundness of the theory.

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.

Deformation analysis and prediction of bank protection structure with river level fluctuations

NASA Astrophysics Data System (ADS)

Hu, Rui; Xing, Yixuan

2017-04-01

Bank structure is an important barrier to maintain the safety of the embankment. The deformation of bank protection structure is not only affected by soil pressure caused by the excavation of the riverway, but also by the water pressure caused river water level fluctuations. Thus, it is necessary to establish a coupled soil-water model to analyze the deformation of bank structure. Based on Druck-Prager failure criteria and groundwater seepage theory, a numerical model of bank protection structure with consideration of the pore water pressure of soil mass is established. According to the measured river level data with seasonal fluctuating, numerical analysis of the deformation of bank protection structure is implemented. The simulation results show that the river water level fluctuation has clear influence on the maximum lateral displacement of the pile. Meanwhile, the distribution of plastic zone is related to the depth of groundwater level. Finally, according to the river water level data of the recent ten years, we analyze the deformation of the bank structure under extreme river level. The result shows that, compared with the scenario of extreme high river level, the horizontal displacement of bank protection structure is larger (up to 65mm) under extreme low river level, which is a potential risk to the embankment. Reference Schweiger H F. On the use of drucker-prager failure criteria for earth pressure problems[J]. Computers and Geotechnics, 1994, 16(3): 223-246. DING Yong-chun，CHENG Ze-kun. Numerical study on performance of waterfront excavation[J]. Chinese Journal of Geotechnical Engineering，2013，35(2):515-521. Wu L M, Wang Z Q. Three gorges reservoir water level fluctuation influents on the stability of the slope[J]. Advanced Materials Research. Trans Tech Publications, 2013, 739: 283-286.

Synthesis and Control of Flexible Systems with Component-Level Uncertainties

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.; Lim, Kyong B.

2009-01-01

An efficient and computationally robust method for synthesis of component dynamics is developed. The method defines the interface forces/moments as feasible vectors in transformed coordinates to ensure that connectivity requirements of the combined structure are met. The synthesized system is then defined in a transformed set of feasible coordinates. The simplicity of form is exploited to effectively deal with modeling parametric and non-parametric uncertainties at the substructure level. Uncertainty models of reasonable size and complexity are synthesized for the combined structure from those in the substructure models. In particular, we address frequency and damping uncertainties at the component level. The approach first considers the robustness of synthesized flexible systems. It is then extended to deal with non-synthesized dynamic models with component-level uncertainties by projecting uncertainties to the system level. A numerical example is given to demonstrate the feasibility of the proposed approach.

Mathematical Methods of System Analysis in Construction Materials

NASA Astrophysics Data System (ADS)

Garkina, Irina; Danilov, Alexander

2017-10-01

System attributes of construction materials are defined: complexity of an object, integrity of set of elements, existence of essential, stable relations between elements defining integrative properties of system, existence of structure, etc. On the basis of cognitive modelling (intensive and extensive properties; the operating parameters) materials (as difficult systems) and creation of the cognitive map the hierarchical modular structure of criteria of quality is under construction. It actually is a basis for preparation of the specification on development of material (the required organization and properties). Proceeding from a modern paradigm (model of statement of problems and their decisions) of development of materials, levels and modules are specified in structure of material. It when using the principles of the system analysis allows to considered technological process as the difficult system consisting of elements of the distinguished specification level: from atomic before separate process. Each element of system depending on an effective objective is considered as separate system with more detailed levels of decomposition. Among them, semantic and qualitative analyses of an object (are considered a research objective, decomposition levels, separate elements and communications between them come to light). Further formalization of the available knowledge in the form of mathematical models (structural identification) is carried out; communications between input and output parameters (parametrical identification) are defined. Hierarchical structures of criteria of quality are under construction for each allocated level. On her the relevant hierarchical structures of system (material) are under construction. Regularities of structurization and formation of properties, generally are considered at the levels from micro to a macrostructure. The mathematical model of material is represented as set of the models corresponding to private criteria by which separate modules and their levels (the mathematical description, a decision algorithm) are defined. Adequacy is established (compliance of results of modelling to experimental data; is defined by the level of knowledge of process and validity of the accepted assumptions). The global criterion of quality of material is considered as a set of private criteria (properties). Synthesis of material is carried out on the basis of one-criteria optimization on each of the chosen private criteria. Results of one-criteria optimization are used at multicriteria optimization. The methods of developing materials as single-purpose, multi-purpose, including contradictory, systems are indicated. The scheme of synthesis of composite materials as difficult systems is developed. The specified system approach effectively was used in case of synthesis of composite materials with special properties.

Regression Levels of Selected Affective Factors on Science Achievement: A Structural Equation Model with TIMSS 2011 Data

ERIC Educational Resources Information Center

Akilli, Mustafa

2015-01-01

The aim of this study is to demonstrate the science success regression levels of chosen emotional features of 8th grade students using Structural Equation Model. The study was conducted by the analysis of students' questionnaires and science success in TIMSS 2011 data using SEM. Initially, the factors that are thought to have an effect on science…

Bayesian Hierarchical Random Intercept Model Based on Three Parameter Gamma Distribution

NASA Astrophysics Data System (ADS)

Wirawati, Ika; Iriawan, Nur; Irhamah

2017-06-01

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

A size-structured model of bacterial growth and reproduction.

PubMed

Ellermeyer, S F; Pilyugin, S S

2012-01-01

We consider a size-structured bacterial population model in which the rate of cell growth is both size- and time-dependent and the average per capita reproduction rate is specified as a model parameter. It is shown that the model admits classical solutions. The population-level and distribution-level behaviours of these solutions are then determined in terms of the model parameters. The distribution-level behaviour is found to be different from that found in similar models of bacterial population dynamics. Rather than convergence to a stable size distribution, we find that size distributions repeat in cycles. This phenomenon is observed in similar models only under special assumptions on the functional form of the size-dependent growth rate factor. Our main results are illustrated with examples, and we also provide an introductory study of the bacterial growth in a chemostat within the framework of our model.

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.

Pain and the defense response: structural equation modeling reveals a coordinated psychophysiological response to increasing painful stimulation.

PubMed

Donaldson, Gary W; Chapman, C Richard; Nakamura, Yoshi; Bradshaw, David H; Jacobson, Robert C; Chapman, Christopher N

2003-03-01

The defense response theory implies that individuals should respond to increasing levels of painful stimulation with correlated increases in affectively mediated psychophysiological responses. This paper employs structural equation modeling to infer the latent processes responsible for correlated growth in the pain report, evoked potential amplitudes, pupil dilation, and skin conductance of 92 normal volunteers who experienced 144 trials of three levels of increasingly painful electrical stimulation. The analysis assumed a two-level model of latent growth as a function of stimulus level. The first level of analysis formulated a nonlinear growth model for each response measure, and allowed intercorrelations among the parameters of these models across individuals. The second level of analysis posited latent process factors to account for these intercorrelations. The best-fitting parsimonious model suggests that two latent processes account for the correlations. One of these latent factors, the activation threshold, determines the initial threshold response, while the other, the response gradient, indicates the magnitude of the coherent increase in response with stimulus level. Collectively, these two second-order factors define the defense response, a broad construct comprising both subjective pain evaluation and physiological mechanisms.

Structural modeling and optimization of a joined-wing configuration of a High-Altitude Long-Endurance (HALE) aircraft

NASA Astrophysics Data System (ADS)

Kaloyanova, Valentina B.

Recent research trends have indicated an interest in High-Altitude, Long-Endurance (HALE) aircraft as a low-cost alternative to certain space missions, such as telecommunication relay, environmental sensing and military reconnaissance. HALE missions require a light vehicle flying at low speed in the stratosphere at altitudes of 60,000-80,000 ft, with a continuous loiter time of up to several days. To provide high lift and low drag at these high altitudes, where the air density is low, the wing area should be increased, i.e., high-aspect-ratio wings are necessary. Due to its large span and lightweight, the wing structure is very flexible. To reduce the structural deformation, and increase the total lift in a long-spanned wing, a sensorcraft model with a joined-wing configuration, proposed by AFRL, is employed. The joined-wing encompasses a forward wing, which is swept back with a positive dihedral angle, and connected with an aft wing, which is swept forward. The joined-wing design combines structural strength, high aerodynamic performance and efficiency. As a first step to study the joined-wing structural behavior an 1-D approximation model is developed. The 1-D approximation is a simple structural model created using ANSYS BEAM4 elements to present a possible approach for the aerodynamics-structure coupling. The pressure loads from the aerodynamic analysis are integrated numerically to obtain the resultant aerodynamic forces and moments (spanwise lift and pitching moment distributions, acting at the aerodynamic center). These are applied on the 1-D structural model. A linear static analysis is performed under this equivalent load, and the deformed shape of the 1-D model is used to obtain the deformed shape of the actual 3-D joined wing, i.e. deformed aerodynamic surface grid. To date in the existing studies, only simplified structural models have been examined. In the present work, in addition to the simple 1-D beam model, a semi-monocoque structural model is developed. All stringers, skin panels, ribs and spars are represented by appropriate elements in a finite-element model. Also, the model accounts for the fuel weight and sensorcraft antennae housed within the wings. Linear and nonlinear static analyses under the aerodynamic load are performed. The stress distribution in the wing as well as deformation is explored. Starting with a structural model with uniform mass distribution, a design optimization is performed to achieve a fully stressed design. As the joined-wing structure is prone to buckling, after the design optimization is complete linear and nonlinear bucking analyses are performed to study the global joined-wing structural instability, the load magnitude at which it is expected to occur, and the buckling mode. The buckled shape of the aft wing (which is subjected to compression) is found to resemble that of a fixed-pinned column. The linear buckling analysis overestimates the buckling load. However, even the nonlinear buckling analysis results in a load factor higher than 3, i.e. the wing structure is buckling safe under its current loading conditions. As the region of the joint has a very complicated geometry that has adverse effects in the flow and stress behavior an independent, more finely meshed model (submodel) of the joint region is generated and analyzed. A detailed discussion of the stress distribution obtained in the joint region via the submodeling technique is presented in this study as well. It is found out that compared to its structural response, the joint adverse effects are much more pronounced in its aerodynamic response, so it is suggested for future studies the geometry of the joint to be optimized based on its aerodynamic performance. As this design and analysis study is aimed towards developing a realistic structural representation of the innovative joined-wing configuration, in addition to the "global", or upper-level optimization, a local level design optimization is performed as well. At the lower (local) level detailed models of wing structural panels are used to compute more complex failure modes and to design the details that are not included in the upper (global) level model. Proper coordination between local skin-stringer panel models and the global joined-wing model prevents inconsistency between the upper- (global) and lower- (local) level design models. (Abstract shortened by UMI.)

Image understanding systems based on the unifying representation of perceptual and conceptual information and the solution of mid-level and high-level vision problems

NASA Astrophysics Data System (ADS)

Kuvychko, Igor

2001-10-01

Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, that is an interpretation of visual information in terms of such knowledge models. A computer vision system based on such principles requires unifying representation of perceptual and conceptual information. Computer simulation models are built on the basis of graphs/networks. The ability of human brain to emulate similar graph/networks models is found. That means a very important shift of paradigm in our knowledge about brain from neural networks to the cortical software. Starting from the primary visual areas, brain analyzes an image as a graph-type spatial structure. Primary areas provide active fusion of image features on a spatial grid-like structure, where nodes are cortical columns. The spatial combination of different neighbor features cannot be described as a statistical/integral characteristic of the analyzed region, but uniquely characterizes such region itself. Spatial logic and topology naturally present in such structures. Mid-level vision processes like clustering, perceptual grouping, multilevel hierarchical compression, separation of figure from ground, etc. are special kinds of graph/network transformations. They convert low-level image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena like shape from shading, occlusion, etc. are results of such analysis. Such approach gives opportunity not only to explain frequently unexplainable results of the cognitive science, but also to create intelligent computer vision systems that simulate perceptional processes in both what and where visual pathways. Such systems can open new horizons for robotic and computer vision industries.

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

Transportation Safety Analysis

DOT National Transportation Integrated Search

1976-11-01

A conceptual structure was developed for a model expressing transportation accident deaths as a function of transportation activity levels. The literature and data bases were reviewed. A first-level model was developed for the following modes: highwa...

Modelling CEC variations versus structural iron reduction levels in dioctahedral smectites. Existing approaches, new data and model refinements.

PubMed

Hadi, Jebril; Tournassat, Christophe; Ignatiadis, Ioannis; Greneche, Jean Marc; Charlet, Laurent

2013-10-01

A model was developed to describe how the 2:1 layer excess negative charge induced by the reduction of Fe(III) to Fe(II) by sodium dithionite buffered with citrate-bicarbonate is balanced and applied to nontronites. This model is based on new experimental data and extends structural interpretation introduced by a former model [36-38]. The 2:1 layer negative charge increase due to Fe(III) to Fe(II) reduction is balanced by an excess adsorption of cations in the clay interlayers and a specific sorption of H(+) from solution. Prevalence of one compensating mechanism over the other is related to the growing lattice distortion induced by structural Fe(III) reduction. At low reduction levels, cation adsorption dominates and some of the incorporated protons react with structural OH groups, leading to a dehydroxylation of the structure. Starting from a moderate reduction level, other structural changes occur, leading to a reorganisation of the octahedral and tetrahedral lattice: migration or release of cations, intense dehydroxylation and bonding of protons to undersaturated oxygen atoms. Experimental data highlight some particular properties of ferruginous smectites regarding chemical reduction. Contrary to previous assumptions, the negative layer charge of nontronites does not only increase towards a plateau value upon reduction. A peak is observed in the reduction domain. After this peak, the negative layer charge decreases upon extended reduction (>30%). The decrease is so dramatic that the layer charge of highly reduced nontronites can fall below that of its fully oxidised counterpart. Furthermore, the presence of a large amount of tetrahedral Fe seems to promote intense clay structural changes and Fe reducibility. Our newly acquired data clearly show that models currently available in the literature cannot be applied to the whole reduction range of clay structural Fe. Moreover, changes in the model normalising procedure clearly demonstrate that the investigated low tetrahedral bearing nontronites (SWa-1, GAN and NAu-1) all exhibit the same behaviour at low reduction levels. Consequently, we restricted our model to the case of moderate reduction (<30%) in low tetrahedral Fe-bearing nontronites. Our adapted model provides the relative amounts of Na(+) (p) and H(+) (ni) cations incorporated in the structure as a function of the amount of Fe reduction. Two equations enable the investigated systems to be described: p=m/(1+Kr·ω·mrel) and ni=Kr·ω·m·mrel/(1+Kr·ω·mrel); where m is the Fe(II) content, mrel, the reduction level (m/mtot), ω, the cation exchange capacity (CEC, and Kr, an empirical constant specific to the system. Copyright © 2013 Elsevier Inc. All rights reserved.

Simulation of wheat growth and development based on organ-level photosynthesis and assimilate allocation.

PubMed

Evers, J B; Vos, J; Yin, X; Romero, P; van der Putten, P E L; Struik, P C

2010-05-01

Intimate relationships exist between form and function of plants, determining many processes governing their growth and development. However, in most crop simulation models that have been created to simulate plant growth and, for example, predict biomass production, plant structure has been neglected. In this study, a detailed simulation model of growth and development of spring wheat (Triticum aestivum) is presented, which integrates degree of tillering and canopy architecture with organ-level light interception, photosynthesis, and dry-matter partitioning. An existing spatially explicit 3D architectural model of wheat development was extended with routines for organ-level microclimate, photosynthesis, assimilate distribution within the plant structure according to organ demands, and organ growth and development. Outgrowth of tiller buds was made dependent on the ratio between assimilate supply and demand of the plants. Organ-level photosynthesis, biomass production, and bud outgrowth were simulated satisfactorily. However, to improve crop simulation results more efforts are needed mechanistically to model other major plant physiological processes such as nitrogen uptake and distribution, tiller death, and leaf senescence. Nevertheless, the work presented here is a significant step forwards towards a mechanistic functional-structural plant model, which integrates plant architecture with key plant processes.

Stiffness degradation-based damage model for RC members and structures using fiber-beam elements

NASA Astrophysics Data System (ADS)

Guo, Zongming; Zhang, Yaoting; Lu, Jiezhi; Fan, Jian

2016-12-01

To meet the demand for an accurate and highly efficient damage model with a distinct physical meaning for performance-based earthquake engineering applications, a stiffness degradation-based damage model for reinforced concrete (RC) members and structures was developed using fiber beam-column elements. In this model, damage indices for concrete and steel fibers were defined by the degradation of the initial reloading modulus and the low-cycle fatigue law. Then, section, member, story and structure damage was evaluated by the degradation of the sectional bending stiffness, rod-end bending stiffness, story lateral stiffness and structure lateral stiffness, respectively. The damage model was realized in Matlab by reading in the outputs of OpenSees. The application of the damage model to RC columns and a RC frame indicates that the damage model is capable of accurately predicting the magnitude, position, and evolutionary process of damage, and estimating story damage more precisely than inter-story drift. Additionally, the damage model establishes a close connection between damage indices at various levels without introducing weighting coefficients or force-displacement relationships. The development of the model has perfected the damage assessment function of OpenSees, laying a solid foundation for damage estimation at various levels of a large-scale structure subjected to seismic loading.

Automated protein structure modeling in CASP9 by I-TASSER pipeline combined with QUARK-based ab initio folding and FG-MD-based structure refinement

PubMed Central

Xu, Dong; Zhang, Jian; Roy, Ambrish; Zhang, Yang

2011-01-01

I-TASSER is an automated pipeline for protein tertiary structure prediction using multiple threading alignments and iterative structure assembly simulations. In CASP9 experiments, two new algorithms, QUARK and FG-MD, were added to the I-TASSER pipeline for improving the structural modeling accuracy. QUARK is a de novo structure prediction algorithm used for structure modeling of proteins that lack detectable template structures. For distantly homologous targets, QUARK models are found useful as a reference structure for selecting good threading alignments and guiding the I-TASSER structure assembly simulations. FG-MD is an atomic-level structural refinement program that uses structural fragments collected from the PDB structures to guide molecular dynamics simulation and improve the local structure of predicted model, including hydrogen-bonding networks, torsion angles and steric clashes. Despite considerable progress in both the template-based and template-free structure modeling, significant improvements on protein target classification, domain parsing, model selection, and ab initio folding of beta-proteins are still needed to further improve the I-TASSER pipeline. PMID:22069036

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.

Measurement and Structural Model Class Separation in Mixture CFA: ML/EM versus MCMC

ERIC Educational Resources Information Center

Depaoli, Sarah

2012-01-01

Parameter recovery was assessed within mixture confirmatory factor analysis across multiple estimator conditions under different simulated levels of mixture class separation. Mixture class separation was defined in the measurement model (through factor loadings) and the structural model (through factor variances). Maximum likelihood (ML) via the…

A Structural Equation Model of Expertise in College Physics

ERIC Educational Resources Information Center

Taasoobshirazi, Gita; Carr, Martha

2009-01-01

A model of expertise in physics was tested on a sample of 374 college students in 2 different level physics courses. Structural equation modeling was used to test hypothesized relationships among variables linked to expert performance in physics including strategy use, pictorial representation, categorization skills, and motivation, and these…

A Structural Equation Model of Conceptual Change in Physics

ERIC Educational Resources Information Center

Taasoobshirazi, Gita; Sinatra, Gale M.

2011-01-01

A model of conceptual change in physics was tested on introductory-level, college physics students. Structural equation modeling was used to test hypothesized relationships among variables linked to conceptual change in physics including an approach goal orientation, need for cognition, motivation, and course grade. Conceptual change in physics…

Multilayered Word Structure Model for Assessing Spelling of Finnish Children in Shallow Orthography

ERIC Educational Resources Information Center

Kulju, Pirjo; Mäkinen, Marita

2017-01-01

This study explores Finnish children's word-level spelling by applying a linguistically based multilayered word structure model for assessing spelling performance. The model contributes to the analytical qualitative assessment approach in order to identify children's spelling performance for enhancing writing skills. The children (N = 105)…

Structural empowerment and burnout among Portuguese nursing staff: An explicative model.

PubMed

Orgambídez-Ramos, Alejandro; Borrego-Alés, Yolanda; Vázquez-Aguado, Octavio; March-Amegual, Jaume

2017-11-01

Kanter's structural empowerment model was used to assess the influence of access to opportunities, resources, information and support on core burnout through global empowerment in a nursing sample in Portugal. The empowerment experience increases the levels of nursing professionals' satisfaction and performance preventing the emergence of burnout. However, the relationship between structural empowerment and burnout has been scarcely studied in Portugal. We conducted a cross-sectional correlational study assessing a final sample of 297 participants (62.13% response rate, 63.64% women). Model fit and mediation test were examined using structural equation modelling (path analysis). Access to opportunities and access to support had direct impact, through global empowerment, on core burnout, whereas access to resources had both direct and indirect impact on core burnout. The results validated the structural empowerment model and its application in nursing staff in Portugal. Professional training plans, the development of formal and informal support networks, and the availability of resources increase the levels of empowerment and decrease the likelihood of experiencing burnout in nursing professionals. © 2017 John Wiley & Sons Ltd.

Modelling road accidents: An approach using structural time series

NASA Astrophysics Data System (ADS)

Junus, Noor Wahida Md; Ismail, Mohd Tahir

2014-09-01

In this paper, the trend of road accidents in Malaysia for the years 2001 until 2012 was modelled using a structural time series approach. The structural time series model was identified using a stepwise method, and the residuals for each model were tested. The best-fitted model was chosen based on the smallest Akaike Information Criterion (AIC) and prediction error variance. In order to check the quality of the model, a data validation procedure was performed by predicting the monthly number of road accidents for the year 2012. Results indicate that the best specification of the structural time series model to represent road accidents is the local level with a seasonal model.

Determination of Elevator and Rudder Hinge Forces on the Learjet Model 55 Aircraft

NASA Technical Reports Server (NTRS)

Boroughs, R. R.; Padmanabhan, V.

1983-01-01

The empennage structure on the Learjet 55 aircraft was quite similar to the empennage structure on earlier Learjet models. However, due to an important structural change in the vertical fin along with the new loads environment on the 50 series aircraft, a structural test was required on the vertical fin, but the horizontal tail was substantiated by a comparative analysis with previous tests. NASTRAN analysis was used to investigate empennage deflections, stress levels, and control surface hinge forces. The hinge force calculations were made with the control surfaces in the deflected as well as undeflected configurations. A skin panel buckling analysis was also performed, and the non-linear effects of buckling were simulated in the NASTRAN model to more accurately define internal loads and stress levels. Comparisons were then made between the Model 55 and the Model 35/36 stresses and internal forces to determine which components were qualified by previous tests. Some of the methods and techniques used in this analysis are described.

Modeling spike-wave discharges by a complex network of neuronal oscillators.

PubMed

Medvedeva, Tatiana M; Sysoeva, Marina V; van Luijtelaar, Gilles; Sysoev, Ilya V

2018-02-01

The organization of neural networks and the mechanisms, which generate the highly stereotypical for absence epilepsy spike-wave discharges (SWDs) is heavily debated. Here we describe such a model which can both reproduce the characteristics of SWDs and dynamics of coupling between brain regions, relying mainly on properties of hierarchically organized networks of a large number of neuronal oscillators. We used a two level mesoscale model. The first level consists of three structures: the nervus trigeminus serving as an input, the thalamus and the somatosensory cortex; the second level of a group of nearby situated neurons belonging to one of three modeled structures. The model reproduces the main features of the transition from normal to epileptiformic activity and its spontaneous abortion: an increase in the oscillation amplitude, the emergence of the main frequency and its higher harmonics, and the ability to generate trains of seizures. The model was stable with respect to variations in the structure of couplings and to scaling. The analyzes of the interactions between model structures from their time series using Granger causality method showed that the model reproduced the preictal coupling increase detected previously from experimental data. SWDs can be generated by changes in network organization. It is proposed that a specific pathological architecture of couplings in the brain is necessary to allow the transition from normal to epileptiformic activity, next to by others modeled and reported factors referring to complex, intrinsic, and synaptic mechanisms. Copyright © 2017 Elsevier Ltd. All rights reserved.

Resilience of branching and massive corals to wave loading under sea level rise--a coupled computational fluid dynamics-structural analysis.

PubMed

Baldock, Tom E; Karampour, Hassan; Sleep, Rachael; Vyltla, Anisha; Albermani, Faris; Golshani, Aliasghar; Callaghan, David P; Roff, George; Mumby, Peter J

2014-09-15

Measurements of coral structural strength are coupled with a fluid dynamics-structural analysis to investigate the resilience of coral to wave loading under sea level rise and a typical Great Barrier Reef lagoon wave climate. The measured structural properties were used to determine the wave conditions and flow velocities that lead to structural failure. Hydrodynamic modelling was subsequently used to investigate the type of the bathymetry where coral is most vulnerable to breakage under cyclonic wave conditions, and how sea level rise (SLR) changes this vulnerability. Massive corals are determined not to be vulnerable to wave induced structural damage, whereas branching corals are susceptible at wave induced orbital velocities exceeding 0.5m/s. Model results from a large suite of idealised bathymetry suggest that SLR of 1m or a loss of skeleton strength of order 25% significantly increases the area of reef flat where branching corals are exposed to damaging wave induced flows. Copyright © 2014 Elsevier Ltd. All rights reserved.

Interband magneto-spectroscopy in InSb square and parabolic quantum wells

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

Kasturiarachchi, T.; Edirisooriya, M.; Mishima, T. D.

We measure the magneto-optical absorption due to intersubband optical transitions between conduction and valence subband Landau levels in InSb square and parabolic quantum wells. InSb has the narrowest band gap (0.24 eV at low temperature) of the III–V semiconductors leading to a small effective mass (0.014 m{sub 0}) and a large g–factor (−51). As a result, the Landau level spacing is large at relatively small magnetic fields (<8 T), and one can observe spin-splitting of the Landau levels. We examine two structures: (i) a multiple-square-well structure and (ii) a structure containing multiple parabolic wells. The energies and intensities of the strongest featuresmore » are well explained by a modified Pidgeon-Brown model based on an 8-band k•p model that explicitly incorporates pseudomorphic strain. The strain is essential for obtaining agreement between theory and experiment. While modeling the square well is relatively straight-forward, the parabolic well consists of 43 different layers of various thickness to approximate a parabolic potential. Agreement between theory and experiment for the parabolic well validates the applicability of the model to complicated structures, which demonstrates the robustness of our model and confirms its relevance for developing electronic and spintronic devices that seek to exploit the properties of the InSb band structure.« less

A Method for Incorporating Changing Structural Characteristics Due to Propellant Mass Usage in a Launch Vehicle Ascent Simulation

NASA Technical Reports Server (NTRS)

McGhee, D. S.

2004-01-01

Launch vehicles consume large quantities of propellant quickly, causing the mass properties and structural dynamics of the vehicle to change dramatically. Currently, structural load assessments account for this change with a large collection of structural models representing various propellant fill levels. This creates a large database of models complicating the delivery of reduced models and requiring extensive work for model changes. Presented here is a method to account for these mass changes in a more efficient manner. The method allows for the subtraction of propellant mass as the propellant is used in the simulation. This subtraction is done in the modal domain of the vehicle generalized model. Additional computation required is primarily for constructing the used propellant mass matrix from an initial propellant model and further matrix multiplications and subtractions. An additional eigenvalue solution is required to uncouple the new equations of motion; however, this is a much simplier calculation starting from a system that is already substantially uncoupled. The method was successfully tested in a simulation of Saturn V loads. Results from the method are compared to results from separate structural models for several propellant levels, showing excellent agreement. Further development to encompass more complicated propellant models, including slosh dynamics, is possible.

A 3-level Bayesian mixed effects location scale model with an application to ecological momentary assessment data.

PubMed

Lin, Xiaolei; Mermelstein, Robin J; Hedeker, Donald

2018-06-15

Ecological momentary assessment studies usually produce intensively measured longitudinal data with large numbers of observations per unit, and research interest is often centered around understanding the changes in variation of people's thoughts, emotions and behaviors. Hedeker et al developed a 2-level mixed effects location scale model that allows observed covariates as well as unobserved variables to influence both the mean and the within-subjects variance, for a 2-level data structure where observations are nested within subjects. In some ecological momentary assessment studies, subjects are measured at multiple waves, and within each wave, subjects are measured over time. Li and Hedeker extended the original 2-level model to a 3-level data structure where observations are nested within days and days are then nested within subjects, by including a random location and scale intercept at the intermediate wave level. However, the 3-level random intercept model assumes constant response change rate for both the mean and variance. To account for changes in variance across waves, as well as clustering attributable to waves, we propose a more comprehensive location scale model that allows subject heterogeneity at baseline as well as across different waves, for a 3-level data structure where observations are nested within waves and waves are then further nested within subjects. The model parameters are estimated using Markov chain Monte Carlo methods. We provide details on the Bayesian estimation approach and demonstrate how the Stan statistical software can be used to sample from the desired distributions and achieve consistent estimates. The proposed model is validated via a series of simulation studies. Data from an adolescent smoking study are analyzed to demonstrate this approach. The analyses clearly favor the proposed model and show significant subject heterogeneity at baseline as well as change over time, for both mood mean and variance. The proposed 3-level location scale model can be widely applied to areas of research where the interest lies in the consistency in addition to the mean level of the responses. Copyright © 2018 John Wiley & Sons, Ltd.

Optimization of the time series NDVI-rainfall relationship using linear mixed-effects modeling for the anti-desertification area in the Beijing and Tianjin sandstorm source region

NASA Astrophysics Data System (ADS)

Wang, Jin; Sun, Tao; Fu, Anmin; Xu, Hao; Wang, Xinjie

2018-05-01

Degradation in drylands is a critically important global issue that threatens ecosystem and environmental in many ways. Researchers have tried to use remote sensing data and meteorological data to perform residual trend analysis and identify human-induced vegetation changes. However, complex interactions between vegetation and climate, soil units and topography have not yet been considered. Data used in the study included annual accumulated Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m normalized difference vegetation index (NDVI) from 2002 to 2013, accumulated rainfall from September to August, digital elevation model (DEM) and soil units. This paper presents linear mixed-effect (LME) modeling methods for the NDVI-rainfall relationship. We developed linear mixed-effects models that considered the random effects of sample points nested in soil units for nested two-level modeling and single-level modeling of soil units and sample points, respectively. Additionally, three functions, including the exponential function (exp), the power function (power), and the constant plus power function (CPP), were tested to remove heterogeneity, and an additional three correlation structures, including the first-order autoregressive structure [AR(1)], a combination of first-order autoregressive and moving average structures [ARMA(1,1)] and the compound symmetry structure (CS), were used to address the spatiotemporal correlations. It was concluded that the nested two-level model considering both heteroscedasticity with (CPP) and spatiotemporal correlation with [ARMA(1,1)] showed the best performance (AMR = 0.1881, RMSE = 0.2576, adj- R 2 = 0.9593). Variations between soil units and sample points that may have an effect on the NDVI-rainfall relationship should be included in model structures, and linear mixed-effects modeling achieves this in an effective and accurate way.

Long-term stand growth of interior ponderosa pine stands in response to structural modifications and burning treatments in northeastern California

Treesearch

Justin S. Crotteau; Martin W. Ritchie

2014-01-01

The Blacks Mountain Experimental Research Project created two distinct overstory structural classes (high structural diversity [HiD]; low-structural diversity [LoD]) across 12 stands and subsequently burned half of each stand. We analyzed stand-level growth 10 years after treatment and then modeled individual tree growth to forecast stand-level growth 10–20 years after...

A structural model of health behavior: a pragmatic approach to explain and influence health behaviors at the population level.

PubMed

Cohen, D A; Scribner, R A; Farley, T A

2000-02-01

Behavior is influenced by individual-level attributes as well as by the conditions under which people live. Altering policies, practices, and the conditions of life can directly and indirectly influence individual behavior. This paper builds on existing ecological theories of health behavior by specifying structural mechanisms by which population-level factors effect change in individual health behaviors. This paper moves ecological theory from model building to a pragmatic characterization of structural interventions. We examined social and environmental factors beyond individual control and mechanisms as to how they influence behavior. Four categories of structural factors are identified: (1) availability of protective or harmful consumer products, (2) physical structures (or physical characteristics of products), (3) social structures and policies, and (4) media and cultural messages. The first three can directly influence individuals through facilitating or constraining behavior. The fourth, media, operates by changing individual-level attitudes, beliefs, and cognitions, as well as group norms. Interventions that target the four identified structural factors are a means to provide conditions that not only reduce high-risk behavior but also prevent the adoption of high-risk behaviors. Structural interventions are important and underutilized approaches for improving our nation's health. Copyright 2000 American Health Foundation and Academic Press.

Statistical mechanics of protein structural transitions: Insights from the island model

PubMed Central

Kobayashi, Yukio

2016-01-01

The so-called island model of protein structural transition holds that hydrophobic interactions are the key to both the folding and function of proteins. Herein, the genesis and statistical mechanical basis of the island model of transitions are reviewed, by presenting the results of simulations of such transitions. Elucidating the physicochemical mechanism of protein structural formation is the foundation for understanding the hierarchical structure of life at the microscopic level. Based on the results obtained to date using the island model, remaining problems and future work in the field of protein structures are discussed, referencing Professor Saitô’s views on the hierarchic structure of science. PMID:28409078

Damage level prediction of non-reshaped berm breakwater using ANN, SVM and ANFIS models

NASA Astrophysics Data System (ADS)

Mandal, Sukomal; Rao, Subba; N., Harish; Lokesha

2012-06-01

The damage analysis of coastal structure is very important as it involves many design parameters to be considered for the better and safe design of structure. In the present study experimental data for non-reshaped berm breakwater are collected from Marine Structures Laboratory, Department of Applied Mechanics and Hydraulics, NITK, Surathkal, India. Soft computing techniques like Artificial Neural Network (ANN), Support Vector Machine (SVM) and Adaptive Neuro Fuzzy Inference system (ANFIS) models are constructed using experimental data sets to predict the damage level of non-reshaped berm breakwater. The experimental data are used to train ANN, SVM and ANFIS models and results are determined in terms of statistical measures like mean square error, root mean square error, correla-tion coefficient and scatter index. The result shows that soft computing techniques i.e., ANN, SVM and ANFIS can be efficient tools in predicting damage levels of non reshaped berm breakwater.

Probabilistic Estimates of Global Mean Sea Level and its Underlying Processes

NASA Astrophysics Data System (ADS)

Hay, C.; Morrow, E.; Kopp, R. E.; Mitrovica, J. X.

2015-12-01

Local sea level can vary significantly from the global mean value due to a suite of processes that includes ongoing sea-level changes due to the last ice age, land water storage, ocean circulation changes, and non-uniform sea-level changes that arise when modern-day land ice rapidly melts. Understanding these sources of spatial and temporal variability is critical to estimating past and present sea-level change and projecting future sea-level rise. Using two probabilistic techniques, a multi-model Kalman smoother and Gaussian process regression, we have reanalyzed 20th century tide gauge observations to produce a new estimate of global mean sea level (GMSL). Our methods allow us to extract global information from the sparse tide gauge field by taking advantage of the physics-based and model-derived geometry of the contributing processes. Both methods provide constraints on the sea-level contribution of glacial isostatic adjustment (GIA). The Kalman smoother tests multiple discrete models of glacial isostatic adjustment (GIA), probabilistically computing the most likely GIA model given the observations, while the Gaussian process regression characterizes the prior covariance structure of a suite of GIA models and then uses this structure to estimate the posterior distribution of local rates of GIA-induced sea-level change. We present the two methodologies, the model-derived geometries of the underlying processes, and our new probabilistic estimates of GMSL and GIA.

Substrate Creep on The Fatigue Life of A Model Dental Multilayer Structure

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

Zhou, J; Huang, M; Niu, X

In this paper, we investigated the effects of substrate creep on the fatigue behavior of a model dental multilayer structure, in which a top glass layer was bonded to a polycarbonate substrate through a dental adhesive. The top glass layers were ground using 120 grit or 600 grit sand papers before bonding to create different sub-surface crack sizes and morphologies. The multilayer structures were tested under cyclic Hertzian contact loading to study crack growth and obtain fatigue life curves. The experiment results showed that the fatigue lives of the multilayer structures were impaired by increasing crack sizes in the sub-surfaces.more » They were also significantly reduced by the substrate creep when tested at relatively low load levels i.e. P{sub m} < 60 N (Pm is the maximum magnitude of cyclic load). But at relatively high load levels i.e. P{sub m} > 65 N, slow crack growth (SCG) was the major failure mechanisms. A modeling study was then carried out to explore the possible failure mechanisms over a range of load levels. It is found that fatigue life at relatively low load levels can be better estimated by considering the substrate creep effect (SCE).« less

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.

Linking models and data on vegetation structure

NASA Astrophysics Data System (ADS)

Hurtt, G. C.; Fisk, J.; Thomas, R. Q.; Dubayah, R.; Moorcroft, P. R.; Shugart, H. H.

2010-06-01

For more than a century, scientists have recognized the importance of vegetation structure in understanding forest dynamics. Now future satellite missions such as Deformation, Ecosystem Structure, and Dynamics of Ice (DESDynI) hold the potential to provide unprecedented global data on vegetation structure needed to reduce uncertainties in terrestrial carbon dynamics. Here, we briefly review the uses of data on vegetation structure in ecosystem models, develop and analyze theoretical models to quantify model-data requirements, and describe recent progress using a mechanistic modeling approach utilizing a formal scaling method and data on vegetation structure to improve model predictions. Generally, both limited sampling and coarse resolution averaging lead to model initialization error, which in turn is propagated in subsequent model prediction uncertainty and error. In cases with representative sampling, sufficient resolution, and linear dynamics, errors in initialization tend to compensate at larger spatial scales. However, with inadequate sampling, overly coarse resolution data or models, and nonlinear dynamics, errors in initialization lead to prediction error. A robust model-data framework will require both models and data on vegetation structure sufficient to resolve important environmental gradients and tree-level heterogeneity in forest structure globally.

Composite Stress Rupture: A New Reliability Model Based on Strength Decay

NASA Technical Reports Server (NTRS)

Reeder, James R.

2012-01-01

A model is proposed to estimate reliability for stress rupture of composite overwrap pressure vessels (COPVs) and similar composite structures. This new reliability model is generated by assuming a strength degradation (or decay) over time. The model suggests that most of the strength decay occurs late in life. The strength decay model will be shown to predict a response similar to that predicted by a traditional reliability model for stress rupture based on tests at a single stress level. In addition, the model predicts that even though there is strength decay due to proof loading, a significant overall increase in reliability is gained by eliminating any weak vessels, which would fail early. The model predicts that there should be significant periods of safe life following proof loading, because time is required for the strength to decay from the proof stress level to the subsequent loading level. Suggestions for testing the strength decay reliability model have been made. If the strength decay reliability model predictions are shown through testing to be accurate, COPVs may be designed to carry a higher level of stress than is currently allowed, which will enable the production of lighter structures

Learning to Apply Models of Materials While Explaining Their Properties

ERIC Educational Resources Information Center

Karpin, Tiia; Juuti, Kalle; Lavonen, Jari

2014-01-01

Background: Applying structural models is important to chemistry education at the upper secondary level, but it is considered one of the most difficult topics to learn. Purpose: This study analyses to what extent in designed lessons students learned to apply structural models in explaining the properties and behaviours of various materials.…

Multilevel SEM Strategies for Evaluating Mediation in Three-Level Data

ERIC Educational Resources Information Center

Preacher, Kristopher J.

2011-01-01

Strategies for modeling mediation effects in multilevel data have proliferated over the past decade, keeping pace with the demands of applied research. Approaches for testing mediation hypotheses with 2-level clustered data were first proposed using multilevel modeling (MLM) and subsequently using multilevel structural equation modeling (MSEM) to…

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…

Sample Size Limits for Estimating Upper Level Mediation Models Using Multilevel SEM

ERIC Educational Resources Information Center

Li, Xin; Beretvas, S. Natasha

2013-01-01

This simulation study investigated use of the multilevel structural equation model (MLSEM) for handling measurement error in both mediator and outcome variables ("M" and "Y") in an upper level multilevel mediation model. Mediation and outcome variable indicators were generated with measurement error. Parameter and standard…

A spatial panel ordered-response model with application to the analysis of urban land-use development intensity patterns

NASA Astrophysics Data System (ADS)

Ferdous, Nazneen; Bhat, Chandra R.

2013-01-01

This paper proposes and estimates a spatial panel ordered-response probit model with temporal autoregressive error terms to analyze changes in urban land development intensity levels over time. Such a model structure maintains a close linkage between the land owner's decision (unobserved to the analyst) and the land development intensity level (observed by the analyst) and accommodates spatial interactions between land owners that lead to spatial spillover effects. In addition, the model structure incorporates spatial heterogeneity as well as spatial heteroscedasticity. The resulting model is estimated using a composite marginal likelihood (CML) approach that does not require any simulation machinery and that can be applied to data sets of any size. A simulation exercise indicates that the CML approach recovers the model parameters very well, even in the presence of high spatial and temporal dependence. In addition, the simulation results demonstrate that ignoring spatial dependency and spatial heterogeneity when both are actually present will lead to bias in parameter estimation. A demonstration exercise applies the proposed model to examine urban land development intensity levels using parcel-level data from Austin, Texas.

Structured Hypermedia Application Development Model (SHADM): A structured Model for Technical Documentation Application Design

DTIC Science & Technology

1991-12-01

effective (19:15) Figure 2 details a flowchart of the basic steps in prototyping. The basic concept behind prototyping is to quickly produce a working...One approach to overcoming this is to structure the document relative to the experience level of the user (14:49). A "novice" or beginner would

77 FR 28533 - Special Conditions: Boeing, Model 737-800; Large Non-Structural Glass in the Passenger Compartment

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-15

...-0499; Notice No. 25-12-01-SC] Special Conditions: Boeing, Model 737-800; Large Non-Structural Glass in... associated with the installation of large non-structural glass items in the cabin area of an executive... standards that the Administrator considers necessary to establish a level of safety equivalent to that...

77 FR 40255 - Special Conditions: Boeing, Model 737-800; Large Non-Structural Glass in the Passenger Compartment

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-09

...-0499; Special Conditions No. 25-466-SC] Special Conditions: Boeing, Model 737-800; Large Non-Structural... with the installation of large non-structural glass items in the cabin area of an executive interior... Administrator considers necessary to establish a level of safety equivalent to that established by the existing...

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.

Particle decay of proton-unbound levels in N 12

DOE PAGES

Chipps, K. A.; Pain, S. D.; Greife, U.; ...

2017-04-24

Transfer reactions are a useful tool for studying nuclear structure, particularly in the regime of low level densities and strong single-particle strengths. Additionally, transfer reactions can populate levels above particle decay thresholds, allowing for the possibility of studying the subsequent decays and furthering our understanding of the nuclei being probed. In particular, the decay of loosely bound nuclei such as 12 N can help inform and improve structure models.The purpose of this paper is to learn about the decay of excited states in 12 N , to more generally inform nuclear structure models, particularly in the case of particle-unbound levelsmore » in low-mass systems which are within the reach of state-of-the-art ab initio calculations.« less

The influence of lateral Earth structure on glacial isostatic adjustment in Greenland

NASA Astrophysics Data System (ADS)

Milne, Glenn A.; Latychev, Konstantin; Schaeffer, Andrew; Crowley, John W.; Lecavalier, Benoit S.; Audette, Alexandre

2018-05-01

We present the first results that focus on the influence of lateral Earth structure on Greenland glacial isostatic adjustment (GIA) using a model that can explicitly incorporate 3-D Earth structure. In total, eight realisations of lateral viscosity structure were developed using four global seismic velocity models and two global lithosphere (elastic) thickness models. Our results show that lateral viscosity structure has a significant influence on model output of both deglacial relative sea level (RSL) changes and present-day rates of vertical land motion. For example, lateral structure changes the RSL predictions in the Holocene by several 10 s of metres in many locations relative to the 1-D case. Modelled rates of vertical land motion are also significantly affected, with differences from the 1-D case commonly at the mm/yr level and exceeding 2 mm/yr in some locations. The addition of lateral structure was unable to account for previously identified data-model RSL misfits in northern and southern Greenland, suggesting limitations in the adopted ice model (Lecavalier et al. 2014) and/or the existence of processes not included in our model. Our results show large data-model discrepancies in uplift rates when applying a 1-D viscosity model tuned to fit the RSL data; these discrepancies cannot be reconciled by adding the realisations of lateral structure considered here. In many locations, the spread in model output for the eight different 3-D Earth models is of similar amplitude or larger than the influence of lateral structure (as defined by the average of all eight model runs). This reflects the differences between the four seismic and two lithosphere models used and implies a large uncertainty in defining the GIA signal given that other aspects that contribute to this uncertainty (e.g. scaling from seismic velocity to viscosity) were not considered in this study. In order to reduce this large model uncertainty, an important next step is to develop more accurate constraints on Earth structure beneath Greenland based on regional geophysical data sets.

Stand-level forest structure and avian habitat: Scale dependencies in predicting occurrence in a heterogeneous forest

USGS Publications Warehouse

Smith, K.M.; Keeton, W.S.; Donovan, T.M.; Mitchell, B.

2008-01-01

We explored the role of stand-level forest structure and spatial extent of forest sampling in models of avian occurrence in northern hardwood-conifer forests for two species: black-throated blue warbler (Dendroica caerulescens) and ovenbird (Seiurus aurocapillus). We estimated site occupancy from point counts at 20 sites and characterized the forest structure at these sites at three spatial extents (0.2, 3.0, and 12.0 ha). Weight of evidence was greatest for habitat models using forest stand structure at the 12.0-ha extent and diminished only slightly at the 3.0-ha extent, a scale that was slightly larger than the average territory size of both species. Habitat models characterized at the 0.2-ha extent had low support, yet are the closest in design to those used in many of the habitat studies we reviewed. These results suggest that the role of stand-level vegetation may have been underestimated in the past, which will be of interest to land managers who use habitat models to assess the suitability of habitat for species of concern. Copyright ?? 2008 by the Society of American Foresters.

Aerostructural Level Set Topology Optimization for a Common Research Model Wing

NASA Technical Reports Server (NTRS)

Dunning, Peter D.; Stanford, Bret K.; Kim, H. Alicia

2014-01-01

The purpose of this work is to use level set topology optimization to improve the design of a representative wing box structure for the NASA common research model. The objective is to minimize the total compliance of the structure under aerodynamic and body force loading, where the aerodynamic loading is coupled to the structural deformation. A taxi bump case was also considered, where only body force loads were applied. The trim condition that aerodynamic lift must balance the total weight of the aircraft is enforced by allowing the root angle of attack to change. The level set optimization method is implemented on an unstructured three-dimensional grid, so that the method can optimize a wing box with arbitrary geometry. Fast matching and upwind schemes are developed for an unstructured grid, which make the level set method robust and efficient. The adjoint method is used to obtain the coupled shape sensitivities required to perform aerostructural optimization of the wing box structure.

Using topographic networks to build a representation of consciousness.

PubMed

Tinsley, Chris J

2008-04-01

The subject of consciousness has intrigued both psychologists and neuroscientists for many years. Recently, following many recent advances in the emerging field of cognitive neuroscience, there is the possibility that this fundamental process may soon be explained. In particular, there have been dramatic insights gained into the mechanisms of attention, cognition and perception in recent decades. Here, simple network models are proposed which are used to create a representation of consciousness. The models are inspired by the structure of the thalamus and all incorporate topographic layers in their structure. Operation of the models allows filtering of the information reaching the representation according to (1) modality and/or (2) sub-modality, in addition several of the models allowing filtering at the topographic level. The models presented have different structures and employ different integrative mechanisms to produce gating or amplification at different levels; the resultant representations of consciousness are discussed.

Exactly solvable model of transitional nuclei based on dual algebraic structure for the three level pairing model in the framework of sdg interacting boson model

NASA Astrophysics Data System (ADS)

Jafarizadeh, M. A.; Ranjbar, Z.; Fouladi, N.; Ghapanvari, M.

2018-01-01

In this paper, a successful algebraic method based on the dual algebraic structure for three level pairing model in the framework of sdg IBM is proposed for transitional nuclei which show transitional behavior from spherical to gamma-unstable quantum shape phase transition. In this method complicated sdg Hamiltonian, which is a three level pairing Hamiltonian is determined easily via the exactly solvable method. This description provides a better interpretation of some observables such as BE (4) in nuclei which exhibits the necessity of inclusion of g boson in the sd IBM, while BE (4) cannot be explained in the sd boson model. Some observables such as Energy levels, BE (2), BE (4), the two neutron separation energies signature splitting of the γ-vibrational band and expectation values of the g-boson number operator are calculated and examined for 46 104 - 110Pd isotopes.

The origin of consistent protein structure refinement from structural averaging.

PubMed

Park, Hahnbeom; DiMaio, Frank; Baker, David

2015-06-02

Recent studies have shown that explicit solvent molecular dynamics (MD) simulation followed by structural averaging can consistently improve protein structure models. We find that improvement upon averaging is not limited to explicit water MD simulation, as consistent improvements are also observed for more efficient implicit solvent MD or Monte Carlo minimization simulations. To determine the origin of these improvements, we examine the changes in model accuracy brought about by averaging at the individual residue level. We find that the improvement in model quality from averaging results from the superposition of two effects: a dampening of deviations from the correct structure in the least well modeled regions, and a reinforcement of consistent movements towards the correct structure in better modeled regions. These observations are consistent with an energy landscape model in which the magnitude of the energy gradient toward the native structure decreases with increasing distance from the native state. Copyright © 2015 Elsevier Ltd. All rights reserved.

Marginalized identities, discrimination burden, and mental health: Empirical exploration of an interpersonal-level approach to modeling intersectionality

PubMed Central

Seng, Julia S; Lopez, William D; Sperlich, Mickey; Hamama, Lydia; Meldrum, Caroline D Reed

2012-01-01

Intersectionality is a term used to describe the intersecting effects of race, class, gender, and other marginalizing characteristics that contribute to social identity and affect health. Adverse health effects are thought to occur via social processes including discrimination and structural inequalities (i.e., reduced opportunities for education and income). Although intersectionality has been well-described conceptually, approaches to modeling it in quantitative studies of health outcomes are still emerging. Strategies to date have focused on modeling demographic characteristics as proxies for structural inequality. Our objective was to extend these methodological efforts by modeling intersectionality across three levels: structural, contextual, and interpersonal, consistent with a social-ecological framework. We conducted a secondary analysis of a database that included two components of a widely used survey instrument, the Everyday Discrimination Scale. We operationalized a meso- or interpersonal-level of intersectionality using two variables, the frequency score of discrimination experiences and the sum of characteristics listed as reasons for these (i.e., the person’s race, ethnicity, gender, sexual orientation, nationality, religion, disability or pregnancy status, or physical appearance). We controlled for two structural inequality factors (low education, poverty) and three contextual factors (high crime neighborhood, racial minority status, and trauma exposures). The outcome variables we modeled were posttraumatic stress disorder symptoms and a quality of life index score. We used data from 619 women who completed the Everyday Discrimination Scale for a perinatal study in the U.S. state of Michigan. Statistical results indicated that the two interpersonal-level variables (i.e., number of marginalized identities, frequency of discrimination) explained 15% of variance in posttraumatic stress symptoms and 13% of variance in quality of life scores, improving the predictive value of the models over those using structural inequality and contextual factors alone. This study’s results point to instrument development ideas to improve the statistical modeling of intersectionality in health and social science research. PMID:23089613

Marginalized identities, discrimination burden, and mental health: empirical exploration of an interpersonal-level approach to modeling intersectionality.

PubMed

Seng, Julia S; Lopez, William D; Sperlich, Mickey; Hamama, Lydia; Reed Meldrum, Caroline D

2012-12-01

Intersectionality is a term used to describe the intersecting effects of race, class, gender, and other marginalizing characteristics that contribute to social identity and affect health. Adverse health effects are thought to occur via social processes including discrimination and structural inequalities (i.e., reduced opportunities for education and income). Although intersectionality has been well-described conceptually, approaches to modeling it in quantitative studies of health outcomes are still emerging. Strategies to date have focused on modeling demographic characteristics as proxies for structural inequality. Our objective was to extend these methodological efforts by modeling intersectionality across three levels: structural, contextual, and interpersonal, consistent with a social-ecological framework. We conducted a secondary analysis of a database that included two components of a widely used survey instrument, the Everyday Discrimination Scale. We operationalized a meso- or interpersonal-level of intersectionality using two variables, the frequency score of discrimination experiences and the sum of characteristics listed as reasons for these (i.e., the person's race, ethnicity, gender, sexual orientation, nationality, religion, disability or pregnancy status, or physical appearance). We controlled for two structural inequality factors (low education, poverty) and three contextual factors (high crime neighborhood, racial minority status, and trauma exposures). The outcome variables we modeled were posttraumatic stress disorder symptoms and a quality of life index score. We used data from 619 women who completed the Everyday Discrimination Scale for a perinatal study in the U.S. state of Michigan. Statistical results indicated that the two interpersonal-level variables (i.e., number of marginalized identities, frequency of discrimination) explained 15% of variance in posttraumatic stress symptoms and 13% of variance in quality of life scores, improving the predictive value of the models over those using structural inequality and contextual factors alone. This study's results point to instrument development ideas to improve the statistical modeling of intersectionality in health and social science research. Copyright © 2012 Elsevier Ltd. All rights reserved.

Spatio-temporal hierarchical modeling of rates and variability of Holocene sea-level changes in the western North Atlantic and the Caribbean

NASA Astrophysics Data System (ADS)

Ashe, E.; Kopp, R. E.; Khan, N.; Horton, B.; Engelhart, S. E.

2016-12-01

Sea level varies over of both space and time. Prior to the instrumental period, the sea-level record depends upon geological reconstructions that contain vertical and temporal uncertainty. Spatio-temporal statistical models enable the interpretation of RSL and rates of change as well as the reconstruction of the entire sea-level field from such noisy data. Hierarchical models explicitly distinguish between a process level, which characterizes the spatio-temporal field, and a data level, by which sparse proxy data and its noise is recorded. A hyperparameter level depicts prior expectations about the structure of variability in the spatio-temporal field. Spatio-temporal hierarchical models are amenable to several analysis approaches, with tradeoffs regarding computational efficiency and comprehensiveness of uncertainty characterization. A fully-Bayesian hierarchical model (BHM), which places prior probability distributions upon the hyperparameters, is more computationally intensive than an empirical hierarchical model (EHM), which uses point estimates of hyperparameters, derived from the data [1]. Here, we assess the sensitivity of posterior estimates of relative sea level (RSL) and rates to different statistical approaches by varying prior assumptions about the spatial and temporal structure of sea-level variability and applying multiple analytical approaches to Holocene sea-level proxies along the Atlantic coast of North American and the Caribbean [2]. References: 1. N Cressie, Wikle CK (2011) Statistics for spatio-temporal data (John Wiley & Sons). 2. Kahn N et al. (2016). Quaternary Science Reviews (in revision).

The Construction and Validation of All-Atom Bulk-Phase Models of Amorphous Polymers Using the TIGER2/TIGER3 Empirical Sampling Method

PubMed Central

Li, Xianfeng; Murthy, Sanjeeva; Latour, Robert A.

2011-01-01

A new empirical sampling method termed “temperature intervals with global exchange of replicas and reduced radii” (TIGER3) is presented and demonstrated to efficiently equilibrate entangled long-chain molecular systems such as amorphous polymers. The TIGER3 algorithm is a replica exchange method in which simulations are run in parallel over a range of temperature levels at and above a designated baseline temperature. The replicas sampled at temperature levels above the baseline are run through a series of cycles with each cycle containing four stages – heating, sampling, quenching, and temperature level reassignment. The method allows chain segments to pass through one another at elevated temperature levels during the sampling stage by reducing the van der Waals radii of the atoms, thus eliminating chain entanglement problems. Atomic radii are then returned to their regular values and re-equilibrated at elevated temperature prior to quenching to the baseline temperature. Following quenching, replicas are compared using a Metropolis Monte Carlo exchange process for the construction of an approximate Boltzmann-weighted ensemble of states and then reassigned to the elevated temperature levels for additional sampling. Further system equilibration is performed by periodic implementation of the previously developed TIGER2 algorithm between cycles of TIGER3, which applies thermal cycling without radii reduction. When coupled with a coarse-grained modeling approach, the combined TIGER2/TIGER3 algorithm yields fast equilibration of bulk-phase models of amorphous polymer, even for polymers with complex, highly branched structures. The developed method was tested by modeling the polyethylene melt. The calculated properties of chain conformation and chain segment packing agreed well with published data. The method was also applied to generate equilibrated structural models of three increasingly complex amorphous polymer systems: poly(methyl methacrylate), poly(butyl methacrylate), and DTB-succinate copolymer. Calculated glass transition temperature (Tg) and structural parameter profile (S(q)) for each resulting polymer model were found to be in close agreement with experimental Tg values and structural measurements obtained by x-ray diffraction, thus validating that the developed methods provide realistic models of amorphous polymer structure. PMID:21769156

Optimisation and evaluation of pre-design models for offshore wind turbines with jacket support structures and their influence on integrated load simulations

NASA Astrophysics Data System (ADS)

Schafhirt, S.; Kaufer, D.; Cheng, P. W.

2014-12-01

In recent years many advanced load simulation tools, allowing an aero-servo-hydroelastic analyses of an entire offshore wind turbine, have been developed and verified. Nowadays, even an offshore wind turbine with a complex support structure such as a jacket can be analysed. However, the computational effort rises significantly with an increasing level of details. This counts especially for offshore wind turbines with lattice support structures, since those models do naturally have a higher number of nodes and elements than simpler monopile structures. During the design process multiple load simulations are demanded to obtain an optimal solution. In the view of pre-design tasks it is crucial to apply load simulations which keep the simulation quality and the computational effort in balance. The paper will introduce a reference wind turbine model consisting of the REpower5M wind turbine and a jacket support structure with a high level of detail. In total twelve variations of this reference model are derived and presented. Main focus is to simplify the models of the support structure and the foundation. The reference model and the simplified models are simulated with the coupled simulation tool Flex5-Poseidon and analysed regarding frequencies, fatigue loads, and ultimate loads. A model has been found which reaches an adequate increase of simulation speed while holding the results in an acceptable range compared to the reference results.

Fuselage Versus Subcomponent Panel Response Correlation Based on ABAQUS Explicit Progressive Damage Analysis Tools

NASA Technical Reports Server (NTRS)

Gould, Kevin E.; Satyanarayana, Arunkumar; Bogert, Philip B.

2016-01-01

Analysis performed in this study substantiates the need for high fidelity vehicle level progressive damage analyses (PDA) structural models for use in the verification and validation of proposed sub-scale structural models and to support required full-scale vehicle level testing. PDA results are presented that capture and correlate the responses of sub-scale 3-stringer and 7-stringer panel models and an idealized 8-ft diameter fuselage model, which provides a vehicle level environment for the 7-stringer sub-scale panel model. Two unique skin-stringer attachment assumptions are considered and correlated in the models analyzed: the TIE constraint interface versus the cohesive element (COH3D8) interface. Evaluating different interfaces allows for assessing a range of predicted damage modes, including delamination and crack propagation responses. Damage models considered in this study are the ABAQUS built-in Hashin procedure and the COmplete STress Reduction (COSTR) damage procedure implemented through a VUMAT user subroutine using the ABAQUS/Explicit code.

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…

Structural studies of RNA-protein complexes: A hybrid approach involving hydrodynamics, scattering, and computational methods.

PubMed

Patel, Trushar R; Chojnowski, Grzegorz; Astha; Koul, Amit; McKenna, Sean A; Bujnicki, Janusz M

2017-04-15

The diverse functional cellular roles played by ribonucleic acids (RNA) have emphasized the need to develop rapid and accurate methodologies to elucidate the relationship between the structure and function of RNA. Structural biology tools such as X-ray crystallography and Nuclear Magnetic Resonance are highly useful methods to obtain atomic-level resolution models of macromolecules. However, both methods have sample, time, and technical limitations that prevent their application to a number of macromolecules of interest. An emerging alternative to high-resolution structural techniques is to employ a hybrid approach that combines low-resolution shape information about macromolecules and their complexes from experimental hydrodynamic (e.g. analytical ultracentrifugation) and solution scattering measurements (e.g., solution X-ray or neutron scattering), with computational modeling to obtain atomic-level models. While promising, scattering methods rely on aggregation-free, monodispersed preparations and therefore the careful development of a quality control pipeline is fundamental to an unbiased and reliable structural determination. This review article describes hydrodynamic techniques that are highly valuable for homogeneity studies, scattering techniques useful to study the low-resolution shape, and strategies for computational modeling to obtain high-resolution 3D structural models of RNAs, proteins, and RNA-protein complexes. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Active influence in dynamical models of structural balance in social networks

NASA Astrophysics Data System (ADS)

Summers, Tyler H.; Shames, Iman

2013-07-01

We consider a nonlinear dynamical system on a signed graph, which can be interpreted as a mathematical model of social networks in which the links can have both positive and negative connotations. In accordance with a concept from social psychology called structural balance, the negative links play a key role in both the structure and dynamics of the network. Recent research has shown that in a nonlinear dynamical system modeling the time evolution of “friendliness levels” in the network, two opposing factions emerge from almost any initial condition. Here we study active external influence in this dynamical model and show that any agent in the network can achieve any desired structurally balanced state from any initial condition by perturbing its own local friendliness levels. Based on this result, we also introduce a new network centrality measure for signed networks. The results are illustrated in an international-relations network using United Nations voting record data from 1946 to 2008 to estimate friendliness levels amongst various countries.

Measuring and modeling stemflow by two xerophytic shrubs in the Loess Plateau: The role of dynamic canopy structure

NASA Astrophysics Data System (ADS)

Zhang, Y.; Li, X.; Li, W.; Shi, F.; Wu, H.; WU, X.; Pei, T.

2016-12-01

Stemflow plays an important role in hydrological processes in dryland shrubs, but it still remains poorly understood, especially regarding the effects of dynamic canopy structure on stemflow. This study aimed to measure and model the stemflow of two dominant xerophytic shrub (Hippophae rhamnoides and Spiraea pubescens) communities and to identify the key controlling factors of stemflow yield. We quantified and scaled-up stemflow from branches and leaves to stand levels. Correlations and stepwise regression analysis between stemflow and meteorological and biological factors indicated that at branch level, the rainfall amount and the branch diameter were the best variables for modelling and predicting stemflow for Hippophae rhamnoides, while the rainfall amount and the aboveground biomass were the best variables for modelling and predicting stemflow for Spiraea pubescens. At stand level, the stemflow yield is mostly affected by rainfall amount and leaf area index for both shrubs. The stemflow fluxes account for 3.5±0.9% of incident rainfall for H. rhamnoides community and 9.4±2.1% for S. pubescens community, respectively. The differences in percentages of stemflow between the two shrub communities was attributed to differences in canopy structures and water storage capacities. This evaluation of the effects of canopy structure dynamics on stemflow, and of the developed model, provided a better understanding of the effect of the canopy structure on the water cycles in dryland shrub ecosystems.

Theoretical study of the noble metals on semiconductor surfaces and Ti-base shape memory alloys

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

Ding, Yungui

1994-07-27

The electronic and structural properties of the (√3 x√3) R30° Ag/Si(111) and (√3 x √3) R30° Au/Si(111) surfaces are investigated using first principles total energy calculations. We have tested almost all experimentally proposed structural models for both surfaces and found the energetically most favorable model for each of them. The lowest energy model structure of the (√3 x √3) R30° Ag/Si(111) surface consists of a top layer of Ag atoms arranged as ``honeycomb-chained-trimers`` lying above a distorted ``missing top layer`` Si(111) substrate. The coverage of Ag is 1 monolayer (ML). We find that the honeycomb structure observed in STM imagesmore » arise from the electronic charge densities of an empty surface band near the Fermi level. The electronic density of states of this model gives a ``pseudo-gap`` around the Fermi level, which is consistent with experimental results. The lowest energy model for the (√3 x √3) R30° Au/Si(111) surface is a conjugate honeycomb-chained-trimer (CHCT-1) configuration which consists of a top layer of trimers formed by 1 ML Au atoms lying above a ``missing top layer`` Si(111) substrate with a honeycomb-chained-trimer structure for its first layer. The structures of Au and Ag are in fact quite similar and belong to the same class of structural models. However, small variation in the structural details gives rise to quite different observed STM images, as revealed in the theoretical calculations. The electronic charge density from bands around the Fermi level for the (√3 x √3) R30°, Au/Si(111) surface also gives a good description of the images observed in STM experiments. First principles calculations are performed to study the electronic and structural properties of a series of Ti-base binary alloys TiFe, TiNi, TiPd, TiMo, and TiAu in the B2 structure.« less

Investigating the Relationships among Stressors, Stress Level, and Mental Symptoms for Infertile Patients: A Structural Equation Modeling Approach.

PubMed

Wang, Jong-Yi; Li, Yi-Shan; Chen, Jen-De; Liang, Wen-Miin; Yang, Tung-Chuan; Lee, Young-Chang; Wang, Chia-Woei

2015-01-01

Patients with infertility are a high risk group in depression and anxiety. However, an existing theoretically and empirically validated model of stressors, stress, and mental symptoms specific for infertile patients is still a void. This study aimed to determine the related factors and their relational structures that affect the level of depressive and anxiety symptoms among infertile patients. A cross-sectional sample of 400 infertility outpatients seeking reproduction treatments in three teaching hospitals across Taiwan participated in the structured questionnaire survey in 2011. The hypothesized model comprising 10 latent variables was tested by Structural Equation Modeling using AMOS 17. Goodness-of-fit indexes, including χ2/DF = 1.871, PGFI = 0.746, PNFI = 0.764, and others, confirmed the modified model fit the data well. Marital stressor, importance of children, guilt-and-blame, and social stressor showed a direct effect on perceived stress. Instead of being a factor of stress, social support was directly and positively related to self-esteem. Perceived stress and self-esteem were the two major mediators for the relationships between stressors and mental symptoms. Increase in social support and self-esteem led to decrease in mental symptoms among the infertile patients. The relational structures were identified and named as the Stressors Stress Symptoms Model, clinically applied to predict anxiety and depression from various stressors. Assessing sources and level of infertility-related stress and implementing culturally-sensitive counseling with an emphasis on positive personal value may assist in preventing the severity of depression and anxiety.

Investigating the Relationships among Stressors, Stress Level, and Mental Symptoms for Infertile Patients: A Structural Equation Modeling Approach

PubMed Central

Wang, Jong-Yi; Liang, Wen-Miin; Yang, Tung-Chuan; Lee, Young-Chang; Wang, Chia-Woei

2015-01-01

Objective Patients with infertility are a high risk group in depression and anxiety. However, an existing theoretically and empirically validated model of stressors, stress, and mental symptoms specific for infertile patients is still a void. This study aimed to determine the related factors and their relational structures that affect the level of depressive and anxiety symptoms among infertile patients. Methods A cross-sectional sample of 400 infertility outpatients seeking reproduction treatments in three teaching hospitals across Taiwan participated in the structured questionnaire survey in 2011. The hypothesized model comprising 10 latent variables was tested by Structural Equation Modeling using AMOS 17. Results Goodness-of-fit indexes, including χ2/DF = 1.871, PGFI = 0.746, PNFI = 0.764, and others, confirmed the modified model fit the data well. Marital stressor, importance of children, guilt-and-blame, and social stressor showed a direct effect on perceived stress. Instead of being a factor of stress, social support was directly and positively related to self-esteem. Perceived stress and self-esteem were the two major mediators for the relationships between stressors and mental symptoms. Increase in social support and self-esteem led to decrease in mental symptoms among the infertile patients. Conclusions The relational structures were identified and named as the Stressors Stress Symptoms Model, clinically applied to predict anxiety and depression from various stressors. Assessing sources and level of infertility-related stress and implementing culturally-sensitive counseling with an emphasis on positive personal value may assist in preventing the severity of depression and anxiety. PMID:26484531

Conceptual Hierarchies in a Flat Attractor Network

PubMed Central

O’Connor, Christopher M.; Cree, George S.; McRae, Ken

2009-01-01

The structure of people’s conceptual knowledge of concrete nouns has traditionally been viewed as hierarchical (Collins & Quillian, 1969). For example, superordinate concepts (vegetable) are assumed to reside at a higher level than basic-level concepts (carrot). A feature-based attractor network with a single layer of semantic features developed representations of both basic-level and superordinate concepts. No hierarchical structure was built into the network. In Experiment and Simulation 1, the graded structure of categories (typicality ratings) is accounted for by the flat attractor-network. Experiment and Simulation 2 show that, as with basic-level concepts, such a network predicts feature verification latencies for superordinate concepts (vegetable ). In Experiment and Simulation 3, counterintuitive results regarding the temporal dynamics of similarity in semantic priming are explained by the model. By treating both types of concepts the same in terms of representation, learning, and computations, the model provides new insights into semantic memory. PMID:19543434

On Muthen's Maximum Likelihood for Two-Level Covariance Structure Models

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Hayashi, Kentaro

2005-01-01

Data in social and behavioral sciences are often hierarchically organized. Special statistical procedures that take into account the dependence of such observations have been developed. Among procedures for 2-level covariance structure analysis, Muthen's maximum likelihood (MUML) has the advantage of easier computation and faster convergence. When…

EIT intensity noise spectroscopy power-broadening and level structure

NASA Astrophysics Data System (ADS)

Snider, Charles; Crescimanno, Michael; Oleary, Shannon

2011-05-01

One particularly interesting (and potentially technologically useful) characteristic of EIT coherence as viewed through intensity noise spectroscopy is its power-broadening resistant features. We detail a connection between the power broadening behavior and the underlying level structure by solving a more realistic quantum optics scenario modeled on recent experiments.

A two-way interface between limited Systems Biology Markup Language and R.

PubMed

Radivoyevitch, Tomas

2004-12-07

Systems Biology Markup Language (SBML) is gaining broad usage as a standard for representing dynamical systems as data structures. The open source statistical programming environment R is widely used by biostatisticians involved in microarray analyses. An interface between SBML and R does not exist, though one might be useful to R users interested in SBML, and SBML users interested in R. A model structure that parallels SBML to a limited degree is defined in R. An interface between this structure and SBML is provided through two function definitions: write.SBML() which maps this R model structure to SBML level 2, and read.SBML() which maps a limited range of SBML level 2 files back to R. A published model of purine metabolism is provided in this SBML-like format and used to test the interface. The model reproduces published time course responses before and after its mapping through SBML. List infrastructure preexisting in R makes it well-suited for manipulating SBML models. Further developments of this SBML-R interface seem to be warranted.

A two-way interface between limited Systems Biology Markup Language and R

PubMed Central

Radivoyevitch, Tomas

2004-01-01

Background Systems Biology Markup Language (SBML) is gaining broad usage as a standard for representing dynamical systems as data structures. The open source statistical programming environment R is widely used by biostatisticians involved in microarray analyses. An interface between SBML and R does not exist, though one might be useful to R users interested in SBML, and SBML users interested in R. Results A model structure that parallels SBML to a limited degree is defined in R. An interface between this structure and SBML is provided through two function definitions: write.SBML() which maps this R model structure to SBML level 2, and read.SBML() which maps a limited range of SBML level 2 files back to R. A published model of purine metabolism is provided in this SBML-like format and used to test the interface. The model reproduces published time course responses before and after its mapping through SBML. Conclusions List infrastructure preexisting in R makes it well-suited for manipulating SBML models. Further developments of this SBML-R interface seem to be warranted. PMID:15585059

Physical models have gender-specific effects on student understanding of protein structure-function relationships.

PubMed

Forbes-Lorman, Robin M; Harris, Michelle A; Chang, Wesley S; Dent, Erik W; Nordheim, Erik V; Franzen, Margaret A

2016-07-08

Understanding how basic structural units influence function is identified as a foundational/core concept for undergraduate biological and biochemical literacy. It is essential for students to understand this concept at all size scales, but it is often more difficult for students to understand structure-function relationships at the molecular level, which they cannot as effectively visualize. Students need to develop accurate, 3-dimensional mental models of biomolecules to understand how biomolecular structure affects cellular functions at the molecular level, yet most traditional curricular tools such as textbooks include only 2-dimensional representations. We used a controlled, backward design approach to investigate how hand-held physical molecular model use affected students' ability to logically predict structure-function relationships. Brief (one class period) physical model use increased quiz score for females, whereas there was no significant increase in score for males using physical models. Females also self-reported higher learning gains in their understanding of context-specific protein function. Gender differences in spatial visualization may explain the gender-specific benefits of physical model use observed. © 2016 The Authors Biochemistry and Molecular Biology Education published by Wiley Periodicals, Inc. on behalf of International Union of Biochemistry and Molecular Biology, 44(4):326-335, 2016. © 2016 The International Union of Biochemistry and Molecular Biology.

Field- and Remote Sensing-based Structural Attributes Measured at Multiple Scales Influence the Relationship Between Nitrogen and Reflectance of Forest Canopies

NASA Astrophysics Data System (ADS)

Sullivan, F.; Ollinger, S. V.; Palace, M. W.; Ouimette, A.; Sanders-DeMott, R.; Lepine, L. C.

2017-12-01

The correlation between near-infrared reflectance and forest canopy nitrogen concentration has been demonstrated at varying scales using a range of optical sensors on airborne and satellite platforms. Although the mechanism underpinning the relationship is unclear, at its basis are biologically-driven functional relationships of multiple plant traits that affect canopy chemistry and structure. The link between near-infrared reflectance and canopy nitrogen has been hypothesized to be partially driven by covariation of canopy nitrogen with canopy structure. In this study, we used a combination of airborne LiDAR data and field measured leaf and canopy chemical and structural traits to explore interrelationships between canopy nitrogen, near-infrared reflectance, and canopy structure on plots at Bartlett Experimental Forest in the White Mountain National Forest, New Hampshire. Over each plot, we developed a 1-meter resolution canopy height profile and a 1-meter resolution canopy height model. From canopy height profiles and canopy height models, we calculated a set of metrics describing the plot-level variability, breadth, depth, and arrangement of LiDAR returns. This combination of metrics was used to describe both vertical and horizontal variation in structure. In addition, we developed and measured several field-based metrics of leaf and canopy structure at the plot scale by directly measuring the canopy or by weighting leaf-level metrics by species leaf area contribution. We assessed relationships between leaf and structural metrics, near-infrared reflectance and canopy nitrogen concentration using multiple linear regression and mixed effects modeling. Consistent with our hypothesis, we found moderately strong links between both near-infrared reflectance and canopy nitrogen concentration with LiDAR-derived structural metrics, and we additionally found that leaf-level metrics scaled to the plot level share an important role in canopy reflectance. We suggest that canopy structure has a governing role in canopy reflectance, reducing maximum potential reflectance as structural complexity increases, and therefore also influences the relationship between canopy nitrogen and NIR reflectance.

Investigating Supervisory Relationships and Therapeutic Alliances Using Structural Equation Modeling

ERIC Educational Resources Information Center

DePue, Mary Kristina; Lambie, Glenn W.; Liu, Ren; Gonzalez, Jessica

2016-01-01

The authors used structural equation modeling to examine the contribution of supervisees' supervisory relationship levels to therapeutic alliance (TA) scores with their clients in practicum. Results showed that supervisory relationship scores positively contributed to the TA. Client and counselor ratings of the TA also differed.

Pressure And Thermal Modeling Of Rocket Launches

NASA Technical Reports Server (NTRS)

Smith, Sheldon D.; Myruski, Brian L.; Farmer, Richard C.; Freeman, Jon A.

1995-01-01

Report presents mathematical model for use in designing rocket-launching stand. Predicts pressure and thermal environment, as well as thermal responses of structures to impinging rocket-exhaust plumes. Enables relatively inexperienced analyst to determine time-varying distributions and absolute levels of pressure and heat loads on structures.

Geotechnical centrifuge use at University of Cambridge Geotechnical Centre, August-September 1991

NASA Astrophysics Data System (ADS)

Gilbert, Paul A.

1992-01-01

A geotechnical centrifuge applies elevated acceleration to small-scale soil models to simulate body forces and stress levels characteristic of full-size soil structures. Since the constitutive behavior of soil is stress level development, the centrifuge offers considerable advantage in studying soil structures using models. Several experiments were observed and described in relative detail, including experiments in soil dynamics and liquefaction study, an experiment investigation leaning towers on soft foundations, and an experiment investigating migration of hot pollutants through soils.

Visual Basic, Excel-based fish population modeling tool - The pallid sturgeon example

USGS Publications Warehouse

Moran, Edward H.; Wildhaber, Mark L.; Green, Nicholas S.; Albers, Janice L.

2016-02-10

The model presented in this report is a spreadsheet-based model using Visual Basic for Applications within Microsoft Excel (http://dx.doi.org/10.5066/F7057D0Z) prepared in cooperation with the U.S. Army Corps of Engineers and U.S. Fish and Wildlife Service. It uses the same model structure and, initially, parameters as used by Wildhaber and others (2015) for pallid sturgeon. The difference between the model structure used for this report and that used by Wildhaber and others (2015) is that variance is not partitioned. For the model of this report, all variance is applied at the iteration and time-step levels of the model. Wildhaber and others (2015) partition variance into parameter variance (uncertainty about the value of a parameter itself) applied at the iteration level and temporal variance (uncertainty caused by random environmental fluctuations with time) applied at the time-step level. They included implicit individual variance (uncertainty caused by differences between individuals) within the time-step level.The interface developed for the model of this report is designed to allow the user the flexibility to change population model structure and parameter values and uncertainty separately for every component of the model. This flexibility makes the modeling tool potentially applicable to any fish species; however, the flexibility inherent in this modeling tool makes it possible for the user to obtain spurious outputs. The value and reliability of the model outputs are only as good as the model inputs. Using this modeling tool with improper or inaccurate parameter values, or for species for which the structure of the model is inappropriate, could lead to untenable management decisions. By facilitating fish population modeling, this modeling tool allows the user to evaluate a range of management options and implications. The goal of this modeling tool is to be a user-friendly modeling tool for developing fish population models useful to natural resource managers to inform their decision-making processes; however, as with all population models, caution is needed, and a full understanding of the limitations of a model and the veracity of user-supplied parameters should always be considered when using such model output in the management of any species.

From Data-Sharing to Model-Sharing: SCEC and the Development of Earthquake System Science (Invited)

NASA Astrophysics Data System (ADS)

Jordan, T. H.

2009-12-01

Earthquake system science seeks to construct system-level models of earthquake phenomena and use them to predict emergent seismic behavior—an ambitious enterprise that requires high degree of interdisciplinary, multi-institutional collaboration. This presentation will explore model-sharing structures that have been successful in promoting earthquake system science within the Southern California Earthquake Center (SCEC). These include disciplinary working groups to aggregate data into community models; numerical-simulation working groups to investigate system-specific phenomena (process modeling) and further improve the data models (inverse modeling); and interdisciplinary working groups to synthesize predictive system-level models. SCEC has developed a cyberinfrastructure, called the Community Modeling Environment, that can distribute the community models; manage large suites of numerical simulations; vertically integrate the hardware, software, and wetware needed for system-level modeling; and promote the interactions among working groups needed for model validation and refinement. Various socio-scientific structures contribute to successful model-sharing. Two of the most important are “communities of trust” and collaborations between government and academic scientists on mission-oriented objectives. The latter include improvements of earthquake forecasts and seismic hazard models and the use of earthquake scenarios in promoting public awareness and disaster management.

Mathematical analysis of compressive/tensile molecular and nuclear structures

NASA Astrophysics Data System (ADS)

Wang, Dayu

Mathematical analysis in chemistry is a fascinating and critical tool to explain experimental observations. In this dissertation, mathematical methods to present chemical bonding and other structures for many-particle systems are discussed at different levels (molecular, atomic, and nuclear). First, the tetrahedral geometry of single, double, or triple carbon-carbon bonds gives an unsatisfying demonstration of bond lengths, compared to experimental trends. To correct this, Platonic solids and Archimedean solids were evaluated as atoms in covalent carbon or nitrogen bond systems in order to find the best solids for geometric fitting. Pentagonal solids, e.g. the dodecahedron and icosidodecahedron, give the best fit with experimental bond lengths; an ideal pyramidal solid which models covalent bonds was also generated. Second, the macroscopic compression/tension architectural approach was applied to forces at the molecular level, considering atomic interactions as compressive (repulsive) and tensile (attractive) forces. Two particle interactions were considered, followed by a model of the dihydrogen molecule (H2; two protons and two electrons). Dihydrogen was evaluated as two different types of compression/tension structures: a coaxial spring model and a ring model. Using similar methods, covalent diatomic molecules (made up of C, N, O, or F) were evaluated. Finally, the compression/tension model was extended to the nuclear level, based on the observation that nuclei with certain numbers of protons/neutrons (magic numbers) have extra stability compared to other nucleon ratios. A hollow spherical model was developed that combines elements of the classic nuclear shell model and liquid drop model. Nuclear structure and the trend of the "island of stability" for the current and extended periodic table were studied.

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

ERIC Educational Resources Information Center

Choi, Kilchan

2011-01-01

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

The Analysis of Elementary Mathematics Preservice Teachers' Spatial Orientation Skills with SOLO Model

ERIC Educational Resources Information Center

Özdemir, Ahmet Sükrü; Göktepe Yildiz, Sevda

2015-01-01

Problem Statement: The SOLO model places responses provided by students on a certain level instead of placing students there themselves. SOLO taxonomy, including five sub-levels, is used for determining observed structures of learning outcomes in various disciplines and grade levels. On the other hand, the spatial orientation skill is the ability…

Issue of Building Information Modelling Implementation into the Czech Republic’s Legislation using the Level of Development

NASA Astrophysics Data System (ADS)

Prušková, Kristýna; Nývlt, Vladimír

2017-10-01

The object of this paper is the issue of links between the Level of Development of particular project in Building Information Modeling environment and the projects of certain stages of project documentation within the existing Czech Republic’s Legislation. This research article uses the experiences from the initiative of active working group „WG#03: BIM & Realization“, which is the part of the Czech BIM Council, especially the document called “Draft of unified data structure for Building Information Modeling in the Czech Republic”. The findings of this paper are in the defining specific Level of Development of relative parameters, mentioned in this document, connected to the specific level of information and details requested by the Czech Republic’s Legislation. These findings could be used as an underlay to create document called “Level of Development draft assignment to the individual stages of project documentation in the Czech Republic”. The Level of Development is the most useful way of the information visualization, which leads to the most effortless way of exact stated implementation of Building Information Modeling into the practice of designing structures and buildings in the Czech Republic. The Implementation of using Building Information Modeling technology in designing structures and buildings will lead to the enhanced quality of the project documentation and generally to more effective cost savings during whole life cycle of buildings. Moreover, the all over using of the BIM technology in the Czech Republic will be very useful in the Facility Management area, especially in the facility management and maintenance of state buildings.

The consequences of ignoring measurement invariance for path coefficients in structural equation models

PubMed Central

Guenole, Nigel; Brown, Anna

2014-01-01

We report a Monte Carlo study examining the effects of two strategies for handling measurement non-invariance – modeling and ignoring non-invariant items – on structural regression coefficients between latent variables measured with item response theory models for categorical indicators. These strategies were examined across four levels and three types of non-invariance – non-invariant loadings, non-invariant thresholds, and combined non-invariance on loadings and thresholds – in simple, partial, mediated and moderated regression models where the non-invariant latent variable occupied predictor, mediator, and criterion positions in the structural regression models. When non-invariance is ignored in the latent predictor, the focal group regression parameters are biased in the opposite direction to the difference in loadings and thresholds relative to the referent group (i.e., lower loadings and thresholds for the focal group lead to overestimated regression parameters). With criterion non-invariance, the focal group regression parameters are biased in the same direction as the difference in loadings and thresholds relative to the referent group. While unacceptable levels of parameter bias were confined to the focal group, bias occurred at considerably lower levels of ignored non-invariance than was previously recognized in referent and focal groups. PMID:25278911

Biomimetic cellular metals-using hierarchical structuring for energy absorption.

PubMed

Bührig-Polaczek, A; Fleck, C; Speck, T; Schüler, P; Fischer, S F; Caliaro, M; Thielen, M

2016-07-19

Fruit walls as well as nut and seed shells typically perform a multitude of functions. One of the biologically most important functions consists in the direct or indirect protection of the seeds from mechanical damage or other negative environmental influences. This qualifies such biological structures as role models for the development of new materials and components that protect commodities and/or persons from damage caused for example by impacts due to rough handling or crashes. We were able to show how the mechanical properties of metal foam based components can be improved by altering their structure on various hierarchical levels inspired by features and principles important for the impact and/or puncture resistance of the biological role models, rather than by tuning the properties of the bulk material. For this various investigation methods have been established which combine mechanical testing with different imaging methods, as well as with in situ and ex situ mechanical testing methods. Different structural hierarchies especially important for the mechanical deformation and failure behaviour of the biological role models, pomelo fruit (Citrus maxima) and Macadamia integrifolia, were identified. They were abstracted and transferred into corresponding structural principles and thus hierarchically structured bio-inspired metal foams have been designed. A production route for metal based bio-inspired structures by investment casting was successfully established. This allows the production of complex and reliable structures, by implementing and combining different hierarchical structural elements found in the biological concept generators, such as strut design and integration of fibres, as well as by minimising casting defects. To evaluate the structural effects, similar investigation methods and mechanical tests were applied to both the biological role models and the metallic foams. As a result an even deeper quantitative understanding of the form-structure-function relationship of the biological concept generators as well as the bio-inspired metal foams was achieved, on deeper hierarchical levels and overarching different levels.

Implementation of the ANNs ensembles in macro-BIM cost estimates of buildings' floor structural frames

NASA Astrophysics Data System (ADS)

Juszczyk, Michał

2018-04-01

This paper reports some results of the studies on the use of artificial intelligence tools for the purposes of cost estimation based on building information models. A problem of the cost estimates based on the building information models on a macro level supported by the ensembles of artificial neural networks is concisely discussed. In the course of the research a regression model has been built for the purposes of cost estimation of buildings' floor structural frames, as higher level elements. Building information models are supposed to serve as a repository of data used for the purposes of cost estimation. The core of the model is the ensemble of neural networks. The developed model allows the prediction of cost estimates with satisfactory accuracy.

A cascaded neuro-computational model for spoken word recognition

NASA Astrophysics Data System (ADS)

Hoya, Tetsuya; van Leeuwen, Cees

2010-03-01

In human speech recognition, words are analysed at both pre-lexical (i.e., sub-word) and lexical (word) levels. The aim of this paper is to propose a constructive neuro-computational model that incorporates both these levels as cascaded layers of pre-lexical and lexical units. The layered structure enables the system to handle the variability of real speech input. Within the model, receptive fields of the pre-lexical layer consist of radial basis functions; the lexical layer is composed of units that perform pattern matching between their internal template and a series of labels, corresponding to the winning receptive fields in the pre-lexical layer. The model adapts through self-tuning of all units, in combination with the formation of a connectivity structure through unsupervised (first layer) and supervised (higher layers) network growth. Simulation studies show that the model can achieve a level of performance in spoken word recognition similar to that of a benchmark approach using hidden Markov models, while enabling parallel access to word candidates in lexical decision making.

Variable Complexity Optimization of Composite Structures

NASA Technical Reports Server (NTRS)

Haftka, Raphael T.

2002-01-01

The use of several levels of modeling in design has been dubbed variable complexity modeling. The work under the grant focused on developing variable complexity modeling strategies with emphasis on response surface techniques. Applications included design of stiffened composite plates for improved damage tolerance, the use of response surfaces for fitting weights obtained by structural optimization, and design against uncertainty using response surface techniques.

Coarse-grained mechanics of viral shells

NASA Astrophysics Data System (ADS)

Klug, William S.; Gibbons, Melissa M.

2008-03-01

We present an approach for creating three-dimensional finite element models of viral capsids from atomic-level structural data (X-ray or cryo-EM). The models capture heterogeneous geometric features and are used in conjunction with three-dimensional nonlinear continuum elasticity to simulate nanoindentation experiments as performed using atomic force microscopy. The method is extremely flexible; able to capture varying levels of detail in the three-dimensional structure. Nanoindentation simulations are presented for several viruses: Hepatitis B, CCMV, HK97, and φ29. In addition to purely continuum elastic models a multiscale technique is developed that combines finite-element kinematics with MD energetics such that large-scale deformations are facilitated by a reduction in degrees of freedom. Simulations of these capsid deformation experiments provide a testing ground for the techniques, as well as insight into the strength-determining mechanisms of capsid deformation. These methods can be extended as a framework for modeling other proteins and macromolecular structures in cell biology.

Das Bremerhavener Grundwasser im Klimawandel - Eine FREEWAT-Fallstudie

NASA Astrophysics Data System (ADS)

Panteleit, Björn; Jensen, Sven; Seiter, Katherina; Siebert, Yvonne

2018-01-01

A 3D structural model was created for the state of Bremen based on an extensive borehole database. Parameters were assigned to the model by interpretation and interpolation of the borehole descriptions. This structural model was transferred into a flow model via the FREEWAT platform, an open-source plug-in of the free QGIS software, with connection to the MODFLOW code. This groundwater management tool is intended for long-term use. As a case study for the FREEWAT Project, possible effects of climate change on groundwater levels in the Bremerhaven area have been simulated. In addition to the calibration year 2010, scenarios with a sea-level rise and decreasing groundwater recharge were simulated for the years 2040, 2070 and 2100. In addition to seawater intrusion in the coastal area, declining groundwater levels are also a concern. Possibilities for future groundwater management already include active control of the water level of a lake and the harbor basin. With the help of a focused groundwater monitoring program based on the model results, the planned flow model can become an important forecasting tool for groundwater management within the framework of the planned continuous model management and for representing the effects of changing climatic conditions and mitigation measures.

Crystal field analysis of the energy level structure of Cs2NaAlF6:Cr3+

NASA Astrophysics Data System (ADS)

Rudowicz, C.; Brik, M. G.; Avram, N. M.; Yeung, Y. Y.; Gnutek, P.

2006-06-01

An analysis of the energy level structure of Cr3+ ions in Cs2NaAlF6 crystal is performed using the exchange charge model (ECM) together with the crystal field analysis/microscopic spin Hamiltonian (CFA/MSH) computer package. Utilizing the crystal structure data, our approach enables modelling of the crystal field parameters (CFPs) and thus the energy level structure for Cr3+ ions at the two crystallographically inequivalent sites in Cs2NaAlF6. Using the ECM initial adjustment procedure, the CFPs are calculated in the crystallographic axis system centred at the Cr3+ ion at each site. Additionally the CFPs are also calculated using the superposition model (SPM). The ECM and SPM predicted CFP values match very well. Consideration of the symmetry aspects for the so-obtained CFP datasets reveals that the latter axis system matches the symmetry-adapted axis system related directly to the six Cr-F bonds well. Using the ECM predicted CFPs as an input for the CFA/MSH package, the complete energy level schemes are calculated for Cr3+ ions at the two sites. Comparison of the theoretical results with the experimental spectroscopic data yields satisfactory agreement. Our results confirm that the actual symmetry at both impurity sites I and II in the Cs2NaAlF6:Cr3+ system is trigonal D3d. The ECM predicted CFPs may be used as the initial (starting) parameters for simulations and fittings of the energy levels for Cr3+ ions in structurally similar hosts.

A Modal Model to Simulate Typical Structural Dynamic Nonlinearity [PowerPoint

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

Mayes, Randall L.; Pacini, Benjamin Robert; Roettgen, Dan

2016-01-01

Some initial investigations have been published which simulate nonlinear response with almost traditional modal models: instead of connecting the modal mass to ground through the traditional spring and damper, a nonlinear Iwan element was added. This assumes that the mode shapes do not change with amplitude and there are no interactions between modal degrees of freedom. This work expands on these previous studies. An impact experiment is performed on a structure which exhibits typical structural dynamic nonlinear response, i.e. weak frequency dependence and strong damping dependence on the amplitude of vibration. Use of low level modal test results in combinationmore » with high level impacts are processed using various combinations of modal filtering, the Hilbert Transform and band-pass filtering to develop response data that are then fit with various nonlinear elements to create a nonlinear pseudo-modal model. Simulations of forced response are compared with high level experimental data for various nonlinear element assumptions.« less

A Modal Model to Simulate Typical Structural Dynamic Nonlinearity

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

Pacini, Benjamin Robert; Mayes, Randall L.; Roettgen, Daniel R

2015-10-01

Some initial investigations have been published which simulate nonlinear response with almost traditional modal models: instead of connecting the modal mass to ground through the traditional spring and damper, a nonlinear Iwan element was added. This assumes that the mode shapes do not change with amplitude and there are no interactions between modal degrees of freedom. This work expands on these previous studies. An impact experiment is performed on a structure which exhibits typical structural dynamic nonlinear response, i.e. weak frequency dependence and strong damping dependence on the amplitude of vibration. Use of low level modal test results in combinationmore » with high level impacts are processed using various combinations of modal filtering, the Hilbert Transform and band-pass filtering to develop response data that are then fit with various nonlinear elements to create a nonlinear pseudo-modal model. Simulations of forced response are compared with high level experimental data for various nonlinear element assumptions.« less

Organizational home care models across Europe: A cross sectional study.

PubMed

Van Eenoo, Liza; van der Roest, Henriëtte; Onder, Graziano; Finne-Soveri, Harriet; Garms-Homolova, Vjenka; Jonsson, Palmi V; Draisma, Stasja; van Hout, Hein; Declercq, Anja

2018-01-01

Decision makers are searching for models to redesign home care and to organize health care in a more sustainable way. The aim of this study is to identify and characterize home care models within and across European countries by means of structural characteristics and care processes at the policy and the organization level. At the policy level, variables that reflected variation in health care policy were included based on a literature review on the home care policy for older persons in six European countries: Belgium, Finland, Germany, Iceland, Italy, and the Netherlands. At the organizational level, data on the structural characteristics and the care processes were collected from 36 home care organizations by means of a survey. Data were collected between 2013 and 2015 during the IBenC project. An observational, cross sectional, quantitative design was used. The analyses consisted of a principal component analysis followed by a hierarchical cluster analysis. Fifteen variables at the organizational level, spread across three components, explained 75.4% of the total variance. The three components made it possible to distribute home care organizations into six care models that differ on the level of patient-centered care delivery, the availability of specialized care professionals, and the level of monitoring care performance. Policy level variables did not contribute to distinguishing between home care models. Six home care models were identified and characterized. These models can be used to describe best practices. Copyright © 2017 Elsevier Ltd. All rights reserved.

Control structural interaction testbed: A model for multiple flexible body verification

NASA Technical Reports Server (NTRS)

Chory, M. A.; Cohen, A. L.; Manning, R. A.; Narigon, M. L.; Spector, V. A.

1993-01-01

Conventional end-to-end ground tests for verification of control system performance become increasingly complicated with the development of large, multiple flexible body spacecraft structures. The expense of accurately reproducing the on-orbit dynamic environment and the attendant difficulties in reducing and accounting for ground test effects limits the value of these tests. TRW has developed a building block approach whereby a combination of analysis, simulation, and test has replaced end-to-end performance verification by ground test. Tests are performed at the component, subsystem, and system level on engineering testbeds. These tests are aimed at authenticating models to be used in end-to-end performance verification simulations: component and subassembly engineering tests and analyses establish models and critical parameters, unit level engineering and acceptance tests refine models, and subsystem level tests confirm the models' overall behavior. The Precision Control of Agile Spacecraft (PCAS) project has developed a control structural interaction testbed with a multibody flexible structure to investigate new methods of precision control. This testbed is a model for TRW's approach to verifying control system performance. This approach has several advantages: (1) no allocation for test measurement errors is required, increasing flight hardware design allocations; (2) the approach permits greater latitude in investigating off-nominal conditions and parametric sensitivities; and (3) the simulation approach is cost effective, because the investment is in understanding the root behavior of the flight hardware and not in the ground test equipment and environment.

Quantifying inter- and intra-population niche variability using hierarchical bayesian stable isotope mixing models.

PubMed

Semmens, Brice X; Ward, Eric J; Moore, Jonathan W; Darimont, Chris T

2009-07-09

Variability in resource use defines the width of a trophic niche occupied by a population. Intra-population variability in resource use may occur across hierarchical levels of population structure from individuals to subpopulations. Understanding how levels of population organization contribute to population niche width is critical to ecology and evolution. Here we describe a hierarchical stable isotope mixing model that can simultaneously estimate both the prey composition of a consumer diet and the diet variability among individuals and across levels of population organization. By explicitly estimating variance components for multiple scales, the model can deconstruct the niche width of a consumer population into relevant levels of population structure. We apply this new approach to stable isotope data from a population of gray wolves from coastal British Columbia, and show support for extensive intra-population niche variability among individuals, social groups, and geographically isolated subpopulations. The analytic method we describe improves mixing models by accounting for diet variability, and improves isotope niche width analysis by quantitatively assessing the contribution of levels of organization to the niche width of a population.

Optimizing a desirable fare structure for a bus-subway corridor

PubMed Central

Liu, Bing-Zheng; Ge, Ying-En; Cao, Kai; Jiang, Xi; Meng, Lingyun; Liu, Ding; Gao, Yunfeng

2017-01-01

This paper aims to optimize a desirable fare structure for the public transit service along a bus-subway corridor with the consideration of those factors related to equity in trip, including travel distance and comfort level. The travel distance factor is represented by the distance-based fare strategy, which is an existing differential strategy. The comfort level one is considered in the area-based fare strategy which is a new differential strategy defined in this paper. Both factors are referred to by the combined fare strategy which is composed of distance-based and area-based fare strategies. The flat fare strategy is applied to determine a reference level of social welfare and obtain the general passenger flow along transit lines, which is used to divide areas or zones along the corridor. This problem is formulated as a bi-level program, of which the upper level maximizes the social welfare and the lower level capturing traveler choice behavior is a variable-demand stochastic user equilibrium assignment model. A genetic algorithm is applied to solve the bi-level program while the method of successive averages is adopted to solve the lower-level model. A series of numerical experiments are carried out to illustrate the performance of the models and solution methods. Numerical results indicate that all three differential fare strategies play a better role in enhancing the social welfare than the flat fare strategy and that the fare structure under the combined fare strategy generates the highest social welfare and the largest resulting passenger demand, which implies that the more equity factors a differential fare strategy involves the more desirable fare structure the strategy has. PMID:28981508

Optimizing a desirable fare structure for a bus-subway corridor.

PubMed

Liu, Bing-Zheng; Ge, Ying-En; Cao, Kai; Jiang, Xi; Meng, Lingyun; Liu, Ding; Gao, Yunfeng

2017-01-01

This paper aims to optimize a desirable fare structure for the public transit service along a bus-subway corridor with the consideration of those factors related to equity in trip, including travel distance and comfort level. The travel distance factor is represented by the distance-based fare strategy, which is an existing differential strategy. The comfort level one is considered in the area-based fare strategy which is a new differential strategy defined in this paper. Both factors are referred to by the combined fare strategy which is composed of distance-based and area-based fare strategies. The flat fare strategy is applied to determine a reference level of social welfare and obtain the general passenger flow along transit lines, which is used to divide areas or zones along the corridor. This problem is formulated as a bi-level program, of which the upper level maximizes the social welfare and the lower level capturing traveler choice behavior is a variable-demand stochastic user equilibrium assignment model. A genetic algorithm is applied to solve the bi-level program while the method of successive averages is adopted to solve the lower-level model. A series of numerical experiments are carried out to illustrate the performance of the models and solution methods. Numerical results indicate that all three differential fare strategies play a better role in enhancing the social welfare than the flat fare strategy and that the fare structure under the combined fare strategy generates the highest social welfare and the largest resulting passenger demand, which implies that the more equity factors a differential fare strategy involves the more desirable fare structure the strategy has.

Stress-strain state of the structure in the service area of underground railway

NASA Astrophysics Data System (ADS)

Barabash, M.; Bashinsky, Y.; Korjakins, A.

2017-10-01

The paper focuses on numerical study how vibration due to underground trains influences the load-bearing building structures. Diagrams of vibration levels for monolithic floor slab depending on frequency are obtained. Levels of vibrations on floor slabs and columns are measured. The simulation of dynamic load from underground railway onto load-bearing building structures is presented as an example with account of load transmission through the soil. Recommendations for generation of design model in dynamic analysis of structure are provided.

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.

A software-based sensor for combined sewer overflows.

PubMed

Leonhardt, G; Fach, S; Engelhard, C; Kinzel, H; Rauch, W

2012-01-01

A new methodology for online estimation of excess flow from combined sewer overflow (CSO) structures based on simulation models is presented. If sufficient flow and water level data from the sewer system is available, no rainfall data are needed to run the model. An inverse rainfall-runoff model was developed to simulate net rainfall based on flow and water level data. Excess flow at all CSO structures in a catchment can then be simulated with a rainfall-runoff model. The method is applied to a case study and results show that the inverse rainfall-runoff model can be used instead of missing rain gauges. Online operation is ensured by software providing an interface to the SCADA-system of the operator and controlling the model. A water quality model could be included to simulate also pollutant concentrations in the excess flow.

Analysis of factors affecting satisfaction level on problem based learning approach using structural equation modeling

NASA Astrophysics Data System (ADS)

Hussain, Nur Farahin Mee; Zahid, Zalina

2014-12-01

Nowadays, in the job market demand, graduates are expected not only to have higher performance in academic but they must also be excellent in soft skill. Problem-Based Learning (PBL) has a number of distinct advantages as a learning method as it can deliver graduates that will be highly prized by industry. This study attempts to determine the satisfaction level of engineering students on the PBL Approach and to evaluate their determinant factors. The Structural Equation Modeling (SEM) was used to investigate how the factors of Good Teaching Scale, Clear Goals, Student Assessment and Levels of Workload affected the student satisfaction towards PBL approach.

[Topographological-anatomic changes in the structure of temporo-mandibular joint in case of fracture of the mandible condylar process at cervical level].

PubMed

Volkov, S I; Bazhenov, D V; Semkin, V A

2011-01-01

Pathological changes in soft tissues surrounding the fracture site as well as in the structural elements of temporo-mandibular joint always occured in condylar process fracture with shift at cervical mandibular jaw level. Other changes were also seen in the joint on the opposite normal side. Modelling of condylar process fracture at mandibular cervical level by means of three-dimensional computer model of temporo-mandibular joint contributed to proper understanding of this pathology emergence as well as to prediction and elimination of disorders arising in adjacent to the fracture site tissues.

Effect of Material Ion Exchanges on the Mechanical Stiffness Properties and Shear Deformation of Hydrated Cement Material Chemistry Structure C-S-H Jennite -- A Computational Modeling Study

NASA Astrophysics Data System (ADS)

Adebiyi, Babatunde Mattew

Material properties and performance are governed by material molecular chemistry structures and molecular level interactions. Methods to understand relationships between the material properties and performance and their correlation to the molecular level chemistry and morphology, and thus find ways of manipulating and adjusting matters at the atomistic level in order to improve material performance, are required. A computational material modeling methodology is investigated and demonstrated for a key cement hydrated component material chemistry structure of Calcium-Silicate-Hydrate (C-S-H) Jennite in this work. The effect of material ion exchanges on the mechanical stiffness properties and shear deformation behavior of hydrated cement material chemistry structure of Calcium Silicate Hydrate (C-S-H) Jennite was studied. Calcium ions were replaced with Magnesium ions in Jennite structure of the C-S-H gel. Different level of substitution of the ions was used. The traditional Jennite structure was obtained from the American Mineralogist Crystal Structure Database and super cells of the structures were created using a Molecular Dynamics Analyzer and Visualizer Material Studio. Molecular dynamics parameters used in the modeling analysis were determined by carrying out initial dynamic studies. 64 unit cell of C-S-H Jennite was used in material modeling analysis studies based on convergence results obtained from the elastic modulus and total energies. NVT forcite dynamics using COMPASS force field based on 200 ps dynamics time was used to determine mechanical modulus of the traditional C-S-H gel and the Magnesium ion modified structures. NVT Discover dynamics using COMPASS forcefield was used in the material modeling studies to investigate the influence of ionic exchange on the shear deformation of the associated material chemistry structures. A prior established quasi-static deformation method to emulate shear deformation of C-S-H material chemistry structure that is based on a triclinic crystal structure was used, by deforming the triclinic crystal structure at 0.2 degree per time step for 75 steps of deformation. It was observed that there is a decrease in the total energies of the systems as the percentage of magnesium ion increases in the C-S-H Jennite molecular structure systems. Investigation of effect of ion exchange on the elastic modulus shows that the elastic stiffness modulus tends to decrease as the amount of Mg in the systems increases, using either COMPASS or universal force field. On the other hand, shear moduli obtained after deforming the structures computed from the stress-strain curve obtained from material modeling increases as the amount of Mg increases in the system. The present investigations also showed that ultimate shear stress obtained from predicted shear stress---strain also increases with amount of Mg in the chemistry structure. Present study clearly demonstrates that computational material modeling following molecular dynamics analysis methodology is an effective way to predict and understand the effective material chemistry and additive changes on the stiffness and deformation characteristics in cementitious materials, and the results suggest that this method can be extended to other materials.

Software for Estimating Costs of Testing Rocket Engines

NASA Technical Reports Server (NTRS)

Hines, Merlon M.

2004-01-01

A high-level parametric mathematical model for estimating the costs of testing rocket engines and components at Stennis Space Center has been implemented as a Microsoft Excel program that generates multiple spreadsheets. The model and the program are both denoted, simply, the Cost Estimating Model (CEM). The inputs to the CEM are the parameters that describe particular tests, including test types (component or engine test), numbers and duration of tests, thrust levels, and other parameters. The CEM estimates anticipated total project costs for a specific test. Estimates are broken down into testing categories based on a work-breakdown structure and a cost-element structure. A notable historical assumption incorporated into the CEM is that total labor times depend mainly on thrust levels. As a result of a recent modification of the CEM to increase the accuracy of predicted labor times, the dependence of labor time on thrust level is now embodied in third- and fourth-order polynomials.

Software for Estimating Costs of Testing Rocket Engines

NASA Technical Reports Server (NTRS)

Hines, Merion M.

2002-01-01

A high-level parametric mathematical model for estimating the costs of testing rocket engines and components at Stennis Space Center has been implemented as a Microsoft Excel program that generates multiple spreadsheets. The model and the program are both denoted, simply, the Cost Estimating Model (CEM). The inputs to the CEM are the parameters that describe particular tests, including test types (component or engine test), numbers and duration of tests, thrust levels, and other parameters. The CEM estimates anticipated total project costs for a specific test. Estimates are broken down into testing categories based on a work-breakdown structure and a cost-element structure. A notable historical assumption incorporated into the CEM is that total labor times depend mainly on thrust levels. As a result of a recent modification of the CEM to increase the accuracy of predicted labor times, the dependence of labor time on thrust level is now embodied in third- and fourth-order polynomials.

Software for Estimating Costs of Testing Rocket Engines

NASA Technical Reports Server (NTRS)

Hines, Merlon M.

2003-01-01

A high-level parametric mathematical model for estimating the costs of testing rocket engines and components at Stennis Space Center has been implemented as a Microsoft Excel program that generates multiple spreadsheets. The model and the program are both denoted, simply, the Cost Estimating Model (CEM). The inputs to the CEM are the parameters that describe particular tests, including test types (component or engine test), numbers and duration of tests, thrust levels, and other parameters. The CEM estimates anticipated total project costs for a specific test. Estimates are broken down into testing categories based on a work-breakdown structure and a cost-element structure. A notable historical assumption incorporated into the CEM is that total labor times depend mainly on thrust levels. As a result of a recent modification of the CEM to increase the accuracy of predicted labor times, the dependence of labor time on thrust level is now embodied in third- and fourth-order polynomials.

Bilevel Model-Based Discriminative Dictionary Learning for Recognition.

PubMed

Zhou, Pan; Zhang, Chao; Lin, Zhouchen

2017-03-01

Most supervised dictionary learning methods optimize the combinations of reconstruction error, sparsity prior, and discriminative terms. Thus, the learnt dictionaries may not be optimal for recognition tasks. Also, the sparse codes learning models in the training and the testing phases are inconsistent. Besides, without utilizing the intrinsic data structure, many dictionary learning methods only employ the l 0 or l 1 norm to encode each datum independently, limiting the performance of the learnt dictionaries. We present a novel bilevel model-based discriminative dictionary learning method for recognition tasks. The upper level directly minimizes the classification error, while the lower level uses the sparsity term and the Laplacian term to characterize the intrinsic data structure. The lower level is subordinate to the upper level. Therefore, our model achieves an overall optimality for recognition in that the learnt dictionary is directly tailored for recognition. Moreover, the sparse codes learning models in the training and the testing phases can be the same. We further propose a novel method to solve our bilevel optimization problem. It first replaces the lower level with its Karush-Kuhn-Tucker conditions and then applies the alternating direction method of multipliers to solve the equivalent problem. Extensive experiments demonstrate the effectiveness and robustness of our method.

Application of nonlinear least-squares regression to ground-water flow modeling, west-central Florida

USGS Publications Warehouse

Yobbi, D.K.

2000-01-01

A nonlinear least-squares regression technique for estimation of ground-water flow model parameters was applied to an existing model of the regional aquifer system underlying west-central Florida. The regression technique minimizes the differences between measured and simulated water levels. Regression statistics, including parameter sensitivities and correlations, were calculated for reported parameter values in the existing model. Optimal parameter values for selected hydrologic variables of interest are estimated by nonlinear regression. Optimal estimates of parameter values are about 140 times greater than and about 0.01 times less than reported values. Independently estimating all parameters by nonlinear regression was impossible, given the existing zonation structure and number of observations, because of parameter insensitivity and correlation. Although the model yields parameter values similar to those estimated by other methods and reproduces the measured water levels reasonably accurately, a simpler parameter structure should be considered. Some possible ways of improving model calibration are to: (1) modify the defined parameter-zonation structure by omitting and/or combining parameters to be estimated; (2) carefully eliminate observation data based on evidence that they are likely to be biased; (3) collect additional water-level data; (4) assign values to insensitive parameters, and (5) estimate the most sensitive parameters first, then, using the optimized values for these parameters, estimate the entire data set.

Tensor Analysis Reveals Distinct Population Structure that Parallels the Different Computational Roles of Areas M1 and V1

PubMed Central

Ryu, Stephen I.; Shenoy, Krishna V.; Cunningham, John P.; Churchland, Mark M.

2016-01-01

Cortical firing rates frequently display elaborate and heterogeneous temporal structure. One often wishes to compute quantitative summaries of such structure—a basic example is the frequency spectrum—and compare with model-based predictions. The advent of large-scale population recordings affords the opportunity to do so in new ways, with the hope of distinguishing between potential explanations for why responses vary with time. We introduce a method that assesses a basic but previously unexplored form of population-level structure: when data contain responses across multiple neurons, conditions, and times, they are naturally expressed as a third-order tensor. We examined tensor structure for multiple datasets from primary visual cortex (V1) and primary motor cortex (M1). All V1 datasets were ‘simplest’ (there were relatively few degrees of freedom) along the neuron mode, while all M1 datasets were simplest along the condition mode. These differences could not be inferred from surface-level response features. Formal considerations suggest why tensor structure might differ across modes. For idealized linear models, structure is simplest across the neuron mode when responses reflect external variables, and simplest across the condition mode when responses reflect population dynamics. This same pattern was present for existing models that seek to explain motor cortex responses. Critically, only dynamical models displayed tensor structure that agreed with the empirical M1 data. These results illustrate that tensor structure is a basic feature of the data. For M1 the tensor structure was compatible with only a subset of existing models. PMID:27814353

Analyzing and designing object-oriented missile simulations with concurrency

NASA Astrophysics Data System (ADS)

Randorf, Jeffrey Allen

2000-11-01

A software object model for the six degree-of-freedom missile modeling domain is presented. As a precursor, a domain analysis of the missile modeling domain was started, based on the Feature-Oriented Domain Analysis (FODA) technique described by the Software Engineering Institute (SEI). It was subsequently determined the FODA methodology is functionally equivalent to the Object Modeling Technique. The analysis used legacy software documentation and code from the ENDOSIM, KDEC, and TFrames 6-DOF modeling tools, including other technical literature. The SEI Object Connection Architecture (OCA) was the template for designing the object model. Three variants of the OCA were considered---a reference structure, a recursive structure, and a reference structure with augmentation for flight vehicle modeling. The reference OCA design option was chosen for maintaining simplicity while not compromising the expressive power of the OMT model. The missile architecture was then analyzed for potential areas of concurrent computing. It was shown how protected objects could be used for data passing between OCA object managers, allowing concurrent access without changing the OCA reference design intent or structure. The implementation language was the 1995 release of Ada. OCA software components were shown how to be expressed as Ada child packages. While acceleration of several low level and other high operations level are possible on proper hardware, there was a 33% degradation of 4th order Runge-Kutta integrator performance of two simultaneous ordinary differential equations using Ada tasking on a single processor machine. The Defense Department's High Level Architecture was introduced and explained in context with the OCA. It was shown the HLA and OCA were not mutually exclusive architectures, but complimentary. HLA was shown as an interoperability solution, with the OCA as an architectural vehicle for software reuse. Further directions for implementing a 6-DOF missile modeling environment are discussed.

Entropy of level-cut random Gaussian structures at different volume fractions

NASA Astrophysics Data System (ADS)

Marčelja, Stjepan

2017-10-01

Cutting random Gaussian fields at a given level can create a variety of morphologically different two- or several-phase structures that have often been used to describe physical systems. The entropy of such structures depends on the covariance function of the generating Gaussian random field, which in turn depends on its spectral density. But the entropy of level-cut structures also depends on the volume fractions of different phases, which is determined by the selection of the cutting level. This dependence has been neglected in earlier work. We evaluate the entropy of several lattice models to show that, even in the cases of strongly coupled systems, the dependence of the entropy of level-cut structures on molar fractions of the constituents scales with the simple ideal noninteracting system formula. In the last section, we discuss the application of the results to binary or ternary fluids and microemulsions.

Acoustic design criteria in a general system for structural optimization

NASA Technical Reports Server (NTRS)

Brama, Torsten

1990-01-01

Passenger comfort is of great importance in most transport vehicles. For instance, in the new generation of regional turboprop aircraft, a low noise level is vital to be competitive on the market. The possibilities to predict noise levels analytically has improved rapidly in recent years. This will make it possible to take acoustic design criteria into account in early project stages. The development of the ASKA FE-system to include also acoustic analysis has been carried out at Saab Aircraft Division and the Aeronautical Research Institute of Sweden in a joint project. New finite elements have been developed to model the free fluid, porous damping materials, and the interaction between the fluid and structural degrees of freedom. The FE approach to the acoustic analysis is best suited for lower frequencies up to a few hundred Hz. For accurate analysis of interior cabin noise, large 3-D FE-models are built, but 2-D models are also considered to be useful for parametric studies and optimization. The interest is here focused on the introduction of an acoustic design criteria in the general structural optimization system OPTSYS available at the Saab Aircraft Division. The first implementation addresses a somewhat limited class of problems. The problems solved are formulated: Minimize the structural weight by modifying the dimensions of the structure while keeping the noise level in the cavity and other structural design criteria within specified limits.

Spectrodirectional Investigation of a Geometric-Optical Canopy Reflectance Model by Laboratory Simulation

NASA Astrophysics Data System (ADS)

Stanford, Adam Christopher

Canopy reflectance models (CRMs) can accurately estimate vegetation canopy biophysical-structural information such as Leaf Area Index (LAI) inexpensively using satellite imagery. The strict physical basis which geometric-optical CRMs employ to mathematically link canopy bidirectional reflectance and structure allows for the tangible replication of a CRM's geometric abstraction of a canopy in the laboratory, enabling robust CRM validation studies. To this end, the ULGS-2 goniometer was used to obtain multiangle, hyperspectral (Spectrodirectional) measurements of a specially-designed tangible physical model forest, developed based upon the Geometric-Optical Mutual Shadowing (GOMS) CRM, at three different canopy cover densities. GOMS forward-modelled reflectance values had high levels of agreement with ULGS-2 measurements, with obtained reflectance RMSE values ranging from 0.03% to 0.1%. Canopy structure modelled via GOMS Multiple-Forward-Mode (MFM) inversion had varying levels of success. The methods developed in this thesis can potentially be extended to more complex CRMs through the implementation of 3D printing.

The self as a mediator between personality and adjustment.

PubMed

Graziano, W G; Jensen-Campbell, L A; Finch, J F

1997-08-01

The self can be conceptualized as a mediating agent that translates personality into situated goal-directed activities and adaptation. This research used a level-of-analysis approach to link personality dimensions (Level I) to self-systems (Level II) and to teacher ratings of adjustment in African American, Mexican American, and European American students (N = 317). The authors hypothesized that links among aspects of self-esteem and teacher ratings of adjustment would be domain specific, and those links to dimensions of the 5-factor model would reflects the domain specificity. Structural equation modeling corroborated hypotheses about domain specificity in links between adjustment and 5-factor dimensions. Results were discussed in terms of levels of analysis for personality structure, personality development, and age-related adaptations to social contexts.

Symbolic modeling of human anatomy for visualization and simulation

NASA Astrophysics Data System (ADS)

Pommert, Andreas; Schubert, Rainer; Riemer, Martin; Schiemann, Thomas; Tiede, Ulf; Hoehne, Karl H.

1994-09-01

Visualization of human anatomy in a 3D atlas requires both spatial and more abstract symbolic knowledge. Within our 'intelligent volume' model which integrates these two levels, we developed and implemented a semantic network model for describing human anatomy. Concepts for structuring (abstraction levels, domains, views, generic and case-specific modeling, inheritance) are introduced. Model, tools for generation and exploration and applications in our 3D anatomical atlas are presented and discussed.

Linear mixed-effects models to describe individual tree crown width for China-fir in Fujian Province, southeast China.

PubMed

Hao, Xu; Yujun, Sun; Xinjie, Wang; Jin, Wang; Yao, Fu

2015-01-01

A multiple linear model was developed for individual tree crown width of Cunninghamia lanceolata (Lamb.) Hook in Fujian province, southeast China. Data were obtained from 55 sample plots of pure China-fir plantation stands. An Ordinary Linear Least Squares (OLS) regression was used to establish the crown width model. To adjust for correlations between observations from the same sample plots, we developed one level linear mixed-effects (LME) models based on the multiple linear model, which take into account the random effects of plots. The best random effects combinations for the LME models were determined by the Akaike's information criterion, the Bayesian information criterion and the -2logarithm likelihood. Heteroscedasticity was reduced by three residual variance functions: the power function, the exponential function and the constant plus power function. The spatial correlation was modeled by three correlation structures: the first-order autoregressive structure [AR(1)], a combination of first-order autoregressive and moving average structures [ARMA(1,1)], and the compound symmetry structure (CS). Then, the LME model was compared to the multiple linear model using the absolute mean residual (AMR), the root mean square error (RMSE), and the adjusted coefficient of determination (adj-R2). For individual tree crown width models, the one level LME model showed the best performance. An independent dataset was used to test the performance of the models and to demonstrate the advantage of calibrating LME models.

State-level minimum wage and heart disease death rates in the United States, 1980-2015: A novel application of marginal structural modeling.

PubMed

Van Dyke, Miriam E; Komro, Kelli A; Shah, Monica P; Livingston, Melvin D; Kramer, Michael R

2018-07-01

Despite substantial declines since the 1960's, heart disease remains the leading cause of death in the United States (US) and geographic disparities in heart disease mortality have grown. State-level socioeconomic factors might be important contributors to geographic differences in heart disease mortality. This study examined the association between state-level minimum wage increases above the federal minimum wage and heart disease death rates from 1980 to 2015 among 'working age' individuals aged 35-64 years in the US. Annual, inflation-adjusted state and federal minimum wage data were extracted from legal databases and annual state-level heart disease death rates were obtained from CDC Wonder. Although most minimum wage and health studies to date use conventional regression models, we employed marginal structural models to account for possible time-varying confounding. Quasi-experimental, marginal structural models accounting for state, year, and state × year fixed effects estimated the association between increases in the state-level minimum wage above the federal minimum wage and heart disease death rates. In models of 'working age' adults (35-64 years old), a $1 increase in the state-level minimum wage above the federal minimum wage was on average associated with ~6 fewer heart disease deaths per 100,000 (95% CI: -10.4, -1.99), or a state-level heart disease death rate that was 3.5% lower per year. In contrast, for older adults (65+ years old) a $1 increase was on average associated with a 1.1% lower state-level heart disease death rate per year (b = -28.9 per 100,000, 95% CI: -71.1, 13.3). State-level economic policies are important targets for population health research. Copyright © 2018 Elsevier Inc. All rights reserved.

Versatile Micromechanics Model for Multiscale Analysis of Composite Structures

NASA Astrophysics Data System (ADS)

Kwon, Y. W.; Park, M. S.

2013-08-01

A general-purpose micromechanics model was developed so that the model could be applied to various composite materials such as reinforced by particles, long fibers and short fibers as well as those containing micro voids. Additionally, the model can be used with hierarchical composite materials. The micromechanics model can be used to compute effective material properties like elastic moduli, shear moduli, Poisson's ratios, and coefficients of thermal expansion for the various composite materials. The model can also calculate the strains and stresses at the constituent material level such as fibers, particles, and whiskers from the composite level stresses and strains. The model was implemented into ABAQUS using the UMAT option for multiscale analysis. An extensive set of examples are presented to demonstrate the reliability and accuracy of the developed micromechanics model for different kinds of composite materials. Another set of examples is provided to study the multiscale analysis of composite structures.

Dynamic Characterization of an Inflatable Concentrator for Solar Thermal Propulsion

NASA Technical Reports Server (NTRS)

Leigh, Larry; Hamidzadeh, Hamid; Tinker, Michael L.; Rodriguez, Pedro I. (Technical Monitor)

2001-01-01

An inflatable structural system that is a technology demonstrator for solar thermal propulsion and other applications is characterized for structural dynamic behavior both experimentally and computationally. The inflatable structure is a pressurized assembly developed for use in orbit to support a Fresnel lens or inflatable lenticular element for focusing sunlight into a solar thermal rocket engine. When the engine temperature reaches a pre-set level, the propellant is injected into the engine, absorbs heat from an exchanger, and is expanded through the nozzle to produce thrust. The inflatable structure is a passively adaptive system in that a regulator and relief valve are utilized to maintain pressure within design limits during the full range of orbital conditions. Modeling and test activities are complicated by the fact that the polyimide film material used for construction of the inflatable is nonlinear, with modulus varying as a function of frequency, temperature, and level of excitation. Modal vibration testing and finite element modeling are described in detail in this paper. The test database is used for validation and modification of the model. This work is highly significant because of the current interest in inflatable structures for space application, and because of the difficulty in accurately modeling such systems.

On the road to metallic nanoparticles by rational design: bridging the gap between atomic-level theoretical modeling and reality by total scattering experiments

NASA Astrophysics Data System (ADS)

Prasai, Binay; Wilson, A. R.; Wiley, B. J.; Ren, Y.; Petkov, Valeri

2015-10-01

The extent to which current theoretical modeling alone can reveal real-world metallic nanoparticles (NPs) at the atomic level was scrutinized and demonstrated to be insufficient and how it can be improved by using a pragmatic approach involving straightforward experiments is shown. In particular, 4 to 6 nm in size silica supported Au100-xPdx (x = 30, 46 and 58) explored for catalytic applications is characterized structurally by total scattering experiments including high-energy synchrotron X-ray diffraction (XRD) coupled to atomic pair distribution function (PDF) analysis. Atomic-level models for the NPs are built by molecular dynamics simulations based on the archetypal for current theoretical modeling Sutton-Chen (SC) method. Models are matched against independent experimental data and are demonstrated to be inaccurate unless their theoretical foundation, i.e. the SC method, is supplemented with basic yet crucial information on the length and strength of metal-to-metal bonds and, when necessary, structural disorder in the actual NPs studied. An atomic PDF-based approach for accessing such information and implementing it in theoretical modeling is put forward. For completeness, the approach is concisely demonstrated on 15 nm in size water-dispersed Au particles explored for bio-medical applications and 16 nm in size hexane-dispersed Fe48Pd52 particles explored for magnetic applications as well. It is argued that when ``tuned up'' against experiments relevant to metals and alloys confined to nanoscale dimensions, such as total scattering coupled to atomic PDF analysis, rather than by mere intuition and/or against data for the respective solids, atomic-level theoretical modeling can provide a sound understanding of the synthesis-structure-property relationships in real-world metallic NPs. Ultimately this can help advance nanoscience and technology a step closer to producing metallic NPs by rational design.The extent to which current theoretical modeling alone can reveal real-world metallic nanoparticles (NPs) at the atomic level was scrutinized and demonstrated to be insufficient and how it can be improved by using a pragmatic approach involving straightforward experiments is shown. In particular, 4 to 6 nm in size silica supported Au100-xPdx (x = 30, 46 and 58) explored for catalytic applications is characterized structurally by total scattering experiments including high-energy synchrotron X-ray diffraction (XRD) coupled to atomic pair distribution function (PDF) analysis. Atomic-level models for the NPs are built by molecular dynamics simulations based on the archetypal for current theoretical modeling Sutton-Chen (SC) method. Models are matched against independent experimental data and are demonstrated to be inaccurate unless their theoretical foundation, i.e. the SC method, is supplemented with basic yet crucial information on the length and strength of metal-to-metal bonds and, when necessary, structural disorder in the actual NPs studied. An atomic PDF-based approach for accessing such information and implementing it in theoretical modeling is put forward. For completeness, the approach is concisely demonstrated on 15 nm in size water-dispersed Au particles explored for bio-medical applications and 16 nm in size hexane-dispersed Fe48Pd52 particles explored for magnetic applications as well. It is argued that when ``tuned up'' against experiments relevant to metals and alloys confined to nanoscale dimensions, such as total scattering coupled to atomic PDF analysis, rather than by mere intuition and/or against data for the respective solids, atomic-level theoretical modeling can provide a sound understanding of the synthesis-structure-property relationships in real-world metallic NPs. Ultimately this can help advance nanoscience and technology a step closer to producing metallic NPs by rational design. Electronic supplementary information (ESI) available: XRD patterns, TEM and 3D structure modelling methodology. See DOI: 10.1039/c5nr04678e

Comparing Families of Dynamic Causal Models

PubMed Central

Penny, Will D.; Stephan, Klaas E.; Daunizeau, Jean; Rosa, Maria J.; Friston, Karl J.; Schofield, Thomas M.; Leff, Alex P.

2010-01-01

Mathematical models of scientific data can be formally compared using Bayesian model evidence. Previous applications in the biological sciences have mainly focussed on model selection in which one first selects the model with the highest evidence and then makes inferences based on the parameters of that model. This “best model” approach is very useful but can become brittle if there are a large number of models to compare, and if different subjects use different models. To overcome this shortcoming we propose the combination of two further approaches: (i) family level inference and (ii) Bayesian model averaging within families. Family level inference removes uncertainty about aspects of model structure other than the characteristic of interest. For example: What are the inputs to the system? Is processing serial or parallel? Is it linear or nonlinear? Is it mediated by a single, crucial connection? We apply Bayesian model averaging within families to provide inferences about parameters that are independent of further assumptions about model structure. We illustrate the methods using Dynamic Causal Models of brain imaging data. PMID:20300649

Modeling posttraumatic growth among cancer patients: The roles of social support, appraisals, and adaptive coping.

PubMed

Cao, Weidan; Qi, Xiaona; Cai, Deborah A; Han, Xuanye

2018-01-01

The purpose of the study was to build a model to explain the relationships between social support, uncontrollability appraisal, adaptive coping, and posttraumatic growth (PTG) among cancer patients in China. The participants who were cancer patients in a cancer hospital in China filled out a survey. The final sample size was 201. Structural equation modeling was used to build a model explaining PTG. Structural equation modeling results indicated that higher levels of social support predicted higher levels of adaptive coping, higher levels of uncontrollability appraisal predicted lower levels of adaptive coping, and higher levels of adaptive coping predicted higher levels of PTG. Moreover, adaptive coping was a mediator between social support and growth, as well as a mediator between uncontrollability and growth. The direct effects of social support and uncontrollability on PTG were insignificant. The model demonstrated the relationships between social support, uncontrollability appraisal, adaptive coping, and PTG. It could be concluded that uncontrollability appraisal was a required but not sufficient condition for PTG. Neither social support nor uncontrollability appraisal had direct influence on PTG. However, social support and uncontrollability might indirectly influence PTG, through adaptive coping. It implies that both internal factors (eg, cognitive appraisal and coping) and external factors (eg, social support) are required in order for growth to happen. Copyright © 2017 John Wiley & Sons, Ltd.

Novel nonlinear knowledge-based mean force potentials based on machine learning.

PubMed

Dong, Qiwen; Zhou, Shuigeng

2011-01-01

The prediction of 3D structures of proteins from amino acid sequences is one of the most challenging problems in molecular biology. An essential task for solving this problem with coarse-grained models is to deduce effective interaction potentials. The development and evaluation of new energy functions is critical to accurately modeling the properties of biological macromolecules. Knowledge-based mean force potentials are derived from statistical analysis of proteins of known structures. Current knowledge-based potentials are almost in the form of weighted linear sum of interaction pairs. In this study, a class of novel nonlinear knowledge-based mean force potentials is presented. The potential parameters are obtained by nonlinear classifiers, instead of relative frequencies of interaction pairs against a reference state or linear classifiers. The support vector machine is used to derive the potential parameters on data sets that contain both native structures and decoy structures. Five knowledge-based mean force Boltzmann-based or linear potentials are introduced and their corresponding nonlinear potentials are implemented. They are the DIH potential (single-body residue-level Boltzmann-based potential), the DFIRE-SCM potential (two-body residue-level Boltzmann-based potential), the FS potential (two-body atom-level Boltzmann-based potential), the HR potential (two-body residue-level linear potential), and the T32S3 potential (two-body atom-level linear potential). Experiments are performed on well-established decoy sets, including the LKF data set, the CASP7 data set, and the Decoys “R”Us data set. The evaluation metrics include the energy Z score and the ability of each potential to discriminate native structures from a set of decoy structures. Experimental results show that all nonlinear potentials significantly outperform the corresponding Boltzmann-based or linear potentials, and the proposed discriminative framework is effective in developing knowledge-based mean force potentials. The nonlinear potentials can be widely used for ab initio protein structure prediction, model quality assessment, protein docking, and other challenging problems in computational biology.

Simulations of the flocculent spiral M33: what drives the spiral structure?

NASA Astrophysics Data System (ADS)

Dobbs, C. L.; Pettitt, A. R.; Corbelli, E.; Pringle, J. E.

2018-05-01

We perform simulations of isolated galaxies in order to investigate the likely origin of the spiral structure in M33. In our models, we find that gravitational instabilities in the stars and gas are able to reproduce the observed spiral pattern and velocity field of M33, as seen in HI, and no interaction is required. We also find that the optimum models have high levels of stellar feedback which create large holes similar to those observed in M33, whilst lower levels of feedback tend to produce a large amount of small scale structure, and undisturbed long filaments of high surface density gas, hardly detected in the M33 disc. The gas component appears to have a significant role in producing the structure, so if there is little feedback, both the gas and stars organise into clear spiral arms, likely due to a lower combined Q (using gas and stars), and the ready ability of cold gas to undergo spiral shocks. By contrast models with higher feedback have weaker spiral structure, especially in the stellar component, compared to grand design galaxies. We did not see a large difference in the behaviour of Qstars with most of these models, however, because Qstars stayed relatively constant unless the disc was more strongly unstable. Our models suggest that although the stars produce some underlying spiral structure, this is relatively weak, and the gas physics has a considerable role in producing the large scale structure of the ISM in flocculent spirals.

Effects of parceling on model selection: Parcel-allocation variability in model ranking.

PubMed

Sterba, Sonya K; Rights, Jason D

2017-03-01

Research interest often lies in comparing structural model specifications implying different relationships among latent factors. In this context parceling is commonly accepted, assuming the item-level measurement structure is well known and, conservatively, assuming items are unidimensional in the population. Under these assumptions, researchers compare competing structural models, each specified using the same parcel-level measurement model. However, little is known about consequences of parceling for model selection in this context-including whether and when model ranking could vary across alternative item-to-parcel allocations within-sample. This article first provides a theoretical framework that predicts the occurrence of parcel-allocation variability (PAV) in model selection index values and its consequences for PAV in ranking of competing structural models. These predictions are then investigated via simulation. We show that conditions known to manifest PAV in absolute fit of a single model may or may not manifest PAV in model ranking. Thus, one cannot assume that low PAV in absolute fit implies a lack of PAV in ranking, and vice versa. PAV in ranking is shown to occur under a variety of conditions, including large samples. To provide an empirically supported strategy for selecting a model when PAV in ranking exists, we draw on relationships between structural model rankings in parcel- versus item-solutions. This strategy employs the across-allocation modal ranking. We developed software tools for implementing this strategy in practice, and illustrate them with an example. Even if a researcher has substantive reason to prefer one particular allocation, investigating PAV in ranking within-sample still provides an informative sensitivity analysis. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Study on safety level of RC beam bridges under earthquake

NASA Astrophysics Data System (ADS)

Zhao, Jun; Lin, Junqi; Liu, Jinlong; Li, Jia

2017-08-01

This study considers uncertainties in material strengths and the modeling which have important effects on structural resistance force based on reliability theory. After analyzing the destruction mechanism of a RC bridge, structural functions and the reliability were given, then the safety level of the piers of a reinforced concrete continuous girder bridge with stochastic structural parameters against earthquake was analyzed. Using response surface method to calculate the failure probabilities of bridge piers under high-level earthquake, their seismic reliability for different damage states within the design reference period were calculated applying two-stage design, which describes seismic safety level of the built bridges to some extent.

Energy Level Alignment at the Interface between Linear-Structured Benzenediamine Molecules and Au(111) Surface

NASA Astrophysics Data System (ADS)

Li, Guo; Rangel, Tonatiuh; Liu, Zhenfei; Cooper, Valentino; Neaton, Jeffrey

Using density functional theory with model self-energy corrections, we calculate the adsorption energetics and geometry, and the energy level alignment of benzenediamine (BDA) molecules adsorbed on Au(111) surfaces. Our calculations show that linear structures of BDA, stabilized via hydrogen bonds between amine groups, are energetically more favorable than monomeric phases. Moreover, our self-energy-corrected calculations of energy level alignment show that the highest occupied molecular orbital energy of the BDA linear structure is deeper relative to the Fermi level relative to the isolated monomer and agrees well with the values measured with photoemission spectroscopy. This work supported by DOE.

The Misspecification of the Covariance Structures in Multilevel Models for Single-Case Data: A Monte Carlo Simulation Study

ERIC Educational Resources Information Center

Moeyaert, Mariola; Ugille, Maaike; Ferron, John M.; Beretvas, S. Natasha; Van den Noortgate, Wim

2016-01-01

The impact of misspecifying covariance matrices at the second and third levels of the three-level model is evaluated. Results indicate that ignoring existing covariance has no effect on the treatment effect estimate. In addition, the between-case variance estimates are unbiased when covariance is either modeled or ignored. If the research interest…

Comparing Vertical Scales Derived from Dichotomous and Polytomous IRT Models for a Test Composed of Testlets.

ERIC Educational Resources Information Center

Bishop, N. Scott; Omar, Md Hafidz

Previous research has shown that testlet structures often violate important assumptions of dichotomous item response theory (D-IRT) models, applied to item-level scores, that can in turn affect the results of many measurement applications. In this situation, polytomous IRT (P-IRT) models, applied to testlet-level scores, have been used as an…

Dynamic and fluid-structure interaction simulations of bioprosthetic heart valves using parametric design with T-splines and Fung-type material models

NASA Astrophysics Data System (ADS)

Hsu, Ming-Chen; Kamensky, David; Xu, Fei; Kiendl, Josef; Wang, Chenglong; Wu, Michael C. H.; Mineroff, Joshua; Reali, Alessandro; Bazilevs, Yuri; Sacks, Michael S.

2015-06-01

This paper builds on a recently developed immersogeometric fluid-structure interaction (FSI) methodology for bioprosthetic heart valve (BHV) modeling and simulation. It enhances the proposed framework in the areas of geometry design and constitutive modeling. With these enhancements, BHV FSI simulations may be performed with greater levels of automation, robustness and physical realism. In addition, the paper presents a comparison between FSI analysis and standalone structural dynamics simulation driven by prescribed transvalvular pressure, the latter being a more common modeling choice for this class of problems. The FSI computation achieved better physiological realism in predicting the valve leaflet deformation than its standalone structural dynamics counterpart.

Food-web models predict species abundances in response to habitat change.

PubMed

Gotelli, Nicholas J; Ellison, Aaron M

2006-10-01

Plant and animal population sizes inevitably change following habitat loss, but the mechanisms underlying these changes are poorly understood. We experimentally altered habitat volume and eliminated top trophic levels of the food web of invertebrates that inhabit rain-filled leaves of the carnivorous pitcher plant Sarracenia purpurea. Path models that incorporated food-web structure better predicted population sizes of food-web constituents than did simple keystone species models, models that included only autecological responses to habitat volume, or models including both food-web structure and habitat volume. These results provide the first experimental confirmation that trophic structure can determine species abundances in the face of habitat loss.

Modeling Framework for Fracture in Multiscale Cement-Based Material Structures

PubMed Central

Qian, Zhiwei; Schlangen, Erik; Ye, Guang; van Breugel, Klaas

2017-01-01

Multiscale modeling for cement-based materials, such as concrete, is a relatively young subject, but there are already a number of different approaches to study different aspects of these classical materials. In this paper, the parameter-passing multiscale modeling scheme is established and applied to address the multiscale modeling problem for the integrated system of cement paste, mortar, and concrete. The block-by-block technique is employed to solve the length scale overlap challenge between the mortar level (0.1–10 mm) and the concrete level (1–40 mm). The microstructures of cement paste are simulated by the HYMOSTRUC3D model, and the material structures of mortar and concrete are simulated by the Anm material model. Afterwards the 3D lattice fracture model is used to evaluate their mechanical performance by simulating a uniaxial tensile test. The simulated output properties at a lower scale are passed to the next higher scale to serve as input local properties. A three-level multiscale lattice fracture analysis is demonstrated, including cement paste at the micrometer scale, mortar at the millimeter scale, and concrete at centimeter scale. PMID:28772948

Factors promoting sense of coherence among university students in urban areas of Japan: individual-level social capital, self-efficacy, and mental health.

PubMed

Mato, Mie; Tsukasaki, Keiko

2017-04-01

Sense of coherence (SOC) is a concept that helps to explain the relation between personal intentionality as psychosocial factors and health-related behaviors. Thus, it is essential to enhance SOC when encouraging a healthy lifestyle. However, the factors that promote SOC have not been fully investigated among university students. The objective of this study was to clarify the general resistance resources (GRRs) that may promote the development of the SOC among university students. Therefore, we examined the relationship between SOC and social capital (SC), self-efficacy, and mental health. Participants included 443 students from nine academic departments at eight universities in the Kanto or Kinki metropolitan areas of Japan. Participants completed an anonymous questionnaire. Individual-level cognitive and structural SC, generalized self-efficacy, mental health inventory (from SF-36v2), and SOC were measured. Confirmatory factor analysis using structural equation modeling was conducted to verify the factor structure of the SOC-13 scale. Stepwise multiple regression analysis and two-way layout analysis of variance were performed with SOC as the dependent variable. The factor structure of SOC indicated the optimal model fit in the second-order three-factor model of the 12 items. SOC was predicted by five variables: age, cognitive SC, structural SC, mental health, and self-efficacy. For students from urban areas, SOC was predicted by the interaction between cognitive and structural SC. SOC was significantly related to cognitive SC, structural SC, and self-efficacy as well as mental health in university students from urban areas. Furthermore, the combination of higher-level cognitive SC and higher-level structural SC exerted an inhibitory influence on SOC among students who previously and currently live in urban areas. Therefore, the findings indicated that both cognitive and structural SC as well as self-efficacy may act as GRRs that promote the development of SOC, and similarly, good mental health may promote a strong SOC.

PROJECTED POPULATION-LEVEL EFFECTS OF THIOBENCARB EXPOSURE ON THE MYSID, AMERICAMYSIS BAHIA, AND EXTINCTION PROBABILITY IN A CONCENTRATION-DECAY EXPOSURE SYSTEM

EPA Science Inventory

Population-level effects of the mysid, Americamysis bahia, exposed to varying thiobencarb concentrations were estimated using stage-structured matrix models. A deterministic density-independent matrix model estimated the decrease in population growth rate, l, with increas...

Vibro-Acoustic FE Analyses of the Saab 2000 Aircraft

NASA Technical Reports Server (NTRS)

Green, Inge S.

1992-01-01

A finite element model of the Saab 2000 fuselage structure and interior cavity has been created in order to compute the noise level in the passenger cabin due to propeller noise. Areas covered in viewgraph format include the following: coupled acoustic/structural noise; data base creation; frequency response analysis; model validation; and planned analyses.

Assessing Mediation Using Marginal Structural Models in the Presence of Confounding and Moderation

ERIC Educational Resources Information Center

Coffman, Donna L.; Zhong, Wei

2012-01-01

This article presents marginal structural models with inverse propensity weighting (IPW) for assessing mediation. Generally, individuals are not randomly assigned to levels of the mediator. Therefore, confounders of the mediator and outcome may exist that limit causal inferences, a goal of mediation analysis. Either regression adjustment or IPW…

Structuring Formal Control Systems Specifications for Reuse: Surviving Hardware Changes

NASA Technical Reports Server (NTRS)

Thompson, Jeffrey M.; Heimdahl, Mats P. E.; Erickson, Debra M.

2000-01-01

Formal capture and analysis of the required behavior of control systems have many advantages. For instance, it encourages rigorous requirements analysis, the required behavior is unambiguously defined, and we can assure that various safety properties are satisfied. Formal modeling is, however, a costly and time consuming process and if one could reuse the formal models over a family of products, significant cost savings would be realized. In an ongoing project we are investigating how to structure state-based models to achieve a high level of reusability within product families. In this paper we discuss a high-level structure of requirements models that achieves reusability of the desired control behavior across varying hardware platforms in a product family. The structuring approach is demonstrated through a case study in the mobile robotics domain where the desired robot behavior is reused on two diverse platforms-one commercial mobile platform and one build in-house. We use our language RSML (-e) to capture the control behavior for reuse and our tool NIMBUS to demonstrate how the formal specification can be validated and used as a prototype on the two platforms.

Cognitive control over learning: Creating, clustering and generalizing task-set structure

PubMed Central

Collins, Anne G.E.; Frank, Michael J.

2013-01-01

Executive functions and learning share common neural substrates essential for their expression, notably in prefrontal cortex and basal ganglia. Understanding how they interact requires studying how cognitive control facilitates learning, but also how learning provides the (potentially hidden) structure, such as abstract rules or task-sets, needed for cognitive control. We investigate this question from three complementary angles. First, we develop a new computational “C-TS” (context-task-set) model inspired by non-parametric Bayesian methods, specifying how the learner might infer hidden structure and decide whether to re-use that structure in new situations, or to create new structure. Second, we develop a neurobiologically explicit model to assess potential mechanisms of such interactive structured learning in multiple circuits linking frontal cortex and basal ganglia. We systematically explore the link betweens these levels of modeling across multiple task demands. We find that the network provides an approximate implementation of high level C-TS computations, where manipulations of specific neural mechanisms are well captured by variations in distinct C-TS parameters. Third, this synergism across models yields strong predictions about the nature of human optimal and suboptimal choices and response times during learning. In particular, the models suggest that participants spontaneously build task-set structure into a learning problem when not cued to do so, which predicts positive and negative transfer in subsequent generalization tests. We provide evidence for these predictions in two experiments and show that the C-TS model provides a good quantitative fit to human sequences of choices in this task. These findings implicate a strong tendency to interactively engage cognitive control and learning, resulting in structured abstract representations that afford generalization opportunities, and thus potentially long-term rather than short-term optimality. PMID:23356780

Using ‘particle in a box’ models to calculate energy levels in semiconductor quantum well structures

NASA Astrophysics Data System (ADS)

Ebbens, A. T.

2018-07-01

Although infinite potential ‘particle in a box’ models are widely used to introduce quantised energy levels their predictions cannot be quantitatively compared with atomic emission spectra. Here, this problem is overcome by describing how both infinite and finite potential well models can be used to calculate the confined energy levels of semiconductor quantum wells. This is done by using physics and mathematics concepts that are accessible to pre-university students. The results of the models are compared with experimental data and their accuracy discussed.

Aeon: Synthesizing Scheduling Algorithms from High-Level Models

NASA Astrophysics Data System (ADS)

Monette, Jean-Noël; Deville, Yves; van Hentenryck, Pascal

This paper describes the aeon system whose aim is to synthesize scheduling algorithms from high-level models. A eon, which is entirely written in comet, receives as input a high-level model for a scheduling application which is then analyzed to generate a dedicated scheduling algorithm exploiting the structure of the model. A eon provides a variety of synthesizers for generating complete or heuristic algorithms. Moreover, synthesizers are compositional, making it possible to generate complex hybrid algorithms naturally. Preliminary experimental results indicate that this approach may be competitive with state-of-the-art search algorithms.

Recognition and characterization of hierarchical interstellar structure. II - Structure tree statistics

NASA Technical Reports Server (NTRS)

Houlahan, Padraig; Scalo, John

1992-01-01

A new method of image analysis is described, in which images partitioned into 'clouds' are represented by simplified skeleton images, called structure trees, that preserve the spatial relations of the component clouds while disregarding information concerning their sizes and shapes. The method can be used to discriminate between images of projected hierarchical (multiply nested) and random three-dimensional simulated collections of clouds constructed on the basis of observed interstellar properties, and even intermediate systems formed by combining random and hierarchical simulations. For a given structure type, the method can distinguish between different subclasses of models with different parameters and reliably estimate their hierarchical parameters: average number of children per parent, scale reduction factor per level of hierarchy, density contrast, and number of resolved levels. An application to a column density image of the Taurus complex constructed from IRAS data is given. Moderately strong evidence for a hierarchical structural component is found, and parameters of the hierarchy, as well as the average volume filling factor and mass efficiency of fragmentation per level of hierarchy, are estimated. The existence of nested structure contradicts models in which large molecular clouds are supposed to fragment, in a single stage, into roughly stellar-mass cores.

Multilevel structural equation models for assessing moderation within and across levels of analysis.

PubMed

Preacher, Kristopher J; Zhang, Zhen; Zyphur, Michael J

2016-06-01

Social scientists are increasingly interested in multilevel hypotheses, data, and statistical models as well as moderation or interactions among predictors. The result is a focus on hypotheses and tests of multilevel moderation within and across levels of analysis. Unfortunately, existing approaches to multilevel moderation have a variety of shortcomings, including conflated effects across levels of analysis and bias due to using observed cluster averages instead of latent variables (i.e., "random intercepts") to represent higher-level constructs. To overcome these problems and elucidate the nature of multilevel moderation effects, we introduce a multilevel structural equation modeling (MSEM) logic that clarifies the nature of the problems with existing practices and remedies them with latent variable interactions. This remedy uses random coefficients and/or latent moderated structural equations (LMS) for unbiased tests of multilevel moderation. We describe our approach and provide an example using the publicly available High School and Beyond data with Mplus syntax in Appendix. Our MSEM method eliminates problems of conflated multilevel effects and reduces bias in parameter estimates while offering a coherent framework for conceptualizing and testing multilevel moderation effects. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Testing Models of Psychopathology in Preschool-aged Children Using a Structured Interview-based Assessment

PubMed Central

Dougherty, Lea R.; Bufferd, Sara J.; Carlson, Gabrielle A.; Klein, Daniel N.

2014-01-01

A number of studies have found that broadband internalizing and externalizing factors provide a parsimonious framework for understanding the structure of psychopathology across childhood, adolescence, and adulthood. However, few of these studies have examined psychopathology in young children, and several recent studies have found support for alternative models, including a bi-factor model with common and specific factors. The present study used parents’ (typically mothers’) reports on a diagnostic interview in a community sample of 3-year old children (n=541; 53.9 % male) to compare the internalizing-externalizing latent factor model with a bi-factor model. The bi-factor model provided a better fit to the data. To test the concurrent validity of this solution, we examined associations between this model and paternal reports and laboratory observations of child temperament. The internalizing factor was associated with low levels of surgency and high levels of fear; the externalizing factor was associated with high levels of surgency and disinhibition and low levels of effortful control; and the common factor was associated with high levels of surgency and negative affect and low levels of effortful control. These results suggest that psychopathology in preschool-aged children may be explained by a single, common factor influencing nearly all disorders and unique internalizing and externalizing factors. These findings indicate that shared variance across internalizing and externalizing domains is substantial and are consistent with recent suggestions that emotion regulation difficulties may be a common vulnerability for a wide array of psychopathology. PMID:24652485

Structural empowerment, job stress and burnout of nurses in China.

PubMed

Guo, Jiajia; Chen, Juan; Fu, Jie; Ge, Xinling; Chen, Min; Liu, Yanhui

2016-08-01

To investigate the status of structural empowerment, job stress and burnout in China, and to explore the relationships among them. The questionnaires of CWEQ-II, job stressors and MBI were used to investigate 1002 nurses working at tertiary-level hospitals. The average score of CWEQ-II was 2.23±0.59. The score of EE of MBI was 29.75±13.94, PA was 27.40±11.21, both of them showed a high level of exhaustion, DP was 8.07±5.82 and showed a middle level of exhaustion. The findings showed that workload and time pressure were the most frequently encountered job stress among staff nurses, the score was 3.23±0.95; There was a significantly correlation among structural empowerment, job stressors and the level of burnout(p<0.05). Hierarchical regression analysis showed that structural empowerment had significant influence on the every factors of job stressors (p<0.05) and burnout, job stressors had significant influence on the every factors of burnout (p<0.05). Structural equation modeling analyses revealed a good fit to the data based on various fit indices (χ(2)/df=2.29, GFI=0.945, CFI=0.965, IFI=0.966, RMSEA=0.061). Staff nurses felt that structural empowerment in their workplace resulted in lower levels of job stress which in turn strongly influenced Burnout. These results provide initial support for an expanded model of structural empowerment, and offer a broader understanding of the empowerment process. Copyright © 2016 Elsevier Inc. All rights reserved.

Determination of the nuclear level densities and radiative strength function for 43 nuclei in the mass interval 28≤A≤200

NASA Astrophysics Data System (ADS)

Knezevic, David; Jovancevic, Nikola; Sukhovoj, Anatoly M.; Mitsyna, Ludmila V.; Krmar, Miodrag; Cong, Vu D.; Hambsch, Franz-Josef; Oberstedt, Stephan; Revay, Zsolt; Stieghorst, Christian; Dragic, Aleksandar

2018-03-01

The determination of nuclear level densities and radiative strength functions is one of the most important tasks in low-energy nuclear physics. Accurate experimental values of these parameters are critical for the study of the fundamental properties of nuclear structure. The step-like structure in the dependence of the level densities p on the excitation energy of nuclei Eex is observed in the two-step gamma cascade measurements for nuclei in the 28 ≤ A ≤ 200 mass region. This characteristic structure can be explained only if a co-existence of quasi-particles and phonons, as well as their interaction in a nucleus, are taken into account in the process of gamma-decay. Here we present a new improvement to the Dubna practical model for the determination of nuclear level densities and radiative strength functions. The new practical model guarantees a good description of the available intensities of the two step gamma cascades, comparable to the experimental data accuracy.

The application of the multi-alternative approach in active neural network models

NASA Astrophysics Data System (ADS)

Podvalny, S.; Vasiljev, E.

2017-02-01

The article refers to the construction of intelligent systems based artificial neuron networks are used. We discuss the basic properties of the non-compliance of artificial neuron networks and their biological prototypes. It is shown here that the main reason for these discrepancies is the structural immutability of the neuron network models in the learning process, that is, their passivity. Based on the modern understanding of the biological nervous system as a structured ensemble of nerve cells, it is proposed to abandon the attempts to simulate its work at the level of the elementary neurons functioning processes and proceed to the reproduction of the information structure of data storage and processing on the basis of the general enough evolutionary principles of multialternativity, i.e. the multi-level structural model, diversity and modularity. The implementation method of these principles is offered, using the faceted memory organization in the neuron network with the rearranging active structure. An example of the implementation of the active facet-type neuron network in the intellectual decision-making system in the conditions of critical events development in the electrical distribution system.

Decentralized control of large flexible structures by joint decoupling

NASA Technical Reports Server (NTRS)

Su, Tzu-Jeng; Juang, Jer-Nan

1992-01-01

A decentralized control design method is presented for large complex flexible structures by using the idea of joint decoupling. The derivation is based on a coupled substructure state-space model, which is obtained from enforcing conditions of interface compatibility and equilibrium to the substructure state-space models. It is shown that by restricting the control law to be localized state feedback and by setting the joint actuator input commands to decouple joint 'degrees of freedom' (dof) from interior dof, the global structure control design problem can be decomposed into several substructure control design problems. The substructure control gains and substructure observers are designed based on modified substructure state-space models. The controllers produced by the proposed method can operate successfully at the individual substructure level as well as at the global structure level. Therefore, not only control design but also control implementation is decentralized. Stability and performance requirement of the closed-loop system can be achieved by using any existing state feedback control design method. A two-component mass-spring damper system and a three-truss structure are used as examples to demonstrate the proposed method.

RECURSIVE PROTEIN MODELING: A DIVIDE AND CONQUER STRATEGY FOR PROTEIN STRUCTURE PREDICTION AND ITS CASE STUDY IN CASP9

PubMed Central

CHENG, JIANLIN; EICKHOLT, JESSE; WANG, ZHENG; DENG, XIN

2013-01-01

After decades of research, protein structure prediction remains a very challenging problem. In order to address the different levels of complexity of structural modeling, two types of modeling techniques — template-based modeling and template-free modeling — have been developed. Template-based modeling can often generate a moderate- to high-resolution model when a similar, homologous template structure is found for a query protein but fails if no template or only incorrect templates are found. Template-free modeling, such as fragment-based assembly, may generate models of moderate resolution for small proteins of low topological complexity. Seldom have the two techniques been integrated together to improve protein modeling. Here we develop a recursive protein modeling approach to selectively and collaboratively apply template-based and template-free modeling methods to model template-covered (i.e. certain) and template-free (i.e. uncertain) regions of a protein. A preliminary implementation of the approach was tested on a number of hard modeling cases during the 9th Critical Assessment of Techniques for Protein Structure Prediction (CASP9) and successfully improved the quality of modeling in most of these cases. Recursive modeling can signicantly reduce the complexity of protein structure modeling and integrate template-based and template-free modeling to improve the quality and efficiency of protein structure prediction. PMID:22809379

Modified social ecological model: a tool to guide the assessment of the risks and risk contexts of HIV epidemics.

PubMed

Baral, Stefan; Logie, Carmen H; Grosso, Ashley; Wirtz, Andrea L; Beyrer, Chris

2013-05-17

Social and structural factors are now well accepted as determinants of HIV vulnerabilities. These factors are representative of social, economic, organizational and political inequities. Associated with an improved understanding of multiple levels of HIV risk has been the recognition of the need to implement multi-level HIV prevention strategies. Prevention sciences research and programming aiming to decrease HIV incidence requires epidemiologic studies to collect data on multiple levels of risk to inform combination HIV prevention packages. Proximal individual-level risks, such as sharing injection devices and unprotected penile-vaginal or penile-anal sex, are necessary in mediating HIV acquisition and transmission. However, higher order social and structural-level risks can facilitate or reduce HIV transmission on population levels. Data characterizing these risks is often far more actionable than characterizing individual-level risks. We propose a modified social ecological model (MSEM) to help visualize multi-level domains of HIV infection risks and guide the development of epidemiologic HIV studies. Such a model may inform research in epidemiology and prevention sciences, particularly for key populations including men who have sex with men (MSM), people who inject drugs (PID), and sex workers. The MSEM builds on existing frameworks by examining multi-level risk contexts for HIV infection and situating individual HIV infection risks within wider network, community, and public policy contexts as well as epidemic stage. The utility of the MSEM is demonstrated with case studies of HIV risk among PID and MSM. The MSEM is a flexible model for guiding epidemiologic studies among key populations at risk for HIV in diverse sociocultural contexts. Successful HIV prevention strategies for key populations require effective integration of evidence-based biomedical, behavioral, and structural interventions. While the focus of epidemiologic studies has traditionally been on describing individual-level risk factors, the future necessitates comprehensive epidemiologic data characterizing multiple levels of HIV risk.

Atomic data and line intensities for the S V ion

NASA Astrophysics Data System (ADS)

Iorga, C.; Stancalie, V.

2017-05-01

The energy levels, oscillator strengths, spontaneous radiative decay rates, lifetimes and electron impact collision strengths have been obtained for the [ Ne ] 3s nl, [ Ne ] 3p nl, [ Ne ] 3d nl configurations belonging to S V ion, with n ≤ 7 and l ≤ 4, resulting in 567 fine-structure levels. The calculations have been performed within the fully relativistic Flexible Atomic Code (FAC, Gu, 2008) framework and the distorted wave approximation. To attain the desired accuracy for the levels energy, the valence-valence and valence-core correlations have been taken care of by including 96 configuration state functions (CSFs) in the model, reaching a total of 3147 fine-structure levels. Two separate calculations have been performed with the local central potential computed for two different average configurations. A third calculation is also performed without the addition of the core-excited states in the atomic model for completeness. The effects of slightly different mean configurations and valence-core correlations on the energy levels and decay rates are investigated. The collision data have been computed employing the relativistic distorted-wave method along with the atomic model containing the 96 CSFs and corresponding to the ground state mean configuration. The collision strengths corresponding to excitation from the first four fine-structure levels are given for five energy values of the scattered electron 2.65, 6.18, 11.02, 17.36, 25.43 Rydberg, plus an additional variable small energy value near the threshold. A collisional-radiative model has been employed to solve the rate equations for the populations of the 567 fine-structure levels, for a temperature of LogTE(K) = 5.2 corresponding to the maximum abundance of S V, and at densities 106-1016cm-3, assuming a Maxwellian electron energy distribution function and black body radiation of temperature 6000 K and dilution factor 0.35 for the photon distribution function. The main processes responsible for the level population variations are the electron-impact collisional excitation and the radiative decay along with their inverse processes. As a result, the level populations along with the spectral high-line intensity ratios are provided.

Identity related to living situation in six individuals with congenital quadriplegia.

PubMed

Robey, Kenneth L

2008-01-01

This study was a preliminary examination of structural aspects of identity, particularly identity associated with living situation, in individuals who have quadriplegia due to cerebral palsy. A hierarchical classes algorithm (HICLAS) was used to construct idiographic 'identity structure' models for three individuals who are living in an inpatient hospital setting and for three individuals living in community-based group residences. Indices derived from the models indicate that the identity 'myself as one who has a disability' was structurally superordinate (i.e., resided at a high hierarchical level) for all six participants, suggesting a high level of importance of this identity in participants' sense of self. The models also indicate that while identity associated with one's particular living situation was superordinate for persons living in the hospital, it was not for persons living in community residences. While conclusions based on this small sample are necessarily limited, the data suggest that identity associated with living situation might differ in structural centrality, and presumably subjective importance, for persons living in inpatient versus community-based settings.

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.

The NASTRAN user's manual (level 17.0)

NASA Technical Reports Server (NTRS)

1979-01-01

NASTRAN embodies a lumped element approach, wherein the distributed physical properties of a structure are represented by a model consisting of a finite number of idealized substructures or elements that are interconnected at a finite of grid points, to which loads are applied. All input and output data pertain to the idealized structural model. The general procedures for defining structural models are described and instructions are given for each of the bulk data cards and case control cards. Additional information on the case control cards and use of parameters is included for each rigid format.

Dynamic analysis of space structures including elastic, multibody, and control behavior

NASA Technical Reports Server (NTRS)

Pinson, Larry; Soosaar, Keto

1989-01-01

The problem is to develop analysis methods, modeling stategies, and simulation tools to predict with assurance the on-orbit performance and integrity of large complex space structures that cannot be verified on the ground. The problem must incorporate large reliable structural models, multi-body flexible dynamics, multi-tier controller interaction, environmental models including 1g and atmosphere, various on-board disturbances, and linkage to mission-level performance codes. All areas are in serious need of work, but the weakest link is multi-body flexible dynamics.

Unraveling protein folding mechanism by analyzing the hierarchy of models with increasing level of detail

NASA Astrophysics Data System (ADS)

Hayashi, Tomohiko; Yasuda, Satoshi; Škrbić, Tatjana; Giacometti, Achille; Kinoshita, Masahiro

2017-09-01

Taking protein G with 56 residues for a case study, we investigate the mechanism of protein folding. In addition to its native structure possessing α-helix and β-sheet contents of 27% and 39%, respectively, we construct a number of misfolded decoys with a wide variety of α-helix and β-sheet contents. We then consider a hierarchy of 8 different models with increasing level of detail in terms of the number of entropic and energetic physical factors incorporated. The polyatomic structure is always taken into account, but the side chains are removed in half of the models. The solvent is formed by either neutral hard spheres or water molecules. Protein intramolecular hydrogen bonds (H-bonds) and protein-solvent H-bonds (the latter is present only in water) are accounted for or not, depending on the model considered. We then apply a physics-based free-energy function (FEF) corresponding to each model and investigate which structures are most stabilized. This special approach taken on a step-by-step basis enables us to clarify the role of each physical factor in contributing to the structural stability and separately elucidate its effect. Depending on the model employed, significantly different structures such as very compact configurations with no secondary structures and configurations of associated α-helices are optimally stabilized. The native structure can be identified as that with lowest FEF only when the most detailed model is employed. This result is significant for at least the two reasons: The most detailed model considered here is able to capture the fundamental aspects of protein folding notwithstanding its simplicity; and it is shown that the native structure is stabilized by a complex interplay of minimal multiple factors that must be all included in the description. In the absence of even a single of these factors, the protein is likely to be driven towards a different, more stable state.

Effects of organizational complexity and resources on construction site risk.

PubMed

Forteza, Francisco J; Carretero-Gómez, Jose M; Sesé, Albert

2017-09-01

Our research is aimed at studying the relationship between risk level and organizational complexity and resources on constructions sites. Our general hypothesis is that site complexity increases risk, whereas more resources of the structure decrease risk. A Structural Equation Model (SEM) approach was adopted to validate our theoretical model. To develop our study, 957 building sites in Spain were visited and assessed in 2003-2009. All needed data were obtained using a specific tool developed by the authors to assess site risk, structure and resources (Construction Sites Risk Assessment Tool, or CONSRAT). This tool operationalizes the variables to fit our model, specifically, via a site risk index (SRI) and 10 organizational variables. Our random sample is composed largely of small building sites with general high levels of risk, moderate complexity, and low resources on site. The model obtained adequate fit, and results showed empirical evidence that the factors of complexity and resources can be considered predictors of site risk level. Consequently, these results can help companies, managers of construction and regulators to identify which organizational aspects should be improved to prevent risks on sites and consequently accidents. Copyright © 2017 National Safety Council and Elsevier Ltd. All rights reserved.

From single fiber to macro-level mechanics: A structural finite-element model for elastomeric fibrous biomaterials

PubMed Central

D'Amore, Antonio; Amoroso, Nicholas; Gottardi, Riccardo; Hobson, Christopher; Carruthers, Christopher; Watkins, Simon; Wagner, William R.; Sacks, Michael S.

2014-01-01

In the present work, we demonstrate that the mesoscopic in-plane mechanical behavior of membrane elastomeric scaffolds can be simulated by replication of actual quantified fibrous geometries. Elastomeric electrospun polyurethane (ES-PEUU) scaffolds, with and without particulate inclusions, were utilized. Simulations were developed from experimentally-derived fiber network geometries, based on a range of scaffold isotropic and anisotropic behaviors. These were chosen to evaluate the effects on macro-mechanics based on measurable geometric parameters such as fiber intersections, connectivity, orientation, and diameter. Simulations were conducted with only the fiber material model parameters adjusted to match the macro-level mechanical test data. Fiber model validation was performed at the microscopic level by individual fiber mechanical tests using AFM. Results demonstrated very good agreement to the experimental data, and revealed the formation of extended preferential fiber orientations spanning the entire model space. We speculate that these emergent structures may be responsible for the tissue-like macroscale behaviors observed in electrospun scaffolds. To conclude, the modeling approach has implications for (1) gaining insight on the intricate relationship between fabrication variables, structure, and mechanics to manufacture more functional devices/materials, (2) elucidating the effects of cell or particulate inclusions on global construct mechanics, and (3) fabricating better performing tissue surrogates that could recapitulate native tissue mechanics. PMID:25128869

Lithologic Effects on Landscape Response to Base Level Changes: A Modeling Study in the Context of the Eastern Jura Mountains, Switzerland

NASA Astrophysics Data System (ADS)

Yanites, Brian J.; Becker, Jens K.; Madritsch, Herfried; Schnellmann, Michael; Ehlers, Todd A.

2017-11-01

Landscape evolution is a product of the forces that drive geomorphic processes (e.g., tectonics and climate) and the resistance to those processes. The underlying lithology and structural setting in many landscapes set the resistance to erosion. This study uses a modified version of the Channel-Hillslope Integrated Landscape Development (CHILD) landscape evolution model to determine the effect of a spatially and temporally changing erodibility in a terrain with a complex base level history. Specifically, our focus is to quantify how the effects of variable lithology influence transient base level signals. We set up a series of numerical landscape evolution models with increasing levels of complexity based on the lithologic variability and base level history of the Jura Mountains of northern Switzerland. The models are consistent with lithology (and therewith erodibility) playing an important role in the transient evolution of the landscape. The results show that the erosion rate history at a location depends on the rock uplift and base level history, the range of erodibilities of the different lithologies, and the history of the surface geology downstream from the analyzed location. Near the model boundary, the history of erosion is dominated by the base level history. The transient wave of incision, however, is quite variable in the different model runs and depends on the geometric structure of lithology used. It is thus important to constrain the spatiotemporal erodibility patterns downstream of any given point of interest to understand the evolution of a landscape subject to variable base level in a quantitative framework.

Cognitive aging on latent constructs for visual processing capacity: a novel structural equation modeling framework with causal assumptions based on a theory of visual attention.

PubMed

Nielsen, Simon; Wilms, L Inge

2014-01-01

We examined the effects of normal aging on visual cognition in a sample of 112 healthy adults aged 60-75. A testbattery was designed to capture high-level measures of visual working memory and low-level measures of visuospatial attention and memory. To answer questions of how cognitive aging affects specific aspects of visual processing capacity, we used confirmatory factor analyses in Structural Equation Modeling (SEM; Model 2), informed by functional structures that were modeled with path analyses in SEM (Model 1). The results show that aging effects were selective to measures of visual processing speed compared to visual short-term memory (VSTM) capacity (Model 2). These results are consistent with some studies reporting selective aging effects on processing speed, and inconsistent with other studies reporting aging effects on both processing speed and VSTM capacity. In the discussion we argue that this discrepancy may be mediated by differences in age ranges, and variables of demography. The study demonstrates that SEM is a sensitive method to detect cognitive aging effects even within a narrow age-range, and a useful approach to structure the relationships between measured variables, and the cognitive functional foundation they supposedly represent.

X-56A MUTT: Aeroservoelastic Modeling

NASA Technical Reports Server (NTRS)

Ouellette, Jeffrey A.

2015-01-01

For the NASA X-56a Program, Armstrong Flight Research Center has been developing a set of linear states space models that integrate the flight dynamics and structural dynamics. These high order models are needed for the control design, control evaluation, and test input design. The current focus has been on developing stiff wing models to validate the current modeling approach. The extension of the modeling approach to the flexible wings requires only a change in the structural model. Individual subsystems models (actuators, inertial properties, etc.) have been validated by component level ground tests. Closed loop simulation of maneuvers designed to validate the flight dynamics of these models correlates very well flight test data. The open loop structural dynamics are also shown to correlate well to the flight test data.

Levels of Emotional Awareness: a model for conceptualizing and measuring emotion-centered structural change.

PubMed

Subic-Wrana, Claudia; Beutel, Manfred E; Garfield, David A S; Lane, Richard D

2011-04-01

The need to establish the efficacy of psychoanalytic long-term treatments has promoted efforts to operationalize psychic structure and structural change as key elements of psychoanalytic treatments and their outcomes. Current, promising measures of structural change, however, require extensive interviews and rater training. The purpose of this paper is to present the theory and measurement of Levels of Emotional Awareness (LEA) and to illustrate its use based on clinical case vignettes. The LEA model lays out a developmental trajectory of affective processing, akin to Piaget's theory of sensory-cognitive development, from implicit to explicit processing. Unlike other current assessments of psychic structure (Scales of Psychological Capacities, Reflective Functioning, Operationalized Psychodynamic Diagnostics) requiring intensive rater and interviewer training, it is easily assessed based on a self-report performance test. The LEA model conceptualizes a basic psychological capacity, affect processing. As we will illustrate using two case vignettes, by operationalizing implicit and explicit modes of affect processing, it provides a clinical measure of emotional awareness that is highly pertinent to the ongoing psychoanalytic debate on the nature and mechanisms of structural change. Copyright © 2011 Institute of Psychoanalysis.

A closer look at the lower-order structure of the Personality Inventory for DSM-5: comparison with the Five-Factor Model.

PubMed

Griffin, Sarah A; Samuel, Douglas B

2014-10-01

The Personality Inventory for DSM-5 (PID-5) was developed as a measure of the maladaptive personality trait model included within Section III of the DSM-5. Although preliminary findings have suggested the PID-5 has a five-factor structure that overlaps considerably with the Five-Factor Model (FFM) at the higher order level, there has been much less attention on the specific locations of the 25 lower-order traits. Joint exploratory factor analysis of the PID-5 traits and the 30 facets of the NEO-PI-R were used to determine the lower-order structure of the PID-5. Results indicated the PID-5's domain-level structure closely resembled the FFM. We also explored the placement of several lower-order facets that have not loaded consistently in previous studies. Overall, these results indicate that the PID-5 shares a common structure with the FFM and clarify the placement of some interstitial facets. More research investigating the lower-order facets is needed to determine how they fit into the hierarchical structure and explicate their relationships to existing measures of pathological traits. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

The Domain of Cognition: An Alternative to Bloom's Cognitive Domain within the Framework of an Information Processing Model.

ERIC Educational Resources Information Center

Stahl, Robert J.; Murphy, Gary T.

Weaknesses in the structure, levels, and sequence of Bloom's taxonomy of cognitive domains emphasize the need for both a new model of how individual learners process information and a new taxonomy of the different levels of memory, thinking, and learning. Both the model and the taxonomy should be consistent with current research findings. The…

Multi-quasiparticle excitations in 145Tb

NASA Astrophysics Data System (ADS)

Zheng, Y.; Zhou, X. H.; Zhang, Y. H.; Hayakawa, T.; Oshima, M.; Toh, Y.; Shizuma, T.; Katakura, J.; Hatsukawa, Y.; Matsuda, M.; Kusakari, H.; Sugawara, M.; Furuno, K.; Komatsubara, T.

2004-04-01

High-spin states in 145Tb have been investigated by means of in-beam ggr-ray spectroscopy techniques with the 118Sn(32S, 1p4n) reaction. Excitation functions, X-ggr-t and ggr-ggr-t coincidences and ggr-ray anisotropies were measured. A level scheme of 145Tb was established up to Exap 7 MeV. The level structure shows characteristics of a spherical nucleus. Based on the systematics of level structure in the odd-A N = 80 isotones, the level structure below 2 MeV excitation is interpreted by coupling an h11/2 proton to the excitations in the even-even 144Gd core. Above 2 MeV excitation, most of the yrast levels are interpreted with multi-quasiparticle shell-model configurations.

In Silico Prediction of Organ Level Toxicity: Linking Chemistry to Adverse Effects

PubMed Central

Cronin, Mark T.D.; Enoch, Steven J.; Mellor, Claire L.; Przybylak, Katarzyna R.; Richarz, Andrea-Nicole; Madden, Judith C.

2017-01-01

In silico methods to predict toxicity include the use of (Quantitative) Structure-Activity Relationships ((Q)SARs) as well as grouping (category formation) allowing for read-across. A challenging area for in silico modelling is the prediction of chronic toxicity and the No Observed (Adverse) Effect Level (NO(A)EL) in particular. A proposed solution to the prediction of chronic toxicity is to consider organ level effects, as opposed to modelling the NO(A)EL itself. This review has focussed on the use of structural alerts to identify potential liver toxicants. In silico profilers, or groups of structural alerts, have been developed based on mechanisms of action and informed by current knowledge of Adverse Outcome Pathways. These profilers are robust and can be coded computationally to allow for prediction. However, they do not cover all mechanisms or modes of liver toxicity and recommendations for the improvement of these approaches are given. PMID:28744348

In Silico Prediction of Organ Level Toxicity: Linking Chemistry to Adverse Effects.

PubMed

Cronin, Mark T D; Enoch, Steven J; Mellor, Claire L; Przybylak, Katarzyna R; Richarz, Andrea-Nicole; Madden, Judith C

2017-07-01

In silico methods to predict toxicity include the use of (Quantitative) Structure-Activity Relationships ((Q)SARs) as well as grouping (category formation) allowing for read-across. A challenging area for in silico modelling is the prediction of chronic toxicity and the No Observed (Adverse) Effect Level (NO(A)EL) in particular. A proposed solution to the prediction of chronic toxicity is to consider organ level effects, as opposed to modelling the NO(A)EL itself. This review has focussed on the use of structural alerts to identify potential liver toxicants. In silico profilers, or groups of structural alerts, have been developed based on mechanisms of action and informed by current knowledge of Adverse Outcome Pathways. These profilers are robust and can be coded computationally to allow for prediction. However, they do not cover all mechanisms or modes of liver toxicity and recommendations for the improvement of these approaches are given.

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

USGS Publications Warehouse

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

2005-01-01

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

Perceived stress in first year medical students - associations with personal resources and emotional distress.

PubMed

Heinen, Ines; Bullinger, Monika; Kocalevent, Rüya-Daniela

2017-01-06

Medical students have been found to report high levels of perceived stress, yet there is a lack of theoretical frameworks examining possible reasons. This cross-sectional study examines correlates of perceived stress in medical students on the basis of a conceptual stress model originally developed for and applied to the general population. The aim was to identify via structural equation modeling the associations between perceived stress and emotional distress (anxiety and depression), taking into account the activation of personal resources (optimism, self-efficacy and resilient coping). Within this cross-sectional study, 321 first year medical students (age 22 ± 4 years, 39.3% men) completed the Perceived Stress Questionnaire (PSQ-20), the Self-Efficacy Optimism Scale (SWOP) and the Brief Resilient Coping Scale (BRCS) as well as the Patient Health Questionnaire (PHQ-4). The statistical analyses used t-tests, ANOVA, Spearman Rho correlation and multiple regression analysis as well as structural equation modeling. Medical students reported higher levels of perceived stress and higher levels of anxiety and depression than reference samples. No statistically significant differences in stress levels were found within the sample according to gender, migration background or employment status. Students reported more self-efficacy, optimism, and resilient coping and higher emotional distress compared to validation samples and results in other studies. Structural equation analysis revealed a satisfactory fit between empirical data and the proposed stress model indicating that personal resources modulated perceived stress, which in turn had an impact on emotional distress. Medical students' perceived stress and emotional distress levels are generally high, with personal resources acting as a buffer, thus supporting the population-based general stress model. Results suggest providing individual interventions for those students, who need support in dealing with the challenges of the medical curriculum as well as addressing structural determinants of student stress such as course load and timing of exams.

Revisiting the PLUMBER Experiments from a Process-Diagnostics Perspective

NASA Astrophysics Data System (ADS)

Nearing, G. S.; Ruddell, B. L.; Clark, M. P.; Nijssen, B.; Peters-Lidard, C. D.

2017-12-01

The PLUMBER benchmarking experiments [1] showed that some of the most sophisticated land models (CABLE, CH-TESSEL, COLA-SSiB, ISBA-SURFEX, JULES, Mosaic, Noah, ORCHIDEE) were outperformed - in simulations of half-hourly surface energy fluxes - by instantaneous, out-of-sample, and globally-stationary regressions with no state memory. One criticism of PLUMBER is that the benchmarking methodology was not derived formally, so that applying a similar methodology with different performance metrics can result in qualitatively different results. Another common criticism of model intercomparison projects in general is that they offer little insight into process-level deficiencies in the models, and therefore are of marginal value for helping to improve the models. We address both of these issues by proposing a formal benchmarking methodology that also yields a formal and quantitative method for process-level diagnostics. We apply this to the PLUMBER experiments to show that (1) the PLUMBER conclusions were generally correct - the models use only a fraction of the information available to them from met forcing data (<50% by our analysis), and (2) all of the land models investigated by PLUMBER have similar process-level error structures, and therefore together do not represent a meaningful sample of structural or epistemic uncertainty. We conclude by suggesting two ways to improve the experimental design of model intercomparison and/or model benchmarking studies like PLUMBER. First, PLUMBER did not report model parameter values, and it is necessary to know these values to separate parameter uncertainty from structural uncertainty. This is a first order requirement if we want to use intercomparison studies to provide feedback to model development. Second, technical documentation of land models is inadequate. Future model intercomparison projects should begin with a collaborative effort by model developers to document specific differences between model structures. This could be done in a reproducible way using a unified, process-flexible system like SUMMA [2]. [1] Best, M.J. et al. (2015) 'The plumbing of land surface models: benchmarking model performance', J. Hydrometeor. [2] Clark, M.P. et al. (2015) 'A unified approach for process-based hydrologic modeling: 1. Modeling concept', Water Resour. Res.

Mixed Effects Models for Resampled Network Statistics Improves Statistical Power to Find Differences in Multi-Subject Functional Connectivity

PubMed Central

Narayan, Manjari; Allen, Genevera I.

2016-01-01

Many complex brain disorders, such as autism spectrum disorders, exhibit a wide range of symptoms and disability. To understand how brain communication is impaired in such conditions, functional connectivity studies seek to understand individual differences in brain network structure in terms of covariates that measure symptom severity. In practice, however, functional connectivity is not observed but estimated from complex and noisy neural activity measurements. Imperfect subject network estimates can compromise subsequent efforts to detect covariate effects on network structure. We address this problem in the case of Gaussian graphical models of functional connectivity, by proposing novel two-level models that treat both subject level networks and population level covariate effects as unknown parameters. To account for imperfectly estimated subject level networks when fitting these models, we propose two related approaches—R2 based on resampling and random effects test statistics, and R3 that additionally employs random adaptive penalization. Simulation studies using realistic graph structures reveal that R2 and R3 have superior statistical power to detect covariate effects compared to existing approaches, particularly when the number of within subject observations is comparable to the size of subject networks. Using our novel models and methods to study parts of the ABIDE dataset, we find evidence of hypoconnectivity associated with symptom severity in autism spectrum disorders, in frontoparietal and limbic systems as well as in anterior and posterior cingulate cortices. PMID:27147940

An Introductory Classroom Exercise on Protein Molecular Model Visualization and Detailed Analysis of Protein-Ligand Binding

ERIC Educational Resources Information Center

Poeylaut-Palena, Andres, A.; de los Angeles Laborde, Maria

2013-01-01

A learning module for molecular level analysis of protein structure and ligand/drug interaction through the visualization of X-ray diffraction is presented. Using DeepView as molecular model visualization software, students learn about the general concepts of protein structure. This Biochemistry classroom exercise is designed to be carried out by…

Are Teachers' Approaches to Teaching Responsive to Individual Student Variation? A Two-Level Structural Equation Modeling

ERIC Educational Resources Information Center

Rosário, Pedro; Núñez, José Carlos; Vallejo, Guilermo; Paiva, Olímpia; Valle, António; Fuentes, Sonia; Pinto, Ricardo

2014-01-01

In the framework of teacher's approaches to teaching, this study investigates the relationship between student-related variables (i.e., study time, class absence, domain knowledge, and homework completion), students' approaches to learning, and teachers' approaches to teaching using structural equation modeling (SEM) with two…

Using a Structural Equation Model to Examine Factors Affecting Married Individuals' Sexual Embarrassment

ERIC Educational Resources Information Center

Celik, Eyup; Arici, Neslihan

2014-01-01

This study aimed to predict the effects of levels of sexual awareness, sexual courage, and sexual self-disclosure on sexual embarrassment. Data was collected from 336 married individuals, who have students in the Sultangazi District of Istanbul. According to the structural equation model (SEM), sexual self-disclosure, directly, and sexual courage…

A Novice-Expert Study of Modeling Skills and Knowledge Structures about Air Quality

ERIC Educational Resources Information Center

Hsu, Ying-Shao; Lin, Li-Fen; Wu, Hsin-Kai; Lee, Dai-Ying; Hwang, Fu-Kwun

2012-01-01

This study compared modeling skills and knowledge structures of four groups as seen in their understanding of air quality. The four groups were: experts (atmospheric scientists), intermediates (upper-level graduate students in a different field), advanced novices (talented 11th and 12th graders), and novices (10th graders). It was found that when…

Relationships between hormones and aggressive behavior in green anole lizards: an analysis using structural equation modeling.

PubMed

Yang, Eun-Jin; Wilczynski, Walter

2002-09-01

We investigated the relationship between aggressive behavior and circulating androgens in the context of agonistic social interaction and examined the effect of this interaction on the androgen-aggression relationship in response to a subsequent social challenge in male Anolis carolinensis lizards. Individuals comprising an aggressive encounter group were exposed to an aggressive conspecific male for 10 min per day during a 5-day encounter period, while controls were exposed to a neutral stimulus for the same period. On the sixth day, their responses to an intruder test were observed. At intervals, individuals were sacrificed to monitor plasma androgen levels. Structural equation modeling (SEM) was used to test three a priori interaction models of the relationship between social stimulus, aggressive behavior, and androgen. Model 1 posits that exposure to a social stimulus influences androgen and aggressive behavior independently. In Model 2, a social stimulus triggers aggressive behavior, which in turn increases circulating levels of androgen. In Model 3, exposure to a social stimulus influences circulating androgen levels, which in turn triggers aggressive behavior. During the 5 days of the encounter period, circulating testosterone (T) levels of the aggressive encounter group followed the same pattern as their aggressive behavioral responses, while the control group did not show significant changes in their aggressive behavior or T level. Our SEM results supported Model 2. A means analysis showed that during the intruder test, animals with 5 days of aggressive encounters showed more aggressive responses than did control animals, while their circulating androgen levels did not differ. This further supports Model 2, suggesting that an animal's own aggressive behavior may trigger increases in levels of plasma androgen. Copyright 2002 Elsevier Science (USA)

Sample size determinations for group-based randomized clinical trials with different levels of data hierarchy between experimental and control arms.

PubMed

Heo, Moonseong; Litwin, Alain H; Blackstock, Oni; Kim, Namhee; Arnsten, Julia H

2017-02-01

We derived sample size formulae for detecting main effects in group-based randomized clinical trials with different levels of data hierarchy between experimental and control arms. Such designs are necessary when experimental interventions need to be administered to groups of subjects whereas control conditions need to be administered to individual subjects. This type of trial, often referred to as a partially nested or partially clustered design, has been implemented for management of chronic diseases such as diabetes and is beginning to emerge more commonly in wider clinical settings. Depending on the research setting, the level of hierarchy of data structure for the experimental arm can be three or two, whereas that for the control arm is two or one. Such different levels of data hierarchy assume correlation structures of outcomes that are different between arms, regardless of whether research settings require two or three level data structure for the experimental arm. Therefore, the different correlations should be taken into account for statistical modeling and for sample size determinations. To this end, we considered mixed-effects linear models with different correlation structures between experimental and control arms to theoretically derive and empirically validate the sample size formulae with simulation studies.

Topology optimization analysis based on the direct coupling of the boundary element method and the level set method

NASA Astrophysics Data System (ADS)

Vitório, Paulo Cezar; Leonel, Edson Denner

2017-12-01

The structural design must ensure suitable working conditions by attending for safe and economic criteria. However, the optimal solution is not easily available, because these conditions depend on the bodies' dimensions, materials strength and structural system configuration. In this regard, topology optimization aims for achieving the optimal structural geometry, i.e. the shape that leads to the minimum requirement of material, respecting constraints related to the stress state at each material point. The present study applies an evolutionary approach for determining the optimal geometry of 2D structures using the coupling of the boundary element method (BEM) and the level set method (LSM). The proposed algorithm consists of mechanical modelling, topology optimization approach and structural reconstruction. The mechanical model is composed of singular and hyper-singular BEM algebraic equations. The topology optimization is performed through the LSM. Internal and external geometries are evolved by the LS function evaluated at its zero level. The reconstruction process concerns the remeshing. Because the structural boundary moves at each iteration, the body's geometry change and, consequently, a new mesh has to be defined. The proposed algorithm, which is based on the direct coupling of such approaches, introduces internal cavities automatically during the optimization process, according to the intensity of Von Mises stress. The developed optimization model was applied in two benchmarks available in the literature. Good agreement was observed among the results, which demonstrates its efficiency and accuracy.

Modeling our understanding of the His-Purkinje system.

PubMed

Vigmond, Edward J; Stuyvers, Bruno D

2016-01-01

The His-Purkinje System (HPS) is responsible for the rapid electric conduction in the ventricles. It relays electrical impulses from the atrioventricular node to the muscle cells and, thus, coordinates the contraction of ventricles in order to ensure proper cardiac pump function. The HPS has been implicated in the genesis of ventricular tachycardia and fibrillation as a source of ectopic beats, as well as forming distinct portions of reentry circuitry. Despite its importance, it remains much less well characterized, structurally and functionally, than the myocardium. Notably, important differences exist with regard to cell structure and electrophysiology, including ion channels, intracellular calcium handling, and gap junctions. Very few computational models address the HPS, and the majority of organ level modeling studies omit it. This review will provide an overview of our current knowledge of structure and function (including electrophysiology) of the HPS. We will review the most recent advances in modeling of the system from the single cell to the organ level, with considerations for relevant interspecies distinctions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Ares I-X Upper Stage Simulator Structural Analyses Supporting the NESC Critical Initial Flaw Size Assessment

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.; Phillips, Dawn R.; Raju, Ivatury S.

2008-01-01

The structural analyses described in the present report were performed in support of the NASA Engineering and Safety Center (NESC) Critical Initial Flaw Size (CIFS) assessment for the ARES I-X Upper Stage Simulator (USS) common shell segment. The structural analysis effort for the NESC assessment had three thrusts: shell buckling analyses, detailed stress analyses of the single-bolt joint test; and stress analyses of two-segment 10 degree-wedge models for the peak axial tensile running load. Elasto-plastic, large-deformation simulations were performed. Stress analysis results indicated that the stress levels were well below the material yield stress for the bounding axial tensile design load. This report also summarizes the analyses and results from parametric studies on modeling the shell-to-gusset weld, flange-surface mismatch, bolt preload, and washer-bearing-surface modeling. These analyses models were used to generate the stress levels specified for the fatigue crack growth assessment using the design load with a factor of safety.

Improving Water Level and Soil Moisture Over Peatlands in a Global Land Modeling System

NASA Technical Reports Server (NTRS)

Bechtold, M.; De Lannoy, G. J. M.; Roose, D.; Reichle, R. H.; Koster, R. D.; Mahanama, S. P.

2017-01-01

New model structure for peatlands results in improved skill metrics (without any parameter calibration) Simulated surface soil moisture strongly affected by new model, but reliable soil moisture data lacking for validation.

Dynamic and fluid–structure interaction simulations of bioprosthetic heart valves using parametric design with T-splines and Fung-type material models

PubMed Central

Kamensky, David; Xu, Fei; Kiendl, Josef; Wang, Chenglong; Wu, Michael C. H.; Mineroff, Joshua; Reali, Alessandro; Bazilevs, Yuri; Sacks, Michael S.

2015-01-01

This paper builds on a recently developed immersogeometric fluid–structure interaction (FSI) methodology for bioprosthetic heart valve (BHV) modeling and simulation. It enhances the proposed framework in the areas of geometry design and constitutive modeling. With these enhancements, BHV FSI simulations may be performed with greater levels of automation, robustness and physical realism. In addition, the paper presents a comparison between FSI analysis and standalone structural dynamics simulation driven by prescribed transvalvular pressure, the latter being a more common modeling choice for this class of problems. The FSI computation achieved better physiological realism in predicting the valve leaflet deformation than its standalone structural dynamics counterpart. PMID:26392645

Lost in folding space? Comparing four variants of the thermodynamic model for RNA secondary structure prediction.

PubMed

Janssen, Stefan; Schudoma, Christian; Steger, Gerhard; Giegerich, Robert

2011-11-03

Many bioinformatics tools for RNA secondary structure analysis are based on a thermodynamic model of RNA folding. They predict a single, "optimal" structure by free energy minimization, they enumerate near-optimal structures, they compute base pair probabilities and dot plots, representative structures of different abstract shapes, or Boltzmann probabilities of structures and shapes. Although all programs refer to the same physical model, they implement it with considerable variation for different tasks, and little is known about the effects of heuristic assumptions and model simplifications used by the programs on the outcome of the analysis. We extract four different models of the thermodynamic folding space which underlie the programs RNAFOLD, RNASHAPES, and RNASUBOPT. Their differences lie within the details of the energy model and the granularity of the folding space. We implement probabilistic shape analysis for all models, and introduce the shape probability shift as a robust measure of model similarity. Using four data sets derived from experimentally solved structures, we provide a quantitative evaluation of the model differences. We find that search space granularity affects the computed shape probabilities less than the over- or underapproximation of free energy by a simplified energy model. Still, the approximations perform similar enough to implementations of the full model to justify their continued use in settings where computational constraints call for simpler algorithms. On the side, we observe that the rarely used level 2 shapes, which predict the complete arrangement of helices, multiloops, internal loops and bulges, include the "true" shape in a rather small number of predicted high probability shapes. This calls for an investigation of new strategies to extract high probability members from the (very large) level 2 shape space of an RNA sequence. We provide implementations of all four models, written in a declarative style that makes them easy to be modified. Based on our study, future work on thermodynamic RNA folding may make a choice of model based on our empirical data. It can take our implementations as a starting point for further program development.

Effect of Material Ion Exchanges on the Mechanical Stiffness Properties and Shear Deformation of Hydrated Cement Material Chemistry Structure C-S-H Jennit - A Computational Modeling Study

DTIC Science & Technology

2014-01-01

Study Material properties and performance are governed by material molecular chemistry structures and molecular level interactions. Methods to...understand relationships between the material properties and performance and their correlation to the molecular level chemistry and morphology, and thus...find ways of manipulating and adjusting matters at the atomistic level in order to improve material performance are required. A computational material

Clusternomics: Integrative context-dependent clustering for heterogeneous datasets

PubMed Central

Wernisch, Lorenz

2017-01-01

Integrative clustering is used to identify groups of samples by jointly analysing multiple datasets describing the same set of biological samples, such as gene expression, copy number, methylation etc. Most existing algorithms for integrative clustering assume that there is a shared consistent set of clusters across all datasets, and most of the data samples follow this structure. However in practice, the structure across heterogeneous datasets can be more varied, with clusters being joined in some datasets and separated in others. In this paper, we present a probabilistic clustering method to identify groups across datasets that do not share the same cluster structure. The proposed algorithm, Clusternomics, identifies groups of samples that share their global behaviour across heterogeneous datasets. The algorithm models clusters on the level of individual datasets, while also extracting global structure that arises from the local cluster assignments. Clusters on both the local and the global level are modelled using a hierarchical Dirichlet mixture model to identify structure on both levels. We evaluated the model both on simulated and on real-world datasets. The simulated data exemplifies datasets with varying degrees of common structure. In such a setting Clusternomics outperforms existing algorithms for integrative and consensus clustering. In a real-world application, we used the algorithm for cancer subtyping, identifying subtypes of cancer from heterogeneous datasets. We applied the algorithm to TCGA breast cancer dataset, integrating gene expression, miRNA expression, DNA methylation and proteomics. The algorithm extracted clinically meaningful clusters with significantly different survival probabilities. We also evaluated the algorithm on lung and kidney cancer TCGA datasets with high dimensionality, again showing clinically significant results and scalability of the algorithm. PMID:29036190

Clusternomics: Integrative context-dependent clustering for heterogeneous datasets.

PubMed

Gabasova, Evelina; Reid, John; Wernisch, Lorenz

2017-10-01

Integrative clustering is used to identify groups of samples by jointly analysing multiple datasets describing the same set of biological samples, such as gene expression, copy number, methylation etc. Most existing algorithms for integrative clustering assume that there is a shared consistent set of clusters across all datasets, and most of the data samples follow this structure. However in practice, the structure across heterogeneous datasets can be more varied, with clusters being joined in some datasets and separated in others. In this paper, we present a probabilistic clustering method to identify groups across datasets that do not share the same cluster structure. The proposed algorithm, Clusternomics, identifies groups of samples that share their global behaviour across heterogeneous datasets. The algorithm models clusters on the level of individual datasets, while also extracting global structure that arises from the local cluster assignments. Clusters on both the local and the global level are modelled using a hierarchical Dirichlet mixture model to identify structure on both levels. We evaluated the model both on simulated and on real-world datasets. The simulated data exemplifies datasets with varying degrees of common structure. In such a setting Clusternomics outperforms existing algorithms for integrative and consensus clustering. In a real-world application, we used the algorithm for cancer subtyping, identifying subtypes of cancer from heterogeneous datasets. We applied the algorithm to TCGA breast cancer dataset, integrating gene expression, miRNA expression, DNA methylation and proteomics. The algorithm extracted clinically meaningful clusters with significantly different survival probabilities. We also evaluated the algorithm on lung and kidney cancer TCGA datasets with high dimensionality, again showing clinically significant results and scalability of the algorithm.

Food-Web Models Predict Species Abundances in Response to Habitat Change

PubMed Central

Gotelli, Nicholas J; Ellison, Aaron M

2006-01-01

Plant and animal population sizes inevitably change following habitat loss, but the mechanisms underlying these changes are poorly understood. We experimentally altered habitat volume and eliminated top trophic levels of the food web of invertebrates that inhabit rain-filled leaves of the carnivorous pitcher plant Sarracenia purpurea. Path models that incorporated food-web structure better predicted population sizes of food-web constituents than did simple keystone species models, models that included only autecological responses to habitat volume, or models including both food-web structure and habitat volume. These results provide the first experimental confirmation that trophic structure can determine species abundances in the face of habitat loss. PMID:17002518

RADIATIVE TRANSFER MODELING OF THE ENIGMATIC SCATTERING POLARIZATION IN THE SOLAR Na i D{sub 1} LINE

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

Belluzzi, Luca; Bueno, Javier Trujillo; Degl’Innocenti, Egidio Landi

2015-12-01

The modeling of the peculiar scattering polarization signals observed in some diagnostically important solar resonance lines requires the consideration of the detailed spectral structure of the incident radiation field as well as the possibility of ground level polarization, along with the atom's hyperfine structure and quantum interference between hyperfine F-levels pertaining either to the same fine structure J-level, or to different J-levels of the same term. Here we present a theoretical and numerical approach suitable for solving this complex non-LTE radiative transfer problem. This approach is based on the density-matrix metalevel theory (where each level is viewed as a continuousmore » distribution of sublevels) and on accurate formal solvers of the transfer equations and efficient iterative methods. We show an application to the D-lines of Na i, with emphasis on the enigmatic D{sub 1} line, pointing out the observable signatures of the various physical mechanisms considered. We demonstrate that the linear polarization observed in the core of the D{sub 1} line may be explained by the effect that one gets when the detailed spectral structure of the anisotropic radiation responsible for the optical pumping is taken into account. This physical ingredient is capable of introducing significant scattering polarization in the core of the Na i D{sub 1} line without the need for ground-level polarization.« less

Use of airborne lidar data to improve plant species richness and diversity monitoring in lowland and mountain forests

PubMed Central

Durrieu, Sylvie; Gosselin, Frédéric; Herpigny, Basile

2017-01-01

We explored the potential of airborne laser scanner (ALS) data to improve Bayesian models linking biodiversity indicators of the understory vegetation to environmental factors. Biodiversity was studied at plot level and models were built to investigate species abundance for the most abundant plants found on each study site, and for ecological group richness based on light preference. The usual abiotic explanatory factors related to climate, topography and soil properties were used in the models. ALS data, available for two contrasting study sites, were used to provide biotic factors related to forest structure, which was assumed to be a key driver of understory biodiversity. Several ALS variables were found to have significant effects on biodiversity indicators. However, the responses of biodiversity indicators to forest structure variables, as revealed by the Bayesian model outputs, were shown to be dependent on the abiotic environmental conditions characterizing the study areas. Lower responses were observed on the lowland site than on the mountainous site. In the latter, shade-tolerant and heliophilous species richness was impacted by vegetation structure indicators linked to light penetration through the canopy. However, to reveal the full effects of forest structure on biodiversity indicators, forest structure would need to be measured over much wider areas than the plot we assessed. It seems obvious that the forest structure surrounding the field plots can impact biodiversity indicators measured at plot level. Various scales were found to be relevant depending on: the biodiversity indicators that were modelled, and the ALS variable. Finally, our results underline the utility of lidar data in abundance and richness models to characterize forest structure with variables that are difficult to measure in the field, either due to their nature or to the size of the area they relate to. PMID:28902920

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.

Multi-Length Scale-Enriched Continuum-Level Material Model for Kevlar (registered trademark)-Fiber-Reinforced Polymer-Matrix Composites

DTIC Science & Technology

2013-03-01

of coarser-scale materials and structures containing Kevlar fibers (e.g., yarns, fabrics, plies, lamina, and laminates ). Journal of Materials...Multi-Length Scale-Enriched Continuum-Level Material Model for Kevlar -Fiber-Reinforced Polymer-Matrix Composites M. Grujicic, B. Pandurangan, J.S...extensive set of molecular-level computational analyses regarding the role of various microstructural/morphological defects on the Kevlar fiber

Construction of a three-dimensional finite element model of maxillary first molar and it's supporting structures

PubMed Central

Begum, M. Sameena; Dinesh, M. R.; Tan, Kenneth F. H.; Jairaj, Vani; Md Khalid, K.; Singh, Varun Pratap

2015-01-01

The finite element method (FEM) is a powerful computational tool for solving stress-strain problems; its ability to handle material inhomogeneity and complex shapes makes the FEM, the most suitable method for the analysis of internal stress levels in the tooth, periodontium, and alveolar bone. This article intends to explain the steps involved in the generation of a three-dimensional finite element model of tooth, periodontal ligament (PDL) and alveolar bone, as the procedure of modeling is most important because the result is based on the nature of the modeling systems. Finite element analysis offers a means of determining strain-stress levels in the tooth, ligament, and bone structures for a broad range of orthodontic loading scenarios without producing tissue damage. PMID:26538895

Protein loop modeling using a new hybrid energy function and its application to modeling in inaccurate structural environments.

PubMed

Park, Hahnbeom; Lee, Gyu Rie; Heo, Lim; Seok, Chaok

2014-01-01

Protein loop modeling is a tool for predicting protein local structures of particular interest, providing opportunities for applications involving protein structure prediction and de novo protein design. Until recently, the majority of loop modeling methods have been developed and tested by reconstructing loops in frameworks of experimentally resolved structures. In many practical applications, however, the protein loops to be modeled are located in inaccurate structural environments. These include loops in model structures, low-resolution experimental structures, or experimental structures of different functional forms. Accordingly, discrepancies in the accuracy of the structural environment assumed in development of the method and that in practical applications present additional challenges to modern loop modeling methods. This study demonstrates a new strategy for employing a hybrid energy function combining physics-based and knowledge-based components to help tackle this challenge. The hybrid energy function is designed to combine the strengths of each energy component, simultaneously maintaining accurate loop structure prediction in a high-resolution framework structure and tolerating minor environmental errors in low-resolution structures. A loop modeling method based on global optimization of this new energy function is tested on loop targets situated in different levels of environmental errors, ranging from experimental structures to structures perturbed in backbone as well as side chains and template-based model structures. The new method performs comparably to force field-based approaches in loop reconstruction in crystal structures and better in loop prediction in inaccurate framework structures. This result suggests that higher-accuracy predictions would be possible for a broader range of applications. The web server for this method is available at http://galaxy.seoklab.org/loop with the PS2 option for the scoring function.

Uncertainty and Intelligence in Computational Stochastic Mechanics

NASA Technical Reports Server (NTRS)

Ayyub, Bilal M.

1996-01-01

Classical structural reliability assessment techniques are based on precise and crisp (sharp) definitions of failure and non-failure (survival) of a structure in meeting a set of strength, function and serviceability criteria. These definitions are provided in the form of performance functions and limit state equations. Thus, the criteria provide a dichotomous definition of what real physical situations represent, in the form of abrupt change from structural survival to failure. However, based on observing the failure and survival of real structures according to the serviceability and strength criteria, the transition from a survival state to a failure state and from serviceability criteria to strength criteria are continuous and gradual rather than crisp and abrupt. That is, an entire spectrum of damage or failure levels (grades) is observed during the transition to total collapse. In the process, serviceability criteria are gradually violated with monotonically increasing level of violation, and progressively lead into the strength criteria violation. Classical structural reliability methods correctly and adequately include the ambiguity sources of uncertainty (physical randomness, statistical and modeling uncertainty) by varying amounts. However, they are unable to adequately incorporate the presence of a damage spectrum, and do not consider in their mathematical framework any sources of uncertainty of the vagueness type. Vagueness can be attributed to sources of fuzziness, unclearness, indistinctiveness, sharplessness and grayness; whereas ambiguity can be attributed to nonspecificity, one-to-many relations, variety, generality, diversity and divergence. Using the nomenclature of structural reliability, vagueness and ambiguity can be accounted for in the form of realistic delineation of structural damage based on subjective judgment of engineers. For situations that require decisions under uncertainty with cost/benefit objectives, the risk of failure should depend on the underlying level of damage and the uncertainties associated with its definition. A mathematical model for structural reliability assessment that includes both ambiguity and vagueness types of uncertainty was suggested to result in the likelihood of failure over a damage spectrum. The resulting structural reliability estimates properly represent the continuous transition from serviceability to strength limit states over the ultimate time exposure of the structure. In this section, a structural reliability assessment method based on a fuzzy definition of failure is suggested to meet these practical needs. A failure definition can be developed to indicate the relationship between failure level and structural response. In this fuzzy model, a subjective index is introduced to represent all levels of damage (or failure). This index can be interpreted as either a measure of failure level or a measure of a degree of belief in the occurrence of some performance condition (e.g., failure). The index allows expressing the transition state between complete survival and complete failure for some structural response based on subjective evaluation and judgment.

An object-relational model for structured representation of medical knowledge.

PubMed

Koch, S; Risch, T; Schneider, W; Wagner, I V

2006-07-01

Domain specific knowledge is often not static but continuously evolving. This is especially true for the medical domain. Furthermore, the lack of standardized structures for presenting knowledge makes it difficult or often impossible to assess new knowledge in the context of existing knowledge. Possibilities to compare knowledge easily and directly are often not given. It is therefore of utmost importance to create a model that allows for comparability, consistency and quality assurance of medical knowledge in specific work situations. For this purpose, we have designed on object-relational model based on structured knowledge elements that are dynamically reusable by different multi-media-based tools for case-based documentation, disease course simulation, and decision support. With this model, high-level components, such as patient case reports or simulations of the course of a disease, and low-level components (e.g., diagnoses, symptoms or treatments) as well as the relationships between these components are modeled. The resulting schema has been implemented in AMOS II, on object-relational multi-database system supporting different views with regard to search and analysis depending on different work situations.

Hierarchical Bayesian models to assess between- and within-batch variability of pathogen contamination in food.

PubMed

Commeau, Natalie; Cornu, Marie; Albert, Isabelle; Denis, Jean-Baptiste; Parent, Eric

2012-03-01

Assessing within-batch and between-batch variability is of major interest for risk assessors and risk managers in the context of microbiological contamination of food. For example, the ratio between the within-batch variability and the between-batch variability has a large impact on the results of a sampling plan. Here, we designed hierarchical Bayesian models to represent such variability. Compatible priors were built mathematically to obtain sound model comparisons. A numeric criterion is proposed to assess the contamination structure comparing the ability of the models to replicate grouped data at the batch level using a posterior predictive loss approach. Models were applied to two case studies: contamination by Listeria monocytogenes of pork breast used to produce diced bacon and contamination by the same microorganism on cold smoked salmon at the end of the process. In the first case study, a contamination structure clearly exists and is located at the batch level, that is, between batches variability is relatively strong, whereas in the second a structure also exists but is less marked. © 2012 Society for Risk Analysis.

First-principle calculation of core level binding energies of Li{sub x}PO{sub y}N{sub z} solid electrolyte

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

Guille, Émilie; Vallverdu, Germain, E-mail: germain.vallverdu@univ-pau.fr; Baraille, Isabelle

2014-12-28

We present first-principle calculations of core-level binding energies for the study of insulating, bulk phase, compounds, based on the Slater-Janak transition state model. Those calculations were performed in order to find a reliable model of the amorphous Li{sub x}PO{sub y}N{sub z} solid electrolyte which is able to reproduce its electronic properties gathered from X-ray photoemission spectroscopy (XPS) experiments. As a starting point, Li{sub 2}PO{sub 2}N models were investigated. These models, proposed by Du et al. on the basis of thermodynamics and vibrational properties, were the first structural models of Li{sub x}PO{sub y}N{sub z}. Thanks to chemical and structural modifications appliedmore » to Li{sub 2}PO{sub 2}N structures, which allow to demonstrate the relevance of our computational approach, we raise an issue concerning the possibility of encountering a non-bridging kind of nitrogen atoms (=N{sup −}) in Li{sub x}PO{sub y}N{sub z} compounds.« less

Bayesian Chance-Constrained Hydraulic Barrier Design under Geological Structure Uncertainty.

PubMed

Chitsazan, Nima; Pham, Hai V; Tsai, Frank T-C

2015-01-01

The groundwater community has widely recognized geological structure uncertainty as a major source of model structure uncertainty. Previous studies in aquifer remediation design, however, rarely discuss the impact of geological structure uncertainty. This study combines chance-constrained (CC) programming with Bayesian model averaging (BMA) as a BMA-CC framework to assess the impact of geological structure uncertainty in remediation design. To pursue this goal, the BMA-CC method is compared with traditional CC programming that only considers model parameter uncertainty. The BMA-CC method is employed to design a hydraulic barrier to protect public supply wells of the Government St. pump station from salt water intrusion in the "1500-foot" sand and the "1700-foot" sand of the Baton Rouge area, southeastern Louisiana. To address geological structure uncertainty, three groundwater models based on three different hydrostratigraphic architectures are developed. The results show that using traditional CC programming overestimates design reliability. The results also show that at least five additional connector wells are needed to achieve more than 90% design reliability level. The total amount of injected water from the connector wells is higher than the total pumpage of the protected public supply wells. While reducing the injection rate can be achieved by reducing the reliability level, the study finds that the hydraulic barrier design to protect the Government St. pump station may not be economically attractive. © 2014, National Ground Water Association.

3D hierarchical geometric modeling and multiscale FE analysis as a base for individualized medical diagnosis of bone structure.

PubMed

Podshivalov, L; Fischer, A; Bar-Yoseph, P Z

2011-04-01

This paper describes a new alternative for individualized mechanical analysis of bone trabecular structure. This new method closes the gap between the classic homogenization approach that is applied to macro-scale models and the modern micro-finite element method that is applied directly to micro-scale high-resolution models. The method is based on multiresolution geometrical modeling that generates intermediate structural levels. A new method for estimating multiscale material properties has also been developed to facilitate reliable and efficient mechanical analysis. What makes this method unique is that it enables direct and interactive analysis of the model at every intermediate level. Such flexibility is of principal importance in the analysis of trabecular porous structure. The method enables physicians to zoom-in dynamically and focus on the volume of interest (VOI), thus paving the way for a large class of investigations into the mechanical behavior of bone structure. This is one of the very few methods in the field of computational bio-mechanics that applies mechanical analysis adaptively on large-scale high resolution models. The proposed computational multiscale FE method can serve as an infrastructure for a future comprehensive computerized system for diagnosis of bone structures. The aim of such a system is to assist physicians in diagnosis, prognosis, drug treatment simulation and monitoring. Such a system can provide a better understanding of the disease, and hence benefit patients by providing better and more individualized treatment and high quality healthcare. In this paper, we demonstrate the feasibility of our method on a high-resolution model of vertebra L3. Copyright © 2010 Elsevier Inc. All rights reserved.

A Structural Equation Model on Korean Adolescents' Excessive Use of Smartphones.

PubMed

Lee, Hana; Kim, JooHyun

2018-03-31

We develop a unified structural model that defines multi-relationships between systematic factors causing excessive use of smartphones and the corresponding results. We conducted a survey with adolescents who live in Seoul, Pusan, Gangneung, Donghae, and Samcheok from Feb. to Mar. 2016. We utilized SPSS Ver. 22 and Amos Ver. 22 to analyze the survey result at a 0.05 significance level. To investigate demographic characteristics of the participants and their variations, we employed descriptive analysis. We adopted the maximum likelihood estimate method to verify the fitness of the hypothetical model and the hypotheses therein. We used χ 2 statistics, GFI, AGFI, CFI, NFI, IFI, RMR, and RMSEA to verify the fitness of our structural model. (1) Our proposed structural model demonstrated a fine fitness level. (2) Our proposed structural model could describe the excessive use of a smartphone with 88.6% accuracy. (3) The absence of the family function and relationship between friends, impulsiveness, and low self-esteem were confirmed as key factors that cause excessive use of smartphones. (4) Further, impulsiveness and low self-esteem are closely related to the absence of family functions and relations between friends by 68.3% and 54.4%, respectively. We suggest that nursing intervention programs from various angles are required to reduce adolescents' excessive use of smartphones. For example, family communication programs would be helpful for both parents and children. Consultant programs about friend relationship also meaningful for the program. Copyright © 2018. Published by Elsevier B.V.

Evaluation of the Use of Zero-Augmented Regression Techniques to Model Incidence of Campylobacter Infections in FoodNet.

PubMed

Tremblay, Marlène; Crim, Stacy M; Cole, Dana J; Hoekstra, Robert M; Henao, Olga L; Döpfer, Dörte

2017-10-01

The Foodborne Diseases Active Surveillance Network (FoodNet) is currently using a negative binomial (NB) regression model to estimate temporal changes in the incidence of Campylobacter infection. FoodNet active surveillance in 483 counties collected data on 40,212 Campylobacter cases between years 2004 and 2011. We explored models that disaggregated these data to allow us to account for demographic, geographic, and seasonal factors when examining changes in incidence of Campylobacter infection. We hypothesized that modeling structural zeros and including demographic variables would increase the fit of FoodNet's Campylobacter incidence regression models. Five different models were compared: NB without demographic covariates, NB with demographic covariates, hurdle NB with covariates in the count component only, hurdle NB with covariates in both zero and count components, and zero-inflated NB with covariates in the count component only. Of the models evaluated, the nonzero-augmented NB model with demographic variables provided the best fit. Results suggest that even though zero inflation was not present at this level, individualizing the level of aggregation and using different model structures and predictors per site might be required to correctly distinguish between structural and observational zeros and account for risk factors that vary geographically.

Ensemble-based evaluation for protein structure models.

PubMed

Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke

2016-06-15

Comparing protein tertiary structures is a fundamental procedure in structural biology and protein bioinformatics. Structure comparison is important particularly for evaluating computational protein structure models. Most of the model structure evaluation methods perform rigid body superimposition of a structure model to its crystal structure and measure the difference of the corresponding residue or atom positions between them. However, these methods neglect intrinsic flexibility of proteins by treating the native structure as a rigid molecule. Because different parts of proteins have different levels of flexibility, for example, exposed loop regions are usually more flexible than the core region of a protein structure, disagreement of a model to the native needs to be evaluated differently depending on the flexibility of residues in a protein. We propose a score named FlexScore for comparing protein structures that consider flexibility of each residue in the native state of proteins. Flexibility information may be extracted from experiments such as NMR or molecular dynamics simulation. FlexScore considers an ensemble of conformations of a protein described as a multivariate Gaussian distribution of atomic displacements and compares a query computational model with the ensemble. We compare FlexScore with other commonly used structure similarity scores over various examples. FlexScore agrees with experts' intuitive assessment of computational models and provides information of practical usefulness of models. https://bitbucket.org/mjamroz/flexscore dkihara@purdue.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Ensemble-based evaluation for protein structure models

PubMed Central

Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke

2016-01-01

Motivation: Comparing protein tertiary structures is a fundamental procedure in structural biology and protein bioinformatics. Structure comparison is important particularly for evaluating computational protein structure models. Most of the model structure evaluation methods perform rigid body superimposition of a structure model to its crystal structure and measure the difference of the corresponding residue or atom positions between them. However, these methods neglect intrinsic flexibility of proteins by treating the native structure as a rigid molecule. Because different parts of proteins have different levels of flexibility, for example, exposed loop regions are usually more flexible than the core region of a protein structure, disagreement of a model to the native needs to be evaluated differently depending on the flexibility of residues in a protein. Results: We propose a score named FlexScore for comparing protein structures that consider flexibility of each residue in the native state of proteins. Flexibility information may be extracted from experiments such as NMR or molecular dynamics simulation. FlexScore considers an ensemble of conformations of a protein described as a multivariate Gaussian distribution of atomic displacements and compares a query computational model with the ensemble. We compare FlexScore with other commonly used structure similarity scores over various examples. FlexScore agrees with experts’ intuitive assessment of computational models and provides information of practical usefulness of models. Availability and implementation: https://bitbucket.org/mjamroz/flexscore Contact: dkihara@purdue.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307633

Simulation model for plant growth in controlled environment systems

NASA Technical Reports Server (NTRS)

Raper, C. D., Jr.; Wann, M.

1986-01-01

The role of the mathematical model is to relate the individual processes to environmental conditions and the behavior of the whole plant. Using the controlled-environment facilities of the phytotron at North Carolina State University for experimentation at the whole-plant level and methods for handling complex models, researchers developed a plant growth model to describe the relationships between hierarchial levels of the crop production system. The fundamental processes that are considered are: (1) interception of photosynthetically active radiation by leaves, (2) absorption of photosynthetically active radiation, (3) photosynthetic transformation of absorbed radiation into chemical energy of carbon bonding in solube carbohydrates in the leaves, (4) translocation between carbohydrate pools in leaves, stems, and roots, (5) flow of energy from carbohydrate pools for respiration, (6) flow from carbohydrate pools for growth, and (7) aging of tissues. These processes are described at the level of organ structure and of elementary function processes. The driving variables of incident photosynthetically active radiation and ambient temperature as inputs pertain to characterization at the whole-plant level. The output of the model is accumulated dry matter partitioned among leaves, stems, and roots; thus, the elementary processes clearly operate under the constraints of the plant structure which is itself the output of the model.

Model tracking system for low-level radioactive waste disposal facilities: License application interrogatories and responses

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

Benbennick, M.E.; Broton, M.S.; Fuoto, J.S.

This report describes a model tracking system for a low-level radioactive waste (LLW) disposal facility license application. In particular, the model tracks interrogatories (questions, requests for information, comments) and responses. A set of requirements and desired features for the model tracking system was developed, including required structure and computer screens. Nine tracking systems were then reviewed against the model system requirements and only two were found to meet all requirements. Using Kepner-Tregoe decision analysis, a model tracking system was selected.

Modified level II streambed-scour analysis for structure I-65-85-5527 crossing Sugar Creek in Johnson County, Indiana

USGS Publications Warehouse

Robinson, B.A.; Voelker, D.C.; Miller, R.L.

1997-01-01

Level II scour evaluations follow a process in which hydrologic, hydraulic, and sediment transport data are evaluated to calculate the depth of scour that may result when a given discharge is routed through a bridge opening. The results of the modified Level II analysis for structure 1-65-85-5527 on Interstate 65 crossing Sugar Creek in Johnson County, Indiana, are presented. The site is near the town of Amity in the southeastern part of Johnson County. Scour depths were computed with the Water Surface PROfile model, version V050196, which incorporates the scour-calculation procedures outlined in Hydraulic Engineering Circular No. 18. Total scour depths at the piers were approximately 26.8 feet for the modeled discharge of 26,000 cubic feet per second and approximately 30.8 feet for the modeled discharge of 34,100 cubic feet per second

Modified level II streambed-scour analysis for structure I-74-32-4946 crossing Sugar Creek in Montgomery County, Indiana

USGS Publications Warehouse

Miller, R.L.; Robinson, B.A.; Voelker, D.C.

1997-01-01

Level II scour evaluations follow a process in which hydrologic, hydraulic, and sedient-transport data are evaluated to calculate the depth of scour that may result when given discharge is routed through a bridge opening. The results of the modified Levell II analysis for structure I-74-32-4946 on Interstate 74 crossing Sugar Creek in Montgomery County, Indiana are presented. The site is near the town of Crawfordsville in the central part of Montgomery County. Scour depths were computed with the Water Surface PROfile model, version V050196, which incorporates the scour-calculation procedures outlined in Hydraulic Engineering Circular No. 18. Total scour depths at the piers were approximately 13.0 feet for the modeled discharge of 3,000  cubic feet per second and approximately 15.1 feet for the modeled discharge of 41,900 cubic feet per second.

Structure and dynamics of human vimentin intermediate filament dimer and tetramer in explicit and implicit solvent models.

PubMed

Qin, Zhao; Buehler, Markus J

2011-01-01

Intermediate filaments, in addition to microtubules and microfilaments, are one of the three major components of the cytoskeleton in eukaryotic cells, and play an important role in mechanotransduction as well as in providing mechanical stability to cells at large stretch. The molecular structures, mechanical and dynamical properties of the intermediate filament basic building blocks, the dimer and the tetramer, however, have remained elusive due to persistent experimental challenges owing to the large size and fibrillar geometry of this protein. We have recently reported an atomistic-level model of the human vimentin dimer and tetramer, obtained through a bottom-up approach based on structural optimization via molecular simulation based on an implicit solvent model (Qin et al. in PLoS ONE 2009 4(10):e7294, 9). Here we present extensive simulations and structural analyses of the model based on ultra large-scale atomistic-level simulations in an explicit solvent model, with system sizes exceeding 500,000 atoms and simulations carried out at 20 ns time-scales. We report a detailed comparison of the structural and dynamical behavior of this large biomolecular model with implicit and explicit solvent models. Our simulations confirm the stability of the molecular model and provide insight into the dynamical properties of the dimer and tetramer. Specifically, our simulations reveal a heterogeneous distribution of the bending stiffness along the molecular axis with the formation of rather soft and highly flexible hinge-like regions defined by non-alpha-helical linker domains. We report a comparison of Ramachandran maps and the solvent accessible surface area between implicit and explicit solvent models, and compute the persistence length of the dimer and tetramer structure of vimentin intermediate filaments for various subdomains of the protein. Our simulations provide detailed insight into the dynamical properties of the vimentin dimer and tetramer intermediate filament building blocks, which may guide the development of novel coarse-grained models of intermediate filaments, and could also help in understanding assembly mechanisms.

Exploring the hierarchical structure of the MMPI-2-RF Personality Psychopathology Five in psychiatric patient and university student samples.

PubMed

Bagby, R Michael; Sellbom, Martin; Ayearst, Lindsay E; Chmielewski, Michael S; Anderson, Jaime L; Quilty, Lena C

2014-01-01

In this study our goal was to examine the hierarchical structure of personality pathology as conceptualized by Harkness and McNulty's (1994) Personality Psychopathology Five (PSY-5) model, as recently operationalized by the MMPI-2-RF (Ben-Porath & Tellegen, 2011) PSY-5r scales. We used Goldberg's (2006) "bass-ackwards" method to obtain factor structure using PSY-5r item data, successively extracting from 1 to 5 factors in a sample of psychiatric patients (n = 1,000) and a sample of university undergraduate students (n = 1,331). Participants from these samples had completed either the MMPI-2 or the MMPI-2-RF. The results were mostly consistent across the 2 samples, with some differences at the 3-factor level. In the patient sample a factor structure representing 3 broad psychopathology domains (internalizing, externalizing, and psychoticism) emerged; in the student sample the 3-factor level represented what is more commonly observed in "normal-range" personality models (negative emotionality, introversion, and disconstraint). At the 5-factor level the basic structure was similar across the 2 samples and represented well the PSY-5r domains.

Contribution to viscosity from the structural relaxation via the atomic scale Green-Kubo stress correlation function.

PubMed

Levashov, V A

2017-11-14

We studied the connection between the structural relaxation and viscosity for a binary model of repulsive particles in the supercooled liquid regime. The used approach is based on the decomposition of the macroscopic Green-Kubo stress correlation function into the correlation functions between the atomic level stresses. Previously we used the approach to study an iron-like single component system of particles. The role of vibrational motion has been addressed through the demonstration of the relationship between viscosity and the shear waves propagating over large distances. In our previous considerations, however, we did not discuss the role of the structural relaxation. Here we suggest that the contribution to viscosity from the structural relaxation can be taken into account through the consideration of the contribution from the atomic stress auto-correlation term only. This conclusion, however, does not mean that only the auto-correlation term represents the contribution to viscosity from the structural relaxation. Previously the role of the structural relaxation for viscosity has been addressed through the considerations of the transitions between inherent structures and within the mode-coupling theory by other authors. In the present work, we study the structural relaxation through the considerations of the parent liquid and the atomic level stress correlations in it. The comparison with the results obtained on the inherent structures also is made. Our current results suggest, as our previous observations, that in the supercooled liquid regime, the vibrational contribution to viscosity extends over the times that are much larger than the Einstein's vibrational period and much larger than the times that it takes for the shear waves to propagate over the model systems. Besides addressing the atomic level shear stress correlations, we also studied correlations between the atomic level pressure elements.

Contribution to viscosity from the structural relaxation via the atomic scale Green-Kubo stress correlation function

NASA Astrophysics Data System (ADS)

Levashov, V. A.

2017-11-01

We studied the connection between the structural relaxation and viscosity for a binary model of repulsive particles in the supercooled liquid regime. The used approach is based on the decomposition of the macroscopic Green-Kubo stress correlation function into the correlation functions between the atomic level stresses. Previously we used the approach to study an iron-like single component system of particles. The role of vibrational motion has been addressed through the demonstration of the relationship between viscosity and the shear waves propagating over large distances. In our previous considerations, however, we did not discuss the role of the structural relaxation. Here we suggest that the contribution to viscosity from the structural relaxation can be taken into account through the consideration of the contribution from the atomic stress auto-correlation term only. This conclusion, however, does not mean that only the auto-correlation term represents the contribution to viscosity from the structural relaxation. Previously the role of the structural relaxation for viscosity has been addressed through the considerations of the transitions between inherent structures and within the mode-coupling theory by other authors. In the present work, we study the structural relaxation through the considerations of the parent liquid and the atomic level stress correlations in it. The comparison with the results obtained on the inherent structures also is made. Our current results suggest, as our previous observations, that in the supercooled liquid regime, the vibrational contribution to viscosity extends over the times that are much larger than the Einstein's vibrational period and much larger than the times that it takes for the shear waves to propagate over the model systems. Besides addressing the atomic level shear stress correlations, we also studied correlations between the atomic level pressure elements.

The effects of time-varying observation errors on semi-empirical sea-level projections

DOE PAGES

Ruckert, Kelsey L.; Guan, Yawen; Bakker, Alexander M. R.; ...

2016-11-30

Sea-level rise is a key driver of projected flooding risks. The design of strategies to manage these risks often hinges on projections that inform decision-makers about the surrounding uncertainties. Producing semi-empirical sea-level projections is difficult, for example, due to the complexity of the error structure of the observations, such as time-varying (heteroskedastic) observation errors and autocorrelation of the data-model residuals. This raises the question of how neglecting the error structure impacts hindcasts and projections. Here, we quantify this effect on sea-level projections and parameter distributions by using a simple semi-empirical sea-level model. Specifically, we compare three model-fitting methods: a frequentistmore » bootstrap as well as a Bayesian inversion with and without considering heteroskedastic residuals. All methods produce comparable hindcasts, but the parametric distributions and projections differ considerably based on methodological choices. In conclusion, our results show that the differences based on the methodological choices are enhanced in the upper tail projections. For example, the Bayesian inversion accounting for heteroskedasticity increases the sea-level anomaly with a 1% probability of being equaled or exceeded in the year 2050 by about 34% and about 40% in the year 2100 compared to a frequentist bootstrap. These results indicate that neglecting known properties of the observation errors and the data-model residuals can lead to low-biased sea-level projections.« less

The effects of time-varying observation errors on semi-empirical sea-level projections

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

Ruckert, Kelsey L.; Guan, Yawen; Bakker, Alexander M. R.

Sea-level rise is a key driver of projected flooding risks. The design of strategies to manage these risks often hinges on projections that inform decision-makers about the surrounding uncertainties. Producing semi-empirical sea-level projections is difficult, for example, due to the complexity of the error structure of the observations, such as time-varying (heteroskedastic) observation errors and autocorrelation of the data-model residuals. This raises the question of how neglecting the error structure impacts hindcasts and projections. Here, we quantify this effect on sea-level projections and parameter distributions by using a simple semi-empirical sea-level model. Specifically, we compare three model-fitting methods: a frequentistmore » bootstrap as well as a Bayesian inversion with and without considering heteroskedastic residuals. All methods produce comparable hindcasts, but the parametric distributions and projections differ considerably based on methodological choices. In conclusion, our results show that the differences based on the methodological choices are enhanced in the upper tail projections. For example, the Bayesian inversion accounting for heteroskedasticity increases the sea-level anomaly with a 1% probability of being equaled or exceeded in the year 2050 by about 34% and about 40% in the year 2100 compared to a frequentist bootstrap. These results indicate that neglecting known properties of the observation errors and the data-model residuals can lead to low-biased sea-level projections.« less

Prediction of the interior noise levels of high-speed propeller-driven aircraft

NASA Technical Reports Server (NTRS)

Rennison, D. C.; Wilby, J. F.; Wilby, E. G.

1980-01-01

The theoretical basis for an analytical model developed to predict the interior noise levels of high-speed propeller-driven airplanes is presented. Particular emphasis is given to modeling the transmission of discrete tones through a fuselage element into a cavity, estimates for the mean and standard deviation of the acoustic power flow, the coupling between a non-homogeneous excitation and the fuselage vibration response, and the prediction of maximum interior noise levels. The model allows for convenient examination of the various roles of the excitation and fuselage structural characteristics on the fuselage vibration response and the interior noise levels, as is required for the design of model or prototype noise control validation tests.

Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands

NASA Astrophysics Data System (ADS)

Costanzi, Stefano; Tikhonova, Irina G.; Harden, T. Kendall; Jacobson, Kenneth A.

2009-11-01

Accurate in silico models for the quantitative prediction of the activity of G protein-coupled receptor (GPCR) ligands would greatly facilitate the process of drug discovery and development. Several methodologies have been developed based on the properties of the ligands, the direct study of the receptor-ligand interactions, or a combination of both approaches. Ligand-based three-dimensional quantitative structure-activity relationships (3D-QSAR) techniques, not requiring knowledge of the receptor structure, have been historically the first to be applied to the prediction of the activity of GPCR ligands. They are generally endowed with robustness and good ranking ability; however they are highly dependent on training sets. Structure-based techniques generally do not provide the level of accuracy necessary to yield meaningful rankings when applied to GPCR homology models. However, they are essentially independent from training sets and have a sufficient level of accuracy to allow an effective discrimination between binders and nonbinders, thus qualifying as viable lead discovery tools. The combination of ligand and structure-based methodologies in the form of receptor-based 3D-QSAR and ligand and structure-based consensus models results in robust and accurate quantitative predictions. The contribution of the structure-based component to these combined approaches is expected to become more substantial and effective in the future, as more sophisticated scoring functions are developed and more detailed structural information on GPCRs is gathered.

Taking a systems approach to ecological systems

USGS Publications Warehouse

Grace, James B.

2015-01-01

Increasingly, there is interest in a systems-level understanding of ecological problems, which requires the evaluation of more complex, causal hypotheses. In this issue of the Journal of Vegetation Science, Soliveres et al. use structural equation modeling to test a causal network hypothesis about how tree canopies affect understorey communities. Historical analysis suggests structural equation modeling has been under-utilized in ecology.

The power of structural modeling of sub-grid scales - application to astrophysical plasmas

NASA Astrophysics Data System (ADS)

Georgiev Vlaykov, Dimitar; Grete, Philipp

2015-08-01

In numerous astrophysical phenomena the dynamical range can span 10s of orders of magnitude. This implies more than billions of degrees-of-freedom and precludes direct numerical simulations from ever being a realistic possibility. A physical model is necessary to capture the unresolved physics occurring at the sub-grid scales (SGS).Structural modeling is a powerful concept which renders itself applicable to various physical systems. It stems from the idea of capturing the structure of the SGS terms in the evolution equations based on the scale-separation mechanism and independently of the underlying physics. It originates in the hydrodynamics field of large-eddy simulations. We apply it to the study of astrophysical MHD.Here, we present a non-linear SGS model for compressible MHD turbulence. The model is validated a priori at the tensorial, vectorial and scalar levels against of set of high-resolution simulations of stochastically forced homogeneous isotropic turbulence in a periodic box. The parameter space spans 2 decades in sonic Mach numbers (0.2 - 20) and approximately one decade in magnetic Mach number ~(1-8). This covers the super-Alfvenic sub-, trans-, and hyper-sonic regimes, with a range of plasma beta from 0.05 to 25. The Reynolds number is of the order of 103.At the tensor level, the model components correlate well with the turbulence ones, at the level of 0.8 and above. Vectorially, the alignment with the true SGS terms is encouraging with more than 50% of the model within 30° of the data. At the scalar level we look at the dynamics of the SGS energy and cross-helicity. The corresponding SGS flux terms have median correlations of ~0.8. Physically, the model represents well the two directions of the energy cascade.In comparison, traditional functional models exhibit poor local correlations with the data already at the scalar level. Vectorially, they are indifferent to the anisotropy of the SGS terms. They often struggle to represent the energy backscatter from small to large scales as well as the turbulent dynamo mechanism.Overall, the new model surpasses the traditional ones in all tests by a large margin.

The interface of protein structure, protein biophysics, and molecular evolution

PubMed Central

Liberles, David A; Teichmann, Sarah A; Bahar, Ivet; Bastolla, Ugo; Bloom, Jesse; Bornberg-Bauer, Erich; Colwell, Lucy J; de Koning, A P Jason; Dokholyan, Nikolay V; Echave, Julian; Elofsson, Arne; Gerloff, Dietlind L; Goldstein, Richard A; Grahnen, Johan A; Holder, Mark T; Lakner, Clemens; Lartillot, Nicholas; Lovell, Simon C; Naylor, Gavin; Perica, Tina; Pollock, David D; Pupko, Tal; Regan, Lynne; Roger, Andrew; Rubinstein, Nimrod; Shakhnovich, Eugene; Sjölander, Kimmen; Sunyaev, Shamil; Teufel, Ashley I; Thorne, Jeffrey L; Thornton, Joseph W; Weinreich, Daniel M; Whelan, Simon

2012-01-01

Abstract The interface of protein structural biology, protein biophysics, molecular evolution, and molecular population genetics forms the foundations for a mechanistic understanding of many aspects of protein biochemistry. Current efforts in interdisciplinary protein modeling are in their infancy and the state-of-the art of such models is described. Beyond the relationship between amino acid substitution and static protein structure, protein function, and corresponding organismal fitness, other considerations are also discussed. More complex mutational processes such as insertion and deletion and domain rearrangements and even circular permutations should be evaluated. The role of intrinsically disordered proteins is still controversial, but may be increasingly important to consider. Protein geometry and protein dynamics as a deviation from static considerations of protein structure are also important. Protein expression level is known to be a major determinant of evolutionary rate and several considerations including selection at the mRNA level and the role of interaction specificity are discussed. Lastly, the relationship between modeling and needed high-throughput experimental data as well as experimental examination of protein evolution using ancestral sequence resurrection and in vitro biochemistry are presented, towards an aim of ultimately generating better models for biological inference and prediction. PMID:22528593

An optimum organizational structure for a large earth-orbiting multidisciplinary space base. Ph.D. Thesis - Fla. State Univ., 1973

NASA Technical Reports Server (NTRS)

Ragusa, J. M.

1975-01-01

An optimum hypothetical organizational structure was studied for a large earth-orbiting, multidisciplinary research and applications space base manned by a crew of technologists. Because such a facility does not presently exist, in situ empirical testing was not possible. Study activity was, therefore, concerned with the identification of a desired organizational structural model rather than with the empirical testing of the model. The essential finding of this research was that a four-level project type total matrix model will optimize the efficiency and effectiveness of space base technologists.

Technological Adoption and Organizational Adaptation: Developing a Model for Human Resource Management in an International Business Environment.

ERIC Educational Resources Information Center

Gattiker, Urs E.

A model of technological training has two dimensions: level of cultural stability and employee's level of cognitive ability. Each dimension has two variables. The variables of cultural stability are (1) technological adoption and organizational adaptation and (2) structure of work and work processes. For cognitive ability, the variables are…

A Model of Creativity in Organizations: John Holland's Theory of Vocational Choice (1973) at Multiple Levels of Analysis

ERIC Educational Resources Information Center

Sharif, Rukhsar

2017-01-01

This conceptual paper serves to create a model of creativity and innovation at different organizational levels. It draws on John Holland's Theory of Vocational Choice (1973) as the basis for its structure by incorporating the six different personality types from his theory: conventional, enterprising, realistic, social, investigative, and…

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…

Speeded Old-New Recognition of Multidimensional Perceptual Stimuli: Modeling Performance at the Individual-Participant and Individual-Item Levels

ERIC Educational Resources Information Center

Nosofsky, Robert M.; Stanton, Roger D.

2006-01-01

Observers made speeded old-new recognition judgments of color stimuli embedded in a multidimensional similarity space. The paradigm used multiple lists but with the underlying similarity structures repeated across lists, to allow for quantitative modeling of the data at the individual-participant and individual-item levels. Correct rejection…

Foundational model of structural connectivity in the nervous system with a schema for wiring diagrams, connectome, and basic plan architecture

PubMed Central

Swanson, Larry W.; Bota, Mihail

2010-01-01

The nervous system is a biological computer integrating the body's reflex and voluntary environmental interactions (behavior) with a relatively constant internal state (homeostasis)—promoting survival of the individual and species. The wiring diagram of the nervous system's structural connectivity provides an obligatory foundational model for understanding functional localization at molecular, cellular, systems, and behavioral organization levels. This paper provides a high-level, downwardly extendible, conceptual framework—like a compass and map—for describing and exploring in neuroinformatics systems (such as our Brain Architecture Knowledge Management System) the structural architecture of the nervous system's basic wiring diagram. For this, the Foundational Model of Connectivity's universe of discourse is the structural architecture of nervous system connectivity in all animals at all resolutions, and the model includes two key elements—a set of basic principles and an internally consistent set of concepts (defined vocabulary of standard terms)—arranged in an explicitly defined schema (set of relationships between concepts) allowing automatic inferences. In addition, rules and procedures for creating and modifying the foundational model are considered. Controlled vocabularies with broad community support typically are managed by standing committees of experts that create and refine boundary conditions, and a set of rules that are available on the Web. PMID:21078980

[Stress in Medical Students: A Cross-Sectional Study on the Relevance of Attachment Style and Structural Integration].

PubMed

Bugaj, Till Johannes; Müksch, Christine; Ehrenthal, Johannes C; Köhl-Hackert, Nadja; Schauenburg, Henning; Huber, Julia; Schmid, Carolin; Erschens, Rebecca; Junne, Florian; Herzog, Wolfgang; Nikendei, Christoph

2016-02-01

From year one of studying medicine an increase of psychological stress is found. The relationship between the occurrence of this stress and attachment patterns or structural personality functions remains unclear. The present study aimed at investigating whether a relationship between the enduring personality variables, attachment style and level of structural integration of the personality, and acute stress experience at the beginning of medical students' studies exists. In this study, all students in the first semester of medicine were invited to participate in a study to identify stress factors via questionnaire (MBI-SS, PSQ, PHQ-9, GAD-7) in the WS 2013/2014. Simultaneously, the predominant attachment style (RQ-2) and structural abilities (OPD-SFK) were evaluated. The study included 293 students (return: 91.3%). Securely attached students experienced significantly less stress than insecurely attached students (p=0.019). Students with a high level of structural integration showed significantly less stress burden (p<0.001) and lower exhaustion- (p<0.001) and cynicism values (p<0.001), while showing a higher experience of self-efficacy (p<0.001). The influence of attachment behavior on stress experience is mediated by the level of the structural integration of the personality. Significant correlations exist between attachment style and the level of structural integration of the personality, and burnout risk as well as stress burden. The level of structural integration of the personality mediates the relationship between the attachment-related "model of self" and stress experience, i. e. a positive "model of self" can have a stress-protective effect when good structural abilities are present. Practical implication: An insecure attachment style and a low level of structural integration may be associated with higher stress experience when transitioning to study. The results suggest that the enduring personality variable attachment style, mediated by the level of structural integration of the personality, leads to higher stress and burnout experience. Affected students could be supported by early preventive measures enabling the sustainable preparation for this transitional period. Longitudinal prospective studies are needed to explore if the assumption is applicable that pre-existing vulnerabilities in school are exacerbated at this transitional stage. © Georg Thieme Verlag KG Stuttgart · New York.

Constructing inquiry: One school's journey to develop an inquiry-based school for teachers and students

NASA Astrophysics Data System (ADS)

Sisk-Hilton, Stephanie Lee

This study examines the two way relationship between an inquiry-based professional development model and teacher enactors. The two year study follows a group of teachers enacting the emergent Supporting Knowledge Integration for Inquiry Practice (SKIIP) professional development model. This study seeks to: (a) identify activity structures in the model that interact with teachers' underlying assumptions regarding professional development and inquiry learning; (b) explain key decision points during implementation in terms of these underlying assumptions; and (c) examine the impact of key activity structures on individual teachers' stated belief structures regarding inquiry learning. Linn's knowledge integration framework facilitates description and analysis of teacher development. Three sets of tensions emerge as themes that describe and constrain participants' interaction with and learning through the model. These are: learning from the group vs. learning on one's own; choosing and evaluating evidence based on impressions vs. specific criteria; and acquiring new knowledge vs. maintaining feelings of autonomy and efficacy. In each of these tensions, existing group goals and operating assumptions initially fell at one end of the tension, while the professional development goals and forms fell at the other. Changes to the model occurred as participants reacted to and negotiated these points of tension. As the group engaged in and modified the SKIIP model, they had repeated opportunities to articulate goals and to make connections between goals and model activity structures. Over time, decisions to modify the model took into consideration an increasingly complex set of underlying assumptions and goals. Teachers identified and sought to balance these tensions. This led to more complex and nuanced decision making, which reflected growing capacity to consider multiple goals in choosing activity structures to enact. The study identifies key activity structures that scaffolded this process for teachers, and which ultimately promoted knowledge integration at both the group and individual levels. This study is an "extreme case" which examines implementation of the SKIIP model under very favorable conditions. Lessons learned regarding appropriate levels of model responsiveness, likely areas of conflict between model form and teacher underlying assumptions, and activity structures that scaffold knowledge integration provide a starting point for future, larger scale implementation.

Development of an Aeroelastic Modeling Capability for Transient Nozzle Side Load Analysis

NASA Technical Reports Server (NTRS)

Wang, Ten-See; Zhao, Xiang; Zhang, Sijun; Chen, Yen-Sen

2013-01-01

Lateral nozzle forces are known to cause severe structural damage to any new rocket engine in development during test. While three-dimensional, transient, turbulent, chemically reacting computational fluid dynamics methodology has been demonstrated to capture major side load physics with rigid nozzles, hot-fire tests often show nozzle structure deformation during major side load events, leading to structural damages if structural strengthening measures were not taken. The modeling picture is incomplete without the capability to address the two-way responses between the structure and fluid. The objective of this study is to develop a coupled aeroelastic modeling capability by implementing the necessary structural dynamics component into an anchored computational fluid dynamics methodology. The computational fluid dynamics component is based on an unstructured-grid, pressure-based computational fluid dynamics formulation, while the computational structural dynamics component is developed in the framework of modal analysis. Transient aeroelastic nozzle startup analyses of the Block I Space Shuttle Main Engine at sea level were performed. The computed results from the aeroelastic nozzle modeling are presented.

Structure Prediction of the Second Extracellular Loop in G-Protein-Coupled Receptors

PubMed Central

Kmiecik, Sebastian; Jamroz, Michal; Kolinski, Michal

2014-01-01

G-protein-coupled receptors (GPCRs) play key roles in living organisms. Therefore, it is important to determine their functional structures. The second extracellular loop (ECL2) is a functionally important region of GPCRs, which poses significant challenge for computational structure prediction methods. In this work, we evaluated CABS, a well-established protein modeling tool for predicting ECL2 structure in 13 GPCRs. The ECL2s (with between 13 and 34 residues) are predicted in an environment of other extracellular loops being fully flexible and the transmembrane domain fixed in its x-ray conformation. The modeling procedure used theoretical predictions of ECL2 secondary structure and experimental constraints on disulfide bridges. Our approach yielded ensembles of low-energy conformers and the most populated conformers that contained models close to the available x-ray structures. The level of similarity between the predicted models and x-ray structures is comparable to that of other state-of-the-art computational methods. Our results extend other studies by including newly crystallized GPCRs. PMID:24896119

The Search for Efficiency in Arboreal Ray Tracing Applications

NASA Astrophysics Data System (ADS)

van Leeuwen, M.; Disney, M.; Chen, J. M.; Gomez-Dans, J.; Kelbe, D.; van Aardt, J. A.; Lewis, P.

2016-12-01

Forest structure significantly impacts a range of abiotic conditions, including humidity and the radiation regime, all of which affect the rate of net and gross primary productivity. Current forest productivity models typically consider abstract media to represent the transfer of radiation within the canopy. Examples include the representation forest structure via a layered canopy model, where leaf area and inclination angles are stratified with canopy depth, or as turbid media where leaves are randomly distributed within space or within confined geometric solids such as blocks, spheres or cones. While these abstract models are known to produce accurate estimates of primary productivity at the stand level, their limited geometric resolution restricts applicability at fine spatial scales, such as the cell, leaf or shoot levels, thereby not addressing the full potential of assimilation of data from laboratory and field measurements with that of remote sensing technology. Recent research efforts have explored the use of laser scanning to capture detailed tree morphology at millimeter accuracy. These data can subsequently be used to combine ray tracing with primary productivity models, providing an ability to explore trade-offs among different morphological traits or assimilate data from spatial scales, spanning the leaf- to the stand level. Ray tracing has a major advantage of allowing the most accurate structural description of the canopy, and can directly exploit new 3D structural measurements, e.g., from laser scanning. However, the biggest limitation of ray tracing models is their high computational cost, which currently limits their use for large-scale applications. In this talk, we explore ways to more efficiently exploit ray tracing simulations and capture this information in a readily computable form for future evaluation, thus potentially enabling large-scale first-principles forest growth modelling applications.

Health Promotion Behavior of Chinese International Students in Korea Including Acculturation Factors: A Structural Equation Model.

PubMed

Kim, Sun Jung; Yoo, Il Young

2016-03-01

The purpose of this study was to explain the health promotion behavior of Chinese international students in Korea using a structural equation model including acculturation factors. A survey using self-administered questionnaires was employed. Data were collected from 272 Chinese students who have resided in Korea for longer than 6 months. The data were analyzed using structural equation modeling. The p value of final model is .31. The fitness parameters of the final model such as goodness of fit index, adjusted goodness of fit index, normed fit index, non-normed fit index, and comparative fit index were more than .95. Root mean square of residual and root mean square error of approximation also met the criteria. Self-esteem, perceived health status, acculturative stress and acculturation level had direct effects on health promotion behavior of the participants and the model explained 30.0% of variance. The Chinese students in Korea with higher self-esteem, perceived health status, acculturation level, and lower acculturative stress reported higher health promotion behavior. The findings can be applied to develop health promotion strategies for this population. Copyright © 2016. Published by Elsevier B.V.

Probabilistic Methods for Structural Reliability and Risk

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2010-01-01

A probabilistic method is used to evaluate the structural reliability and risk of select metallic and composite structures. The method is a multiscale, multifunctional and it is based on the most elemental level. A multifactor interaction model is used to describe the material properties which are subsequently evaluated probabilistically. The metallic structure is a two rotor aircraft engine, while the composite structures consist of laminated plies (multiscale) and the properties of each ply are the multifunctional representation. The structural component is modeled by finite element. The solution method for structural responses is obtained by an updated simulation scheme. The results show that the risk for the two rotor engine is about 0.0001 and the composite built-up structure is also 0.0001.

Probabilistic Methods for Structural Reliability and Risk

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2008-01-01

A probabilistic method is used to evaluate the structural reliability and risk of select metallic and composite structures. The method is a multiscale, multifunctional and it is based on the most elemental level. A multi-factor interaction model is used to describe the material properties which are subsequently evaluated probabilistically. The metallic structure is a two rotor aircraft engine, while the composite structures consist of laminated plies (multiscale) and the properties of each ply are the multifunctional representation. The structural component is modeled by finite element. The solution method for structural responses is obtained by an updated simulation scheme. The results show that the risk for the two rotor engine is about 0.0001 and the composite built-up structure is also 0.0001.

Assessing the factor structures of the 55- and 22-item versions of the conformity to masculine norms inventory.

PubMed

Owen, Jesse

2011-03-01

The current study examined the psychometric properties of the abbreviated versions, 55- and 22-items, of the Conformity to Masculine Norms Inventory (CMNI). The authors tested the factor structure for the 11 subscales of the CMNI-55 and the global masculinity factor for the CMNI-55 and the CMNI-22. In a clinical sample of men and women (n=522), the results supported the 11-factor model. Furthermore, the factor structure was invariant for men and women. The higher order model, which tested the utility of the global masculine score, demonstrated marginal fit. The factor structures for the global masculinity score for the CMNI-22 demonstrated poor fit. Collectively, the results suggest that the CMNI-55 is better represented in a multidimensional construct. The subscales' alpha levels and factor loadings were, generally, within acceptable limits. Gender and ethnic mean level differences are also reported. © The Author(s) 2011

In silico biology of bone modelling and remodelling: adaptation.

PubMed

Gerhard, Friederike A; Webster, Duncan J; van Lenthe, G Harry; Müller, Ralph

2009-05-28

Modelling and remodelling are the processes by which bone adapts its shape and internal structure to external influences. However, the cellular mechanisms triggering osteoclastic resorption and osteoblastic formation are still unknown. In order to investigate current biological theories, in silico models can be applied. In the past, most of these models were based on the continuum assumption, but some questions related to bone adaptation can be addressed better by models incorporating the trabecular microstructure. In this paper, existing simulation models are reviewed and one of the microstructural models is extended to test the hypothesis that bone adaptation can be simulated without particular knowledge of the local strain distribution in the bone. Validation using an experimental murine loading model showed that this is possible. Furthermore, the experimental model revealed that bone formation cannot be attributed only to an increase in trabecular thickness but also to structural reorganization including the growth of new trabeculae. How these new trabeculae arise is still an unresolved issue and might be better addressed by incorporating other levels of hierarchy, especially the cellular level. The cellular level sheds light on the activity and interplay between the different cell types, leading to the effective change in the whole bone. For this reason, hierarchical multi-scale simulations might help in the future to better understand the biomathematical laws behind bone adaptation.

Three Big Hands-On Noncomputer Models for the Biology Classroom.

ERIC Educational Resources Information Center

Miller, James E.

1998-01-01

Proposes models for the lichen symbiosis, genomic, and plasmid DNA and fluid mosaic membrane structure. The models operate at the classroom level with the classroom becoming the cell in a DNA exercise with students as interactive components. (DDR)

Segmentation of kidney using C-V model and anatomy priors

NASA Astrophysics Data System (ADS)

Lu, Jinghua; Chen, Jie; Zhang, Juan; Yang, Wenjia

2007-12-01

This paper presents an approach for kidney segmentation on abdominal CT images as the first step of a virtual reality surgery system. Segmentation for medical images is often challenging because of the objects' complicated anatomical structures, various gray levels, and unclear edges. A coarse to fine approach has been applied in the kidney segmentation using Chan-Vese model (C-V model) and anatomy prior knowledge. In pre-processing stage, the candidate kidney regions are located. Then C-V model formulated by level set method is applied in these smaller ROI, which can reduce the calculation complexity to a certain extent. At last, after some mathematical morphology procedures, the specified kidney structures have been extracted interactively with prior knowledge. The satisfying results on abdominal CT series show that the proposed approach keeps all the advantages of C-V model and overcome its disadvantages.

Towards methodical modelling: Differences between the structure and output dynamics of multiple conceptual models

NASA Astrophysics Data System (ADS)

Knoben, Wouter; Woods, Ross; Freer, Jim

2016-04-01

Conceptual hydrologic models consist of a certain arrangement of spatial and temporal dynamics consisting of stores, fluxes and transformation functions, depending on the modeller's choices and intended use. They have the advantages of being computationally efficient, being relatively easy model structures to reconfigure and having relatively low input data demands. This makes them well-suited for large-scale and large-sample hydrology, where appropriately representing the dominant hydrologic functions of a catchment is a main concern. Given these requirements, the number of parameters in the model cannot be too high, to avoid equifinality and identifiability issues. This limits the number and level of complexity of dominant hydrologic processes the model can represent. Specific purposes and places thus require a specific model and this has led to an abundance of conceptual hydrologic models. No structured overview of these models exists and there is no clear method to select appropriate model structures for different catchments. This study is a first step towards creating an overview of the elements that make up conceptual models, which may later assist a modeller in finding an appropriate model structure for a given catchment. To this end, this study brings together over 30 past and present conceptual models. The reviewed model structures are simply different configurations of three basic model elements (stores, fluxes and transformation functions), depending on the hydrologic processes the models are intended to represent. Differences also exist in the inner workings of the stores, fluxes and transformations, i.e. the mathematical formulations that describe each model element's intended behaviour. We investigate the hypothesis that different model structures can produce similar behavioural simulations. This can clarify the overview of model elements by grouping elements which are similar, which can improve model structure selection.

Configurable product design considering the transition of multi-hierarchical models

NASA Astrophysics Data System (ADS)

Ren, Bin; Qiu, Lemiao; Zhang, Shuyou; Tan, Jianrong; Cheng, Jin

2013-03-01

The current research of configurable product design mainly focuses on how to convert a predefined set of components into a valid set of product structures. With the scale and complexity of configurable products increasing, the interdependencies between customer demands and product structures grow up as well. The result is that existing product structures fails to satisfy the individual customer requirements and hence product variants are needed. This paper is aimed to build a bridge between customer demands and product structures in order to make demand-driven fast response design feasible. First of all, multi-hierarchical models of configurable product design are established with customer demand model, technical requirement model and product structure model. Then, the transition of multi-hierarchical models among customer demand model, technical requirement model and product structure model is solved with fuzzy analytic hierarchy process (FAHP) and the algorithm of multi-level matching. Finally, optimal structure according to the customer demands is obtained with the calculation of Euclidean distance and similarity of some cases. In practice, the configuration design of a clamping unit of injection molding machine successfully performs an optimal search strategy for the product variants with reasonable satisfaction to individual customer demands. The proposed method can automatically generate a configuration design with better alternatives for each product structures, and shorten the time of finding the configuration of a product.

Cybermaterials: materials by design and accelerated insertion of materials

NASA Astrophysics Data System (ADS)

Xiong, Wei; Olson, Gregory B.

2016-02-01

Cybermaterials innovation entails an integration of Materials by Design and accelerated insertion of materials (AIM), which transfers studio ideation into industrial manufacturing. By assembling a hierarchical architecture of integrated computational materials design (ICMD) based on materials genomic fundamental databases, the ICMD mechanistic design models accelerate innovation. We here review progress in the development of linkage models of the process-structure-property-performance paradigm, as well as related design accelerating tools. Extending the materials development capability based on phase-level structural control requires more fundamental investment at the level of the Materials Genome, with focus on improving applicable parametric design models and constructing high-quality databases. Future opportunities in materials genomic research serving both Materials by Design and AIM are addressed.

Correlation of ground tests and analyses of a dynamically scaled Space Station model configuration

NASA Technical Reports Server (NTRS)

Javeed, Mehzad; Edighoffer, Harold H.; Mcgowan, Paul E.

1993-01-01

Verification of analytical models through correlation with ground test results of a complex space truss structure is demonstrated. A multi-component, dynamically scaled space station model configuration is the focus structure for this work. Previously established test/analysis correlation procedures are used to develop improved component analytical models. Integrated system analytical models, consisting of updated component analytical models, are compared with modal test results to establish the accuracy of system-level dynamic predictions. Design sensitivity model updating methods are shown to be effective for providing improved component analytical models. Also, the effects of component model accuracy and interface modeling fidelity on the accuracy of integrated model predictions is examined.

Inoculation density and nutrient level determine the formation of mushroom-shaped structures in Pseudomonas aeruginosa biofilms

NASA Astrophysics Data System (ADS)

Ghanbari, Azadeh; Dehghany, Jaber; Schwebs, Timo; Müsken, Mathias; Häussler, Susanne; Meyer-Hermann, Michael

2016-09-01

Pseudomonas aeruginosa often colonises immunocompromised patients and the lungs of cystic fibrosis patients. It exhibits resistance to many antibiotics by forming biofilms, which makes it hard to eliminate. P. aeruginosa biofilms form mushroom-shaped structures under certain circumstances. Bacterial motility and the environment affect the eventual mushroom morphology. This study provides an agent-based model for the bacterial dynamics and interactions influencing bacterial biofilm shape. Cell motility in the model relies on recently published experimental data. Our simulations show colony formation by immotile cells. Motile cells escape from a single colony by nutrient chemotaxis and hence no mushroom shape develops. A high number density of non-motile colonies leads to migration of motile cells onto the top of the colonies and formation of mushroom-shaped structures. This model proposes that the formation of mushroom-shaped structures can be predicted by parameters at the time of bacteria inoculation. Depending on nutrient levels and the initial number density of stalks, mushroom-shaped structures only form in a restricted regime. This opens the possibility of early manipulation of spatial pattern formation in bacterial colonies, using environmental factors.

Energy Finite Element Analysis Developments for Vibration Analysis of Composite Aircraft Structures

NASA Technical Reports Server (NTRS)

Vlahopoulos, Nickolas; Schiller, Noah H.

2011-01-01

The Energy Finite Element Analysis (EFEA) has been utilized successfully for modeling complex structural-acoustic systems with isotropic structural material properties. In this paper, a formulation for modeling structures made out of composite materials is presented. An approach based on spectral finite element analysis is utilized first for developing the equivalent material properties for the composite material. These equivalent properties are employed in the EFEA governing differential equations for representing the composite materials and deriving the element level matrices. The power transmission characteristics at connections between members made out of non-isotropic composite material are considered for deriving suitable power transmission coefficients at junctions of interconnected members. These coefficients are utilized for computing the joint matrix that is needed to assemble the global system of EFEA equations. The global system of EFEA equations is solved numerically and the vibration levels within the entire system can be computed. The new EFEA formulation for modeling composite laminate structures is validated through comparison to test data collected from a representative composite aircraft fuselage that is made out of a composite outer shell and composite frames and stiffeners. NASA Langley constructed the composite cylinder and conducted the test measurements utilized in this work.

Tensegrity I. Cell structure and hierarchical systems biology

NASA Technical Reports Server (NTRS)

Ingber, Donald E.

2003-01-01

In 1993, a Commentary in this journal described how a simple mechanical model of cell structure based on tensegrity architecture can help to explain how cell shape, movement and cytoskeletal mechanics are controlled, as well as how cells sense and respond to mechanical forces (J. Cell Sci. 104, 613-627). The cellular tensegrity model can now be revisited and placed in context of new advances in our understanding of cell structure, biological networks and mechanoregulation that have been made over the past decade. Recent work provides strong evidence to support the use of tensegrity by cells, and mathematical formulations of the model predict many aspects of cell behavior. In addition, development of the tensegrity theory and its translation into mathematical terms are beginning to allow us to define the relationship between mechanics and biochemistry at the molecular level and to attack the larger problem of biological complexity. Part I of this two-part article covers the evidence for cellular tensegrity at the molecular level and describes how this building system may provide a structural basis for the hierarchical organization of living systems--from molecule to organism. Part II, which focuses on how these structural networks influence information processing networks, appears in the next issue.

Inoculation density and nutrient level determine the formation of mushroom-shaped structures in Pseudomonas aeruginosa biofilms.

PubMed

Ghanbari, Azadeh; Dehghany, Jaber; Schwebs, Timo; Müsken, Mathias; Häussler, Susanne; Meyer-Hermann, Michael

2016-09-09

Pseudomonas aeruginosa often colonises immunocompromised patients and the lungs of cystic fibrosis patients. It exhibits resistance to many antibiotics by forming biofilms, which makes it hard to eliminate. P. aeruginosa biofilms form mushroom-shaped structures under certain circumstances. Bacterial motility and the environment affect the eventual mushroom morphology. This study provides an agent-based model for the bacterial dynamics and interactions influencing bacterial biofilm shape. Cell motility in the model relies on recently published experimental data. Our simulations show colony formation by immotile cells. Motile cells escape from a single colony by nutrient chemotaxis and hence no mushroom shape develops. A high number density of non-motile colonies leads to migration of motile cells onto the top of the colonies and formation of mushroom-shaped structures. This model proposes that the formation of mushroom-shaped structures can be predicted by parameters at the time of bacteria inoculation. Depending on nutrient levels and the initial number density of stalks, mushroom-shaped structures only form in a restricted regime. This opens the possibility of early manipulation of spatial pattern formation in bacterial colonies, using environmental factors.

Two-bead polarizable water models combined with a two-bead multipole force field (TMFF) for coarse-grained simulation of proteins.

PubMed

Li, Min; Zhang, John Z H

2017-03-08

The development of polarizable water models at coarse-grained (CG) levels is of much importance to CG molecular dynamics simulations of large biomolecular systems. In this work, we combined the newly developed two-bead multipole force field (TMFF) for proteins with the two-bead polarizable water models to carry out CG molecular dynamics simulations for benchmark proteins. In our simulations, two different two-bead polarizable water models are employed, the RTPW model representing five water molecules by Riniker et al. and the LTPW model representing four water molecules. The LTPW model is developed in this study based on the Martini three-bead polarizable water model. Our simulation results showed that the combination of TMFF with the LTPW model significantly stabilizes the protein's native structure in CG simulations, while the use of the RTPW model gives better agreement with all-atom simulations in predicting the residue-level fluctuation dynamics. Overall, the TMFF coupled with the two-bead polarizable water models enables one to perform an efficient and reliable CG dynamics study of the structural and functional properties of large biomolecules.

Multi-Level Anomaly Detection on Time-Varying Graph Data

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

Bridges, Robert A; Collins, John P; Ferragut, Erik M

This work presents a novel modeling and analysis framework for graph sequences which addresses the challenge of detecting and contextualizing anomalies in labelled, streaming graph data. We introduce a generalization of the BTER model of Seshadhri et al. by adding flexibility to community structure, and use this model to perform multi-scale graph anomaly detection. Specifically, probability models describing coarse subgraphs are built by aggregating probabilities at finer levels, and these closely related hierarchical models simultaneously detect deviations from expectation. This technique provides insight into a graph's structure and internal context that may shed light on a detected event. Additionally, thismore » multi-scale analysis facilitates intuitive visualizations by allowing users to narrow focus from an anomalous graph to particular subgraphs or nodes causing the anomaly. For evaluation, two hierarchical anomaly detectors are tested against a baseline Gaussian method on a series of sampled graphs. We demonstrate that our graph statistics-based approach outperforms both a distribution-based detector and the baseline in a labeled setting with community structure, and it accurately detects anomalies in synthetic and real-world datasets at the node, subgraph, and graph levels. To illustrate the accessibility of information made possible via this technique, the anomaly detector and an associated interactive visualization tool are tested on NCAA football data, where teams and conferences that moved within the league are identified with perfect recall, and precision greater than 0.786.« less

From single fiber to macro-level mechanics: A structural finite-element model for elastomeric fibrous biomaterials.

PubMed

D'Amore, Antonio; Amoroso, Nicholas; Gottardi, Riccardo; Hobson, Christopher; Carruthers, Christopher; Watkins, Simon; Wagner, William R; Sacks, Michael S

2014-11-01

In the present work, we demonstrate that the mesoscopic in-plane mechanical behavior of membrane elastomeric scaffolds can be simulated by replication of actual quantified fibrous geometries. Elastomeric electrospun polyurethane (ES-PEUU) scaffolds, with and without particulate inclusions, were utilized. Simulations were developed from experimentally-derived fiber network geometries, based on a range of scaffold isotropic and anisotropic behaviors. These were chosen to evaluate the effects on macro-mechanics based on measurable geometric parameters such as fiber intersections, connectivity, orientation, and diameter. Simulations were conducted with only the fiber material model parameters adjusted to match the macro-level mechanical test data. Fiber model validation was performed at the microscopic level by individual fiber mechanical tests using AFM. Results demonstrated very good agreement to the experimental data, and revealed the formation of extended preferential fiber orientations spanning the entire model space. We speculate that these emergent structures may be responsible for the tissue-like macroscale behaviors observed in electrospun scaffolds. To conclude, the modeling approach has implications for (1) gaining insight on the intricate relationship between fabrication variables, structure, and mechanics to manufacture more functional devices/materials, (2) elucidating the effects of cell or particulate inclusions on global construct mechanics, and (3) fabricating better performing tissue surrogates that could recapitulate native tissue mechanics. Copyright © 2014 Elsevier Ltd. All rights reserved.

Modeling Syntax for Parsing and Translation

DTIC Science & Technology

2003-12-15

20 CHAPTER 2. MONOLINGUAL PROBABILISTIC PARSING a the D cat snake D S O chased S O ran SS Mary O Figure 2.1: Part of a dictionary . the cat S chased S O...along with their training algorithms: a monolingual gen- erative model of sentence structure, and a model of the relationship between the structure of a...tasks of monolingual parsing and word-level bilingual corpus alignment, they are demonstrated in two additional applications. First, a new statistical

Information Object Definition–based Unified Modeling Language Representation of DICOM Structured Reporting

PubMed Central

Tirado-Ramos, Alfredo; Hu, Jingkun; Lee, K.P.

2002-01-01

Supplement 23 to DICOM (Digital Imaging and Communications for Medicine), Structured Reporting, is a specification that supports a semantically rich representation of image and waveform content, enabling experts to share image and related patient information. DICOM SR supports the representation of textual and coded data linked to images and waveforms. Nevertheless, the medical information technology community needs models that work as bridges between the DICOM relational model and open object-oriented technologies. The authors assert that representations of the DICOM Structured Reporting standard, using object-oriented modeling languages such as the Unified Modeling Language, can provide a high-level reference view of the semantically rich framework of DICOM and its complex structures. They have produced an object-oriented model to represent the DICOM SR standard and have derived XML-exchangeable representations of this model using World Wide Web Consortium specifications. They expect the model to benefit developers and system architects who are interested in developing applications that are compliant with the DICOM SR specification. PMID:11751804

An analytical coarse-graining method which preserves the free energy, structural correlations, and thermodynamic state of polymer melts from the atomistic to the mesoscale.

PubMed

McCarty, J; Clark, A J; Copperman, J; Guenza, M G

2014-05-28

Structural and thermodynamic consistency of coarse-graining models across multiple length scales is essential for the predictive role of multi-scale modeling and molecular dynamic simulations that use mesoscale descriptions. Our approach is a coarse-grained model based on integral equation theory, which can represent polymer chains at variable levels of chemical details. The model is analytical and depends on molecular and thermodynamic parameters of the system under study, as well as on the direct correlation function in the k → 0 limit, c0. A numerical solution to the PRISM integral equations is used to determine c0, by adjusting the value of the effective hard sphere diameter, dHS, to agree with the predicted equation of state. This single quantity parameterizes the coarse-grained potential, which is used to perform mesoscale simulations that are directly compared with atomistic-level simulations of the same system. We test our coarse-graining formalism by comparing structural correlations, isothermal compressibility, equation of state, Helmholtz and Gibbs free energies, and potential energy and entropy using both united atom and coarse-grained descriptions. We find quantitative agreement between the analytical formalism for the thermodynamic properties, and the results of Molecular Dynamics simulations, independent of the chosen level of representation. In the mesoscale description, the potential energy of the soft-particle interaction becomes a free energy in the coarse-grained coordinates which preserves the excess free energy from an ideal gas across all levels of description. The structural consistency between the united-atom and mesoscale descriptions means the relative entropy between descriptions has been minimized without any variational optimization parameters. The approach is general and applicable to any polymeric system in different thermodynamic conditions.

The factor structure of the Values in Action Inventory of Strengths (VIA-IS): An item-level exploratory structural equation modeling (ESEM) bifactor analysis.

PubMed

Ng, Vincent; Cao, Mengyang; Marsh, Herbert W; Tay, Louis; Seligman, Martin E P

2017-08-01

The factor structure of the Values in Action Inventory of Strengths (VIA-IS; Peterson & Seligman, 2004) has not been well established as a result of methodological challenges primarily attributable to a global positivity factor, item cross-loading across character strengths, and questions concerning the unidimensionality of the scales assessing character strengths. We sought to overcome these methodological challenges by applying exploratory structural equation modeling (ESEM) at the item level using a bifactor analytic approach to a large sample of 447,573 participants who completed the VIA-IS with all 240 character strengths items and a reduced set of 107 unidimensional character strength items. It was found that a 6-factor bifactor structure generally held for the reduced set of unidimensional character strength items; these dimensions were justice, temperance, courage, wisdom, transcendence, humanity, and an overarching general factor that is best described as dispositional positivity. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Coupled Analysis of In Vitro and Histology Tissue Samples to Quantify Structure-Function Relationship

PubMed Central

Acar, Evrim; Plopper, George E.; Yener, Bülent

2012-01-01

The structure/function relationship is fundamental to our understanding of biological systems at all levels, and drives most, if not all, techniques for detecting, diagnosing, and treating disease. However, at the tissue level of biological complexity we encounter a gap in the structure/function relationship: having accumulated an extraordinary amount of detailed information about biological tissues at the cellular and subcellular level, we cannot assemble it in a way that explains the correspondingly complex biological functions these structures perform. To help close this information gap we define here several quantitative temperospatial features that link tissue structure to its corresponding biological function. Both histological images of human tissue samples and fluorescence images of three-dimensional cultures of human cells are used to compare the accuracy of in vitro culture models with their corresponding human tissues. To the best of our knowledge, there is no prior work on a quantitative comparison of histology and in vitro samples. Features are calculated from graph theoretical representations of tissue structures and the data are analyzed in the form of matrices and higher-order tensors using matrix and tensor factorization methods, with a goal of differentiating between cancerous and healthy states of brain, breast, and bone tissues. We also show that our techniques can differentiate between the structural organization of native tissues and their corresponding in vitro engineered cell culture models. PMID:22479315

Ultra small angle x-ray scattering in complex mixtures of triacylglycerols

NASA Astrophysics Data System (ADS)

Peyronel, Fernanda; Quinn, Bonnie; Marangoni, Alejandro G.; Pink, David A.

2014-11-01

Ultra-small angle x-ray scattering (USAXS) has been used to elucidate, in situ, the aggregation structure of unsheared model edible oils. Each system comprised one or two solid lipids and a combination of liquid lipids. The 3D nano- to micro-structures of each system were characterized. The length scale investigated, using the Bonse-Hart camera at beamline ID-15D at the Advanced Photon Source, ANL, ranged from 300 Å-10 µm. Using the Unified Fit model, level-1 analysis showed that the scatterers were 2D objects with either a smooth, a rough, or a diffuse surface. These 2D objects had an average radius of gyration Rg1 between 200-1500 Å. Level-2 analysis displayed a slope between -1 and -2. Use of the Guinier-Porod model gave s ≈ 1 thus showing that it was cylinders (TAGwoods) aggregating with fractal dimension 1 ≤ D2 ≤ 2. D2 = 1 is consistent with 1D structures formed from TAGwoods, while D2 = 2 implies that the TAGwoods had formed structures characteristic of diffusion or reaction limited cluster-cluster aggregation (DLCA/RLCA). These aggregates exhibited radii of gyration, Rg2, between 2500 and 6500 Å. Level-3 analyses showed diffuse surfaces, for most of the systems. These interpretations are in accord with theoretical models which studied crystalline nano-platelets (CNPs) coated with nano-scale layers arising from phase separation at the CNP surfaces. These layers could be due to either liquid-liquid phase separation with the CNPs coated, uniformly or non-uniformly, by a diffuse layer of TAGs, or solid-liquid phase separation with the CNPs coated by a rough layer of crystallites. A fundamental understanding of the self-organizing structures arising in these systems helps advance the characterization of fat crystal networks from nanometres to micrometres. This research can be used to design novel fat structures that use healthier fats via nano- and meso-scale structural engineering.

Micro-mechanical model for the tension-stabilized enzymatic degradation of collagen tissues

NASA Astrophysics Data System (ADS)

Nguyen, Thao; Ruberti, Jeffery

We present a study of how the collagen fiber structure influences the enzymatic degradation of collagen tissues. Experiments of collagen fibrils and tissues show that mechanical tension can slow and halt enzymatic degradation. Tissue-level experiments also show that degradation rate is minimum at a stretch level coincident with the onset of strain-stiffening in the stress response. To understand these phenomena, we developed a micro-mechanical model of a fibrous collagen tissue undergoing enzymatic degradation. Collagen fibers are described as sinusoidal elastica beams, and the tissue is described as a distribution of fibers. We assumed that the degradation reaction is inhibited by the axial strain energy of the crimped collagen fibers. The degradation rate law was calibrated to experiments on isolated single fibrils from bovine sclera. The fiber crimp and properties were fit to uniaxial tension tests of tissue strips. The fibril-level kinetic and tissue-level structural parameters were used to predict tissue-level degradation-induced creep rate under a constant applied force. We showed that we could accurately predict the degradation-induce creep rate of the pericardium and cornea once we accounted for differences in the fiber crimp structure and properties.

Vibration Penalty Estimates for Indoor Annoyance Caused by Sonic Boom

NASA Technical Reports Server (NTRS)

Rathsam, Jonathan; Klos, Jacob

2016-01-01

Commercial supersonic flight is currently forbidden over land because sonic booms have historically caused unacceptable annoyance levels in overflown communities. NASA is providing data and expertise to noise regulators as they consider relaxing the ban for future quiet supersonic aircraft. One key objective is a predictive model for indoor annoyance based on factors such as noise and indoor vibration levels. The current study quantified the increment in indoor sonic boom annoyance when sonic booms can be felt directly through structural vibrations in addition to being heard. A shaker mounted below each chair in the sonic boom simulator emulated vibrations transmitting through the structure to that chair. The vibration amplitudes were determined from numeric models of a large range of residential structures excited by the same sonic boom waveforms used in the experiment. The analysis yielded vibration penalties, which are the increments in sound level needed to increase annoyance as much as the vibration does. For sonic booms at acoustic levels from 75 to 84 dB Perceived Level, vibration signals with lower amplitudes (+1 sigma) yielded penalties from 0 to 5 dB, and vibration signals with higher amplitudes (+3 sigma) yielded penalties from 6 to 10 dB.

Examining the Moderating Effect of Individual-Level Cultural Values on Users' Acceptance of E-Learning in Developing Countries: A Structural Equation Modeling of an Extended Technology Acceptance Model

ERIC Educational Resources Information Center

Tarhini, Ali; Hone, Kate; Liu, Xiaohui; Tarhini, Takwa

2017-01-01

In this study, we examine the effects of individual-level culture on the adoption and acceptance of e-learning tools by students in Lebanon using a theoretical framework based on the Technology Acceptance Model (TAM). To overcome possible limitations of using TAM in developing countries, we extend TAM to include "subjective norms" (SN)…

Characterization of proton exchange membrane materials for fuel cells by solid state nuclear magnetic resonance

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

Kong, Zueqian

2010-01-01

Solid-state nuclear magnetic resonance (NMR) has been used to explore the nanometer-scale structure of Nafion, the widely used fuel cell membrane, and its composites. We have shown that solid-state NMR can characterize chemical structure and composition, domain size and morphology, internuclear distances, molecular dynamics, etc. The newly-developed water channel model of Nafion has been confirmed, and important characteristic length-scales established. Nafion-based organic and inorganic composites with special properties have also been characterized and their structures elucidated. The morphology of Nafion varies with hydration level, and is reflected in the changes in surface-to-volume (S/V) ratio of the polymer obtained by small-anglemore » X-ray scattering (SAXS). The S/V ratios of different Nafion models have been evaluated numerically. It has been found that only the water channel model gives the measured S/V ratios in the normal hydration range of a working fuel cell, while dispersed water molecules and polymer ribbons account for the structures at low and high hydration levels, respectively.« less

A united event grand canonical Monte Carlo study of partially doped polyaniline

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

Byshkin, M. S., E-mail: mbyshkin@unisa.it, E-mail: gmilano@unisa.it; Correa, A.; Buonocore, F.

2013-12-28

A Grand Canonical Monte Carlo scheme, based on united events combining protonation/deprotonation and insertion/deletion of HCl molecules is proposed for the generation of polyaniline structures at intermediate doping levels between 0% (PANI EB) and 100% (PANI ES). A procedure based on this scheme and subsequent structure relaxations using molecular dynamics is described and validated. Using the proposed scheme and the corresponding procedure, atomistic models of amorphous PANI-HCl structures were generated and studied at different doping levels. Density, structure factors, and solubility parameters were calculated. Their values agree well with available experimental data. The interactions of HCl with PANI have beenmore » studied and distribution of their energies has been analyzed. The procedure has also been extended to the generation of PANI models including adsorbed water and the effect of inclusion of water molecules on PANI properties has also been modeled and discussed. The protocol described here is general and the proposed United Event Grand Canonical Monte Carlo scheme can be easily extended to similar polymeric materials used in gas sensing and to other systems involving adsorption and chemical reactions steps.« less

Dynamics of leaf gas exchange, xylem and phloem transport, water potential and carbohydrate concentration in a realistic 3-D model tree crown.

PubMed

Nikinmaa, Eero; Sievänen, Risto; Hölttä, Teemu

2014-09-01

Tree models simulate productivity using general gas exchange responses and structural relationships, but they rarely check whether leaf gas exchange and resulting water and assimilate transport and driving pressure gradients remain within acceptable physical boundaries. This study presents an implementation of the cohesion-tension theory of xylem transport and the Münch hypothesis of phloem transport in a realistic 3-D tree structure and assesses the gas exchange and transport dynamics. A mechanistic model of xylem and phloem transport was used, together with a tested leaf assimilation and transpiration model in a realistic tree architecture to simulate leaf gas exchange and water and carbohydrate transport within an 8-year-old Scots pine tree. The model solved the dynamics of the amounts of water and sucrose solute in the xylem, cambium and phloem using a fine-grained mesh with a system of coupled ordinary differential equations. The simulations predicted the observed patterns of pressure gradients and sugar concentration. Diurnal variation of environmental conditions influenced tree-level gradients in turgor pressure and sugar concentration, which are important drivers of carbon allocation. The results and between-shoot variation were sensitive to structural and functional parameters such as tree-level scaling of conduit size and phloem unloading. Linking whole-tree-level water and assimilate transport, gas exchange and sink activity opens a new avenue for plant studies, as features that are difficult to measure can be studied dynamically with the model. Tree-level responses to local and external conditions can be tested, thus making the approach described here a good test-bench for studies of whole-tree physiology.

Structural invariance of multiple intelligences, based on the level of execution.

PubMed

Almeida, Leandro S; Prieto, María Dolores; Ferreira, Arístides; Ferrando, Mercedes; Ferrandiz, Carmen; Bermejo, Rosario; Hernández, Daniel

2011-11-01

The independence of multiple intelligences (MI) of Gardner's theory has been debated since its conception. This article examines whether the one- factor structure of the MI theory tested in previous studies is invariant for low and high ability students. Two hundred ninety-four children (aged 5 to 7) participated in this study. A set of Gardner's Multiple Intelligence assessment tasks based on the Spectrum Project was used. To analyze the invariance of a general dimension of intelligence, the different models of behaviours were studied in samples of participants with different performance on the Spectrum Project tasks with Multi-Group Confirmatory Factor Analysis (MGCFA). Results suggest an absence of structural invariance in Gardner's tasks. Exploratory analyses suggest a three-factor structure for individuals with higher performance levels and a two-factor structure for individuals with lower performance levels.

System identification of the JPL micro-precision interferometer truss - Test-analysis reconciliation

NASA Technical Reports Server (NTRS)

Red-Horse, J. R.; Marek, E. L.; Levine-West, M.

1993-01-01

The JPL Micro-Precision Interferometer (MPI) is a testbed for studying the use of control-structure interaction technology in the design of space-based interferometers. A layered control architecture will be employed to regulate the interferometer optical system to tolerances in the nanometer range. An important aspect of designing and implementing the control schemes for such a system is the need for high fidelity, test-verified analytical structural models. This paper focuses on one aspect of the effort to produce such a model for the MPI structure, test-analysis model reconciliation. Pretest analysis, modal testing, and model refinement results are summarized for a series of tests at both the component and full system levels.

Design of Accelerator Online Simulator Server Using Structured Data

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

Shen, Guobao; /Brookhaven; Chu, Chungming

2012-07-06

Model based control plays an important role for a modern accelerator during beam commissioning, beam study, and even daily operation. With a realistic model, beam behaviour can be predicted and therefore effectively controlled. The approach used by most current high level application environments is to use a built-in simulation engine and feed a realistic model into that simulation engine. Instead of this traditional monolithic structure, a new approach using a client-server architecture is under development. An on-line simulator server is accessed via network accessible structured data. With this approach, a user can easily access multiple simulation codes. This paper describesmore » the design, implementation, and current status of PVData, which defines the structured data, and PVAccess, which provides network access to the structured data.« less

Bayesian Model Comparison for the Order Restricted RC Association Model

ERIC Educational Resources Information Center

Iliopoulos, G.; Kateri, M.; Ntzoufras, I.

2009-01-01

Association models constitute an attractive alternative to the usual log-linear models for modeling the dependence between classification variables. They impose special structure on the underlying association by assigning scores on the levels of each classification variable, which can be fixed or parametric. Under the general row-column (RC)…

CONSTRUCTING, PERTURBATION ANALYSIIS AND TESTING OF A MULTI-HABITAT PERIODIC MATRIX POPULATION MODEL

EPA Science Inventory

We present a matrix model that explicitly incorporates spatial habitat structure and seasonality and discuss preliminary results from a landscape level experimental test. Ecological risk to populations is often modeled without explicit treatment of spatially or temporally distri...

Assessment of Galileo modal test results for mathematical model verification

NASA Technical Reports Server (NTRS)

Trubert, M.

1984-01-01

The modal test program for the Galileo Spacecraft was completed at the Jet Propulsion Laboratory in the summer of 1983. The multiple sine dwell method was used for the baseline test. The Galileo Spacecraft is a rather complex 2433 kg structure made of a central core on which seven major appendages representing 30 percent of the total mass are attached, resulting in a high modal density structure. The test revealed a strong nonlinearity in several major modes. This nonlinearity discovered in the course of the test necessitated running additional tests at the unusually high response levels of up to about 21 g. The high levels of response were required to obtain a model verification valid at the level of loads for which the spacecraft was designed. Because of the high modal density and the nonlinearity, correlation between the dynamic mathematical model and the test results becomes a difficult task. Significant changes in the pre-test analytical model are necessary to establish confidence in the upgraded analytical model used for the final load verification. This verification, using a test verified model, is required by NASA to fly the Galileo Spacecraft on the Shuttle/Centaur launch vehicle in 1986.

Structure-mechanics relationships of collagen fibrils in the osteogenesis imperfecta mouse model.

PubMed

Andriotis, O G; Chang, S W; Vanleene, M; Howarth, P H; Davies, D E; Shefelbine, S J; Buehler, M J; Thurner, P J

2015-10-06

The collagen molecule, which is the building block of collagen fibrils, is a triple helix of two α1(I) chains and one α2(I) chain. However, in the severe mouse model of osteogenesis imperfecta (OIM), deletion of the COL1A2 gene results in the substitution of the α2(I) chain by one α1(I) chain. As this substitution severely impairs the structure and mechanics of collagen-rich tissues at the tissue and organ level, the main aim of this study was to investigate how the structure and mechanics are altered in OIM collagen fibrils. Comparing results from atomic force microscopy imaging and cantilever-based nanoindentation on collagen fibrils from OIM and wild-type (WT) animals, we found a 33% lower indentation modulus in OIM when air-dried (bound water present) and an almost fivefold higher indentation modulus in OIM collagen fibrils when fully hydrated (bound and unbound water present) in phosphate-buffered saline solution (PBS) compared with WT collagen fibrils. These mechanical changes were accompanied by an impaired swelling upon hydration within PBS. Our experimental and atomistic simulation results show how the structure and mechanics are altered at the individual collagen fibril level as a result of collagen gene mutation in OIM. We envisage that the combination of experimental and modelling approaches could allow mechanical phenotyping at the collagen fibril level of virtually any alteration of collagen structure or chemistry. © 2015 The Authors.

Can Student Nurse Critical Thinking Be Predicted from Perceptions of Structural Empowerment within the Undergraduate, Pre-Licensure Learning Environment?

ERIC Educational Resources Information Center

Caswell-Moore, Shelley P.

2013-01-01

The purpose of this study was to test a model using Rosabeth Kanter's theory (1977; 1993) of structural empowerment to determine if this model can predict student nurses' level of critical thinking. Major goals of nursing education are to cultivate graduates who can think critically with a keen sense of clinical judgment, and who can perform…

Learning the Cell Structures with Three-Dimensional Models: Students' Achievement by Methods, Type of School and Questions' Cognitive Level

ERIC Educational Resources Information Center

Lazarowitz, Reuven; Naim, Raphael

2014-01-01

The cell topic was taught to 9th-grade students in three modes of instruction: (a) students "hands-on," who constructed three-dimensional cell organelles and macromolecules during the learning process; (b) teacher demonstration of the three-dimensional model of the cell structures; and (c) teaching the cell topic with the regular…

Impact of sea level rise on tide gate function.

PubMed

Walsh, Sean; Miskewitz, Robert

2013-01-01

Sea level rise resulting from climate change and land subsidence is expected to severely impact the duration and associated damage resulting from flooding events in tidal communities. These communities must continuously invest resources for the maintenance of existing structures and installation of new flood prevention infrastructure. Tide gates are a common flood prevention structure for low-lying communities in the tidal zone. Tide gates close during incoming tides to prevent inundation from downstream water propagating inland and open during outgoing tides to drain upland areas. Higher downstream mean sea level elevations reduce the effectiveness of tide gates by impacting the hydraulics of the system. This project developed a HEC-RAS and HEC-HMS model of an existing tide gate structure and its upland drainage area in the New Jersey Meadowlands to simulate the impact of rising mean sea level elevations on the tide gate's ability to prevent upstream flooding. Model predictions indicate that sea level rise will reduce the tide gate effectiveness resulting in longer lasting and deeper flood events. The results indicate that there is a critical point in the sea level elevation for this local area, beyond which flooding scenarios become dramatically worse and would have a significantly negative impact on the standard of living and ability to do business in one of the most densely populated areas of America.

A temporal and spatial analysis of ground-water levels for effective monitoring in Huron County, Michigan

USGS Publications Warehouse

Holtschlag, David J.; Sweat, M.J.

1999-01-01

Quarterly water-level measurements were analyzed to assess the effectiveness of a monitoring network of 26 wells in Huron County, Michigan. Trends were identified as constant levels and autoregressive components were computed at all wells on the basis of data collected from 1993 to 1997, using structural time series analysis. Fixed seasonal components were identified at 22 wells and outliers were identified at 23 wells. The 95- percent confidence intervals were forecast for water-levels during the first and second quarters of 1998. Intervals in the first quarter were consistent with 92.3 percent of the measured values. In the second quarter, measured values were within the forecast intervals only 65.4 percent of the time. Unusually low precipitation during the second quarter is thought to have contributed to the reduced reliability of the second-quarter forecasts. Spatial interrelations among wells were investigated on the basis of the autoregressive components, which were filtered to create a set of innovation sequences that were temporally uncorrelated. The empirical covariance among the innovation sequences indicated both positive and negative spatial interrelations. The negative covariance components are considered to be physically implausible and to have resulted from random sampling error. Graphical modeling, a form of multivariate analysis, was used to model the covariance structure. Results indicate that only 29 of the 325 possible partial correlations among the water-level innovations were statistically significant. The model covariance matrix, corresponding to the model partial correlation structure, contained only positive elements. This model covariance was sequentially partitioned to compute a set of partial covariance matrices that were used to rank the effectiveness of the 26 monitoring wells from greatest to least. Results, for example, indicate that about 50 percent of the uncertainty of the water-level innovations currently monitored by the 26- well network could be described by the 6 most effective wells.

Fungal prion HET-s as a model for structural complexity and self-propagation in prions.

PubMed

Wan, William; Stubbs, Gerald

2014-04-08

The highly ordered and reproducible structure of the fungal prion HET-s makes it an excellent model system for studying the inherent properties of prions, self-propagating infectious proteins that have been implicated in a number of fatal diseases. In particular, the HET-s prion-forming domain readily folds into a relatively complex two-rung β-solenoid amyloid. The faithful self-propagation of this fold involves a diverse array of inter- and intramolecular structural features. These features include a long flexible loop connecting the two rungs, buried polar residues, salt bridges, and asparagine ladders. We have used site-directed mutagenesis and X-ray fiber diffraction to probe the relative importance of these features for the formation of β-solenoid structure, as well as the cumulative effects of multiple mutations. Using fibrillization kinetics and chemical stability assays, we have determined the biophysical effects of our mutations on the assembly and stability of the prion-forming domain. We have found that a diversity of structural features provides a level of redundancy that allows robust folding and stability even in the face of significant sequence alterations and suboptimal environmental conditions. Our findings provide fundamental insights into the structural interactions necessary for self-propagation. Propagation of prion structure seems to require an obligatory level of complexity that may not be reproducible in short peptide models.

Finite Element Model Development and Validation for Aircraft Fuselage Structures

NASA Technical Reports Server (NTRS)

Buehrle, Ralph D.; Fleming, Gary A.; Pappa, Richard S.; Grosveld, Ferdinand W.

2000-01-01

The ability to extend the valid frequency range for finite element based structural dynamic predictions using detailed models of the structural components and attachment interfaces is examined for several stiffened aircraft fuselage structures. This extended dynamic prediction capability is needed for the integration of mid-frequency noise control technology. Beam, plate and solid element models of the stiffener components are evaluated. Attachment models between the stiffener and panel skin range from a line along the rivets of the physical structure to a constraint over the entire contact surface. The finite element models are validated using experimental modal analysis results. The increased frequency range results in a corresponding increase in the number of modes, modal density and spatial resolution requirements. In this study, conventional modal tests using accelerometers are complemented with Scanning Laser Doppler Velocimetry and Electro-Optic Holography measurements to further resolve the spatial response characteristics. Whenever possible, component and subassembly modal tests are used to validate the finite element models at lower levels of assembly. Normal mode predictions for different finite element representations of components and assemblies are compared with experimental results to assess the most accurate techniques for modeling aircraft fuselage type structures.

Estimating the Term Structure With a Semiparametric Bayesian Hierarchical Model: An Application to Corporate Bonds.

PubMed

Cruz-Marcelo, Alejandro; Ensor, Katherine B; Rosner, Gary L

2011-06-01

The term structure of interest rates is used to price defaultable bonds and credit derivatives, as well as to infer the quality of bonds for risk management purposes. We introduce a model that jointly estimates term structures by means of a Bayesian hierarchical model with a prior probability model based on Dirichlet process mixtures. The modeling methodology borrows strength across term structures for purposes of estimation. The main advantage of our framework is its ability to produce reliable estimators at the company level even when there are only a few bonds per company. After describing the proposed model, we discuss an empirical application in which the term structure of 197 individual companies is estimated. The sample of 197 consists of 143 companies with only one or two bonds. In-sample and out-of-sample tests are used to quantify the improvement in accuracy that results from approximating the term structure of corporate bonds with estimators by company rather than by credit rating, the latter being a popular choice in the financial literature. A complete description of a Markov chain Monte Carlo (MCMC) scheme for the proposed model is available as Supplementary Material.

Estimating the Term Structure With a Semiparametric Bayesian Hierarchical Model: An Application to Corporate Bonds1

PubMed Central

Cruz-Marcelo, Alejandro; Ensor, Katherine B.; Rosner, Gary L.

2011-01-01

The term structure of interest rates is used to price defaultable bonds and credit derivatives, as well as to infer the quality of bonds for risk management purposes. We introduce a model that jointly estimates term structures by means of a Bayesian hierarchical model with a prior probability model based on Dirichlet process mixtures. The modeling methodology borrows strength across term structures for purposes of estimation. The main advantage of our framework is its ability to produce reliable estimators at the company level even when there are only a few bonds per company. After describing the proposed model, we discuss an empirical application in which the term structure of 197 individual companies is estimated. The sample of 197 consists of 143 companies with only one or two bonds. In-sample and out-of-sample tests are used to quantify the improvement in accuracy that results from approximating the term structure of corporate bonds with estimators by company rather than by credit rating, the latter being a popular choice in the financial literature. A complete description of a Markov chain Monte Carlo (MCMC) scheme for the proposed model is available as Supplementary Material. PMID:21765566

Analysis of Relationships between Coaches' Organizational Justice and Leader-Member Exchange by Structural Equation Modeling

ERIC Educational Resources Information Center

Akyel, Yakup

2018-01-01

In this study, it was aimed to determine to what extent coaches' organizational justice levels were explained by a leader-member exchange. This study was conducted by using correlational survey model and its sub-purposes were to determine the coaches' organizational justice levels and to examine the differences in organizational justice levels…

Stand-level growth and yield component models for red oak-sweetgum forests on Mid-South minor stream bottoms

Treesearch

Emily B. Schultz; J. Clint Iles; Thomas G. Matney; Andrew W. Ezell; James S. Meadows; Theodor D. Leininger; al. et.

2010-01-01

Greater emphasis is being placed on Southern bottomland hardwood management, but relatively few growth and yield prediction systems exist that are based on sufficient measurements. We present the aggregate stand-level expected yield and structural component equations for a red oak (Quercus section Lobatae)-sweetgum (Liquidambar styraciflua L.) growth and yield model....

Connecting Protein Structure to Intermolecular Interactions: A Computer Modeling Laboratory

ERIC Educational Resources Information Center

Abualia, Mohammed; Schroeder, Lianne; Garcia, Megan; Daubenmire, Patrick L.; Wink, Donald J.; Clark, Ginevra A.

2016-01-01

An understanding of protein folding relies on a solid foundation of a number of critical chemical concepts, such as molecular structure, intra-/intermolecular interactions, and relating structure to function. Recent reports show that students struggle on all levels to achieve these understandings and use them in meaningful ways. Further, several…

The study of features of the structural organization of the au-tomated information processing system of the collective type

NASA Astrophysics Data System (ADS)

Nikolaev, V. N.; Titov, D. V.; Syryamkin, V. I.

2018-05-01

The comparative assessment of the level of channel capacity of different variants of the structural organization of the automated information processing systems is made. The information processing time assessment model depending on the type of standard elements and their structural organization is developed.

Structural Constraints on the Training of Peer Educators in Hepatitis C Prevention

ERIC Educational Resources Information Center

Treloar, Carla; Rance, Jake; Laybutt, Becky; Crawford, Sione

2012-01-01

Despite advances in understanding the structural contexts in which drug use occurs and shifts beyond the individual-level focus of adult education theory, peer education models remain wedded to questions of individual behaviour. Our analysis examines the structural context of peer education and its implications for peer training. People who inject…

Habitat fragmentation resulting in overgrazing by herbivores.

PubMed

Kondoh, Michio

2003-12-21

Habitat fragmentation sometimes results in outbreaks of herbivorous insect and causes an enormous loss of primary production. It is hypothesized that the driving force behind such herbivore outbreaks is disruption of natural enemy attack that releases herbivores from top-down control. To test this hypothesis I studied how trophic community structure changes along a gradient of habitat fragmentation level using spatially implicit and explicit models of a tri-trophic (plant, herbivore and natural enemy) food chain. While in spatially implicit model number of trophic levels gradually decreases with increasing fragmentation, in spatially explicit model a relatively low level of habitat fragmentation leads to overgrazing by herbivore to result in extinction of the plant population followed by a total system collapse. This provides a theoretical support to the hypothesis that habitat fragmentation can lead to overgrazing by herbivores and suggests a central role of spatial structure in the influence of habitat fragmentation on trophic communities. Further, the spatially explicit model shows (i) that the total system collapse by the overgrazing can occur only if herbivore colonization rate is high; (ii) that with increasing natural enemy colonization rate, the fragmentation level that leads to the system collapse becomes higher, and the frequency of the collapse is lowered.

Comparative molecular field analysis of artemisinin derivatives: Ab initio versus semiempirical optimized structures

NASA Astrophysics Data System (ADS)

Tonmunphean, Somsak; Kokpol, Sirirat; Parasuk, Vudhichai; Wolschann, Peter; Winger, Rudolf H.; Liedl, Klaus R.; Rode, Bernd M.

1998-07-01

Based on the belief that structural optimization methods, producing structures more closely to the experimental ones, should give better, i.e. more relevant, steric fields and hence more predictive CoMFA models, comparative molecular field analyses of artemisinin derivatives were performed based on semiempirical AM1 and HF/3-21G optimized geometries. Using these optimized geometries, the CoMFA results derived from the HF/3-21G method are found to be usually but not drastically better than those from AM1. Additional calculations were performed to investigate the electrostatic field difference using the Gasteiger and Marsili charges, the electrostatic potential fit charges at the AM1 level, and the natural population analysis charges at the HF/3-21G level of theory. For the HF/3-21G optimized structures no difference in predictability was observed, whereas for AM1 optimized structures such differences were found. Interestingly, if ionic compounds are omitted, differences between the various HF/3-21G optimized structure models using these electrostatic fields were found.

Dependence of credit spread and macro-conditions based on an alterable structure model.

PubMed

Xie, Yun; Tian, Yixiang; Xiao, Zhuang; Zhou, Xiangyun

2018-01-01

The fat-tail financial data and cyclical financial market makes it difficult for the fixed structure model based on Gaussian distribution to characterize the dynamics of corporate bonds spreads. Using a flexible structure model based on generalized error distribution, this paper focuses on the impact of macro-level factors on the spreads of corporate bonds in China. It is found that in China's corporate bonds market, macroeconomic conditions have obvious structural transformational effects on bonds spreads, and their structural features remain stable with the downgrade of bonds ratings. The impact of macroeconomic conditions on spreads is significant for different structures, and the differences between the structures increase as ratings decline. For different structures, the persistent characteristics of bonds spreads are obviously stronger than those of recursive ones, which suggest an obvious speculation in bonds market. It is also found that the structure switching of bonds with different ratings is not synchronous, which indicates the shift of investment between different grades of bonds.

Dependence of credit spread and macro-conditions based on an alterable structure model

PubMed Central

2018-01-01

The fat-tail financial data and cyclical financial market makes it difficult for the fixed structure model based on Gaussian distribution to characterize the dynamics of corporate bonds spreads. Using a flexible structure model based on generalized error distribution, this paper focuses on the impact of macro-level factors on the spreads of corporate bonds in China. It is found that in China's corporate bonds market, macroeconomic conditions have obvious structural transformational effects on bonds spreads, and their structural features remain stable with the downgrade of bonds ratings. The impact of macroeconomic conditions on spreads is significant for different structures, and the differences between the structures increase as ratings decline. For different structures, the persistent characteristics of bonds spreads are obviously stronger than those of recursive ones, which suggest an obvious speculation in bonds market. It is also found that the structure switching of bonds with different ratings is not synchronous, which indicates the shift of investment between different grades of bonds. PMID:29723295

On predicting monitoring system effectiveness

NASA Astrophysics Data System (ADS)

Cappello, Carlo; Sigurdardottir, Dorotea; Glisic, Branko; Zonta, Daniele; Pozzi, Matteo

2015-03-01

While the objective of structural design is to achieve stability with an appropriate level of reliability, the design of systems for structural health monitoring is performed to identify a configuration that enables acquisition of data with an appropriate level of accuracy in order to understand the performance of a structure or its condition state. However, a rational standardized approach for monitoring system design is not fully available. Hence, when engineers design a monitoring system, their approach is often heuristic with performance evaluation based on experience, rather than on quantitative analysis. In this contribution, we propose a probabilistic model for the estimation of monitoring system effectiveness based on information available in prior condition, i.e. before acquiring empirical data. The presented model is developed considering the analogy between structural design and monitoring system design. We assume that the effectiveness can be evaluated based on the prediction of the posterior variance or covariance matrix of the state parameters, which we assume to be defined in a continuous space. Since the empirical measurements are not available in prior condition, the estimation of the posterior variance or covariance matrix is performed considering the measurements as a stochastic variable. Moreover, the model takes into account the effects of nuisance parameters, which are stochastic parameters that affect the observations but cannot be estimated using monitoring data. Finally, we present an application of the proposed model to a real structure. The results show how the model enables engineers to predict whether a sensor configuration satisfies the required performance.

Evidence from a rare case study for Hebbian-like changes in structural connectivity induced by long-term deep brain stimulation.

PubMed

van Hartevelt, Tim J; Cabral, Joana; Møller, Arne; FitzGerald, James J; Green, Alexander L; Aziz, Tipu Z; Deco, Gustavo; Kringelbach, Morten L

2015-01-01

It is unclear whether Hebbian-like learning occurs at the level of long-range white matter connections in humans, i.e., where measurable changes in structural connectivity (SC) are correlated with changes in functional connectivity. However, the behavioral changes observed after deep brain stimulation (DBS) suggest the existence of such Hebbian-like mechanisms occurring at the structural level with functional consequences. In this rare case study, we obtained the full network of white matter connections of one patient with Parkinson's disease (PD) before and after long-term DBS and combined it with a computational model of ongoing activity to investigate the effects of DBS-induced long-term structural changes. The results show that the long-term effects of DBS on resting-state functional connectivity is best obtained in the computational model by changing the structural weights from the subthalamic nucleus (STN) to the putamen and the thalamus in a Hebbian-like manner. Moreover, long-term DBS also significantly changed the SC towards normality in terms of model-based measures of segregation and integration of information processing, two key concepts of brain organization. This novel approach using computational models to model the effects of Hebbian-like changes in SC allowed us to causally identify the possible underlying neural mechanisms of long-term DBS using rare case study data. In time, this could help predict the efficacy of individual DBS targeting and identify novel DBS targets.

Conceptual-level workflow modeling of scientific experiments using NMR as a case study

PubMed Central

Verdi, Kacy K; Ellis, Heidi JC; Gryk, Michael R

2007-01-01

Background Scientific workflows improve the process of scientific experiments by making computations explicit, underscoring data flow, and emphasizing the participation of humans in the process when intuition and human reasoning are required. Workflows for experiments also highlight transitions among experimental phases, allowing intermediate results to be verified and supporting the proper handling of semantic mismatches and different file formats among the various tools used in the scientific process. Thus, scientific workflows are important for the modeling and subsequent capture of bioinformatics-related data. While much research has been conducted on the implementation of scientific workflows, the initial process of actually designing and generating the workflow at the conceptual level has received little consideration. Results We propose a structured process to capture scientific workflows at the conceptual level that allows workflows to be documented efficiently, results in concise models of the workflow and more-correct workflow implementations, and provides insight into the scientific process itself. The approach uses three modeling techniques to model the structural, data flow, and control flow aspects of the workflow. The domain of biomolecular structure determination using Nuclear Magnetic Resonance spectroscopy is used to demonstrate the process. Specifically, we show the application of the approach to capture the workflow for the process of conducting biomolecular analysis using Nuclear Magnetic Resonance (NMR) spectroscopy. Conclusion Using the approach, we were able to accurately document, in a short amount of time, numerous steps in the process of conducting an experiment using NMR spectroscopy. The resulting models are correct and precise, as outside validation of the models identified only minor omissions in the models. In addition, the models provide an accurate visual description of the control flow for conducting biomolecular analysis using NMR spectroscopy experiment. PMID:17263870

Conceptual-level workflow modeling of scientific experiments using NMR as a case study.

PubMed

Verdi, Kacy K; Ellis, Heidi Jc; Gryk, Michael R

2007-01-30

Scientific workflows improve the process of scientific experiments by making computations explicit, underscoring data flow, and emphasizing the participation of humans in the process when intuition and human reasoning are required. Workflows for experiments also highlight transitions among experimental phases, allowing intermediate results to be verified and supporting the proper handling of semantic mismatches and different file formats among the various tools used in the scientific process. Thus, scientific workflows are important for the modeling and subsequent capture of bioinformatics-related data. While much research has been conducted on the implementation of scientific workflows, the initial process of actually designing and generating the workflow at the conceptual level has received little consideration. We propose a structured process to capture scientific workflows at the conceptual level that allows workflows to be documented efficiently, results in concise models of the workflow and more-correct workflow implementations, and provides insight into the scientific process itself. The approach uses three modeling techniques to model the structural, data flow, and control flow aspects of the workflow. The domain of biomolecular structure determination using Nuclear Magnetic Resonance spectroscopy is used to demonstrate the process. Specifically, we show the application of the approach to capture the workflow for the process of conducting biomolecular analysis using Nuclear Magnetic Resonance (NMR) spectroscopy. Using the approach, we were able to accurately document, in a short amount of time, numerous steps in the process of conducting an experiment using NMR spectroscopy. The resulting models are correct and precise, as outside validation of the models identified only minor omissions in the models. In addition, the models provide an accurate visual description of the control flow for conducting biomolecular analysis using NMR spectroscopy experiment.

Multilevel Deficiency of White Matter Connectivity Networks in Alzheimer's Disease: A Diffusion MRI Study with DTI and HARDI Models.

PubMed

Wang, Tao; Shi, Feng; Jin, Yan; Yap, Pew-Thian; Wee, Chong-Yaw; Zhang, Jianye; Yang, Cece; Li, Xia; Xiao, Shifu; Shen, Dinggang

2016-01-01

Alzheimer's disease (AD) is the most common form of dementia in elderly people. It is an irreversible and progressive brain disease. In this paper, we utilized diffusion-weighted imaging (DWI) to detect abnormal topological organization of white matter (WM) structural networks. We compared the differences between WM connectivity characteristics at global, regional, and local levels in 26 patients with probable AD and 16 normal control (NC) elderly subjects, using connectivity networks constructed with the diffusion tensor imaging (DTI) model and the high angular resolution diffusion imaging (HARDI) model, respectively. At the global level, we found that the WM structural networks of both AD and NC groups had a small-world topology; however, the AD group showed a significant decrease in both global and local efficiency, but an increase in clustering coefficient and the average shortest path length. We further found that the AD patients had significantly decreased nodal efficiency at the regional level, as well as weaker connections in multiple local cortical and subcortical regions, such as precuneus, temporal lobe, hippocampus, and thalamus. The HARDI model was found to be more advantageous than the DTI model, as it was more sensitive to the deficiencies in AD at all of the three levels.

Evaluation of Multi-Level Support Structure Requirements for New Weapon Systems.

DTIC Science & Technology

1987-09-01

transformer 1 total consumed manhours on this level 19.45 hrs average manhrs within 4 weeks on this level : .38 hrs average rounded number of mainten; personal ...major unit data to provide conclusions about the logistics behavior of failing weapon systems. The modeling of system behavior with CAESAR has severa-l...characteristic data and major unit data to provide conclusions about the logistics behavior of failing weapon systems. The modelling of system behavior

Coral reef structural complexity provides important coastal protection from waves under rising sea levels.

PubMed

Harris, Daniel L; Rovere, Alessio; Casella, Elisa; Power, Hannah; Canavesio, Remy; Collin, Antoine; Pomeroy, Andrew; Webster, Jody M; Parravicini, Valeriano

2018-02-01

Coral reefs are diverse ecosystems that support millions of people worldwide by providing coastal protection from waves. Climate change and human impacts are leading to degraded coral reefs and to rising sea levels, posing concerns for the protection of tropical coastal regions in the near future. We use a wave dissipation model calibrated with empirical wave data to calculate the future increase of back-reef wave height. We show that, in the near future, the structural complexity of coral reefs is more important than sea-level rise in determining the coastal protection provided by coral reefs from average waves. We also show that a significant increase in average wave heights could occur at present sea level if there is sustained degradation of benthic structural complexity. Our results highlight that maintaining the structural complexity of coral reefs is key to ensure coastal protection on tropical coastlines in the future.

Coral reef structural complexity provides important coastal protection from waves under rising sea levels

PubMed Central

Harris, Daniel L.; Rovere, Alessio; Casella, Elisa; Power, Hannah; Canavesio, Remy; Collin, Antoine; Pomeroy, Andrew; Webster, Jody M.; Parravicini, Valeriano

2018-01-01

Coral reefs are diverse ecosystems that support millions of people worldwide by providing coastal protection from waves. Climate change and human impacts are leading to degraded coral reefs and to rising sea levels, posing concerns for the protection of tropical coastal regions in the near future. We use a wave dissipation model calibrated with empirical wave data to calculate the future increase of back-reef wave height. We show that, in the near future, the structural complexity of coral reefs is more important than sea-level rise in determining the coastal protection provided by coral reefs from average waves. We also show that a significant increase in average wave heights could occur at present sea level if there is sustained degradation of benthic structural complexity. Our results highlight that maintaining the structural complexity of coral reefs is key to ensure coastal protection on tropical coastlines in the future. PMID:29503866

Transferable atomistic model to describe the energetics of zirconia

NASA Astrophysics Data System (ADS)

Wilson, Mark; Schönberger, Uwe; Finnis, Michael W.

1996-10-01

We have investigated the energies of a number of phases of ZrO2 using models of an increasing degree of sophistication: the simple ionic model, the polarizable ion model, the compressible ion model, and finally a model including quadrupole polarizability of the oxygen ions. The three structures which are observed with increasing temperatures are monoclinic, tetragonal, and cubic (fluorite). Besides these we have studied some hypothetical structures which certain potentials erroneously predict or which occur in other oxides with this stoichiometry, e.g., the α-PbO2 structure and rutile. We have also performed ab initio density functional calculations with the full-potential linear combination of muffin-tin orbitals method to investigate the cubic-tetragonal distortion. A detailed comparison is made between the results using classical potentials, the experimental data, and our own and other ab initio results. The factors which stabilize the various structure are analyzed. We find the only genuinely transferable model is the one including compressible ions and anion polarizability to the quadrupole level.

Experiments and numerical simulations of nonlinear vibration responses of an assembly with friction joints - Application on a test structure named "Harmony"

NASA Astrophysics Data System (ADS)

Claeys, M.; Sinou, J.-J.; Lambelin, J.-P.; Todeschini, R.

2016-03-01

In presence of friction, the frequency response function of a metallic assembly is strongly dependent on the excitation level. The local stick-slip behavior at the friction interfaces induces energy dissipation and local stiffness softening. These phenomena are studied both experimentally and numerically on a test structure named "Harmony". Concerning the numerical part, a classical complete methodology from the finite element and friction modeling to the prediction of the nonlinear vibrational response is implemented. The well-known Harmonic Balance Method with a specific condensation process on the nonlinear frictional elements is achieved. Also, vibration experiments are performed to validate not only the finite element model of the test structure named "Harmony" at low excitation levels but also to investigate the nonlinear behavior of the system on several excitation levels. A scanning laser vibrometer is used to measure the nonlinear behavior and the local stick-slip movement near the contacts.

An efficient sequential strategy for realizing cross-gradient joint inversion: method and its application to 2-D cross borehole seismic traveltime and DC resistivity tomography

NASA Astrophysics Data System (ADS)

Gao, Ji; Zhang, Haijiang

2018-05-01

Cross-gradient joint inversion that enforces structural similarity between different models has been widely utilized in jointly inverting different geophysical data types. However, it is a challenge to combine different geophysical inversion systems with the cross-gradient structural constraint into one joint inversion system because they may differ greatly in the model representation, forward modelling and inversion algorithm. Here we propose a new joint inversion strategy that can avoid this issue. Different models are separately inverted using the existing inversion packages and model structure similarity is only enforced through cross-gradient minimization between two models after each iteration. Although the data fitting and structural similarity enforcing processes are decoupled, our proposed strategy is still able to choose appropriate models to balance the trade-off between geophysical data fitting and structural similarity. This is realized by using model perturbations from separate data inversions to constrain the cross-gradient minimization process. We have tested this new strategy on 2-D cross borehole synthetic seismic traveltime and DC resistivity data sets. Compared to separate geophysical inversions, our proposed joint inversion strategy fits the separate data sets at comparable levels while at the same time resulting in a higher structural similarity between the velocity and resistivity models.

Classification of Farmland Landscape Structure in Multiple Scales

NASA Astrophysics Data System (ADS)

Jiang, P.; Cheng, Q.; Li, M.

2017-12-01

Farmland is one of the basic terrestrial resources that support the development and survival of human beings and thus plays a crucial role in the national security of every country. Pattern change is the intuitively spatial representation of the scale and quality variation of farmland. Through the characteristic development of spatial shapes as well as through changes in system structures, functions and so on, farmland landscape patterns may indicate the landscape health level. Currently, it is still difficult to perform positioning analyses of landscape pattern changes that reflect the landscape structure variations of farmland with an index model. Depending on a number of spatial properties such as locations and adjacency relations, distance decay, fringe effect, and on the model of patch-corridor-matrix that is applied, this study defines a type system of farmland landscape structure on the national, provincial, and city levels. According to such a definition, the classification model of farmland landscape-structure type at the pixel scale is developed and validated based on mathematical-morphology concepts and on spatial-analysis methods. Then, the laws that govern farmland landscape-pattern change in multiple scales are analyzed from the perspectives of spatial heterogeneity, spatio-temporal evolution, and function transformation. The result shows that the classification model of farmland landscape-structure type can reflect farmland landscape-pattern change and its effects on farmland production function. Moreover, farmland landscape change in different scales displayed significant disparity in zonality, both within specific regions and in urban-rural areas.

THz emission of donor and acceptor doped GaAs/AlGaAs quantum well structures with inserted thin AlAs monolayer

NASA Astrophysics Data System (ADS)

van Dommelen, Paphavee; Daengngam, Chalongrat; Kalasuwan, Pruet

2018-04-01

In this paper, we explore THz range optical intersubband transition energies in a donor doped quantum well of a GaAs/AlGaAs system as a function of the insertion position of an AlAs monolayer in the GaAs quantum well. In simulated models, the optical transition energies between electron subband levels 1 and 2 were higher in the doped structure than in the undoped structure. This may be because the envelope wave function of the second electron subband strongly overlapped the envelope wave function of the first electron subband and influenced the optical intersubband transition between the two levels in the THz range. At different levels of bias voltage at the Schottky barrier on the donor doped structure, the electric field in the growth direction of the structure linearly increased the further away the AlAs monolayer was placed from the reference position. We also simulated the optical transition energies between acceptor energy levels of the acceptor doped structure as a function of the insertion position of the AlAs monolayer. The acceptor doped structure induced THz range emission whereas the undoped structure induced mid-IR emission.

Reduced modeling of flexible structures for decentralized control

NASA Technical Reports Server (NTRS)

Yousuff, A.; Tan, T. M.; Bahar, L. Y.; Konstantinidis, M. F.

1986-01-01

Based upon the modified finite element-transfer matrix method, this paper presents a technique for reduced modeling of flexible structures for decentralized control. The modeling decisions are carried out at (finite-) element level, and are dictated by control objectives. A simply supported beam with two sets of actuators and sensors (linear force actuator and linear position and velocity sensors) is considered for illustration. In this case, it is conjectured that the decentrally controlled closed loop system is guaranteed to be at least marginally stable.

Structured Spatial Modeling and Mapping of Domestic Violence Against Women of Reproductive Age in Rwanda.

PubMed

Habyarimana, Faustin; Zewotir, Temesgen; Ramroop, Shaun

2018-03-01

The main objective of this study was to assess the risk factors and spatial correlates of domestic violence against women of reproductive age in Rwanda. A structured spatial approach was used to account for the nonlinear nature of some covariates and the spatial variability on domestic violence. The nonlinear effect was modeled through second-order random walk, and the structured spatial effect was modeled through Gaussian Markov Random Fields specified as an intrinsic conditional autoregressive model. The data from the Rwanda Demographic and Health Survey 2014/2015 were used as an application. The findings of this study revealed that the risk factors of domestic violence against women are the wealth quintile of the household, the size of the household, the husband or partner's age, the husband or partner's level of education, ownership of the house, polygamy, the alcohol consumption status of the husband or partner, the woman's perception of wife-beating attitude, and the use of contraceptive methods. The study also highlighted the significant spatial variation of domestic violence against women at district level.

Regression analysis using dependent Polya trees.

PubMed

Schörgendorfer, Angela; Branscum, Adam J

2013-11-30

Many commonly used models for linear regression analysis force overly simplistic shape and scale constraints on the residual structure of data. We propose a semiparametric Bayesian model for regression analysis that produces data-driven inference by using a new type of dependent Polya tree prior to model arbitrary residual distributions that are allowed to evolve across increasing levels of an ordinal covariate (e.g., time, in repeated measurement studies). By modeling residual distributions at consecutive covariate levels or time points using separate, but dependent Polya tree priors, distributional information is pooled while allowing for broad pliability to accommodate many types of changing residual distributions. We can use the proposed dependent residual structure in a wide range of regression settings, including fixed-effects and mixed-effects linear and nonlinear models for cross-sectional, prospective, and repeated measurement data. A simulation study illustrates the flexibility of our novel semiparametric regression model to accurately capture evolving residual distributions. In an application to immune development data on immunoglobulin G antibodies in children, our new model outperforms several contemporary semiparametric regression models based on a predictive model selection criterion. Copyright © 2013 John Wiley & Sons, Ltd.

Vibrations and structureborne noise in space station

NASA Technical Reports Server (NTRS)

Vaicaitis, R.; Lyrintzis, C. S.; Bofilios, D. A.

1987-01-01

Analytical models were developed to predict vibrations and structureborne noise generation of cylindrical and rectangular acoustic enclosures. These models are then used to determine structural vibration levels and interior noise to random point input forces. The guidelines developed could provide preliminary information on acoustical and vibrational environments in space station habitability modules under orbital operations. The structural models include single wall monocoque shell, double wall shell, stiffened orthotropic shell, descretely stiffened flat panels, and a coupled system composed of a cantilever beam structure and a stiffened sidewall. Aluminum and fiber reinforced composite materials are considered for single and double wall shells. The end caps of the cylindrical enclosures are modeled either as single or double wall circular plates. Sound generation in the interior space is calculated by coupling the structural vibrations to the acoustic field in the enclosure. Modal methods and transfer matrix techniques are used to obtain structural vibrations. Parametric studies are performed to determine the sensitivity of interior noise environment to changes in input, geometric and structural conditions.

Development of an Aeroelastic Modeling Capability for Transient Nozzle Side Load Analysis

NASA Technical Reports Server (NTRS)

Wang, Ten-See; Zhao, Xiang; Zhang, Sijun; Chen, Yen-Sen

2013-01-01

Lateral nozzle forces are known to cause severe structural damage to any new rocket engine in development. Currently there is no fully coupled computational tool to analyze this fluid/structure interaction process. The objective of this study was to develop a fully coupled aeroelastic modeling capability to describe the fluid/structure interaction process during the transient nozzle operations. The aeroelastic model composes of three components: the computational fluid dynamics component based on an unstructured-grid, pressure-based computational fluid dynamics formulation, the computational structural dynamics component developed in the framework of modal analysis, and the fluid-structural interface component. The developed aeroelastic model was applied to the transient nozzle startup process of the Space Shuttle Main Engine at sea level. The computed nozzle side loads and the axial nozzle wall pressure profiles from the aeroelastic nozzle are compared with those of the published rigid nozzle results, and the impact of the fluid/structure interaction on nozzle side loads is interrogated and presented.

Use of 13Cα Chemical-Shifts in Protein Structure Determination

PubMed Central

Vila, Jorge A.; Ripoll, Daniel R.; Scheraga, Harold A.

2008-01-01

A physics-based method, aimed at determining protein structures by using NOE-derived distances together with observed and computed 13C chemical shifts, is proposed. The approach makes use of 13Cα chemical shifts, computed at the density functional level of theory, to obtain torsional constraints for all backbone and side-chain torsional angles without making a priori use of the occupancy of any region of the Ramachandran map by the amino acid residues. The torsional constraints are not fixed but are changed dynamically in each step of the procedure, following an iterative self-consistent approach intended to identify a set of conformations for which the computed 13Cα chemical shifts match the experimental ones. A test is carried out on a 76-amino acid all-α-helical protein, namely the B. Subtilis acyl carrier protein. It is shown that, starting from randomly generated conformations, the final protein models are more accurate than an existing NMR-derived structure model of this protein, in terms of both the agreement between predicted and observed 13Cα chemical shifts and some stereochemical quality indicators, and of similar accuracy as one of the protein models solved at a high level of resolution. The results provide evidence that this methodology can be used not only for structure determination but also for additional protein structure refinement of NMR-derived models deposited in the Protein Data Bank. PMID:17516673

Affinity comparison of different THCA synthase to CBGA using modeling computational approaches.

PubMed

Alaoui, Moulay Abdelaziz El; Ibrahimi, Azeddine; Semlali, Oussama; Tarhda, Zineb; Marouane, Melloul; Najwa, Alaoui; Soulaymani, Abdelmajid; Fahime, Elmostafa El

2014-01-01

The Δ(9-)Tetrahydrocannabinol (THCA) is the primary psychoactive compound of Cannabis Sativa. It is produced by Δ(1-) Tetrahydrocannabinolic acid synthase (THCA) which catalyzes the oxidative cyclization of cannabigerolic acid (CBGA) the precursor of the THCA. In this study, we were interested by the three dimensional structure of THCA synthase protein. Generation of models were done by MODELLER v9.11 and homology modeling with Δ1-tetrahydrocannabinolic acid (THCA) synthase X ray structure (PDB code 3VTE) on the basis of sequences retrieved from GenBank. Procheck, Errat, and Verify 3D tools were used to verify the reliability of the six 3D models obtained, the overall quality factor and the Prosa Z-score were also used to check the quality of the six modeled proteins. The RMSDs for C-alpha atoms, main-chain atoms, side-chain atoms and all atoms between the modeled structures and the corresponding template ranged between 0.290 Å-1.252 Å, reflecting the good quality of the obtained models. Our study of the CBGA-THCA synthase docking demonstrated that the active site pocket was successfully recognized using computational approach. The interaction energy of CBGA computed in 'fiber types' proteins ranged between -4.1 95 kcal/mol and -5.95 kcal/mol whereas in the 'drug type' was about -7.02 kcal/mol to -7.16 kcal/mol, which maybe indicate the important role played by the interaction energy of CBGA in the determination of the THCA level in Cannabis Sativa L. varieties. Finally, we have proposed an experimental design in order to explore the binding energy source of ligand-enzyme in Cannabis Sativa and the production level of the THCA in the absence of any information regarding the correlation between the enzyme affinity and THCA level production. This report opens the doors to more studies predicting the binding site pocket with accuracy from the perspective of the protein affinity and THCA level produced in Cannabis Sativa.

Coarse-grained component concurrency in Earth system modeling: parallelizing atmospheric radiative transfer in the GFDL AM3 model using the Flexible Modeling System coupling framework

NASA Astrophysics Data System (ADS)

Balaji, V.; Benson, Rusty; Wyman, Bruce; Held, Isaac

2016-10-01

Climate models represent a large variety of processes on a variety of timescales and space scales, a canonical example of multi-physics multi-scale modeling. Current hardware trends, such as Graphical Processing Units (GPUs) and Many Integrated Core (MIC) chips, are based on, at best, marginal increases in clock speed, coupled with vast increases in concurrency, particularly at the fine grain. Multi-physics codes face particular challenges in achieving fine-grained concurrency, as different physics and dynamics components have different computational profiles, and universal solutions are hard to come by. We propose here one approach for multi-physics codes. These codes are typically structured as components interacting via software frameworks. The component structure of a typical Earth system model consists of a hierarchical and recursive tree of components, each representing a different climate process or dynamical system. This recursive structure generally encompasses a modest level of concurrency at the highest level (e.g., atmosphere and ocean on different processor sets) with serial organization underneath. We propose to extend concurrency much further by running more and more lower- and higher-level components in parallel with each other. Each component can further be parallelized on the fine grain, potentially offering a major increase in the scalability of Earth system models. We present here first results from this approach, called coarse-grained component concurrency, or CCC. Within the Geophysical Fluid Dynamics Laboratory (GFDL) Flexible Modeling System (FMS), the atmospheric radiative transfer component has been configured to run in parallel with a composite component consisting of every other atmospheric component, including the atmospheric dynamics and all other atmospheric physics components. We will explore the algorithmic challenges involved in such an approach, and present results from such simulations. Plans to achieve even greater levels of coarse-grained concurrency by extending this approach within other components, such as the ocean, will be discussed.

Advanced Computational Methods for High-accuracy Refinement of Protein Low-quality Models

NASA Astrophysics Data System (ADS)

Zang, Tianwu

Predicting the 3-dimentional structure of protein has been a major interest in the modern computational biology. While lots of successful methods can generate models with 3˜5A root-mean-square deviation (RMSD) from the solution, the progress of refining these models is quite slow. It is therefore urgently needed to develop effective methods to bring low-quality models to higher-accuracy ranges (e.g., less than 2 A RMSD). In this thesis, I present several novel computational methods to address the high-accuracy refinement problem. First, an enhanced sampling method, named parallel continuous simulated tempering (PCST), is developed to accelerate the molecular dynamics (MD) simulation. Second, two energy biasing methods, Structure-Based Model (SBM) and Ensemble-Based Model (EBM), are introduced to perform targeted sampling around important conformations. Third, a three-step method is developed to blindly select high-quality models along the MD simulation. These methods work together to make significant refinement of low-quality models without any knowledge of the solution. The effectiveness of these methods is examined in different applications. Using the PCST-SBM method, models with higher global distance test scores (GDT_TS) are generated and selected in the MD simulation of 18 targets from the refinement category of the 10th Critical Assessment of Structure Prediction (CASP10). In addition, in the refinement test of two CASP10 targets using the PCST-EBM method, it is indicated that EBM may bring the initial model to even higher-quality levels. Furthermore, a multi-round refinement protocol of PCST-SBM improves the model quality of a protein to the level that is sufficient high for the molecular replacement in X-ray crystallography. Our results justify the crucial position of enhanced sampling in the protein structure prediction and demonstrate that a considerable improvement of low-accuracy structures is still achievable with current force fields.

Advances in Micromechanics Modeling of Composites Structures for Structural Health Monitoring

NASA Astrophysics Data System (ADS)

Moncada, Albert

Although high performance, light-weight composites are increasingly being used in applications ranging from aircraft, rotorcraft, weapon systems and ground vehicles, the assurance of structural reliability remains a critical issue. In composites, damage is absorbed through various fracture processes, including fiber failure, matrix cracking and delamination. An important element in achieving reliable composite systems is a strong capability of assessing and inspecting physical damage of critical structural components. Installation of a robust Structural Health Monitoring (SHM) system would be very valuable in detecting the onset of composite failure. A number of major issues still require serious attention in connection with the research and development aspects of sensor-integrated reliable SHM systems for composite structures. In particular, the sensitivity of currently available sensor systems does not allow detection of micro level damage; this limits the capability of data driven SHM systems. As a fundamental layer in SHM, modeling can provide in-depth information on material and structural behavior for sensing and detection, as well as data for learning algorithms. This dissertation focuses on the development of a multiscale analysis framework, which is used to detect various forms of damage in complex composite structures. A generalized method of cells based micromechanics analysis, as implemented in NASA's MAC/GMC code, is used for the micro-level analysis. First, a baseline study of MAC/GMC is performed to determine the governing failure theories that best capture the damage progression. The deficiencies associated with various layups and loading conditions are addressed. In most micromechanics analysis, a representative unit cell (RUC) with a common fiber packing arrangement is used. The effect of variation in this arrangement within the RUC has been studied and results indicate this variation influences the macro-scale effective material properties and failure stresses. The developed model has been used to simulate impact damage in a composite beam and an airfoil structure. The model data was verified through active interrogation using piezoelectric sensors. The multiscale model was further extended to develop a coupled damage and wave attenuation model, which was used to study different damage states such as fiber-matrix debonding in composite structures with surface bonded piezoelectric sensors.

The role of zinc deficiency-induced changes in the phospholipid-protein balance of blood serum in animal depression model by Raman, FTIR and UV-vis spectroscopy.

PubMed

Depciuch, J; Sowa-Kućma, M; Nowak, G; Szewczyk, B; Doboszewska, U; Parlinska-Wojtan, M

2017-05-01

Depression is a serious mental illness. To study the mechanisms of diseases and search for new, more effective therapies, animal models are used. Unfortunately, none of the available models does reflect all symptoms of depression. Zinc deficiency is proposed as a new animal model of depression. However, it has not been yet validated in a detailed manner. Recently, spectroscopic techniques are increasingly being used both in clinical and preclinical studies. Here we examined the effect of zinc deficiency and amitryptyline treatment on the phospholipid - protein balance in the blood serum of rats using Raman, Fourier Transform Infra Red (FTIR) and UV-vis technique. Male Sprague Dawley rats were fed with a zinc ample diet (ZnA, 50mg Zn/kg) or a zinc deficient diet (ZnD, 3mg Zn/kg) for 4 weeks. Then amitriptyline administration (AMI, 10mg/kg, i.p.) was started. After injecting the drug for 2-weeks, blood samples were collected and analyzed. It was found that zinc deficiency decreases both the level of phospholipids and proteins and also causes structural changes in their structures. In the ZnD group amitriptyline treatment influenced the protein level and structure. UV-vis spectroscopy combined with the second derivative calculated from the FTIR spectra provided information that the proteins in blood serum of rat fed with a low Zn diet regain their intact structure after amitriptyline medication. Simultaneously, the antidepressant therapy did not have any effect on the level of phospholipids in this group of rats. Additionally, our results show, that amitriptyline administration can change the structure of phospholipids in rats subjected to zinc ample diet. This altered structure of phospholipids was identified as shortening of carbon chains. Our findings indicate that the decreased level of zinc may be the cause of depressive disorders, as it leads to changes in the phospholipid-protein balance necessary for the proper functioning of the body. This study also shows possible new applications of spectroscopic techniques in the diagnosis of affective disorders, and maybe even identifies markers of depressive disorders. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Matrix Management: An Organizational Alternative for Libraries.

ERIC Educational Resources Information Center

Johnson, Peggy

1990-01-01

Describes various organizational structures and models, presents matrix management as an alternative to traditional hierarchical structures, and suggests matrix management as an appropriate organizational alternative for academic libraries. Benefits that are discussed include increased flexibility, a higher level of professional independence, and…

Engine-induced structural-borne noise in a general aviation aircraft

NASA Technical Reports Server (NTRS)

Unruh, J. F.; Scheidt, D. C.; Pomerening, D. J.

1979-01-01

Structural borne interior noise in a single engine general aviation aircraft was studied to determine the importance of engine induced structural borne noise and to determine the necessary modeling requirements for the prediction of structural borne interior noise. Engine attached/detached ground test data show that engine induced structural borne noise is a primary interior noise source for the single engine test aircraft, cabin noise is highly influenced by responses at the propeller tone, and cabin acoustic resonances can influence overall noise levels. Results from structural and acoustic finite element coupled models of the test aircraft show that wall flexibility has a strong influence on fundamental cabin acoustic resonances, the lightweight fuselage structure has a high modal density, and finite element analysis procedures are appropriate for the prediction of structural borne noise.

Developing an integrative level-dimensional taxonomy model for rehabilitation psychology research and practice.

PubMed

Mermis, Bernie J

2018-02-01

The present article concerns the development of a taxonomy model for organizing and classifying all aspects of rehabilitation psychology from an integrative level-dimensional conceptualization. This conceptualization is presented as an alternative to a primarily categorical approach to classification. It also assumes a continuity perspective for all aspects of behavior and experience. Development of this taxonomy model involves organizing information relevant to levels/domains of all aspects of behavior and experience, and to constructs describing their underlying components conceptually as well as dimensions which constitute the measurable basis of constructs. A taxonomy model with levels/domains, representative examples of constructs and dimensions is presented as a foundation for development of the present taxonomy model, with specific relevance to rehabilitation psychology. This integrative level-dimensional taxonomy model provides a structure for organizing all aspects of rehabilitation psychology relevant to understanding, assessing, and influencing the rehabilitation process. Suggestions for development and research are provided for the taxonomy model. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Protein Models Docking Benchmark 2

PubMed Central

Anishchenko, Ivan; Kundrotas, Petras J.; Tuzikov, Alexander V.; Vakser, Ilya A.

2015-01-01

Structural characterization of protein-protein interactions is essential for our ability to understand life processes. However, only a fraction of known proteins have experimentally determined structures. Such structures provide templates for modeling of a large part of the proteome, where individual proteins can be docked by template-free or template-based techniques. Still, the sensitivity of the docking methods to the inherent inaccuracies of protein models, as opposed to the experimentally determined high-resolution structures, remains largely untested, primarily due to the absence of appropriate benchmark set(s). Structures in such a set should have pre-defined inaccuracy levels and, at the same time, resemble actual protein models in terms of structural motifs/packing. The set should also be large enough to ensure statistical reliability of the benchmarking results. We present a major update of the previously developed benchmark set of protein models. For each interactor, six models were generated with the model-to-native Cα RMSD in the 1 to 6 Å range. The models in the set were generated by a new approach, which corresponds to the actual modeling of new protein structures in the “real case scenario,” as opposed to the previous set, where a significant number of structures were model-like only. In addition, the larger number of complexes (165 vs. 63 in the previous set) increases the statistical reliability of the benchmarking. We estimated the highest accuracy of the predicted complexes (according to CAPRI criteria), which can be attained using the benchmark structures. The set is available at http://dockground.bioinformatics.ku.edu. PMID:25712716

Damage assessment of composite plate structures with material and measurement uncertainty

NASA Astrophysics Data System (ADS)

Chandrashekhar, M.; Ganguli, Ranjan

2016-06-01

Composite materials are very useful in structural engineering particularly in weight sensitive applications. Two different test models of the same structure made from composite materials can display very different dynamic behavior due to large uncertainties associated with composite material properties. Also, composite structures can suffer from pre-existing imperfections like delaminations, voids or cracks during fabrication. In this paper, we show that modeling and material uncertainties in composite structures can cause considerable problem in damage assessment. A recently developed C0 shear deformable locking free refined composite plate element is employed in the numerical simulations to alleviate modeling uncertainty. A qualitative estimate of the impact of modeling uncertainty on the damage detection problem is made. A robust Fuzzy Logic System (FLS) with sliding window defuzzifier is used for delamination damage detection in composite plate type structures. The FLS is designed using variations in modal frequencies due to randomness in material properties. Probabilistic analysis is performed using Monte Carlo Simulation (MCS) on a composite plate finite element model. It is demonstrated that the FLS shows excellent robustness in delamination detection at very high levels of randomness in input data.

Impact of representation of hydraulic structures in modelling a Severn barrage

NASA Astrophysics Data System (ADS)

Bray, Samuel; Ahmadian, Reza; Falconer, Roger A.

2016-04-01

In this study, enhancements to the numerical representation of sluice gates and turbines were made to the hydro-environmental model Environmental Fluid Dynamics Code (EFDC), and applied to the Severn Tidal Power Group Cardiff-Weston Barrage. The extended domain of the EFDC Continental Shelf Model (CSM) allows far-field hydrodynamic impact assessment of the Severn Barrage, pre- and post-enhancement, to demonstrate the importance of accurate hydraulic structure representation. The enhancements were found to significantly affect peak water levels in the Bristol Channel, reducing levels by nearly 1 m in some areas, and even affect predictions as far-field as the West Coast of Scotland, albeit to a far lesser extent. The model was tested for sensitivity to changes in the discharge coefficient, Cd, used in calculating discharge through sluice gates and turbines. It was found that the performance of the Severn Barrage is not sensitive to changes to the Cd value, and is mitigated through the continual, rather than instantaneous, discharge across the structure. The EFDC CSM can now be said to be more accurately predicting the impacts of tidal range proposals, and the investigation of sensitivity to Cd improves the confidence in the modelling results, despite the uncertainty in this coefficient.

Parents who influence their children to become scientists: effects of gender and parental education.

PubMed

Sonnert, Gerhard

2009-12-01

In this paper we report on testing the 'role-model' and 'opportunity-structure' hypotheses about the parents whom scientists mentioned as career influencers. According to the role-model hypothesis, the gender match between scientist and influencer is paramount (for example, women scientists would disproportionately often mention their mothers as career influencers). According to the opportunity-structure hypothesis, the parent's educational level predicts his/her probability of being mentioned as a career influencer (that is, parents with higher educational levels would be more likely to be named). The examination of a sample of American scientists who had received prestigious postdoctoral fellowships resulted in rejecting the role-model hypothesis and corroborating the opportunity-structure hypothesis. There were a few additional findings. First, women scientists were more likely than men scientists to mention parental influencers. Second, fathers were more likely than mothers to be mentioned as influencers. Third, an interaction was found between the scientist's gender and parental education when predicting a parent's nomination as influencer.

The Structure of Morpho-Functional Conditions Determining the Level of Sports Performance of Young Badminton Players

PubMed Central

Jaworski, Janusz; Żak, Michał

2015-01-01

The aim of the study was to determine the structure of morpho-functional models that determine the level of sports performance in three consecutive stages of training of young badminton players. In the course of the study, 3 groups of young badminton players were examined: 40 preadolescents aged 11–13, 32 adolescents aged 14–16, and 24 adolescents aged 17–19. The scope of the study involved basic anthropometric measurements, computer tests analysing motor coordination abilities, motor skills encompassing speed, muscular power and strength, and cardiorespiratory endurance. Results of the study indicate that the structure of morpho-functional models varies at different stages of sports training. Sets of variables determining sports performance create characteristic complexes of variables that do not constitute permanent models. The dominance of somatic features and coordination abilities in the early stages of badminton training changes for the benefit of speed and strength abilities. PMID:26557205

IB2d: a Python and MATLAB implementation of the immersed boundary method.

PubMed

Battista, Nicholas A; Strickland, W Christopher; Miller, Laura A

2017-03-29

The development of fluid-structure interaction (FSI) software involves trade-offs between ease of use, generality, performance, and cost. Typically there are large learning curves when using low-level software to model the interaction of an elastic structure immersed in a uniform density fluid. Many existing codes are not publicly available, and the commercial software that exists usually requires expensive licenses and may not be as robust or allow the necessary flexibility that in house codes can provide. We present an open source immersed boundary software package, IB2d, with full implementations in both MATLAB and Python, that is capable of running a vast range of biomechanics models and is accessible to scientists who have experience in high-level programming environments. IB2d contains multiple options for constructing material properties of the fiber structure, as well as the advection-diffusion of a chemical gradient, muscle mechanics models, and artificial forcing to drive boundaries with a preferred motion.

A Framework for Performing Multiscale Stochastic Progressive Failure Analysis of Composite Structures

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M.

2006-01-01

A framework is presented that enables coupled multiscale analysis of composite structures. The recently developed, free, Finite Element Analysis - Micromechanics Analysis Code (FEAMAC) software couples the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) with ABAQUS to perform micromechanics based FEA such that the nonlinear composite material response at each integration point is modeled at each increment by MAC/GMC. As a result, the stochastic nature of fiber breakage in composites can be simulated through incorporation of an appropriate damage and failure model that operates within MAC/GMC on the level of the fiber. Results are presented for the progressive failure analysis of a titanium matrix composite tensile specimen that illustrate the power and utility of the framework and address the techniques needed to model the statistical nature of the problem properly. In particular, it is shown that incorporating fiber strength randomness on multiple scales improves the quality of the simulation by enabling failure at locations other than those associated with structural level stress risers.

A Framework for Performing Multiscale Stochastic Progressive Failure Analysis of Composite Structures

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M.

2007-01-01

A framework is presented that enables coupled multiscale analysis of composite structures. The recently developed, free, Finite Element Analysis-Micromechanics Analysis Code (FEAMAC) software couples the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) with ABAQUS to perform micromechanics based FEA such that the nonlinear composite material response at each integration point is modeled at each increment by MAC/GMC. As a result, the stochastic nature of fiber breakage in composites can be simulated through incorporation of an appropriate damage and failure model that operates within MAC/GMC on the level of the fiber. Results are presented for the progressive failure analysis of a titanium matrix composite tensile specimen that illustrate the power and utility of the framework and address the techniques needed to model the statistical nature of the problem properly. In particular, it is shown that incorporating fiber strength randomness on multiple scales improves the quality of the simulation by enabling failure at locations other than those associated with structural level stress risers.

Electron-Impact Excitation Cross Sections for Modeling Non-Equilibrium Gas

NASA Technical Reports Server (NTRS)

Huo, Winifred M.; Liu, Yen; Panesi, Marco; Munafo, Alessandro; Wray, Alan; Carbon, Duane F.

2015-01-01

In order to provide a database for modeling hypersonic entry in a partially ionized gas under non-equilibrium, the electron-impact excitation cross sections of atoms have been calculated using perturbation theory. The energy levels covered in the calculation are retrieved from the level list in the HyperRad code. The downstream flow-field is determined by solving a set of continuity equations for each component. The individual structure of each energy level is included. These equations are then complemented by the Euler system of equations. Finally, the radiation field is modeled by solving the radiative transfer equation.

Capturing the Energy Absorbing Mechanisms of Composite Structures under Crash Loading

NASA Astrophysics Data System (ADS)

Wade, Bonnie

As fiber reinforced composite material systems become increasingly utilized in primary aircraft and automotive structures, the need to understand their contribution to the crashworthiness of the structure is of great interest to meet safety certification requirements. The energy absorbing behavior of a composite structure, however, is not easily predicted due to the great complexity of the failure mechanisms that occur within the material. Challenges arise both in the experimental characterization and in the numerical modeling of the material/structure combination. At present, there is no standardized test method to characterize the energy absorbing capability of composite materials to aide crashworthy structural design. In addition, although many commercial finite element analysis codes exist and offer a means to simulate composite failure initiation and propagation, these models are still under development and refinement. As more metallic structures are replaced by composite structures, the need for both experimental guidelines to characterize the energy absorbing capability of a composite structure, as well as guidelines for using numerical tools to simulate composite materials in crash conditions has become a critical matter. This body of research addresses both the experimental characterization of the energy absorption mechanisms occurring in composite materials during crushing, as well as the numerical simulation of composite materials undergoing crushing. In the experimental investigation, the specific energy absorption (SEA) of a composite material system is measured using a variety of test element geometries, such as corrugated plates and tubes. Results from several crush experiments reveal that SEA is not a constant material property for laminated composites, and varies significantly with the geometry of the test specimen used. The variation of SEA measured for a single material system requires that crush test data must be generated for a range of different test geometries in order to define the range of its energy absorption capability. Further investigation from the crush tests has led to the development of a direct link between geometric features of the crush specimen and its resulting SEA. Through micrographic analysis, distinct failure modes are shown to be guided by the geometry of the specimen, and subsequently are shown to directly influence energy absorption. A new relationship between geometry, failure mode, and SEA has been developed. This relationship has allowed for the reduction of the element-level crush testing requirement to characterize the composite material energy absorption capability. In the numerical investigation, the LS-DYNA composite material model MAT54 is selected for its suitability to model composite materials beyond failure determination, as required by crush simulation, and its capability to remain within the scope of ultimately using this model for large-scale crash simulation. As a result of this research, this model has been thoroughly investigated in depth for its capacity to simulate composite materials in crush, and results from several simulations of the element-level crush experiments are presented. A modeling strategy has been developed to use MAT54 for crush simulation which involves using the experimental data collected from the coupon- and element-level crush tests to directly calibrate the crush damage parameter in MAT54 such that it may be used in higher-level simulations. In addition, the source code of the material model is modified to improve upon its capability. The modifications include improving the elastic definition such that the elastic response to multi-axial load cases can be accurately portrayed simultaneously in each element, which is a capability not present in other composite material models. Modifications made to the failure determination and post-failure model have newly emphasized the post-failure stress degradation scheme rather than the failure criterion which is traditionally considered the most important composite material model definition for crush simulation. The modification efforts have also validated the use of the MAT54 failure criterion and post-failure model for crash modeling when its capabilities and limitations are well understood, and for this reason guidelines for using MAT54 for composite crush simulation are presented. This research has effectively (a) developed and demonstrated a procedure that defines a set of experimental crush results that characterize the energy absorption capability of a composite material system, (b) used the experimental results in the development and refinement of a composite material model for crush simulation, (c) explored modifying the material model to improve its use in crush modeling, and (d) provided experimental and modeling guidelines for composite structures under crush at the element-level in the scope of the Building Block Approach.

The measurement equivalence of Big Five factor markers for persons with different levels of education.

PubMed

Rammstedt, Beatrice; Goldberg, Lewis R; Borg, Ingwer

2010-02-01

Previous findings suggest that the Big-Five factor structure is not guaranteed in samples with lower educational levels. The present study investigates the Big-Five factor structure in two large samples representative of the German adult population. In both samples, the Big-Five factor structure emerged only in a blurry way at lower educational levels, whereas for highly educated persons it emerged with textbook-like clarity. Because well-educated persons are most comparable to the usual subjects of psychological research, it might be asked if the Big Five are limited to such persons. Our data contradict this conclusion. There are strong individual differences in acquiescence response tendencies among less highly educated persons. After controlling for this bias the Big-Five model holds at all educational levels.

Aeroelastic Modeling of a Nozzle Startup Transient

NASA Technical Reports Server (NTRS)

Wang, Ten-See; Zhao, Xiang; Zhang, Sijun; Chen, Yen-Sen

2014-01-01

Lateral nozzle forces are known to cause severe structural damage to any new rocket engine in development during test. While three-dimensional, transient, turbulent, chemically reacting computational fluid dynamics methodology has been demonstrated to capture major side load physics with rigid nozzles, hot-fire tests often show nozzle structure deformation during major side load events, leading to structural damages if structural strengthening measures were not taken. The modeling picture is incomplete without the capability to address the two-way responses between the structure and fluid. The objective of this study is to develop a tightly coupled aeroelastic modeling algorithm by implementing the necessary structural dynamics component into an anchored computational fluid dynamics methodology. The computational fluid dynamics component is based on an unstructured-grid, pressure-based computational fluid dynamics formulation, while the computational structural dynamics component is developed under the framework of modal analysis. Transient aeroelastic nozzle startup analyses at sea level were performed, and the computed transient nozzle fluid-structure interaction physics presented,

Universal Session-Level Change Processes in an Early Session of Psychotherapy: Path Models

ERIC Educational Resources Information Center

Kolden, Gregory G.; Chisholm-Stockard, Sarah M.; Strauman, Timothy J.; Tierney, Sandy C.; Mullen, Elizabeth A.; Schneider, Kristin L.

2006-01-01

The authors used structural equation modeling to investigate universal change processes identified in the generic model of psychotherapy (GMP). Three path models of increasing complexity were examined in Study 1 in dynamic therapy. The best fitting model from Study one was replicated in Study two for participants receiving either cognitive or…

The mental health continuum-short form: The structure and application for cross-cultural studies-A 38 nation study.

PubMed

Żemojtel-Piotrowska, Magdalena; Piotrowski, Jarosław P; Osin, Evgeny N; Cieciuch, Jan; Adams, Byron G; Ardi, Rahkman; Bălţătescu, Sergiu; Bogomaz, Sergey; Bhomi, Arbinda Lal; Clinton, Amanda; de Clunie, Gisela T; Czarna, Anna Z; Esteves, Carla; Gouveia, Valdiney; Halik, Murnizam H J; Hosseini, Ashraf; Khachatryan, Narine; Kamble, Shanmukh Vasant; Kawula, Anna; Lun, Vivian Miu-Chi; Ilisko, Dzintra; Klicperova-Baker, Martina; Liik, Kadi; Letovancova, Eva; Cerrato, Sara Malo; Michalowski, Jaroslaw; Malysheva, Natalia; Marganski, Alison; Nikolic, Marija; Park, Joonha; Paspalanova, Elena; de Leon, Pablo Perez; Pék, Győző; Różycka-Tran, Joanna; Samekin, Adil; Shahbaz, Wahab; Khanh Ha, Truong Thi; Tiliouine, Habib; Van Hiel, Alain; Vauclair, Melanie; Wills-Herrera, Eduardo; Włodarczyk, Anna; Yahiiaev, Illia; Maltby, John

2018-06-01

The Mental Health Continuum-Short Form (MHC-SF) is a brief scale measuring positive human functioning. The study aimed to examine the factor structure and to explore the cross-cultural utility of the MHC-SF using bifactor models and exploratory structural equation modelling. Using multigroup confirmatory analysis (MGCFA) we examined the measurement invariance of the MHC-SF in 38 countries (university students, N = 8,066; 61.73% women, mean age 21.55 years). MGCFA supported the cross-cultural replicability of a bifactor structure and a metric level of invariance between student samples. The average proportion of variance explained by the general factor was high (ECV = .66), suggesting that the three aspects of mental health (emotional, social, and psychological well-being) can be treated as a single dimension of well-being. The metric level of invariance offers the possibility of comparing correlates and predictors of positive mental functioning across countries; however, the comparison of the levels of mental health across countries is not possible due to lack of scalar invariance. Our study has preliminary character and could serve as an initial assessment of the structure of the MHC-SF across different cultural settings. Further studies on general populations are required for extending our findings. © 2018 Wiley Periodicals, Inc.

Hispanic ethnicity and Caucasian race: Relations with posttraumatic stress disorder's factor structure in clinic-referred youth.

PubMed

Contractor, Ateka A; Claycomb, Meredith A; Byllesby, Brianna M; Layne, Christopher M; Kaplow, Julie B; Steinberg, Alan M; Elhai, Jon D

2015-09-01

The severity of posttraumatic stress disorder (PTSD) symptoms is linked to race and ethnicity, albeit with contradictory findings (reviewed in Alcántara, Casement, & Lewis-Fernández, 2013; Pole, Gone, & Kulkarni, 2008). We systematically examined Caucasian (n = 3,767) versus non-Caucasian race (n = 2,824) and Hispanic (n = 2,395) versus non-Hispanic ethnicity (n = 3,853) as candidate moderators of PTSD's 5-factor model structural parameters (Elhai et al., 2013). The sample was drawn from the National Child Traumatic Stress Network's Core Data Set, currently the largest national data set of clinic-referred children and adolescents exposed to potentially traumatic events. Using confirmatory factor analysis, we tested the invariance of PTSD symptom structural parameters by race and ethnicity. Chi-square difference tests and goodness-of-fit values showed statistical equivalence across racial and ethnic groups in the factor structure of PTSD and in mean item-level indicators of PTSD symptom severity. Results support the structural invariance of PTSD's 5-factor model across the compared racial and ethnic groups. Furthermore, results indicated equivalent item-level severity across racial and ethnic groups; this supports the use of item-level comparisons across these groups. (c) 2015 APA, all rights reserved).

Observed and modeled patterns of covariability between low-level cloudiness and the structure of the trade-wind layer

DOE PAGES

Nuijens, Louise; Medeiros, Brian; Sandu, Irina; ...

2015-11-06

We present patterns of covariability between low-level cloudiness and the trade-wind boundary layer structure using long-term measurements at a site representative of dynamical regimes with moderate subsidence or weak ascent. We compare these with ECMWF’s Integrated Forecast System and 10 CMIP5 models. By using single-time step output at a single location, we find that models can produce a fairly realistic trade-wind layer structure in long-term means, but with unrealistic variability at shorter-time scales. The unrealistic variability in modeled cloudiness near the lifting condensation level (LCL) is due to stronger than observed relationships with mixed-layer relative humidity (RH) and temperature stratificationmore » at the mixed-layer top. Those relationships are weak in observations, or even of opposite sign, which can be explained by a negative feedback of convection on cloudiness. Cloudiness near cumulus tops at the tradewind inversion instead varies more pronouncedly in observations on monthly time scales, whereby larger cloudiness relates to larger surface winds and stronger trade-wind inversions. However, these parameters appear to be a prerequisite, rather than strong controlling factors on cloudiness, because they do not explain submonthly variations in cloudiness. Models underestimate the strength of these relationships and diverge in particular in their responses to large-scale vertical motion. No model stands out by reproducing the observed behavior in all respects. As a result, these findings suggest that climate models do not realistically represent the physical processes that underlie the coupling between trade-wind clouds and their environments in present-day climate, which is relevant for how we interpret modeled cloud feedbacks.« less

Observed and modeled patterns of covariability between low-level cloudiness and the structure of the trade-wind layer

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

Nuijens, Louise; Medeiros, Brian; Sandu, Irina

We present patterns of covariability between low-level cloudiness and the trade-wind boundary layer structure using long-term measurements at a site representative of dynamical regimes with moderate subsidence or weak ascent. We compare these with ECMWF’s Integrated Forecast System and 10 CMIP5 models. By using single-time step output at a single location, we find that models can produce a fairly realistic trade-wind layer structure in long-term means, but with unrealistic variability at shorter-time scales. The unrealistic variability in modeled cloudiness near the lifting condensation level (LCL) is due to stronger than observed relationships with mixed-layer relative humidity (RH) and temperature stratificationmore » at the mixed-layer top. Those relationships are weak in observations, or even of opposite sign, which can be explained by a negative feedback of convection on cloudiness. Cloudiness near cumulus tops at the tradewind inversion instead varies more pronouncedly in observations on monthly time scales, whereby larger cloudiness relates to larger surface winds and stronger trade-wind inversions. However, these parameters appear to be a prerequisite, rather than strong controlling factors on cloudiness, because they do not explain submonthly variations in cloudiness. Models underestimate the strength of these relationships and diverge in particular in their responses to large-scale vertical motion. No model stands out by reproducing the observed behavior in all respects. As a result, these findings suggest that climate models do not realistically represent the physical processes that underlie the coupling between trade-wind clouds and their environments in present-day climate, which is relevant for how we interpret modeled cloud feedbacks.« less

The Sensitivity of Glacial Isostatic Adjustment in West Antarctica to Lateral Variations in Earth Structure

NASA Astrophysics Data System (ADS)

Nield, G.; Whitehouse, P. L.; Blank, B.; van der Wal, W.; O'Donnell, J. P.; Stuart, G. W.; Lloyd, A. J.; Wiens, D.

2017-12-01

Accurate models of Glacial Isostatic Adjustment (GIA) are required for correcting satellite measurements of ice-mass change and for interpretation of geodetic data at the location of present and former ice sheets. Global models of GIA tend to adopt a 1-D representation of Earth structure, varying in the radial direction only. In some regions rheological parameters may differ significantly from this global average leading to bias in model predictions of present-day deformation, geoid change rates and sea-level change. The advancement of 3-D GIA modelling techniques in recent years has led to improvements in the representation of the Earth via the incorporation of laterally varying structure. This study investigates the influence of 3-D Earth structure on deformation rates in West Antarctica using a finite element GIA model with power-law rheology. We utilise datasets of seismic velocity and temperature for the crust and upper mantle with the aim of determining a data-driven Earth model, and consider the differences when compared to deformation predicted from an equivalent 1-D Earth structure.

Optimum element density studies for finite-element thermal analysis of hypersonic aircraft structures

NASA Technical Reports Server (NTRS)

Ko, William L.; Olona, Timothy; Muramoto, Kyle M.

1990-01-01

Different finite element models previously set up for thermal analysis of the space shuttle orbiter structure are discussed and their shortcomings identified. Element density criteria are established for the finite element thermal modelings of space shuttle orbiter-type large, hypersonic aircraft structures. These criteria are based on rigorous studies on solution accuracies using different finite element models having different element densities set up for one cell of the orbiter wing. Also, a method for optimization of the transient thermal analysis computer central processing unit (CPU) time is discussed. Based on the newly established element density criteria, the orbiter wing midspan segment was modeled for the examination of thermal analysis solution accuracies and the extent of computation CPU time requirements. The results showed that the distributions of the structural temperatures and the thermal stresses obtained from this wing segment model were satisfactory and the computation CPU time was at the acceptable level. The studies offered the hope that modeling the large, hypersonic aircraft structures using high-density elements for transient thermal analysis is possible if a CPU optimization technique was used.

COMMUNITY LEVEL ANALYSIS OF VECTOR-BORNE DISEASE

EPA Science Inventory

Ecological community structure is particularly important in vector-borne zoonotic diseases with complex life cycles. Single population models, such as the so-called Ross-Macdonald model (Baily, 1982), have been important in developing and characterizing our current understanding...

Construction and evaluation of thoracic injury risk curves for a finite element human body model in frontal car crashes.

PubMed

Mendoza-Vazquez, Manuel; Davidsson, Johan; Brolin, Karin

2015-12-01

There is a need to improve the protection to the thorax of occupants in frontal car crashes. Finite element human body models are a more detailed representation of humans than anthropomorphic test devices (ATDs). On the other hand, there is no clear consensus on the injury criteria and the thresholds to use with finite element human body models to predict rib fractures. The objective of this study was to establish a set of injury risk curves to predict rib fractures using a modified Total HUman Model for Safety (THUMS). Injury criteria at the global, structural and material levels were computed with a modified THUMS in matched Post Mortem Human Subjects (PMHSs) tests. Finally, the quality of each injury risk curve was determined. For the included PMHS tests and the modified THUMS, DcTHOR and shear stress were the criteria at the global and material levels that reached an acceptable quality. The injury risk curves at the structural level did not reach an acceptable quality. Copyright © 2015 Elsevier Ltd. All rights reserved.

Role of beach morphology in wave overtopping hazard assessment

NASA Astrophysics Data System (ADS)

Phillips, Benjamin; Brown, Jennifer; Bidlot, Jean-Raymond; Plater, Andrew

2017-04-01

Understanding the role of beach morphology in controlling wave overtopping volume will further minimise uncertainties in flood risk assessments at coastal locations defended by engineered structures worldwide. XBeach is used to model wave overtopping volume for a 1:200 yr joint probability distribution of waves and water levels with measured, pre- and post-storm beach profiles. The simulation with measured bathymetry is repeated with and without morphological evolution enabled during the modelled storm event. This research assesses the role of morphology in controlling wave overtopping volumes for hazardous events that meet the typical design level of coastal defence structures. Results show disabling storm-driven morphology under-represents modelled wave overtopping volumes by up to 39% under high Hs conditions, and has a greater impact on the wave overtopping rate than the variability applied within the boundary conditions due to the range of wave-water level combinations that meet the 1:200 yr joint probability criterion. Accounting for morphology in flood modelling is therefore critical for accurately predicting wave overtopping volumes and the resulting flood hazard and to assess economic losses.

Construction, MD simulation, and hydrodynamic validation of an all-atom model of a monoclonal IgG antibody.

PubMed

Brandt, J Paul; Patapoff, Thomas W; Aragon, Sergio R

2010-08-04

At 150 kDa, antibodies of the IgG class are too large for their structure to be determined with current NMR methodologies. Because of hinge-region flexibility, it is difficult to obtain atomic-level structural information from the crystal, and questions regarding antibody structure and dynamics in solution remain unaddressed. Here we describe the construction of a model of a human IgG1 monoclonal antibody (trastuzumab) from the crystal structures of fragments. We use a combination of molecular-dynamics (MD) simulation, continuum hydrodynamics modeling, and experimental diffusion measurements to explore antibody behavior in aqueous solution. Hydrodynamic modeling provides a link between the atomic-level details of MD simulation and the size- and shape-dependent data provided by hydrodynamic measurements. Eight independent 40 ns MD trajectories were obtained with the AMBER program suite. The ensemble average of the computed transport properties over all of the MD trajectories agrees remarkably well with the value of the translational diffusion coefficient obtained with dynamic light scattering at 20 degrees C and 27 degrees C, and the intrinsic viscosity measured at 20 degrees C. Therefore, our MD results likely represent a realistic sampling of the conformational space that an antibody explores in aqueous solution. 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Structure analysis for hole-nuclei close to 132Sn by a large-scale shell-model calculation

NASA Astrophysics Data System (ADS)

Wang, Han-Kui; Sun, Yang; Jin, Hua; Kaneko, Kazunari; Tazaki, Shigeru

2013-11-01

The structure of neutron-rich nuclei with a few holes in respect of the doubly magic nucleus 132Sn is investigated by means of large-scale shell-model calculations. For a considerably large model space, including orbitals allowing both neutron and proton core excitations, an effective interaction for the extended pairing-plus-quadrupole model with monopole corrections is tested through detailed comparison between the calculation and experimental data. By using the experimental energy of the core-excited 21/2+ level in 131In as a benchmark, monopole corrections are determined that describe the size of the neutron N=82 shell gap. The level spectra, up to 5 MeV of excitation in 131In, 131Sn, 130In, 130Cd, and 130Sn, are well described and clearly explained by couplings of single-hole orbitals and by core excitations.

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…

A deep structural ridge beneath central India

NASA Astrophysics Data System (ADS)

Agrawal, P. K.; Thakur, N. K.; Negi, J. G.

A joint-inversion of magnetic satellite (MAGSAT) and free air gravity data has been conducted to quantitatively investigate the cause for Bouguer gravity anomaly over Central Indian plateaus and possible fold consequences beside Himalayan zone in the Indian sub-continent due to collision between Indian and Eurasian plates. The appropriate inversion with 40 km crustal depth model has delineated after discriminating high density and magnetisation models, for the first time, about 1500 km long hidden ridge structure trending NW-SE. The structure is parallel to Himalayan fold axis and the Indian Ocean ridge in the Arabian Sea. A quantitative relief model across a representative anomaly profile confirms the ridge structure with its highest point nearly 6 km higher than the surrounding crustal level in peninsular India. The ridge structure finds visible support from the astro-geoidal contours.

A Multivariate Model of Physics Problem Solving

ERIC Educational Resources Information Center

Taasoobshirazi, Gita; Farley, John

2013-01-01

A model of expertise in physics problem solving was tested on undergraduate science, physics, and engineering majors enrolled in an introductory-level physics course. Structural equation modeling was used to test hypothesized relationships among variables linked to expertise in physics problem solving including motivation, metacognitive planning,…

Logic Models: A Tool for Effective Program Planning, Collaboration, and Monitoring. REL 2014-025

ERIC Educational Resources Information Center

Kekahio, Wendy; Lawton, Brian; Cicchinelli, Louis; Brandon, Paul R.

2014-01-01

A logic model is a visual representation of the assumptions and theory of action that underlie the structure of an education program. A program can be a strategy for instruction in a classroom, a training session for a group of teachers, a grade-level curriculum, a building-level intervention, or a district-or statewide initiative. This guide, an…

Neutrino mass in flavor dependent gauged lepton model

NASA Astrophysics Data System (ADS)

Nomura, Takaaki; Okada, Hiroshi

2018-03-01

We study a neutrino model introducing an additional nontrivial gauged lepton symmetry where the neutrino masses are induced at two-loop level, while the first and second charged-leptons of the standard model are done at one-loop level. As a result of the model structure, we can predict one massless active neutrino, and there is a dark matter candidate. Then we discuss the neutrino mass matrix, muon anomalous magnetic moment, lepton flavor violations, oblique parameters, and relic density of dark matter, taking into account the experimental constraints.

Damage Tolerance of Large Shell Structures

NASA Technical Reports Server (NTRS)

Minnetyan, L.; Chamis, C. C.

1999-01-01

Progressive damage and fracture of large shell structures is investigated. A computer model is used for the assessment of structural response, progressive fracture resistance, and defect/damage tolerance characteristics. Critical locations of a stiffened conical shell segment are identified. Defective and defect-free computer models are simulated to evaluate structural damage/defect tolerance. Safe pressurization levels are assessed for the retention of structural integrity at the presence of damage/ defects. Damage initiation, growth, accumulation, and propagation to fracture are included in the simulations. Damage propagation and burst pressures for defective and defect-free shells are compared to evaluate damage tolerance. Design implications with regard to defect and damage tolerance of a large steel pressure vessel are examined.

A flexural crack model for damage detection in reinforced concrete structures

NASA Astrophysics Data System (ADS)

Hamad, W. I.; Owen, J. S.; Hussein, M. F. M.

2011-07-01

The use of changes in vibration data for damage detection of reinforced concrete structures faces many challenges that obstruct its transition from a research topic to field applications. Among these is the lack of appropriate damage models that can be deployed in the damage detection methods. In this paper, a model of a simply supported reinforced concrete beam with multiple cracks is developed to examine its use for damage detection and structural health monitoring. The cracks are simulated by a model that accounts for crack formation, propagation and closure. The beam model is studied under different dynamic excitations, including sine sweep and single excitation frequency, for various damage levels. The changes in resonant frequency with increasing loads are examined along with the nonlinear vibration characteristics. The model demonstrates that the resonant frequency reduces by about 10% at the application of 30% of the ultimate load and then drops gradually by about 25% at 70% of the ultimate load. The model also illustrates some nonlinearity in the dynamic response of damaged beams. The appearance of super-harmonics shows that the nonlinearity is higher when the damage level is about 35% and then decreases with increasing damage. The restoring force-displacement relationship predicted the reduction in the overall stiffness of the damaged beam. The model quantitatively predicts the experimental vibration behaviour of damaged RC beams and also shows the damage dependency of nonlinear vibration behaviour.

Ground-Level Digital Terrain Model (DTM) Construction from Tandem-X InSAR Data and Worldview Stereo-Photogrammetric Images

NASA Technical Reports Server (NTRS)

Lee, Seung-Kuk; Fatoyinbo, Temilola; Lagomasino, David; Osmanoglu, Batuhan; Feliciano, Emanuelle

2016-01-01

The ground-level digital elevation model (DEM) or digital terrain model (DTM) information are invaluable for environmental modeling, such as water dynamics in forests, canopy height, forest biomass, carbon estimation, etc. We propose to extract the DTM over forested areas from the combination of interferometric complex coherence from single-pass TanDEM-X (TDX) data at HH polarization and Digital Surface Model (DSM) derived from high-resolution WorldView (WV) image pair by means of random volume over ground (RVoG) model. The RVoG model is a widely and successfully used model for polarimetric SAR interferometry (Pol-InSAR) technique for vertical forest structure parameter retrieval [1][2][3][4]. The ground-level DEM have been obtained by complex volume decorrelation in the RVoG model with the DSM using stereo-photogrammetric technique. Finally, the airborne lidar data were used to validate the ground-level DEM and forest canopy height results.

Self-Efficacy, School Resources, Job Stressors and Burnout among Spanish Primary and Secondary School Teachers: A Structural Equation Approach

ERIC Educational Resources Information Center

Betoret, Fernando Domenech

2009-01-01

This study examines the relationship between school resources, teacher self-efficacy, potential multi-level stressors and teacher burnout using structural equation modelling. The causal structure for primary and secondary school teachers was also examined. The sample was composed of 724 primary and secondary Spanish school teachers. The changes…

Using Molecular Visualization to Explore Protein Structure and Function and Enhance Student Facility with Computational Tools

ERIC Educational Resources Information Center

Terrell, Cassidy R.; Listenberger, Laura L.

2017-01-01

Recognizing that undergraduate students can benefit from analysis of 3D protein structure and function, we have developed a multiweek, inquiry-based molecular visualization project for Biochemistry I students. This project uses a virtual model of cyclooxygenase-1 (COX-1) to guide students through multiple levels of protein structure analysis. The…

Spatial-structural analysis of leafless woody riparian vegetation for hydraulic considerations

NASA Astrophysics Data System (ADS)

Weissteiner, Clemens; Jalonen, Johanna; Järvelä, Juha; Rauch, Hans Peter

2013-04-01

Woody riparian vegetation is a vital element of riverine environments. On one hand woody riparian vegetation has to be taken into account from a civil engineering point of view due to boundary shear stress and vegetation drag. On the other hand it has to be considered from a river ecological point of view due to shadowing effects and as a source of organic material for aquatic habitats. In hydrodynamic and hydro-ecological studies the effects of woody riparian vegetation on flow patterns are usually investigated on a very detailed level. On the contrary vegetation elements and their spatial patterns are generally analysed and discussed on the basis of an integral approach measuring for example basal diameters, heights and projected plant areas. For a better understanding of the influence of woody riparian vegetation on turbulent flow and on river ecology, it is essential to record and analyse plant data sets on the same level of quality as for hydrodynamic or hydro-ecologic purposes. As a result of the same scale of the analysis it is possible to incorporate riparian vegetation as a sub-model in the hydraulic analysis. For plant structural components, such as branches on different topological levels it is crucial to record plant geometrical parameters describing the habitus of the plant on branch level. An exact 3D geometrical model of real plants allows for an extraction of various spatial-structural plant parameters. In addition, allometric relationships help to summarize and describe plant traits of riparian vegetation. This paper focuses on the spatial-structural composition of leafless riparia woddy vegetation. Structural and spatial analyses determine detailed geometric properties of the structural components of the plants. Geometrical and topological parameters were recorded with an electro-magnetic scanning device. In total, 23 plants (willows, alders and birches) were analysed in the study. Data were recorded on branch level, which allowed for the development of a 3D geometric plant model. The results are expected to improve knowledge on how the architectural system and allometric relationships of the plants relate to ecological and hydrodynamic properties.

Structure prediction of the second extracellular loop in G-protein-coupled receptors.

PubMed

Kmiecik, Sebastian; Jamroz, Michal; Kolinski, Michal

2014-06-03

G-protein-coupled receptors (GPCRs) play key roles in living organisms. Therefore, it is important to determine their functional structures. The second extracellular loop (ECL2) is a functionally important region of GPCRs, which poses significant challenge for computational structure prediction methods. In this work, we evaluated CABS, a well-established protein modeling tool for predicting ECL2 structure in 13 GPCRs. The ECL2s (with between 13 and 34 residues) are predicted in an environment of other extracellular loops being fully flexible and the transmembrane domain fixed in its x-ray conformation. The modeling procedure used theoretical predictions of ECL2 secondary structure and experimental constraints on disulfide bridges. Our approach yielded ensembles of low-energy conformers and the most populated conformers that contained models close to the available x-ray structures. The level of similarity between the predicted models and x-ray structures is comparable to that of other state-of-the-art computational methods. Our results extend other studies by including newly crystallized GPCRs. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Friendship Network and Dental Brushing Behavior among Middle School Students: An Agent Based Modeling Approach.

PubMed

Sadeghipour, Maryam; Khoshnevisan, Mohammad Hossein; Jafari, Afshin; Shariatpanahi, Seyed Peyman

2017-01-01

By using a standard questionnaire, the level of dental brushing frequency was assessed among 201 adolescent female middle school students in Tehran. The initial assessment was repeated after 5 months, in order to observe the dynamics in dental health behavior level. Logistic Regression model was used to evaluate the correlation among individuals' dental health behavior in their social network. A significant correlation on dental brushing habits was detected among groups of friends. This correlation was further spread over the network within the 5 months period. Moreover, it was identified that the average brushing level was improved within the 5 months period. Given that there was a significant correlation between social network's nodes' in-degree value, and brushing level, it was suggested that the observed improvement was partially due to more popularity of individuals with better tooth brushing habit. Agent Based Modeling (ABM) was used to demonstrate the dynamics of dental brushing frequency within a sample of friendship network. Two models with static and dynamic assumptions for the network structure were proposed. The model with dynamic network structure successfully described the dynamics of dental health behavior. Based on this model, on average, every 43 weeks a student changes her brushing habit due to learning from her friends. Finally, three training scenarios were tested by these models in order to evaluate their effectiveness. When training more popular students, considerable improvement in total students' brushing frequency was demonstrated by simulation results.

A Deep Neural Network Model for Rainfall Estimation UsingPolarimetric WSR-88DP Radar Observations

NASA Astrophysics Data System (ADS)

Tan, H.; Chandra, C. V.; Chen, H.

2016-12-01

Rainfall estimation based on radar measurements has been an important topic for a few decades. Generally, radar rainfall estimation is conducted through parametric algorisms such as reflectivity-rainfall relation (i.e., Z-R relation). On the other hand, neural networks are developed for ground rainfall estimation based on radar measurements. This nonparametric method, which takes into account of both radar observations and rainfall measurements from ground rain gauges, has been demonstrated successfully for rainfall rate estimation. However, the neural network-based rainfall estimation is limited in practice due to the model complexity and structure, data quality, as well as different rainfall microphysics. Recently, the deep learning approach has been introduced in pattern recognition and machine learning areas. Compared to traditional neural networks, the deep learning based methodologies have larger number of hidden layers and more complex structure for data representation. Through a hierarchical learning process, the high level structured information and knowledge can be extracted automatically from low level features of the data. In this paper, we introduce a novel deep neural network model for rainfall estimation based on ground polarimetric radar measurements .The model is designed to capture the complex abstractions of radar measurements at different levels using multiple layers feature identification and extraction. The abstractions at different levels can be used independently or fused with other data resource such as satellite-based rainfall products and/or topographic data to represent the rain characteristics at certain location. In particular, the WSR-88DP radar and rain gauge data collected in Dallas - Fort Worth Metroplex and Florida are used extensively to train the model, and for demonstration purposes. Quantitative evaluation of the deep neural network based rainfall products will also be presented, which is based on an independent rain gauge network.

Applying spatio-temporal models to assess variations across health care areas and regions: Lessons from the decentralized Spanish National Health System.

PubMed

Librero, Julián; Ibañez, Berta; Martínez-Lizaga, Natalia; Peiró, Salvador; Bernal-Delgado, Enrique

2017-01-01

To illustrate the ability of hierarchical Bayesian spatio-temporal models in capturing different geo-temporal structures in order to explain hospital risk variations using three different conditions: Percutaneous Coronary Intervention (PCI), Colectomy in Colorectal Cancer (CCC) and Chronic Obstructive Pulmonary Disease (COPD). This is an observational population-based spatio-temporal study, from 2002 to 2013, with a two-level geographical structure, Autonomous Communities (AC) and Health Care Areas (HA). The Spanish National Health System, a quasi-federal structure with 17 regional governments (AC) with full responsibility in planning and financing, and 203 HA providing hospital and primary care to a defined population. A poisson-log normal mixed model in the Bayesian framework was fitted using the INLA efficient estimation procedure. The spatio-temporal hospitalization relative risks, the evolution of their variation, and the relative contribution (fraction of variation) of each of the model components (AC, HA, year and interaction AC-year). Following PCI-CCC-CODP order, the three conditions show differences in the initial hospitalization rates (from 4 to 21 per 10,000 person-years) and in their trends (upward, inverted V shape, downward). Most of the risk variation is captured by phenomena occurring at the HA level (fraction variance: 51.6, 54.7 and 56.9%). At AC level, the risk of PCI hospitalization follow a heterogeneous ascending dynamic (interaction AC-year: 17.7%), whereas in COPD the AC role is more homogenous and important (37%). In a system where the decisions loci are differentiated, the spatio-temporal modeling allows to assess the dynamic relative role of different levels of decision and their influence on health outcomes.

Genetic diversity and population structure among six cattle breeds in South Africa using a whole genome SNP panel

PubMed Central

Makina, Sithembile O.; Muchadeyi, Farai C.; van Marle-Köster, Este; MacNeil, Michael D.; Maiwashe, Azwihangwisi

2014-01-01

Information about genetic diversity and population structure among cattle breeds is essential for genetic improvement, understanding of environmental adaptation as well as utilization and conservation of cattle breeds. This study investigated genetic diversity and the population structure among six cattle breeds in South African (SA) including Afrikaner (n = 44), Nguni (n = 54), Drakensberger (n = 47), Bonsmara (n = 44), Angus (n = 31), and Holstein (n = 29). Genetic diversity within cattle breeds was analyzed using three measures of genetic diversity namely allelic richness (AR), expected heterozygosity (He) and inbreeding coefficient (f). Genetic distances between breed pairs were evaluated using Nei's genetic distance. Population structure was assessed using model-based clustering (ADMIXTURE). Results of this study revealed that the allelic richness ranged from 1.88 (Afrikaner) to 1.73 (Nguni). Afrikaner cattle had the lowest level of genetic diversity (He = 0.24) and the Drakensberger cattle (He = 0.30) had the highest level of genetic variation among indigenous and locally-developed cattle breeds. The level of inbreeding was lower across the studied cattle breeds. As expected the average genetic distance was the greatest between indigenous cattle breeds and Bos taurus cattle breeds but the lowest among indigenous and locally-developed breeds. Model-based clustering revealed some level of admixture among indigenous and locally-developed breeds and supported the clustering of the breeds according to their history of origin. The results of this study provided useful insight regarding genetic structure of SA cattle breeds. PMID:25295053

Genetic diversity and population structure among six cattle breeds in South Africa using a whole genome SNP panel.

PubMed

Makina, Sithembile O; Muchadeyi, Farai C; van Marle-Köster, Este; MacNeil, Michael D; Maiwashe, Azwihangwisi

2014-01-01

Information about genetic diversity and population structure among cattle breeds is essential for genetic improvement, understanding of environmental adaptation as well as utilization and conservation of cattle breeds. This study investigated genetic diversity and the population structure among six cattle breeds in South African (SA) including Afrikaner (n = 44), Nguni (n = 54), Drakensberger (n = 47), Bonsmara (n = 44), Angus (n = 31), and Holstein (n = 29). Genetic diversity within cattle breeds was analyzed using three measures of genetic diversity namely allelic richness (AR), expected heterozygosity (He) and inbreeding coefficient (f). Genetic distances between breed pairs were evaluated using Nei's genetic distance. Population structure was assessed using model-based clustering (ADMIXTURE). Results of this study revealed that the allelic richness ranged from 1.88 (Afrikaner) to 1.73 (Nguni). Afrikaner cattle had the lowest level of genetic diversity (He = 0.24) and the Drakensberger cattle (He = 0.30) had the highest level of genetic variation among indigenous and locally-developed cattle breeds. The level of inbreeding was lower across the studied cattle breeds. As expected the average genetic distance was the greatest between indigenous cattle breeds and Bos taurus cattle breeds but the lowest among indigenous and locally-developed breeds. Model-based clustering revealed some level of admixture among indigenous and locally-developed breeds and supported the clustering of the breeds according to their history of origin. The results of this study provided useful insight regarding genetic structure of SA cattle breeds.

A Structural Equation Model of HIV-related Symptoms, Depressive Symptoms, and Medication Adherence.

PubMed

Yoo-Jeong, Moka; Waldrop-Valverde, Drenna; McCoy, Katryna; Ownby, Raymond L

2016-05-01

Adherence to combined antiretroviral therapy (cART) remains critical in management of HIV infection. This study evaluated depression as a potential mechanism by which HIV-related symptoms affect medication adherence and explored if particular clusters of HIV symptoms are susceptible to this mechanism. Baseline data from a multi-visit intervention study were analyzed among 124 persons living with HIV (PLWH). A bifactor model showed two clusters of HIV-related symptom distress: general HIV-related symptoms and gastrointestinal (GI) symptoms. Structural equation modeling showed that both general HIV-related symptoms and GI symptoms were related to higher levels of depressive symptoms, and higher levels of depressive symptoms were related to lower levels of medication adherence. Although general HIV-related symptoms and GI symptoms were not directly related to adherence, they were indirectly associated with adherence via depression. The findings highlight the importance of early recognition and evaluation of symptoms of depression, as well as the underlying physical symptoms that might cause depression, to improve medication adherence.

A Structural Equation Model of HIV-related Symptoms, Depressive Symptoms, and Medication Adherence

PubMed Central

Yoo-Jeong, Moka; Waldrop-Valverde, Drenna; McCoy, Katryna; Ownby, Raymond L

2016-01-01

Adherence to combined antiretroviral therapy (cART) remains critical in management of HIV infection. This study evaluated depression as a potential mechanism by which HIV-related symptoms affect medication adherence and explored if particular clusters of HIV symptoms are susceptible to this mechanism. Baseline data from a multi-visit intervention study were analyzed among 124 persons living with HIV (PLWH). A bifactor model showed two clusters of HIV-related symptom distress: general HIV-related symptoms and gastrointestinal (GI) symptoms. Structural equation modeling showed that both general HIV-related symptoms and GI symptoms were related to higher levels of depressive symptoms, and higher levels of depressive symptoms were related to lower levels of medication adherence. Although general HIV-related symptoms and GI symptoms were not directly related to adherence, they were indirectly associated with adherence via depression. The findings highlight the importance of early recognition and evaluation of symptoms of depression, as well as the underlying physical symptoms that might cause depression, to improve medication adherence. PMID:27695710

Computing by physical interaction in neurons.

PubMed

Aur, Dorian; Jog, Mandar; Poznanski, Roman R

2011-12-01

The electrodynamics of action potentials represents the fundamental level where information is integrated and processed in neurons. The Hodgkin-Huxley model cannot explain the non-stereotyped spatial charge density dynamics that occur during action potential propagation. Revealed in experiments as spike directivity, the non-uniform charge density dynamics within neurons carry meaningful information and suggest that fragments of information regarding our memories are endogenously stored in structural patterns at a molecular level and are revealed only during spiking activity. The main conceptual idea is that under the influence of electric fields, efficient computation by interaction occurs between charge densities embedded within molecular structures and the transient developed flow of electrical charges. This process of computation underlying electrical interactions and molecular mechanisms at the subcellular level is dissimilar from spiking neuron models that are completely devoid of physical interactions. Computation by interaction describes a more powerful continuous model of computation than the one that consists of discrete steps as represented in Turing machines.

Multi-quasiparticle excitations in145Tb

NASA Astrophysics Data System (ADS)

Zheng, Yong; Zhou, Xiaohong; Zhang, Yuhu; Liu, Minliang; Guo, Yingxiang; Lei, Xiangguo; Hayakawa, T.; Oshima, M.; Toh, T.; Shizuma, T.; Katakura, J.; Hatsukawa, Y.; Matsuda, M.; Kusakari, H.; Sugawara, M.

2004-09-01

High-spin states in145Tb have been populated using the118Sn (32S, 1p4n) reaction at beam energy of 165 MeV. The level scheme of145Tb has been established up to Ex≈7.4 MeV. The level scheme shows characteristics of a spherical or slightly oblate nucleus. Based on the systematic trends of the level structure in the neighboring N=80 isotones, the level structure in145Tb below 2 MeV excitation is well eplained by coupling an h 11/2 valence proton to the even-even144Gd core. Above 2 MeV excitation, most of the yrast levels are interpreted with multi-quasiparticle shell-model configurations.

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

PubMed Central

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

2014-01-01

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

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

PubMed

Wright, Aidan G C; Simms, Leonard J

2014-01-01

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

A matrix dependent/algebraic multigrid approach for extruded meshes with applications to ice sheet modeling

DOE PAGES

Tuminaro, Raymond S.; Perego, Mauro; Tezaur, Irina Kalashnikova; ...

2016-10-06

A multigrid method is proposed that combines ideas from matrix dependent multigrid for structured grids and algebraic multigrid for unstructured grids. It targets problems where a three-dimensional mesh can be viewed as an extrusion of a two-dimensional, unstructured mesh in a third dimension. Our motivation comes from the modeling of thin structures via finite elements and, more specifically, the modeling of ice sheets. Extruded meshes are relatively common for thin structures and often give rise to anisotropic problems when the thin direction mesh spacing is much smaller than the broad direction mesh spacing. Within our approach, the first few multigridmore » hierarchy levels are obtained by applying matrix dependent multigrid to semicoarsen in a structured thin direction fashion. After sufficient structured coarsening, the resulting mesh contains only a single layer corresponding to a two-dimensional, unstructured mesh. Algebraic multigrid can then be employed in a standard manner to create further coarse levels, as the anisotropic phenomena is no longer present in the single layer problem. The overall approach remains fully algebraic, with the minor exception that some additional information is needed to determine the extruded direction. Furthermore, this facilitates integration of the solver with a variety of different extruded mesh applications.« less

On the road to metallic nanoparticles by rational design: bridging the gap between atomic-level theoretical modeling and reality by total scattering experiments.

PubMed

Prasai, Binay; Wilson, A R; Wiley, B J; Ren, Y; Petkov, Valeri

2015-11-14

The extent to which current theoretical modeling alone can reveal real-world metallic nanoparticles (NPs) at the atomic level was scrutinized and demonstrated to be insufficient and how it can be improved by using a pragmatic approach involving straightforward experiments is shown. In particular, 4 to 6 nm in size silica supported Au(100-x)Pd(x) (x = 30, 46 and 58) explored for catalytic applications is characterized structurally by total scattering experiments including high-energy synchrotron X-ray diffraction (XRD) coupled to atomic pair distribution function (PDF) analysis. Atomic-level models for the NPs are built by molecular dynamics simulations based on the archetypal for current theoretical modeling Sutton-Chen (SC) method. Models are matched against independent experimental data and are demonstrated to be inaccurate unless their theoretical foundation, i.e. the SC method, is supplemented with basic yet crucial information on the length and strength of metal-to-metal bonds and, when necessary, structural disorder in the actual NPs studied. An atomic PDF-based approach for accessing such information and implementing it in theoretical modeling is put forward. For completeness, the approach is concisely demonstrated on 15 nm in size water-dispersed Au particles explored for bio-medical applications and 16 nm in size hexane-dispersed Fe48Pd52 particles explored for magnetic applications as well. It is argued that when "tuned up" against experiments relevant to metals and alloys confined to nanoscale dimensions, such as total scattering coupled to atomic PDF analysis, rather than by mere intuition and/or against data for the respective solids, atomic-level theoretical modeling can provide a sound understanding of the synthesis-structure-property relationships in real-world metallic NPs. Ultimately this can help advance nanoscience and technology a step closer to producing metallic NPs by rational design.

Stress distribution in fixed-partial prosthesis and peri-implant bone tissue with different framework materials and vertical misfit levels: a three-dimensional finite element analysis.

PubMed

Bacchi, Ataís; Consani, Rafael L X; Mesquita, Marcelo F; dos Santos, Mateus B F

2013-09-01

The purpose of this study was to evaluate the influence of superstructure material and vertical misfits on the stresses created in an implant-supported partial prosthesis. A three-dimensional (3-D) finite element model was prepared based on common clinical data. The posterior part of a severely resorbed jaw with two osseointegrated implants at the second premolar and second molar regions was modeled using specific modeling software (SolidWorks 2010). Finite element models were created by importing the solid model into mechanical simulation software (ANSYS Workbench 11). The models were divided into groups according to the prosthesis framework material (type IV gold alloy, silver-palladium alloy, commercially pure titanium, cobalt-chromium alloy, or zirconia) and vertical misfit level (10 µm, 50 µm, and 100 µm) created at one implant-prosthesis interface. The gap of the vertical misfit was set to be closed and the stress values were measured in the framework, porcelain veneer, retention screw, and bone tissue. Stiffer materials led to higher stress concentration in the framework and increased stress values in the retention screw, while in the same circumstances, the porcelain veneer showed lower stress values, and there was no significant difference in stress in the peri-implant bone tissue. A considerable increase in stress concentration was observed in all the structures evaluated within the misfit amplification. The framework material influenced the stress concentration in the prosthetic structures and retention screw, but not that in bone tissue. All the structures were significantly influenced by the increase in the misfit levels.

Information object definition-based unified modeling language representation of DICOM structured reporting: a case study of transcoding DICOM to XML.

PubMed

Tirado-Ramos, Alfredo; Hu, Jingkun; Lee, K P

2002-01-01

Supplement 23 to DICOM (Digital Imaging and Communications for Medicine), Structured Reporting, is a specification that supports a semantically rich representation of image and waveform content, enabling experts to share image and related patient information. DICOM SR supports the representation of textual and coded data linked to images and waveforms. Nevertheless, the medical information technology community needs models that work as bridges between the DICOM relational model and open object-oriented technologies. The authors assert that representations of the DICOM Structured Reporting standard, using object-oriented modeling languages such as the Unified Modeling Language, can provide a high-level reference view of the semantically rich framework of DICOM and its complex structures. They have produced an object-oriented model to represent the DICOM SR standard and have derived XML-exchangeable representations of this model using World Wide Web Consortium specifications. They expect the model to benefit developers and system architects who are interested in developing applications that are compliant with the DICOM SR specification.

Follow on Research for Multi-Utility Technology Test Bed Aircraft at NASA Dryden Flight Research Center (FY13 Progress Report)

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi

2013-01-01

Modern aircraft employ a significant fraction of their weight in composite materials to reduce weight and improve performance. Aircraft aeroservoelastic models are typically characterized by significant levels of model parameter uncertainty due to the composite manufacturing process. Small modeling errors in the finite element model will eventually induce errors in the structural flexibility and mass, thus propagating into unpredictable errors in the unsteady aerodynamics and the control law design. One of the primary objectives of Multi Utility Technology Test-bed (MUTT) aircraft is the flight demonstration of active flutter suppression, and therefore in this study, the identification of the primary and secondary modes for the structural model tuning based on the flutter analysis of MUTT aircraft. The ground vibration test-validated structural dynamic finite element model of the MUTT aircraft is created in this study. The structural dynamic finite element model of MUTT aircraft is improved using the in-house Multi-disciplinary Design, Analysis, and Optimization tool. In this study, two different weight configurations of MUTT aircraft have been improved simultaneously in a single model tuning procedure.

The spatial structure of chronic morbidity: evidence from UK census returns.

PubMed

Dutey-Magni, Peter F; Moon, Graham

2016-08-24

Disease prevalence models have been widely used to estimate health, lifestyle and disability characteristics for small geographical units when other data are not available. Yet, knowledge is often lacking about how to make informed decisions around the specification of such models, especially regarding spatial assumptions placed on their covariance structure. This paper is concerned with understanding processes of spatial dependency in unexplained variation in chronic morbidity. 2011 UK census data on limiting long-term illness (LLTI) is used to look at the spatial structure in chronic morbidity across England and Wales. The variance and spatial clustering of the odds of LLTI across local authority districts (LADs) and middle layer super output areas are measured across 40 demographic cross-classifications. A series of adjacency matrices based on distance, contiguity and migration flows are tested to examine the spatial structure in LLTI. Odds are then modelled using a logistic mixed model to examine the association with district-level covariates and their predictive power. The odds of chronic illness are more dispersed than local age characteristics, mortality, hospitalisation rates and chance alone would suggest. Of all adjacency matrices, the three-nearest neighbour method is identified as the best fitting. Migration flows can also be used to construct spatial weights matrices which uncover non-negligible autocorrelation. Once the most important characteristics observable at the LAD-level are taken into account, substantial spatial autocorrelation remains which can be modelled explicitly to improve disease prevalence predictions. Systematic investigation of spatial structures and dependency is important to develop model-based estimation tools in chronic disease mapping. Spatial structures reflecting migration interactions are easy to develop and capture autocorrelation in LLTI. Patterns of spatial dependency in the geographical distribution of LLTI are not comparable across ethnic groups. Ethnic stratification of local health information is needed and there is potential to further address complexity in prevalence models by improving access to disaggregated data.

A case control study on the structural equation model of the mechanism of coagulation and fibrinolysis imbalance in chronic schistosomiasis.

PubMed

Le, Aiping; Zhang, Lunli; Liu, Wei; Li, Xiaopeng; Ren, Jianwei; Ning, An

2017-02-01

A structural equation model was used for verification with chronic schistosomiasis to investigate the coagulation-anticoagulation system imbalance and to deduce the mechanism of D-dimer (D-D) level elevation in patients with advanced schistosome hepatic disease. We detected the plasma levels of tissue-type fiber plasminogen activator (tPA), urokinase type plasminogen activator (uPA), plasmin-antiplasmin complex (PAP), plasminogen (PLG), antithrombin (AT), plasminogen activator inhibitor 1 (PAI1), D-D, factor VIII: C (FVIII:C), antithrombin-III (AT-III), PLG, protein S (PS), and protein C (PC) in the healthy people as control (69), patients with chronic schistosomiasis (150) or advanced chronic schistosomiasis (90). FVIII, PAP, D-D, tPA, and uPA plasma levels were significantly higher in the chronic group than in the control group and were also significantly higher in the advanced group. However, AT-III, PC, PS, AT, PLG, and PAI1 plasma levels in the advanced and chronic groups were significantly lower than those in the control group. With progression of disease in patients with schistosomiasis japonica, a hypercoagulable state is induced by the coagulation-anticoagulation imbalance, eventually leading to patients with high levels of D-D. Furthermore, we established a structural equation model path of a "chronic schistosomiasis disease stage-(coagulation-anticoagulation-fibrinolysis)-D-D." By using analysis of moment structures (AMOS), it was shown that the chronic schistosomiasis stage was positively related to factor VIII and had negative correlation with AT-III; a good positive correlation with PAP, tPA, and uPA; and a good negative correlation with PLG and PAI1. In addition, our results show that the path coefficient of anticoagulation-fibrinolysis system to the chronic stage of schistosomiasis or D-D levels was significantly higher than that of the coagulation system. In conclusion, the coagulation and fibrinolysis imbalance in patients with chronic schistosomiasis, especially with advanced schistosomiasis, is due to the progression of disease stages.

Sensitivity of system stability to model structure

USGS Publications Warehouse

Hosack, G.R.; Li, H.W.; Rossignol, P.A.

2009-01-01

A community is stable, and resilient, if the levels of all community variables can return to the original steady state following a perturbation. The stability properties of a community depend on its structure, which is the network of direct effects (interactions) among the variables within the community. These direct effects form feedback cycles (loops) that determine community stability. Although feedback cycles have an intuitive interpretation, identifying how they form the feedback properties of a particular community can be intractable. Furthermore, determining the role that any specific direct effect plays in the stability of a system is even more daunting. Such information, however, would identify important direct effects for targeted experimental and management manipulation even in complex communities for which quantitative information is lacking. We therefore provide a method that determines the sensitivity of community stability to model structure, and identifies the relative role of particular direct effects, indirect effects, and feedback cycles in determining stability. Structural sensitivities summarize the degree to which each direct effect contributes to stabilizing feedback or destabilizing feedback or both. Structural sensitivities prove useful in identifying ecologically important feedback cycles within the community structure and for detecting direct effects that have strong, or weak, influences on community stability. The approach may guide the development of management intervention and research design. We demonstrate its value with two theoretical models and two empirical examples of different levels of complexity. ?? 2009 Elsevier B.V. All rights reserved.

Geographical distance and local environmental conditions drive the genetic population structure of a freshwater microalga (Bathycoccaceae; Chlorophyta) in Patagonian lakes.

PubMed

Fernández, Leonardo D; Hernández, Cristián E; Schiaffino, M Romina; Izaguirre, Irina; Lara, Enrique

2017-10-01

The patterns and mechanisms underlying the genetic structure of microbial populations remain unresolved. Herein we investigated the role played by two non-mutually exclusive models (i.e. isolation by distance and isolation by environment) in shaping the genetic structure of lacustrine populations of a microalga (a freshwater Bathycoccaceae) in the Argentinean Patagonia. To our knowledge, this was the first study to investigate the genetic population structure in a South American microorganism. Population-level analyses based on ITS1-5.8S-ITS2 sequences revealed high levels of nucleotide and haplotype diversity within and among populations. Fixation index and a spatially explicit Bayesian analysis confirmed the occurrence of genetically distinct microalga populations in Patagonia. Isolation by distance and isolation by environment accounted for 38.5% and 17.7% of the genetic structure observed, respectively, whereas together these models accounted for 41% of the genetic differentiation. While our results highlighted isolation by distance and isolation by environment as important mechanisms in driving the genetic population structure of the microalga studied, none of these models (either alone or together) could explain the entire genetic differentiation observed. The unexplained variation in the genetic differentiation observed could be the result of founder events combined with rapid local adaptations, as proposed by the monopolisation hypothesis. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Toward a multiscale modeling framework for understanding serotonergic function

PubMed Central

Wong-Lin, KongFatt; Wang, Da-Hui; Moustafa, Ahmed A; Cohen, Jeremiah Y; Nakamura, Kae

2017-01-01

Despite its importance in regulating emotion and mental wellbeing, the complex structure and function of the serotonergic system present formidable challenges toward understanding its mechanisms. In this paper, we review studies investigating the interactions between serotonergic and related brain systems and their behavior at multiple scales, with a focus on biologically-based computational modeling. We first discuss serotonergic intracellular signaling and neuronal excitability, followed by neuronal circuit and systems levels. At each level of organization, we will discuss the experimental work accompanied by related computational modeling work. We then suggest that a multiscale modeling approach that integrates the various levels of neurobiological organization could potentially transform the way we understand the complex functions associated with serotonin. PMID:28417684

Finite element model updating of riveted joints of simplified model aircraft structure

NASA Astrophysics Data System (ADS)

Yunus, M. A.; Rani, M. N. Abdul; Sani, M. S. M.; Shah, M. A. S. Aziz

2018-04-01

Thin metal sheets are widely used to fabricate a various type of aerospace structures because of its flexibility and easily to form into any type shapes of structure. The riveted joint has turn out to be one of the popular joint types in jointing the aerospace structures because they can be easily be disassembled, maintained and inspected. In this paper, thin metal sheet components are assembled together via riveted joints to form a simplified model of aerospace structure. However, to model the jointed structure that are attached together via the mechanical joints such as riveted joint are very difficult due to local effects. Understandably that the dynamic characteristic of the joined structure can be significantly affected by these joints due to local effects at the mating areas of the riveted joints such as surface contact, clamping force and slips. A few types of element connectors that available in MSC NATRAN/PATRAN have investigated in order to presented as the rivet joints. Thus, the results obtained in term of natural frequencies and mode shapes are then contrasted with experimental counterpart in order to investigate the acceptance level of accuracy between element connectors that are used in modelling the rivet joints of the riveted joints structure. The reconciliation method via finiteelement model updating is used to minimise the discrepancy of the initial finite element model of the riveted joined structure as close as experimental data and their results are discussed.

Hierarchical drivers of reef-fish metacommunity structure.

PubMed

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

2009-01-01

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

Social Structure Shapes Cultural Stereotypes and Emotions: A Causal Test of the Stereotype Content Model

PubMed Central

Caprariello, Peter A.; Cuddy, Amy J. C.; Fiske, Susan T.

2013-01-01

The stereotype content model (SCM) posits that social structure predicts specific cultural stereotypes and associated emotional prejudices. No prior evidence at a societal level has manipulated both structural predictors and measured both stereotypes and prejudices. In the present study, participants (n = 120) responded to an immigration scenario depicting a high- or low-status group, competitive or not competitive, and rated their likely stereotype (on warmth and competence) and elicited emotional prejudices (admiration, contempt, envy, and pity). Seven of eight specific predictions are fully confirmed, supporting the SCM's predicted causality for social structural effects on cultural stereotypes and emotional prejudices. PMID:24285928

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…

Gender and Grade-Level Comparisons in the Structure of Problem Behaviors among Adolescents

ERIC Educational Resources Information Center

Chun, Heejung; Mobley, Michael

2010-01-01

Based on Jessor's theory (1987) the comparability of a second-order problem behavior model (SPBM) was investigated across gender and grade-level among adolescents. In addition, gender and grade-level differences in problem behavior engagement were addressed examining latent mean differences. Using a sample of 6504 adolescents drawn from the…

Using Models to Understand Sea Level Rise

ERIC Educational Resources Information Center

Barth-Cohen, Lauren; Medina, Edwing

2017-01-01

Important science phenomena--such as atomic structure, evolution, and climate change--are often hard to observe directly. That's why an important scientific practice is to use scientific models to represent one's current understanding of a system. Using models has been included as an essential science and engineering practice in the "Next…

The Protective Role of Supportive Friends against Bullying Perpetration and Victimization

ERIC Educational Resources Information Center

Kendrick, Kristin; Jutengren, Goran; Stattin, Hakan

2012-01-01

A crossed-lagged regression model was tested to investigate relationships between friendship support, bullying involvement, and its consequences during adolescence. Students, 12-16 years (N = 880), were administered questionnaires twice, one year apart. Using structural equation modeling, a model was specified and higher levels of support from…

The Influence of Sexual Identity on Higher Education Outcomes

ERIC Educational Resources Information Center

Sorgen, Carl H., IV.

2011-01-01

This research empirically explores how sexual identity influences higher education outcomes for lesbian, gay, bisexual, and queer (LGBQ) college students. A path model was constructed with structural equation modeling using responses from 1,125 non-heterosexual college students. The model includes four psychological variables (level of sexual…

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.

Structural analysis of glycoproteins: building N-linked glycans with Coot.

PubMed

Emsley, Paul; Crispin, Max

2018-04-01

Coot is a graphics application that is used to build or manipulate macromolecular models; its particular forte is manipulation of the model at the residue level. The model-building tools of Coot have been combined and extended to assist or automate the building of N-linked glycans. The model is built by the addition of monosaccharides, placed by variation of internal coordinates. The subsequent model is refined by real-space refinement, which is stabilized with modified and additional restraints. It is hoped that these enhanced building tools will help to reduce building errors of N-linked glycans and improve our knowledge of the structures of glycoproteins.

Analysis of spatial correlations in a model two-dimensional liquid through eigenvalues and eigenvectors of atomic-level stress matrices.

PubMed

Levashov, V A; Stepanov, M G

2016-01-01

Considerations of local atomic-level stresses associated with each atom represent a particular approach to address structures of disordered materials at the atomic level. We studied structural correlations in a two-dimensional model liquid using molecular dynamics simulations in the following way. We diagonalized the atomic-level stress tensor of every atom and investigated correlations between the eigenvalues and orientations of the eigenvectors of different atoms as a function of distance between them. It is demonstrated that the suggested approach can be used to characterize structural correlations in disordered materials. In particular, we found that changes in the stress correlation functions on decrease of temperature are the most pronounced for the pairs of atoms with separation distance that corresponds to the first minimum in the pair density function. We also show that the angular dependencies of the stress correlation functions previously reported by Wu et al. [Phys. Rev. E 91, 032301 (2015)10.1103/PhysRevE.91.032301] do not represent the anisotropic Eshelby's stress fields, as it is suggested, but originate in the rotational properties of the stress tensors.

A Simplified Model of Local Structure in Aqueous Proline Amino Acid Revealed by First-Principles Molecular Dynamics Simulations

PubMed Central

Troitzsch, Raphael Z.; Tulip, Paul R.; Crain, Jason; Martyna, Glenn J.

2008-01-01

Aqueous proline solutions are deceptively simple as they can take on complex roles such as protein chaperones, cryoprotectants, and hydrotropic agents in biological processes. Here, a molecular level picture of proline/water mixtures is developed. Car-Parrinello ab initio molecular dynamics (CPAIMD) simulations of aqueous proline amino acid at the B-LYP level of theory, performed using IBM's Blue Gene/L supercomputer and massively parallel software, reveal hydrogen-bonding propensities that are at odds with the predictions of the CHARMM22 empirical force field but are in better agreement with results of recent neutron diffraction experiments. In general, the CPAIMD (B-LYP) simulations predict a simplified structural model of proline/water mixtures consisting of fewer distinct local motifs. Comparisons of simulation results to experiment are made by direct evaluation of the neutron static structure factor S(Q) from CPAIMD (B-LYP) trajectories as well as to the results of the empirical potential structure refinement reverse Monte Carlo procedure applied to the neutron data. PMID:18790850

A simplified model of local structure in aqueous proline amino acid revealed by first-principles molecular dynamics simulations.

PubMed

Troitzsch, Raphael Z; Tulip, Paul R; Crain, Jason; Martyna, Glenn J

2008-12-01

Aqueous proline solutions are deceptively simple as they can take on complex roles such as protein chaperones, cryoprotectants, and hydrotropic agents in biological processes. Here, a molecular level picture of proline/water mixtures is developed. Car-Parrinello ab initio molecular dynamics (CPAIMD) simulations of aqueous proline amino acid at the B-LYP level of theory, performed using IBM's Blue Gene/L supercomputer and massively parallel software, reveal hydrogen-bonding propensities that are at odds with the predictions of the CHARMM22 empirical force field but are in better agreement with results of recent neutron diffraction experiments. In general, the CPAIMD (B-LYP) simulations predict a simplified structural model of proline/water mixtures consisting of fewer distinct local motifs. Comparisons of simulation results to experiment are made by direct evaluation of the neutron static structure factor S(Q) from CPAIMD (B-LYP) trajectories as well as to the results of the empirical potential structure refinement reverse Monte Carlo procedure applied to the neutron data.

Numerical Estimation of Sound Transmission Loss in Launch Vehicle Payload Fairing

NASA Astrophysics Data System (ADS)

Chandana, Pawan Kumar; Tiwari, Shashi Bhushan; Vukkadala, Kishore Nath

2017-08-01

Coupled acoustic-structural analysis of a typical launch vehicle composite payload faring is carried out, and results are validated with experimental data. Depending on the frequency range of interest, prediction of vibro-acoustic behavior of a structure is usually done using the finite element method, boundary element method or through statistical energy analysis. The present study focuses on low frequency dynamic behavior of a composite payload fairing structure using both coupled and uncoupled vibro-acoustic finite element models up to 710 Hz. A vibro-acoustic model, characterizing the interaction between the fairing structure, air cavity, and satellite, is developed. The external sound pressure levels specified for the payload fairing's acoustic test are considered as external loads for the analysis. Analysis methodology is validated by comparing the interior noise levels with those obtained from full scale Acoustic tests conducted in a reverberation chamber. The present approach has application in the design and optimization of acoustic control mechanisms at lower frequencies.

The effect of structural empowerment and organizational commitment on Chinese nurses' job satisfaction.

PubMed

Yang, Jinhua; Liu, Yanhui; Chen, Yan; Pan, Xiaoyan

2014-08-01

The purposes of this study were (1) to examine the level of structural empowerment, organizational commitment and job satisfaction in Chinese nurses; and (2) to investigate the relationships among the three variables. A high turnover rate was identified in Chinese staff nurses, and it was highly correlated with lower job satisfaction. Structural empowerment and organizational commitment have been positively related to job satisfaction in western countries. A cross-sectional survey design was employed. Data analysis included descriptive statistics and multiple step-wise regression to test the hypothesized model. Moderate levels of the three variables were found in this study. Both empowerment and commitment were found to be significantly associated with job satisfaction (r=0.722, r=0.693, p<0.01, respectively). The variables of work objectives, resources, support and informal power, normative and ideal commitment were significant predictors of job satisfaction. Support for an expanded model of Kanter's structural empowerment was achieved in this study. Copyright © 2014 Elsevier Inc. All rights reserved.

SMART Structures User's Guide - Version 3.0

NASA Technical Reports Server (NTRS)

Spangler, Jan L.

1996-01-01

Version 3.0 of the Solid Modeling Aerospace Research Tool (SMART Structures) is used to generate structural models for conceptual and preliminary-level aerospace designs. Features include the generation of structural elements for wings and fuselages, the integration of wing and fuselage structural assemblies, and the integration of fuselage and tail structural assemblies. The highly interactive nature of this software allows the structural engineer to move quickly from a geometry that defines a vehicle's external shape to one that has both external components and internal components which may include ribs, spars, longerons, variable depth ringframes, a floor, a keel, and fuel tanks. The geometry that is output is consistent with FEA requirements and includes integrated wing and empennage carry-through and frame attachments. This report provides a comprehensive description of SMART Structures and how to use it.

Protein Structure and Function Prediction Using I-TASSER

PubMed Central

Yang, Jianyi; Zhang, Yang

2016-01-01

I-TASSER is a hierarchical protocol for automated protein structure prediction and structure-based function annotation. Starting from the amino acid sequence of target proteins, I-TASSER first generates full-length atomic structural models from multiple threading alignments and iterative structural assembly simulations followed by atomic-level structure refinement. The biological functions of the protein, including ligand-binding sites, enzyme commission number, and gene ontology terms, are then inferred from known protein function databases based on sequence and structure profile comparisons. I-TASSER is freely available as both an on-line server and a stand-alone package. This unit describes how to use the I-TASSER protocol to generate structure and function prediction and how to interpret the prediction results, as well as alternative approaches for further improving the I-TASSER modeling quality for distant-homologous and multi-domain protein targets. PMID:26678386

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}.

On the utilization of hydrological modelling for road drainage design under climate and land use change.

PubMed

Kalantari, Zahra; Briel, Annemarie; Lyon, Steve W; Olofsson, Bo; Folkeson, Lennart

2014-03-15

Road drainage structures are often designed using methods that do not consider process-based representations of a landscape's hydrological response. This may create inadequately sized structures as coupled land cover and climate changes can lead to an amplified hydrological response. This study aims to quantify potential increases of runoff in response to future extreme rain events in a 61 km(2) catchment (40% forested) in southwest Sweden using a physically-based hydrological modelling approach. We simulate peak discharge and water level (stage) at two types of pipe bridges and one culvert, both of which are commonly used at Swedish road/stream intersections, under combined forest clear-cutting and future climate scenarios for 2050 and 2100. The frequency of changes in peak flow and water level varies with time (seasonality) and storm size. These changes indicate that the magnitude of peak flow and the runoff response are highly correlated to season rather than storm size. In all scenarios considered, the dimensions of the current culvert are insufficient to handle the increase in water level estimated using a physically-based modelling approach. It also appears that the water level at the pipe bridges changes differently depending on the size and timing of the storm events. The findings of the present study and the approach put forward should be considered when planning investigations on and maintenance for areas at risk of high water flows. In addition, the research highlights the utility of physically-based hydrological models to identify the appropriateness of road drainage structure dimensioning. Copyright © 2014 Elsevier B.V. All rights reserved.

A novel simulation theory and model system for multi-field coupling pipe-flow system

NASA Astrophysics Data System (ADS)

Chen, Yang; Jiang, Fan; Cai, Guobiao; Xu, Xu

2017-09-01

Due to the lack of a theoretical basis for multi-field coupling in many system-level models, a novel set of system-level basic equations for flow/heat transfer/combustion coupling is put forward. Then a finite volume model of quasi-1D transient flow field for multi-species compressible variable-cross-section pipe flow is established by discretising the basic equations on spatially staggered grids. Combining with the 2D axisymmetric model for pipe-wall temperature field and specific chemical reaction mechanisms, a finite volume model system is established; a set of specific calculation methods suitable for multi-field coupling system-level research is structured for various parameters in this model; specific modularisation simulation models can be further derived in accordance with specific structures of various typical components in a liquid propulsion system. This novel system can also be used to derive two sub-systems: a flow/heat transfer two-field coupling pipe-flow model system without chemical reaction and species diffusion; and a chemical equilibrium thermodynamic calculation-based multi-field coupling system. The applicability and accuracy of two sub-systems have been verified through a series of dynamic modelling and simulations in earlier studies. The validity of this system is verified in an air-hydrogen combustion sample system. The basic equations and the model system provide a unified universal theory and numerical system for modelling and simulation and even virtual testing of various pipeline systems.

Students' understanding of primary and secondary protein structure: drawing secondary protein structure reveals student understanding better than simple recognition of structures.

PubMed

Harle, Marissa; Towns, Marcy H

2013-01-01

The interdisciplinary nature of biochemistry courses requires students to use both chemistry and biology knowledge to understand biochemical concepts. Research that has focused on external representations in biochemistry has uncovered student difficulties in comprehending and interpreting external representations in addition to a fragmented understanding of fundamental biochemistry concepts. This project focuses on students' understanding of primary and secondary protein structure and drawings (representations) of hydrogen-bonding in alpha helices and beta sheets. Analysis demonstrated that students can recognize and identify primary protein structure concepts when given a polypeptide. However, when asked to draw alpha helices and beta sheets and explain the role of hydrogen bonding their drawings students exhibited a fragmented understanding that lacked coherence. Faculty are encouraged to have students draw molecular level representations to make their mental models more explicit, complete, and coherent. This is in contrast to recognition and identification tasks, which do not adequately probe mental models and molecular level understanding. © 2013 by The International Union of Biochemistry and Molecular Biology.

Update on HCDstruct - A Tool for Hybrid Wing Body Conceptual Design and Structural Optimization

NASA Technical Reports Server (NTRS)

Gern, Frank H.

2015-01-01

HCDstruct is a Matlab® based software tool to rapidly build a finite element model for structural optimization of hybrid wing body (HWB) aircraft at the conceptual design level. The tool uses outputs from a Flight Optimization System (FLOPS) performance analysis together with a conceptual outer mold line of the vehicle, e.g. created by Vehicle Sketch Pad (VSP), to generate a set of MSC Nastran® bulk data files. These files can readily be used to perform a structural optimization and weight estimation using Nastran’s® Solution 200 multidisciplinary optimization solver. Initially developed at NASA Langley Research Center to perform increased fidelity conceptual level HWB centerbody structural analyses, HCDstruct has grown into a complete HWB structural sizing and weight estimation tool, including a fully flexible aeroelastic loads analysis. Recent upgrades to the tool include the expansion to a full wing tip-to-wing tip model for asymmetric analyses like engine out conditions and dynamic overswings, as well as a fully actuated trailing edge, featuring up to 15 independently actuated control surfaces and twin tails. Several example applications of the HCDstruct tool are presented.

Mediation in dyadic data at the level of the dyads: a Structural Equation Modeling approach.

PubMed

Ledermann, Thomas; Macho, Siegfried

2009-10-01

An extended version of the Common Fate Model (CFM) is presented to estimate and test mediation in dyadic data. The model can be used for distinguishable dyad members (e.g., heterosexual couples) or indistinguishable dyad members (e.g., homosexual couples) if (a) the variables measure characteristics of the dyadic relationship or shared external influences that affect both partners; if (b) the causal associations between the variables should be analyzed at the dyadic level; and if (c) the measured variables are reliable indicators of the latent variables. To assess mediation using Structural Equation Modeling, a general three-step procedure is suggested. The first is a selection of a good fitting model, the second a test of the direct effects, and the third a test of the mediating effect by means of bootstrapping. The application of the model along with the procedure for assessing mediation is illustrated using data from 184 couples on marital problems, communication, and marital quality. Differences with the Actor-Partner Interdependence Model and the analysis of longitudinal mediation by using the CFM are discussed.

Robust Real-Time Music Transcription with a Compositional Hierarchical Model.

PubMed

Pesek, Matevž; Leonardis, Aleš; Marolt, Matija

2017-01-01

The paper presents a new compositional hierarchical model for robust music transcription. Its main features are unsupervised learning of a hierarchical representation of input data, transparency, which enables insights into the learned representation, as well as robustness and speed which make it suitable for real-world and real-time use. The model consists of multiple layers, each composed of a number of parts. The hierarchical nature of the model corresponds well to hierarchical structures in music. The parts in lower layers correspond to low-level concepts (e.g. tone partials), while the parts in higher layers combine lower-level representations into more complex concepts (tones, chords). The layers are learned in an unsupervised manner from music signals. Parts in each layer are compositions of parts from previous layers based on statistical co-occurrences as the driving force of the learning process. In the paper, we present the model's structure and compare it to other hierarchical approaches in the field of music information retrieval. We evaluate the model's performance for the multiple fundamental frequency estimation. Finally, we elaborate on extensions of the model towards other music information retrieval tasks.

Item-level and subscale-level factoring of Biggs' Learning Process Questionnaire (LPQ) in a mainland Chinese sample.

PubMed

Sachs, J; Gao, L

2000-09-01

The learning process questionnaire (LPQ) has been the source of intensive cross-cultural study. However, an item-level factor analysis of all the LPQ items simultaneously has never been reported. Rather, items within each subscale have been factor analysed to establish subscale unidimensionality and justify the use of composite subscale scores. It was of major interest to see if the six logically constructed items groups of the LPQ would be supported by empirical evidence. Additionally, it was of interest to compare the consistency of the reliability and correlational structure of the LPQ subscales in our study with those of previous cross-cultural studies. Confirmatory factor analysis was used to fit the six-factor item level model and to fit five representative subscale level factor models. A total of 1070 students between the ages of 15 to 18 years was drawn from a representative selection of 29 classes from within 15 secondary schools in Guangzhou, China. Males and females were almost equally represented. The six-factor item level model of the LPQ seemed to fit reasonably well, thus supporting the six dimensional structure of the LPQ and justifying the use of composite subscale scores for each LPQ dimension. However, the reliability of many of these subscales was low. Furthermore, only two subscale-level factor models showed marginally acceptable fit. Substantive considerations supported an oblique three-factor model. Because the LPQ subscales often show low internal consistency reliability, experimental and correlational studies that have used these subscales as dependent measures have been disappointing. It is suggested that some LPQ items should be revised and other items added to improve the inventory's overall psychometric properties.

PRISM-EM: template interface-based modelling of multi-protein complexes guided by cryo-electron microscopy density maps.

PubMed

Kuzu, Guray; Keskin, Ozlem; Nussinov, Ruth; Gursoy, Attila

2016-10-01

The structures of protein assemblies are important for elucidating cellular processes at the molecular level. Three-dimensional electron microscopy (3DEM) is a powerful method to identify the structures of assemblies, especially those that are challenging to study by crystallography. Here, a new approach, PRISM-EM, is reported to computationally generate plausible structural models using a procedure that combines crystallographic structures and density maps obtained from 3DEM. The predictions are validated against seven available structurally different crystallographic complexes. The models display mean deviations in the backbone of <5 Å. PRISM-EM was further tested on different benchmark sets; the accuracy was evaluated with respect to the structure of the complex, and the correlation with EM density maps and interface predictions were evaluated and compared with those obtained using other methods. PRISM-EM was then used to predict the structure of the ternary complex of the HIV-1 envelope glycoprotein trimer, the ligand CD4 and the neutralizing protein m36.

Control of Flow Structure in Square Cross-Sectioned U Bend using Numerical Modeling

NASA Astrophysics Data System (ADS)

Yavuz, Mehmet Metin; Guden, Yigitcan

2014-11-01

Due to the curvature in U-bends, the flow development involves complex flow structures including Dean vortices and high levels of turbulence that are quite critical in considering noise problems and structural failure of the ducts. Computational fluid dynamic (CFD) models are developed using ANSYS Fluent to analyze and to control the flow structure in a square cross-sectioned U-bend with a radius of curvature Rc/D = 0.65. The predictions of velocity profiles on different angular positions of the U-bend are compared against the experimental results available in the literature and the previous numerical studies. The performances of different turbulence models are evaluated to propose the best numerical approach that has high accuracy with reduced computation time. The numerical results of the present study indicate improvements with respect to the previous numerical predictions and very good agreement with the available experimental results. In addition, a flow control technique is utilized to regulate the flow inside the bend. The elimination of Dean vortices along with significant reduction in turbulence levels in different cross flow planes are successfully achieved when the flow control technique is applied. The project is supported by Meteksan Defense Industries, Inc.

Modeling Of Object- And Scene-Prototypes With Hierarchically Structured Classes

NASA Astrophysics Data System (ADS)

Ren, Z.; Jensch, P.; Ameling, W.

1989-03-01

The success of knowledge-based image analysis methodology and implementation tools depends largely on an appropriately and efficiently built model wherein the domain-specific context information about and the inherent structure of the observed image scene have been encoded. For identifying an object in an application environment a computer vision system needs to know firstly the description of the object to be found in an image or in an image sequence, secondly the corresponding relationships between object descriptions within the image sequence. This paper presents models of image objects scenes by means of hierarchically structured classes. Using the topovisual formalism of graph and higraph, we are currently studying principally the relational aspect and data abstraction of the modeling in order to visualize the structural nature resident in image objects and scenes, and to formalize. their descriptions. The goal is to expose the structure of image scene and the correspondence of image objects in the low level image interpretation. process. The object-based system design approach has been applied to build the model base. We utilize the object-oriented programming language C + + for designing, testing and implementing the abstracted entity classes and the operation structures which have been modeled topovisually. The reference images used for modeling prototypes of objects and scenes are from industrial environments as'well as medical applications.

FOSSIL2 energy policy model documentation: generic structures of the FOSSIL2 model

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

None

1980-10-01

This report discusses the structure, derivations, assumptions, and mathematical formulation of the FOSSIL2 model. Each major facet of the model - supply/demand interactions, industry financing, and production - has been designed to parallel closely the actual cause/effect relationships determining the behavior of the United States energy system. The data base for the FOSSIL2 program is large. When possible, all data were obtained from sources well known to experts in the energy field. Cost and resource estimates are based on DOE data whenever possible. This report presents the FOSSIL2 model at several levels. In Volume I, an overview of the basicmore » structures, assumptions, and behavior of the FOSSIL2 model is presented so that the reader can understand the results of various policy tests. The discussion covers the three major building blocks, or generic structures, used to construct the model: supply/demand balance; finance and capital formation; and energy production. These structures reflect the components and interactions of the major processes within each energy industry that directly affect the dynamics of fuel supply, demand, and price within the energy system as a whole.« less

PDE-4 Inhibition Rescues Aberrant Synaptic Plasticity in Drosophila and Mouse Models of Fragile X Syndrome

PubMed Central

Choi, Catherine H.; Schoenfeld, Brian P.; Weisz, Eliana D.; Bell, Aaron J.; Chambers, Daniel B.; Hinchey, Joseph; Choi, Richard J.; Hinchey, Paul; Kollaros, Maria; Gertner, Michael J.; Ferrick, Neal J.; Terlizzi, Allison M.; Yohn, Nicole; Koenigsberg, Eric; Liebelt, David A.; Zukin, R. Suzanne; Woo, Newton H.; Tranfaglia, Michael R.; Louneva, Natalia; Arnold, Steven E.; Siegel, Steven J.

2015-01-01

Fragile X syndrome (FXS) is the leading cause of both intellectual disability and autism resulting from a single gene mutation. Previously, we characterized cognitive impairments and brain structural defects in a Drosophila model of FXS and demonstrated that these impairments were rescued by treatment with metabotropic glutamate receptor (mGluR) antagonists or lithium. A well-documented biochemical defect observed in fly and mouse FXS models and FXS patients is low cAMP levels. cAMP levels can be regulated by mGluR signaling. Herein, we demonstrate PDE-4 inhibition as a therapeutic strategy to ameliorate memory impairments and brain structural defects in the Drosophila model of fragile X. Furthermore, we examine the effects of PDE-4 inhibition by pharmacologic treatment in the fragile X mouse model. We demonstrate that acute inhibition of PDE-4 by pharmacologic treatment in hippocampal slices rescues the enhanced mGluR-dependent LTD phenotype observed in FXS mice. Additionally, we find that chronic treatment of FXS model mice, in adulthood, also restores the level of mGluR-dependent LTD to that observed in wild-type animals. Translating the findings of successful pharmacologic intervention from the Drosophila model into the mouse model of FXS is an important advance, in that this identifies and validates PDE-4 inhibition as potential therapeutic intervention for the treatment of individuals afflicted with FXS. PMID:25568131

Modelling, teachers' views on the nature of modelling, and implications for the education of modellers

NASA Astrophysics Data System (ADS)

Justi, Rosária S.; Gilbert, John K.

2002-04-01

In this paper, the role of modelling in the teaching and learning of science is reviewed. In order to represent what is entailed in modelling, a 'model of modelling' framework is proposed. Five phases in moving towards a full capability in modelling are established by a review of the literature: learning models; learning to use models; learning how to revise models; learning to reconstruct models; learning to construct models de novo. In order to identify the knowledge and skills that science teachers think are needed to produce a model successfully, a semi-structured interview study was conducted with 39 Brazilian serving science teachers: 10 teaching at the 'fundamental' level (6-14 years); 10 teaching at the 'medium'-level (15-17 years); 10 undergraduate pre-service 'medium'-level teachers; 9 university teachers of chemistry. Their responses are used to establish what is entailed in implementing the 'model of modelling' framework. The implications for students, teachers, and for teacher education, of moving through the five phases of capability, are discussed.

Halo Nuclei

NASA Astrophysics Data System (ADS)

Al-Khalili, Jim

2017-10-01

While neutron halos were discovered 30 years ago, this is the first book written on the subject of this exotic form of nuclei that typically contain many more neutrons than stable isotopes of those elements. It provides an introductory description of the halo and outlines the discovery and evidence for its existence. It also discusses different theoretical models of the halo's structure as well as models and techniques in reaction theory that have allowed us to study the halo. This is written at the graduate student (starting at PhD) level. The author of the book, Jim Al-Khalili, is a theoretician who published some of the key papers on the structure of the halo in the mid and late 90s and was the first to determine its true size. This monograph is based on review articles he has written on the mathematical models used to determine the halo structure and the reactions used to model that structure.

Cognitive Abilities Explain Wording Effects in the Rosenberg Self-Esteem Scale.

PubMed

Gnambs, Timo; Schroeders, Ulrich

2017-12-01

There is consensus that the 10 items of the Rosenberg Self-Esteem Scale (RSES) reflect wording effects resulting from positively and negatively keyed items. The present study examined the effects of cognitive abilities on the factor structure of the RSES with a novel, nonparametric latent variable technique called local structural equation models. In a nationally representative German large-scale assessment including 12,437 students competing measurement models for the RSES were compared: a bifactor model with a common factor and a specific factor for all negatively worded items had an optimal fit. Local structural equation models showed that the unidimensionality of the scale increased with higher levels of reading competence and reasoning, while the proportion of variance attributed to the negatively keyed items declined. Wording effects on the factor structure of the RSES seem to represent a response style artifact associated with cognitive abilities.

Bridging the Gap Between the Social and the Technical: The Enrolment of Socio-Technical Information Architects to Cope with the Two-Level Model of EPR Systems.

PubMed

Pedersen, Rune

2017-01-01

This is a project proposal derived from an urge to re-define the governance of ICT in healthcare towards regional and national standardization of the patient pathways. The focus is on a two-levelled approach for governing EPR systems where the clinicians' model structured variables and patient pathways. The overall goal is a patient centric EPR portfolio. This paper define and enlighten the need for establishing the socio- technical architect role necessary to obtain the capabilities of a modern structured EPR system. Clinicians are not capable to moderate between the technical and the clinical.

Elastic body dynamics

NASA Technical Reports Server (NTRS)

Holder, B. W.

1981-01-01

Most of the structural dynamics resources allocated to the Space Shuttle are concentrated on the flight events which result in critical structural loads and/or minimum control stability margins. Since these events are primarily sub-orbital, the data base of interest to those involved in orbital experimentation is somewhat limited. A brief discussion of available data is given. Although estimates of peak acceleration levels and the associated frequency spectrum in the payload bay due to thrusting of the various control system thrusters were made, the actual levels and time histories must be based on updated structural math models and a detailed knowledge of the input forcing functions.

Surface atomic structure of alloyed Mn 5Ge 3(0 0 0 1) by scanning tunneling microscopy

NASA Astrophysics Data System (ADS)

Kim, Howon; Jung, Goo-Eun; Yoon, Jong Keon; Chung, Kyung Hoon; Kahng, Se-Jong

Surface atomic structure of Mn 5Ge 3(0 0 0 1) is studied by scanning tunneling microscopy. Hexagonal honeycomb ordering is observed at high energy levels, ∣ E - EF∣ ˜ 1.2 eV, on the flat regions of three-dimensional Mn 5Ge 3 islands. At low energy levels, ∣ E - EF∣ ˜ 0.5 eV, however, atomic images exhibit dot-array and ring-array structures, which show complete and partial contrast inversion, compared to the honeycomb ordering. Experimental observations are discussed on the basis of possible atomic models.

Exploring Conceptual Frameworks of Models of Atomic Structures and Periodic Variations, Chemical Bonding, and Molecular Shape and Polarity: A Comparison of Undergraduate General Chemistry Students with High and Low Levels of Content Knowledge

ERIC Educational Resources Information Center

Wang, Chia-Yu; Barrow, Lloyd H.

2013-01-01

The purpose of the study was to explore students' conceptual frameworks of models of atomic structure and periodic variations, chemical bonding, and molecular shape and polarity, and how these conceptual frameworks influence their quality of explanations and ability to shift among chemical representations. This study employed a purposeful sampling…

Perceived sexual harassment at work: meta-analysis and structural model of antecedents and consequences.

PubMed

Topa Cantisano, Gabriela; Morales Domínguez, J F; Depolo, Marco

2008-05-01

Although sexual harassment has been extensively studied, empirical research has not led to firm conclusions about its antecedents and consequences, both at the personal and organizational level. An extensive literature search yielded 42 empirical studies with 60 samples. The matrix correlation obtained through meta-analytic techniques was used to test a structural equation model. Results supported the hypotheses regarding organizational environmental factors as main predictors of harassment.

A drug procurement, storage and distribution model in public hospitals in a developing country.

PubMed

Kjos, Andrea L; Binh, Nguyen Thanh; Robertson, Caitlin; Rovers, John

2016-01-01

There is growing interest in pharmaceutical supply chains and distribution of medications at national and international levels. Issues of access and efficiency have been called into question. However, evaluations of system outcomes are not possible unless there are contextual data to describe the systems in question. Available guidelines provided by international advisory bodies such as the World Health Organization and the International Pharmacy Federation may be useful for developing countries like Vietnam when seeking to describe the pharmaceutical system. The purpose of this study was to describe a conceptual model for drug procurement, storage, and distribution in four government-owned hospitals in Vietnam. This study was qualitative and used semi-structured interviews with key informants from within the Vietnamese pharmaceutical system. Translated transcriptions were used to conduct a content analysis of the data. A conceptual model for the Vietnamese pharmaceutical system was described using structural and functional components. This model showed that in Vietnam, governmental policy influences the structural framework of the system, but allows for flexibility at the functional level of practice. Further, this model can be strongly differentiated from the models described by international advisory bodies. This study demonstrates a method for health care systems to describe their own models of drug distribution to address quality assurance, systems design and benchmarking for quality improvement. Copyright © 2016 Elsevier Inc. All rights reserved.

The Effects of Autocorrelation on the Curve-of-Factors Growth Model

ERIC Educational Resources Information Center

Murphy, Daniel L.; Beretvas, S. Natasha; Pituch, Keenan A.

2011-01-01

This simulation study examined the performance of the curve-of-factors model (COFM) when autocorrelation and growth processes were present in the first-level factor structure. In addition to the standard curve-of factors growth model, 2 new models were examined: one COFM that included a first-order autoregressive autocorrelation parameter, and a…

Normal Theory Two-Stage ML Estimator When Data Are Missing at the Item Level

ERIC Educational Resources Information Center

Savalei, Victoria; Rhemtulla, Mijke

2017-01-01

In many modeling contexts, the variables in the model are linear composites of the raw items measured for each participant; for instance, regression and path analysis models rely on scale scores, and structural equation models often use parcels as indicators of latent constructs. Currently, no analytic estimation method exists to appropriately…

Integration of system identification and finite element modelling of nonlinear vibrating structures

NASA Astrophysics Data System (ADS)

Cooper, Samson B.; DiMaio, Dario; Ewins, David J.

2018-03-01

The Finite Element Method (FEM), Experimental modal analysis (EMA) and other linear analysis techniques have been established as reliable tools for the dynamic analysis of engineering structures. They are often used to provide solutions to small and large structures and other variety of cases in structural dynamics, even those exhibiting a certain degree of nonlinearity. Unfortunately, when the nonlinear effects are substantial or the accuracy of the predicted response is of vital importance, a linear finite element model will generally prove to be unsatisfactory. As a result, the validated linear FE model requires further enhancement so that it can represent and predict the nonlinear behaviour exhibited by the structure. In this paper, a pragmatic approach to integrating test-based system identification and FE modelling of a nonlinear structure is presented. This integration is based on three different phases: the first phase involves the derivation of an Underlying Linear Model (ULM) of the structure, the second phase includes experiment-based nonlinear identification using measured time series and the third phase covers augmenting the linear FE model and experimental validation of the nonlinear FE model. The proposed case study is demonstrated on a twin cantilever beam assembly coupled with a flexible arch shaped beam. In this case, polynomial-type nonlinearities are identified and validated with force-controlled stepped-sine test data at several excitation levels.

Structural dynamic testing of composite propfan blades for a cruise missile wind tunnel model

NASA Technical Reports Server (NTRS)

Elgin, Stephen D.; Sutliff, Thomas J.

1993-01-01

The Naval Weapons Center at China Lake, California is currently evaluating a counter rotating propfan system as a means of propulsion for the next generation of cruise missiles. The details and results of a structural dynamic test program are presented for scale model graphite-epoxy composite propfan blades. These blades are intended for use on a cruise missile wind tunnel model. Both dynamic characteristics and strain operating limits of the blades are presented. Complications associated with high strain level fatigue testing methods are also discussed.

Space-time latent component modeling of geo-referenced health data.

PubMed

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

2010-08-30

Latent structure models have been proposed in many applications. For space-time health data it is often important to be able to find the underlying trends in time, which are supported by subsets of small areas. Latent structure modeling is one such approach to this analysis. This paper presents a mixture-based approach that can be applied to component selection. The analysis of a Georgia ambulatory asthma county-level data set is presented and a simulation-based evaluation is made. Copyright (c) 2010 John Wiley & Sons, Ltd.

Advanced methods for modeling water-levels and estimating drawdowns with SeriesSEE, an Excel add-in

USGS Publications Warehouse

Halford, Keith; Garcia, C. Amanda; Fenelon, Joe; Mirus, Benjamin B.

2012-12-21

Water-level modeling is used for multiple-well aquifer tests to reliably differentiate pumping responses from natural water-level changes in wells, or “environmental fluctuations.” Synthetic water levels are created during water-level modeling and represent the summation of multiple component fluctuations, including those caused by environmental forcing and pumping. Pumping signals are modeled by transforming step-wise pumping records into water-level changes by using superimposed Theis functions. Water-levels can be modeled robustly with this Theis-transform approach because environmental fluctuations and pumping signals are simulated simultaneously. Water-level modeling with Theis transforms has been implemented in the program SeriesSEE, which is a Microsoft® Excel add-in. Moving average, Theis, pneumatic-lag, and gamma functions transform time series of measured values into water-level model components in SeriesSEE. Earth tides and step transforms are additional computed water-level model components. Water-level models are calibrated by minimizing a sum-of-squares objective function where singular value decomposition and Tikhonov regularization stabilize results. Drawdown estimates from a water-level model are the summation of all Theis transforms minus residual differences between synthetic and measured water levels. The accuracy of drawdown estimates is limited primarily by noise in the data sets, not the Theis-transform approach. Drawdowns much smaller than environmental fluctuations have been detected across major fault structures, at distances of more than 1 mile from the pumping well, and with limited pre-pumping and recovery data at sites across the United States. In addition to water-level modeling, utilities exist in SeriesSEE for viewing, cleaning, manipulating, and analyzing time-series data.

A case of isolation by distance and short-term temporal stability of population structure in brown trout (Salmo trutta) within the River Dart, southwest England

PubMed Central

Griffiths, Andrew M; Koizumi, Itsuro; Bright, Dylan; Stevens, Jamie R

2009-01-01

Salmonid fishes exhibit high levels of population differentiation. In particular, the brown trout (Salmo trutta L.) demonstrates complex within river drainage genetic structure. Increasingly, these patterns can be related to the underlying evolutionary models, of which three scenarios (member-vagrant hypothesis, metapopulation model and panmixia) facilitate testable predictions for investigations into population structure. We analysed 1225 trout collected from the River Dart, a 75 km long river located in southwest England. Specimens were collected from 22 sample sites across three consecutive summers (2001–2003) and genetic variation was examined at nine microsatellite loci. A hierarchical analysis of molecular variance revealed that negligible genetic variation was attributed among temporal samples. The highest levels of differentiation occurred among samples isolated above barriers to fish movement, and once these samples were removed, a significant effect of isolation-by-distance was observed. These results suggest that, at least in the short-term, ecological events are more important in shaping the population structure of Dart trout than stochastic extinction events, and certainly do not contradict the expectations of a member-vagrant hypothesis. Furthermore, individual-level spatial autocorrelation analyses support previous recommendations for the preservation of a number of spawning sites spaced throughout the tributary system to conserve the high levels of genetic variation identified in salmonid species. PMID:25567897

Synchrotron IR microspectroscopy for protein structure analysis: Potential and questions

DOE PAGES

Yu, Peiqiang

2006-01-01

Synchrotron radiation-based Fourier transform infrared microspectroscopy (S-FTIR) has been developed as a rapid, direct, non-destructive, bioanalytical technique. This technique takes advantage of synchrotron light brightness and small effective source size and is capable of exploring the molecular chemical make-up within microstructures of a biological tissue without destruction of inherent structures at ultra-spatial resolutions within cellular dimension. To date there has been very little application of this advanced technique to the study of pure protein inherent structure at a cellular level in biological tissues. In this review, a novel approach was introduced to show the potential of the newly developed, advancedmore » synchrotron-based analytical technology, which can be used to localize relatively “pure“ protein in the plant tissues and relatively reveal protein inherent structure and protein molecular chemical make-up within intact tissue at cellular and subcellular levels. Several complex protein IR spectra data analytical techniques (Gaussian and Lorentzian multi-component peak modeling, univariate and multivariate analysis, principal component analysis (PCA), and hierarchical cluster analysis (CLA) are employed to relatively reveal features of protein inherent structure and distinguish protein inherent structure differences between varieties/species and treatments in plant tissues. By using a multi-peak modeling procedure, RELATIVE estimates (but not EXACT determinations) for protein secondary structure analysis can be made for comparison purpose. The issues of pro- and anti-multi-peaking modeling/fitting procedure for relative estimation of protein structure were discussed. By using the PCA and CLA analyses, the plant molecular structure can be qualitatively separate one group from another, statistically, even though the spectral assignments are not known. The synchrotron-based technology provides a new approach for protein structure research in biological tissues at ultraspatial resolutions.« less

A fully-stochasticized, age-structured population model for population viability analysis of fish: Lower Missouri River endangered pallid sturgeon example

USGS Publications Warehouse

Wildhaber, Mark L.; Albers, Janice; Green, Nicholas; Moran, Edward H.

2017-01-01

We develop a fully-stochasticized, age-structured population model suitable for population viability analysis (PVA) of fish and demonstrate its use with the endangered pallid sturgeon (Scaphirhynchus albus) of the Lower Missouri River as an example. The model incorporates three levels of variance: parameter variance (uncertainty about the value of a parameter itself) applied at the iteration level, temporal variance (uncertainty caused by random environmental fluctuations over time) applied at the time-step level, and implicit individual variance (uncertainty caused by differences between individuals) applied within the time-step level. We found that population dynamics were most sensitive to survival rates, particularly age-2+ survival, and to fecundity-at-length. The inclusion of variance (unpartitioned or partitioned), stocking, or both generally decreased the influence of individual parameters on population growth rate. The partitioning of variance into parameter and temporal components had a strong influence on the importance of individual parameters, uncertainty of model predictions, and quasiextinction risk (i.e., pallid sturgeon population size falling below 50 age-1+ individuals). Our findings show that appropriately applying variance in PVA is important when evaluating the relative importance of parameters, and reinforce the need for better and more precise estimates of crucial life-history parameters for pallid sturgeon.

Broadband locally resonant metamaterials with graded hierarchical architecture

NASA Astrophysics Data System (ADS)

Liu, Chenchen; Reina, Celia

2018-03-01

We investigate the effect of hierarchical designs on the bandgap structure of periodic lattice systems with inner resonators. A detailed parameter study reveals various interesting features of structures with two levels of hierarchy as compared with one level systems with identical static mass. In particular: (i) their overall bandwidth is approximately equal, yet bounded above by the bandwidth of the single-resonator system; (ii) the number of bandgaps increases with the level of hierarchy; and (iii) the spectrum of bandgap frequencies is also enlarged. Taking advantage of these features, we propose graded hierarchical structures with ultra-broadband properties. These designs are validated over analogous continuum models via finite element simulations, demonstrating their capability to overcome the bandwidth narrowness that is typical of resonant metamaterials.

Dimensional Model for Estimating Factors influencing Childhood Obesity: Path Analysis Based Modeling

PubMed Central

Kheirollahpour, Maryam; Shohaimi, Shamarina

2014-01-01

The main objective of this study is to identify and develop a comprehensive model which estimates and evaluates the overall relations among the factors that lead to weight gain in children by using structural equation modeling. The proposed models in this study explore the connection among the socioeconomic status of the family, parental feeding practice, and physical activity. Six structural models were tested to identify the direct and indirect relationship between the socioeconomic status and parental feeding practice general level of physical activity, and weight status of children. Finally, a comprehensive model was devised to show how these factors relate to each other as well as to the body mass index (BMI) of the children simultaneously. Concerning the methodology of the current study, confirmatory factor analysis (CFA) was applied to reveal the hidden (secondary) effect of socioeconomic factors on feeding practice and ultimately on the weight status of the children and also to determine the degree of model fit. The comprehensive structural model tested in this study suggested that there are significant direct and indirect relationships among variables of interest. Moreover, the results suggest that parental feeding practice and physical activity are mediators in the structural model. PMID:25097878