On the Interface of Probabilistic and PDE Methods in a Multifactor Term Structure Theory

ERIC Educational Resources Information Center

Mamon, Rogemar S.

2004-01-01

Within the general framework of a multifactor term structure model, the fundamental partial differential equation (PDE) satisfied by a default-free zero-coupon bond price is derived via a martingale-oriented approach. Using this PDE, a result characterizing a model belonging to an exponential affine class is established using only a system of…

Contact-assisted protein structure modeling by global optimization in CASP11.

PubMed

Joo, Keehyoung; Joung, InSuk; Cheng, Qianyi; Lee, Sung Jong; Lee, Jooyoung

2016-09-01

We have applied the conformational space annealing method to the contact-assisted protein structure modeling in CASP11. For Tp targets, where predicted residue-residue contact information was provided, the contact energy term in the form of the Lorentzian function was implemented together with the physical energy terms used in our template-free modeling of proteins. Although we observed some structural improvement of Tp models over the models predicted without the Tp information, the improvement was not substantial on average. This is partly due to the inaccuracy of the provided contact information, where only about 18% of it was correct. For Ts targets, where the information of ambiguous NOE (Nuclear Overhauser Effect) restraints was provided, we formulated the modeling in terms of the two-tier optimization problem, which covers: (1) the assignment of NOE peaks and (2) the three-dimensional (3D) model generation based on the assigned NOEs. Although solving the problem in a direct manner appears to be intractable at first glance, we demonstrate through CASP11 that remarkably accurate protein 3D modeling is possible by brute force optimization of a relevant energy function. For 19 Ts targets of the average size of 224 residues, generated protein models were of about 3.6 Å Cα atom accuracy. Even greater structural improvement was observed when additional Tc contact information was provided. For 20 out of the total 24 Tc targets, we were able to generate protein structures which were better than the best model from the rest of the CASP11 groups in terms of GDT-TS. Proteins 2016; 84(Suppl 1):189-199. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Two-Fluid Models and Interfacial Area Transport in Microgravity Condition

NASA Technical Reports Server (NTRS)

Ishii, Mamoru; Sun, Xiao-Dong; Vasavada, Shilp

2004-01-01

The objective of the present study is to develop a two-fluid model formulation with interfacial area transport equation applicable for microgravity conditions. The new model is expected to make a leapfrog improvement by furnishing the constitutive relations for the interfacial interaction terms with the interfacial area transport equation, which can dynamically model the changes of the interfacial structures. In the first year of this three-year project supported by the U.S. NASA, Office of Biological and Physics Research, the primary focus is to design and construct a ground-based, microgravity two-phase flow simulation facility, in which two immiscible fluids with close density will be used. In predicting the two-phase flow behaviors in any two-phase flow system, the interfacial transfer terms are among the most essential factors in the modeling. These interfacial transfer terms in a two-fluid model specify the rate of phase change, momentum exchange, and energy transfer at the interface between the two phases. For the two-phase flow under the microgravity condition, the stability of the fluid particle interface and the interfacial structures are quite different from those under normal gravity condition. The flow structure may not reach an equilibrium condition and the two fluids may be loosely coupled such that the inertia terms of each fluid should be considered separately by use of the two-fluid model. Previous studies indicated that, unless phase-interaction terms are accurately modeled in the two-fluid model, the complex modeling does not necessarily warrant an accurate solution.

Advanced moisture modeling of polymer composites.

DOT National Transportation Integrated Search

2014-04-01

Long term moisture exposure has been shown to affect the mechanical performance of polymeric composite structures. This reduction : in mechanical performance must be considered during product design in order to ensure long term structure survival. In...

Two ways to solve, using Lie group analysis, the fundamental valuation equation in the double-square-root model of the term structure

NASA Astrophysics Data System (ADS)

Sinkala, W.

2011-01-01

Two approaches based on Lie group analysis are employed to obtain the closed-form solution of a partial differential equation derived by Francis A. Longstaff [J Financial Econom 1989;23:195-224] for the price of a discount bond in the double-square-root model of the term structure.

Direct-method SAD phasing with partial-structure iteration: towards automation.

PubMed

Wang, J W; Chen, J R; Gu, Y X; Zheng, C D; Fan, H F

2004-11-01

The probability formula of direct-method SAD (single-wavelength anomalous diffraction) phasing proposed by Fan & Gu (1985, Acta Cryst. A41, 280-284) contains partial-structure information in the form of a Sim-weighting term. Previously, only the substructure of anomalous scatterers has been included in this term. In the case that the subsequent density modification and model building yields only structure fragments, which do not straightforwardly lead to the complete solution, the partial structure can be fed back into the Sim-weighting term of the probability formula in order to strengthen its phasing power and to benefit the subsequent automatic model building. The procedure has been tested with experimental SAD data from two known proteins with copper and sulfur as the anomalous scatterers.

Effect of structural distortion on the electronic band structure of NaOsO3 studied within density functional theory and a three-orbital model

NASA Astrophysics Data System (ADS)

Mohapatra, Shubhajyoti; Bhandari, Churna; Satpathy, Sashi; Singh, Avinash

2018-04-01

Effects of the structural distortion associated with the OsO6 octahedral rotation and tilting on the electronic band structure and magnetic anisotropy energy for the 5 d3 compound NaOsO3 are investigated using the density functional theory (DFT) and within a three-orbital model. Comparison of the essential features of the DFT band structures with the three-orbital model for both the undistorted and distorted structures provides insight into the orbital and directional asymmetry in the electron hopping terms resulting from the structural distortion. The orbital mixing terms obtained in the transformed hopping Hamiltonian resulting from the octahedral rotations are shown to account for the fine features in the DFT band structure. Staggered magnetization and the magnetic character of states near the Fermi energy indicate weak coupling behavior.

TrOn: an anatomical ontology for the beetle Tribolium castaneum.

PubMed

Dönitz, Jürgen; Grossmann, Daniela; Schild, Inga; Schmitt-Engel, Christian; Bradler, Sven; Prpic, Nikola-Michael; Bucher, Gregor

2013-01-01

In a morphological ontology the expert's knowledge is represented in terms, which describe morphological structures and how these structures relate to each other. With the assistance of ontologies this expert knowledge is made processable by machines, through a formal and standardized representation of terms and their relations to each other. The red flour beetle Tribolium castaneum, a representative of the most species rich animal taxon on earth (the Coleoptera), is an emerging model organism for development, evolution, physiology, and pest control. In order to foster Tribolium research, we have initiated the Tribolium Ontology (TrOn), which describes the morphology of the red flour beetle. The content of this ontology comprises so far most external morphological structures as well as some internal ones. All modeled structures are consistently annotated for the developmental stages larva, pupa and adult. In TrOn all terms are grouped into three categories: Generic terms represent morphological structures, which are independent of a developmental stage. In contrast, downstream of such terms are concrete terms which stand for a dissectible structure of a beetle at a specific life stage. Finally, there are mixed terms describing structures that are only found at one developmental stage. These terms combine the characteristics of generic and concrete terms with features of both. These annotation principles take into account the changing morphology of the beetle during development and provide generic terms to be used in applications or for cross linking with other ontologies and data resources. We use the ontology for implementing an intuitive search function at the electronic iBeetle-Base, which stores morphological defects found in a genome wide RNA interference (RNAi) screen. The ontology is available for download at http://ibeetle-base.uni-goettingen.de.

A Neural Network Model of the Structure and Dynamics of Human Personality

ERIC Educational Resources Information Center

Read, Stephen J.; Monroe, Brian M.; Brownstein, Aaron L.; Yang, Yu; Chopra, Gurveen; Miller, Lynn C.

2010-01-01

We present a neural network model that aims to bridge the historical gap between dynamic and structural approaches to personality. The model integrates work on the structure of the trait lexicon, the neurobiology of personality, temperament, goal-based models of personality, and an evolutionary analysis of motives. It is organized in terms of two…

3D Nanoporous Anodic Alumina Structures for Sustained Drug Release

PubMed Central

Xifré-Pérez, Elisabet; Eckstein, Chris; Ferré-Borrull, Josep

2017-01-01

The use of nanoporous anodic alumina (NAA) for the development of drug delivery systems has gained much attention in recent years. The release of drugs loaded inside NAA pores is complex and depends on the morphology of the pores. In this study, NAA, with different three-dimensional (3D) pore structures (cylindrical pores with several pore diameters, multilayered nanofunnels, and multilayered inverted funnels) were fabricated, and their respective drug delivery rates were studied and modeled using doxorubicin as a model drug. The obtained results reveal optimal modeling of all 3D pore structures, differentiating two drug release stages. Thus, an initial short-term and a sustained long-term release were successfully modeled by the Higuchi and the Korsmeyer–Peppas equations, respectively. This study demonstrates the influence of pore geometries on drug release rates, and further presents a sustained long-term drug release that exceeds 60 days without an undesired initial burst. PMID:28825654

PDB_REDO: automated re-refinement of X-ray structure models in the PDB.

PubMed

Joosten, Robbie P; Salzemann, Jean; Bloch, Vincent; Stockinger, Heinz; Berglund, Ann-Charlott; Blanchet, Christophe; Bongcam-Rudloff, Erik; Combet, Christophe; Da Costa, Ana L; Deleage, Gilbert; Diarena, Matteo; Fabbretti, Roberto; Fettahi, Géraldine; Flegel, Volker; Gisel, Andreas; Kasam, Vinod; Kervinen, Timo; Korpelainen, Eija; Mattila, Kimmo; Pagni, Marco; Reichstadt, Matthieu; Breton, Vincent; Tickle, Ian J; Vriend, Gert

2009-06-01

Structural biology, homology modelling and rational drug design require accurate three-dimensional macromolecular coordinates. However, the coordinates in the Protein Data Bank (PDB) have not all been obtained using the latest experimental and computational methods. In this study a method is presented for automated re-refinement of existing structure models in the PDB. A large-scale benchmark with 16 807 PDB entries showed that they can be improved in terms of fit to the deposited experimental X-ray data as well as in terms of geometric quality. The re-refinement protocol uses TLS models to describe concerted atom movement. The resulting structure models are made available through the PDB_REDO databank (http://www.cmbi.ru.nl/pdb_redo/). Grid computing techniques were used to overcome the computational requirements of this endeavour.

Structural Acoustic Physics Based Modeling of Curved Composite Shells

DTIC Science & Technology

2017-09-19

Results show that the finite element computational models accurately match analytical calculations, and that the composite material studied in this...products. 15. SUBJECT TERMS Finite Element Analysis, Structural Acoustics, Fiber-Reinforced Composites, Physics-Based Modeling 16. SECURITY...2 4 FINITE ELEMENT MODEL DESCRIPTION

Tertiary structural propensities reveal fundamental sequence/structure relationships.

PubMed

Zheng, Fan; Zhang, Jian; Grigoryan, Gevorg

2015-05-05

Extracting useful generalizations from the continually growing Protein Data Bank (PDB) is of central importance. We hypothesize that the PDB contains valuable quantitative information on the level of local tertiary structural motifs (TERMs). We show that by breaking a protein structure into its constituent TERMs, and querying the PDB to characterize the natural ensemble matching each, we can estimate the compatibility of the structure with a given amino acid sequence through a metric we term "structure score." Considering submissions from recent Critical Assessment of Structure Prediction (CASP) experiments, we found a strong correlation (R = 0.69) between structure score and model accuracy, with poorly predicted regions readily identifiable. This performance exceeds that of leading atomistic statistical energy functions. Furthermore, TERM-based analysis of two prototypical multi-state proteins rapidly produced structural insights fully consistent with prior extensive experimental studies. We thus find that TERM-based analysis should have considerable utility for protein structural biology. Copyright © 2015 Elsevier Ltd. All rights reserved.

Final Report, 2011-2014. Forecasting Carbon Storage as Eastern Forests Age. Joining Experimental and Modeling Approaches at the UMBS AmeriFlux Site

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

Curtis, Peter; Bohrer, Gil; Gough, Christopher

2015-03-12

At the University of Michigan Biological Station (UMBS) AmeriFlux sites (US-UMB and US-UMd), long-term C cycling measurements and a novel ecosystem-scale experiment are revealing physical, biological, and ecological mechanisms driving long-term trajectories of C cycling, providing new data for improving modeling forecasts of C storage in eastern forests. Our findings provide support for previously untested hypotheses that stand-level structural and biological properties constrain long-term trajectories of C storage, and that remotely sensed canopy structural parameters can substantially improve model forecasts of forest C storage. Through the Forest Accelerated Succession ExperimenT (FASET), we are directly testing the hypothesis that forest Cmore » storage will increase due to increasing structural and biological complexity of the emerging tree communities. Support from this project, 2011-2014, enabled us to incorporate novel physical and ecological mechanisms into ecological, meteorological, and hydrological models to improve forecasts of future forest C storage in response to disturbance, succession, and current and long-term climate variation« less

Modeling Long-term Creep Performance for Welded Nickel-base Superalloy Structures for Power Generation Systems

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

Shen, Chen; Gupta, Vipul; Huang, Shenyan

The goal of this project is to model long-term creep performance for nickel-base superalloy weldments in high temperature power generation systems. The project uses physics-based modeling methodologies and algorithms for predicting alloy properties in heterogeneous material structures. The modeling methodology will be demonstrated on a gas turbine combustor liner weldment of Haynes 282 precipitate-strengthened nickel-base superalloy. The major developments are: (1) microstructure-property relationships under creep conditions and microstructure characterization (2) modeling inhomogeneous microstructure in superalloy weld (3) modeling mesoscale plastic deformation in superalloy weld and (4) a constitutive creep model that accounts for weld and base metal microstructure and theirmore » long term evolution. The developed modeling technology is aimed to provide a more efficient and accurate assessment of a material’s long-term performance compared with current testing and extrapolation methods. This modeling technology will also accelerate development and qualification of new materials in advanced power generation systems. This document is a final technical report for the project, covering efforts conducted from October 2014 to December 2016.« less

SEMI-SUPERVISED OBJECT RECOGNITION USING STRUCTURE KERNEL

PubMed Central

Wang, Botao; Xiong, Hongkai; Jiang, Xiaoqian; Ling, Fan

2013-01-01

Object recognition is a fundamental problem in computer vision. Part-based models offer a sparse, flexible representation of objects, but suffer from difficulties in training and often use standard kernels. In this paper, we propose a positive definite kernel called “structure kernel”, which measures the similarity of two part-based represented objects. The structure kernel has three terms: 1) the global term that measures the global visual similarity of two objects; 2) the part term that measures the visual similarity of corresponding parts; 3) the spatial term that measures the spatial similarity of geometric configuration of parts. The contribution of this paper is to generalize the discriminant capability of local kernels to complex part-based object models. Experimental results show that the proposed kernel exhibit higher accuracy than state-of-art approaches using standard kernels. PMID:23666108

Using structure to explore the sequence alignment space of remote homologs.

PubMed

Kuziemko, Andrew; Honig, Barry; Petrey, Donald

2011-10-01

Protein structure modeling by homology requires an accurate sequence alignment between the query protein and its structural template. However, sequence alignment methods based on dynamic programming (DP) are typically unable to generate accurate alignments for remote sequence homologs, thus limiting the applicability of modeling methods. A central problem is that the alignment that is "optimal" in terms of the DP score does not necessarily correspond to the alignment that produces the most accurate structural model. That is, the correct alignment based on structural superposition will generally have a lower score than the optimal alignment obtained from sequence. Variations of the DP algorithm have been developed that generate alternative alignments that are "suboptimal" in terms of the DP score, but these still encounter difficulties in detecting the correct structural alignment. We present here a new alternative sequence alignment method that relies heavily on the structure of the template. By initially aligning the query sequence to individual fragments in secondary structure elements and combining high-scoring fragments that pass basic tests for "modelability", we can generate accurate alignments within a small ensemble. Our results suggest that the set of sequences that can currently be modeled by homology can be greatly extended.

Sustained Innovation Through Shared Capitalism and Democratic Governance

NASA Astrophysics Data System (ADS)

Beyster, M. A.; Blasi, J.; Sibilia, J.; Zebuchen, T.; Bowman, A.

The Foundation for Enterprise Development (FED) explores application of democratic representative governance models and structures for long-term interdisciplinary research, development and education to the concept of an organization that can sustain activity in support of interstellar travel in the 100-year timeframe, as outlined by the 100 Year StarshipTM. This paper titled, Sustained Innovation through Shared Capitalism and Democratic Governance , explores the roots of representative structures and organizations as long-lived success stories throughout history. Research, innovation, organizational structures and associated issues are explored to address the long-term focus required for development, both material and human. Impact investing vehicles are also explored as potential investment structures addressing the long-term horizon required by the organization. This paper provides an illustration, description and philosophical approach of this model as developed by the FED and our collaborators.

Global/local methods for probabilistic structural analysis

NASA Technical Reports Server (NTRS)

Millwater, H. R.; Wu, Y.-T.

1993-01-01

A probabilistic global/local method is proposed to reduce the computational requirements of probabilistic structural analysis. A coarser global model is used for most of the computations with a local more refined model used only at key probabilistic conditions. The global model is used to establish the cumulative distribution function (cdf) and the Most Probable Point (MPP). The local model then uses the predicted MPP to adjust the cdf value. The global/local method is used within the advanced mean value probabilistic algorithm. The local model can be more refined with respect to the g1obal model in terms of finer mesh, smaller time step, tighter tolerances, etc. and can be used with linear or nonlinear models. The basis for this approach is described in terms of the correlation between the global and local models which can be estimated from the global and local MPPs. A numerical example is presented using the NESSUS probabilistic structural analysis program with the finite element method used for the structural modeling. The results clearly indicate a significant computer savings with minimal loss in accuracy.

Global/local methods for probabilistic structural analysis

NASA Astrophysics Data System (ADS)

Millwater, H. R.; Wu, Y.-T.

1993-04-01

A probabilistic global/local method is proposed to reduce the computational requirements of probabilistic structural analysis. A coarser global model is used for most of the computations with a local more refined model used only at key probabilistic conditions. The global model is used to establish the cumulative distribution function (cdf) and the Most Probable Point (MPP). The local model then uses the predicted MPP to adjust the cdf value. The global/local method is used within the advanced mean value probabilistic algorithm. The local model can be more refined with respect to the g1obal model in terms of finer mesh, smaller time step, tighter tolerances, etc. and can be used with linear or nonlinear models. The basis for this approach is described in terms of the correlation between the global and local models which can be estimated from the global and local MPPs. A numerical example is presented using the NESSUS probabilistic structural analysis program with the finite element method used for the structural modeling. The results clearly indicate a significant computer savings with minimal loss in accuracy.

Is nucleon spin structure inconsistent with the constituent quark model?

NASA Astrophysics Data System (ADS)

Qing, Di; Chen, Xiang-Song; Wang, Fan

1998-12-01

Proton spin structure discovered in polarized deep inelastic scattering is shown to be consistent with the valence-sea quark mixing constituent quark model. The relativistic correction and quark-antiquark pair creation (annihilation) terms inherently involved in the quark axial vector current suppress the quark spin contribution to the proton spin. The relativistic quark orbital angular momentum provides compensative terms to keep the proton spin 12 untouched. The tensor charge of the proton is predicted to have a similar but smaller suppression. An explanation on why baryon magnetic moments can be parametrized by the naive quark model spin content as well as the spin structure discovered in polarized deep inelastic scattering is given.

Applying an Empirical Hydropathic Forcefield in Refinement May Improve Low-Resolution Protein X-Ray Crystal Structures

PubMed Central

Koparde, Vishal N.; Scarsdale, J. Neel; Kellogg, Glen E.

2011-01-01

Background The quality of X-ray crystallographic models for biomacromolecules refined from data obtained at high-resolution is assured by the data itself. However, at low-resolution, >3.0 Å, additional information is supplied by a forcefield coupled with an associated refinement protocol. These resulting structures are often of lower quality and thus unsuitable for downstream activities like structure-based drug discovery. Methodology An X-ray crystallography refinement protocol that enhances standard methodology by incorporating energy terms from the HINT (Hydropathic INTeractions) empirical forcefield is described. This protocol was tested by refining synthetic low-resolution structural data derived from 25 diverse high-resolution structures, and referencing the resulting models to these structures. The models were also evaluated with global structural quality metrics, e.g., Ramachandran score and MolProbity clashscore. Three additional structures, for which only low-resolution data are available, were also re-refined with this methodology. Results The enhanced refinement protocol is most beneficial for reflection data at resolutions of 3.0 Å or worse. At the low-resolution limit, ≥4.0 Å, the new protocol generated models with Cα positions that have RMSDs that are 0.18 Å more similar to the reference high-resolution structure, Ramachandran scores improved by 13%, and clashscores improved by 51%, all in comparison to models generated with the standard refinement protocol. The hydropathic forcefield terms are at least as effective as Coulombic electrostatic terms in maintaining polar interaction networks, and significantly more effective in maintaining hydrophobic networks, as synthetic resolution is decremented. Even at resolutions ≥4.0 Å, these latter networks are generally native-like, as measured with a hydropathic interactions scoring tool. PMID:21246043

Long-term effects of child punishment on Mexican women: a structural model.

PubMed

Frias-Armenta, Martha

2002-04-01

The aim of this study was to investigate long-term effects of parental use of physical and verbal punishment on Mexican women. To study both direct and indirect effects of these phenomena, a structural model was developed and tested. One hundred and fifty Mexican women were interviewed with regard to their history of child abuse, their level of depression, alcohol use, antisocial behavior, and punishment of their own children. Factors representing such constructs were specified within a structural equation model and their inter-relations were estimated. Women's history of abuse was considered as an exogenous latent variable directly affecting three other factors: mothers' antisocial behavior, their alcohol consumption, and their levels of depression or anxiety. These factors, in turn, were specified as influencing mothers' harsh discipline of their own children. Data supported this model, indicating that a history of abuse has long-term effects on women's behavior and psychological functioning, which in turn cause women's punitive behavior against their children. These results are discussed in terms of the theoretical framework of intergenerational transmission of violence. The direct consequences (depression, anxiety, alcohol consumption, and antisocial behavior) of child punishment act as risk factors for the next generation of child abuse.

Integrated modeling of long-term vegetation and hydrologic dynamics in Rocky Mountain watersheds

Treesearch

Robert Steven Ahl

2007-01-01

Changes in forest structure resulting from natural disturbances, or managed treatments, can have negative and long lasting impacts on water resources. To facilitate integrated management of forest and water resources, a System for Long-Term Integrated Management Modeling (SLIMM) was developed. By combining two spatially explicit, continuous time models, vegetation...

Western root disease model simulation versus plot remeasurement: 11 years of change in stand structure and density induced by Armillaria root disease in Central Oregon

Treesearch

Helen M. Maffei; Gregory M. Filip; Kristen L. Chadwick; Lance David

2008-01-01

The purpose of this analysis was to use long term permanent plots to evaluate the short-term predictive capability of the Western Root Disease Model extension (WRDM) of the Forest Vegetation Simulator (FVS) in central Oregon mixed-conifer forests in project planning situations. Measured (1991–2002) structure and density changes on a 100-acre unmanaged area in south-...

Contributions to the simulation of turbulence

NASA Technical Reports Server (NTRS)

Dutton, J. A.; Kerman, B. R.; Petersen, E. L.

1976-01-01

The simulation modeling of turbulence in the boundary layer in consolidated in terms of boundary layer similarity principles and empirical results. The modeling is extended for some aspects of the nonlinear and non-Gaussian structure of the turbulence. Properties of the discrete gust form structure of the modeled turbulence are identified.

The Concept of Adjustment: A Structural Model.

ERIC Educational Resources Information Center

Dodds, A.; And Others

1994-01-01

This study analyzed scores of 469 British adult clients with recent loss of sight on the Nottingham Adjustment Scale using LISREL structural modeling techniques. Results supported a theoretical model of the self in terms of two latent factors--internal self-worth and self as agent. Implications for rehabilitation and intervention with cognitive…

The structure of the casein micelle of milk and its changes during processing.

PubMed

Dalgleish, Douglas G; Corredig, Milena

2012-01-01

The majority of the protein in cow's milk is contained in the particles known as casein micelles. This review describes the main structural features of these particles and the different models that have been used to define the interior structures. The reactions of the micelles during processing operations are described in terms of the structural models.

Multiscale Computational Design Optimization of Copper-Strengthened Steel for High Cycle Fatigue

DTIC Science & Technology

2010-03-19

strain energy) and (3) modeling of a slip band (of PSB ladder underlying structure) and attendant crack initiation process. 15. SUBJECT TERMS 16...energy). (C) A modeling of a slip band (of PSB ladder underlying structure) and attendant crack initiation process. Major results obtained are...differentiate the morphology from others, e.g., vein and planar structures of dislocations. Results and Discussion for (C) (C-1) Modeling PSB For modeling

Renormalizing a viscous fluid model for large scale structure formation

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

Führer, Florian; Rigopoulos, Gerasimos, E-mail: fuhrer@thphys.uni-heidelberg.de, E-mail: gerasimos.rigopoulos@ncl.ac.uk

2016-02-01

Using the Stochastic Adhesion Model (SAM) as a simple toy model for cosmic structure formation, we study renormalization and the removal of the cutoff dependence from loop integrals in perturbative calculations. SAM shares the same symmetry with the full system of continuity+Euler equations and includes a viscosity term and a stochastic noise term, similar to the effective theories recently put forward to model CDM clustering. We show in this context that if the viscosity and noise terms are treated as perturbative corrections to the standard eulerian perturbation theory, they are necessarily non-local in time. To ensure Galilean Invariance higher ordermore » vertices related to the viscosity and the noise must then be added and we explicitly show at one-loop that these terms act as counter terms for vertex diagrams. The Ward Identities ensure that the non-local-in-time theory can be renormalized consistently. Another possibility is to include the viscosity in the linear propagator, resulting in exponential damping at high wavenumber. The resulting local-in-time theory is then renormalizable to one loop, requiring less free parameters for its renormalization.« less

Bayesian Analysis of Structural Equation Models with Nonlinear Covariates and Latent Variables

ERIC Educational Resources Information Center

Song, Xin-Yuan; Lee, Sik-Yum

2006-01-01

In this article, we formulate a nonlinear structural equation model (SEM) that can accommodate covariates in the measurement equation and nonlinear terms of covariates and exogenous latent variables in the structural equation. The covariates can come from continuous or discrete distributions. A Bayesian approach is developed to analyze the…

The structures of native celluloses, and the origin of their variability

Treesearch

R. H. Atalla

1999-01-01

The structures of native celluloses have traditionally been presented in terms of two-domain models consisting of crystalline and non-crystalline fractions. Such models have been of little help in advancing understanding of enzyme-substrate interactions. In this report we first address issues that complicate characterization of the structure of native celluloses...

Probabilistic structural analysis methods of hot engine structures

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Hopkins, D. A.

1989-01-01

Development of probabilistic structural analysis methods for hot engine structures is a major activity at Lewis Research Center. Recent activities have focused on extending the methods to include the combined uncertainties in several factors on structural response. This paper briefly describes recent progress on composite load spectra models, probabilistic finite element structural analysis, and probabilistic strength degradation modeling. Progress is described in terms of fundamental concepts, computer code development, and representative numerical results.

Curvature and gravity actions for matrix models: II. The case of general Poisson structures

NASA Astrophysics Data System (ADS)

Blaschke, Daniel N.; Steinacker, Harold

2010-12-01

We study the geometrical meaning of higher order terms in matrix models of Yang-Mills type in the semi-classical limit, generalizing recent results (Blaschke and Steinacker 2010 Class. Quantum Grav. 27 165010 (arXiv:1003.4132)) to the case of four-dimensional spacetime geometries with general Poisson structure. Such terms are expected to arise e.g. upon quantization of the IKKT-type models. We identify terms which depend only on the intrinsic geometry and curvature, including modified versions of the Einstein-Hilbert action as well as terms which depend on the extrinsic curvature. Furthermore, a mechanism is found which implies that the effective metric G on the spacetime brane {\\cal M}\\subset \\mathds{R}^D 'almost' coincides with the induced metric g. Deviations from G = g are suppressed, and characterized by the would-be U(1) gauge field.

Use of a Dual-Structure Constitutive Model for Predicting the Long-Term Behavior of an Expansive Clay Buffer in a Nuclear Waste Repository

DOE PAGES

Vilarrasa, Víctor; Rutqvist, Jonny; Blanco Martin, Laura; ...

2015-12-31

Expansive soils are suitable as backfill and buffer materials in engineered barrier systems to isolate heat-generating nuclear waste in deep geological formations. The canisters containing nuclear waste would be placed in tunnels excavated at a depth of several hundred meters. The expansive soil should provide enough swelling capacity to support the tunnel walls, thereby reducing the impact of the excavation-damaged zone on the long-term mechanical and flow-barrier performance. In addition to their swelling capacity, expansive soils are characterized by accumulating irreversible strain on suction cycles and by effects of microstructural swelling on water permeability that for backfill or buffer materialsmore » can significantly delay the time it takes to reach full saturation. In order to simulate these characteristics of expansive soils, a dual-structure constitutive model that includes two porosity levels is necessary. The authors present the formulation of a dual-structure model and describe its implementation into a coupled fluid flow and geomechanical numerical simulator. The authors use the Barcelona Basic Model (BBM), which is an elastoplastic constitutive model for unsaturated soils, to model the macrostructure, and it is assumed that the strains of the microstructure, which are volumetric and elastic, induce plastic strain to the macrostructure. The authors tested and demonstrated the capabilities of the implemented dual-structure model by modeling and reproducing observed behavior in two laboratory tests of expansive clay. As observed in the experiments, the simulations yielded nonreversible strain accumulation with suction cycles and a decreasing swelling capacity with increasing confining stress. Finally, the authors modeled, for the first time using a dual-structure model, the long-term (100,000 years) performance of a generic heat-generating nuclear waste repository with waste emplacement in horizontal tunnels backfilled with expansive clay and hosted in a clay rock formation. The thermo-hydro-mechanical results of the dual-structure model were compared with those of the standard single-structure BBM. The main difference between the simulation results from the two models is that the dual-structure model predicted a time to fully saturate the expansive clay barrier on the order of thousands of years, whereas the standard single-structure BBM yielded a time on the order of tens of years. These examples show that a dual-structure model, such as the one presented here, is necessary to properly model the thermo-hydro-mechanical behavior of expansive soils.« less

New lumped-mass-stick model based on modal characteristics of structures: development and application to a nuclear containment building

NASA Astrophysics Data System (ADS)

Roh, Hwasung; Lee, Huseok; Lee, Jong Seh

2013-06-01

In this study, a new lumped-mass-stick model (LMSM) is developed based on the modal characteristics of a structure such as eigenvalues and eigenvectors. The simplified model, named the "frequency adaptive lumped-massstick model," hasonly a small number of stick elements and nodes to provide the same natural frequencies of the structure and is applied to a nuclear containment building. To investigate the numerical performance of the LMSM, a time history analysis is carried out on both the LMSM and the finite element model (FEM) for a nuclear containment building. A comparison of the results shows that the dynamic responses of the LMSM in terms of displacement and acceleration are almost identical to those of the FEM. In addition, the results in terms of fl oor response spectra at certain elevations are also in good agreement.

75 FR 43105 - Airworthiness Directives; PIAGGIO AERO INDUSTRIES S.p.A Model PIAGGIO P-180 Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-23

... beams and the rear pressurized bulkhead. If left uncorrected, long term fatigue stress could locally... term fatigue stress could locally weaken the structure, compromising the fuselage structural integrity... reviewed the MCAI and related service information and, in general, agree with their substance. But we might...

Maximum Likelihood Estimation in Meta-Analytic Structural Equation Modeling

ERIC Educational Resources Information Center

Oort, Frans J.; Jak, Suzanne

2016-01-01

Meta-analytic structural equation modeling (MASEM) involves fitting models to a common population correlation matrix that is estimated on the basis of correlation coefficients that are reported by a number of independent studies. MASEM typically consist of two stages. The method that has been found to perform best in terms of statistical…

Fractal and chaotic laws on seismic dissipated energy in an energy system of engineering structures

NASA Astrophysics Data System (ADS)

Cui, Yu-Hong; Nie, Yong-An; Yan, Zong-Da; Wu, Guo-You

1998-09-01

Fractal and chaotic laws of engineering structures are discussed in this paper, it means that the intrinsic essences and laws on dynamic systems which are made from seismic dissipated energy intensity E d and intensity of seismic dissipated energy moment I e are analyzed. Based on the intrinsic characters of chaotic and fractal dynamic system of E d and I e, three kinds of approximate dynamic models are rebuilt one by one: index autoregressive model, threshold autoregressive model and local-approximate autoregressive model. The innate laws, essences and systematic error of evolutional behavior I e are explained over all, the short-term behavior predictability and long-term behavior probability of which are analyzed in the end. That may be valuable for earthquake-resistant theory and analysis method in practical engineering structures.

An AI-based approach to structural damage identification by modal analysis

NASA Technical Reports Server (NTRS)

Glass, B. J.; Hanagud, S.

1990-01-01

Flexible-structure damage is presently addressed by a combined model- and parameter-identification approach which employs the AI methodologies of classification, heuristic search, and object-oriented model knowledge representation. The conditions for model-space search convergence to the best model are discussed in terms of search-tree organization and initial model parameter error. In the illustrative example of a truss structure presented, the use of both model and parameter identification is shown to lead to smaller parameter corrections than would be required by parameter identification alone.

Long-term impacts of recurrent logging and fire in Amazon forests: a modeling study using the Ecosystem Demography Model (ED2)

NASA Astrophysics Data System (ADS)

Longo, M.; Keller, M.; Scaranello, M. A., Sr.; dos-Santos, M. N.; Xu, Y.; Huang, M.; Morton, D. C.

2017-12-01

Logging and understory fires are major drivers of tropical forest degradation, reducing carbon stocks and changing forest structure, composition, and dynamics. In contrast to deforested areas, sites that are disturbed by logging and fires retain some, albeit severely altered, forest structure and function. In this study we simulated selective logging using the Ecosystem Demography Model (ED-2) to investigate the impact of a broad range of logging techniques, harvest intensities, and recurrence cycles on the long-term dynamics of Amazon forests, including the magnitude and duration of changes in forest flammability following timber extraction. Model results were evaluated using eddy covariance towers at logged sites at the Tapajos National Forest in Brazil and data on long-term dynamics reported in the literature. ED-2 is able to reproduce both the fast (< 5yr) recovery of water, energy fluxes compared to flux tower, and the typical, field-observed, decadal time scales for biomass recovery when no additional logging occurs. Preliminary results using the original ED-2 fire model show that canopy cover loss of forests under high-intensity, conventional logging cause sufficient drying to support more intense fires. These results indicate that under intense degradation, forests may shift to novel disturbance regimes, severely reducing carbon stocks, and inducing long-term changes in forest structure and composition from recurrent fires.

The effect of visual arrangement on visuospatial short-term memory: Insights from children with 22q11.2 deletion syndrome.

PubMed

Attout, Lucie; Noël, Marie-Pascale; Rousselle, Laurence

2018-04-11

Recent models of visuospatial (VSSP) short-term memory postulate the existence of two dissociable mechanisms depending on whether VSSP information is presented simultaneously or sequentially. However, they do not specify to what extent VSSP short-term memory is under the influence of general VSSP processing. This issue was examined in people with 22q11.2 deletion syndrome, a genetic condition involving a VSSP deficit. The configuration of VSSP information was manipulated (structured vs. unstructured) to explore the impact of arrangement on VSSP short-term memory. Two presentation modes were used to see whether the VSSP arrangement has the same impact on simultaneous and sequential short-term memory. Compared to children matched on chronological age, children with 22q11.2 deletion syndrome showed impaired performance only for structured arrangement, regardless of the presentation mode, suggesting an influence of VSSP processing on VSSP short-term memory abilities. A revised cognitive architecture for a model of VSSP short-term memory is proposed.

Physics textbooks from the viewpoint of network structures

NASA Astrophysics Data System (ADS)

Králiková, Petra; Teleki, Aba

2017-01-01

We can observe self-organized networks all around us. These networks are, in general, scale invariant networks described by the Bianconi-Barabasi model. The self-organized networks (networks formed naturally when feedback acts on the system) show certain universality. These networks, in simplified models, have scale invariant distribution (Pareto distribution type I) and parameter α has value between 2 and 5. The textbooks are extremely important in the learning process and from this reason we studied physics textbook at the level of sentences and physics terms (bipartite network). The nodes represent physics terms, sentences, and pictures, tables, connected by links (by physics terms and transitional words and transitional phrases). We suppose that learning process are more robust and goes faster and easier if the physics textbook has a structure similar to structures of self-organized networks.

Aeroelastic Model Structure Computation for Envelope Expansion

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2007-01-01

Structure detection is a procedure for selecting a subset of candidate terms, from a full model description, that best describes the observed output. This is a necessary procedure to compute an efficient system description which may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modelling may be of critical importance in the development of robust, parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion which may save significant development time and costs. In this study, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of nonlinear aeroelastic systems. The LASSO minimises the residual sum of squares by the addition of an l(sub 1) penalty term on the parameter vector of the traditional 2 minimisation problem. Its use for structure detection is a natural extension of this constrained minimisation approach to pseudolinear regression problems which produces some model parameters that are exactly zero and, therefore, yields a parsimonious system description. Applicability of this technique for model structure computation for the F/A-18 Active Aeroelastic Wing using flight test data is shown for several flight conditions (Mach numbers) by identifying a parsimonious system description with a high percent fit for cross-validated data.

AIM for Allostery: Using the Ising Model to Understand Information Processing and Transmission in Allosteric Biomolecular Systems.

PubMed

LeVine, Michael V; Weinstein, Harel

2015-05-01

In performing their biological functions, molecular machines must process and transmit information with high fidelity. Information transmission requires dynamic coupling between the conformations of discrete structural components within the protein positioned far from one another on the molecular scale. This type of biomolecular "action at a distance" is termed allostery . Although allostery is ubiquitous in biological regulation and signal transduction, its treatment in theoretical models has mostly eschewed quantitative descriptions involving the system's underlying structural components and their interactions. Here, we show how Ising models can be used to formulate an approach to allostery in a structural context of interactions between the constitutive components by building simple allosteric constructs we termed Allosteric Ising Models (AIMs). We introduce the use of AIMs in analytical and numerical calculations that relate thermodynamic descriptions of allostery to the structural context, and then show that many fundamental properties of allostery, such as the multiplicative property of parallel allosteric channels, are revealed from the analysis of such models. The power of exploring mechanistic structural models of allosteric function in more complex systems by using AIMs is demonstrated by building a model of allosteric signaling for an experimentally well-characterized asymmetric homodimer of the dopamine D2 receptor.

AnatomicalTerms.info: heading for an online solution to the anatomical synonym problem hurdles in data-reuse from the Terminologia Anatomica and the foundational model of anatomy and potentials for future development.

PubMed

Gobée, O Paul; Jansma, Daniël; DeRuiter, Marco C

2011-10-01

The many synonyms for anatomical structures confuse medical students and complicate medical communication. Easily accessible translations would alleviate this problem. None of the presently available resources-Terminologia Anatomica (TA), digital terminologies such as the Foundational Model of Anatomy (FMA), and websites-are fully satisfactory to this aim. Internet technologies offer new possibilities to solve the problem. Several authors have called for an online TA. An online translation resource should be easily accessible, user-friendly, comprehensive, expandable, and its quality determinable. As first step towards this goal, we built a translation website that we named www.AnatomicalTerms.info, based on the database of the FMA. It translates between English, Latin, eponyms, and to a lesser extent other languages, and presently contains over 31,000 terms for 7,250 structures, covering 95% of TA. In addition, it automatically presents searches for images, documents and anatomical variations regarding the sought structure. Several terminological and conceptual issues were encountered in transferring data from TA and FMA into AnatomicalTerms.info, resultant from these resources' different set-ups (paper versus digital) and targets (machine versus human-user). To the best of our knowledge, AnatomicalTerms.info is unique in its combination of user-friendliness and comprehensiveness. As next step, wiki-like expandability will be added to enable open contribution of clinical synonyms and terms in different languages. Specific quality measures will be taken to strike a balance between open contribution and quality assurance. AnatomicalTerms.info's mechanism that "translates" terms to structures furthermore may enhance targeted searching by linking images, descriptions, and other anatomical resources to the structures. Copyright © 2011 Wiley-Liss, Inc.

Structural composite panel performance under long-term load

Treesearch

Theodore L. Laufenberg

1988-01-01

Information on the performance of wood-based structural composite panels under long-term load is currently needed to permit their use in engineered assemblies and systems. A broad assessment of the time-dependent properties of panels is critical for creating databases and models of the creep-rupture phenomenon that lead to reliability-based design procedures. This...

Getting off the Straight and Narrow: Exploiting Non-Linear, Interactive Narrative Structures in Digital Stories for Language Teaching

ERIC Educational Resources Information Center

Prosser, Andrew

2014-01-01

Digital storytelling is already used extensively in language education. Web documentaries, particularly in terms of design and narrative structure, provide an extension of the digital storytelling concept, specifically in terms of increased interactivity. Using a model of interactive, non-linear storytelling, originally derived from computer game…

Menzerath-Altmann Law: Statistical Mechanical Interpretation as Applied to a Linguistic Organization

NASA Astrophysics Data System (ADS)

Eroglu, Sertac

2014-10-01

The distribution behavior described by the empirical Menzerath-Altmann law is frequently encountered during the self-organization of linguistic and non-linguistic natural organizations at various structural levels. This study presents a statistical mechanical derivation of the law based on the analogy between the classical particles of a statistical mechanical organization and the distinct words of a textual organization. The derived model, a transformed (generalized) form of the Menzerath-Altmann model, was termed as the statistical mechanical Menzerath-Altmann model. The derived model allows interpreting the model parameters in terms of physical concepts. We also propose that many organizations presenting the Menzerath-Altmann law behavior, whether linguistic or not, can be methodically examined by the transformed distribution model through the properly defined structure-dependent parameter and the energy associated states.

Attention Problems, Phonological Short-Term Memory, and Visuospatial Short-Term Memory: Differential Effects on Near- and Long-Term Scholastic Achievement

ERIC Educational Resources Information Center

Sarver, Dustin E.; Rapport, Mark D.; Kofler, Michael J.; Scanlan, Sean W.; Raiker, Joseph S.; Altro, Thomas A.; Bolden, Jennifer

2012-01-01

The current study examined individual differences in children's phonological and visuospatial short-term memory as potential mediators of the relationship among attention problems and near- and long-term scholastic achievement. Nested structural equation models revealed that teacher-reported attention problems were associated negatively with…

Learning in Structured Connectionist Networks

DTIC Science & Technology

1988-04-01

the structure is too rigid and learning too difficult for cognitive modeling. Two algorithms for learning simple, feature-based concept descriptions...and learning too difficult for cognitive model- ing. Two algorithms for learning simple, feature-based concept descriptions were also implemented. The...Term Goals Recent progress in connectionist research has been encouraging; networks have success- fully modeled human performance for various cognitive

Methods for evaluating the predictive accuracy of structural dynamic models

NASA Technical Reports Server (NTRS)

Hasselman, Timothy K.; Chrostowski, Jon D.

1991-01-01

Modeling uncertainty is defined in terms of the difference between predicted and measured eigenvalues and eigenvectors. Data compiled from 22 sets of analysis/test results was used to create statistical databases for large truss-type space structures and both pretest and posttest models of conventional satellite-type space structures. Modeling uncertainty is propagated through the model to produce intervals of uncertainty on frequency response functions, both amplitude and phase. This methodology was used successfully to evaluate the predictive accuracy of several structures, including the NASA CSI Evolutionary Structure tested at Langley Research Center. Test measurements for this structure were within + one-sigma intervals of predicted accuracy for the most part, demonstrating the validity of the methodology and computer code.

Research and development activities in unified control-structure modeling and design

NASA Technical Reports Server (NTRS)

Nayak, A. P.

1985-01-01

Results of work to develop a unified control/structures modeling and design capability for large space structures modeling are presented. Recent analytical results are presented to demonstrate the significant interdependence between structural and control properties. A new design methodology is suggested in which the structure, material properties, dynamic model and control design are all optimized simultaneously. Parallel research done by other researchers is reviewed. The development of a methodology for global design optimization is recommended as a long-term goal. It is suggested that this methodology should be incorporated into computer aided engineering programs, which eventually will be supplemented by an expert system to aid design optimization.

Protein Loop Structure Prediction Using Conformational Space Annealing.

PubMed

Heo, Seungryong; Lee, Juyong; Joo, Keehyoung; Shin, Hang-Cheol; Lee, Jooyoung

2017-05-22

We have developed a protein loop structure prediction method by combining a new energy function, which we call E PLM (energy for protein loop modeling), with the conformational space annealing (CSA) global optimization algorithm. The energy function includes stereochemistry, dynamic fragment assembly, distance-scaled finite ideal gas reference (DFIRE), and generalized orientation- and distance-dependent terms. For the conformational search of loop structures, we used the CSA algorithm, which has been quite successful in dealing with various hard global optimization problems. We assessed the performance of E PLM with two widely used loop-decoy sets, Jacobson and RAPPER, and compared the results against the DFIRE potential. The accuracy of model selection from a pool of loop decoys as well as de novo loop modeling starting from randomly generated structures was examined separately. For the selection of a nativelike structure from a decoy set, E PLM was more accurate than DFIRE in the case of the Jacobson set and had similar accuracy in the case of the RAPPER set. In terms of sampling more nativelike loop structures, E PLM outperformed E DFIRE for both decoy sets. This new approach equipped with E PLM and CSA can serve as the state-of-the-art de novo loop modeling method.

The Theory of Planned Behavior within the Stages of the Transtheoretical Model: Latent Structural Modeling of Stage-Specific Prediction Patterns in Physical Activity

ERIC Educational Resources Information Center

Lippke, Sonia; Nigg, Claudio R.; Maddock, Jay E.

2007-01-01

This is the first study to test whether the stages of change of the transtheoretical model are qualitatively different through exploring discontinuity patterns in theory of planned behavior (TPB) variables using latent multigroup structural equation modeling (MSEM) with AMOS. Discontinuity patterns in terms of latent means and prediction patterns…

Consequences of stage-structured predators: cannibalism, behavioral effects, and trophic cascades.

PubMed

Rudolf, Volker H W

2007-12-01

Cannibalistic and asymmetrical behavioral interactions between stages are common within stage-structured predator populations. Such direct interactions between predator stages can result in density- and trait-mediated indirect interactions between a predator and its prey. A set of structured predator-prey models is used to explore how such indirect interactions affect the dynamics and structure of communities. Analyses of the separate and combined effects of stage-structured cannibalism and behavior-mediated avoidance of cannibals under different ecological scenarios show that both cannibalism and behavioral avoidance of cannibalism can result in short- and long-term positive indirect connections between predator stages and the prey, including "apparent mutualism." These positive interactions alter the strength of trophic cascades such that the system's dynamics are determined by the interaction between bottom-up and top-down effects. Contrary to the expectation of simpler models, enrichment increases both predator and prey abundance in systems with cannibalism or behavioral avoidance of cannibalism. The effect of behavioral avoidance of cannibalism, however, depends on how strongly it affects the maturation rate of the predator. Behavioral interactions between predator stages reduce the short-term positive effect of cannibalism on the prey density, but can enhance its positive long-term effects. Both interaction types reduce the destabilizing effect of enrichment. These results suggest that inconsistencies between data and simple models can be resolved by accounting for stage-structured interactions within and among species.

A conceptual framework for a long-term economic model for the treatment of attention-deficit/hyperactivity disorder.

PubMed

Nagy, Balázs; Setyawan, Juliana; Coghill, David; Soroncz-Szabó, Tamás; Kaló, Zoltán; Doshi, Jalpa A

2017-06-01

Models incorporating long-term outcomes (LTOs) are not available to assess the health economic impact of attention-deficit/hyperactivity disorder (ADHD). Develop a conceptual modelling framework capable of assessing long-term economic impact of ADHD therapies. Literature was reviewed; a conceptual structure for the long-term model was outlined with attention to disease characteristics and potential impact of treatment strategies. The proposed model has four layers: i) multi-state short-term framework to differentiate between ADHD treatments; ii) multiple states being merged into three core health states associated with LTOs; iii) series of sub-models in which particular LTOs are depicted; iv) outcomes collected to be either used directly for economic analyses or translated into other relevant measures. This conceptual model provides a framework to assess relationships between short- and long-term outcomes of the disease and its treatment, and to estimate the economic impact of ADHD treatments throughout the course of the disease.

Predicting the Development of Analytical and Creative Abilities in Upper Elementary Grades

ERIC Educational Resources Information Center

Gubbels, Joyce; Segers, Eliane; Verhoeven, Ludo

2017-01-01

In some models, intelligence has been described as a multidimensional construct comprising both analytical and creative abilities. In addition, intelligence is considered to be dynamic rather than static. A structural equation model was used to examine the predictive role of cognitive (visual short-term memory, verbal short-term memory, selective…

Density-dependent microbial turnover improves soil carbon model predictions of long-term litter manipulations

NASA Astrophysics Data System (ADS)

Georgiou, Katerina; Abramoff, Rose; Harte, John; Riley, William; Torn, Margaret

2017-04-01

Climatic, atmospheric, and land-use changes all have the potential to alter soil microbial activity via abiotic effects on soil or mediated by changes in plant inputs. Recently, many promising microbial models of soil organic carbon (SOC) decomposition have been proposed to advance understanding and prediction of climate and carbon (C) feedbacks. Most of these models, however, exhibit unrealistic oscillatory behavior and SOC insensitivity to long-term changes in C inputs. Here we diagnose the sources of instability in four models that span the range of complexity of these recent microbial models, by sequentially adding complexity to a simple model to include microbial physiology, a mineral sorption isotherm, and enzyme dynamics. We propose a formulation that introduces density-dependence of microbial turnover, which acts to limit population sizes and reduce oscillations. We compare these models to results from 24 long-term C-input field manipulations, including the Detritus Input and Removal Treatment (DIRT) experiments, to show that there are clear metrics that can be used to distinguish and validate the inherent dynamics of each model structure. We find that widely used first-order models and microbial models without density-dependence cannot readily capture the range of long-term responses observed across the DIRT experiments as a direct consequence of their model structures. The proposed formulation improves predictions of long-term C-input changes, and implies greater SOC storage associated with CO2-fertilization-driven increases in C inputs over the coming century compared to common microbial models. Finally, we discuss our findings in the context of improving microbial model behavior for inclusion in Earth System Models.

Template-free modeling by LEE and LEER in CASP11.

PubMed

Joung, InSuk; Lee, Sun Young; Cheng, Qianyi; Kim, Jong Yun; Joo, Keehyoung; Lee, Sung Jong; Lee, Jooyoung

2016-09-01

For the template-free modeling of human targets of CASP11, we utilized two of our modeling protocols, LEE and LEER. The LEE protocol took CASP11-released server models as the input and used some of them as templates for 3D (three-dimensional) modeling. The template selection procedure was based on the clustering of the server models aided by a community detection method of a server-model network. Restraining energy terms generated from the selected templates together with physical and statistical energy terms were used to build 3D models. Side-chains of the 3D models were rebuilt using target-specific consensus side-chain library along with the SCWRL4 rotamer library, which completed the LEE protocol. The first success factor of the LEE protocol was due to efficient server model screening. The average backbone accuracy of selected server models was similar to that of top 30% server models. The second factor was that a proper energy function along with our optimization method guided us, so that we successfully generated better quality models than the input template models. In 10 out of 24 cases, better backbone structures than the best of input template structures were generated. LEE models were further refined by performing restrained molecular dynamics simulations to generate LEER models. CASP11 results indicate that LEE models were better than the average template models in terms of both backbone structures and side-chain orientations. LEER models were of improved physical realism and stereo-chemistry compared to LEE models, and they were comparable to LEE models in the backbone accuracy. Proteins 2016; 84(Suppl 1):118-130. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Precision pointing and control of flexible spacecraft

NASA Technical Reports Server (NTRS)

Bantell, M. H., Jr.

1987-01-01

The problem and long term objectives for the precision pointing and control of flexible spacecraft are given. The four basic objectives are stated in terms of two principle tasks. Under Task 1, robust low order controllers, improved structural modeling methods for control applications and identification methods for structural dynamics are being developed. Under Task 2, a lab test experiment for verification of control laws and system identification algorithms is being developed. For Task 1, work has focused on robust low order controller design and some initial considerations for structural modeling in control applications. For Task 2, work has focused on experiment design and fabrication, along with sensor selection and initial digital controller implementation. Conclusions are given.

Brain Structure-Function Couplings: Year 2 Accomplishments and Programmatic Plans

DTIC Science & Technology

2013-06-01

performance through individual-specific neurotechnologies and enhance Soldier protection technologies to minimize neural injury. The long-term vision of this...envision pathways that enable our basic science accomplishments to foster development of revolutionary Soldier neurotechnologies and Soldier protection...improve Soldier-system performance with Soldier-specific neurotechnologies . We expect mid-term impact with models linking structure and function that can

The Structure of Memory in Infants and Toddlers: An SEM Study with Full-Terms and Preterms

ERIC Educational Resources Information Center

Rose, Susan A.; Feldman, Judith F.; Jankowski, Jeffery J.; Van Rossem, Ronan

2011-01-01

There is considerable dispute about the nature of infant memory. Using SEM models, we examined whether popular characterizations of the structure of adult memory, including the two-process theory of recognition, are applicable in the infant and toddler years. The participants were a cohort of preterms and full-terms assessed longitudinally--at 1,…

Using enterprise architecture to analyse how organisational structure impact motivation and learning

NASA Astrophysics Data System (ADS)

Närman, Pia; Johnson, Pontus; Gingnell, Liv

2016-06-01

When technology, environment, or strategies change, organisations need to adjust their structures accordingly. These structural changes do not always enhance the organisational performance as intended partly because organisational developers do not understand the consequences of structural changes in performance. This article presents a model-based analysis framework for quantitative analysis of the effect of organisational structure on organisation performance in terms of employee motivation and learning. The model is based on Mintzberg's work on organisational structure. The quantitative analysis is formalised using the Object Constraint Language (OCL) and the Unified Modelling Language (UML) and implemented in an enterprise architecture tool.

Protein classification using probabilistic chain graphs and the Gene Ontology structure.

PubMed

Carroll, Steven; Pavlovic, Vladimir

2006-08-01

Probabilistic graphical models have been developed in the past for the task of protein classification. In many cases, classifications obtained from the Gene Ontology have been used to validate these models. In this work we directly incorporate the structure of the Gene Ontology into the graphical representation for protein classification. We present a method in which each protein is represented by a replicate of the Gene Ontology structure, effectively modeling each protein in its own 'annotation space'. Proteins are also connected to one another according to different measures of functional similarity, after which belief propagation is run to make predictions at all ontology terms. The proposed method was evaluated on a set of 4879 proteins from the Saccharomyces Genome Database whose interactions were also recorded in the GRID project. Results indicate that direct utilization of the Gene Ontology improves predictive ability, outperforming traditional models that do not take advantage of dependencies among functional terms. Average increase in accuracy (precision) of positive and negative term predictions of 27.8% (2.0%) over three different similarity measures and three subontologies was observed. C/C++/Perl implementation is available from authors upon request.

Short-Term Energy Outlook Model Documentation: Electricity Generation and Fuel Consumption Models

EIA Publications

2014-01-01

The electricity generation and fuel consumption models of the Short-Term Energy Outlook (STEO) model provide forecasts of electricity generation from various types of energy sources and forecasts of the quantities of fossil fuels consumed for power generation. The structure of the electricity industry and the behavior of power generators varies between different areas of the United States. In order to capture these differences, the STEO electricity supply and fuel consumption models are designed to provide forecasts for the four primary Census regions.

Intergenerational Long-Term Effects of Preschool - Structural Estimates from a Discrete Dynamic Programming Model*

PubMed Central

Heckman, James J.; Raut, Lakshmi K.

2015-01-01

This paper formulates a structural dynamic programming model of preschool investment choices of altruistic parents and then empirically estimates the structural parameters of the model using the NLSY79 data. The paper finds that preschool investment significantly boosts cognitive and non-cognitive skills, which enhance earnings and school outcomes. It also finds that a standard Mincer earnings function, by omitting measures of non-cognitive skills on the right-hand side, overestimates the rate of return to schooling. From the estimated equilibrium Markov process, the paper studies the nature of within generation earnings distribution, intergenerational earnings mobility, and schooling mobility. The paper finds that a tax-financed free preschool program for the children of poor socioeconomic status generates positive net gains to the society in terms of average earnings, higher intergenerational earnings mobility, and schooling mobility. PMID:26709326

Aeroelastic Model Structure Computation for Envelope Expansion

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2007-01-01

Structure detection is a procedure for selecting a subset of candidate terms, from a full model description, that best describes the observed output. This is a necessary procedure to compute an efficient system description which may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modeling may be of critical importance in the development of robust, parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion that may save significant development time and costs. In this study, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of non-linear aeroelastic systems. The LASSO minimises the residual sum of squares with the addition of an l(Sub 1) penalty term on the parameter vector of the traditional l(sub 2) minimisation problem. Its use for structure detection is a natural extension of this constrained minimisation approach to pseudo-linear regression problems which produces some model parameters that are exactly zero and, therefore, yields a parsimonious system description. Applicability of this technique for model structure computation for the F/A-18 (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) Active Aeroelastic Wing project using flight test data is shown for several flight conditions (Mach numbers) by identifying a parsimonious system description with a high percent fit for cross-validated data.

Discrete piezoelectric sensors and actuators for active control of two-dimensional spacecraft components

NASA Technical Reports Server (NTRS)

Bayer, Janice I.; Varadan, V. V.; Varadan, V. K.

1991-01-01

This paper describes research into the use of discrete piezoelectric sensors and actuators for active modal control of flexible two-dimensional structures such as might be used as components for spacecraft. A dynamic coupling term is defined between the sensor/actuator and the structure in terms of structural model shapes, location and piezoelectric behavior. The relative size of the coupling term determines sensor/actuator placement. Results are shown for a clamped square plate and for a large antenna. An experiment was performed on a thin foot-square plate clamped on all sides. Sizable vibration control was achieved for first, second/third (degenerate) and fourth modes.

Exploration of the folding dynamics of human telomeric G-quadruplex with a hybrid atomistic structure-based model

NASA Astrophysics Data System (ADS)

Bian, Yunqiang; Ren, Weitong; Song, Feng; Yu, Jiafeng; Wang, Jihua

2018-05-01

Structure-based models or Gō-like models, which are built from one or multiple particular experimental structures, have been successfully applied to the folding of proteins and RNAs. Recently, a variant termed the hybrid atomistic model advances the description of backbone and side chain interactions of traditional structure-based models, by borrowing the description of local interactions from classical force fields. In this study, we assessed the validity of this model in the folding problem of human telomeric DNA G-quadruplex, where local dihedral terms play important roles. A two-state model was developed and a set of molecular dynamics simulations was conducted to study the folding dynamics of sequence Htel24, which was experimentally validated to adopt two different (3 + 1) hybrid G-quadruplex topologies in K+ solution. Consistent with the experimental observations, the hybrid-1 conformation was found to be more stable and the hybrid-2 conformation was kinetically more favored. The simulations revealed that the hybrid-2 conformation folded in a higher cooperative manner, which may be the reason why it was kinetically more accessible. Moreover, by building a Markov state model, a two-quartet G-quadruplex state and a misfolded state were identified as competing states to complicate the folding process of Htel24. Besides, the simulations also showed that the transition between hybrid-1 and hybrid-2 conformations may proceed an ensemble of hairpin structures. The hybrid atomistic structure-based model reproduced the kinetic partitioning folding dynamics of Htel24 between two different folds, and thus can be used to study the complex folding processes of other G-quadruplex structures.

Estimating Model Prediction Error: Should You Treat Predictions as Fixed or Random?

NASA Technical Reports Server (NTRS)

Wallach, Daniel; Thorburn, Peter; Asseng, Senthold; Challinor, Andrew J.; Ewert, Frank; Jones, James W.; Rotter, Reimund; Ruane, Alexander

2016-01-01

Crop models are important tools for impact assessment of climate change, as well as for exploring management options under current climate. It is essential to evaluate the uncertainty associated with predictions of these models. We compare two criteria of prediction error; MSEP fixed, which evaluates mean squared error of prediction for a model with fixed structure, parameters and inputs, and MSEP uncertain( X), which evaluates mean squared error averaged over the distributions of model structure, inputs and parameters. Comparison of model outputs with data can be used to estimate the former. The latter has a squared bias term, which can be estimated using hindcasts, and a model variance term, which can be estimated from a simulation experiment. The separate contributions to MSEP uncertain (X) can be estimated using a random effects ANOVA. It is argued that MSEP uncertain (X) is the more informative uncertainty criterion, because it is specific to each prediction situation.

A modeling framework for deriving the structural and functional architecture of a short-term memory microcircuit.

PubMed

Fisher, Dimitry; Olasagasti, Itsaso; Tank, David W; Aksay, Emre R F; Goldman, Mark S

2013-09-04

Although many studies have identified neural correlates of memory, relatively little is known about the circuit properties connecting single-neuron physiology to behavior. Here we developed a modeling framework to bridge this gap and identify circuit interactions capable of maintaining short-term memory. Unlike typical studies that construct a phenomenological model and test whether it reproduces select aspects of neuronal data, we directly fit the synaptic connectivity of an oculomotor memory circuit to a broad range of anatomical, electrophysiological, and behavioral data. Simultaneous fits to all data, combined with sensitivity analyses, revealed complementary roles of synaptic and neuronal recruitment thresholds in providing the nonlinear interactions required to generate the observed circuit behavior. This work provides a methodology for identifying the cellular and synaptic mechanisms underlying short-term memory and demonstrates how the anatomical structure of a circuit may belie its functional organization. Copyright © 2013 Elsevier Inc. All rights reserved.

Characterizing Uncertainty and Variability in PBPK Models ...

EPA Pesticide Factsheets

Mode-of-action based risk and safety assessments can rely upon tissue dosimetry estimates in animals and humans obtained from physiologically-based pharmacokinetic (PBPK) modeling. However, risk assessment also increasingly requires characterization of uncertainty and variability; such characterization for PBPK model predictions represents a continuing challenge to both modelers and users. Current practices show significant progress in specifying deterministic biological models and the non-deterministic (often statistical) models, estimating their parameters using diverse data sets from multiple sources, and using them to make predictions and characterize uncertainty and variability. The International Workshop on Uncertainty and Variability in PBPK Models, held Oct 31-Nov 2, 2006, sought to identify the state-of-the-science in this area and recommend priorities for research and changes in practice and implementation. For the short term, these include: (1) multidisciplinary teams to integrate deterministic and non-deterministic/statistical models; (2) broader use of sensitivity analyses, including for structural and global (rather than local) parameter changes; and (3) enhanced transparency and reproducibility through more complete documentation of the model structure(s) and parameter values, the results of sensitivity and other analyses, and supporting, discrepant, or excluded data. Longer-term needs include: (1) theoretic and practical methodological impro

Impairment and Abuse of Elderly by Staff in Long-Term Care in Michigan: Evidence from Structural Equation Modeling

ERIC Educational Resources Information Center

Conner, Tom; Prokhorov, Artem; Page, Connie; Fang, Yu; Xiao, Yimin; Post, Lori A.

2011-01-01

Elder abuse in long-term care has become a very important public health concern. Recent estimates of elder abuse prevalence are in the range of 2% to 10% (Lachs & Pillemer, 2004), and current changes in population structure indicate a potential for an upward trend in prevalence (Malley-Morrison, Nolido, & Chawla, 2006; Post et al., 2006).…

Anthropology and affect: a consideration of the idiosyncratic dimension of human behaviour.

PubMed

Izmirlian, H

1977-01-01

In this paper a theoretical perspective is presented in which affect occupies a central position and behaviour is viewed in terms of different degrees of affective expression. Such behaviour is conceptualized in terms of three models: a structural model, a rational model and a psychological model. While the first two models are frequently encountered in the literature, the psychological model has not received explicit formulation, although, as shown here, it is crucial in understanding certain forms of idiosyncratic behaviour that have political and social relevance.

Structural Similitude and Scaling Laws for Plates and Shells: A Review

NASA Technical Reports Server (NTRS)

Simitses, G. J.; Starnes, J. H., Jr.; Rezaeepazhand, J.

2000-01-01

This paper deals with the development and use of scaled-down models in order to predict the structural behavior of large prototypes. The concept is fully described and examples are presented which demonstrate its applicability to beam-plates, plates and cylindrical shells of laminated construction. The concept is based on the use of field equations, which govern the response behavior of both the small model as well as the large prototype. The conditions under which the experimental data of a small model can be used to predict the behavior of a large prototype are called scaling laws or similarity conditions and the term that best describes the process is structural similitude. Moreover, since the term scaling is used to describe the effect of size on strength characteristics of materials, a discussion is included which should clarify the difference between "scaling law" and "size effect". Finally, a historical review of all published work in the broad area of structural similitude is presented for completeness.

GRIZZLY Model of Multi-Reactive Species Diffusion, Moisture/Heat Transfer and Alkali-Silica Reaction for Simulating Concrete Aging and Degradation

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

Huang, Hai; Spencer, Benjamin W.; Cai, Guowei

Concrete is widely used in the construction of nuclear facilities because of its structural strength and its ability to shield radiation. The use of concrete in nuclear power plants for containment and shielding of radiation and radioactive materials has made its performance crucial for the safe operation of the facility. As such, when life extension is considered for nuclear power plants, it is critical to have accurate and reliable predictive tools to address concerns related to various aging processes of concrete structures and the capacity of structures subjected to age-related degradation. The goal of this report is to document themore » progress of the development and implementation of a fully coupled thermo-hydro-mechanical-chemical model in GRIZZLY code with the ultimate goal to reliably simulate and predict long-term performance and response of aged NPP concrete structures subjected to a number of aging mechanisms including external chemical attacks and volume-changing chemical reactions within concrete structures induced by alkali-silica reactions and long-term exposure to irradiation. Based on a number of survey reports of concrete aging mechanisms relevant to nuclear power plants and recommendations from researchers in concrete community, we’ve implemented three modules during FY15 in GRIZZLY code, (1) multi-species reactive diffusion model within cement materials; (2) coupled moisture and heat transfer model in concrete; and (3) anisotropic, stress-dependent, alkali-silica reaction induced swelling model. The multi-species reactive diffusion model was implemented with the objective to model aging of concrete structures subjected to aggressive external chemical attacks (e.g., chloride attack, sulfate attack, etc.). It considers multiple processes relevant to external chemical attacks such as diffusion of ions in aqueous phase within pore spaces, equilibrium chemical speciation reactions and kinetic mineral dissolution/precipitation. The moisture/heat transfer module was implemented to simulate long-term spatial and temporal evolutions of the moisture and temperature fields within concrete structures at both room and elevated temperatures. The ASR swelling model implemented in GRIZZLY code can simulate anisotropic expansions of ASR gel under either uniaxial, biaxial and triaxial stress states, and can be run simultaneously with the moisture/heat transfer model and coupled with various elastic/inelastic solid mechanics models that were implemented in GRIZZLY code previously. This report provides detailed descriptions of the governing equations, constitutive equations and numerical algorithms of the three modules implemented in GRIZZLY during FY15, simulation results of example problems and model validation results by comparing simulations with available experimental data reported in the literature. The close match between the experiments and simulations clearly demonstrate the potential of GRIZZLY code for reliable evaluation and prediction of long-term performance and response of aged concrete structures in nuclear power plants.« less

Donabedian's structure-process-outcome quality of care model: Validation in an integrated trauma system.

PubMed

Moore, Lynne; Lavoie, André; Bourgeois, Gilles; Lapointe, Jean

2015-06-01

According to Donabedian's health care quality model, improvements in the structure of care should lead to improvements in clinical processes that should in turn improve patient outcome. This model has been widely adopted by the trauma community but has not yet been validated in a trauma system. The objective of this study was to assess the performance of an integrated trauma system in terms of structure, process, and outcome and evaluate the correlation between quality domains. Quality of care was evaluated for patients treated in a Canadian provincial trauma system (2005-2010; 57 centers, n = 63,971) using quality indicators (QIs) developed and validated previously. Structural performance was measured by transposing on-site accreditation visit reports onto an evaluation grid according to American College of Surgeons criteria. The composite process QI was calculated as the average sum of proportions of conformity to 15 process QIs derived from literature review and expert opinion. Outcome performance was measured using risk-adjusted rates of mortality, complications, and readmission as well as hospital length of stay (LOS). Correlation was assessed with Pearson's correlation coefficients. Statistically significant correlations were observed between structure and process QIs (r = 0.33), and process and outcome QIs (r = -0.33 for readmission, r = -0.27 for LOS). Significant positive correlations were also observed between outcome QIs (r = 0.37 for mortality-readmission; r = 0.39 for mortality-LOS and readmission-LOS; r = 0.45 for mortality-complications; r = 0.34 for readmission-complications; 0.63 for complications-LOS). Significant correlations between quality domains observed in this study suggest that Donabedian's structure-process-outcome model is a valid model for evaluating trauma care. Trauma centers that perform well in terms of structure also tend to perform well in terms of clinical processes, which in turn has a favorable influence on patient outcomes. Prognostic study, level III.

The NASTRAN user's manual

NASA Technical Reports Server (NTRS)

1983-01-01

All information directly associated with problem solving using the NASTRAN program is presented. This structural analysis program uses the finite element approach to structural modeling wherein the distributed finite properties of a structure are represented by a finite element of structural elements which are interconnected at a finite number of grid points, to which loads are applied and for which displacements are calculated. Procedures are described for defining and loading a structural model. Functional references for every card used for structural modeling, the NASTRAN data deck and control cards, problem solution sequences (rigid formats), using the plotting capability, writing a direct matrix abstraction program, and diagnostic messages are explained. A dictionary of mnemonics, acronyms, phrases, and other commonly used NASTRAN terms is included.

The fractography-modeling link in cleavage fracture

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

Thompson, A.W.

1997-12-31

Cleavage fracture has historically been modelled, out of necessity, in rather idealized terms. In real materials, however, there are a number of difficulties in linking such models with metallographic and fractographic observations. Some of the most vivid examples occur for {alpha}{sub 2} titanium aluminide alloys, in which, when the microstructure contains primary {alpha}{sub 2} particles, the primary particles crack first. When basketweave or Widmanstaetten structures of {alpha}{sub 2} laths comprise the microstructure, it appears that individual laths crack first. And in colony structures, cracking occurs first across the {alpha}{sub 2} lath colonies. Both detailed fractographic observations, and also a statisticalmore » model for brittle fracture by failure of weakest links, have been developed. The extent to which this can be interpreted in classical cleavage terms will be discussed.« less

Subspace Signal Processing in Structured Noise

DTIC Science & Technology

1990-12-01

1.7 Motivation for the Model ....... ........................... 8 1.8 E x am p les...S). We do not require that H be orthogonal to S. * 1.7 Motivation for the Model The linear model is quite versatile in terms of the types of signals...cross terms zero, we choose . = (SHs)- mS~u’ (3.69) This implies that = Ps4 , (3.70) and S t s (3.71) : = Ps . RPs -. The last step is to maximize

A Reaction-Diffusion Model for Synapse Growth and Long-Term Memory

NASA Astrophysics Data System (ADS)

Liu, Kang; Lisman, John; Hagan, Michael

Memory storage involves strengthening of synaptic transmission known as long-term potentiation (LTP). The late phase of LTP is associated with structural processes that enlarge the synapse. Yet, synapses must be stable, despite continual subunit turnover, over the lifetime of an encoded memory. These considerations suggest that synapses are variable-size stable structure (VSSS), meaning they can switch between multiple metastable structures with different sizes. The mechanisms underlying VSSS are poorly understood. While experiments and theory have suggested that the interplay between diffusion and receptor-scaffold interactions can lead to a preferred stable size for synaptic domains, such a mechanism cannot explain how synapses adopt widely different sizes. Here we develop a minimal reaction-diffusion model of VSSS for synapse growth, incorporating the recent observation from super-resolution microscopy that neural activity can build compositional heterogeneities within synaptic domains. We find that introducing such heterogeneities can change the stable domain size in a controlled manner. We discuss a potential connection between this model and experimental data on synapse sizes, and how it provides a possible mechanism to structurally encode graded long-term memory. We acknowledge the support from NSF INSPIRE Award number IOS-1526941 (KL, MFH, JL) and the Brandeis Center for Bioinspired Soft Materials, an NSF MRSEC, DMR- 1420382 (MFH).

Random vectors and spatial analysis by geostatistics for geotechnical applications

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

Young, D.S.

1987-08-01

Geostatistics is extended to the spatial analysis of vector variables by defining the estimation variance and vector variogram in terms of the magnitude of difference vectors. Many random variables in geotechnology are in vectorial terms rather than scalars, and its structural analysis requires those sample variable interpolations to construct and characterize structural models. A better local estimator will result in greater quality of input models; geostatistics can provide such estimators; kriging estimators. The efficiency of geostatistics for vector variables is demonstrated in a case study of rock joint orientations in geological formations. The positive cross-validation encourages application of geostatistics tomore » spatial analysis of random vectors in geoscience as well as various geotechnical fields including optimum site characterization, rock mechanics for mining and civil structures, cavability analysis of block cavings, petroleum engineering, and hydrologic and hydraulic modelings.« less

Integration of nursing assessment concepts into the medical entities dictionary using the LOINC semantic structure as a terminology model.

PubMed

Cieslowski, B J; Wajngurt, D; Cimino, J J; Bakken, S

2001-01-01

Recent investigations have tested the applicability of various terminology models for the representing nursing concepts including those related to nursing diagnoses, nursing interventions, and standardized nursing assessments as a prerequisite for building a reference terminology that supports the nursing domain. We used the semantic structure of Clinical LOINC (Logical Observations, Identifiers, Names, and Codes) as a reference terminology model to support the integration of standardized assessment terms from two nursing terminologies into the Medical Entities Dictionary (MED), the concept-oriented, metadata dictionary at New York Presbyterian Hospital. Although the LOINC semantic structure was used previously to represent laboratory terms in the MED, selected hierarchies and semantic slots required revisions in order to incorporate the nursing assessment concepts. This project was an initial step in integrating nursing assessment concepts into the MED in a manner consistent with evolving standards for reference terminology models. Moreover, the revisions provide the foundation for adding other types of standardized assessments to the MED.

Integration of nursing assessment concepts into the medical entities dictionary using the LOINC semantic structure as a terminology model.

PubMed Central

Cieslowski, B. J.; Wajngurt, D.; Cimino, J. J.; Bakken, S.

2001-01-01

Recent investigations have tested the applicability of various terminology models for the representing nursing concepts including those related to nursing diagnoses, nursing interventions, and standardized nursing assessments as a prerequisite for building a reference terminology that supports the nursing domain. We used the semantic structure of Clinical LOINC (Logical Observations, Identifiers, Names, and Codes) as a reference terminology model to support the integration of standardized assessment terms from two nursing terminologies into the Medical Entities Dictionary (MED), the concept-oriented, metadata dictionary at New York Presbyterian Hospital. Although the LOINC semantic structure was used previously to represent laboratory terms in the MED, selected hierarchies and semantic slots required revisions in order to incorporate the nursing assessment concepts. This project was an initial step in integrating nursing assessment concepts into the MED in a manner consistent with evolving standards for reference terminology models. Moreover, the revisions provide the foundation for adding other types of standardized assessments to the MED. PMID:11825165

Numerical and analytical investigation towards performance enhancement of a newly developed rockfall protective cable-net structure

NASA Astrophysics Data System (ADS)

Dhakal, S.; Bhandary, N. P.; Yatabe, R.; Kinoshita, N.

2012-04-01

In a previous companion paper, we presented a three-tier modelling of a particular type of rockfall protective cable-net structure (barrier), developed newly in Japan. Therein, we developed a three-dimensional, Finite Element based, nonlinear numerical model having been calibrated/back-calculated and verified with the element- and structure-level physical tests. Moreover, using a very simple, lumped-mass, single-degree-of-freedom, equivalently linear analytical model, a global-displacement-predictive correlation was devised by modifying the basic equation - obtained by combining the principles of conservation of linear momentum and energy - based on the back-analysis of the tests on the numerical model. In this paper, we use the developed models to explore the performance enhancement potential of the structure in terms of (a) the control of global displacement - possibly the major performance criterion for the proposed structure owing to a narrow space available in the targeted site, and (b) the increase in energy dissipation by the existing U-bolt-type Friction-brake Devices - which are identified to have performed weakly when integrated into the structure. A set of parametric investigations have revealed correlations to achieve the first objective in terms of the structure's mass, particularly by manipulating the wire-net's characteristics, and has additionally disclosed the effects of the impacting-block's parameters. Towards achieving the second objective, another set of parametric investigations have led to a proposal of a few innovative improvements in the constitutive behaviour (model) of the studied brake device (dissipator), in addition to an important recommendation of careful handling of the device based on the identified potential flaw.

The indirect association of job strain with long-term sickness absence through bullying: a mediation analysis using structural equation modeling.

PubMed

Janssens, Heidi; Braeckman, Lutgart; De Clercq, Bart; Casini, Annalisa; De Bacquer, Dirk; Kittel, France; Clays, Els

2016-08-22

In this longitudinal study the complex interplay between both job strain and bullying in relation to sickness absence was investigated. Following the "work environment hypothesis", which establishes several work characteristics as antecedents of bullying, we assumed that job strain, conceptualized by the Job-Demand-Control model, has an indirect relation with long-term sickness absence through bullying. The sample consisted of 2983 Belgian workers, aged 30 to 55 years, who participated in the Belstress III study. They completed a survey, including the Job Content Questionnaire and a bullying inventory, at baseline. Their sickness absence figures were registered during 1 year follow-up. Long-term sickness absence was defined as at least 15 consecutive days. A mediation analysis, using structural equation modeling, was performed to examine the indirect association of job strain through bullying with long-term sickness absence. The full structural model was adjusted for several possible confounders: age, gender, occupational group, educational level, company, smoking habits, alcohol use, body mass index, self-rated health, baseline long-term sickness absence and neuroticism. The results support the hypothesis: a significant indirect association of job strain with long-term sickness absence through bullying was observed, suggesting that bullying is an intermediate variable between job strain and long-term sickness absence. No evidence for the reversed pathway of an indirect association of bullying through job strain was found. Bullying was observed as a mediating variable in the relation between job strain and sickness absence. The results suggest that exposure to job strain may create circumstances in which a worker risks to become a target of bullying. Our findings are generally in line with the work environment hypothesis, which emphasizes the importance of organizational work factors in the origin of bullying. This study highlights that remodeling jobs to reduce job strain may be important in the prevention of bullying and subsequent sickness absence.

Cumulant-based expressions for the multibody terms for the correlation between local and electrostatic interactions in the united-residue force field

NASA Astrophysics Data System (ADS)

Liwo, Adam; Czaplewski, Cezary; Pillardy, Jarosław; Scheraga, Harold A.

2001-08-01

A general method to derive site-site or united-residue potentials is presented. The basic principle of the method is the separation of the degrees of freedom of a system into the primary and secondary ones. The primary degrees of freedom describe the basic features of the system, while the secondary ones are averaged over when calculating the potential of mean force, which is hereafter referred to as the restricted free energy (RFE) function. The RFE can be factored into one-, two-, and multibody terms, using the cluster-cumulant expansion of Kubo. These factors can be assigned the functional forms of the corresponding lowest-order nonzero generalized cumulants, which can, in most cases, be evaluated analytically, after making some simplifying assumptions. This procedure to derive coarse-grain force fields is very valuable when applied to multibody terms, whose functional forms are hard to deduce in another way (e.g., from structural databases). After the functional forms have been derived, they can be parametrized based on the RFE surfaces of model systems obtained from all-atom models or on the statistics derived from structural databases. The approach has been applied to our united-residue force field for proteins. Analytical expressions were derived for the multibody terms pertaining to the correlation between local and electrostatic interactions within the polypeptide backbone; these expressions correspond to up to sixth-order terms in the cumulant expansion of the RFE. These expressions were subsequently parametrized by fitting to the RFEs of selected peptide fragments, calculated with the empirical conformational energy program for peptides force field. The new multibody terms enable not only the heretofore predictable α-helical segments, but also regular β-sheets, to form as the lowest-energy structures, as assessed by test calculations on a model helical protein A, as well as a model 20-residue polypeptide (betanova); the latter was not possible without introducing these new terms.

Research on the Mechanical Properties of a Glass Fiber Reinforced Polymer-Steel Combined Truss Structure

PubMed Central

Liu, Pengfei; Zhao, Qilin; Li, Fei; Liu, Jinchun; Chen, Haosen

2014-01-01

An assembled plane truss structure used for vehicle loading is designed and manufactured. In the truss, the glass fiber reinforced polymer (GFRP) tube and the steel joint are connected by a new technology featuring a pretightened tooth connection. The detailed description for the rod and node design is introduced in this paper, and a typical truss panel is fabricated. Under natural conditions, the short-term load test and long-term mechanical performance test for one year are performed to analyze its performance and conduct a comparative analysis for a reasonable FEM model. The study shows that the design and fabrication for the node of an assembled truss panel are convenient, safe, and reliable; because of the creep control design of the rods, not only does the short-term structural stiffness meet the design requirement but also the long-term creep deformation tends towards stability. In addition, no significant change is found in the elastic modules, so this structure can be applied in actual engineering. Although the safety factor for the strength of the composite rods is very large, it has a lightweight advantage over the steel truss for the low density of GFRP. In the FEM model, simplifying the node as a hinge connection relatively conforms to the actual status. PMID:25247203

Research on the mechanical properties of a glass fiber reinforced polymer-steel combined truss structure.

PubMed

Liu, Pengfei; Zhao, Qilin; Li, Fei; Liu, Jinchun; Chen, Haosen

2014-01-01

An assembled plane truss structure used for vehicle loading is designed and manufactured. In the truss, the glass fiber reinforced polymer (GFRP) tube and the steel joint are connected by a new technology featuring a pretightened tooth connection. The detailed description for the rod and node design is introduced in this paper, and a typical truss panel is fabricated. Under natural conditions, the short-term load test and long-term mechanical performance test for one year are performed to analyze its performance and conduct a comparative analysis for a reasonable FEM model. The study shows that the design and fabrication for the node of an assembled truss panel are convenient, safe, and reliable; because of the creep control design of the rods, not only does the short-term structural stiffness meet the design requirement but also the long-term creep deformation tends towards stability. In addition, no significant change is found in the elastic modules, so this structure can be applied in actual engineering. Although the safety factor for the strength of the composite rods is very large, it has a lightweight advantage over the steel truss for the low density of GFRP. In the FEM model, simplifying the node as a hinge connection relatively conforms to the actual status.

Carbon fluxes in tropical forest ecosystems: the value of Eddy-covariance data for individual-based dynamic forest gap models

NASA Astrophysics Data System (ADS)

Roedig, Edna; Cuntz, Matthias; Huth, Andreas

2015-04-01

The effects of climatic inter-annual fluctuations and human activities on the global carbon cycle are uncertain and currently a major issue in global vegetation models. Individual-based forest gap models, on the other hand, model vegetation structure and dynamics on a small spatial (<100 ha) and large temporal scale (>1000 years). They are well-established tools to reproduce successions of highly-diverse forest ecosystems and investigate disturbances as logging or fire events. However, the parameterizations of the relationships between short-term climate variability and forest model processes are often uncertain in these models (e.g. daily variable temperature and gross primary production (GPP)) and cannot be constrained from forest inventories. We addressed this uncertainty and linked high-resolution Eddy-covariance (EC) data with an individual-based forest gap model. The forest model FORMIND was applied to three diverse tropical forest sites in the Amazonian rainforest. Species diversity was categorized into three plant functional types. The parametrizations for the steady-state of biomass and forest structure were calibrated and validated with different forest inventories. The parameterizations of relationships between short-term climate variability and forest model processes were evaluated with EC-data on a daily time step. The validations of the steady-state showed that the forest model could reproduce biomass and forest structures from forest inventories. The daily estimations of carbon fluxes showed that the forest model reproduces GPP as observed by the EC-method. Daily fluctuations of GPP were clearly reflected as a response to daily climate variability. Ecosystem respiration remains a challenge on a daily time step due to a simplified soil respiration approach. In the long-term, however, the dynamic forest model is expected to estimate carbon budgets for highly-diverse tropical forests where EC-measurements are rare.

A Comparative Analysis of United States and Chinese Economic Engagement in Sub Saharan Africa

DTIC Science & Technology

2016-03-01

model of conditional aid attached to structural and social reform. The U.S. trade relationships with sub- Saharan Africa are separate from its aid...relationship to the region is fundamentally different, following a Western model of conditional aid attached to structural and social reform. The U.S...demonstrated structural improvement within a given state and Chinese policy forbidding any conditionality beyond the terms of the transaction.8 The

A knowledge-based potential with an accurate description of local interactions improves discrimination between native and near-native protein conformations.

PubMed

Ferrada, Evandro; Vergara, Ismael A; Melo, Francisco

2007-01-01

The correct discrimination between native and near-native protein conformations is essential for achieving accurate computer-based protein structure prediction. However, this has proven to be a difficult task, since currently available physical energy functions, empirical potentials and statistical scoring functions are still limited in achieving this goal consistently. In this work, we assess and compare the ability of different full atom knowledge-based potentials to discriminate between native protein structures and near-native protein conformations generated by comparative modeling. Using a benchmark of 152 near-native protein models and their corresponding native structures that encompass several different folds, we demonstrate that the incorporation of close non-bonded pairwise atom terms improves the discriminating power of the empirical potentials. Since the direct and unbiased derivation of close non-bonded terms from current experimental data is not possible, we obtained and used those terms from the corresponding pseudo-energy functions of a non-local knowledge-based potential. It is shown that this methodology significantly improves the discrimination between native and near-native protein conformations, suggesting that a proper description of close non-bonded terms is important to achieve a more complete and accurate description of native protein conformations. Some external knowledge-based energy functions that are widely used in model assessment performed poorly, indicating that the benchmark of models and the specific discrimination task tested in this work constitutes a difficult challenge.

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

Sparse representation based image interpolation with nonlocal autoregressive modeling.

PubMed

Dong, Weisheng; Zhang, Lei; Lukac, Rastislav; Shi, Guangming

2013-04-01

Sparse representation is proven to be a promising approach to image super-resolution, where the low-resolution (LR) image is usually modeled as the down-sampled version of its high-resolution (HR) counterpart after blurring. When the blurring kernel is the Dirac delta function, i.e., the LR image is directly down-sampled from its HR counterpart without blurring, the super-resolution problem becomes an image interpolation problem. In such cases, however, the conventional sparse representation models (SRM) become less effective, because the data fidelity term fails to constrain the image local structures. In natural images, fortunately, many nonlocal similar patches to a given patch could provide nonlocal constraint to the local structure. In this paper, we incorporate the image nonlocal self-similarity into SRM for image interpolation. More specifically, a nonlocal autoregressive model (NARM) is proposed and taken as the data fidelity term in SRM. We show that the NARM-induced sampling matrix is less coherent with the representation dictionary, and consequently makes SRM more effective for image interpolation. Our extensive experimental results demonstrate that the proposed NARM-based image interpolation method can effectively reconstruct the edge structures and suppress the jaggy/ringing artifacts, achieving the best image interpolation results so far in terms of PSNR as well as perceptual quality metrics such as SSIM and FSIM.

Unified constitutive models for high-temperature structural applications

NASA Technical Reports Server (NTRS)

Lindholm, U. S.; Chan, K. S.; Bodner, S. R.; Weber, R. M.; Walker, K. P.

1988-01-01

Unified constitutive models are characterized by the use of a single inelastic strain rate term for treating all aspects of inelastic deformation, including plasticity, creep, and stress relaxation under monotonic or cyclic loading. The structure of this class of constitutive theory pertinent for high temperature structural applications is first outlined and discussed. The effectiveness of the unified approach for representing high temperature deformation of Ni-base alloys is then evaluated by extensive comparison of experimental data and predictions of the Bodner-Partom and the Walker models. The use of the unified approach for hot section structural component analyses is demonstrated by applying the Walker model in finite element analyses of a benchmark notch problem and a turbine blade problem.

Can We Recognize an Innovation? Perspective from an Evolving Network Model

NASA Astrophysics Data System (ADS)

Jain, Sanjay; Krishna, Sandeep

"Innovations" are central to the evolution of societies and the evolution of life. But what constitutes an innovation? We can often agree after the event, when its consequences and impact over a long term are known, whether something was an innovation, and whether it was a "big" innovation or a "minor" one. But can we recognize an innovation "on the fly" as it appears? Successful entrepreneurs often can. Is it possible to formalize that intuition? We discuss this question in the setting of a mathematical model of evolving networks. The model exhibits self-organization , growth, stasis, and collapse of a complex system with many interacting components, reminiscent of real-world phenomena. A notion of "innovation" is formulated in terms of graph-theoretic constructs and other dynamical variables of the model. A new node in the graph gives rise to an innovation, provided it links up "appropriately" with existing nodes; in this view innovation necessarily depends upon the existing context. We show that innovations, as defined by us, play a major role in the birth, growth, and destruction of organizational structures. Furthermore, innovations can be categorized in terms of their graph-theoretic structure as they appear. Different structural classes of innovation have potentially different qualitative consequences for the future evolution of the system, some minor and some major. Possible general lessons from this specific model are briefly discussed.

Simulating Cyclic Evolution of Coronal Magnetic Fields using a Potential Field Source Surface Model Coupled with a Dynamo Model

NASA Astrophysics Data System (ADS)

Suresh, A.; Dikpati, M.; Burkepile, J.; de Toma, G.

2013-12-01

The structure of the Sun's corona varies with solar cycle, from a near spherical symmetry at solar maximum to an axial dipole at solar minimum. Why does this pattern occur? It is widely accepted that large-scale coronal structure is governed by magnetic fields, which are most likely generated by the dynamo action in the solar interior. In order to understand the variation in coronal structure, we couple a potential field source surface model with a cyclic dynamo model. In this coupled model, the magnetic field inside the convection zone is governed by the dynamo equation and above the photosphere these dynamo-generated fields are extended from the photosphere to the corona by using a potential field source surface model. Under the assumption of axisymmetry, the large-scale poloidal fields can be written in terms of the curl of a vector potential. Since from the photosphere and above the magnetic diffusivity is essentially infinite, the evolution of the vector potential is given by Laplace's Equation, the solution of which is obtained in the form of a first order Associated Legendre Polynomial. By taking linear combinations of these polynomial terms, we find solutions that match more complex coronal structures. Choosing images of the global corona from the Mauna Loa Solar Observatory at each Carrington rotation over half a cycle (1986-1991), we compute the coefficients of the Associated Legendre Polynomials up to degree eight and compare with observation. We reproduce some previous results that at minimum the dipole term dominates, but that this term fades with the progress of the cycle and higher order multipole terms begin to dominate. We find that the amplitudes of these terms are not exactly the same in the two limbs, indicating that there is some phi dependence. Furthermore, by comparing the solar minimum corona during the past three minima (1986, 1996, and 2008), we find that, while both the 1986 and 1996 minima were dipolar, the minimum in 2008 was unusual, as there was departure from a dipole. In order to investigate the physical cause of this departure from dipole, we implement north-south asymmetry in the surface source of the magnetic fields in our model, and find that such n/s asymmetry in solar cycle could be one of the reasons for this departure. This work is partially supported by NASA's LWS grant with award number NNX08AQ34G. NCAR is sponsored by the NSF.

Resolving dispersion and induction components for polarisable molecular simulations of ionic liquids

NASA Astrophysics Data System (ADS)

Pádua, Agílio A. H.

2017-05-01

One important development in interaction potential models, or atomistic force fields, for molecular simulation is the inclusion of explicit polarisation, which represents the induction effects of charged or polar molecules on polarisable electron clouds. Polarisation can be included through fluctuating charges, induced multipoles, or Drude dipoles. This work uses Drude dipoles and is focused on room-temperature ionic liquids, for which fixed-charge models predict too slow dynamics. The aim of this study is to devise a strategy to adapt existing non-polarisable force fields upon addition of polarisation, because induction was already contained to an extent, implicitly, due to parametrisation against empirical data. Therefore, a fraction of the van der Waals interaction energy should be subtracted so that the Lennard-Jones terms only account for dispersion and the Drude dipoles for induction. Symmetry-adapted perturbation theory is used to resolve the dispersion and induction terms in dimers and to calculate scaling factors to reduce the Lennard-Jones terms from the non-polarisable model. Simply adding Drude dipoles to an existing fixed-charge model already improves the prediction of transport properties, increasing diffusion coefficients, and lowering the viscosity. Scaling down the Lennard-Jones terms leads to still faster dynamics and densities that match experiment extremely well. The concept developed here improves the overall prediction of density and transport properties and can be adapted to other models and systems. In terms of microscopic structure of the ionic liquids, the inclusion of polarisation and the down-scaling of Lennard-Jones terms affect only slightly the ordering of the first shell of counterions, leading to small decreases in coordination numbers. Remarkably, the effect of polarisation is major beyond first neighbours, significantly weakening spatial correlations, a structural effect that is certainly related to the faster dynamics of polarisable models.

Cyclic Evolution of Coronal Fields from a Coupled Dynamo Potential-Field Source-Surface Model.

PubMed

Dikpati, Mausumi; Suresh, Akshaya; Burkepile, Joan

The structure of the Sun's corona varies with the solar-cycle phase, from a near spherical symmetry at solar maximum to an axial dipole at solar minimum. It is widely accepted that the large-scale coronal structure is governed by magnetic fields that are most likely generated by dynamo action in the solar interior. In order to understand the variation in coronal structure, we couple a potential-field source-surface model with a cyclic dynamo model. In this coupled model, the magnetic field inside the convection zone is governed by the dynamo equation; these dynamo-generated fields are extended from the photosphere to the corona using a potential-field source-surface model. Assuming axisymmetry, we take linear combinations of associated Legendre polynomials that match the more complex coronal structures. Choosing images of the global corona from the Mauna Loa Solar Observatory at each Carrington rotation over half a cycle (1986 - 1991), we compute the coefficients of the associated Legendre polynomials up to degree eight and compare with observations. We show that at minimum the dipole term dominates, but it fades as the cycle progresses; higher-order multipolar terms begin to dominate. The amplitudes of these terms are not exactly the same for the two limbs, indicating that there is a longitude dependence. While both the 1986 and the 1996 minimum coronas were dipolar, the minimum in 2008 was unusual, since there was a substantial departure from a dipole. We investigate the physical cause of this departure by including a North-South asymmetry in the surface source of the magnetic fields in our flux-transport dynamo model, and find that this asymmetry could be one of the reasons for departure from the dipole in the 2008 minimum.

Ab Initio structure prediction for Escherichia coli: towards genome-wide protein structure modeling and fold assignment

PubMed Central

Xu, Dong; Zhang, Yang

2013-01-01

Genome-wide protein structure prediction and structure-based function annotation have been a long-term goal in molecular biology but not yet become possible due to difficulties in modeling distant-homology targets. We developed a hybrid pipeline combining ab initio folding and template-based modeling for genome-wide structure prediction applied to the Escherichia coli genome. The pipeline was tested on 43 known sequences, where QUARK-based ab initio folding simulation generated models with TM-score 17% higher than that by traditional comparative modeling methods. For 495 unknown hard sequences, 72 are predicted to have a correct fold (TM-score > 0.5) and 321 have a substantial portion of structure correctly modeled (TM-score > 0.35). 317 sequences can be reliably assigned to a SCOP fold family based on structural analogy to existing proteins in PDB. The presented results, as a case study of E. coli, represent promising progress towards genome-wide structure modeling and fold family assignment using state-of-the-art ab initio folding algorithms. PMID:23719418

Studies of Ionospheric Plasma Structuring at Low Latitudes from Space and Ground, their Modeling and Relationship to Scintillations

DTIC Science & Technology

2008-09-30

2006JA011646, 2006. [published, refereed] Lee, J. K., F. Kamalabadi, and J. J. Makela, Three-dimensional tomography of ionospheric variability using a...Studies of Ionospheric Plasma Structuring at Low Latitudes from Space and Ground, their Modeling and...illinois.edu Award Number: N00173-05-1-G904 LONG-TERM GOALS This program combines observations and modeling of the nighttime ionosphere to come to a

A Latent Variable Analysis of Working Memory Capacity, Short-Term Memory Capacity, Processing Speed, and General Fluid Intelligence.

ERIC Educational Resources Information Center

Conway, Andrew R. A.; Cowan, Nelsin; Bunting, Michael F.; Therriault, David J.; Minkoff, Scott R. B.

2002-01-01

Studied the interrelationships among general fluid intelligence, short-term memory capacity, working memory capacity, and processing speed in 120 young adults and used structural equation modeling to determine the best predictor of general fluid intelligence. Results suggest that working memory capacity, but not short-term memory capacity or…

The Cascadia Subduction Zone: two contrasting models of lithospheric structure

USGS Publications Warehouse

Romanyuk, T.V.; Blakely, R.; Mooney, W.D.

1998-01-01

The Pacific margin of North America is one of the most complicated regions in the world in terms of its structure and present day geodynamic regime. The aim of this work is to develop a better understanding of lithospheric structure of the Pacific Northwest, in particular the Cascadia subduction zone of Southwest Canada and Northwest USA. The goal is to compare and contrast the lithospheric density structure along two profiles across the subduction zone and to interpet the differences in terms of active processes. The subduction of the Juan de Fuca plate beneath North America changes markedly along the length of the subduction zone, notably in the angle of subduction, distribution of earthquakes and volcanism, goelogic and seismic structure of the upper plate, and regional horizontal stress. To investigate these characteristics, we conducted detailed density modeling of the crust and mantle along two transects across the Cascadia subduction zone. One crosses Vancouver Island and the Canadian margin, the other crosses the margin of central Oregon.

Characterization of structural connections for multicomponent systems

NASA Technical Reports Server (NTRS)

Lawrence, Charles; Huckelbridge, Arthur A.

1988-01-01

This study explores combining Component Mode Synthesis methods for coupling structural components with Parameter Identification procedures for improving the analytical modeling of the connections. Improvements in the connection stiffness and damping properties are computed in terms of physical parameters so that the physical characteristics of the connections can be better understood, in addition to providing improved input for the system model.

Subjective and Objective Parameters Determining "Salience" in Long-Term Dialect Accommodation.

ERIC Educational Resources Information Center

Auer, Peter; Barden, Birgit; Grosskopf, Beate

1998-01-01

Presents results of a longitudinal study on long-term dialect accommodation in a German dialect setting. An important model of explaining which linguistic structures undergo such convergence and which do not makes use of the notion of "salience." (Author/VWL)

Thermodynamic model of natural, medieval and nuclear waste glass durability

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

Jantzen, C.M.; Plodinec, M.J.

1983-01-01

A thermodynamic model of glass durability based on hydration of structural units has been applied to natural glass, medieval window glasses, and glasses containing nuclear waste. The relative durability predicted from the calculated thermodynamics correlates directly with the experimentally observed release of structural silicon in the leaching solution in short-term laboratory tests. By choosing natural glasses and ancient glasses whose long-term performance is known, and which bracket the durability of waste glasses, the long-term stability of nuclear waste glasses can be interpolated among these materials. The current Savannah River defense waste glass formulation is as durable as natural basalt frommore » the Hanford Reservation (10/sup 6/ years old). The thermodynamic hydration energy is shown to be related to the bond energetics of the glass. 69 references, 2 figures, 1 table.« less

Mathematical model of the loan portfolio dynamics in the form of Markov chain considering the process of new customers attraction

NASA Astrophysics Data System (ADS)

Bozhalkina, Yana

2017-12-01

Mathematical model of the loan portfolio structure change in the form of Markov chain is explored. This model considers in one scheme both the process of customers attraction, their selection based on the credit score, and loans repayment. The model describes the structure and volume of the loan portfolio dynamics, which allows to make medium-term forecasts of profitability and risk. Within the model corrective actions of bank management in order to increase lending volumes or to reduce the risk are formalized.

Automation life-cycle cost model

NASA Technical Reports Server (NTRS)

Gathmann, Thomas P.; Reeves, Arlinda J.; Cline, Rick; Henrion, Max; Ruokangas, Corinne

1992-01-01

The problem domain being addressed by this contractual effort can be summarized by the following list: Automation and Robotics (A&R) technologies appear to be viable alternatives to current, manual operations; Life-cycle cost models are typically judged with suspicion due to implicit assumptions and little associated documentation; and Uncertainty is a reality for increasingly complex problems and few models explicitly account for its affect on the solution space. The objectives for this effort range from the near-term (1-2 years) to far-term (3-5 years). In the near-term, the envisioned capabilities of the modeling tool are annotated. In addition, a framework is defined and developed in the Decision Modelling System (DEMOS) environment. Our approach is summarized as follows: Assess desirable capabilities (structure into near- and far-term); Identify useful existing models/data; Identify parameters for utility analysis; Define tool framework; Encode scenario thread for model validation; and Provide transition path for tool development. This report contains all relevant, technical progress made on this contractual effort.

Static shape control for flexible structures

NASA Technical Reports Server (NTRS)

Rodriguez, G.; Scheid, R. E., Jr.

1986-01-01

An integrated methodology is described for defining static shape control laws for large flexible structures. The techniques include modeling, identifying and estimating the control laws of distributed systems characterized in terms of infinite dimensional state and parameter spaces. The models are expressed as interconnected elliptic partial differential equations governing a range of static loads, with the capability of analyzing electromagnetic fields around antenna systems. A second-order analysis is carried out for statistical errors, and model parameters are determined by maximizing an appropriate defined likelihood functional which adjusts the model to observational data. The parameter estimates are derived from the conditional mean of the observational data, resulting in a least squares superposition of shape functions obtained from the structural model.

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

Vilarrasa, Víctor; Rutqvist, Jonny; Blanco Martin, Laura

Expansive soils are suitable as backfill and buffer materials in engineered barrier systems to isolate heat-generating nuclear waste in deep geological formations. The canisters containing nuclear waste would be placed in tunnels excavated at a depth of several hundred meters. The expansive soil should provide enough swelling capacity to support the tunnel walls, thereby reducing the impact of the excavation-damaged zone on the long-term mechanical and flow-barrier performance. In addition to their swelling capacity, expansive soils are characterized by accumulating irreversible strain on suction cycles and by effects of microstructural swelling on water permeability that for backfill or buffer materialsmore » can significantly delay the time it takes to reach full saturation. In order to simulate these characteristics of expansive soils, a dual-structure constitutive model that includes two porosity levels is necessary. The authors present the formulation of a dual-structure model and describe its implementation into a coupled fluid flow and geomechanical numerical simulator. The authors use the Barcelona Basic Model (BBM), which is an elastoplastic constitutive model for unsaturated soils, to model the macrostructure, and it is assumed that the strains of the microstructure, which are volumetric and elastic, induce plastic strain to the macrostructure. The authors tested and demonstrated the capabilities of the implemented dual-structure model by modeling and reproducing observed behavior in two laboratory tests of expansive clay. As observed in the experiments, the simulations yielded nonreversible strain accumulation with suction cycles and a decreasing swelling capacity with increasing confining stress. Finally, the authors modeled, for the first time using a dual-structure model, the long-term (100,000 years) performance of a generic heat-generating nuclear waste repository with waste emplacement in horizontal tunnels backfilled with expansive clay and hosted in a clay rock formation. The thermo-hydro-mechanical results of the dual-structure model were compared with those of the standard single-structure BBM. The main difference between the simulation results from the two models is that the dual-structure model predicted a time to fully saturate the expansive clay barrier on the order of thousands of years, whereas the standard single-structure BBM yielded a time on the order of tens of years. These examples show that a dual-structure model, such as the one presented here, is necessary to properly model the thermo-hydro-mechanical behavior of expansive soils.« less

Modeling Structure and Dynamics of Protein Complexes with SAXS Profiles

PubMed Central

Schneidman-Duhovny, Dina; Hammel, Michal

2018-01-01

Small-angle X-ray scattering (SAXS) is an increasingly common and useful technique for structural characterization of molecules in solution. A SAXS experiment determines the scattering intensity of a molecule as a function of spatial frequency, termed SAXS profile. SAXS profiles can be utilized in a variety of molecular modeling applications, such as comparing solution and crystal structures, structural characterization of flexible proteins, assembly of multi-protein complexes, and modeling of missing regions in the high-resolution structure. Here, we describe protocols for modeling atomic structures based on SAXS profiles. The first protocol is for comparing solution and crystal structures including modeling of missing regions and determination of the oligomeric state. The second protocol performs multi-state modeling by finding a set of conformations and their weights that fit the SAXS profile starting from a single-input structure. The third protocol is for protein-protein docking based on the SAXS profile of the complex. We describe the underlying software, followed by demonstrating their application on interleukin 33 (IL33) with its primary receptor ST2 and DNA ligase IV-XRCC4 complex. PMID:29605933

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.

Stochastic Time Models of Syllable Structure

PubMed Central

Shaw, Jason A.; Gafos, Adamantios I.

2015-01-01

Drawing on phonology research within the generative linguistics tradition, stochastic methods, and notions from complex systems, we develop a modelling paradigm linking phonological structure, expressed in terms of syllables, to speech movement data acquired with 3D electromagnetic articulography and X-ray microbeam methods. The essential variable in the models is syllable structure. When mapped to discrete coordination topologies, syllabic organization imposes systematic patterns of variability on the temporal dynamics of speech articulation. We simulated these dynamics under different syllabic parses and evaluated simulations against experimental data from Arabic and English, two languages claimed to parse similar strings of segments into different syllabic structures. Model simulations replicated several key experimental results, including the fallibility of past phonetic heuristics for syllable structure, and exposed the range of conditions under which such heuristics remain valid. More importantly, the modelling approach consistently diagnosed syllable structure proving resilient to multiple sources of variability in experimental data including measurement variability, speaker variability, and contextual variability. Prospects for extensions of our modelling paradigm to acoustic data are also discussed. PMID:25996153

Long term corrosion on T91 and AISI1 316L steel in flowing lead alloy and corrosion protection barrier development: Experiments and models

NASA Astrophysics Data System (ADS)

Weisenburger, A.; Schroer, C.; Jianu, A.; Heinzel, A.; Konys, J.; Steiner, H.; Müller, G.; Fazio, C.; Gessi, A.; Babayan, S.; Kobzova, A.; Martinelli, L.; Ginestar, K.; Balbaud-Célerier, F.; Martín-Muñoz, F. J.; Soler Crespo, L.

2011-08-01

Considering the status of knowledge on corrosion and corrosion protection and especially the need for long term compatibility data of structural materials in HLM a set of experiments to generate reliable long term data was defined and performed. The long term corrosion behaviour of the two structural materials foreseen in ADS, 316L and T91, was investigated in the design relevant temperature field, i.e. from 300 to 550 °C. The operational window of the two steels in this temperature range was identified and all oxidation data were used to develop and validate the models of oxide scale growth in PbBi. A mechanistic model capable to predict the oxidation rate applying some experimentally fitted parameters has been developed. This model assumes parabolic oxidation and might be used for design and safety relevant investigations in future. Studies on corrosion barrier development allowed to define the required Al content for the formation of thin alumina scales in LBE. These results as well as future steps and required improvements are discussed. Variation of experimental conditions clearly showed that specific care has to be taken with respect to local flow conditions and oxygen concentrations.

Age or stage structure? A comparison of dynamic outcomes from discrete age- and stage-structured population models.

PubMed

Wikan, Arild

2012-06-01

Discrete stage-structured density-dependent and discrete age-structured density-dependent population models are considered. Regarding the former, we prove that the model at hand is permanent (i.e., that the population will neither go extinct nor exhibit explosive oscillations) and given density dependent fecundity terms we also show that species with delayed semelparous life histories tend to be more stable than species which possess precocious semelparous life histories. Moreover, our findings together with results obtained from other stage-structured models seem to illustrate a fairly general ecological principle, namely that iteroparous species are more stable than semelparous species. Our analysis of various age-structured models does not necessarily support the conclusions above. In fact, species with precocious life histories now appear to possess better stability properties than species with delayed life histories, especially in the iteroparous case. We also show that there are dynamical outcomes from semelparous age-structured models which we are not able to capture in corresponding stage-structured cases. Finally, both age- and stage-structured population models may generate periodic dynamics of low period (either exact or approximate). The important prerequisite is to assume density-dependent survival probabilities.

Assessment of Technologies for the Space Shuttle External Tank Thermal Protection System and Recommendations for Technology Improvement. Part 2; Structural Analysis Technologies and Modeling Practices

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.; Nemeth, Michael P.; Hilburger, Mark W.

2004-01-01

A technology review and assessment of modeling and analysis efforts underway in support of a safe return to flight of the thermal protection system (TPS) for the Space Shuttle external tank (ET) are summarized. This review and assessment effort focuses on the structural modeling and analysis practices employed for ET TPS foam design and analysis and on identifying analysis capabilities needed in the short-term and long-term. The current understanding of the relationship between complex flight environments and ET TPS foam failure modes are reviewed as they relate to modeling and analysis. A literature review on modeling and analysis of TPS foam material systems is also presented. Finally, a review of modeling and analysis tools employed in the Space Shuttle Program is presented for the ET TPS acreage and close-out foam regions. This review includes existing simplified engineering analysis tools are well as finite element analysis procedures.

Reading Quizzes Improve Exam Scores for Community College Students.

PubMed

Pape-Lindstrom, Pamela; Eddy, Sarah; Freeman, Scott

2018-06-01

To test the hypothesis that adding course structure may encourage self-regulated learning skills resulting in an increase in student exam performance in the community college setting, we added daily preclass online, open-book reading quizzes to an introductory biology course. We compared three control terms without reading quizzes and three experimental terms with online, open-book reading quizzes; the instructor of record, class size, and instructional time did not vary. Analyzing the Bloom's taxonomy level of a random sample of exam questions indicated a similar cognitive level of high-stakes assessments across all six terms in the study. To control for possible changes in student preparation or ability over time, we calculated each student's grade point average in courses other than biology during the term under study and included it as a predictor variable in our regression models. Our final model showed that students in the experimental terms had significantly higher exam scores than students in the control terms. This result shows that online reading quizzes can boost achievement in community college students. We also comment on the importance of discipline-based education research in community college settings and the structure of our community college/4-year institution collaboration.

The use of typed lambda calculus for comprehension and construction of simulation models in the domain of ecology

NASA Technical Reports Server (NTRS)

Uschold, Michael

1992-01-01

We are concerned with two important issues in simulation modelling: model comprehension and model construction. Model comprehension is limited because many important choices taken during the modelling process are not documented. This makes it difficult for models to be modified or used by others. A key factor hindering model construction is the vast modelling search space which must be navigated. This is exacerbated by the fact that many modellers are unfamiliar with the terms and concepts catered to by current tools. The root of both problems is the lack of facilities for representing or reasoning about domain concepts in current simulation technology. The basis for our achievements in both of these areas is the development of a language with two distinct levels; one for representing domain information, and the other for representing the simulation model. Of equal importance, is the fact that we make formal connections between these two levels. The domain we are concerned with is ecological modelling. This language, called Elklogic, is based on the typed lambda calculus. Important features include a rich type structure, the use of various higher order functions, and semantics. This enables complex expressions to be constructed from relatively few primitives. The meaning of each expression can be determined in terms of the domain, the simulation model, or the relationship between the two. We describe a novel representation for sets and substructure, and a variety of other general concepts that are especially useful in the ecological domain. We use the type structure in a novel way: for controlling the modelling search space, rather than a proof search space. We facilitate model comprehension by representing modelling decisions that are embodied in the simulation model. We represent the simulation model separately from, but in terms of a domain mode. The explicit links between the two models constitute the modelling decisions. The semantics of Elklogic enables English text to be generated to explain the simulation model in domain terms.

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.

Review of Sample Size for Structural Equation Models in Second Language Testing and Learning Research: A Monte Carlo Approach

ERIC Educational Resources Information Center

In'nami, Yo; Koizumi, Rie

2013-01-01

The importance of sample size, although widely discussed in the literature on structural equation modeling (SEM), has not been widely recognized among applied SEM researchers. To narrow this gap, we focus on second language testing and learning studies and examine the following: (a) Is the sample size sufficient in terms of precision and power of…

The Application of Contagious Disease Epidemiological Models to Known Population Structure and Movement

DTIC Science & Technology

2016-03-01

subpopulation in which they were located, as shown in the following table. 3 While similar in many...estimates in terms of the following three metrics: 1. total numbers of expected casualties, 2. the overall duration of the modeled outbreak, and 3 . the...11  3 . The Effect of Population Structure and Movement on Casualty Estimates ..............15 A.  Plague Results

The Relation of Story Structure to a Model of Conceptual Change in Science Learning

NASA Astrophysics Data System (ADS)

Klassen, Stephen

2010-03-01

Although various reasons have been proposed to explain the potential effectiveness of science stories to promote learning, no explicit relationship of stories to learning theory in science has been propounded. In this paper, two structurally analogous models are developed and compared: a structural model of stories and a temporal conceptual change model of learning. On the basis of the similarity of the models, as elaborated, it is proposed that the structure of science stories may promote a re-enactment of the learning process, and, thereby, such stories serve to encourage active learning through the generation of hypotheses and explanations. The practical implications of this theoretical analogy can be applied to the classroom in that the utilization of stories provides the opportunity for a type of re-enactment of the learning process that may encourage both engagement with the material and the development of long-term memory structures.

Composition Formulas of Inorganic Compounds in Terms of Cluster Plus Glue Atom Model.

PubMed

Ma, Yanping; Dong, Dandan; Wu, Aimin; Dong, Chuang

2018-01-16

The present paper attempts to identify the molecule-like structural units in inorganic compounds, by applying the so-called "cluster plus glue atom model". This model, originating from metallic glasses and quasi-crystals, describes any structure in terms of a nearest-neighbor cluster and a few outer-shell glue atoms, expressed in the cluster formula [cluster](glue atoms). Similar to the case for normal molecules where the charge transfer occurs within the molecule to meet the commonly known octet electron rule, the octet state is reached after matching the nearest-neighbor cluster with certain outer-shell glue atoms. These kinds of structural units contain information on local atomic configuration, chemical composition, and electron numbers, just as for normal molecules. It is shown that the formulas of typical inorganic compounds, such as fluorides, oxides, and nitrides, satisfy a similar octet electron rule, with the total number of valence electrons per unit formula being multiples of eight.

Simulation modeling to understand how selective foraging by beaver can drive the structure and function of a willow community

USGS Publications Warehouse

Peinetti, H.R.; Baker, B.W.; Coughenour, M.B.

2009-01-01

Beaver-willow (Castor-Salix) communities are a unique and vital component of healthy wetlands throughout the Holarctic region. Beaver selectively forage willow to provide fresh food, stored winter food, and construction material. The effects of this complex foraging behavior on the structure and function of willow communities is poorly understood. Simulation modeling may help ecologists understand these complex interactions. In this study, a modified version of the SAVANNA ecosystem model was developed to better understand how beaver foraging affects the structure and function of a willow community in a simulated riparian ecosystem in Rocky Mountain National Park, Colorado (RMNP). The model represents willow in terms of plant and stem dynamics and beaver foraging in terms of the quantity and quality of stems cut to meet the energetic and life history requirements of beaver. Given a site where all stems were equally available, the model suggested a simulated beaver family of 2 adults, 2 yearlings, and 2 kits required a minimum of 4 ha of willow (containing about10 stems m-2) to persist in a steady-state condition. Beaver created a willow community where the annual net primary productivity (ANPP) was 2 times higher and plant architecture was more diverse than the willow community without beaver. Beaver foraging created a plant architecture dominated by medium size willow plants, which likely explains how beaver can increase ANPP. Long-term simulations suggested that woody biomass stabilized at similar values even though availability differed greatly at initial condition. Simulations also suggested that willow ANPP increased across a range of beaver densities until beaver became food limited. Thus, selective foraging by beaver increased productivity, decreased biomass, and increased structural heterogeneity in a simulated willow community.

Dynamic origins of fermionic D -terms

NASA Astrophysics Data System (ADS)

Hudson, Jonathan; Schweitzer, Peter

2018-03-01

The D -term is defined through matrix elements of the energy-momentum tensor, similarly to mass and spin, yet this important particle property is experimentally not known any fermion. In this work we show that the D -term of a spin 1/2 fermion is of dynamical origin: it vanishes for a free fermion. This is in pronounced contrast to the bosonic case where already a free spin-0 boson has a non-zero intrinsic D -term. We illustrate in two simple models how interactions generate the D -term of a fermion with an internal structure, the nucleon. All known matter is composed of elementary fermions. This indicates the importance to study this interesting particle property in more detail, which will provide novel insights especially on the structure of the nucleon.

Advanced prior modeling for 3D bright field electron tomography

NASA Astrophysics Data System (ADS)

Sreehari, Suhas; Venkatakrishnan, S. V.; Drummy, Lawrence F.; Simmons, Jeffrey P.; Bouman, Charles A.

2015-03-01

Many important imaging problems in material science involve reconstruction of images containing repetitive non-local structures. Model-based iterative reconstruction (MBIR) could in principle exploit such redundancies through the selection of a log prior probability term. However, in practice, determining such a log prior term that accounts for the similarity between distant structures in the image is quite challenging. Much progress has been made in the development of denoising algorithms like non-local means and BM3D, and these are known to successfully capture non-local redundancies in images. But the fact that these denoising operations are not explicitly formulated as cost functions makes it unclear as to how to incorporate them in the MBIR framework. In this paper, we formulate a solution to bright field electron tomography by augmenting the existing bright field MBIR method to incorporate any non-local denoising operator as a prior model. We accomplish this using a framework we call plug-and-play priors that decouples the log likelihood and the log prior probability terms in the MBIR cost function. We specifically use 3D non-local means (NLM) as the prior model in the plug-and-play framework, and showcase high quality tomographic reconstructions of a simulated aluminum spheres dataset, and two real datasets of aluminum spheres and ferritin structures. We observe that streak and smear artifacts are visibly suppressed, and that edges are preserved. Also, we report lower RMSE values compared to the conventional MBIR reconstruction using qGGMRF as the prior model.

Modeling the Biodegradability of Chemical Compounds Using the Online CHEmical Modeling Environment (OCHEM).

PubMed

Vorberg, Susann; Tetko, Igor V

2014-01-01

Biodegradability describes the capacity of substances to be mineralized by free-living bacteria. It is a crucial property in estimating a compound's long-term impact on the environment. The ability to reliably predict biodegradability would reduce the need for laborious experimental testing. However, this endpoint is difficult to model due to unavailability or inconsistency of experimental data. Our approach makes use of the Online Chemical Modeling Environment (OCHEM) and its rich supply of machine learning methods and descriptor sets to build classification models for ready biodegradability. These models were analyzed to determine the relationship between characteristic structural properties and biodegradation activity. The distinguishing feature of the developed models is their ability to estimate the accuracy of prediction for each individual compound. The models developed using seven individual descriptor sets were combined in a consensus model, which provided the highest accuracy. The identified overrepresented structural fragments can be used by chemists to improve the biodegradability of new chemical compounds. The consensus model, the datasets used, and the calculated structural fragments are publicly available at http://ochem.eu/article/31660. © 2014 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

ProQ3: Improved model quality assessments using Rosetta energy terms

PubMed Central

Uziela, Karolis; Shu, Nanjiang; Wallner, Björn; Elofsson, Arne

2016-01-01

Quality assessment of protein models using no other information than the structure of the model itself has been shown to be useful for structure prediction. Here, we introduce two novel methods, ProQRosFA and ProQRosCen, inspired by the state-of-art method ProQ2, but using a completely different description of a protein model. ProQ2 uses contacts and other features calculated from a model, while the new predictors are based on Rosetta energies: ProQRosFA uses the full-atom energy function that takes into account all atoms, while ProQRosCen uses the coarse-grained centroid energy function. The two new predictors also include residue conservation and terms corresponding to the agreement of a model with predicted secondary structure and surface area, as in ProQ2. We show that the performance of these predictors is on par with ProQ2 and significantly better than all other model quality assessment programs. Furthermore, we show that combining the input features from all three predictors, the resulting predictor ProQ3 performs better than any of the individual methods. ProQ3, ProQRosFA and ProQRosCen are freely available both as a webserver and stand-alone programs at http://proq3.bioinfo.se/. PMID:27698390

Long-term athletic development- part 1: a pathway for all youth.

PubMed

Lloyd, Rhodri S; Oliver, Jon L; Faigenbaum, Avery D; Howard, Rick; De Ste Croix, Mark B A; Williams, Craig A; Best, Thomas M; Alvar, Brent A; Micheli, Lyle J; Thomas, D Phillip; Hatfield, Disa L; Cronin, John B; Myer, Gregory D

2015-05-01

The concept of developing talent and athleticism in youth is the goal of many coaches and sports systems. Consequently, an increasing number of sporting organizations have adopted long-term athletic development models in an attempt to provide a structured approach to the training of youth. It is clear that maximizing sporting talent is an important goal of long-term athletic development models. However, ensuring that youth of all ages and abilities are provided with a strategic plan for the development of their health and physical fitness is also important to maximize physical activity participation rates, reduce the risk of sport- and activity-related injury, and to ensure long-term health and well-being. Critical reviews of independent models of long-term athletic development are already present within the literature; however, to the best of our knowledge, a comprehensive examination and review of the most prominent models does not exist. Additionally, considerations of modern day issues that may impact on the success of any long-term athletic development model are lacking, as are proposed solutions to address such issues. Therefore, within this 2-part commentary, Part 1 provides a critical review of existing models of practice for long-term athletic development and introduces a composite youth development model that includes the integration of talent, psychosocial and physical development across maturation. Part 2 identifies limiting factors that may restrict the success of such models and offers potential solutions.

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.

Control Design Strategies to Enhance Long-Term Aircraft Structural Integrity

NASA Technical Reports Server (NTRS)

Newman, Brett A.

1999-01-01

Over the operational lifetime of both military and civil aircraft, structural components are exposed to hundreds of thousands of low-stress repetitive load cycles and less frequent but higher-stress transient loads originating from maneuvering flight and atmospheric gusts. Micro-material imperfections in the structure, such as cracks and debonded laminates, expand and grow in this environment, reducing the structural integrity and shortening the life of the airframe. Extreme costs associated with refurbishment of critical load-bearing structural components in a large fleet, or altogether reinventoring the fleet with newer models, indicate alternative solutions for life extension of the airframe structure are highly desirable. Increased levels of operational safety and reliability are also important factors influencing the desirability of such solutions. One area having significant potential for impacting crack growth/fatigue damage reduction and structural life extension is flight control. To modify the airframe response dynamics arising from command inputs and gust disturbances, feedback loops are routinely applied to vehicles. A dexterous flight control system architecture senses key vehicle motions and generates critical forces/moments at multiple points distributed throughout the airframe to elicit the desired motion characteristics. In principle, these same control loops can be utilized to influence the level of exposure to harmful loads during flight on structural components. Project objectives are to investigate and/or assess the leverage control has on reducing fatigue damage and enhancing long-term structural integrity, without degrading attitude control and trajectory guidance performance levels. In particular, efforts have focused on the effects inner loop control parameters and architectures have on fatigue damage rate. To complete this research, an actively controlled flexible aircraft model and a new state space modeling procedure for crack growth have been utilized. Analysis of the analytical state space model for crack growth revealed the critical mathematical factors, and hence the physical mechanism they represent, that influenced high rates of airframe crack growth. The crack model was then exercised with simple load inputs to uncover and expose key crack growth behavior. To characterize crack growth behavior, both "short-term" laboratory specimen test type inputs and "long-term" operational flight type inputs were considered. Harmonic loading with a single overload revealed typical exponential crack growth behavior until the overload application, after which time the crack growth was retarded for a period of time depending on the overload strength. An optimum overload strength was identified which leads to maximum retardation of crack growth. Harmonic loading with a repeated overload of varying strength and frequency again revealed an optimum overload trait for maximizing growth retardation. The optimum overload strength ratio lies near the range of 2 to 3 with dependency on frequency. Experimental data was found to correlate well with the analytical predictions.

The Open Access Association? EAHIL's new model for sustainability.

PubMed

McSean, Tony; Jakobsson, Arne

2009-12-01

To discover a governance structure and a business model for the European Association for Health Information and Libraries (EAHIL) which will be economically sustainable in the medium term, arresting a long-term gradual decline in membership numbers and implementing new revenue streams to sustain association activity. Reviewed survival strategies of other professional associations, investigated potential of emerging interactive web technologies, investigated alternative revenue streams based around the 'franchise' of the annual EAHIL conferences and workshops. A fully worked-through and costed alternative structure was produced, based on abolition of the subscription, web-based procedures and functions, increased income from advertising and sponsorship and a large measure of member participation and engagement. Statutes and Rules of Procedure were rewritten to reflect the changes. This plan was put through the Association's approval cycle and implemented in 2005. The new financial model has proved itself sustainable on the basis of the first 2 years' operations. The long-term gradual decline in membership was reversed, with membership numbers trebling across the EAHIL region. The software worked with minimal problems, including the online electoral process. With no identified precedent from other professional associations, the changes represented a considerable risk, which was justifiable because long-term projections made it clear that continuing the traditional model was not viable. The result is a larger, healthier association with a stronger link to its membership. Long-term risks include the high level of member commitment and expertise. There are also important questions about scalability-diseconomies of scale probably limit the applicability of the overall open access model to larger associations.

Spiral Galaxy Lensing: A Model with Twist

NASA Astrophysics Data System (ADS)

Bell, Steven R.; Ernst, Brett; Fancher, Sean; Keeton, Charles R.; Komanduru, Abi; Lundberg, Erik

2014-12-01

We propose a single galaxy gravitational lensing model with a mass density that has a spiral structure. Namely, we extend the arcsine gravitational lens (a truncated singular isothermal elliptical model), adding an additional parameter that controls the amount of spiraling in the structure of the mass density. An important feature of our model is that, even though the mass density is sophisticated, we succeed in integrating the deflection term in closed form using a Gauss hypergeometric function. When the spiraling parameter is set to zero, this reduces to the arcsine lens.

Structure of the conversion laws in quantum integrable spin chains with short range interactions

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

Grabowski, M.P.; Mathieu, P.

1995-11-01

The authors present a detailed analysis of the structure of the conservation laws in quantum integrable chains of the XYZ-type and in the Hubbard model. The essential tool for the former class of models is the boost operator, which provides a recursive way of calculating the integrals of motion. With its help, they establish the general form of the XYZ conserved charges in terms of simple polynomials in spin variables and derive recursion relations for the relative coefficients of these polynomials. Although these relations are difficult to solve in general, a subset of the coefficients can be determined. Moreover, formore » two submodels of the XYZ chain, namely the XXX and XY cases, all the charges can be calculated in closed form. Using this approach, the authors rederive the known expressions for the XY charges in a novel way. For the XXX case. a simple description of conserved charges is found in terms of a Catalan tree. This construction is generalized for the su(M) invariant integrable chain. They also investigate the circumstances permitting the existence of a recursive (ladder) operator in general quantum integrable systems. They indicate that a quantum ladder operator can be traced back to the presence of a Hamiltonian mastersymmetry of degree one in the classical continuous version of the model. In this way, quantum chains endowed with a recursive structure can be identified from the properties of their classical relatives. The authors also show that in the quantum continuous limits of the XYZ model, the ladder property of the boost operator disappears. For the Hubbard model they demonstrate the nonexistence of a ladder operator. Nevertheless, the general structure of the conserved charges is indicated, and the expression for the terms linear in the model`s free parameter for all charges is derived in closed form. 62 refs., 4 figs.« less

Model tool to describe chemical structures in XML format utilizing structural fragments and chemical ontology.

PubMed

Sankar, Punnaivanam; Alain, Krief; Aghila, Gnanasekaran

2010-05-24

We have developed a model structure-editing tool, ChemEd, programmed in JAVA, which allows drawing chemical structures on a graphical user interface (GUI) by selecting appropriate structural fragments defined in a fragment library. The terms representing the structural fragments are organized in fragment ontology to provide a conceptual support. ChemEd describes the chemical structure in an XML document (ChemFul) with rich semantics explicitly encoding the details of the chemical bonding, the hybridization status, and the electron environment around each atom. The document can be further processed through suitable algorithms and with the support of external chemical ontologies to generate understandable reports about the functional groups present in the structure and their specific environment.

Transform methods for precision continuum and control models of flexible space structures

NASA Technical Reports Server (NTRS)

Lupi, Victor D.; Turner, James D.; Chun, Hon M.

1991-01-01

An open loop optimal control algorithm is developed for general flexible structures, based on Laplace transform methods. A distributed parameter model of the structure is first presented, followed by a derivation of the optimal control algorithm. The control inputs are expressed in terms of their Fourier series expansions, so that a numerical solution can be easily obtained. The algorithm deals directly with the transcendental transfer functions from control inputs to outputs of interest, and structural deformation penalties, as well as penalties on control effort, are included in the formulation. The algorithm is applied to several structures of increasing complexity to show its generality.

Short-term Forecasting Tools for Agricultural Nutrient Management.

PubMed

Easton, Zachary M; Kleinman, Peter J A; Buda, Anthony R; Goering, Dustin; Emberston, Nichole; Reed, Seann; Drohan, Patrick J; Walter, M Todd; Guinan, Pat; Lory, John A; Sommerlot, Andrew R; Sharpley, Andrew

2017-11-01

The advent of real-time, short-term farm management tools is motivated by the need to protect water quality above and beyond the general guidance offered by existing nutrient management plans. Advances in high-performance computing and hydrologic or climate modeling have enabled rapid dissemination of real-time information that can assist landowners and conservation personnel with short-term management planning. This paper reviews short-term decision support tools for agriculture that are under various stages of development and implementation in the United States: (i) Wisconsin's Runoff Risk Advisory Forecast (RRAF) System, (ii) New York's Hydrologically Sensitive Area Prediction Tool, (iii) Virginia's Saturated Area Forecast Model, (iv) Pennsylvania's Fertilizer Forecaster, (v) Washington's Application Risk Management (ARM) System, and (vi) Missouri's Design Storm Notification System. Although these decision support tools differ in their underlying model structure, the resolution at which they are applied, and the hydroclimates to which they are relevant, all provide forecasts (range 24-120 h) of runoff risk or soil moisture saturation derived from National Weather Service Forecast models. Although this review highlights the need for further development of robust and well-supported short-term nutrient management tools, their potential for adoption and ultimate utility requires an understanding of the appropriate context of application, the strategic and operational needs of managers, access to weather forecasts, scales of application (e.g., regional vs. field level), data requirements, and outreach communication structure. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Effect of urbanization on the thermal structure in the atmosphere

Treesearch

R. Viskanta; R. O. Johnson; R. W., Jr. Bergstrom

1977-01-01

An unsteady two-dimensional transport model was used to study the short-term effects of urbanization and air pollution on the thermal structure in the urban atmosphere. A number of simulations for summer conditions representing the city of St. Louis were performed. The diurnal variation of the surface temperature and thermal structure are presented and the influences...

Host Resistance, Population Structure and the Long-Term Persistence of Bubonic Plague: Contributions of a Modelling Approach in the Malagasy Focus

PubMed Central

Gascuel, Fanny; Choisy, Marc; Duplantier, Jean-Marc; Débarre, Florence; Brouat, Carine

2013-01-01

Although bubonic plague is an endemic zoonosis in many countries around the world, the factors responsible for the persistence of this highly virulent disease remain poorly known. Classically, the endemic persistence of plague is suspected to be due to the coexistence of plague resistant and plague susceptible rodents in natural foci, and/or to a metapopulation structure of reservoirs. Here, we test separately the effect of each of these factors on the long-term persistence of plague. We analyse the dynamics and equilibria of a model of plague propagation, consistent with plague ecology in Madagascar, a major focus where this disease is endemic since the 1920s in central highlands. By combining deterministic and stochastic analyses of this model, and including sensitivity analyses, we show that (i) endemicity is favoured by intermediate host population sizes, (ii) in large host populations, the presence of resistant rats is sufficient to explain long-term persistence of plague, and (iii) the metapopulation structure of susceptible host populations alone can also account for plague endemicity, thanks to both subdivision and the subsequent reduction in the size of subpopulations, and extinction-recolonization dynamics of the disease. In the light of these results, we suggest scenarios to explain the localized presence of plague in Madagascar. PMID:23675291

Host resistance, population structure and the long-term persistence of bubonic plague: contributions of a modelling approach in the Malagasy focus.

PubMed

Gascuel, Fanny; Choisy, Marc; Duplantier, Jean-Marc; Débarre, Florence; Brouat, Carine

2013-01-01

Although bubonic plague is an endemic zoonosis in many countries around the world, the factors responsible for the persistence of this highly virulent disease remain poorly known. Classically, the endemic persistence of plague is suspected to be due to the coexistence of plague resistant and plague susceptible rodents in natural foci, and/or to a metapopulation structure of reservoirs. Here, we test separately the effect of each of these factors on the long-term persistence of plague. We analyse the dynamics and equilibria of a model of plague propagation, consistent with plague ecology in Madagascar, a major focus where this disease is endemic since the 1920s in central highlands. By combining deterministic and stochastic analyses of this model, and including sensitivity analyses, we show that (i) endemicity is favoured by intermediate host population sizes, (ii) in large host populations, the presence of resistant rats is sufficient to explain long-term persistence of plague, and (iii) the metapopulation structure of susceptible host populations alone can also account for plague endemicity, thanks to both subdivision and the subsequent reduction in the size of subpopulations, and extinction-recolonization dynamics of the disease. In the light of these results, we suggest scenarios to explain the localized presence of plague in Madagascar.

Patient-specific geometrical modeling of orthopedic structures with high efficiency and accuracy for finite element modeling and 3D printing.

PubMed

Huang, Huajun; Xiang, Chunling; Zeng, Canjun; Ouyang, Hanbin; Wong, Kelvin Kian Loong; Huang, Wenhua

2015-12-01

We improved the geometrical modeling procedure for fast and accurate reconstruction of orthopedic structures. This procedure consists of medical image segmentation, three-dimensional geometrical reconstruction, and assignment of material properties. The patient-specific orthopedic structures reconstructed by this improved procedure can be used in the virtual surgical planning, 3D printing of real orthopedic structures and finite element analysis. A conventional modeling consists of: image segmentation, geometrical reconstruction, mesh generation, and assignment of material properties. The present study modified the conventional method to enhance software operating procedures. Patient's CT images of different bones were acquired and subsequently reconstructed to give models. The reconstruction procedures were three-dimensional image segmentation, modification of the edge length and quantity of meshes, and the assignment of material properties according to the intensity of gravy value. We compared the performance of our procedures to the conventional procedures modeling in terms of software operating time, success rate and mesh quality. Our proposed framework has the following improvements in the geometrical modeling: (1) processing time: (femur: 87.16 ± 5.90 %; pelvis: 80.16 ± 7.67 %; thoracic vertebra: 17.81 ± 4.36 %; P < 0.05); (2) least volume reduction (femur: 0.26 ± 0.06 %; pelvis: 0.70 ± 0.47, thoracic vertebra: 3.70 ± 1.75 %; P < 0.01) and (3) mesh quality in terms of aspect ratio (femur: 8.00 ± 7.38 %; pelvis: 17.70 ± 9.82 %; thoracic vertebra: 13.93 ± 9.79 %; P < 0.05) and maximum angle (femur: 4.90 ± 5.28 %; pelvis: 17.20 ± 19.29 %; thoracic vertebra: 3.86 ± 3.82 %; P < 0.05). Our proposed patient-specific geometrical modeling requires less operating time and workload, but the orthopedic structures were generated at a higher rate of success as compared with the conventional method. It is expected to benefit the surgical planning of orthopedic structures with less operating time and high accuracy of modeling.

49 CFR 579.4 - Terminology.

Code of Federal Regulations, 2012 CFR

2012-10-01

... uses to designate a discrete model of vehicle, irrespective of the calendar year in which the vehicle..., etc.), and mounting elements (such as brackets, fasteners, etc.). Platform means the basic structure... elements of the engine compartment. The term includes a structure that a manufacturer designates as a...

Data Discretization for Novel Relationship Discovery in Information Retrieval.

ERIC Educational Resources Information Center

Benoit, G.

2002-01-01

Describes an information retrieval, visualization, and manipulation model which offers the user multiple ways to exploit the retrieval set, based on weighted query terms, via an interactive interface. Outlines the mathematical model and describes an information retrieval application built on the model to search structured and full-text files.…

Assessment of corneal properties based on statistical modeling of OCT speckle.

PubMed

Jesus, Danilo A; Iskander, D Robert

2017-01-01

A new approach to assess the properties of the corneal micro-structure in vivo based on the statistical modeling of speckle obtained from Optical Coherence Tomography (OCT) is presented. A number of statistical models were proposed to fit the corneal speckle data obtained from OCT raw image. Short-term changes in corneal properties were studied by inducing corneal swelling whereas age-related changes were observed analyzing data of sixty-five subjects aged between twenty-four and seventy-three years. Generalized Gamma distribution has shown to be the best model, in terms of the Akaike's Information Criterion, to fit the OCT corneal speckle. Its parameters have shown statistically significant differences (Kruskal-Wallis, p < 0.001) for short and age-related corneal changes. In addition, it was observed that age-related changes influence the corneal biomechanical behaviour when corneal swelling is induced. This study shows that Generalized Gamma distribution can be utilized to modeling corneal speckle in OCT in vivo providing complementary quantified information where micro-structure of corneal tissue is of essence.

The problem of dimensional instability in airfoil models for cryogenic wind tunnels

NASA Technical Reports Server (NTRS)

Wigley, D. A.

1982-01-01

The problem of dimensional instability in airfoil models for cryogenic wind tunnels is discussed in terms of the various mechanisms that can be responsible. The interrelationship between metallurgical structure and possible dimensional instability in cryogenic usage is discussed for those steel alloys of most interest for wind tunnel model construction at this time. Other basic mechanisms responsible for setting up residual stress systems are discussed, together with ways in which their magnitude may be reduced by various elevated or low temperature thermal cycles. A standard specimen configuration is proposed for use in experimental investigations into the effects of machining, heat treatment, and other variables that influence the dimensional stability of the materials of interest. A brief classification of various materials in terms of their metallurgical structure and susceptability to dimensional instability is presented.

Exploring Contextual Models in Chemical Patent Search

NASA Astrophysics Data System (ADS)

Urbain, Jay; Frieder, Ophir

We explore the development of probabilistic retrieval models for integrating term statistics with entity search using multiple levels of document context to improve the performance of chemical patent search. A distributed indexing model was developed to enable efficient named entity search and aggregation of term statistics at multiple levels of patent structure including individual words, sentences, claims, descriptions, abstracts, and titles. The system can be scaled to an arbitrary number of compute instances in a cloud computing environment to support concurrent indexing and query processing operations on large patent collections.

Early Environmental Enrichment Enhances Abnormal Brain Connectivity in a Rabbit Model of Intrauterine Growth Restriction.

PubMed

Illa, Miriam; Brito, Verónica; Pla, Laura; Eixarch, Elisenda; Arbat-Plana, Ariadna; Batallé, Dafnis; Muñoz-Moreno, Emma; Crispi, Fatima; Udina, Esther; Figueras, Francesc; Ginés, Silvia; Gratacós, Eduard

2017-10-12

The structural correspondence of neurodevelopmental impairments related to intrauterine growth restriction (IUGR) that persists later in life remains elusive. Moreover, early postnatal stimulation strategies have been proposed to mitigate these effects. Long-term brain connectivity abnormalities in an IUGR rabbit model and the effects of early postnatal environmental enrichment (EE) were explored. IUGR was surgically induced in one horn, whereas the contralateral one produced the controls. Postnatally, a subgroup of IUGR animals was housed in an enriched environment. Functional assessment was performed at the neonatal and long-term periods. At the long-term period, structural brain connectivity was evaluated by means of diffusion-weighted brain magnetic resonance imaging and by histological assessment focused on the hippocampus. IUGR animals displayed poorer functional results and presented altered whole-brain networks and decreased median fractional anisotropy in the hippocampus. Reduced density of dendritic spines and perineuronal nets from hippocampal neurons were also observed. Of note, IUGR animals exposed to enriched environment presented an improvement in terms of both function and structure. IUGR is associated with altered brain connectivity at the global and cellular level. A strategy based on early EE has the potential to restore the neurodevelopmental consequences of IUGR. © 2017 S. Karger AG, Basel.

Inner Structure of CME Shock Fronts Revealed by the Electromotive Force and Turbulent Transport Coefficients in Helios-2 Observations

NASA Astrophysics Data System (ADS)

Bourdin, Philippe-A.; Hofer, Bernhard; Narita, Yasuhito

2018-03-01

Electromotive force is an essential quantity in dynamo theory. During a coronal mass ejection (CME), magnetic helicity gets decoupled from the Sun and advected into the heliosphere with the solar wind. Eventually, a heliospheric magnetic transient event might pass by a spacecraft, such as the Helios space observatories. Our aim is to investigate the electromotive force, the kinetic helicity effect (α term), the turbulent diffusion (β term), and the cross-helicity effect (γ term) in the inner heliosphere below 1 au. We set up a one-dimensional model of the solar wind velocity and magnetic field for a hypothetic interplanetary CME. Because turbulent structures within the solar wind evolve much slower than this structure needs to pass by the spacecraft, we use a reduced curl operator to compute the current density and vorticity. We test our CME shock-front model against an observed magnetic transient that passes by the Helios-2 spacecraft. At the peak of the fluctuations in this event we find strongly enhanced α, β, and γ terms, as well as a strong peak in the total electromotive force. Our method allows us to automatically identify magnetic transient events from any in situ spacecraft observations that contain magnetic field and plasma velocity data of the solar wind.

Influence of local demography on asymptotic and transient dynamics of a yellow-bellied marmot metapopulation.

PubMed

Ozgul, Arpat; Oli, Madan K; Armitage, Kenneth B; Blumstein, Daniel T; Van Vuren, Dirk H

2009-04-01

Despite recent advances in biodemography and metapopulation ecology, we still have limited understanding of how local demographic parameters influence short- and long-term metapopulation dynamics. We used long-term data from 17 local populations, along with the recently developed methods of matrix metapopulation modeling and transient sensitivity analysis, to investigate the influence of local demography on long-term (asymptotic) versus short-term (transient) dynamics of a yellow-bellied marmot metapopulation in Colorado. Both long- and short-term dynamics depended primarily on a few colony sites and were highly sensitive to changes in demography at these sites, particularly in survival of reproductive adult females. Interestingly, the relative importance of sites differed between long- and short-term dynamics; the spatial structure and local population sizes, while insignificant for asymptotic dynamics, were influential on transient dynamics. However, considering the spatial structure was uninformative about the relative influence of local demography on metapopulation dynamics. The vital rates that were the most influential on local dynamics were also the most influential on both long- and short-term metapopulation dynamics. Our results show that an explicit consideration of local demography is essential for a complete understanding of the dynamics and persistence of spatially structured populations.

Linear-quadratic-Gaussian synthesis with reduced parameter sensitivity

NASA Technical Reports Server (NTRS)

Lin, J. Y.; Mingori, D. L.

1992-01-01

We present a method for improving the tolerance of a conventional LQG controller to parameter errors in the plant model. The improvement is achieved by introducing additional terms reflecting the structure of the parameter errors into the LQR cost function, and also the process and measurement noise models. Adjusting the sizes of these additional terms permits a trade-off between robustness and nominal performance. Manipulation of some of the additional terms leads to high gain controllers while other terms lead to low gain controllers. Conditions are developed under which the high-gain approach asymptotically recovers the robustness of the corresponding full-state feedback design, and the low-gain approach makes the closed-loop poles asymptotically insensitive to parameter errors.

Special Relativity at the Quantum Scale

PubMed Central

Lam, Pui K.

2014-01-01

It has been suggested that the space-time structure as described by the theory of special relativity is a macroscopic manifestation of a more fundamental quantum structure (pre-geometry). Efforts to quantify this idea have come mainly from the area of abstract quantum logic theory. Here we present a preliminary attempt to develop a quantum formulation of special relativity based on a model that retains some geometric attributes. Our model is Feynman's “checker-board” trajectory for a 1-D relativistic free particle. We use this model to guide us in identifying (1) the quantum version of the postulates of special relativity and (2) the appropriate quantum “coordinates”. This model possesses a useful feature that it admits an interpretation both in terms of paths in space-time and in terms of quantum states. Based on the quantum version of the postulates, we derive a transformation rule for velocity. This rule reduces to the Einstein's velocity-addition formula in the macroscopic limit and reveals an interesting aspect of time. The 3-D case, time-dilation effect, and invariant interval are also discussed in term of this new formulation. This is a preliminary investigation; some results are derived, while others are interesting observations at this point. PMID:25531675

Special relativity at the quantum scale.

PubMed

Lam, Pui K

2014-01-01

It has been suggested that the space-time structure as described by the theory of special relativity is a macroscopic manifestation of a more fundamental quantum structure (pre-geometry). Efforts to quantify this idea have come mainly from the area of abstract quantum logic theory. Here we present a preliminary attempt to develop a quantum formulation of special relativity based on a model that retains some geometric attributes. Our model is Feynman's "checker-board" trajectory for a 1-D relativistic free particle. We use this model to guide us in identifying (1) the quantum version of the postulates of special relativity and (2) the appropriate quantum "coordinates". This model possesses a useful feature that it admits an interpretation both in terms of paths in space-time and in terms of quantum states. Based on the quantum version of the postulates, we derive a transformation rule for velocity. This rule reduces to the Einstein's velocity-addition formula in the macroscopic limit and reveals an interesting aspect of time. The 3-D case, time-dilation effect, and invariant interval are also discussed in term of this new formulation. This is a preliminary investigation; some results are derived, while others are interesting observations at this point.

Generalized Structured Component Analysis with Uniqueness Terms for Accommodating Measurement Error

PubMed Central

Hwang, Heungsun; Takane, Yoshio; Jung, Kwanghee

2017-01-01

Generalized structured component analysis (GSCA) is a component-based approach to structural equation modeling (SEM), where latent variables are approximated by weighted composites of indicators. It has no formal mechanism to incorporate errors in indicators, which in turn renders components prone to the errors as well. We propose to extend GSCA to account for errors in indicators explicitly. This extension, called GSCAM, considers both common and unique parts of indicators, as postulated in common factor analysis, and estimates a weighted composite of indicators with their unique parts removed. Adding such unique parts or uniqueness terms serves to account for measurement errors in indicators in a manner similar to common factor analysis. Simulation studies are conducted to compare parameter recovery of GSCAM and existing methods. These methods are also applied to fit a substantively well-established model to real data. PMID:29270146

MicroRNAfold: pre-microRNA secondary structure prediction based on modified NCM model with thermodynamics-based scoring strategy.

PubMed

Han, Dianwei; Zhang, Jun; Tang, Guiliang

2012-01-01

An accurate prediction of the pre-microRNA secondary structure is important in miRNA informatics. Based on a recently proposed model, nucleotide cyclic motifs (NCM), to predict RNA secondary structure, we propose and implement a Modified NCM (MNCM) model with a physics-based scoring strategy to tackle the problem of pre-microRNA folding. Our microRNAfold is implemented using a global optimal algorithm based on the bottom-up local optimal solutions. Our experimental results show that microRNAfold outperforms the current leading prediction tools in terms of True Negative rate, False Negative rate, Specificity, and Matthews coefficient ratio.

Uniaxial creep property and viscoelastic-plastic modelling of ethylene tetrafluoroethylene (ETFE) foil

NASA Astrophysics Data System (ADS)

Li, Yintang; Wu, Minger

2015-02-01

Ethylene tetrafluoroethylene (ETFE) foil has been widely used in spatial structures for its light weight and high transparency. This paper studies short- and long-term creep properties of ETFE foil. Two series of short-term creep and recovery tests were performed, in which residual strain was observed. A long-term creep test of ETFE foil was also conducted and lasted about 400 days. A viscoelastic-plastic model was then established to describe short-term creep and recovery behaviour of ETFE foil. This model contains a traditional generalised Kelvin part and an added steady-flow component to represent viscoelastic and viscoplastic behaviour, respectively. The model can fit tests' data well at three stresses and six temperatures. Additionally, time-temperature superposition was adopted to simulate long-term creep behaviour of ETFE foil. Horizontal shifting factors were determined by W.L.F. equation in which transition temperature was simulated by shifting factors. Using this equation, long-term creep behaviours at three temperatures were predicted. The results of the long-term creep test showed that a short-term creep test at identical temperatures was insufficient to predict additional creep behaviour, and the long-term creep test verified horizontal shifting factors which were derived from the time-temperature superposition.

Family Structure and Children's Psychosocial Outcomes

ERIC Educational Resources Information Center

Wu, Zheng; Hou, Feng; Schimmele, Christoph M.

2008-01-01

This article examines the influence of family structure on children's short-term psychosocial behavioral outcomes, including emotional disorder, conduct disorder, and prosocial behavior. The analysis uses five waves of data (1994-2003) from Canada's National Longitudinal Survey of Children and Youth to model how living in a cohabitational…

Factor Structure and Psychometric Properties of the Posttraumatic Stress Disorder (PTSD) Checklist and DSM-5 PTSD Symptom Set in a Long-Term Postearthquake Cohort in Armenia.

PubMed

Demirchyan, Anahit; Goenjian, Armen K; Khachadourian, Vahe

2015-10-01

Psychometric properties of the Armenian-language posttraumatic stress disorder (PTSD) Checklist-Civilian version (PCL-C) and the DSM-5 PTSD symptom set were examined in a long-term cohort of earthquake survivors. In 2012, 725 survivors completed the instruments. Item-/scale-level analysis and confirmatory factor analysis (CFA) were performed for both scales. In addition, exploratory factor analysis (EFA) was conducted for DSM-5 symptoms. Also, the differential internal versus external specificity of PTSD symptom clusters taken from the most supported PTSD structural models was examined. Both scales had Cronbach's alpha greater than .9. CFA of PCL-C structure demonstrated an excellent fit by a four-factor (reexperiencing, avoidance, numbing, and hyperarousal) model known as numbing model; however, a superior fit was achieved by a five-factor model (Elhai et al.). EFA yielded a five-factor structure for DSM-5 symptoms with the aforementioned four domains plus a negative state domain. This model achieved an acceptable fit during CFA, whereas the DSM-5 criteria-based model did not. The Armenian-language PCL-C was recommended as a valid PTSD screening tool. The study findings provided support to the proposed new classification of common mental disorders, where PTSD, depression, and generalized anxiety are grouped together as a subclass of distress disorders. Recommendations were made to further improve the PTSD diagnostic criteria. © The Author(s) 2014.

Fatigue analysis of the bow structure of FPSO

NASA Astrophysics Data System (ADS)

Hu, Zhi-Qiang; Gao, Zhen; Gu, Yong-Ning

2003-06-01

The bow structure of FPSO moored by the single mooring system is rather complicated. There are many potential hot spots in connection parts of structures between the mooring support frame and the forecastle. Mooring forces, which are induced by wave excitation and transferred by the YOKE and the mooring support frame, may cause fatigue damage to the bow structure. Different from direct wave-induced-forces, the mooring force consists of wave frequency force (WF) and 2nd draft low frequency force (LF)[3], which are represented by two sets of short-term distribution respectively. Based on two sets of short-term distribution of mooring forces obtained by the model test, the fatigue damage of the bow structure of FPSO is analyzed, with emphasis on two points. One is the procedure and position selection for fatigue check, and the other is the application of new formulae for the calculation of accumulative fatigue damage caused by two sets of short-term distribution of hot spot stress range. From the results distinguished features of fatigue damage to the FPSO’s bow structure can be observed.

Mesoscopic structure conditions the emergence of cooperation on social networks

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

Lozano, S.; Arenas, A.; Sanchez, A.

We study the evolutionary Prisoner's Dilemma on two social networks substrates obtained from actual relational data. We find very different cooperation levels on each of them that cannot be easily understood in terms of global statistical properties of both networks. We claim that the result can be understood at the mesoscopic scale, by studying the community structure of the networks. We explain the dependence of the cooperation level on the temptation parameter in terms of the internal structure of the communities and their interconnections. We then test our results on community-structured, specifically designed artificial networks, finding a good agreement withmore » the observations in both real substrates. Our results support the conclusion that studies of evolutionary games on model networks and their interpretation in terms of global properties may not be sufficient to study specific, real social systems. Further, the study allows us to define new quantitative parameters that summarize the mesoscopic structure of any network. In addition, the community perspective may be helpful to interpret the origin and behavior of existing networks as well as to design structures that show resilient cooperative behavior.« less

The prospect of modern thermomechanics in structural integrity calculations of large-scale pressure vessels

NASA Astrophysics Data System (ADS)

Fekete, Tamás

2018-05-01

Structural integrity calculations play a crucial role in designing large-scale pressure vessels. Used in the electric power generation industry, these kinds of vessels undergo extensive safety analyses and certification procedures before deemed feasible for future long-term operation. The calculations are nowadays directed and supported by international standards and guides based on state-of-the-art results of applied research and technical development. However, their ability to predict a vessel's behavior under accidental circumstances after long-term operation is largely limited by the strong dependence of the analysis methodology on empirical models that are correlated to the behavior of structural materials and their changes during material aging. Recently a new scientific engineering paradigm, structural integrity has been developing that is essentially a synergistic collaboration between a number of scientific and engineering disciplines, modeling, experiments and numerics. Although the application of the structural integrity paradigm highly contributed to improving the accuracy of safety evaluations of large-scale pressure vessels, the predictive power of the analysis methodology has not yet improved significantly. This is due to the fact that already existing structural integrity calculation methodologies are based on the widespread and commonly accepted 'traditional' engineering thermal stress approach, which is essentially based on the weakly coupled model of thermomechanics and fracture mechanics. Recently, a research has been initiated in MTA EK with the aim to review and evaluate current methodologies and models applied in structural integrity calculations, including their scope of validity. The research intends to come to a better understanding of the physical problems that are inherently present in the pool of structural integrity problems of reactor pressure vessels, and to ultimately find a theoretical framework that could serve as a well-grounded theoretical foundation for a new modeling framework of structural integrity. This paper presents the first findings of the research project.

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...

Predicting structured metadata from unstructured metadata.

PubMed

Posch, Lisa; Panahiazar, Maryam; Dumontier, Michel; Gevaert, Olivier

2016-01-01

Enormous amounts of biomedical data have been and are being produced by investigators all over the world. However, one crucial and limiting factor in data reuse is accurate, structured and complete description of the data or data about the data-defined as metadata. We propose a framework to predict structured metadata terms from unstructured metadata for improving quality and quantity of metadata, using the Gene Expression Omnibus (GEO) microarray database. Our framework consists of classifiers trained using term frequency-inverse document frequency (TF-IDF) features and a second approach based on topics modeled using a Latent Dirichlet Allocation model (LDA) to reduce the dimensionality of the unstructured data. Our results on the GEO database show that structured metadata terms can be the most accurately predicted using the TF-IDF approach followed by LDA both outperforming the majority vote baseline. While some accuracy is lost by the dimensionality reduction of LDA, the difference is small for elements with few possible values, and there is a large improvement over the majority classifier baseline. Overall this is a promising approach for metadata prediction that is likely to be applicable to other datasets and has implications for researchers interested in biomedical metadata curation and metadata prediction. © The Author(s) 2016. Published by Oxford University Press.

Predicting structured metadata from unstructured metadata

PubMed Central

Posch, Lisa; Panahiazar, Maryam; Dumontier, Michel; Gevaert, Olivier

2016-01-01

Enormous amounts of biomedical data have been and are being produced by investigators all over the world. However, one crucial and limiting factor in data reuse is accurate, structured and complete description of the data or data about the data—defined as metadata. We propose a framework to predict structured metadata terms from unstructured metadata for improving quality and quantity of metadata, using the Gene Expression Omnibus (GEO) microarray database. Our framework consists of classifiers trained using term frequency-inverse document frequency (TF-IDF) features and a second approach based on topics modeled using a Latent Dirichlet Allocation model (LDA) to reduce the dimensionality of the unstructured data. Our results on the GEO database show that structured metadata terms can be the most accurately predicted using the TF-IDF approach followed by LDA both outperforming the majority vote baseline. While some accuracy is lost by the dimensionality reduction of LDA, the difference is small for elements with few possible values, and there is a large improvement over the majority classifier baseline. Overall this is a promising approach for metadata prediction that is likely to be applicable to other datasets and has implications for researchers interested in biomedical metadata curation and metadata prediction. Database URL: http://www.yeastgenome.org/ PMID:28637268

QSAR, QSPR and QSRR in Terms of 3-D-MoRSE Descriptors for In Silico Screening of Clofibric Acid Analogues.

PubMed

Di Tullio, Maurizio; Maccallini, Cristina; Ammazzalorso, Alessandra; Giampietro, Letizia; Amoroso, Rosa; De Filippis, Barbara; Fantacuzzi, Marialuigia; Wiczling, Paweł; Kaliszan, Roman

2012-07-01

A series of 27 analogues of clofibric acid, mostly heteroarylalkanoic derivatives, have been analyzed by a novel high-throughput reversed-phase HPLC method employing combined gradient of eluent's pH and organic modifier content. The such determined hydrophobicity (lipophilicity) parameters, log kw , and acidity constants, pKa , were subjected to multiple regression analysis to get a QSRR (Quantitative StructureRetention Relationships) and a QSPR (Quantitative Structure-Property Relationships) equation, respectively, describing these pharmacokinetics-determining physicochemical parameters in terms of the calculation chemistry derived structural descriptors. The previously determined in vitro log EC50 values - transactivation activity towards PPARα (human Peroxisome Proliferator-Activated Receptor α) - have also been described in a QSAR (Quantitative StructureActivity Relationships) equation in terms of the 3-D-MoRSE descriptors (3D-Molecule Representation of Structures based on Electron diffraction descriptors). The QSAR model derived can serve for an a priori prediction of bioactivity in vitro of any designed analogue, whereas the QSRR and the QSPR models can be used to evaluate lipophilicity and acidity, respectively, of the compounds, and hence to rational guide selection of structures of proper pharmacokinetics. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Evaluating Vertical Moisture Structure of the Madden-Julian Oscillation in Contemporary GCMs

NASA Astrophysics Data System (ADS)

Guan, B.; Jiang, X.; Waliser, D. E.

2013-12-01

The Madden-Julian Oscillation (MJO) remains a major challenge in our understanding and modeling of the tropical convection and circulation. Many models have troubles in realistically simulating key characteristics of the MJO, such as the strength, period, and eastward propagation. For models that do simulate aspects of the MJO, it remains to be understood what parameters and processes are the most critical in determining the quality of the simulations. This study focuses on the vertical structure of moisture in MJO simulations, with the aim to identify and understand the relationship between MJO simulation qualities and key parameters related to moisture. A series of 20-year simulations conducted by 26 GCMs are analyzed, including four that are coupled to ocean models and two that have a two-dimensional cloud resolving model embedded (i.e., superparameterized). TRMM precipitation and ERA-Interim reanalysis are used to evaluate the model simulations. MJO simulation qualities are evaluated based on pattern correlations of lead/lag regressions of precipitation - a measure of the model representation of the eastward propagating MJO convection. Models with strongest and weakest MJOs (top and bottom quartiles) are compared in terms of differences in moisture content, moisture convergence, moistening rate, and moist static energy. It is found that models with strongest MJOs have better representations of the observed vertical tilt of moisture. Relative importance of convection, advection, boundary layer, and large scale convection/precipitation are discussed in terms of their contribution to the moistening process. The results highlight the overall importance of vertical moisture structure in MJO simulations. The work contributes to the climatological component of the joint WCRP-WWRP/THORPEX YOTC MJO Task Force and the GEWEX Atmosphere System Study (GASS) global model evaluation project focused on the vertical structure and diabatic processes of the MJO.

Bio-functions and molecular carbohydrate structure association study in forage with different source origins revealed using non-destructive vibrational molecular spectroscopy techniques

NASA Astrophysics Data System (ADS)

Ji, Cuiying; Zhang, Xuewei; Yan, Xiaogang; Mostafizar Rahman, M.; Prates, Luciana L.; Yu, Peiqiang

2017-08-01

The objectives of this study were to: 1) investigate forage carbohydrate molecular structure profiles; 2) bio-functions in terms of CHO rumen degradation characteristics and hourly effective degradation ratio of N to OM (HEDN/OM), and 3) quantify interactive association between molecular structures, bio-functions and nutrient availability. The vibrational molecular spectroscopy was applied to investigate the structure feature on a molecular basis. Two sourced-origin alfalfa forages were used as modeled forages. The results showed that the carbohydrate molecular structure profiles were highly linked to the bio-functions in terms of rumen degradation characteristics and hourly effective degradation ratio. The molecular spectroscopic technique can be used to detect forage carbohydrate structure features on a molecular basis and can be used to study interactive association between forage molecular structure and bio-functions.

Using Decision Structures for Policy Analysis in Software Product-line Evolution - A Case Study

NASA Astrophysics Data System (ADS)

Sarang, Nita; Sanglikar, Mukund A.

Project management decisions are the primary basis for project success (or failure). Mostly, such decisions are based on an intuitive understanding of the underlying software engineering and management process and have a likelihood of being misjudged. Our problem domain is product-line evolution. We model the dynamics of the process by incorporating feedback loops appropriate to two decision structures: staffing policy, and the forces of growth associated with long-term software evolution. The model is executable and supports project managers to assess the long-term effects of possible actions. Our work also corroborates results from earlier studies of E-type systems, in particular the FEAST project and the rules for software evolution, planning and management.

The Role of Human Error in Design, Construction, and Reliability of Marine Structures.

DTIC Science & Technology

1994-10-01

The 1979 Three Mile Island nuclear plant accident was largely a result of a failure to properly sort out and recognize critically important information...determinating the goals and objectives of the program and by evaluating and interpreting the results in terms of structural design, construction, and...67 Checking Models in Structural Design ....................................... 69 Nuclear Power Plants

Relationships between nonlinear normal modes and response to random inputs

NASA Astrophysics Data System (ADS)

Schoneman, Joseph D.; Allen, Matthew S.; Kuether, Robert J.

2017-02-01

The ability to model nonlinear structures subject to random excitation is of key importance in designing hypersonic aircraft and other advanced aerospace vehicles. When a structure is linear, superposition can be used to construct its response to a known spectrum in terms of its linear modes. Superposition does not hold for a nonlinear system, but several works have shown that a system's dynamics can still be understood qualitatively in terms of its nonlinear normal modes (NNMs). This work investigates the connection between a structure's undamped nonlinear normal modes and the spectrum of its response to high amplitude random forcing. Two examples are investigated: a spring-mass system and a clamped-clamped beam modeled within a geometrically nonlinear finite element package. In both cases, an intimate connection is observed between the smeared peaks in the response spectrum and the frequency-energy dependence of the nonlinear normal modes. In order to understand the role of coupling between the underlying linear modes, reduced order models with and without modal coupling terms are used to separate the effect of each NNM's backbone from the nonlinear couplings that give rise to internal resonances. In the cases shown here, uncoupled, single-degree-of-freedom nonlinear models are found to predict major features in the response with reasonable accuracy; a highly inexpensive approximation such as this could be useful in design and optimization studies. More importantly, the results show that a reduced order model can be expected to give accurate results only if it is also capable of accurately predicting the frequency-energy dependence of the nonlinear modes that are excited.

Modeling and Simulation of Offshore Wind Power Platform for 5 MW Baseline NREL Turbine.

PubMed

Roni Sahroni, Taufik

2015-01-01

This paper presents the modeling and simulation of offshore wind power platform for oil and gas companies. Wind energy has become the fastest growing renewable energy in the world and major gains in terms of energy generation are achievable when turbines are moved offshore. The objective of this project is to propose new design of an offshore wind power platform. Offshore wind turbine (OWT) is composed of three main structures comprising the rotor/blades, the tower nacelle, and the supporting structure. The modeling analysis was focused on the nacelle and supporting structure. The completed final design was analyzed using finite element modeling tool ANSYS to obtain the structure's response towards loading conditions and to ensure it complies with guidelines laid out by classification authority Det Norske Veritas. As a result, a new model of the offshore wind power platform for 5 MW Baseline NREL turbine was proposed.

Modeling and Simulation of Offshore Wind Power Platform for 5 MW Baseline NREL Turbine

PubMed Central

Roni Sahroni, Taufik

2015-01-01

This paper presents the modeling and simulation of offshore wind power platform for oil and gas companies. Wind energy has become the fastest growing renewable energy in the world and major gains in terms of energy generation are achievable when turbines are moved offshore. The objective of this project is to propose new design of an offshore wind power platform. Offshore wind turbine (OWT) is composed of three main structures comprising the rotor/blades, the tower nacelle, and the supporting structure. The modeling analysis was focused on the nacelle and supporting structure. The completed final design was analyzed using finite element modeling tool ANSYS to obtain the structure's response towards loading conditions and to ensure it complies with guidelines laid out by classification authority Det Norske Veritas. As a result, a new model of the offshore wind power platform for 5 MW Baseline NREL turbine was proposed. PMID:26550605

POPULATION-LEVEL RESPONSE OF THE MYSID, AMERICAMYSIS BAHIA, TO VARYING THIOBENCARB CONCENTRATIONS BASED ON AGE-STRUCTURED POPULATION MODELS

EPA Science Inventory

To fully understand the potential long-term ecological impacts a pollutant has on a species, population-level effects must be estimated. Since long-term field experiments are typically not feasible, vital rates such as survival, growth, and reproduction of individual organisms ar...

Do Guilt- and Shame-Proneness Differentially Predict Prosocial, Aggressive, and Withdrawn Behaviors during Early Adolescence?

ERIC Educational Resources Information Center

Roos, Sanna; Hodges, Ernest V. E.; Salmivalli, Christina

2014-01-01

In this short-term longitudinal study, we systematically examined the distinctiveness of guilt- and shame-proneness in early adolescents (N = 395, mean age = 11.8 years) in terms of differential relations with peer reported prosocial behavior, withdrawal, and aggression. Results from structural equation modeling indicated that guilt-proneness…

Disease model curation improvements at Mouse Genome Informatics

PubMed Central

Bello, Susan M.; Richardson, Joel E.; Davis, Allan P.; Wiegers, Thomas C.; Mattingly, Carolyn J.; Dolan, Mary E.; Smith, Cynthia L.; Blake, Judith A.; Eppig, Janan T.

2012-01-01

Optimal curation of human diseases requires an ontology or structured vocabulary that contains terms familiar to end users, is robust enough to support multiple levels of annotation granularity, is limited to disease terms and is stable enough to avoid extensive reannotation following updates. At Mouse Genome Informatics (MGI), we currently use disease terms from Online Mendelian Inheritance in Man (OMIM) to curate mouse models of human disease. While OMIM provides highly detailed disease records that are familiar to many in the medical community, it lacks structure to support multilevel annotation. To improve disease annotation at MGI, we evaluated the merged Medical Subject Headings (MeSH) and OMIM disease vocabulary created by the Comparative Toxicogenomics Database (CTD) project. Overlaying MeSH onto OMIM provides hierarchical access to broad disease terms, a feature missing from the OMIM. We created an extended version of the vocabulary to meet the genetic disease-specific curation needs at MGI. Here we describe our evaluation of the CTD application, the extensions made by MGI and discuss the strengths and weaknesses of this approach. Database URL: http://www.informatics.jax.org/ PMID:22434831

Long-term Care Insurance and Carers' Labor Supply - A Structural Model.

PubMed

Geyer, Johannes; Korfhage, Thorben

2015-09-01

In Germany, individuals in need of long-term care receive support through benefits of the long-term care insurance. A central goal of the insurance is to support informal care provided by family members. Care recipients can choose between benefits in kind (formal home care services) and benefits in cash. From a budgetary perspective, family care is often considered a cost-saving alternative to formal home care and to stationary nursing care. However, the opportunity costs resulting from reduced labor supply of the carer are often overlooked. We focus on the labor supply decision of family carers and the incentives set by the long-term care insurance. We estimate a structural model of labor supply and the choice of benefits of family carers. We find that benefits in kind have small positive effects on labor supply. Labor supply elasticities of cash benefits are larger and negative. If both types of benefits increase, negative labor supply effects are offset to a large extent. However, the average effect is significantly negative. Copyright © 2015 John Wiley & Sons, Ltd.

Data identification for improving gene network inference using computational algebra.

PubMed

Dimitrova, Elena; Stigler, Brandilyn

2014-11-01

Identification of models of gene regulatory networks is sensitive to the amount of data used as input. Considering the substantial costs in conducting experiments, it is of value to have an estimate of the amount of data required to infer the network structure. To minimize wasted resources, it is also beneficial to know which data are necessary to identify the network. Knowledge of the data and knowledge of the terms in polynomial models are often required a priori in model identification. In applications, it is unlikely that the structure of a polynomial model will be known, which may force data sets to be unnecessarily large in order to identify a model. Furthermore, none of the known results provides any strategy for constructing data sets to uniquely identify a model. We provide a specialization of an existing criterion for deciding when a set of data points identifies a minimal polynomial model when its monomial terms have been specified. Then, we relax the requirement of the knowledge of the monomials and present results for model identification given only the data. Finally, we present a method for constructing data sets that identify minimal polynomial models.

Observation-Oriented Modeling: Going beyond "Is It All a Matter of Chance"?

ERIC Educational Resources Information Center

Grice, James W.; Yepez, Maria; Wilson, Nicole L.; Shoda, Yuichi

2017-01-01

An alternative to null hypothesis significance testing is presented and discussed. This approach, referred to as observation-oriented modeling, is centered on model building in an effort to explicate the structures and processes believed to generate a set of observations. In terms of analysis, this novel approach complements traditional methods…

First order coupled dynamic model of flexible space structures with time-varying configurations

NASA Astrophysics Data System (ADS)

Wang, Jie; Li, Dongxu; Jiang, Jianping

2017-03-01

This paper proposes a first order coupled dynamic modeling method for flexible space structures with time-varying configurations for the purpose of deriving the characteristics of the system. The model considers the first time derivative of the coordinate transformation matrix between the platform's body frame and the appendage's floating frame. As a result it can accurately predict characteristics of the system even if flexible appendages rotate with complex trajectory relative to the rigid part. In general, flexible appendages are fixed on the rigid platform or forced to rotate with a slow angular velocity. So only the zero order of the transformation matrix is considered in conventional models. However, due to neglecting of time-varying terms of the transformation matrix, these models introduce severe error when appendages, like antennas, for example, rotate with a fast speed relative to the platform. The first order coupled dynamic model for flexible space structures proposed in this paper resolve this problem by introducing the first time derivative of the transformation matrix. As a numerical example, a central core with a rotating solar panel is considered and the results are compared with those given by the conventional model. It has been shown that the first order terms are of great importance on the attitude of the rigid body and dynamic response of the flexible appendage.

Improved Modeling and Prediction of Surface Wave Amplitudes

DTIC Science & Technology

2017-05-31

structures and derived attenuation coefficients from the Eurasian Q inversion study. 15. SUBJECT TERMS nuclear explosion monitoring, surface waves, membrane...24 4.6 Inversion of Eurasian Attenuation Data for Q Structure ........................................ 31 4.6.1 Data used in the Q Inversion ...33 4.6.2 Q Inversion Results

The Importance of Model Structure in the Cost-Effectiveness Analysis of Primary Care Interventions for the Management of Hypertension.

PubMed

Peñaloza-Ramos, Maria Cristina; Jowett, Sue; Sutton, Andrew John; McManus, Richard J; Barton, Pelham

2018-03-01

Management of hypertension can lead to significant reductions in blood pressure, thereby reducing the risk of cardiovascular disease. Modeling the course of cardiovascular disease is not without complications, and uncertainty surrounding the structure of a model will almost always arise once a choice of a model structure is defined. To provide a practical illustration of the impact on the results of cost-effectiveness of changing or adapting model structures in a previously published cost-utility analysis of a primary care intervention for the management of hypertension Targets and Self-Management for the Control of Blood Pressure in Stroke and at Risk Groups (TASMIN-SR). The case study assessed the structural uncertainty arising from model structure and from the exclusion of secondary events. Four alternative model structures were implemented. Long-term cost-effectiveness was estimated and the results compared with those from the TASMIN-SR model. The main cost-effectiveness results obtained in the TASMIN-SR study did not change with the implementation of alternative model structures. Choice of model type was limited to a cohort Markov model, and because of the lack of epidemiological data, only model 4 captured structural uncertainty arising from the exclusion of secondary events in the case study model. The results of this study indicate that the main conclusions drawn from the TASMIN-SR model of cost-effectiveness were robust to changes in model structure and the inclusion of secondary events. Even though one of the models produced results that were different to those of TASMIN-SR, the fact that the main conclusions were identical suggests that a more parsimonious model may have sufficed. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Vibroacoustic response of structures and perturbation Reynolds stress near structure-turbulence interface

NASA Technical Reports Server (NTRS)

Maekawa, S.; Lin, Y. K.

1977-01-01

The interaction between a turbulent flow and certain types of structures which respond to its excitation is investigated. One-dimensional models were used to develop the basic ideas applied to a second model resembling the fuselage construction of an aircraft. In the two-dimensional case a simple membrane, with a small random variation in the membrane tension, was used. A decaying turbulence was constructed by superposing infinitely many components, each of which is convected as a frozen pattern at a different velocity. Structure-turbulence interaction results are presented in terms of the spectral densities of the structural response and the perturbation Reynolds stress in the fluid at the vicinity of the interface.

Dynamic Modeling and Very Short-term Prediction of Wind Power Output Using Box-Cox Transformation

NASA Astrophysics Data System (ADS)

Urata, Kengo; Inoue, Masaki; Murayama, Dai; Adachi, Shuichi

2016-09-01

We propose a statistical modeling method of wind power output for very short-term prediction. The modeling method with a nonlinear model has cascade structure composed of two parts. One is a linear dynamic part that is driven by a Gaussian white noise and described by an autoregressive model. The other is a nonlinear static part that is driven by the output of the linear part. This nonlinear part is designed for output distribution matching: we shape the distribution of the model output to match with that of the wind power output. The constructed model is utilized for one-step ahead prediction of the wind power output. Furthermore, we study the relation between the prediction accuracy and the prediction horizon.

CFD-PBM coupled simulation of a nanobubble generator with honeycomb structure

NASA Astrophysics Data System (ADS)

Ren, F.; Noda, N. A.; Ueda, T.; Sano, Y.; Takase, Y.; Umekage, T.; Yonezawa, Y.; Tanaka, H.

2018-06-01

In recent years, nanobubble technologies have drawn great attention due to their wide applications in many fields of science and technology. The nitrogen nanobubble water circulation can be used to slow the progressions of oxidation and spoilage for the seafood long- term storage. From previous studies, a kind of honeycomb structure for high-efficiency nanobubble generation has been proposed. In this paper, the bubbly flow in the honeycomb structure was studied. The numerical simulations of honeycomb structure were performed by using a computational fluid dynamics–population balance model (CFD-PBM) coupled model. The numerical model was based on the Eulerian multiphase model and the population balance model (PBM) was used to calculate the gas bubble size distribution. The bubble coalescence and breakage were included. Considering the effect of bubble diameter on the fluid flow, the phase interactions were coupled with the PBM. The bubble size distributions in the honeycomb structure under different work conditions were predicted. The experimental results were compared with the simulation predictions.

Estimation of beam material random field properties via sensitivity-based model updating using experimental frequency response functions

NASA Astrophysics Data System (ADS)

Machado, M. R.; Adhikari, S.; Dos Santos, J. M. C.; Arruda, J. R. F.

2018-03-01

Structural parameter estimation is affected not only by measurement noise but also by unknown uncertainties which are present in the system. Deterministic structural model updating methods minimise the difference between experimentally measured data and computational prediction. Sensitivity-based methods are very efficient in solving structural model updating problems. Material and geometrical parameters of the structure such as Poisson's ratio, Young's modulus, mass density, modal damping, etc. are usually considered deterministic and homogeneous. In this paper, the distributed and non-homogeneous characteristics of these parameters are considered in the model updating. The parameters are taken as spatially correlated random fields and are expanded in a spectral Karhunen-Loève (KL) decomposition. Using the KL expansion, the spectral dynamic stiffness matrix of the beam is expanded as a series in terms of discretized parameters, which can be estimated using sensitivity-based model updating techniques. Numerical and experimental tests involving a beam with distributed bending rigidity and mass density are used to verify the proposed method. This extension of standard model updating procedures can enhance the dynamic description of structural dynamic models.

Report of the wwPDB Small-Angle Scattering Task Force: data requirements for biomolecular modeling and the PDB.

PubMed

Trewhella, Jill; Hendrickson, Wayne A; Kleywegt, Gerard J; Sali, Andrej; Sato, Mamoru; Schwede, Torsten; Svergun, Dmitri I; Tainer, John A; Westbrook, John; Berman, Helen M

2013-06-04

This report presents the conclusions of the July 12-13, 2012 meeting of the Small-Angle Scattering Task Force of the worldwide Protein Data Bank (wwPDB; Berman et al., 2003) at Rutgers University in New Brunswick, New Jersey. The task force includes experts in small-angle scattering (SAS), crystallography, data archiving, and molecular modeling who met to consider questions regarding the contributions of SAS to modern structural biology. Recognizing there is a rapidly growing community of structural biology researchers acquiring and interpreting SAS data in terms of increasingly sophisticated molecular models, the task force recommends that (1) a global repository is needed that holds standard format X-ray and neutron SAS data that is searchable and freely accessible for download; (2) a standard dictionary is required for definitions of terms for data collection and for managing the SAS data repository; (3) options should be provided for including in the repository SAS-derived shape and atomistic models based on rigid-body refinement against SAS data along with specific information regarding the uniqueness and uncertainty of the model, and the protocol used to obtain it; (4) criteria need to be agreed upon for assessment of the quality of deposited SAS data and the accuracy of SAS-derived models, and the extent to which a given model fits the SAS data; (5) with the increasing diversity of structural biology data and models being generated, archiving options for models derived from diverse data will be required; and (6) thought leaders from the various structural biology disciplines should jointly define what to archive in the PDB and what complementary archives might be needed, taking into account both scientific needs and funding. Copyright © 2013 Elsevier Ltd. All rights reserved.

Creating an Optimal 3D Printed Model for Temporal Bone Dissection Training.

PubMed

Takahashi, Kuniyuki; Morita, Yuka; Ohshima, Shinsuke; Izumi, Shuji; Kubota, Yamato; Yamamoto, Yutaka; Takahashi, Sugata; Horii, Arata

2017-07-01

Making a 3-dimensional (3D) temporal bone model is simple using a plaster powder bed and an inkjet printer. However, it is difficult to reproduce air-containing spaces and precise middle ear structures. The objective of this study was to overcome these problems and create a temporal bone model that would be useful both as a training tool and for preoperative simulation. Drainage holes were made to remove excess materials from air-containing spaces, ossicle ligaments were manually changed to bony structures, and small and/or soft tissue structures were colored differently while designing the 3D models. The outcomes were evaluated by 3 procedures: macroscopic and endoscopic inspection of the model, comparison of computed tomography (CT) images of the model to the original CT, and assessment of tactile sensation and reproducibility by 20 surgeons performing surgery on the model. Macroscopic and endoscopic inspection, CT images, and assessment by surgeons were in agreement in terms of reproducibility of model structures. Most structures could be reproduced, but the stapes, tympanic sinus, and mastoid air cells were unsatisfactory. Perioperative tactile sensation of the model was excellent. Although this model still does not embody perfect reproducibility, it proved sufficiently practical for use in surgical training.

Spatial evolutionary epidemiology of spreading epidemics

PubMed Central

2016-01-01

Most spatial models of host–parasite interactions either neglect the possibility of pathogen evolution or consider that this process is slow enough for epidemiological dynamics to reach an equilibrium on a fast timescale. Here, we propose a novel approach to jointly model the epidemiological and evolutionary dynamics of spatially structured host and pathogen populations. Starting from a multi-strain epidemiological model, we use a combination of spatial moment equations and quantitative genetics to analyse the dynamics of mean transmission and virulence in the population. A key insight of our approach is that, even in the absence of long-term evolutionary consequences, spatial structure can affect the short-term evolution of pathogens because of the build-up of spatial differentiation in mean virulence. We show that spatial differentiation is driven by a balance between epidemiological and genetic effects, and this quantity is related to the effect of kin competition discussed in previous studies of parasite evolution in spatially structured host populations. Our analysis can be used to understand and predict the transient evolutionary dynamics of pathogens and the emergence of spatial patterns of phenotypic variation. PMID:27798295

Spatial evolutionary epidemiology of spreading epidemics.

PubMed

Lion, S; Gandon, S

2016-10-26

Most spatial models of host-parasite interactions either neglect the possibility of pathogen evolution or consider that this process is slow enough for epidemiological dynamics to reach an equilibrium on a fast timescale. Here, we propose a novel approach to jointly model the epidemiological and evolutionary dynamics of spatially structured host and pathogen populations. Starting from a multi-strain epidemiological model, we use a combination of spatial moment equations and quantitative genetics to analyse the dynamics of mean transmission and virulence in the population. A key insight of our approach is that, even in the absence of long-term evolutionary consequences, spatial structure can affect the short-term evolution of pathogens because of the build-up of spatial differentiation in mean virulence. We show that spatial differentiation is driven by a balance between epidemiological and genetic effects, and this quantity is related to the effect of kin competition discussed in previous studies of parasite evolution in spatially structured host populations. Our analysis can be used to understand and predict the transient evolutionary dynamics of pathogens and the emergence of spatial patterns of phenotypic variation. © 2016 The Author(s).

Autonomous oscillation in supramolecular assemblies: Role of free energy landscape and fluctuations

NASA Astrophysics Data System (ADS)

Sereda, Yuriy V.; Ortoleva, Peter J.

2015-11-01

Molecular dynamics studies demonstrated that a supramolecular assembly can express autonomous structural oscillations about equilibrium. It is demonstrated here that for nanosystems such oscillations can result from the interplay of free energy landscape and structural fluctuations. Furthermore, these oscillations have intermittent character, reflecting the conflict between a tendency to oscillate due to features in the free energy landscape, and the Second Law's repression of perpetual oscillation in an isothermal, equilibrium system. The demonstration system is a T = 1 icosahedral structure constituted of 12 protein pentamers in contact with a bath at fixed temperature. The oscillations are explained in terms of a Langevin model accounting for interactions among neighboring pentamers. The model is based on a postulated free energy landscape in the 24-dimensional space of variables describing the centrifugal and rotational motion of each pentamer. The model includes features such as basins of attraction and low free energy corridors. When the system is driven slightly out of equilibrium, the oscillations are transformed into a limit cycle, as expressed in terms of power spectrum narrowing.

Effects of air pollution on thermal structure and dispersion in an urban planetary boundary layer

NASA Technical Reports Server (NTRS)

Viskanta, R.; Johnson, R. O.; Bergstrom, R. W.

1977-01-01

The short-term effects of urbanization and air pollution on the transport processes in the urban planetary boundary layer (PBL) are studied. The investigation makes use of an unsteady two-dimensional transport model which has been developed by Viskanta et al., (1976). The model predicts pollutant concentrations and temperature in the PBL. The potential effects of urbanization and air pollution on the thermal structure in the urban PBL are considered, taking into account the results of numerical simulations modeling the St. Louis, Missouri metropolitan area.

QSAR, docking and ADMET studies of artemisinin derivatives for antimalarial activity targeting plasmepsin II, a hemoglobin-degrading enzyme from P. falciparum.

PubMed

Qidwai, Tabish; Yadav, Dharmendra K; Khan, Feroz; Dhawan, Sangeeta; Bhakuni, R S

2012-01-01

This work presents the development of quantitative structure activity relationship (QSAR) model to predict the antimalarial activity of artemisinin derivatives. The structures of the molecules are represented by chemical descriptors that encode topological, geometric, and electronic structure features. Screening through QSAR model suggested that compounds A24, A24a, A53, A54, A62 and A64 possess significant antimalarial activity. Linear model is developed by the multiple linear regression method to link structures to their reported antimalarial activity. The correlation in terms of regression coefficient (r(2)) was 0.90 and prediction accuracy of model in terms of cross validation regression coefficient (rCV(2)) was 0.82. This study indicates that chemical properties viz., atom count (all atoms), connectivity index (order 1, standard), ring count (all rings), shape index (basic kappa, order 2), and solvent accessibility surface area are well correlated with antimalarial activity. The docking study showed high binding affinity of predicted active compounds against antimalarial target Plasmepsins (Plm-II). Further studies for oral bioavailability, ADMET and toxicity risk assessment suggest that compound A24, A24a, A53, A54, A62 and A64 exhibits marked antimalarial activity comparable to standard antimalarial drugs. Later one of the predicted active compound A64 was chemically synthesized, structure elucidated by NMR and in vivo tested in multidrug resistant strain of Plasmodium yoelii nigeriensis infected mice. The experimental results obtained agreed well with the predicted values.

Open challenges in structure-based virtual screening: Receptor modeling, target flexibility consideration and active site water molecules description.

PubMed

Spyrakis, Francesca; Cavasotto, Claudio N

2015-10-01

Structure-based virtual screening is currently an established tool in drug lead discovery projects. Although in the last years the field saw an impressive progress in terms of algorithm development, computational performance, and retrospective and prospective applications in ligand identification, there are still long-standing challenges where further improvement is needed. In this review, we consider the conceptual frame, state-of-the-art and recent developments of three critical "structural" issues in structure-based drug lead discovery: the use of homology modeling to accurately model the binding site when no experimental structures are available, the necessity of accounting for the dynamics of intrinsically flexible systems as proteins, and the importance of considering active site water molecules in lead identification and optimization campaigns. Copyright © 2015 Elsevier Inc. All rights reserved.

FUN3D and CFL3D Computations for the First High Lift Prediction Workshop

NASA Technical Reports Server (NTRS)

Park, Michael A.; Lee-Rausch, Elizabeth M.; Rumsey, Christopher L.

2011-01-01

Two Reynolds-averaged Navier-Stokes codes were used to compute flow over the NASA Trapezoidal Wing at high lift conditions for the 1st AIAA CFD High Lift Prediction Workshop, held in Chicago in June 2010. The unstructured-grid code FUN3D and the structured-grid code CFL3D were applied to several different grid systems. The effects of code, grid system, turbulence model, viscous term treatment, and brackets were studied. The SST model on this configuration predicted lower lift than the Spalart-Allmaras model at high angles of attack; the Spalart-Allmaras model agreed better with experiment. Neglecting viscous cross-derivative terms caused poorer prediction in the wing tip vortex region. Output-based grid adaptation was applied to the unstructured-grid solutions. The adapted grids better resolved wake structures and reduced flap flow separation, which was also observed in uniform grid refinement studies. Limitations of the adaptation method as well as areas for future improvement were identified.

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

Scoring of Side-Chain Packings: An Analysis of Weight Factors and Molecular Dynamics Structures.

PubMed

Colbes, Jose; Aguila, Sergio A; Brizuela, Carlos A

2018-02-26

The protein side-chain packing problem (PSCPP) is a central task in computational protein design. The problem is usually modeled as a combinatorial optimization problem, which consists of searching for a set of rotamers, from a given rotamer library, that minimizes a scoring function (SF). The SF is a weighted sum of terms, that can be decomposed in physics-based and knowledge-based terms. Although there are many methods to obtain approximate solutions for this problem, all of them have similar performances and there has not been a significant improvement in recent years. Studies on protein structure prediction and protein design revealed the limitations of current SFs to achieve further improvements for these two problems. In the same line, a recent work reported a similar result for the PSCPP. In this work, we ask whether or not this negative result regarding further improvements in performance is due to (i) an incorrect weighting of the SFs terms or (ii) the constrained conformation resulting from the protein crystallization process. To analyze these questions, we (i) model the PSCPP as a bi-objective combinatorial optimization problem, optimizing, at the same time, the two most important terms of two SFs of state-of-the-art algorithms and (ii) performed a preprocessing relaxation of the crystal structure through molecular dynamics to simulate the protein in the solvent and evaluated the performance of these two state-of-the-art SFs under these conditions. Our results indicate that (i) no matter what combination of weight factors we use the current SFs will not lead to better performances and (ii) the evaluated SFs will not be able to improve performance on relaxed structures. Furthermore, the experiments revealed that the SFs and the methods are biased toward crystallized structures.

Contrasts in short- and long-term responses of Mediterranean reptile species to fire and habitat structure.

PubMed

Santos, Xavier; Badiane, Arnaud; Matos, Cátia

2016-01-01

Changes in habitat structure constitute a major factor explaining responses of reptiles to fire. However, few studies have examined habitat factors that covary with fire-history variables to explain reptile responses. We hypothesise that more complex habitats should support richer reptile communities, and that species-specific relative abundance should be related to particular habitat features. From spring 2012-2014, twenty-five transects were surveyed in the Albera Region (north-east Iberia). The vegetation structure was measured and the extent of habitat types in a 1000-m buffer around each transect calculated. Reptile-community metrics (species richness and reptile abundance) were related to fire history, vegetation structure, and habitat types, using generalized additive models. These metrics correlated with habitat-structure variables but not with fire history. The number of species increased with more complex habitats but decreased with pine-plantation abundance in the 1000-m buffer. We found contrasting responses among reptiles in terms of time since fire and those responses differed according to vegetation variables and habitat types. An unplanned fire in August 2012 provided the opportunity to compare reptile abundance values between pre-fire and the short term (1-2 years) after the fire. Most species exhibited a negative short-term response to the 2012 fire except Tarentola mauritanica, a gecko that inhabits large rocks, as opposed to other ground-dwelling species. In the reptiles studied, contrasting responses to time since fire are consistent with the habitat-accommodation model of succession. These differences are linked to specific microhabitat preferences and suggest that functional traits can be used to predict species-specific responses to fire.

Characterizing uncertainty and variability in physiologically based pharmacokinetic models: state of the science and needs for research and implementation.

PubMed

Barton, Hugh A; Chiu, Weihsueh A; Setzer, R Woodrow; Andersen, Melvin E; Bailer, A John; Bois, Frédéric Y; Dewoskin, Robert S; Hays, Sean; Johanson, Gunnar; Jones, Nancy; Loizou, George; Macphail, Robert C; Portier, Christopher J; Spendiff, Martin; Tan, Yu-Mei

2007-10-01

Physiologically based pharmacokinetic (PBPK) models are used in mode-of-action based risk and safety assessments to estimate internal dosimetry in animals and humans. When used in risk assessment, these models can provide a basis for extrapolating between species, doses, and exposure routes or for justifying nondefault values for uncertainty factors. Characterization of uncertainty and variability is increasingly recognized as important for risk assessment; this represents a continuing challenge for both PBPK modelers and users. Current practices show significant progress in specifying deterministic biological models and nondeterministic (often statistical) models, estimating parameters using diverse data sets from multiple sources, using them to make predictions, and characterizing uncertainty and variability of model parameters and predictions. The International Workshop on Uncertainty and Variability in PBPK Models, held 31 Oct-2 Nov 2006, identified the state-of-the-science, needed changes in practice and implementation, and research priorities. For the short term, these include (1) multidisciplinary teams to integrate deterministic and nondeterministic/statistical models; (2) broader use of sensitivity analyses, including for structural and global (rather than local) parameter changes; and (3) enhanced transparency and reproducibility through improved documentation of model structure(s), parameter values, sensitivity and other analyses, and supporting, discrepant, or excluded data. Longer-term needs include (1) theoretical and practical methodological improvements for nondeterministic/statistical modeling; (2) better methods for evaluating alternative model structures; (3) peer-reviewed databases of parameters and covariates, and their distributions; (4) expanded coverage of PBPK models across chemicals with different properties; and (5) training and reference materials, such as cases studies, bibliographies/glossaries, model repositories, and enhanced software. The multidisciplinary dialogue initiated by this Workshop will foster the collaboration, research, data collection, and training necessary to make characterizing uncertainty and variability a standard practice in PBPK modeling and risk assessment.

Design and performance of optimal detectors for guided wave structural health monitoring

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

Dib, G.; Udpa, L.

2016-01-01

Ultrasonic guided wave measurements in a long term structural health monitoring system are affected by measurement noise, environmental conditions, transducer aging and malfunction. This results in measurement variability which affects detection performance, especially in complex structures where baseline data comparison is required. This paper derives the optimal detector structure, within the framework of detection theory, where a guided wave signal at the sensor is represented by a single feature value that can be used for comparison with a threshold. Three different types of detectors are derived depending on the underlying structure’s complexity: (i) Simple structures where defect reflections can bemore » identified without the need for baseline data; (ii) Simple structures that require baseline data due to overlap of defect scatter with scatter from structural features; (iii) Complex structure with dense structural features that require baseline data. The detectors are derived by modeling the effects of variabilities and uncertainties as random processes. Analytical solutions for the performance of detectors in terms of the probability of detection and false alarm are derived. A finite element model is used to generate guided wave signals and the performance results of a Monte-Carlo simulation are compared with the theoretical performance. initial results demonstrate that the problems of signal complexity and environmental variability can in fact be exploited to improve detection performance.« less

Role of vertex corrections in the matrix formulation of the random phase approximation for the multiorbital Hubbard model

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

Altmeyer, Michaela; Guterding, Daniel; Hirschfeld, P. J.

2016-12-21

In the framework of a multiorbital Hubbard model description of superconductivity, a matrix formulation of the superconducting pairing interaction that has been widely used is designed to treat spin, charge, and orbital fluctuations within a random phase approximation (RPA). In terms of Feynman diagrams, this takes into account particle-hole ladder and bubble contributions as expected. It turns out, however, that this matrix formulation also generates additional terms which have the diagrammatic structure of vertex corrections. Furthermore we examine these terms and discuss the relationship between the matrix-RPA superconducting pairing interaction and the Feynman diagrams that it sums.

Chromosome rearrangements and the evolution of genome structuring and adaptability.

PubMed

Crombach, Anton; Hogeweg, Paulien

2007-05-01

Eukaryotes appear to evolve by micro and macro rearrangements. This is observed not only for long-term evolutionary adaptation, but also in short-term experimental evolution of yeast, Saccharomyces cerevisiae. Moreover, based on these and other experiments it has been postulated that repeat elements, retroposons for example, mediate such events. We study an evolutionary model in which genomes with retroposons and a breaking/repair mechanism are subjected to a changing environment. We show that retroposon-mediated rearrangements can be a beneficial mutational operator for short-term adaptations to a new environment. But simply having the ability of rearranging chromosomes does not imply an advantage over genomes in which only single-gene insertions and deletions occur. Instead, a structuring of the genome is needed: genes that need to be amplified (or deleted) in a new environment have to cluster. We show that genomes hosting retroposons, starting with a random order of genes, will in the long run become organized, which enables (fast) rearrangement-based adaptations to the environment. In other words, our model provides a "proof of principle" that genomes can structure themselves in order to increase the beneficial effect of chromosome rearrangements.

Structural synthesis: Precursor and catalyst

NASA Technical Reports Server (NTRS)

Schmit, L. A.

1984-01-01

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

DTFM Modeling and Analysis Method for Gossamer Structures

NASA Technical Reports Server (NTRS)

Fang, Hou-Fei; Lou, Michael; Broduer, Steve (Technical Monitor)

2001-01-01

Gossamer systems are mostly composed of support structures formed by highly flexible, long tubular elements and pre-tensioned thin-film membranes. These systems offer order-of-magnitude reductions in mass and launch volume and will revolutionize the architecture and design of space flight systems that require large in-orbit configurations and apertures. A great interest has been generated in recent years to fly gossamer systems on near-term and future space missions. Modeling and analysis requirements for gossamer structures are unique. Simulation of in-space performance issues of gossamer structures, such as inflation deployment of flexible booms, formation and effects of wrinkle in tensioned membranes, synthesis of tubular and membrane elements into a complete structural system, usually cannot be accomplished by using the general-purpose finite-element structural analysis codes. This has led to the need of structural modeling and analysis capabilities specifically suitable for gossamer structures. The Distributed Transfer Function Method (DTFM) can potentially meet this urgent need. Additional information is contained in the original extended abstract.

Development of a hybrid wave based-transfer matrix model for sound transmission analysis.

PubMed

Dijckmans, A; Vermeir, G

2013-04-01

In this paper, a hybrid wave based-transfer matrix model is presented that allows for the investigation of the sound transmission through finite multilayered structures placed between two reverberant rooms. The multilayered structure may consist of an arbitrary configuration of fluid, elastic, or poro-elastic layers. The field variables (structural displacements and sound pressures) are expanded in terms of structural and acoustic wave functions. The boundary and continuity conditions in the rooms determine the participation factors in the pressure expansions. The displacement of the multilayered structure is determined by the mechanical impedance matrix, which gives a relation between the pressures and transverse displacements at both sides of the structure. The elements of this matrix are calculated with the transfer matrix method. First, the hybrid model is numerically validated. Next a comparison is made with sound transmission loss measurements of a hollow brick wall and a sandwich panel. Finally, numerical simulations show the influence of structural damping, room dimensions and plate dimensions on the sound transmission loss of multilayered structures.

Teaching macromolecular modeling.

PubMed Central

Harvey, S C; Tan, R K

1992-01-01

Training newcomers to the field of macromolecular modeling is as difficult as is training beginners in x-ray crystallography, nuclear magnetic resonance, or other methods in structural biology. In one or two lectures, the most that can be conveyed is a general sense of the relationship between modeling and other structural methods. If a full semester is available, then students can be taught how molecular structures are built, manipulated, refined, and analyzed on a computer. Here we describe a one-semester modeling course that combines lectures, discussions, and a laboratory using a commercial modeling package. In the laboratory, students carry out prescribed exercises that are coordinated to the lectures, and they complete a term project on a modeling problem of their choice. The goal is to give students an understanding of what kinds of problems can be attacked by molecular modeling methods and which problems are beyond the current capabilities of those methods. PMID:1489919

A predictive framework for evaluating models of semantic organization in free recall

PubMed Central

Morton, Neal W; Polyn, Sean M.

2016-01-01

Research in free recall has demonstrated that semantic associations reliably influence the organization of search through episodic memory. However, the specific structure of these associations and the mechanisms by which they influence memory search remain unclear. We introduce a likelihood-based model-comparison technique, which embeds a model of semantic structure within the context maintenance and retrieval (CMR) model of human memory search. Within this framework, model variants are evaluated in terms of their ability to predict the specific sequence in which items are recalled. We compare three models of semantic structure, latent semantic analysis (LSA), global vectors (GloVe), and word association spaces (WAS), and find that models using WAS have the greatest predictive power. Furthermore, we find evidence that semantic and temporal organization is driven by distinct item and context cues, rather than a single context cue. This finding provides important constraint for theories of memory search. PMID:28331243

Vascular structural and functional changes: their association with causality in hypertension: models, remodeling and relevance.

PubMed

Lee, Robert Mkw; Dickhout, Jeffrey G; Sandow, Shaun L

2017-04-01

Essential hypertension is a complex multifactorial disease process that involves the interaction of multiple genes at various loci throughout the genome, and the influence of environmental factors such as diet and lifestyle, to ultimately determine long-term arterial pressure. These factors converge with physiological signaling pathways to regulate the set-point of long-term blood pressure. In hypertension, structural changes in arteries occur and show differences within and between vascular beds, between species, models and sexes. Such changes can also reflect the development of hypertension, and the levels of circulating humoral and vasoactive compounds. The role of perivascular adipose tissue in the modulation of vascular structure under various disease states such as hypertension, obesity and metabolic syndrome is an emerging area of research, and is likely to contribute to the heterogeneity described in this review. Diversity in structure and related function is the norm, with morphological changes being causative in some beds and states, and in others, a consequence of hypertension. Specific animal models of hypertension have advantages and limitations, each with factors influencing the relevance of the model to the human hypertensive state/s. However, understanding the fundamental properties of artery function and how these relate to signalling mechanisms in real (intact) tissues is key for translating isolated cell and model data to have an impact and relevance in human disease etiology. Indeed, the ultimate aim of developing new treatments to correct vascular dysfunction requires understanding and recognition of the limitations of the methodologies used.

Energy-density field approach for low- and medium-frequency vibroacoustic analysis of complex structures using a statistical computational model

NASA Astrophysics Data System (ADS)

Kassem, M.; Soize, C.; Gagliardini, L.

2009-06-01

In this paper, an energy-density field approach applied to the vibroacoustic analysis of complex industrial structures in the low- and medium-frequency ranges is presented. This approach uses a statistical computational model. The analyzed system consists of an automotive vehicle structure coupled with its internal acoustic cavity. The objective of this paper is to make use of the statistical properties of the frequency response functions of the vibroacoustic system observed from previous experimental and numerical work. The frequency response functions are expressed in terms of a dimensionless matrix which is estimated using the proposed energy approach. Using this dimensionless matrix, a simplified vibroacoustic model is proposed.

Sedimentological indicators of paleoenvironments and siliciclastic stratigraphic sequences in some Miocene deposits of the Calvert Cliffs, southern Maryland

USGS Publications Warehouse

Shideler, G.L.

1994-01-01

Middle Miocene siliciclastic deposits comprising the Calvert Cliffs section at the Baltimore Gas and Electric Company's (BG&E) nuclear power plant site in southern Maryland were analyzed in terms of lithostratigraphy, sedimentary structures, and granulometric parameters, to interprete paleo-environments within a sequence-stratigraphic framework. In terms of sequence-stratigraphic models, the BG&E section can be interpreted as consisting of two genetic stratigraphic sequences (Galloway model), namely, a shelf sequence and an overlying deltaic sequence. Using the Exxon model, the section consists of two third-order (1-5 m.y. duration) depositional sequences. The stratigraphic sequences of the BG&E section reflect both relatively short-term eustatic transgressive events, as well as a long-term regressive trend with associated local deltation and coastal progradation. The regression probably signified a regional basinward shift of depocenters within the Salisbury embayment during Miocene time. -from Author

QSAR modeling based on structure-information for properties of interest in human health.

PubMed

Hall, L H; Hall, L M

2005-01-01

The development of QSAR models based on topological structure description is presented for problems in human health. These models are based on the structure-information approach to quantitative biological modeling and prediction, in contrast to the mechanism-based approach. The structure-information approach is outlined, starting with basic structure information developed from the chemical graph (connection table). Information explicit in the connection table (element identity and skeletal connections) leads to significant (implicit) structure information that is useful for establishing sound models of a wide range of properties of interest in drug design. Valence state definition leads to relationships for valence state electronegativity and atom/group molar volume. Based on these important aspects of molecules, together with skeletal branching patterns, both the electrotopological state (E-state) and molecular connectivity (chi indices) structure descriptors are developed and described. A summary of four QSAR models indicates the wide range of applicability of these structure descriptors and the predictive quality of QSAR models based on them: aqueous solubility (5535 chemically diverse compounds, 938 in external validation), percent oral absorption (%OA, 417 therapeutic drugs, 195 drugs in external validation testing), AMES mutagenicity (2963 compounds including 290 therapeutic drugs, 400 in external validation), fish toxicity (92 substituted phenols, anilines and substituted aromatics). These models are established independent of explicit three-dimensional (3-D) structure information and are directly interpretable in terms of the implicit structure information useful to the drug design process.

Skewness in large-scale structure and non-Gaussian initial conditions

NASA Technical Reports Server (NTRS)

Fry, J. N.; Scherrer, Robert J.

1994-01-01

We compute the skewness of the galaxy distribution arising from the nonlinear evolution of arbitrary non-Gaussian intial conditions to second order in perturbation theory including the effects of nonlinear biasing. The result contains a term identical to that for a Gaussian initial distribution plus terms which depend on the skewness and kurtosis of the initial conditions. The results are model dependent; we present calculations for several toy models. At late times, the leading contribution from the initial skewness decays away relative to the other terms and becomes increasingly unimportant, but the contribution from initial kurtosis, previously overlooked, has the same time dependence as the Gaussian terms. Observations of a linear dependence of the normalized skewness on the rms density fluctuation therefore do not necessarily rule out initially non-Gaussian models. We also show that with non-Gaussian initial conditions the first correction to linear theory for the mean square density fluctuation is larger than for Gaussian models.

Short-term memory

NASA Astrophysics Data System (ADS)

Toulouse, G.

This is a rather bold attempt to bridge the gap between neuron structure and psychological data. We try to answer the question: Is there a relation between the neuronal connectivity in the human cortex (around 5,000) and the short-term memory capacity (7±2)? Our starting point is the Hopfield model (Hopfield 1982), presented in this volume by D.J. Amit.

Creating and Benefiting from Institutional Collaboration: Models for Success. New Directions for Community Colleges, Number 103.

ERIC Educational Resources Information Center

McGrath, Dennis, Ed.

1998-01-01

This volume offers a variety of examples of long-term collaborative efforts within schools that began with external funding. Articles include: (1) "Lessons from a Long-Term Collaboration," (Lindsay M. Wright and Rona Middleberg); (2) "Creating Structural Change: Best Practices," (Janet E. Lieberman); (3) "An Urban Intervention That Works: The…

Peak Communication Experiences: Concept, Structure, and Sex Differences.

ERIC Educational Resources Information Center

Gordon, Ron; Dulaney, Earl

A study was conducted to test a "peak communication experience" (PCE) scale developed from Abraham Maslow's theory of PCE's, a model of one's highest interpersonal communication moments in terms of perceived mutual understanding, happiness, and personal fulfillment. Nineteen items, extrapolated from Maslow's model but rendered more…

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

Structural competency: Theorizing a new medical engagement with stigma and inequality

PubMed Central

Metzl, Jonathan M.; Hansen, Helena

2014-01-01

This paper describes a shift in medical education away from pedagogic approaches to stigma and inequalities that emphasize cross-cultural understandings of individual patients, toward attention to forces that influence health outcomes at levels above individual interactions. It reviews existing structural approaches to stigma and health inequalities developed outside of medicine, and proposes changes to U.S. medical education that will infuse clinical training with a structural focus. The approach, termed “structural competency,” consists of training in five core competencies: 1) recognizing the structures that shape clinical interactions; 2) developing an extra-clinical language of structure; 3) rearticulating “cultural” formulations in structural terms; 4) observing and imagining structural interventions; and 5) developing structural humility. Examples are provided of structural health scholarship that should be adopted into medical didactic curricula, and of structural interventions that can provide participant-observation opportunities for clinical trainees. The paper ultimately argues that increasing recognition of the ways in which social and economic forces produce symptoms or methylate genes then needs to be better coupled with medical models for structural change. PMID:24507917

The effect of classroom structure on verbal and physical aggression among peers: a short-term longitudinal study.

PubMed

Bergsmann, Evelyn M; Van De Schoot, Rens; Schober, Barbara; Finsterwald, Monika; Spiel, Christiane

2013-04-01

Teachers promote student learning and well-being in school by establishing a supportive classroom structure. The term classroom structure refers to how teachers design tasks, maintain authority, and evaluate student achievement. Although empirical studies have shown the relation of classroom structure to student motivation, achievement, and well-being, no prior investigations have examined the influence of classroom structure on aggression among peers. The present study examined whether a supportive classroom structure has an impact on verbal and physical aggression. At two points in time, data were collected from 1680 students in Grades 5 to 7 using self-report questionnaires. The results of structural equation modeling revealed that a supportive classroom structure at Time 1 was associated with less perpetrated verbal aggression at Time 2, 9months later. This finding has practical relevance for teacher training as well as for aggression prevention and intervention among children. Copyright © 2012 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Institutional Approaches to Innovation and Change: A Review of the Esman Model of Institution Building.

ERIC Educational Resources Information Center

Bhola, H. S.

The definitional and conceptual structure of the Esman model of institution building is described in great detail, emphasizing its philosophic and process assumptions and its latent dynamics. The author systematically critiques the Esman model in terms of its (1) specificity to the universe of institution building, (2) generalizability across…

A Note on the Specification of Error Structures in Latent Interaction Models

ERIC Educational Resources Information Center

Mao, Xiulin; Harring, Jeffrey R.; Hancock, Gregory R.

2015-01-01

Latent interaction models have motivated a great deal of methodological research, mainly in the area of estimating such models. Product-indicator methods have been shown to be competitive with other methods of estimation in terms of parameter bias and standard error accuracy, and their continued popularity in empirical studies is due, in part, to…

Data-Driven Hierarchical Structure Kernel for Multiscale Part-Based Object Recognition

PubMed Central

Wang, Botao; Xiong, Hongkai; Jiang, Xiaoqian; Zheng, Yuan F.

2017-01-01

Detecting generic object categories in images and videos are a fundamental issue in computer vision. However, it faces the challenges from inter and intraclass diversity, as well as distortions caused by viewpoints, poses, deformations, and so on. To solve object variations, this paper constructs a structure kernel and proposes a multiscale part-based model incorporating the discriminative power of kernels. The structure kernel would measure the resemblance of part-based objects in three aspects: 1) the global similarity term to measure the resemblance of the global visual appearance of relevant objects; 2) the part similarity term to measure the resemblance of the visual appearance of distinctive parts; and 3) the spatial similarity term to measure the resemblance of the spatial layout of parts. In essence, the deformation of parts in the structure kernel is penalized in a multiscale space with respect to horizontal displacement, vertical displacement, and scale difference. Part similarities are combined with different weights, which are optimized efficiently to maximize the intraclass similarities and minimize the interclass similarities by the normalized stochastic gradient ascent algorithm. In addition, the parameters of the structure kernel are learned during the training process with regard to the distribution of the data in a more discriminative way. With flexible part sizes on scale and displacement, it can be more robust to the intraclass variations, poses, and viewpoints. Theoretical analysis and experimental evaluations demonstrate that the proposed multiscale part-based representation model with structure kernel exhibits accurate and robust performance, and outperforms state-of-the-art object classification approaches. PMID:24808345

Between Policy and Practice: Structuring Workplace Learning in Higher Vocational Education in Sweden and Finland

ERIC Educational Resources Information Center

Lindell, Mats; Stenstrom, Marja-Leena

2005-01-01

Purpose: This study considers the recently established higher vocational education reforms with Swedish advanced vocational education (AVE) and Finnish polytechnics in terms of organisational structure, the design of workplace learning, and furthermore, what kind of practical implications these new models of learning at work have resulted in.…

Exploring the Use of a Social Network to Facilitate and Integrate Long-Term Interprofessional Educational Experiences

ERIC Educational Resources Information Center

Pittenger, Amy L.

2011-01-01

The purpose of this study was to evaluate the feasibility and effectiveness of implementing interprofessional education to students from six health professional programs through use of an online social networking platform. Specifically, three pedagogical models (Minimally Structured, Facilitated, Highly Structured) were evaluated for impact on…

On the Delusiveness of Adopting a Common Space for Modeling IR Objects: Are Queries Documents?

ERIC Educational Resources Information Center

Bollmann-Sdorra, Peter; Raghavan, Vjay V.

1993-01-01

Proposes that document space and query space have different structures in information retrieval and discusses similarity measures, term independence, and linear structure. Examples are given using the retrieval functions of dot-product, the cosine measure, the coefficient of Jaccard, and the overlap function. (Contains 28 references.) (LRW)

Structural equation model of total phosphorus loads in the Red River of the North Basin, USA and Canada

USGS Publications Warehouse

Ryberg, Karen R.

2017-01-01

Attribution of the causes of trends in nutrient loading is often limited to correlation, qualitative reasoning, or references to the work of others. This paper represents efforts to improve causal attribution of water-quality changes. The Red River of the North basin provides a regional test case because of international interest in the reduction of total phosphorus loads and the availability of long-term total phosphorus data and ancillary geospatial data with the potential to explain changes in water quality over time. The objectives of the study are to investigate structural equation modeling methods for application to water-quality problems and to test causal hypotheses related to the drivers of total phosphorus loads over the period 1970 to 2012. Multiple working hypotheses that explain total phosphorus loads and methods for estimating missing ancillary data were developed, and water-quality related challenges to structural equation modeling (including skewed data and scaling issues) were addressed. The model indicates that increased precipitation in season 1 (November–February) or season 2 (March–June) would increase total phosphorus loads in the basin. The effect of agricultural practices on total phosphorus loads was significant, although the effect is about one-third of the effect of season 1 precipitation. The structural equation model representing loads at six sites in the basin shows that climate and agricultural practices explain almost 60% of the annual total phosphorus load in the Red River of the North basin. The modeling process and the unexplained variance highlight the need for better ancillary long-term data for causal assessments.

Assessment of corneal properties based on statistical modeling of OCT speckle

PubMed Central

Jesus, Danilo A.; Iskander, D. Robert

2016-01-01

A new approach to assess the properties of the corneal micro-structure in vivo based on the statistical modeling of speckle obtained from Optical Coherence Tomography (OCT) is presented. A number of statistical models were proposed to fit the corneal speckle data obtained from OCT raw image. Short-term changes in corneal properties were studied by inducing corneal swelling whereas age-related changes were observed analyzing data of sixty-five subjects aged between twenty-four and seventy-three years. Generalized Gamma distribution has shown to be the best model, in terms of the Akaike’s Information Criterion, to fit the OCT corneal speckle. Its parameters have shown statistically significant differences (Kruskal-Wallis, p < 0.001) for short and age-related corneal changes. In addition, it was observed that age-related changes influence the corneal biomechanical behaviour when corneal swelling is induced. This study shows that Generalized Gamma distribution can be utilized to modeling corneal speckle in OCT in vivo providing complementary quantified information where micro-structure of corneal tissue is of essence. PMID:28101409

Structure of S-shaped growth in innovation diffusion

NASA Astrophysics Data System (ADS)

Shimogawa, Shinsuke; Shinno, Miyuki; Saito, Hiroshi

2012-05-01

A basic question on innovation diffusion is why the growth curve of the adopter population in a large society is often S shaped. From macroscopic, microscopic, and mesoscopic viewpoints, the growth of the adopter population is observed as the growth curve, individual adoptions, and differences among individual adoptions, respectively. The S shape can be explained if an empirical model of the growth curve can be deduced from models of microscopic and mesoscopic structures. However, even the structure of growth curve has not been revealed yet because long-term extrapolations by proposed models of S-shaped curves are unstable and it has been very difficult to predict the long-term growth and final adopter population. This paper studies the S-shaped growth from the viewpoint of social regularities. Simple methods to analyze power laws enable us to extract the structure of the growth curve directly from the growth data of recent basic telecommunication services. This empirical model of growth curve is singular at the inflection point and a logarithmic function of time after this point, which explains the unstable extrapolations obtained using previously proposed models and the difficulty in predicting the final adopter population. Because the empirical S curve can be expressed in terms of two power laws of the regularity found in social performances of individuals, we propose the hypothesis that the S shape represents the heterogeneity of the adopter population, and the heterogeneity parameter is distributed under the regularity in social performances of individuals. This hypothesis is so powerful as to yield models of microscopic and mesoscopic structures. In the microscopic model, each potential adopter adopts the innovation when the information accumulated by the learning about the innovation exceeds a threshold. The accumulation rate of information is heterogeneous among the adopter population, whereas the threshold is a constant, which is the opposite of previously proposed models. In the mesoscopic model, flows of innovation information incoming to individuals are organized as dimorphic and partially clustered. These microscopic and mesoscopic models yield the empirical model of the S curve and explain the S shape as representing the regularities of information flows generated through a social self-organization. To demonstrate the validity and importance of the hypothesis, the models of three level structures are applied to reveal the mechanism determining and differentiating diffusion speeds. The empirical model of S curves implies that the coefficient of variation of the flow rates determines the diffusion speed for later adopters. Based on this property, a model describing the inside of information flow clusters can be given, which provides a formula interconnecting the diffusion speed, cluster populations, and a network topological parameter of the flow clusters. For two recent basic telecommunication services in Japan, the formula represents the variety of speeds in different areas and enables us to explain speed gaps between urban and rural areas and between the two services. Furthermore, the formula provides a method to estimate the final adopter population.

Solar wind and coronal structure near sunspot minimum - Pioneer and SMM observations from 1985-1987

NASA Technical Reports Server (NTRS)

Mihalov, J. D.; Barnes, A.; Hundhausen, A. J.; Smith, E. J.

1990-01-01

Changes in solar wind speed and magnetic polarity observed at the Pioneer spacecraft are discussed here in terms of the changing magnetic geometry implied by SMM coronagraph observations over the period 1985-1987. The pattern of recurrent solar wind streams, the long-term average speed, and the sector polarity of the interplanetary magnetic field all changed in a manner suggesting both a temporal variation, and a changing dependence on heliographic latitude. Coronal observations during this epoch show a systematic variation in coronal structure and the magnetic structure imposed on the expanding solar wind. These observations suggest interpretation of the solar wind speed variations in terms of the familiar model where the speed increases with distance from a nearly flat interplanetary current sheet, and where this current sheet becomes aligned with the solar equatorial plane as sunspot minimum approaches, but deviates rapidly from that orientation after minimum.

Topology optimization of hyperelastic structures using a level set method

NASA Astrophysics Data System (ADS)

Chen, Feifei; Wang, Yiqiang; Wang, Michael Yu; Zhang, Y. F.

2017-12-01

Soft rubberlike materials, due to their inherent compliance, are finding widespread implementation in a variety of applications ranging from assistive wearable technologies to soft material robots. Structural design of such soft and rubbery materials necessitates the consideration of large nonlinear deformations and hyperelastic material models to accurately predict their mechanical behaviour. In this paper, we present an effective level set-based topology optimization method for the design of hyperelastic structures that undergo large deformations. The method incorporates both geometric and material nonlinearities where the strain and stress measures are defined within the total Lagrange framework and the hyperelasticity is characterized by the widely-adopted Mooney-Rivlin material model. A shape sensitivity analysis is carried out, in the strict sense of the material derivative, where the high-order terms involving the displacement gradient are retained to ensure the descent direction. As the design velocity enters into the shape derivative in terms of its gradient and divergence terms, we develop a discrete velocity selection strategy. The whole optimization implementation undergoes a two-step process, where the linear optimization is first performed and its optimized solution serves as the initial design for the subsequent nonlinear optimization. It turns out that this operation could efficiently alleviate the numerical instability and facilitate the optimization process. To demonstrate the validity and effectiveness of the proposed method, three compliance minimization problems are studied and their optimized solutions present significant mechanical benefits of incorporating the nonlinearities, in terms of remarkable enhancement in not only the structural stiffness but also the critical buckling load.

Biologically Plausible, Human-Scale Knowledge Representation.

PubMed

Crawford, Eric; Gingerich, Matthew; Eliasmith, Chris

2016-05-01

Several approaches to implementing symbol-like representations in neurally plausible models have been proposed. These approaches include binding through synchrony (Shastri & Ajjanagadde, ), "mesh" binding (van der Velde & de Kamps, ), and conjunctive binding (Smolensky, ). Recent theoretical work has suggested that most of these methods will not scale well, that is, that they cannot encode structured representations using any of the tens of thousands of terms in the adult lexicon without making implausible resource assumptions. Here, we empirically demonstrate that the biologically plausible structured representations employed in the Semantic Pointer Architecture (SPA) approach to modeling cognition (Eliasmith, ) do scale appropriately. Specifically, we construct a spiking neural network of about 2.5 million neurons that employs semantic pointers to successfully encode and decode the main lexical relations in WordNet, which has over 100,000 terms. In addition, we show that the same representations can be employed to construct recursively structured sentences consisting of arbitrary WordNet concepts, while preserving the original lexical structure. We argue that these results suggest that semantic pointers are uniquely well-suited to providing a biologically plausible account of the structured representations that underwrite human cognition. Copyright © 2015 Cognitive Science Society, Inc.

U.S. Patent Pending, Cyberspace Security System for Complex Systems, U.S. Patent Application No.: 14/134,949

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

Abercrombie, Robert K; Sheldon, Frederick T; Mili, Ali

A computer implemented method monetizes the security of a cyber-system in terms of losses each stakeholder may expect to lose if a security break down occurs. A non-transitory media stores instructions for generating a stake structure that includes costs that each stakeholder of a system would lose if the system failed to meet security requirements and generating a requirement structure that includes probabilities of failing requirements when computer components fails. The system generates a vulnerability model that includes probabilities of a component failing given threats materializing and generates a perpetrator model that includes probabilities of threats materializing. The system generatesmore » a dot product of the stakes structure, the requirement structure, the vulnerability model and the perpetrator model. The system can further be used to compare, contrast and evaluate alternative courses of actions best suited for the stakeholders and their requirements.« less

Blind source separation based on time-frequency morphological characteristics for rigid acoustic scattering by underwater objects

NASA Astrophysics Data System (ADS)

Yang, Yang; Li, Xiukun

2016-06-01

Separation of the components of rigid acoustic scattering by underwater objects is essential in obtaining the structural characteristics of such objects. To overcome the problem of rigid structures appearing to have the same spectral structure in the time domain, time-frequency Blind Source Separation (BSS) can be used in combination with image morphology to separate the rigid scattering components of different objects. Based on a highlight model, the separation of the rigid scattering structure of objects with time-frequency distribution is deduced. Using a morphological filter, different characteristics in a Wigner-Ville Distribution (WVD) observed for single auto term and cross terms can be simplified to remove any cross-term interference. By selecting time and frequency points of the auto terms signal, the accuracy of BSS can be improved. An experimental simulation has been used, with changes in the pulse width of the transmitted signal, the relative amplitude and the time delay parameter, in order to analyzing the feasibility of this new method. Simulation results show that the new method is not only able to separate rigid scattering components, but can also separate the components when elastic scattering and rigid scattering exist at the same time. Experimental results confirm that the new method can be used in separating the rigid scattering structure of underwater objects.

The accuracy of matrix population model projections for coniferous trees in the Sierra Nevada, California

USGS Publications Warehouse

van Mantgem, P.J.; Stephenson, N.L.

2005-01-01

1 We assess the use of simple, size-based matrix population models for projecting population trends for six coniferous tree species in the Sierra Nevada, California. We used demographic data from 16 673 trees in 15 permanent plots to create 17 separate time-invariant, density-independent population projection models, and determined differences between trends projected from initial surveys with a 5-year interval and observed data during two subsequent 5-year time steps. 2 We detected departures from the assumptions of the matrix modelling approach in terms of strong growth autocorrelations. We also found evidence of observation errors for measurements of tree growth and, to a more limited degree, recruitment. Loglinear analysis provided evidence of significant temporal variation in demographic rates for only two of the 17 populations. 3 Total population sizes were strongly predicted by model projections, although population dynamics were dominated by carryover from the previous 5-year time step (i.e. there were few cases of recruitment or death). Fractional changes to overall population sizes were less well predicted. Compared with a null model and a simple demographic model lacking size structure, matrix model projections were better able to predict total population sizes, although the differences were not statistically significant. Matrix model projections were also able to predict short-term rates of survival, growth and recruitment. Mortality frequencies were not well predicted. 4 Our results suggest that simple size-structured models can accurately project future short-term changes for some tree populations. However, not all populations were well predicted and these simple models would probably become more inaccurate over longer projection intervals. The predictive ability of these models would also be limited by disturbance or other events that destabilize demographic rates. ?? 2005 British Ecological Society.

A priori evaluation of the Pantano and Sarkar model in compressible homogeneous shear flows

NASA Astrophysics Data System (ADS)

Khlifi, Hechmi; Abdallah, J.; Aïcha, H.; Taïeb, L.

2011-01-01

In this study, a Reynolds stress closure, including the Pantano and Sarkar model of the mean part of the pressure-strain correlation is used for the computation of compressible homogeneous at high-speed shear flow. Several studies concerning the compressible homogeneous shear flow show that the changes of the turbulence structures are principally due to the structural compressibility effects which significantly affect the pressure field and then the pressure-strain correlation. Eventually, this term appears as the main term responsible for the changes in the magnitude of the Reynolds stress anisotropies. The structure of the gradient Mach number is similar to that of turbulence, therefore this parameter may be appropriate to study the changes in turbulence structures that arise from structural compressibility effects. Thus, the incompressible model of the pressure strain correlation and its corrected form by using the turbulent Mach turbulent only, fail to correctly evaluate the compressibility effects at high shear flow. An extension of the widely used incompressible Launder, Reece and Rodi model on compressible homogeneous shear flow is the major aim of the present work. From this extension, the standard coefficients C become a function of the extra compressibility parameters (the turbulent Mach number M and the gradient Mach number M) through the Pantano and Sarkar model. Application of the model on compressible homogeneous shear flow by considering various initial conditions shows reasonable agreement with the DNS results of Simone et al. and Sarkar. The observed trend of the dramatic increase in the normal Reynolds stress anisotropies, the significant decrease in the Reynolds shear stress anisotropy and the increase of the turbulent kinetic energy amplification rate with increasing the gradient Mach number are well predicted by the model. The ability of the model to predict the equilibrium states for the flow in cases A to A from DNS results of Sarkar is examined, the results appear to be very encouraging. Thus, both parameters M and M should be used to model significant structural compressibility effects at high-speed shear flow.

Statistical Power of Alternative Structural Models for Comparative Effectiveness Research: Advantages of Modeling Unreliability.

PubMed

Coman, Emil N; Iordache, Eugen; Dierker, Lisa; Fifield, Judith; Schensul, Jean J; Suggs, Suzanne; Barbour, Russell

2014-05-01

The advantages of modeling the unreliability of outcomes when evaluating the comparative effectiveness of health interventions is illustrated. Adding an action-research intervention component to a regular summer job program for youth was expected to help in preventing risk behaviors. A series of simple two-group alternative structural equation models are compared to test the effect of the intervention on one key attitudinal outcome in terms of model fit and statistical power with Monte Carlo simulations. Some models presuming parameters equal across the intervention and comparison groups were underpowered to detect the intervention effect, yet modeling the unreliability of the outcome measure increased their statistical power and helped in the detection of the hypothesized effect. Comparative Effectiveness Research (CER) could benefit from flexible multi-group alternative structural models organized in decision trees, and modeling unreliability of measures can be of tremendous help for both the fit of statistical models to the data and their statistical power.

Understanding molecular structure from molecular mechanics.

PubMed

Allinger, Norman L

2011-04-01

Molecular mechanics gives us a well known model of molecular structure. It is less widely recognized that valence bond theory gives us structures which offer a direct interpretation of molecular mechanics formulations and parameters. The electronic effects well-known in physical organic chemistry can be directly interpreted in terms of valence bond structures, and hence quantitatively calculated and understood. The basic theory is outlined in this paper, and examples of the effects, and their interpretation in illustrative examples is presented.

Semantic similarity-based alignment between clinical archetypes and SNOMED CT: an application to observations.

PubMed

Meizoso García, María; Iglesias Allones, José Luis; Martínez Hernández, Diego; Taboada Iglesias, María Jesús

2012-08-01

One of the main challenges of eHealth is semantic interoperability of health systems. But, this will only be possible if the capture, representation and access of patient data is standardized. Clinical data models, such as OpenEHR Archetypes, define data structures that are agreed by experts to ensure the accuracy of health information. In addition, they provide an option to normalize clinical data by means of binding terms used in the model definition to standard medical vocabularies. Nevertheless, the effort needed to establish the association between archetype terms and standard terminology concepts is considerable. Therefore, the purpose of this study is to provide an automated approach to bind OpenEHR archetypes terms to the external terminology SNOMED CT, with the capability to do it at a semantic level. This research uses lexical techniques and external terminological tools in combination with context-based techniques, which use information about structural and semantic proximity to identify similarities between terms and so, to find alignments between them. The proposed approach exploits both the structural context of archetypes and the terminology context, in which concepts are logically defined through the relationships (hierarchical and definitional) to other concepts. A set of 25 OBSERVATION archetypes with 477 bound terms was used to test the method. Of these, 342 terms (74.6%) were linked with 96.1% precision, 71.7% recall and 1.23 SNOMED CT concepts on average for each mapping. It has been detected that about one third of the archetype clinical information is grouped logically. Context-based techniques take advantage of this to increase the recall and to validate a 30.4% of the bindings produced by lexical techniques. This research shows that it is possible to automatically map archetype terms to a standard terminology with a high precision and recall, with the help of appropriate contextual and semantic information of both models. Moreover, the semantic-based methods provide a means of validating and disambiguating the resulting bindings. Therefore, this work is a step forward to reduce the human participation in the mapping process. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Land Conversion in Amazonia and Northern South America; Influences on Regional Hydrology and Ecosystem Response

NASA Astrophysics Data System (ADS)

Knox, Ryan Gary

A numerical model of the terrestrial biosphere (Ecosystem Demography Model) is compbined with an atmospheric model (Brazilian Regional Atmospheric Modeling System) to investigate how land conversion in the Amazon and Northern South America have changed the hydrology of the region, and to see if those changes are significant enough to produce an ecological response. Two numerical realizations of the structure and composition of terrestrial vegetation are used as boundary conditions in a simulation of the regional land surface and atmosphere. One realization seeks to capture the present day vegetation condition that includes human deforestation and land-conversion, the other is an estimate of the potential structure and composition of the region without human influence. Model output is assessed for consistent and significant differences in hydrometeorology. Locations that show compelling differences are taken as case studies. The seasonal biases in precipitation at these locations are then used to create perturbations to long-term climate datasets. These perturbations then drive long-term simulations of dynamic vegetation to see if the climate consistent with a potential regional vegetation could elicit a change in the vegetation equilibrium at the site. Results show that South American land conversion has had consistent impacts on the regional patterning of precipitation. At some locations, changes in precipitation are persistent and constitute a significant fraction of total precipitation. Land-conversion has decreased mean continental evaporation and increased mean moisture convergence. Case study simulations of long term vegetation dynamic indicate that a hydrologic climate consistent with regional potential vegetation can indeed have significant influence on ecosystem structure and composition, particularly in water limited growth conditions. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs@mit.edu)

Relationships between nonlinear normal modes and response to random inputs

DOE PAGES

Schoneman, Joseph D.; Allen, Matthew S.; Kuether, Robert J.

2016-07-25

The ability to model nonlinear structures subject to random excitation is of key importance in designing hypersonic aircraft and other advanced aerospace vehicles. When a structure is linear, superposition can be used to construct its response to a known spectrum in terms of its linear modes. Superposition does not hold for a nonlinear system, but several works have shown that a system's dynamics can still be understood qualitatively in terms of its nonlinear normal modes (NNMs). Here, this work investigates the connection between a structure's undamped nonlinear normal modes and the spectrum of its response to high amplitude random forcing.more » Two examples are investigated: a spring-mass system and a clamped-clamped beam modeled within a geometrically nonlinear finite element package. In both cases, an intimate connection is observed between the smeared peaks in the response spectrum and the frequency-energy dependence of the nonlinear normal modes. In order to understand the role of coupling between the underlying linear modes, reduced order models with and without modal coupling terms are used to separate the effect of each NNM's backbone from the nonlinear couplings that give rise to internal resonances. In the cases shown here, uncoupled, single-degree-of-freedom nonlinear models are found to predict major features in the response with reasonable accuracy; a highly inexpensive approximation such as this could be useful in design and optimization studies. More importantly, the results show that a reduced order model can be expected to give accurate results only if it is also capable of accurately predicting the frequency-energy dependence of the nonlinear modes that are excited.« less

Unifying error structures in commonly used biotracer mixing models.

PubMed

Stock, Brian C; Semmens, Brice X

2016-10-01

Mixing models are statistical tools that use biotracers to probabilistically estimate the contribution of multiple sources to a mixture. These biotracers may include contaminants, fatty acids, or stable isotopes, the latter of which are widely used in trophic ecology to estimate the mixed diet of consumers. Bayesian implementations of mixing models using stable isotopes (e.g., MixSIR, SIAR) are regularly used by ecologists for this purpose, but basic questions remain about when each is most appropriate. In this study, we describe the structural differences between common mixing model error formulations in terms of their assumptions about the predation process. We then introduce a new parameterization that unifies these mixing model error structures, as well as implicitly estimates the rate at which consumers sample from source populations (i.e., consumption rate). Using simulations and previously published mixing model datasets, we demonstrate that the new error parameterization outperforms existing models and provides an estimate of consumption. Our results suggest that the error structure introduced here will improve future mixing model estimates of animal diet. © 2016 by the Ecological Society of America.

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system structural components

NASA Technical Reports Server (NTRS)

Cruse, T. A.

1987-01-01

The objective is the development of several modular structural analysis packages capable of predicting the probabilistic response distribution for key structural variables such as maximum stress, natural frequencies, transient response, etc. The structural analysis packages are to include stochastic modeling of loads, material properties, geometry (tolerances), and boundary conditions. The solution is to be in terms of the cumulative probability of exceedance distribution (CDF) and confidence bounds. Two methods of probability modeling are to be included as well as three types of structural models - probabilistic finite-element method (PFEM); probabilistic approximate analysis methods (PAAM); and probabilistic boundary element methods (PBEM). The purpose in doing probabilistic structural analysis is to provide the designer with a more realistic ability to assess the importance of uncertainty in the response of a high performance structure. Probabilistic Structural Analysis Method (PSAM) tools will estimate structural safety and reliability, while providing the engineer with information on the confidence that should be given to the predicted behavior. Perhaps most critically, the PSAM results will directly provide information on the sensitivity of the design response to those variables which are seen to be uncertain.

Probabilistic Structural Analysis Methods for select space propulsion system structural components (PSAM)

NASA Technical Reports Server (NTRS)

Cruse, T. A.; Burnside, O. H.; Wu, Y.-T.; Polch, E. Z.; Dias, J. B.

1988-01-01

The objective is the development of several modular structural analysis packages capable of predicting the probabilistic response distribution for key structural variables such as maximum stress, natural frequencies, transient response, etc. The structural analysis packages are to include stochastic modeling of loads, material properties, geometry (tolerances), and boundary conditions. The solution is to be in terms of the cumulative probability of exceedance distribution (CDF) and confidence bounds. Two methods of probability modeling are to be included as well as three types of structural models - probabilistic finite-element method (PFEM); probabilistic approximate analysis methods (PAAM); and probabilistic boundary element methods (PBEM). The purpose in doing probabilistic structural analysis is to provide the designer with a more realistic ability to assess the importance of uncertainty in the response of a high performance structure. Probabilistic Structural Analysis Method (PSAM) tools will estimate structural safety and reliability, while providing the engineer with information on the confidence that should be given to the predicted behavior. Perhaps most critically, the PSAM results will directly provide information on the sensitivity of the design response to those variables which are seen to be uncertain.

Statistical analysis of modal properties of a cable-stayed bridge through long-term structural health monitoring with wireless smart sensor networks

NASA Astrophysics Data System (ADS)

Asadollahi, Parisa; Li, Jian

2016-04-01

Understanding the dynamic behavior of complex structures such as long-span bridges requires dense deployment of sensors. Traditional wired sensor systems are generally expensive and time-consuming to install due to cabling. With wireless communication and on-board computation capabilities, wireless smart sensor networks have the advantages of being low cost, easy to deploy and maintain and therefore facilitate dense instrumentation for structural health monitoring. A long-term monitoring project was recently carried out for a cable-stayed bridge in South Korea with a dense array of 113 smart sensors, which feature the world's largest wireless smart sensor network for civil structural monitoring. This paper presents a comprehensive statistical analysis of the modal properties including natural frequencies, damping ratios and mode shapes of the monitored cable-stayed bridge. Data analyzed in this paper is composed of structural vibration signals monitored during a 12-month period under ambient excitations. The correlation between environmental temperature and the modal frequencies is also investigated. The results showed the long-term statistical structural behavior of the bridge, which serves as the basis for Bayesian statistical updating for the numerical model.

Biomedical word sense disambiguation with ontologies and metadata: automation meets accuracy

PubMed Central

Alexopoulou, Dimitra; Andreopoulos, Bill; Dietze, Heiko; Doms, Andreas; Gandon, Fabien; Hakenberg, Jörg; Khelif, Khaled; Schroeder, Michael; Wächter, Thomas

2009-01-01

Background Ontology term labels can be ambiguous and have multiple senses. While this is no problem for human annotators, it is a challenge to automated methods, which identify ontology terms in text. Classical approaches to word sense disambiguation use co-occurring words or terms. However, most treat ontologies as simple terminologies, without making use of the ontology structure or the semantic similarity between terms. Another useful source of information for disambiguation are metadata. Here, we systematically compare three approaches to word sense disambiguation, which use ontologies and metadata, respectively. Results The 'Closest Sense' method assumes that the ontology defines multiple senses of the term. It computes the shortest path of co-occurring terms in the document to one of these senses. The 'Term Cooc' method defines a log-odds ratio for co-occurring terms including co-occurrences inferred from the ontology structure. The 'MetaData' approach trains a classifier on metadata. It does not require any ontology, but requires training data, which the other methods do not. To evaluate these approaches we defined a manually curated training corpus of 2600 documents for seven ambiguous terms from the Gene Ontology and MeSH. All approaches over all conditions achieve 80% success rate on average. The 'MetaData' approach performed best with 96%, when trained on high-quality data. Its performance deteriorates as quality of the training data decreases. The 'Term Cooc' approach performs better on Gene Ontology (92% success) than on MeSH (73% success) as MeSH is not a strict is-a/part-of, but rather a loose is-related-to hierarchy. The 'Closest Sense' approach achieves on average 80% success rate. Conclusion Metadata is valuable for disambiguation, but requires high quality training data. Closest Sense requires no training, but a large, consistently modelled ontology, which are two opposing conditions. Term Cooc achieves greater 90% success given a consistently modelled ontology. Overall, the results show that well structured ontologies can play a very important role to improve disambiguation. Availability The three benchmark datasets created for the purpose of disambiguation are available in Additional file 1. PMID:19159460

On the formulation of a minimal uncertainty model for robust control with structured uncertainty

NASA Technical Reports Server (NTRS)

Belcastro, Christine M.; Chang, B.-C.; Fischl, Robert

1991-01-01

In the design and analysis of robust control systems for uncertain plants, representing the system transfer matrix in the form of what has come to be termed an M-delta model has become widely accepted and applied in the robust control literature. The M represents a transfer function matrix M(s) of the nominal closed loop system, and the delta represents an uncertainty matrix acting on M(s). The nominal closed loop system M(s) results from closing the feedback control system, K(s), around a nominal plant interconnection structure P(s). The uncertainty can arise from various sources, such as structured uncertainty from parameter variations or multiple unsaturated uncertainties from unmodeled dynamics and other neglected phenomena. In general, delta is a block diagonal matrix, but for real parameter variations delta is a diagonal matrix of real elements. Conceptually, the M-delta structure can always be formed for any linear interconnection of inputs, outputs, transfer functions, parameter variations, and perturbations. However, very little of the currently available literature addresses computational methods for obtaining this structure, and none of this literature addresses a general methodology for obtaining a minimal M-delta model for a wide class of uncertainty, where the term minimal refers to the dimension of the delta matrix. Since having a minimally dimensioned delta matrix would improve the efficiency of structured singular value (or multivariable stability margin) computations, a method of obtaining a minimal M-delta would be useful. Hence, a method of obtaining the interconnection system P(s) is required. A generalized procedure for obtaining a minimal P-delta structure for systems with real parameter variations is presented. Using this model, the minimal M-delta model can then be easily obtained by closing the feedback loop. The procedure involves representing the system in a cascade-form state-space realization, determining the minimal uncertainty matrix, delta, and constructing the state-space representation of P(s). Three examples are presented to illustrate the procedure.

Some Instructional Implications from a Mathematical Model of Cognitive Development.

ERIC Educational Resources Information Center

Mierkiewicz, Diane B.

Cognitive development and various educational implications are discussed in terms of Donald Saari's model of the interaction of a learner and the enviroment and the constraints imposed by the inefficiency of the learner's cognitive system. Saari proposed a hierarchical system of cognitive structures such that the relationships between structures…

Challenging Cognitive Construals: A Dynamic Alternative to Stable Misconceptions

ERIC Educational Resources Information Center

Gouvea, Julia S.; Simon, Matt R.

2018-01-01

In biology education research, it has been common to model cognition in terms of relatively stable knowledge structures (e.g., mental models, alternative frameworks, deeply held misconceptions). For example, John D. Coley and Kimberley D. Tanner recently proposed that many student difficulties in biology stem from underlying cognitive frameworks…

Bayesian source term determination with unknown covariance of measurements

NASA Astrophysics Data System (ADS)

Belal, Alkomiet; Tichý, Ondřej; Šmídl, Václav

2017-04-01

Determination of a source term of release of a hazardous material into the atmosphere is a very important task for emergency response. We are concerned with the problem of estimation of the source term in the conventional linear inverse problem, y = Mx, where the relationship between the vector of observations y is described using the source-receptor-sensitivity (SRS) matrix M and the unknown source term x. Since the system is typically ill-conditioned, the problem is recast as an optimization problem minR,B(y - Mx)TR-1(y - Mx) + xTB-1x. The first term minimizes the error of the measurements with covariance matrix R, and the second term is a regularization of the source term. There are different types of regularization arising for different choices of matrices R and B, for example, Tikhonov regularization assumes covariance matrix B as the identity matrix multiplied by scalar parameter. In this contribution, we adopt a Bayesian approach to make inference on the unknown source term x as well as unknown R and B. We assume prior on x to be a Gaussian with zero mean and unknown diagonal covariance matrix B. The covariance matrix of the likelihood R is also unknown. We consider two potential choices of the structure of the matrix R. First is the diagonal matrix and the second is a locally correlated structure using information on topology of the measuring network. Since the inference of the model is intractable, iterative variational Bayes algorithm is used for simultaneous estimation of all model parameters. The practical usefulness of our contribution is demonstrated on an application of the resulting algorithm to real data from the European Tracer Experiment (ETEX). This research is supported by EEA/Norwegian Financial Mechanism under project MSMT-28477/2014 Source-Term Determination of Radionuclide Releases by Inverse Atmospheric Dispersion Modelling (STRADI).

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

Effects of structural complexity enhancement on eastern red-backed salamander (Plethodon cinereus) populations in northern hardwood forests

USGS Publications Warehouse

McKenny, H.C.; Keeton, W.S.; Donovan, T.M.

2006-01-01

Managing for stand structural complexity in northern hardwood forests has been proposed as a method for promoting microhabitat characteristics important to eastern red-backed salamanders (Plethodon cinereus). We evaluated the effects of alternate, structure-based silvicultural systems on red-backed salamander populations at two research sites in northwestern Vermont. Treatments included two uneven-aged approaches (single-tree selection and group-selection) and one unconventional approach, termed "structural complexity enhancement" (SCE), that promotes development of late-successional structure, including elevated levels of coarse woody debris (CWD). Treatments were applied to 2 ha units and were replicated two to four times depending on treatment. We surveyed red-backed salamanders with a natural cover search method of transects nested within vegetation plots 1 year after logging. Abundance estimates corrected for detection probability were calculated from survey data with a binomial mixture model. Abundance estimates differed between study areas and were influenced by forest structural characteristics. Model selection was conducted using Akaike Information Criteria, corrected for over-dispersed data and small sample size (QAICc). We found no difference in abundance as a response to treatment as a whole, suggesting that all of the uneven-aged silvicultural systems evaluated can maintain salamander populations after harvest. However, abundance was tied to specific structural habitat attributes associated with study plots within treatments. The most parsimonious model of habitat covariates included site, relative density of overstory trees, and density of more-decayed and less-decayed downed CWD. Abundance responded positively to the density of downed, well-decayed CWD and negatively to the density of poorly decayed CWD and to overstory relative density. CWD volume was not a strong predictor of salamander abundance. We conclude that structural complexity enhancement and the two uneven-aged approaches maintained important microhabitat characteristics for red-backed salamander populations in the short term. Over the long-term, given decay processes as a determinant of biological availability, forestry practices such as SCE that enhance CWD availability and recruitment may result in associated population responses. ?? 2006 Elsevier B.V. All rights reserved.

Formulation d'un modele mathematique par des techniques d'estimation de parametres a partir de donnees de vol pour l'helicoptere Bell 427 et l'avion F/A-18 servant a la recherches en aeroservoelasticite

NASA Astrophysics Data System (ADS)

Nadeau-Beaulieu, Michel

In this thesis, three mathematical models are built from flight test data for different aircraft design applications: a ground dynamics model for the Bell 427 helicopter, a prediction model for the rotor and engine parameters for the same helicopter type and a simulation model for the aeroelastic deflections of the F/A-18. In the ground dynamics application, the model structure is derived from physics where the normal force between the helicopter and the ground is modelled as a vertical spring and the frictional force is modelled with static and dynamic friction coefficients. The ground dynamics model coefficients are optimized to ensure that the model matches the landing data within the FAA (Federal Aviation Administration) tolerance bands for a level D flight simulator. In the rotor and engine application, rotors torques (main and tail), the engine torque and main rotor speed are estimated using a state-space model. The model inputs are nonlinear terms derived from the pilot control inputs and the helicopter states. The model parameters are identified using the subspace method and are further optimised with the Levenberg-Marquardt minimisation algorithm. The model built with the subspace method provides an excellent estimate of the outputs within the FAA tolerance bands. The F/A-18 aeroelastic state-space model is built from flight test. The research concerning this model is divided in two parts. Firstly, the deflection of a given structural surface on the aircraft following a differential ailerons control input is represented by a Multiple Inputs Single Outputs linear model whose inputs are the ailerons positions and the structural surfaces deflections. Secondly, a single state-space model is used to represent the deflection of the aircraft wings and trailing edge flaps following any control input. In this case the model is made non-linear by multiplying model inputs into higher order terms and using these terms as the inputs of the state-space equations. In both cases, the identification method is the subspace method. Most fit coefficients between the estimated and the measured signals are above 73% and most correlation coefficient are higher than 90%.

Metastable structures and size effects in small group dynamics

PubMed Central

Lauro Grotto, Rosapia; Guazzini, Andrea; Bagnoli, Franco

2014-01-01

In his seminal works on group dynamics Bion defined a specific therapeutic setting allowing psychoanalytic observations on group phenomena. In describing the setting he proposed that the group was where his voice arrived. This physical limit was later made operative by assuming that the natural dimension of a therapeutic group is around 12 people. Bion introduced a theory of the group aspects of the mind in which proto-mental individual states spontaneously evolve into shared psychological states that are characterized by a series of features: (1) they emerge as a consequence of the natural tendency of (both conscious and unconscious) emotions to combine into structured group patterns; (2) they have a certain degree of stability in time; (3) they tend to alternate so that the dissolution of one is rapidly followed by the emergence of another; (4) they can be described in qualitative terms according to the nature of the emotional mix that dominates the state, in structural terms by a kind of typical “leadership” pattern, and in “cognitive” terms by a set of implicit expectations that are helpful in explaining the group behavior (i.e., the group behaves “as if” it was assuming that). Here we adopt a formal approach derived from Socio-physics in order to explore some of the structural and dynamic properties of this small group dynamics. We will described data from an analytic DS model simulating small group interactions of agents endowed with a very simplified emotional and cognitive dynamic in order to assess the following main points: (1) are metastable collective states allowed to emerge in the model and if so, under which conditions in the parameter space? (2) can these states be differentiated in structural terms? (3) to what extent are the emergent dynamic features of the systems dependent of the system size? We will finally discuss possible future applications of the quantitative descriptions of the interaction structure in the small group clinical setting. PMID:25071665

Macroscopic damping model for structural dynamics with random polycrystalline configurations

NASA Astrophysics Data System (ADS)

Yang, Yantao; Cui, Junzhi; Yu, Yifan; Xiang, Meizhen

2018-06-01

In this paper the macroscopic damping model for dynamical behavior of the structures with random polycrystalline configurations at micro-nano scales is established. First, the global motion equation of a crystal is decomposed into a set of motion equations with independent single degree of freedom (SDOF) along normal discrete modes, and then damping behavior is introduced into each SDOF motion. Through the interpolation of discrete modes, the continuous representation of damping effects for the crystal is obtained. Second, from energy conservation law the expression of the damping coefficient is derived, and the approximate formula of damping coefficient is given. Next, the continuous damping coefficient for polycrystalline cluster is expressed, the continuous dynamical equation with damping term is obtained, and then the concrete damping coefficients for a polycrystalline Cu sample are shown. Finally, by using statistical two-scale homogenization method, the macroscopic homogenized dynamical equation containing damping term for the structures with random polycrystalline configurations at micro-nano scales is set up.

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.

A comparative study of theoretical graph models for characterizing structural networks of human brain.

PubMed

Li, Xiaojin; Hu, Xintao; Jin, Changfeng; Han, Junwei; Liu, Tianming; Guo, Lei; Hao, Wei; Li, Lingjiang

2013-01-01

Previous studies have investigated both structural and functional brain networks via graph-theoretical methods. However, there is an important issue that has not been adequately discussed before: what is the optimal theoretical graph model for describing the structural networks of human brain? In this paper, we perform a comparative study to address this problem. Firstly, large-scale cortical regions of interest (ROIs) are localized by recently developed and validated brain reference system named Dense Individualized Common Connectivity-based Cortical Landmarks (DICCCOL) to address the limitations in the identification of the brain network ROIs in previous studies. Then, we construct structural brain networks based on diffusion tensor imaging (DTI) data. Afterwards, the global and local graph properties of the constructed structural brain networks are measured using the state-of-the-art graph analysis algorithms and tools and are further compared with seven popular theoretical graph models. In addition, we compare the topological properties between two graph models, namely, stickiness-index-based model (STICKY) and scale-free gene duplication model (SF-GD), that have higher similarity with the real structural brain networks in terms of global and local graph properties. Our experimental results suggest that among the seven theoretical graph models compared in this study, STICKY and SF-GD models have better performances in characterizing the structural human brain network.

Application of Markov chain Monte Carlo analysis to biomathematical modeling of respirable dust in US and UK coal miners

PubMed Central

Sweeney, Lisa M.; Parker, Ann; Haber, Lynne T.; Tran, C. Lang; Kuempel, Eileen D.

2015-01-01

A biomathematical model was previously developed to describe the long-term clearance and retention of particles in the lungs of coal miners. The model structure was evaluated and parameters were estimated in two data sets, one from the United States and one from the United Kingdom. The three-compartment model structure consists of deposition of inhaled particles in the alveolar region, competing processes of either clearance from the alveolar region or translocation to the lung interstitial region, and very slow, irreversible sequestration of interstitialized material in the lung-associated lymph nodes. Point estimates of model parameter values were estimated separately for the two data sets. In the current effort, Bayesian population analysis using Markov chain Monte Carlo simulation was used to recalibrate the model while improving assessments of parameter variability and uncertainty. When model parameters were calibrated simultaneously to the two data sets, agreement between the derived parameters for the two groups was very good, and the central tendency values were similar to those derived from the deterministic approach. These findings are relevant to the proposed update of the ICRP human respiratory tract model with revisions to the alveolar-interstitial region based on this long-term particle clearance and retention model. PMID:23454101

Development of a Localized Low-Dimensional Approach to Turbulence Simulation

NASA Astrophysics Data System (ADS)

Juttijudata, Vejapong; Rempfer, Dietmar; Lumley, John

2000-11-01

Our previous study has shown that the localized low-dimensional model derived from a projection of Navier-Stokes equations onto a set of one-dimensional scalar POD modes, with boundary conditions at y^+=40, can predict wall turbulence accurately for short times while failing to give a stable long-term solution. The structures obtained from the model and later studies suggest our boundary conditions from DNS are not consistent with the solution from the localized model resulting in an injection of energy at the top boundary. In the current study, we develop low-dimensional models using one-dimensional scalar POD modes derived from an explicitly filtered DNS. This model problem has exact no-slip boundary conditions at both walls while the locality of the wall layer is still retained. Furthermore, the interaction between wall and core region is attenuated via an explicit filter which allows us to investigate the quality of the model without requiring complicated modeling of the top boundary conditions. The full-channel model gives reasonable wall turbulence structures as well as long-term turbulent statistics while still having difficulty with the prediction of the mean velocity profile farther from the wall. We also consider a localized model with modified boundary conditions in the last part of our study.

Simplified rotor load models and fatigue damage estimates for offshore wind turbines.

PubMed

Muskulus, M

2015-02-28

The aim of rotor load models is to characterize and generate the thrust loads acting on an offshore wind turbine. Ideally, the rotor simulation can be replaced by time series from a model with a few parameters and state variables only. Such models are used extensively in control system design and, as a potentially new application area, structural optimization of support structures. Different rotor load models are here evaluated for a jacket support structure in terms of fatigue lifetimes of relevant structural variables. All models were found to be lacking in accuracy, with differences of more than 20% in fatigue load estimates. The most accurate models were the use of an effective thrust coefficient determined from a regression analysis of dynamic thrust loads, and a novel stochastic model in state-space form. The stochastic model explicitly models the quasi-periodic components obtained from rotational sampling of turbulent fluctuations. Its state variables follow a mean-reverting Ornstein-Uhlenbeck process. Although promising, more work is needed on how to determine the parameters of the stochastic model and before accurate lifetime predictions can be obtained without comprehensive rotor simulations. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Sub- and super-luminar propagation of structures satisfying Poynting-like theorem for incompressible generalized hydrodynamic fluid model depicting strongly coupled dusty plasma medium

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

Dharodi, Vikram; Das, Amita, E-mail: amita@ipr.res.in; Patel, Bhavesh

2016-01-15

The strongly coupled dusty plasma has often been modelled by the Generalized Hydrodynamic (GHD) model used for representing visco-elastic fluid systems. The incompressible limit of the model which supports transverse shear wave mode is studied in detail. In particular, dipole structures are observed to emit transverse shear waves in both the limits of sub- and super-luminar propagation, where the structures move slower and faster than the phase velocity of the shear waves, respectively. In the sub-luminar limit the dipole gets engulfed within the shear waves emitted by itself, which then backreacts on it and ultimately the identity of the structuremore » is lost. However, in the super-luminar limit the emission appears like a wake from the tail region of the dipole. The dipole, however, keeps propagating forward with little damping but minimal distortion in its form. A Poynting-like conservation law with radiative, convective, and dissipative terms being responsible for the evolution of W, which is similar to “enstrophy” like quantity in normal hydrodynamic fluid systems, has also been constructed for the incompressible GHD equations. The conservation law is shown to be satisfied in all the cases of evolution and collision amidst the nonlinear structures to a great accuracy. It is shown that monopole structures which do not move at all but merely radiate shear waves, the radiative term, and dissipative losses solely contribute to the evolution of W. The dipolar structures, on the other hand, propagate in the medium and hence convection also plays an important role in the evolution of W.« less

Physician equity in health care delivery systems: three alternative models.

PubMed

Kennedy, K M; Wofford, D A

1998-01-01

The 1990s have seen many health care organizations attempting to merge, acquire, or affiliate with physician groups. Many have failed to provide physicians a stake in the success of the newly formed enterprise, frequently resulting in declining physician productivity, poor morale, and large operating losses. These problems warrant a reexamination of the traditional acquisition model of growth in favor of structures that retain a physician ownership component. This article examines three models of health care organization in which physicians share in the success of the enterprise and compares them in terms of ownership structure, governance, and funds flow.

Test Cases for Modeling and Validation of Structures with Piezoelectric Actuators

NASA Technical Reports Server (NTRS)

Reaves, Mercedes C.; Horta, Lucas G.

2001-01-01

A set of benchmark test articles were developed to validate techniques for modeling structures containing piezoelectric actuators using commercially available finite element analysis packages. The paper presents the development, modeling, and testing of two structures: an aluminum plate with surface mounted patch actuators and a composite box beam with surface mounted actuators. Three approaches for modeling structures containing piezoelectric actuators using the commercially available packages: MSC/NASTRAN and ANSYS are presented. The approaches, applications, and limitations are discussed. Data for both test articles are compared in terms of frequency response functions from deflection and strain data to input voltage to the actuator. Frequency response function results using the three different analysis approaches provided comparable test/analysis results. It is shown that global versus local behavior of the analytical model and test article must be considered when comparing different approaches. Also, improper bonding of actuators greatly reduces the electrical to mechanical effectiveness of the actuators producing anti-resonance errors.

The Examining Reading Motivation of Primary Students in the Terms of Some Variables

ERIC Educational Resources Information Center

Biyik, Merve Atas; Erdogan, Tolga; Yildiz, Mustafa

2017-01-01

The purpose of this research, is to examine reading motivation of the primary 2, 3 and 4th grade students in the terms of gender, class and socioeconomic status. Research is structured according to model of survey in the descriptive type. In the collection, analysis and interpretation of the data "mix method". The sample consists of…

Hearing Loss Is Negatively Related to Episodic and Semantic Long-Term Memory but Not to Short-Term Memory

ERIC Educational Resources Information Center

Ronnberg, Jerker; Danielsson, Henrik; Rudner, Mary; Arlinger, Stig; Sternang, Ola; Wahlin, Ake; Nilsson, Lars-Goran

2011-01-01

Purpose: To test the relationship between degree of hearing loss and different memory systems in hearing aid users. Method: Structural equation modeling (SEM) was used to study the relationship between auditory and visual acuity and different cognitive and memory functions in an age-hetereogenous subsample of 160 hearing aid users without…

Friction damping of two-dimensional motion and its application in vibration control

NASA Technical Reports Server (NTRS)

Menq, C.-H.; Chidamparam, P.; Griffin, J. H.

1991-01-01

This paper presents an approximate method for analyzing the two-dimensional friction contact problem so as to compute the dynamic response of a structure constrained by friction interfaces. The friction force at the joint is formulated based on the Coulomb model. The single-term harmonic balance scheme, together with the receptance approach of decoupling the effect of the friction force on the structure from those of the external forces has been utilized to obtain the steady state response. The computational efficiency and accuracy of the method are demonstrated by comparing the results with long-term time solutions.

Spatial and temporal changes in the structure of groundwater nitrate concentration time series (1935 1999) as demonstrated by autoregressive modelling

NASA Astrophysics Data System (ADS)

Jones, A. L.; Smart, P. L.

2005-08-01

Autoregressive modelling is used to investigate the internal structure of long-term (1935-1999) records of nitrate concentration for five karst springs in the Mendip Hills. There is a significant short term (1-2 months) positive autocorrelation at three of the five springs due to the availability of sufficient nitrate within the soil store to maintain concentrations in winter recharge for several months. The absence of short term (1-2 months) positive autocorrelation in the other two springs is due to the marked contrast in land use between the limestone and swallet parts of the catchment, rapid concentrated recharge from the latter causing short term switching in the dominant water source at the spring and thus fluctuating nitrate concentrations. Significant negative autocorrelation is evident at lags varying from 4 to 7 months through to 14-22 months for individual springs, with positive autocorrelation at 19-20 months at one site. This variable timing is explained by moderation of the exhaustion effect in the soil by groundwater storage, which gives longer residence times in large catchments and those with a dominance of diffuse flow. The lags derived from autoregressive modelling may therefore provide an indication of average groundwater residence times. Significant differences in the structure of the autocorrelation function for successive 10-year periods are evident at Cheddar Spring, and are explained by the effect the ploughing up of grasslands during the Second World War and increased fertiliser usage on available nitrogen in the soil store. This effect is moderated by the influence of summer temperatures on rates of mineralization, and of both summer and winter rainfall on the timing and magnitude of nitrate leaching. The pattern of nitrate leaching also appears to have been perturbed by the 1976 drought.

A revised econometric model of the domestic pallet market

Treesearch

Albert T. Schuler; Walter B. Wallin

1983-01-01

The purpose of this revised model is to project estimates of consumption and price of wooden pallets in the short term. This model differs from previous ones developed by Schuler and Wallin (1979 and 1980) in the following respects: The structure of the supply side of the market is more realistically identified (from an economic theory point of view) by including...

Mediating Mental Models of Metals: Acknowledging the Priority of the Learner's Prior Learning

ERIC Educational Resources Information Center

Taber, Keith S.

2003-01-01

This paper describes the conceptualizations, or mental models, of the nature of the bonding and structure of metals of a group of U.K. college students. It is suggested that these mental models may be understood in terms of the students' prior learning about covalent and ionic bonding, and the prevalence of a common alternative conceptual…

A Buffer Model of Memory Encoding and Temporal Correlations in Retrieval

ERIC Educational Resources Information Center

Lehman, Melissa; Malmberg, Kenneth J.

2013-01-01

Atkinson and Shiffrin's (1968) dual-store model of memory includes structural aspects of memory along with control processes. The rehearsal buffer is a process by which items are kept in mind and long-term episodic traces are formed. The model has been both influential and controversial. Here, we describe a novel variant of Atkinson and Shiffrin's…

Protein simulation using coarse-grained two-bead multipole force field with polarizable water models.

PubMed

Li, Min; Zhang, John Z H

2017-02-14

A recently developed two-bead multipole force field (TMFF) is employed in coarse-grained (CG) molecular dynamics (MD) simulation of proteins in combination with polarizable CG water models, the Martini polarizable water model, and modified big multipole water model. Significant improvement in simulated structures and dynamics of proteins is observed in terms of both the root-mean-square deviations (RMSDs) of the structures and residue root-mean-square fluctuations (RMSFs) from the native ones in the present simulation compared with the simulation result with Martini's non-polarizable water model. Our result shows that TMFF simulation using CG water models gives much stable secondary structures of proteins without the need for adding extra interaction potentials to constrain the secondary structures. Our result also shows that by increasing the MD time step from 2 fs to 6 fs, the RMSD and RMSF results are still in excellent agreement with those from all-atom simulations. The current study demonstrated clearly that the application of TMFF together with a polarizable CG water model significantly improves the accuracy and efficiency for CG simulation of proteins.

Protein simulation using coarse-grained two-bead multipole force field with polarizable water models

NASA Astrophysics Data System (ADS)

Li, Min; Zhang, John Z. H.

2017-02-01

A recently developed two-bead multipole force field (TMFF) is employed in coarse-grained (CG) molecular dynamics (MD) simulation of proteins in combination with polarizable CG water models, the Martini polarizable water model, and modified big multipole water model. Significant improvement in simulated structures and dynamics of proteins is observed in terms of both the root-mean-square deviations (RMSDs) of the structures and residue root-mean-square fluctuations (RMSFs) from the native ones in the present simulation compared with the simulation result with Martini's non-polarizable water model. Our result shows that TMFF simulation using CG water models gives much stable secondary structures of proteins without the need for adding extra interaction potentials to constrain the secondary structures. Our result also shows that by increasing the MD time step from 2 fs to 6 fs, the RMSD and RMSF results are still in excellent agreement with those from all-atom simulations. The current study demonstrated clearly that the application of TMFF together with a polarizable CG water model significantly improves the accuracy and efficiency for CG simulation of proteins.

Analytical framework for reconstructing heterogeneous environmental variables from mammal community structure.

PubMed

Louys, Julien; Meloro, Carlo; Elton, Sarah; Ditchfield, Peter; Bishop, Laura C

2015-01-01

We test the performance of two models that use mammalian communities to reconstruct multivariate palaeoenvironments. While both models exploit the correlation between mammal communities (defined in terms of functional groups) and arboreal heterogeneity, the first uses a multiple multivariate regression of community structure and arboreal heterogeneity, while the second uses a linear regression of the principal components of each ecospace. The success of these methods means the palaeoenvironment of a particular locality can be reconstructed in terms of the proportions of heavy, moderate, light, and absent tree canopy cover. The linear regression is less biased, and more precisely and accurately reconstructs heavy tree canopy cover than the multiple multivariate model. However, the multiple multivariate model performs better than the linear regression for all other canopy cover categories. Both models consistently perform better than randomly generated reconstructions. We apply both models to the palaeocommunity of the Upper Laetolil Beds, Tanzania. Our reconstructions indicate that there was very little heavy tree cover at this site (likely less than 10%), with the palaeo-landscape instead comprising a mixture of light and absent tree cover. These reconstructions help resolve the previous conflicting palaeoecological reconstructions made for this site. Copyright © 2014 Elsevier Ltd. All rights reserved.

Structure of hydrated gibbsite and brucite edge surfaces: DFT results and further development of the ClayFF classical force field with metal–O–H angle bending terms

DOE PAGES

Pouvreau, Maxime; Greathouse, Jeffery A.; Cygan, Randall T.; ...

2017-06-28

Molecular scale understanding of the structure and properties of aqueous interfaces with clays, metal (oxy-) hydroxides, layered double hydroxides, and other inorganic phases is strongly affected by significant degrees of structural and compositional disorder of the interfaces. ClayFF was originally developed as a robust and flexible force field for classical molecular simulations of such systems. However, despite its success, multiple limitations have also become evident with its use. One of the most important limitations is the difficulty to accurately model the edges of finite size nanoparticles or pores rather than infinitely layered periodic structures. Here we propose a systematic approachmore » to solve this problem by developing specific metal–O–H (M–O–H) bending terms for ClayFF, E bend = k (θ – θ 0) 2 to better describe the structure and dynamics of singly protonated hydroxyl groups at mineral surfaces, particularly edge surfaces. On the basis of a series of DFT calculations, the optimal values of the Al–O–H and Mg–O–H parameters for Al and Mg in octahedral coordination are determined to be θ 0,AlOH = θ 0,MgOH = 110°, k AlOH = 15 kcal mol –1 rad –2 and k MgOH = 6 kcal mol –1 rad –2. Molecular dynamics simulations were performed for fully hydrated models of the basal and edge surfaces of gibbsite, Al(OH) 3, and brucite, Mg(OH) 2, at the DFT level of theory and at the classical level, using ClayFF with and without the M–O–H term. The addition of the new bending term leads to a much more accurate representation of the orientation of O–H groups at the basal and edge surfaces. Finally, the previously observed unrealistic desorption of OH 2 groups from the particle edges within the original ClayFF model is also strongly constrained by the new modification.« less

Free energy force field (FEFF) 3D-QSAR analysis of a set of Plasmodium falciparum dihydrofolate reductase inhibitors

NASA Astrophysics Data System (ADS)

Santos-Filho, Osvaldo A.; Mishra, Rama K.; Hopfinger, A. J.

2001-09-01

Free energy force field (FEFF) 3D-QSAR analysis was used to construct ligand-receptor binding models for a set of 18 structurally diverse antifolates including pyrimethamine, cycloguanil, methotrexate, aminopterin and trimethoprim, and 13 pyrrolo[2,3-d]pyrimidines. The molecular target (`receptor') used was a 3D-homology model of a specific mutant type of Plasmodium falciparum (Pf) dihydrofolate reductase (DHFR). The dependent variable of the 3D-QSAR models is the IC50 inhibition constant for the specific mutant type of PfDHFR. The independent variables of the 3D-QSAR models (the descriptors) are scaled energy terms of a modified first-generation AMBER force field combined with a hydration shell aqueous solvation model and a collection of 2D-QSAR descriptors often used in QSAR studies. Multiple temperature molecular dynamics simulation (MDS) and the genetic function approximation (GFA) were employed using partial least square (PLS) and multidimensional linear regressions as the fitting functions to develop FEFF 3D-QSAR models for the binding process. The significant FEFF energy terms in the best 3D-QSAR models include energy contributions of the direct ligand-receptor interaction. Some changes in conformational energy terms of the ligand due to binding to the enzyme are also found to be important descriptors. The FEFF 3D-QSAR models indicate some structural features perhaps relevant to the mechanism of resistance of the PfDHFR to current antimalarials. The FEFF 3D-QSAR models are also compared to receptor-independent (RI) 4D-QSAR models developed in an earlier study and subsequently refined using recently developed generalized alignment rules.

Fault-tolerant continuous flow systems modelling

NASA Astrophysics Data System (ADS)

Tolbi, B.; Tebbikh, H.; Alla, H.

2017-01-01

This paper presents a structural modelling of faults with hybrid Petri nets (HPNs) for the analysis of a particular class of hybrid dynamic systems, continuous flow systems. HPNs are first used for the behavioural description of continuous flow systems without faults. Then, faults' modelling is considered using a structural method without having to rebuild the model to new. A translation method is given in hierarchical way, it gives a hybrid automata (HA) from an elementary HPN. This translation preserves the behavioural semantics (timed bisimilarity), and reflects the temporal behaviour by giving semantics for each model in terms of timed transition systems. Thus, advantages of the power modelling of HPNs and the analysis ability of HA are taken. A simple example is used to illustrate the ideas.

Dip and anisotropy effects on flow using a vertically skewed model grid.

PubMed

Hoaglund, John R; Pollard, David

2003-01-01

Darcy flow equations relating vertical and bedding-parallel flow to vertical and bedding-parallel gradient components are derived for a skewed Cartesian grid in a vertical plane, correcting for structural dip given the principal hydraulic conductivities in bedding-parallel and bedding-orthogonal directions. Incorrect-minus-correct flow error results are presented for ranges of structural dip (0 < or = theta < or = 90) and gradient directions (0 < or = phi < or = 360). The equations can be coded into ground water models (e.g., MODFLOW) that can use a skewed Cartesian coordinate system to simulate flow in structural terrain with deformed bedding planes. Models modified with these equations will require input arrays of strike and dip, and a solver that can handle off-diagonal hydraulic conductivity terms.

Modeling global vector fields of chaotic systems from noisy time series with the aid of structure-selection techniques.

PubMed

Xu, Daolin; Lu, Fangfang

2006-12-01

We address the problem of reconstructing a set of nonlinear differential equations from chaotic time series. A method that combines the implicit Adams integration and the structure-selection technique of an error reduction ratio is proposed for system identification and corresponding parameter estimation of the model. The structure-selection technique identifies the significant terms from a pool of candidates of functional basis and determines the optimal model through orthogonal characteristics on data. The technique with the Adams integration algorithm makes the reconstruction available to data sampled with large time intervals. Numerical experiment on Lorenz and Rossler systems shows that the proposed strategy is effective in global vector field reconstruction from noisy time series.

The SENSE-Isomorphism Theoretical Image Voxel Estimation (SENSE-ITIVE) Model for Reconstruction and Observing Statistical Properties of Reconstruction Operators

PubMed Central

Bruce, Iain P.; Karaman, M. Muge; Rowe, Daniel B.

2012-01-01

The acquisition of sub-sampled data from an array of receiver coils has become a common means of reducing data acquisition time in MRI. Of the various techniques used in parallel MRI, SENSitivity Encoding (SENSE) is one of the most common, making use of a complex-valued weighted least squares estimation to unfold the aliased images. It was recently shown in Bruce et al. [Magn. Reson. Imag. 29(2011):1267–1287] that when the SENSE model is represented in terms of a real-valued isomorphism, it assumes a skew-symmetric covariance between receiver coils, as well as an identity covariance structure between voxels. In this manuscript, we show that not only is the skew-symmetric coil covariance unlike that of real data, but the estimated covariance structure between voxels over a time series of experimental data is not an identity matrix. As such, a new model, entitled SENSE-ITIVE, is described with both revised coil and voxel covariance structures. Both the SENSE and SENSE-ITIVE models are represented in terms of real-valued isomorphisms, allowing for a statistical analysis of reconstructed voxel means, variances, and correlations resulting from the use of different coil and voxel covariance structures used in the reconstruction processes to be conducted. It is shown through both theoretical and experimental illustrations that the miss-specification of the coil and voxel covariance structures in the SENSE model results in a lower standard deviation in each voxel of the reconstructed images, and thus an artificial increase in SNR, compared to the standard deviation and SNR of the SENSE-ITIVE model where both the coil and voxel covariances are appropriately accounted for. It is also shown that there are differences in the correlations induced by the reconstruction operations of both models, and consequently there are differences in the correlations estimated throughout the course of reconstructed time series. These differences in correlations could result in meaningful differences in interpretation of results. PMID:22617147

A model of activity-dependent changes in dendritic spine density and spine structure.

PubMed

Crook, S M; Dur-E-Ahmad, M; Baer, S M

2007-10-01

Recent evidence indicates that the morphology and density of dendritic spines are regulated during synaptic plasticity. See, for instance, a review by Hayashi and Majewska [9]. In this work, we extend previous modeling studies [27] by combining a model for activity-dependent spine density with one for calcium-mediated spine stem restructuring. The model is based on the standard dimensionless cable equation, which represents the change in the membrane potential in a passive dendrite. Additional equations characterize the change in spine density along the dendrite, the current balance equation for an individual spine head, the change in calcium concentration in the spine head, and the dynamics of spine stem resistance. We use computational studies to investigate the changes in spine density and structure for differing synaptic inputs and demonstrate the effects of these changes on the input-output properties of the dendritic branch. Moderate amounts of high-frequency synaptic activation to dendritic spines result in an increase in spine stem resistance that is correlated with spine stem elongation. In addition, the spine density increases both inside and outside the input region. The model is formulated so that this long-term potentiation-inducing stimulus eventually leads to structural stability. In contrast, a prolonged low-frequency stimulation paradigm that would typically induce long-term depression results in a decrease in stem resistance (correlated with stem shortening) and an eventual decrease in spine density.

[A Methodological Quality Assessment of South Korean Nursing Research using Structural Equation Modeling in South Korea].

PubMed

Kim, Jung-Hee; Shin, Sujin; Park, Jin-Hwa

2015-04-01

The purpose of this study was to evaluate the methodological quality of nursing studies using structural equation modeling in Korea. Databases of KISS, DBPIA, and National Assembly Library up to March 2014 were searched using the MeSH terms 'nursing', 'structure', 'model'. A total of 152 studies were screened. After removal of duplicates and non-relevant titles, 61 papers were read in full. Of the sixty-one articles retrieved, 14 studies were published between 1992 and 2000, 27, between 2001 and 2010, and 20, between 2011 and March 2014. The methodological quality of the review examined varied considerably. The findings of this study suggest that more rigorous research is necessary to address theoretical identification, two indicator rule, distribution of sample, treatment of missing values, mediator effect, discriminant validity, convergent validity, post hoc model modification, equivalent models issues, and alternative models issues should be undergone. Further research with robust consistent methodological study designs from model identification to model respecification is needed to improve the validity of the research.

Modelling vortex-induced fluid-structure interaction.

PubMed

Benaroya, Haym; Gabbai, Rene D

2008-04-13

The principal goal of this research is developing physics-based, reduced-order, analytical models of nonlinear fluid-structure interactions associated with offshore structures. Our primary focus is to generalize the Hamilton's variational framework so that systems of flow-oscillator equations can be derived from first principles. This is an extension of earlier work that led to a single energy equation describing the fluid-structure interaction. It is demonstrated here that flow-oscillator models are a subclass of the general, physical-based framework. A flow-oscillator model is a reduced-order mechanical model, generally comprising two mechanical oscillators, one modelling the structural oscillation and the other a nonlinear oscillator representing the fluid behaviour coupled to the structural motion.Reduced-order analytical model development continues to be carried out using a Hamilton's principle-based variational approach. This provides flexibility in the long run for generalizing the modelling paradigm to complex, three-dimensional problems with multiple degrees of freedom, although such extension is very difficult. As both experimental and analytical capabilities advance, the critical research path to developing and implementing fluid-structure interaction models entails-formulating generalized equations of motion, as a superset of the flow-oscillator models; and-developing experimentally derived, semi-analytical functions to describe key terms in the governing equations of motion. The developed variational approach yields a system of governing equations. This will allow modelling of multiple d.f. systems. The extensions derived generalize the Hamilton's variational formulation for such problems. The Navier-Stokes equations are derived and coupled to the structural oscillator. This general model has been shown to be a superset of the flow-oscillator model. Based on different assumptions, one can derive a variety of flow-oscillator models.

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.

Does exercise habit strength moderate the relationship between emotional distress and short-term memory in Malaysian primary school children?

PubMed

Zainol, Nurul Ain; Hashim, Hairul Anuar

2015-01-01

We examined the moderating effects of exercise habit strength on the relationship between emotional distress and short-term memory in primary school children. The sample consisted of 165 primary school students (10-12 years old). Participants completed measures of emotional distress, exercise habit strength, and the Digit Span Test. Mid-year exam results were used as an indicator of academic performance. Structural equation modelling (SEM) was used to analyse the data. The results of SEM revealed an acceptable fit for the hypothesised model. Exercise habit was positively associated with short-term memory, and better short-term memory was associated with better academic performance. However, although an inverse relationship was found between emotional distress and short-term memory, a positive association was found between exercise habit strength and emotional distress. The findings indicate that exercise habit is positively associated with cognitive ability and mediates the negative effect of distress.

Progress Implementing a Model-Based Iterative Reconstruction Algorithm for Ultrasound Imaging of Thick Concrete

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

Almansouri, Hani; Johnson, Christi R; Clayton, Dwight A

All commercial nuclear power plants (NPPs) in the United States contain concrete structures. These structures provide important foundation, support, shielding, and containment functions. Identification and management of aging and the degradation of concrete structures is fundamental to the proposed long-term operation of NPPs. Concrete structures in NPPs are often inaccessible and contain large volumes of massively thick concrete. While acoustic imaging using the synthetic aperture focusing technique (SAFT) works adequately well for thin specimens of concrete such as concrete transportation structures, enhancements are needed for heavily reinforced, thick concrete. We argue that image reconstruction quality for acoustic imaging in thickmore » concrete could be improved with Model-Based Iterative Reconstruction (MBIR) techniques. MBIR works by designing a probabilistic model for the measurements (forward model) and a probabilistic model for the object (prior model). Both models are used to formulate an objective function (cost function). The final step in MBIR is to optimize the cost function. Previously, we have demonstrated a first implementation of MBIR for an ultrasonic transducer array system. The original forward model has been upgraded to account for direct arrival signal. Updates to the forward model will be documented and the new algorithm will be assessed with synthetic and empirical samples.« less

Progress implementing a model-based iterative reconstruction algorithm for ultrasound imaging of thick concrete

NASA Astrophysics Data System (ADS)

Almansouri, Hani; Johnson, Christi; Clayton, Dwight; Polsky, Yarom; Bouman, Charles; Santos-Villalobos, Hector

2017-02-01

All commercial nuclear power plants (NPPs) in the United States contain concrete structures. These structures provide important foundation, support, shielding, and containment functions. Identification and management of aging and the degradation of concrete structures is fundamental to the proposed long-term operation of NPPs. Concrete structures in NPPs are often inaccessible and contain large volumes of massively thick concrete. While acoustic imaging using the synthetic aperture focusing technique (SAFT) works adequately well for thin specimens of concrete such as concrete transportation structures, enhancements are needed for heavily reinforced, thick concrete. We argue that image reconstruction quality for acoustic imaging in thick concrete could be improved with Model-Based Iterative Reconstruction (MBIR) techniques. MBIR works by designing a probabilistic model for the measurements (forward model) and a probabilistic model for the object (prior model). Both models are used to formulate an objective function (cost function). The final step in MBIR is to optimize the cost function. Previously, we have demonstrated a first implementation of MBIR for an ultrasonic transducer array system. The original forward model has been upgraded to account for direct arrival signal. Updates to the forward model will be documented and the new algorithm will be assessed with synthetic and empirical samples.

Refinement of protein termini in template-based modeling using conformational space annealing.

PubMed

Park, Hahnbeom; Ko, Junsu; Joo, Keehyoung; Lee, Julian; Seok, Chaok; Lee, Jooyoung

2011-09-01

The rapid increase in the number of experimentally determined protein structures in recent years enables us to obtain more reliable protein tertiary structure models than ever by template-based modeling. However, refinement of template-based models beyond the limit available from the best templates is still needed for understanding protein function in atomic detail. In this work, we develop a new method for protein terminus modeling that can be applied to refinement of models with unreliable terminus structures. The energy function for terminus modeling consists of both physics-based and knowledge-based potential terms with carefully optimized relative weights. Effective sampling of both the framework and terminus is performed using the conformational space annealing technique. This method has been tested on a set of termini derived from a nonredundant structure database and two sets of termini from the CASP8 targets. The performance of the terminus modeling method is significantly improved over our previous method that does not employ terminus refinement. It is also comparable or superior to the best server methods tested in CASP8. The success of the current approach suggests that similar strategy may be applied to other types of refinement problems such as loop modeling or secondary structure rearrangement. Copyright © 2011 Wiley-Liss, Inc.

Ab Initio Structural Modeling of and Experimental Validation for Chlamydia trachomatis Protein CT296 Reveal Structural Similarity to Fe(II) 2-Oxoglutarate-Dependent Enzymes▿

PubMed Central

Kemege, Kyle E.; Hickey, John M.; Lovell, Scott; Battaile, Kevin P.; Zhang, Yang; Hefty, P. Scott

2011-01-01

Chlamydia trachomatis is a medically important pathogen that encodes a relatively high percentage of proteins with unknown function. The three-dimensional structure of a protein can be very informative regarding the protein's functional characteristics; however, determining protein structures experimentally can be very challenging. Computational methods that model protein structures with sufficient accuracy to facilitate functional studies have had notable successes. To evaluate the accuracy and potential impact of computational protein structure modeling of hypothetical proteins encoded by Chlamydia, a successful computational method termed I-TASSER was utilized to model the three-dimensional structure of a hypothetical protein encoded by open reading frame (ORF) CT296. CT296 has been reported to exhibit functional properties of a divalent cation transcription repressor (DcrA), with similarity to the Escherichia coli iron-responsive transcriptional repressor, Fur. Unexpectedly, the I-TASSER model of CT296 exhibited no structural similarity to any DNA-interacting proteins or motifs. To validate the I-TASSER-generated model, the structure of CT296 was solved experimentally using X-ray crystallography. Impressively, the ab initio I-TASSER-generated model closely matched (2.72-Å Cα root mean square deviation [RMSD]) the high-resolution (1.8-Å) crystal structure of CT296. Modeled and experimentally determined structures of CT296 share structural characteristics of non-heme Fe(II) 2-oxoglutarate-dependent enzymes, although key enzymatic residues are not conserved, suggesting a unique biochemical process is likely associated with CT296 function. Additionally, functional analyses did not support prior reports that CT296 has properties shared with divalent cation repressors such as Fur. PMID:21965559

Ab initio structural modeling of and experimental validation for Chlamydia trachomatis protein CT296 reveal structural similarity to Fe(II) 2-oxoglutarate-dependent enzymes

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

Kemege, Kyle E.; Hickey, John M.; Lovell, Scott

2012-02-13

Chlamydia trachomatis is a medically important pathogen that encodes a relatively high percentage of proteins with unknown function. The three-dimensional structure of a protein can be very informative regarding the protein's functional characteristics; however, determining protein structures experimentally can be very challenging. Computational methods that model protein structures with sufficient accuracy to facilitate functional studies have had notable successes. To evaluate the accuracy and potential impact of computational protein structure modeling of hypothetical proteins encoded by Chlamydia, a successful computational method termed I-TASSER was utilized to model the three-dimensional structure of a hypothetical protein encoded by open reading frame (ORF)more » CT296. CT296 has been reported to exhibit functional properties of a divalent cation transcription repressor (DcrA), with similarity to the Escherichia coli iron-responsive transcriptional repressor, Fur. Unexpectedly, the I-TASSER model of CT296 exhibited no structural similarity to any DNA-interacting proteins or motifs. To validate the I-TASSER-generated model, the structure of CT296 was solved experimentally using X-ray crystallography. Impressively, the ab initio I-TASSER-generated model closely matched (2.72-{angstrom} C{alpha} root mean square deviation [RMSD]) the high-resolution (1.8-{angstrom}) crystal structure of CT296. Modeled and experimentally determined structures of CT296 share structural characteristics of non-heme Fe(II) 2-oxoglutarate-dependent enzymes, although key enzymatic residues are not conserved, suggesting a unique biochemical process is likely associated with CT296 function. Additionally, functional analyses did not support prior reports that CT296 has properties shared with divalent cation repressors such as Fur.« less

Tectonic models for Yucca Mountain, Nevada

USGS Publications Warehouse

O'Leary, Dennis W.

2006-01-01

Performance of a high-level nuclear waste repository at Yucca Mountain hinges partly on long-term structural stability of the mountain, its susceptibility to tectonic disruption that includes fault displacement, seismic ground motion, and igneous intrusion. Because of the uncertainty involved with long-term (10,000 yr minimum) prediction of tectonic events (e.g., earthquakes) and the incomplete understanding of the history of strain and its mechanisms in the Yucca Mountain region, a tectonic model is needed. A tectonic model should represent the structural assemblage of the mountain in its tectonic setting and account for that assemblage through a history of deformation in which all of the observed deformation features are linked in time and space. Four major types of tectonic models have been proposed for Yucca Mountain: a caldera model; simple shear (detachment fault) models; pure shear (planar fault) models; and lateral shear models. Most of the models seek to explain local features in the context of well-accepted regional deformation mechanisms. Evaluation of the models in light of site characterization shows that none of them completely accounts for all the known tectonic features of Yucca Mountain or is fully compatible with the deformation history. The Yucca Mountain project does not endorse a preferred tectonic model. However, most experts involved in the probabilistic volcanic hazards analysis and the probabilistic seismic hazards analysis preferred a planar fault type model. ?? 2007 Geological Society of America. All rights reserved.

Creating a Test Validated Structural Dynamic Finite Element Model of the X-56A Aircraft

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi; Truong, Samson

2014-01-01

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 the Multi Utility Technology Test-bed, X-56A 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 the X-56A aircraft. The ground vibration test-validated structural dynamic finite element model of the X-56A aircraft is created in this study. The structural dynamic finite element model of the X-56A aircraft is improved using a model tuning tool. In this study, two different weight configurations of the X-56A aircraft have been improved in a single optimization run. Frequency and the cross-orthogonality (mode shape) matrix were the primary focus for improvement, while other properties such as center of gravity location, total weight, and offdiagonal terms of the mass orthogonality matrix were used as constraints. The end result was a more improved and desirable structural dynamic finite element model configuration for the X-56A aircraft. Improved frequencies and mode shapes in this study increased average flutter speeds of the X-56A aircraft by 7.6% compared to the baseline model.

Creating a Test-Validated Finite-Element Model of the X-56A Aircraft Structure

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi; Truong, Samson

2014-01-01

Small modeling errors in a 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 the X-56A Multi-Utility Technology Testbed 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 the X-56A aircraft. The ground-vibration test-validated structural dynamic finite-element model of the X-56A aircraft is created in this study. The structural dynamic finite-element model of the X-56A aircraft is improved using a model-tuning tool. In this study, two different weight configurations of the X-56A aircraft have been improved in a single optimization run. Frequency and the cross-orthogonality (mode shape) matrix were the primary focus for improvement, whereas other properties such as c.g. location, total weight, and off-diagonal terms of the mass orthogonality matrix were used as constraints. The end result was an improved structural dynamic finite-element model configuration for the X-56A aircraft. Improved frequencies and mode shapes in this study increased average flutter speeds of the X-56A aircraft by 7.6% compared to the baseline model.

Simulation of Electronic Circular Dichroism of Nucleic Acids: From the Structure to the Spectrum.

PubMed

Padula, Daniele; Jurinovich, Sandro; Di Bari, Lorenzo; Mennucci, Benedetta

2016-11-14

We present a quantum mechanical (QM) simulation of the electronic circular dichroism (ECD) of nucleic acids (NAs). The simulation combines classical molecular dynamics, to obtain the structure and its temperature-dependent fluctuations, with a QM excitonic model to determine the ECD. The excitonic model takes into account environmental effects through a polarizable embedding and uses a refined approach to calculate the electronic couplings in terms of full transition densities. Three NAs with either similar conformations but different base sequences or similar base sequences but different conformations have been investigated and the results were compared with experimental observations; a good agreement was seen in all cases. A detailed analysis of the nature of the ECD bands in terms of their excitonic composition was also carried out. Finally, a comparison between the QM and the DeVoe models clearly revealed the importance of including fluctuations of the excitonic parameters and of accurately determining the electronic couplings. This study demonstrates the feasibility of the ab initio simulation of the ECD spectra of NAs, that is, without the need of experimental structural or electronic data. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

The variability, structure and energy conversion of the northern hemisphere traveling waves simulated in a Mars general circulation model

NASA Astrophysics Data System (ADS)

Wang, Huiqun; Toigo, Anthony D.

2016-06-01

Investigations of the variability, structure and energetics of the m = 1-3 traveling waves in the northern hemisphere of Mars are conducted with the MarsWRF general circulation model. Using a simple, annually repeatable dust scenario, the model reproduces many general characteristics of the observed traveling waves. The simulated m = 1 and m = 3 traveling waves show large differences in terms of their structures and energetics. For each representative wave mode, the geopotential signature maximizes at a higher altitude than the temperature signature, and the wave energetics suggests a mixed baroclinic-barotropic nature. There is a large contrast in wave energetics between the near-surface and higher altitudes, as well as between the lower latitudes and higher latitudes at high altitudes. Both barotropic and baroclinic conversions can act as either sources or sinks of eddy kinetic energy. Band-pass filtered transient eddies exhibit strong zonal variations in eddy kinetic energy and various energy transfer terms. Transient eddies are mainly interacting with the time mean flow. However, there appear to be non-negligible wave-wave interactions associated with wave mode transitions. These interactions include those between traveling waves and thermal tides and those among traveling waves.

Pursuit tracking and higher levels of skill development in the human pilot

NASA Technical Reports Server (NTRS)

Hess, R. A.

1981-01-01

A model of the human pilot is offered for pursuit tracking tasks; the model encompasses an existing model for compensatory tracking. The central hypothesis in the development of this model states that those primary structural elements in the compensatory model responsible for the pilot's equalization capabilities remain intact in the pursuit model. In this latter case, effective low-frequency inversion of the controlled-element dynamics occurs by feeding-forward derived input rate through the equalization dynamics, with low-frequency phase droop minimized. The sharp reduction in low-frequency phase lag beyond that associated with the disappearance of phase droop is seen to accompany relatively low-gain feedback of vehicle output. The results of some recent motion cue research are discussed and interpreted in terms of the compensatory-pursuit display dichotomy. Tracking with input preview is discussed in a qualitative way. In terms of the model, preview is shown to demand no fundamental changes in structure or equalization and to allow the pilot to eliminate the effective time delays that accrue in the inversion of the controlled-element dynamics. Precognitive behavior is discussed, and a model that encompasses all the levels of skill development outlined in the successive organizations of perception theory is finally proposed.

Anisotropic piezoelectric twist actuation of helicopter rotor blades: Aeroelastic analysis and design optimization

NASA Astrophysics Data System (ADS)

Wilkie, William Keats

1997-12-01

An aeroelastic model suitable for control law and preliminary structural design of composite helicopter rotor blades incorporating embedded anisotropic piezoelectric actuator laminae is developed. The aeroelasticity model consists of a linear, nonuniform beam representation of the blade structure, including linear piezoelectric actuation terms, coupled with a nonlinear, finite-state unsteady aerodynamics model. A Galerkin procedure and numerical integration in the time domain are used to obtain a soluti An aeroelastic model suitable for control law and preliminary structural design of composite helicopter rotor blades incorporating embedded anisotropic piezoelectric actuator laminae is developed. The aeroelasticity model consists of a linear, nonuniform beam representation of the blade structure, including linear piezoelectric actuation terms, coupled with a nonlinear, finite-state unsteady aerodynamics model. A Galerkin procedure and numerical integration in the time domain are used to obtain amited additional piezoelectric material mass, it is shown that blade twist actuation approaches which exploit in-plane piezoelectric free-stain anisotropies are capable of producing amplitudes of oscillatory blade twisting sufficient for rotor vibration reduction applications. The second study examines the effectiveness of using embedded piezoelectric actuator laminae to alleviate vibratory loads due to retreating blade stall. A 10 to 15 percent improvement in dynamic stall limited forward flight speed, and a 5 percent improvement in stall limited rotor thrust were numerically demonstrated for the active twist rotor blade relative to a conventional blade design. The active twist blades are also demonstrated to be more susceptible than the conventional blades to dynamic stall induced vibratory loads when not operating with twist actuation. This is the result of designing the active twist blades with low torsional stiffness in order to maximize piezoelectric twist authority. Determining the optimum tradeoff between blade torsional stiffness and piezoelectric twist actuation authority is the subject of the third study. For this investigation, a linearized hovering-flight eigenvalue analysis is developed. Linear optimal control theory is then utilized to develop an optimum active twist blade design in terms of reducing structural energy and control effort cost. The forward flight vibratory loads characteristics of the torsional stiffness optimized active twist blade are then examined using the nonlinear, forward flight aeroelastic analysis. The optimized active twist rotor blade is shown to have improved passive and active vibratory loads characteristics relative to the baseline active twist blades.

Conformal phased surfaces for wireless powering of bioelectronic microdevices

PubMed Central

Agrawal, Devansh R.; Tanabe, Yuji; Weng, Desen; Ma, Andrew; Hsu, Stephanie; Liao, Song-Yan; Zhen, Zhe; Zhu, Zi-Yi; Sun, Chuanbowen; Dong, Zhenya; Yang, Fengyuan; Tse, Hung Fat; Poon, Ada S. Y.; Ho, John S.

2017-01-01

Wireless powering could enable the long-term operation of advanced bioelectronic devices within the human body. Although both enhanced powering depth and device miniaturization can be achieved by shaping the field pattern within the body, existing electromagnetic structures do not provide the spatial phase control required to synthesize such patterns. Here, we describe the design and operation of conformal electromagnetic structures, termed phased surfaces, that interface with non-planar body surfaces and optimally modulate the phase response to enhance the performance of wireless powering. We demonstrate that the phased surfaces can wirelessly transfer energy across anatomically heterogeneous tissues in large animal models, powering miniaturized semiconductor devices (<12 mm3) deep within the body (>4 cm). As an illustration of in vivo operation, we wirelessly regulated cardiac rhythm by powering miniaturized stimulators at multiple endocardial sites in a porcine animal model. PMID:29226018

Key Process Uncertainties in Soil Carbon Dynamics: Comparing Multiple Model Structures and Observational Meta-analysis

NASA Astrophysics Data System (ADS)

Sulman, B. N.; Moore, J.; Averill, C.; Abramoff, R. Z.; Bradford, M.; Classen, A. T.; Hartman, M. D.; Kivlin, S. N.; Luo, Y.; Mayes, M. A.; Morrison, E. W.; Riley, W. J.; Salazar, A.; Schimel, J.; Sridhar, B.; Tang, J.; Wang, G.; Wieder, W. R.

2016-12-01

Soil carbon (C) dynamics are crucial to understanding and predicting C cycle responses to global change and soil C modeling is a key tool for understanding these dynamics. While first order model structures have historically dominated this area, a recent proliferation of alternative model structures representing different assumptions about microbial activity and mineral protection is providing new opportunities to explore process uncertainties related to soil C dynamics. We conducted idealized simulations of soil C responses to warming and litter addition using models from five research groups that incorporated different sets of assumptions about processes governing soil C decomposition and stabilization. We conducted a meta-analysis of published warming and C addition experiments for comparison with simulations. Assumptions related to mineral protection and microbial dynamics drove strong differences among models. In response to C additions, some models predicted long-term C accumulation while others predicted transient increases that were counteracted by accelerating decomposition. In experimental manipulations, doubling litter addition did not change soil C stocks in studies spanning as long as two decades. This result agreed with simulations from models with strong microbial growth responses and limited mineral sorption capacity. In observations, warming initially drove soil C loss via increased CO2 production, but in some studies soil C rebounded and increased over decadal time scales. In contrast, all models predicted sustained C losses under warming. The disagreement with experimental results could be explained by physiological or community-level acclimation, or by warming-related changes in plant growth. In addition to the role of microbial activity, assumptions related to mineral sorption and protected C played a key role in driving long-term model responses. In general, simulations were similar in their initial responses to perturbations but diverged over decadal time scales. This suggests that more long-term soil experiments may be necessary to resolve important process uncertainties related to soil C storage. We also suggest future experiments examine how microbial activity responds to warming under a range of soil clay contents and in concert with changes in litter inputs.

Modeling relations in nature and eco-informatics: a practical application of rosennean complexity.

PubMed

Kineman, John J

2007-10-01

The purpose of eco-informatics is to communicate critical information about organisms and ecosystems. To accomplish this, it must reflect the complexity of natural systems. Present information systems are designed around mechanistic concepts that do not capture complexity. Robert Rosen's relational theory offers a way of representing complexity in terms of information entailments that are part of an ontologically implicit 'modeling relation'. This relation has corresponding epistemological components that can be captured empirically, the components being structure (associated with model encoding) and function (associated with model decoding). Relational complexity, thus, provides a long-awaited theoretical underpinning for these concepts that ecology has found indispensable. Structural information pertains to the material organization of a system, which can be represented by data. Functional information specifies potential change, which can be inferred from experiment and represented as models or descriptions of state transformations. Contextual dependency (of structure or function) implies meaning. Biological functions imply internalized or system-dependent laws. Complexity can be represented epistemologically by relating structure and function in two different ways. One expresses the phenomenal relation that exists in any present or past instance, and the other draws the ontology of a system into the empirical world in terms of multiple potentials subject to natural forms of selection and optimality. These act as system attractors. Implementing these components and their theoretical relations in an informatics system will provide more-complete ecological informatics than is possible from a strictly mechanistic point of view. This approach will enable many new possibilities for supporting science and decision making.

Quantitative structure-property relationship (QSPR) modeling of drug-loaded polymeric micelles via genetic function approximation.

PubMed

Wu, Wensheng; Zhang, Canyang; Lin, Wenjing; Chen, Quan; Guo, Xindong; Qian, Yu; Zhang, Lijuan

2015-01-01

Self-assembled nano-micelles of amphiphilic polymers represent a novel anticancer drug delivery system. However, their full clinical utilization remains challenging because the quantitative structure-property relationship (QSPR) between the polymer structure and the efficacy of micelles as a drug carrier is poorly understood. Here, we developed a series of QSPR models to account for the drug loading capacity of polymeric micelles using the genetic function approximation (GFA) algorithm. These models were further evaluated by internal and external validation and a Y-randomization test in terms of stability and generalization, yielding an optimization model that is applicable to an expanded materials regime. As confirmed by experimental data, the relationship between microstructure and drug loading capacity can be well-simulated, suggesting that our models are readily applicable to the quantitative evaluation of the drug-loading capacity of polymeric micelles. Our work may offer a pathway to the design of formulation experiments.

Quantitative Structure-Property Relationship (QSPR) Modeling of Drug-Loaded Polymeric Micelles via Genetic Function Approximation

PubMed Central

Lin, Wenjing; Chen, Quan; Guo, Xindong; Qian, Yu; Zhang, Lijuan

2015-01-01

Self-assembled nano-micelles of amphiphilic polymers represent a novel anticancer drug delivery system. However, their full clinical utilization remains challenging because the quantitative structure-property relationship (QSPR) between the polymer structure and the efficacy of micelles as a drug carrier is poorly understood. Here, we developed a series of QSPR models to account for the drug loading capacity of polymeric micelles using the genetic function approximation (GFA) algorithm. These models were further evaluated by internal and external validation and a Y-randomization test in terms of stability and generalization, yielding an optimization model that is applicable to an expanded materials regime. As confirmed by experimental data, the relationship between microstructure and drug loading capacity can be well-simulated, suggesting that our models are readily applicable to the quantitative evaluation of the drug-loading capacity of polymeric micelles. Our work may offer a pathway to the design of formulation experiments. PMID:25780923

Extended Czjzek model applied to NMR parameter distributions in sodium metaphosphate glass

NASA Astrophysics Data System (ADS)

Vasconcelos, Filipe; Cristol, Sylvain; Paul, Jean-François; Delevoye, Laurent; Mauri, Francesco; Charpentier, Thibault; Le Caër, Gérard

2013-06-01

The extended Czjzek model (ECM) is applied to the distribution of NMR parameters of a simple glass model (sodium metaphosphate, NaPO3) obtained by molecular dynamics (MD) simulations. Accurate NMR tensors, electric field gradient (EFG) and chemical shift anisotropy (CSA) are calculated from density functional theory (DFT) within the well-established PAW/GIPAW framework. The theoretical results are compared to experimental high-resolution solid-state NMR data and are used to validate the considered structural model. The distributions of the calculated coupling constant CQ ∝ |Vzz| and the asymmetry parameter ηQ that characterize the quadrupolar interaction are discussed in terms of structural considerations with the help of a simple point charge model. Finally, the ECM analysis is shown to be relevant for studying the distribution of CSA tensor parameters and gives new insight into the structural characterization of disordered systems by solid-state NMR.

Extended Czjzek model applied to NMR parameter distributions in sodium metaphosphate glass.

PubMed

Vasconcelos, Filipe; Cristol, Sylvain; Paul, Jean-François; Delevoye, Laurent; Mauri, Francesco; Charpentier, Thibault; Le Caër, Gérard

2013-06-26

The extended Czjzek model (ECM) is applied to the distribution of NMR parameters of a simple glass model (sodium metaphosphate, NaPO3) obtained by molecular dynamics (MD) simulations. Accurate NMR tensors, electric field gradient (EFG) and chemical shift anisotropy (CSA) are calculated from density functional theory (DFT) within the well-established PAW/GIPAW framework. The theoretical results are compared to experimental high-resolution solid-state NMR data and are used to validate the considered structural model. The distributions of the calculated coupling constant C(Q) is proportional to |V(zz)| and the asymmetry parameter η(Q) that characterize the quadrupolar interaction are discussed in terms of structural considerations with the help of a simple point charge model. Finally, the ECM analysis is shown to be relevant for studying the distribution of CSA tensor parameters and gives new insight into the structural characterization of disordered systems by solid-state NMR.

Short-term energy outlook. Volume 2. Methodology

NASA Astrophysics Data System (ADS)

1983-05-01

Recent changes in forecasting methodology for nonutility distillate fuel oil demand and for the near-term petroleum forecasts are discussed. The accuracy of previous short-term forecasts of most of the major energy sources published in the last 13 issues of the Outlook is evaluated. Macroeconomic and weather assumptions are included in this evaluation. Energy forecasts for 1983 are compared. Structural change in US petroleum consumption, the use of appropriate weather data in energy demand modeling, and petroleum inventories, imports, and refinery runs are discussed.

Array seismological investigation of the South Atlantic 'Superplume'

NASA Astrophysics Data System (ADS)

Hempel, Stefanie; Gassmöller, Rene; Thomas, Christine

2015-04-01

We apply the axisymmetric, spherical Earth spectral elements code AxiSEM to model seismic compressional waves which sample complex `superplume' structures in the lower mantle. High-resolution array seismological stacking techniques are evaluated regarding their capability to resolve large-scale high-density low-velocity bodies including interior structure such as inner upwellings, high density lenses, ultra-low velocity zones (ULVZs), neighboring remnant slabs and adjacent small-scale uprisings. Synthetic seismograms are also computed and processed for models of the Earth resulting from geodynamic modelling of the South Atlantic mantle including plate reconstruction. We discuss the interference and suppression of the resulting seismic signals and implications for a seismic data study in terms of visibility of the South Atlantic `superplume' structure. This knowledge is used to process, invert and interpret our data set of seismic sources from the Andes and the South Sandwich Islands detected at seismic arrays spanning from Ethiopia over Cameroon to South Africa mapping the South Atlantic `superplume' structure including its interior structure. In order too present the model of the South Atlantic `superplume' structure that best fits the seismic data set, we iteratively compute synthetic seismograms while adjusting the model according to the dependencies found in the parameter study.

Time simulation of flutter with large stiffness changes

NASA Technical Reports Server (NTRS)

Karpel, M.; Wieseman, C. D.

1992-01-01

Time simulation of flutter, involving large local structural changes, is formulated with a state-space model that is based on a relatively small number of generalized coordinates. Free-free vibration modes are first calculated for a nominal finite-element model with relatively large fictitious masses located at the area of structural changes. A low-frequency subset of these modes is then transformed into a set of structural modal coordinates with which the entire simulation is performed. These generalized coordinates and the associated oscillatory aerodynamic force coefficient matrices are used to construct an efficient time-domain, state-space model for basic aeroelastic case. The time simulation can then be performed by simply changing the mass, stiffness and damping coupling terms when structural changes occur. It is shown that the size of the aeroelastic model required for time simulation with large structural changes at a few a priori known locations is similar to that required for direct analysis of a single structural case. The method is applied to the simulation of an aeroelastic wind-tunnel model. The diverging oscillations are followed by the activation of a tip-ballast decoupling mechanism that stabilizes the system but may cause significant transient overshoots.

Time simulation of flutter with large stiffness changes

NASA Technical Reports Server (NTRS)

Karpel, Mordechay; Wieseman, Carol D.

1992-01-01

Time simulation of flutter, involving large local structural changes, is formulated with a state-space model that is based on a relatively small number of generalized coordinates. Free-free vibration modes are first calculated for a nominal finite-element model with relatively large fictitious masses located at the area of structural changes. A low-frequency subset of these modes is then transformed into a set of structural modal coordinates with which the entire simulation is performed. These generalized coordinates and the associated oscillatory aerodynamic force coefficient matrices are used to construct an efficient time-domain, state-space model for a basic aeroelastic case. The time simulation can then be performed by simply changing the mass, stiffness, and damping coupling terms when structural changes occur. It is shown that the size of the aeroelastic model required for time simulation with large structural changes at a few apriori known locations is similar to that required for direct analysis of a single structural case. The method is applied to the simulation of an aeroelastic wind-tunnel model. The diverging oscillations are followed by the activation of a tip-ballast decoupling mechanism that stabilizes the system but may cause significant transient overshoots.

An exploration of partnership through interactions between young 'expert' patients with cystic fibrosis and healthcare professionals.

PubMed

MacDonald, Kath; Irvine, Lindesay; Smith, Margaret Coulter

2015-12-01

To explore how young 'expert patients' living with Cystic Fibrosis and the healthcare professionals with whom they interact perceive partnership and negotiate care. Modern healthcare policy encourages partnership, engagement and self-management of long-term conditions. This philosophy is congruent with the model adopted in the care of those with Cystic Fibrosis, where self-management, trust and mutual respect are perceived to be integral to the development of the ongoing patient/professional relationship. Self-management is associated with the term; 'expert patient'; an individual with a long-term condition whose knowledge and skills are valued and used in partnership with healthcare professionals. However, the term 'expert patient' is debated in the literature as are the motivation for its use and the assumptions implicit in the term. A qualitative exploratory design informed by Interpretivism and Symbolic Interactionism was conducted. Thirty-four consultations were observed and 23 semi-structured interviews conducted between 10 patients, 2 carers and 12 healthcare professionals. Data were analysed thematically using the five stages of 'Framework' a matrix-based qualitative data analysis approach and were subject to peer review and respondent validation. The study received full ethical approval. Three main themes emerged; experiences of partnership, attributes of the expert patient and constructions of illness. Sub-themes of the 'ceremonial order of the clinic', negotiation and trust in relationships and perceptions of the expert patient are presented. The model of consultation may be a barrier to person-centred care. Healthcare professionals show leniency in negotiations, but do not always trust patients' accounts. The term 'expert patient' is unpopular and remains contested. Gaining insight into structures and processes that enable or inhibit partnership can lead to a collaborative approach to service redesign and a revision of the consultation model. © 2015 John Wiley & Sons Ltd.

Predictive Modeling of Chemical Hazard by Integrating Numerical Descriptors of Chemical Structures and Short-term Toxicity Assay Data

PubMed Central

Rusyn, Ivan; Sedykh, Alexander; Guyton, Kathryn Z.; Tropsha, Alexander

2012-01-01

Quantitative structure-activity relationship (QSAR) models are widely used for in silico prediction of in vivo toxicity of drug candidates or environmental chemicals, adding value to candidate selection in drug development or in a search for less hazardous and more sustainable alternatives for chemicals in commerce. The development of traditional QSAR models is enabled by numerical descriptors representing the inherent chemical properties that can be easily defined for any number of molecules; however, traditional QSAR models often have limited predictive power due to the lack of data and complexity of in vivo endpoints. Although it has been indeed difficult to obtain experimentally derived toxicity data on a large number of chemicals in the past, the results of quantitative in vitro screening of thousands of environmental chemicals in hundreds of experimental systems are now available and continue to accumulate. In addition, publicly accessible toxicogenomics data collected on hundreds of chemicals provide another dimension of molecular information that is potentially useful for predictive toxicity modeling. These new characteristics of molecular bioactivity arising from short-term biological assays, i.e., in vitro screening and/or in vivo toxicogenomics data can now be exploited in combination with chemical structural information to generate hybrid QSAR–like quantitative models to predict human toxicity and carcinogenicity. Using several case studies, we illustrate the benefits of a hybrid modeling approach, namely improvements in the accuracy of models, enhanced interpretation of the most predictive features, and expanded applicability domain for wider chemical space coverage. PMID:22387746

Electronic Structures of Anti-Ferromagnetic Tetraradicals: Ab Initio and Semi-Empirical Studies.

PubMed

Zhang, Dawei; Liu, Chungen

2016-04-12

The energy relationships and electronic structures of the lowest-lying spin states in several anti-ferromagnetic tetraradical model systems are studied with high-level ab initio and semi-empirical methods. The Full-CI method (FCI), the complete active space second-order perturbation theory (CASPT2), and the n-electron valence state perturbation theory (NEVPT2) are employed to obtain reference results. By comparing the energy relationships predicted from the Heisenberg and Hubbard models with ab initio benchmarks, the accuracy of the widely used Heisenberg model for anti-ferromagnetic spin-coupling in low-spin polyradicals is cautiously tested in this work. It is found that the strength of electron correlation (|U/t|) concerning anti-ferromagnetically coupled radical centers could range widely from strong to moderate correlation regimes and could become another degree of freedom besides the spin multiplicity. Accordingly, the Heisenberg-type model works well in the regime of strong correlation, which reproduces well the energy relationships along with the wave functions of all the spin states. In moderately spin-correlated tetraradicals, the results of the prototype Heisenberg model deviate severely from those of multi-reference electron correlation ab initio methods, while the extended Heisenberg model, containing four-body terms, can introduce reasonable corrections and maintains its accuracy in this condition. In the weak correlation regime, both the prototype Heisenberg model and its extended forms containing higher-order correction terms will encounter difficulties. Meanwhile, the Hubbard model shows balanced accuracy from strong to weak correlation cases and can reproduce qualitatively correct electronic structures, which makes it more suitable for the study of anti-ferromagnetic coupling in polyradical systems.

Dynamic response of some tentative compliant wall structures to convected turbulence fields

NASA Technical Reports Server (NTRS)

Nijim, H. H.; Lin, Y. K.

1977-01-01

Some tentative compliant wall structures designed for possible skin friction drag reduction are investigated. Among the structural models considered is a ribbed membrane backed by polyurethane or PVS plastisol. This model is simplified as a beam placed on a viscoelastic foundation as well as on a set of evenly spaced supports. The total length of the beam may be either finite or infinite, and the supports may be either rigid or elastic. Another structural model considered is a membrane mounted over a series of pretensioned wires, also evenly spaced, and the entire membrane is backed by an air cavity. The forcing pressure field is idealized as a frozen random pattern convected downstream at a characteristic velocity. The results are given in terms of the frequency response functions of the system, the spectral density of the structural motion, and the spectral density of the boundary layer pressure including the effect of structural motion. These results are used in a parametric study of structural configurations capable of generating favorable wave lengths, wave amplitudes, and wave speeds in the structural motion for potential drag reduction.

Measurement of the polarized structure function σL T' for p ( e→ , e' π+ ) n in the Δ ( 1232 ) resonance region

NASA Astrophysics Data System (ADS)

Joo, K.; Smith, L. C.; Aznauryan, I. G.; Burkert, V. D.; Minehart, R.; Adams, G.; Ambrozewicz, P.; Anciant, E.; Anghinolfi, M.; Asavapibhop, B.; Asryan, G.; Audit, G.; Auger, T.; Avakian, H.; Bagdasaryan, H.; Ball, J. P.; Barrow, S.; Batourine, V.; Battaglieri, M.; Beard, K.; Bektasoglu, M.; Benmouna, N.; Bianchi, N.; Biselli, A. S.; Boiarinov, S.; Bonner, B. E.; Bouchigny, S.; Bradford, R.; Branford, D.; Briscoe, W. J.; Brooks, W. K.; Bültmann, S.; Butuceanu, C.; Calarco, J. R.; Carman, D. S.; Carnahan, B.; Cetina, C.; Chen, S.; Ciciani, L.; Cole, P. L.; Cords, D.; Corvisiero, P.; Crabb, D.; Crannell, H.; Cummings, J. P.; de Sanctis, E.; Devita, R.; Degtyarenko, P. V.; Dennis, L.; Deur, A.; Dharmawardane, K. V.; Dhuga, K. S.; Djalali, C.; Dodge, G. E.; Doughty, D.; Dragovitsch, P.; Dugger, M.; Dytman, S.; Dzyubak, O. P.; Egiyan, H.; Egiyan, K. S.; Elouadrhiri, L.; Empl, A.; Eugenio, P.; Fersch, R.; Feuerbach, R. J.; Forest, T. A.; Funsten, H.; Gaff, S. J.; Garçon, M.; Gavalian, G.; Gilad, S.; Gilfoyle, G. P.; Giovanetti, K. L.; Gothe, R. W.; Griffioen, K. A.; Guidal, M.; Guillo, M.; Guler, N.; Guo, L.; Gyurjyan, V.; Hadjidakis, C.; Hakobyan, R. S.; Hardie, J.; Heddle, D.; Hersman, F. W.; Hicks, K.; Hleiqawi, I.; Holtrop, M.; Hu, J.; Hyde-Wright, C. E.; Ilieva, Y.; Ireland, D.; Ito, M. M.; Jenkins, D.; Juengst, H. G.; Kellie, J. D.; Kelley, J. H.; Khandaker, M.; Kim, K. Y.; Kim, K.; Kim, W.; Klein, A.; Klein, F. J.; Klimenko, A. V.; Klusman, M.; Kossov, M.; Koubarovski, V.; Kramer, L. H.; Kuhn, S. E.; Kuhn, J.; Lachniet, J.; Laget, J. M.; Langheinrich, J.; Lawrence, D.; Lee, T.; Livingston, K.; Lukashin, K.; Manak, J. J.; Marchand, C.; McAleer, S.; McNabb, J. W.; Mecking, B. A.; Mestayer, M. D.; Meyer, C. A.; Mikhailov, K.; Mirazita, M.; Miskimen, R.; Mokeev, V.; Morand, L.; Morrow, S. A.; Muccifora, V.; Mueller, J.; Mutchler, G. S.; Napolitano, J.; Nasseripour, R.; Nelson, S. O.; Niccolai, S.; Niculescu, G.; Niculescu, I.; Niczyporuk, B. B.; Niyazov, R. A.; Nozar, M.; O'Rielly, G. V.; Osipenko, M.; Ostrovidov, A. I.; Park, K.; Pasyuk, E.; Peterson, G.; Philips, S. A.; Pivnyuk, N.; Pocanic, D.; Pogorelko, O.; Polli, E.; Pozdniakov, S.; Preedom, B. M.; Price, J. W.; Prok, Y.; Protopopescu, D.; Qin, L. M.; Raue, B. A.; Riccardi, G.; Ricco, G.; Ripani, M.; Ritchie, B. G.; Ronchetti, F.; Rosner, G.; Rossi, P.; Rowntree, D.; Rubin, P. D.; Sabatié, F.; Sabourov, K.; Salgado, C.; Santoro, J. P.; Sapunenko, V.; Schumacher, R. A.; Serov, V. S.; Sharabian, Y. G.; Shaw, J.; Simionatto, S.; Skabelin, A. V.; Smith, E. S.; Sober, D. I.; Spraker, M.; Stavinsky, A.; Stepanyan, S.; Stepanyan, S. S.; Stokes, B. E.; Stoler, P.; Strakovsky, I. I.; Strauch, S.; Taiuti, M.; Taylor, S.; Tedeschi, D. J.; Thoma, U.; Thompson, R.; Tkabladze, A.; Todor, L.; Tur, C.; Ungaro, M.; Vineyard, M. F.; Vlassov, A. V.; Wang, K.; Weinstein, L. B.; Weller, H.; Weygand, D. P.; Williams, M.; Wolin, E.; Wood, M. H.; Yegneswaran, A.; Yun, J.; Zana, L.

2004-10-01

The polarized longitudinal-transverse structure function σL T' has been measured using the p ( e→ , e' π+ ) n reaction in the Δ ( 1232 ) resonance region at Q2 =0.40 and 0.65 GeV2 . No previous σL T' data exist for this reaction channel. The kinematically complete experiment was performed at the Jefferson Lab with the CEBAF large acceptance spectrometer using longitudinally polarized electrons at an energy of 1.515 GeV . A partial-wave analysis of the data shows generally better agreement with recent phenomenological models of pion electroproduction compared to the previously measured π0 p channel. A fit to both π0 p and π+ n channels using a unitary isobar model suggests the unitarized Born terms provide a consistent description of the nonresonant background. The t -channel pion pole term is important in the π0 p channel through a rescattering correction, which could be model dependent.

Computer-Based Learning: Graphical Integration of Whole and Sectional Neuroanatomy Improves Long-Term Retention

PubMed Central

Naaz, Farah; Chariker, Julia H.; Pani, John R.

2013-01-01

A study was conducted to test the hypothesis that instruction with graphically integrated representations of whole and sectional neuroanatomy is especially effective for learning to recognize neural structures in sectional imagery (such as MRI images). Neuroanatomy was taught to two groups of participants using computer graphical models of the human brain. Both groups learned whole anatomy first with a three-dimensional model of the brain. One group then learned sectional anatomy using two-dimensional sectional representations, with the expectation that there would be transfer of learning from whole to sectional anatomy. The second group learned sectional anatomy by moving a virtual cutting plane through the three-dimensional model. In tests of long-term retention of sectional neuroanatomy, the group with graphically integrated representation recognized more neural structures that were known to be challenging to learn. This study demonstrates the use of graphical representation to facilitate a more elaborated (deeper) understanding of complex spatial relations. PMID:24563579

An Investigation of Employee Involvement Schemes and Governance Structures in Professional Employment.

ERIC Educational Resources Information Center

Douglas, Joel M.

1995-01-01

Employee Involvement Schemes (EIS) are modeled after Western European worker participation models. These are grounded in collaborative labor relations and encourage employees to participate in work place decision-making. If employees, as the term is defined in the National Labor Relations Act, take part in EIS decision-making processes, they may…

Multipath analysis diffraction calculations

NASA Technical Reports Server (NTRS)

Statham, Richard B.

1996-01-01

This report describes extensions of the Kirchhoff diffraction equation to higher edge terms and discusses their suitability to model diffraction multipath effects of a small satellite structure. When receiving signals, at a satellite, from the Global Positioning System (GPS), reflected signals from the satellite structure result in multipath errors in the determination of the satellite position. Multipath error can be caused by diffraction of the reflected signals and a method of calculating this diffraction is required when using a facet model of the satellite. Several aspects of the Kirchhoff equation are discussed and numerical examples, in the near and far fields, are shown. The vector form of the extended Kirchhoff equation, by adding the Larmor-Tedone and Kottler edge terms, is given as a mathematical model in an appendix. The Kirchhoff equation was investigated as being easily implemented and of good accuracy in the basic form, especially in phase determination. The basic Kirchhoff can be extended for higher accuracy if desired. A brief discussion of the method of moments and the geometric theory of diffraction is included, but seems to offer no clear advantage in implementation over the Kirchhoff for facet models.

Road safety forecasts in five European countries using structural time series models.

PubMed

Antoniou, Constantinos; Papadimitriou, Eleonora; Yannis, George

2014-01-01

Modeling road safety development is a complex task and needs to consider both the quantifiable impact of specific parameters as well as the underlying trends that cannot always be measured or observed. The objective of this research is to apply structural time series models for obtaining reliable medium- to long-term forecasts of road traffic fatality risk using data from 5 countries with different characteristics from all over Europe (Cyprus, Greece, Hungary, Norway, and Switzerland). Two structural time series models are considered: (1) the local linear trend model and the (2) latent risk time series model. Furthermore, a structured decision tree for the selection of the applicable model for each situation (developed within the Road Safety Data, Collection, Transfer and Analysis [DaCoTA] research project, cofunded by the European Commission) is outlined. First, the fatality and exposure data that are used for the development of the models are presented and explored. Then, the modeling process is presented, including the model selection process, introduction of intervention variables, and development of mobility scenarios. The forecasts using the developed models appear to be realistic and within acceptable confidence intervals. The proposed methodology is proved to be very efficient for handling different cases of data availability and quality, providing an appropriate alternative from the family of structural time series models in each country. A concluding section providing perspectives and directions for future research is presented.

Lagrange multiplier and Wess-Zumino variable as extra dimensions in the torus universe

NASA Astrophysics Data System (ADS)

Nejad, Salman Abarghouei; Dehghani, Mehdi; Monemzadeh, Majid

2018-01-01

We study the effect of the simplest geometry which is imposed via the topology of the universe by gauging non-relativistic particle model on torus and 3-torus with the help of symplectic formalism of constrained systems. Also, we obtain generators of gauge transformations for gauged models. Extracting corresponding Poisson structure of existed constraints, we show the effect of the shape of the universe on canonical structure of phase-spaces of models and suggest some phenomenology to prove the topology of the universe and probable non-commutative structure of the space. In addition, we show that the number of extra dimensions in the phase-spaces of gauged embedded models are exactly two. Moreover, in classical form, we talk over modification of Newton's second law in order to study the origin of the terms appeared in the gauged theory.

Including fluid shear viscosity in a structural acoustic finite element model using a scalar fluid representation

PubMed Central

Cheng, Lei; Li, Yizeng; Grosh, Karl

2013-01-01

An approximate boundary condition is developed in this paper to model fluid shear viscosity at boundaries of coupled fluid-structure system. The effect of shear viscosity is approximated by a correction term to the inviscid boundary condition, written in terms of second order in-plane derivatives of pressure. Both thin and thick viscous boundary layer approximations are formulated; the latter subsumes the former. These approximations are used to develop a variational formation, upon which a viscous finite element method (FEM) model is based, requiring only minor modifications to the boundary integral contributions of an existing inviscid FEM model. Since this FEM formulation has only one degree of freedom for pressure, it holds a great computational advantage over the conventional viscous FEM formulation which requires discretization of the full set of linearized Navier-Stokes equations. The results from thick viscous boundary layer approximation are found to be in good agreement with the prediction from a Navier-Stokes model. When applicable, thin viscous boundary layer approximation also gives accurate results with computational simplicity compared to the thick boundary layer formulation. Direct comparison of simulation results using the boundary layer approximations and a full, linearized Navier-Stokes model are made and used to evaluate the accuracy of the approximate technique. Guidelines are given for the parameter ranges over which the accurate application of the thick and thin boundary approximations can be used for a fluid-structure interaction problem. PMID:23729844

Including fluid shear viscosity in a structural acoustic finite element model using a scalar fluid representation.

PubMed

Cheng, Lei; Li, Yizeng; Grosh, Karl

2013-08-15

An approximate boundary condition is developed in this paper to model fluid shear viscosity at boundaries of coupled fluid-structure system. The effect of shear viscosity is approximated by a correction term to the inviscid boundary condition, written in terms of second order in-plane derivatives of pressure. Both thin and thick viscous boundary layer approximations are formulated; the latter subsumes the former. These approximations are used to develop a variational formation, upon which a viscous finite element method (FEM) model is based, requiring only minor modifications to the boundary integral contributions of an existing inviscid FEM model. Since this FEM formulation has only one degree of freedom for pressure, it holds a great computational advantage over the conventional viscous FEM formulation which requires discretization of the full set of linearized Navier-Stokes equations. The results from thick viscous boundary layer approximation are found to be in good agreement with the prediction from a Navier-Stokes model. When applicable, thin viscous boundary layer approximation also gives accurate results with computational simplicity compared to the thick boundary layer formulation. Direct comparison of simulation results using the boundary layer approximations and a full, linearized Navier-Stokes model are made and used to evaluate the accuracy of the approximate technique. Guidelines are given for the parameter ranges over which the accurate application of the thick and thin boundary approximations can be used for a fluid-structure interaction problem.

Stability and growth of continental shields in mantle convection models including recurrent melt production

NASA Astrophysics Data System (ADS)

de Smet, J. H.; van den Berg, A. P.; Vlaar, N. J.

1998-10-01

The long-term growth and stability of compositionally layered continental upper mantle has been investigated by numerical modelling. We present the first numerical model of a convecting mantle including differentiation through partial melting resulting in a stable compositionally layered continental upper mantle structure. This structure includes a continental root extending to a depth of about 200 km. The model covers the upper mantle including the crust and incorporates physical features important for the study of the continental upper mantle during secular cooling of the Earth since the Archaean. Among these features are: a partial melt generation mechanism allowing consistent recurrent melting, time-dependent non-uniform radiogenic heat production, and a temperature- and pressure-dependent rheology. The numerical results reveal a long-term growth mechanism of the continental compositional root. This mechanism operates through episodical injection of small diapiric upwellings from the deep layer of undepleted mantle into the continental root which consists of compositionally distinct depleted mantle material. Our modelling results show the layered continental structure to remain stable during at least 1.5 Ga. After this period mantle differentiation through partial melting ceases due to the prolonged secular cooling and small-scale instabilities set in through continental delamination. This stable period of 1.5 Ga is related to a number of limitations in our model. By improving on these limitations in the future this stable period will be extended to more realistic values.

Exploring the Variability of Short-term Precipitation and Hydrological Response of Small Czech Watersheds

NASA Astrophysics Data System (ADS)

Kavka, Petr; Strouhal, Ludek; Weyskrabova, Lenka; Müller, Miloslav; Kozant, Petr

2017-04-01

The short-term rainfall temporal distribution is known to have a significant effect on the small watersheds' hydrological response. In Czech Republic there are limited publicly available data on rainfall patterns of short-term precipitation. On one side there are catalogues of very short-term synthetic rainfalls used in urban drainage planning and on the other side hourly distribution of daily totals of rainfalls with long return period for larger catchments analyses. This contribution introduces the preliminary outcomes of a running three years' project, which should bridge this gap and provide such data and methodology to the community of scientists, state administration as well as design planners. Six generalized 6-hours hyetographs with 1 minute resolution were derived from 10 years of radar and gauging stations data. These hyetographs are accompanied with information concerning the region of occurrence as well as their frequency related to the rainfall amount. In the next step these hyetographs are used in a complex sensitivity analysis focused on a rainfall-runoff response of small watersheds. This analysis takes into account the uncertainty related to type of the hydrological model, watershed characteristics and main model routines parameterization. Five models with different methods and structure are considered and each model is applied on 5 characteristic watersheds selected from a classification of 7700 small Czech watersheds. For each combination of model and watershed 30, rainfall scenarios were simulated and other scenarios will be used to address the parameters uncertainty. In the last step the variability of outputs will be assessed in the context of economic impacts on design of landscape water structures or mitigation measures. The research is supported by the grant QJ1520265 of the Czech Ministry of Agriculture, rainfall data were provided by the Czech Hydrometeorological Institute.

Evolution of individual versus social learning on social networks.

PubMed

Tamura, Kohei; Kobayashi, Yutaka; Ihara, Yasuo

2015-03-06

A number of studies have investigated the roles played by individual and social learning in cultural phenomena and the relative advantages of the two learning strategies in variable environments. Because social learning involves the acquisition of behaviours from others, its utility depends on the availability of 'cultural models' exhibiting adaptive behaviours. This indicates that social networks play an essential role in the evolution of learning. However, possible effects of social structure on the evolution of learning have not been fully explored. Here, we develop a mathematical model to explore the evolutionary dynamics of learning strategies on social networks. We first derive the condition under which social learners (SLs) are selectively favoured over individual learners in a broad range of social network. We then obtain an analytical approximation of the long-term average frequency of SLs in homogeneous networks, from which we specify the condition, in terms of three relatedness measures, for social structure to facilitate the long-term evolution of social learning. Finally, we evaluate our approximation by Monte Carlo simulations in complete graphs, regular random graphs and scale-free networks. We formally show that whether social structure favours the evolution of social learning is determined by the relative magnitudes of two effects of social structure: localization in competition, by which competition between learning strategies is evaded, and localization in cultural transmission, which slows down the spread of adaptive traits. In addition, our estimates of the relatedness measures suggest that social structure disfavours the evolution of social learning when selection is weak. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

RNA secondary structure prediction with pseudoknots: Contribution of algorithm versus energy model.

PubMed

Jabbari, Hosna; Wark, Ian; Montemagno, Carlo

2018-01-01

RNA is a biopolymer with various applications inside the cell and in biotechnology. Structure of an RNA molecule mainly determines its function and is essential to guide nanostructure design. Since experimental structure determination is time-consuming and expensive, accurate computational prediction of RNA structure is of great importance. Prediction of RNA secondary structure is relatively simpler than its tertiary structure and provides information about its tertiary structure, therefore, RNA secondary structure prediction has received attention in the past decades. Numerous methods with different folding approaches have been developed for RNA secondary structure prediction. While methods for prediction of RNA pseudoknot-free structure (structures with no crossing base pairs) have greatly improved in terms of their accuracy, methods for prediction of RNA pseudoknotted secondary structure (structures with crossing base pairs) still have room for improvement. A long-standing question for improving the prediction accuracy of RNA pseudoknotted secondary structure is whether to focus on the prediction algorithm or the underlying energy model, as there is a trade-off on computational cost of the prediction algorithm versus the generality of the method. The aim of this work is to argue when comparing different methods for RNA pseudoknotted structure prediction, the combination of algorithm and energy model should be considered and a method should not be considered superior or inferior to others if they do not use the same scoring model. We demonstrate that while the folding approach is important in structure prediction, it is not the only important factor in prediction accuracy of a given method as the underlying energy model is also as of great value. Therefore we encourage researchers to pay particular attention in comparing methods with different energy models.

A Data-Driven Diagnostic Framework for Wind Turbine Structures: A Holistic Approach

PubMed Central

Bogoevska, Simona; Spiridonakos, Minas; Chatzi, Eleni; Dumova-Jovanoska, Elena; Höffer, Rudiger

2017-01-01

The complex dynamics of operational wind turbine (WT) structures challenges the applicability of existing structural health monitoring (SHM) strategies for condition assessment. At the center of Europe’s renewable energy strategic planning, WT systems call for implementation of strategies that may describe the WT behavior in its complete operational spectrum. The framework proposed in this paper relies on the symbiotic treatment of acting environmental/operational variables and the monitored vibration response of the structure. The approach aims at accurate simulation of the temporal variability characterizing the WT dynamics, and subsequently at the tracking of the evolution of this variability in a longer-term horizon. The bi-component analysis tool is applied on long-term data, collected as part of continuous monitoring campaigns on two actual operating WT structures located in different sites in Germany. The obtained data-driven structural models verify the potential of the proposed strategy for development of an automated SHM diagnostic tool. PMID:28358346

A Stochastic Model for Detecting Overlapping and Hierarchical Community Structure

PubMed Central

Cao, Xiaochun; Wang, Xiao; Jin, Di; Guo, Xiaojie; Tang, Xianchao

2015-01-01

Community detection is a fundamental problem in the analysis of complex networks. Recently, many researchers have concentrated on the detection of overlapping communities, where a vertex may belong to more than one community. However, most current methods require the number (or the size) of the communities as a priori information, which is usually unavailable in real-world networks. Thus, a practical algorithm should not only find the overlapping community structure, but also automatically determine the number of communities. Furthermore, it is preferable if this method is able to reveal the hierarchical structure of networks as well. In this work, we firstly propose a generative model that employs a nonnegative matrix factorization (NMF) formulization with a l2,1 norm regularization term, balanced by a resolution parameter. The NMF has the nature that provides overlapping community structure by assigning soft membership variables to each vertex; the l2,1 regularization term is a technique of group sparsity which can automatically determine the number of communities by penalizing too many nonempty communities; and hence the resolution parameter enables us to explore the hierarchical structure of networks. Thereafter, we derive the multiplicative update rule to learn the model parameters, and offer the proof of its correctness. Finally, we test our approach on a variety of synthetic and real-world networks, and compare it with some state-of-the-art algorithms. The results validate the superior performance of our new method. PMID:25822148

Simplified and refined structural modeling for economical flutter analysis and design

NASA Technical Reports Server (NTRS)

Ricketts, R. H.; Sobieszczanski, J.

1977-01-01

A coordinated use of two finite-element models of different levels of refinement is presented to reduce the computer cost of the repetitive flutter analysis commonly encountered in structural resizing to meet flutter requirements. One model, termed a refined model (RM), represents a high degree of detail needed for strength-sizing and flutter analysis of an airframe. The other model, called a simplified model (SM), has a relatively much smaller number of elements and degrees-of-freedom. A systematic method of deriving an SM from a given RM is described. The method consists of judgmental and numerical operations to make the stiffness and mass of the SM elements equivalent to the corresponding substructures of RM. The structural data are automatically transferred between the two models. The bulk of analysis is performed on the SM with periodical verifications carried out by analysis of the RM. In a numerical example of a supersonic cruise aircraft with an arrow wing, this approach permitted substantial savings in computer costs and acceleration of the job turn-around.

Assessment of Simulated Ground Motions in Earthquake Engineering Practice: A Case Study for Duzce (Turkey)

NASA Astrophysics Data System (ADS)

Karimzadeh, Shaghayegh; Askan, Aysegul; Yakut, Ahmet

2017-09-01

Simulated ground motions can be used in structural and earthquake engineering practice as an alternative to or to augment the real ground motion data sets. Common engineering applications of simulated motions are linear and nonlinear time history analyses of building structures, where full acceleration records are necessary. Before using simulated ground motions in such applications, it is important to assess those in terms of their frequency and amplitude content as well as their match with the corresponding real records. In this study, a framework is outlined for assessment of simulated ground motions in terms of their use in structural engineering. Misfit criteria are determined for both ground motion parameters and structural response by comparing the simulated values against the corresponding real values. For this purpose, as a case study, the 12 November 1999 Duzce earthquake is simulated using stochastic finite-fault methodology. Simulated records are employed for time history analyses of frame models of typical residential buildings. Next, the relationships between ground motion misfits and structural response misfits are studied. Results show that the seismological misfits around the fundamental period of selected buildings determine the accuracy of the simulated responses in terms of their agreement with the observed responses.

Flexible polyurethane foam modelling and identification of viscoelastic parameters for automotive seating applications

NASA Astrophysics Data System (ADS)

Deng, R.; Davies, P.; Bajaj, A. K.

2003-05-01

A hereditary model and a fractional derivative model for the dynamic properties of flexible polyurethane foams used in automotive seat cushions are presented. Non-linear elastic and linear viscoelastic properties are incorporated into these two models. A polynomial function of compression is used to represent the non-linear elastic behavior. The viscoelastic property is modelled by a hereditary integral with a relaxation kernel consisting of two exponential terms in the hereditary model and by a fractional derivative term in the fractional derivative model. The foam is used as the only viscoelastic component in a foam-mass system undergoing uniaxial compression. One-term harmonic balance solutions are developed to approximate the steady state response of the foam-mass system to the harmonic base excitation. System identification procedures based on the direct non-linear optimization and a sub-optimal method are formulated to estimate the material parameters. The effects of the choice of the cost function, frequency resolution of data and imperfections in experiments are discussed. The system identification procedures are also applied to experimental data from a foam-mass system. The performances of the two models for data at different compression and input excitation levels are compared, and modifications to the structure of the fractional derivative model are briefly explored. The role of the viscous damping term in both types of model is discussed.

Testing a Model of Self-Management of Fluid Intake in Community-Residing Long-Term Indwelling Urinary Catheter Users

PubMed Central

Wilde, Mary H.; Crean, Hugh F.; McMahon, James M.; McDonald, Margaret V.; Tang, Wan; Brasch, Judith; Fairbanks, Eileen; Shah, Shivani; Zhang, Feng

2015-01-01

Background Urinary tract infection and blockage are serious and recurrent challenges for people with long-term indwelling catheters, and these catheter problems cause worry and anxiety when they disrupt normal daily activities. Objectives The goal was to determine whether urinary catheter-related self-management behaviors focusing on fluid intake would mediate fluid intake related self-efficacy toward decreasing catheter-associated urinary tract infection (CAUTI) and/or catheter blockage. Method The sample involved data collected from 180 adult community-living, long-term indwelling urinary catheter users. The authors tested a model of fluid intake self-management (F-SMG) related to fluid intake self-efficacy (F-SE) for key outcomes of CAUTI and blockage. To account for the large number of zeros in both outcomes, a zero inflated negative binomial (ZINB) structural equation model was tested. Results Structurally, F-SE was positively associated with F-SMG, suggesting that higher F-SE predicts more (higher) F-SMG; however, F-SMG was not associated with either the frequency of CAUTI’s or the presence or absence of CAUTI. F-SE was positively related to F-SMG and F-SMG predicted less frequency of catheter blockage, but neither F-SE nor F-SMG predicted the presence or absence of blockage. Discussion Further research is needed to better understand determinants of CAUTI in long-term catheter users and factors which might influence or prevent its occurrence. Increased confidence (self-efficacy) and self-management behaviors to promote fluid intake could be of value in long-term urinary catheter users to decrease catheter blockage. PMID:26938358

Perturbation theory for cosmologies with nonlinear structure

NASA Astrophysics Data System (ADS)

Goldberg, Sophia R.; Gallagher, Christopher S.; Clifton, Timothy

2017-11-01

The next generation of cosmological surveys will operate over unprecedented scales, and will therefore provide exciting new opportunities for testing general relativity. The standard method for modelling the structures that these surveys will observe is to use cosmological perturbation theory for linear structures on horizon-sized scales, and Newtonian gravity for nonlinear structures on much smaller scales. We propose a two-parameter formalism that generalizes this approach, thereby allowing interactions between large and small scales to be studied in a self-consistent and well-defined way. This uses both post-Newtonian gravity and cosmological perturbation theory, and can be used to model realistic cosmological scenarios including matter, radiation and a cosmological constant. We find that the resulting field equations can be written as a hierarchical set of perturbation equations. At leading-order, these equations allow us to recover a standard set of Friedmann equations, as well as a Newton-Poisson equation for the inhomogeneous part of the Newtonian energy density in an expanding background. For the perturbations in the large-scale cosmology, however, we find that the field equations are sourced by both nonlinear and mode-mixing terms, due to the existence of small-scale structures. These extra terms should be expected to give rise to new gravitational effects, through the mixing of gravitational modes on small and large scales—effects that are beyond the scope of standard linear cosmological perturbation theory. We expect our formalism to be useful for accurately modeling gravitational physics in universes that contain nonlinear structures, and for investigating the effects of nonlinear gravity in the era of ultra-large-scale surveys.

De novo protein structure prediction by dynamic fragment assembly and conformational space annealing.

PubMed

Lee, Juyong; Lee, Jinhyuk; Sasaki, Takeshi N; Sasai, Masaki; Seok, Chaok; Lee, Jooyoung

2011-08-01

Ab initio protein structure prediction is a challenging problem that requires both an accurate energetic representation of a protein structure and an efficient conformational sampling method for successful protein modeling. In this article, we present an ab initio structure prediction method which combines a recently suggested novel way of fragment assembly, dynamic fragment assembly (DFA) and conformational space annealing (CSA) algorithm. In DFA, model structures are scored by continuous functions constructed based on short- and long-range structural restraint information from a fragment library. Here, DFA is represented by the full-atom model by CHARMM with the addition of the empirical potential of DFIRE. The relative contributions between various energy terms are optimized using linear programming. The conformational sampling was carried out with CSA algorithm, which can find low energy conformations more efficiently than simulated annealing used in the existing DFA study. The newly introduced DFA energy function and CSA sampling algorithm are implemented into CHARMM. Test results on 30 small single-domain proteins and 13 template-free modeling targets of the 8th Critical Assessment of protein Structure Prediction show that the current method provides comparable and complementary prediction results to existing top methods. Copyright © 2011 Wiley-Liss, Inc.

Human Spacecraft Structures Internship

NASA Technical Reports Server (NTRS)

Bhakta, Kush

2017-01-01

DSG will be placed in halo orbit around themoon- Platform for international/commercialpartners to explore lunar surface- Testbed for technologies needed toexplore Mars• Habitat module used to house up to 4crew members aboard the DSG- Launched on EM-3- Placed inside SLS fairing Habitat Module - Task Habitat Finite Element Model Re-modeled entire structure in NX2) Used Beam and Shell elements torepresent the pressure vessel structure3) Created a point cloud of centers of massfor mass components- Can now inspect local moments andinertias for thrust ring application8/ Habitat Structure – Docking Analysis Problem: Artificial Gravity may be necessary forastronaut health in deep spaceGoal: develop concepts that show how artificialgravity might be incorporated into a spacecraft inthe near term Orion Window Radiant Heat Testing.

Hierarchical modeling of molecular energies using a deep neural network

NASA Astrophysics Data System (ADS)

Lubbers, Nicholas; Smith, Justin S.; Barros, Kipton

2018-06-01

We introduce the Hierarchically Interacting Particle Neural Network (HIP-NN) to model molecular properties from datasets of quantum calculations. Inspired by a many-body expansion, HIP-NN decomposes properties, such as energy, as a sum over hierarchical terms. These terms are generated from a neural network—a composition of many nonlinear transformations—acting on a representation of the molecule. HIP-NN achieves the state-of-the-art performance on a dataset of 131k ground state organic molecules and predicts energies with 0.26 kcal/mol mean absolute error. With minimal tuning, our model is also competitive on a dataset of molecular dynamics trajectories. In addition to enabling accurate energy predictions, the hierarchical structure of HIP-NN helps to identify regions of model uncertainty.

Dark matter admixed strange quark stars in the Starobinsky model

NASA Astrophysics Data System (ADS)

Lopes, Ilídio; Panotopoulos, Grigoris

2018-01-01

We compute the mass-to-radius profiles for dark matter admixed strange quark stars in the Starobinsky model of modified gravity. For quark matter, we assume the MIT bag model, while self-interacting dark matter inside the star is modeled as a Bose-Einstein condensate with a polytropic equation of state. We numerically integrate the structure equations in the Einstein frame, adopting the two-fluid formalism, and we treat the curvature correction term nonperturbatively. The effects on the properties of the stars of the amount of dark matter as well as the higher curvature term are investigated. We find that strange quark stars (in agreement with current observational constraints) with the highest masses are equally affected by dark matter and modified gravity.

LETTER TO THE EDITOR: Bicomplexes and conservation laws in non-Abelian Toda models

NASA Astrophysics Data System (ADS)

Gueuvoghlanian, E. P.

2001-08-01

A bicomplex structure is associated with the Leznov-Saveliev equation of integrable models. The linear problem associated with the zero-curvature condition is derived in terms of the bicomplex linear equation. The explicit example of a non-Abelian conformal affine Toda model is discussed in detail and its conservation laws are derived from the zero-curvature representation of its equation of motion.

Tensor models, Kronecker coefficients and permutation centralizer algebras

NASA Astrophysics Data System (ADS)

Geloun, Joseph Ben; Ramgoolam, Sanjaye

2017-11-01

We show that the counting of observables and correlators for a 3-index tensor model are organized by the structure of a family of permutation centralizer algebras. These algebras are shown to be semi-simple and their Wedderburn-Artin decompositions into matrix blocks are given in terms of Clebsch-Gordan coefficients of symmetric groups. The matrix basis for the algebras also gives an orthogonal basis for the tensor observables which diagonalizes the Gaussian two-point functions. The centres of the algebras are associated with correlators which are expressible in terms of Kronecker coefficients (Clebsch-Gordan multiplicities of symmetric groups). The color-exchange symmetry present in the Gaussian model, as well as a large class of interacting models, is used to refine the description of the permutation centralizer algebras. This discussion is extended to a general number of colors d: it is used to prove the integrality of an infinite family of number sequences related to color-symmetrizations of colored graphs, and expressible in terms of symmetric group representation theory data. Generalizing a connection between matrix models and Belyi maps, correlators in Gaussian tensor models are interpreted in terms of covers of singular 2-complexes. There is an intriguing difference, between matrix and higher rank tensor models, in the computational complexity of superficially comparable correlators of observables parametrized by Young diagrams.

Variable Complexity Structural Optimization of Shells

NASA Technical Reports Server (NTRS)

Haftka, Raphael T.; Venkataraman, Satchi

1999-01-01

Structural designers today face both opportunities and challenges in a vast array of available analysis and optimization programs. Some programs such as NASTRAN, are very general, permitting the designer to model any structure, to any degree of accuracy, but often at a higher computational cost. Additionally, such general procedures often do not allow easy implementation of all constraints of interest to the designer. Other programs, based on algebraic expressions used by designers one generation ago, have limited applicability for general structures with modem materials. However, when applicable, they provide easy understanding of design decisions trade-off. Finally, designers can also use specialized programs suitable for designing efficiently a subset of structural problems. For example, PASCO and PANDA2 are panel design codes, which calculate response and estimate failure much more efficiently than general-purpose codes, but are narrowly applicable in terms of geometry and loading. Therefore, the problem of optimizing structures based on simultaneous use of several models and computer programs is a subject of considerable interest. The problem of using several levels of models in optimization has been dubbed variable complexity modeling. Work under NASA grant NAG1-2110 has been concerned with the development of variable complexity modeling strategies with special emphasis on response surface techniques. In addition, several modeling issues for the design of shells of revolution were studied.

Variable Complexity Structural Optimization of Shells

NASA Technical Reports Server (NTRS)

Haftka, Raphael T.; Venkataraman, Satchi

1998-01-01

Structural designers today face both opportunities and challenges in a vast array of available analysis and optimization programs. Some programs such as NASTRAN, are very general, permitting the designer to model any structure, to any degree of accuracy, but often at a higher computational cost. Additionally, such general procedures often do not allow easy implementation of all constraints of interest to the designer. Other programs, based on algebraic expressions used by designers one generation ago, have limited applicability for general structures with modem materials. However, when applicable, they provide easy understanding of design decisions trade-off. Finally, designers can also use specialized programs suitable for designing efficiently a subset of structural problems. For example, PASCO and PANDA2 are panel design codes, which calculate response and estimate failure much more efficiently than general-purpose codes, but are narrowly applicable in terms of geometry and loading. Therefore, the problem of optimizing structures based on simultaneous use of several models and computer programs is a subject of considerable interest. The problem of using several levels of models in optimization has been dubbed variable complexity modeling. Work under NASA grant NAG1-1808 has been concerned with the development of variable complexity modeling strategies with special emphasis on response surface techniques. In addition several modeling issues for the design of shells of revolution were studied.

Causal discovery and inference: concepts and recent methodological advances.

PubMed

Spirtes, Peter; Zhang, Kun

This paper aims to give a broad coverage of central concepts and principles involved in automated causal inference and emerging approaches to causal discovery from i.i.d data and from time series. After reviewing concepts including manipulations, causal models, sample predictive modeling, causal predictive modeling, and structural equation models, we present the constraint-based approach to causal discovery, which relies on the conditional independence relationships in the data, and discuss the assumptions underlying its validity. We then focus on causal discovery based on structural equations models, in which a key issue is the identifiability of the causal structure implied by appropriately defined structural equation models: in the two-variable case, under what conditions (and why) is the causal direction between the two variables identifiable? We show that the independence between the error term and causes, together with appropriate structural constraints on the structural equation, makes it possible. Next, we report some recent advances in causal discovery from time series. Assuming that the causal relations are linear with nonGaussian noise, we mention two problems which are traditionally difficult to solve, namely causal discovery from subsampled data and that in the presence of confounding time series. Finally, we list a number of open questions in the field of causal discovery and inference.

Study on Solution Properties of Binary Mixtures of Some Industrially Important Solvents with Cyclohexylamine and Cyclohexanone at 298.15 K

NASA Astrophysics Data System (ADS)

Roy, Mahendra Nath; Das, Rajesh Kumar; Chanda, Riju

2010-03-01

Densities and viscosities were measured for the binary mixtures of cyclohexylamine and cyclohexanone with butyl acetate, butanone, butylamine, tert-butylamine, and 2-butoxyethanol at 298.15 K over the entire composition range. From density data, the values of the excess molar volume ( V E) have been calculated. The experimental viscosity data were correlated by means of the equation of Grunberg-Nissan. The density and viscosity data have been analyzed in terms of some semiempirical viscosity models. The results are discussed in terms of molecular interactions and structural effects. The excess molar volume is found to be either negative or positive depending on the molecular interactions and the nature of the liquid mixtures and is discussed in terms of molecular interactions and structural changes.

Protein Structure Prediction by Protein Threading

NASA Astrophysics Data System (ADS)

Xu, Ying; Liu, Zhijie; Cai, Liming; Xu, Dong

The seminal work of Bowie, Lüthy, and Eisenberg (Bowie et al., 1991) on "the inverse protein folding problem" laid the foundation of protein structure prediction by protein threading. By using simple measures for fitness of different amino acid types to local structural environments defined in terms of solvent accessibility and protein secondary structure, the authors derived a simple and yet profoundly novel approach to assessing if a protein sequence fits well with a given protein structural fold. Their follow-up work (Elofsson et al., 1996; Fischer and Eisenberg, 1996; Fischer et al., 1996a,b) and the work by Jones, Taylor, and Thornton (Jones et al., 1992) on protein fold recognition led to the development of a new brand of powerful tools for protein structure prediction, which we now term "protein threading." These computational tools have played a key role in extending the utility of all the experimentally solved structures by X-ray crystallography and nuclear magnetic resonance (NMR), providing structural models and functional predictions for many of the proteins encoded in the hundreds of genomes that have been sequenced up to now.

Characterization and modeling of an advanced flexible thermal protection material for space applications

NASA Technical Reports Server (NTRS)

Clayton, Joseph P.; Tinker, Michael L.

1991-01-01

This paper describes experimental and analytical characterization of a new flexible thermal protection material known as Tailorable Advanced Blanket Insulation (TABI). This material utilizes a three-dimensional ceramic fabric core structure and an insulation filler. TABI is the leading candidate for use in deployable aeroassisted vehicle designs. Such designs require extensive structural modeling, and the most significant in-plane material properties necessary for model development are measured and analytically verified in this study. Unique test methods are developed for damping measurements. Mathematical models are developed for verification of the experimental modulus and damping data, and finally, transverse properties are described in terms of the inplane properties through use of a 12-dof finite difference model of a simple TABI configuration.

A review of failure models for unidirectional ceramic matrix composites under monotonic loads

NASA Technical Reports Server (NTRS)

Tripp, David E.; Hemann, John H.; Gyekenyesi, John P.

1989-01-01

Ceramic matrix composites offer significant potential for improving the performance of turbine engines. In order to achieve their potential, however, improvements in design methodology are needed. In the past most components using structural ceramic matrix composites were designed by trial and error since the emphasis of feasibility demonstration minimized the development of mathematical models. To understand the key parameters controlling response and the mechanics of failure, the development of structural failure models is required. A review of short term failure models with potential for ceramic matrix composite laminates under monotonic loads is presented. Phenomenological, semi-empirical, shear-lag, fracture mechanics, damage mechanics, and statistical models for the fast fracture analysis of continuous fiber unidirectional ceramic matrix composites under monotonic loads are surveyed.

A review of economic evaluation models for cardiac resynchronization therapy with implantable cardioverter defibrillators in patients with heart failure.

PubMed

Tomini, F; Prinzen, F; van Asselt, A D I

2016-12-01

Cardiac resynchronization therapy with a biventricular pacemaker (CRT-P) is an effective treatment for dyssynchronous heart failure (DHF). Adding an implantable cardioverter defibrillator (CRT-D) may further reduce the risk of sudden cardiac death (SCD). However, if the majority of patients do not require shock therapy, the cost-effectiveness ratio of CRT-D compared to CRT-P may be high. The objective of this study was to systematically review decision models evaluating the cost-effectiveness of CRT-D for patients with DHF, compare the structure and inputs of these models and identify the main factors influencing the ICERs for CRT-D. A comprehensive search strategy of Medline (Ovid), Embase (Ovid) and EconLit identified eight cost-effectiveness models evaluating CRT-D against optimal pharmacological therapy (OPT) and/or CRT-P. The selected economic studies differed in terms of model structure, treatment path, time horizons, and sources of efficacy data. CRT-D was found cost-effective when compared to OPT but its cost-effectiveness became questionable when compared to CRT-P. Cost-effectiveness of CRT-D may increase depending on improvement of all-cause mortality rates and HF mortality rates in patients who receive CRT-D, costs of the device, and battery life. In particular, future studies need to investigate longer-term mortality rates and identify CRT-P patients that will gain the most, in terms of life expectancy, from being treated with a CRT-D.

Evolutionary Design of Controlled Structures

NASA Technical Reports Server (NTRS)

Masters, Brett P.; Crawley, Edward F.

1997-01-01

Basic physical concepts of structural delay and transmissibility are provided for simple rod and beam structures. Investigations show the sensitivity of these concepts to differing controlled-structures variables, and to rational system modeling effects. An evolutionary controls/structures design method is developed. The basis of the method is an accurate model formulation for dynamic compensator optimization and Genetic Algorithm based updating of sensor/actuator placement and structural attributes. One and three dimensional examples from the literature are used to validate the method. Frequency domain interpretation of these controlled structure systems provide physical insight as to how the objective is optimized and consequently what is important in the objective. Several disturbance rejection type controls-structures systems are optimized for a stellar interferometer spacecraft application. The interferometric designs include closed loop tracking optics. Designs are generated for differing structural aspect ratios, differing disturbance attributes, and differing sensor selections. Physical limitations in achieving performance are given in terms of average system transfer function gains and system phase loss. A spacecraft-like optical interferometry system is investigated experimentally over several different optimized controlled structures configurations. Configurations represent common and not-so-common approaches to mitigating pathlength errors induced by disturbances of two different spectra. Results show that an optimized controlled structure for low frequency broadband disturbances achieves modest performance gains over a mass equivalent regular structure, while an optimized structure for high frequency narrow band disturbances is four times better in terms of root-mean-square pathlength. These results are predictable given the nature of the physical system and the optimization design variables. Fundamental limits on controlled performance are discussed based on the measured and fit average system transfer function gains and system phase loss.

Exploring the Structure of Library and Information Science Web Space Based on Multivariate Analysis of Social Tags

ERIC Educational Resources Information Center

Joo, Soohyung; Kipp, Margaret E. I.

2015-01-01

Introduction: This study examines the structure of Web space in the field of library and information science using multivariate analysis of social tags from the Website, Delicious.com. A few studies have examined mathematical modelling of tags, mainly examining tagging in terms of tripartite graphs, pattern tracing and descriptive statistics. This…

Highly Complex Syllable Structure: A Typological Study of Its Phonological Characteristics and Diachronic Development

ERIC Educational Resources Information Center

Easterday, Shelece Michelle

2017-01-01

The syllable is a natural unit of organization in spoken language. Strong cross-linguistic tendencies in syllable size and shape are often explained in terms of a universal preference for the CV structure, a type which is also privileged in abstract models of the syllable. Syllable patterns such as those found in Itelmen "qsa?txt??"…

Development of a stock-recruitment model and assessment of biological reference points for the Lake Erie walleye fishery

USGS Publications Warehouse

Zhao, Yingming; Kocovsky, Patrick M.; Madenjian, Charles P.

2013-01-01

We developed an updated stock–recruitment relationship for Lake Erie Walleye Sander vitreus using the Akaike information criterion model selection approach. Our best stock–recruitment relationship was a Ricker spawner–recruit function to which spring warming rate was added as an environmental variable, and this regression model explained 39% of the variability in Walleye recruitment over the 1978 through 2006 year-classes. Thus, most of the variability in Lake Erie Walleye recruitment appeared to be attributable to factors other than spawning stock size and spring warming rate. The abundance of age-0 Gizzard Shad Dorosoma cepedianum, which was an important term in previous models, may still be an important factor for Walleye recruitment, but poorer ability to monitor Gizzard Shad since the late 1990s could have led to that term failing to appear in our best model. Secondly, we used numerical simulation to demonstrate how to use the stock recruitment relationship to characterize the population dynamics (such as stable age structure, carrying capacity, and maximum sustainable yield) and some biological reference points (such as fishing rates at different important biomass or harvest levels) for an age-structured population in a deterministic way.

Tetrahedrality and structural order for hydrophobic interactions in a coarse-grained water model

NASA Astrophysics Data System (ADS)

Chaimovich, Aviel; Shell, M. Scott

2014-02-01

The hydrophobic interaction manifests two separate regimes in terms of size: Small nonpolar bodies exhibit a weak oscillatory force (versus distance) while large nonpolar surfaces exhibit a strong monotonic one. This crossover in hydrophobic behavior is typically explained in terms of water's tetrahedral structure: Its tetrahedrality is enhanced near small solutes and diminished near large planar ones. Here, we demonstrate that water's tetrahedral correlations signal this switch even in a highly simplified, isotropic, "core-softened" water model. For this task, we introduce measures of tetrahedrality based on the angular distribution of water's nearest neighbors. On a quantitative basis, the coarse-grained model of course is only approximate: (1) While greater than simple Lennard-Jones liquids, its bulk tetrahedrality remains lower than that of fully atomic models; and (2) the decay length of the large-scale hydrophobic interaction is less than has been found in experiments. Even so, the qualitative behavior of the model is surprisingly rich and exhibits numerous waterlike hydrophobic behaviors, despite its simplicity. We offer several arguments for the manner in which it should be able to (at least partially) reproduce tetrahedral correlations underlying these effects.

Tetrahedrality and structural order for hydrophobic interactions in a coarse-grained water model.

PubMed

Chaimovich, Aviel; Shell, M Scott

2014-02-01

The hydrophobic interaction manifests two separate regimes in terms of size: Small nonpolar bodies exhibit a weak oscillatory force (versus distance) while large nonpolar surfaces exhibit a strong monotonic one. This crossover in hydrophobic behavior is typically explained in terms of water's tetrahedral structure: Its tetrahedrality is enhanced near small solutes and diminished near large planar ones. Here, we demonstrate that water's tetrahedral correlations signal this switch even in a highly simplified, isotropic, "core-softened" water model. For this task, we introduce measures of tetrahedrality based on the angular distribution of water's nearest neighbors. On a quantitative basis, the coarse-grained model of course is only approximate: (1) While greater than simple Lennard-Jones liquids, its bulk tetrahedrality remains lower than that of fully atomic models; and (2) the decay length of the large-scale hydrophobic interaction is less than has been found in experiments. Even so, the qualitative behavior of the model is surprisingly rich and exhibits numerous waterlike hydrophobic behaviors, despite its simplicity. We offer several arguments for the manner in which it should be able to (at least partially) reproduce tetrahedral correlations underlying these effects.

Centrifuge modeling of rocking-isolated inelastic RC bridge piers

PubMed Central

Loli, Marianna; Knappett, Jonathan A; Brown, Michael J; Anastasopoulos, Ioannis; Gazetas, George

2014-01-01

Experimental proof is provided of an unconventional seismic design concept, which is based on deliberately underdesigning shallow foundations to promote intense rocking oscillations and thereby to dramatically improve the seismic resilience of structures. Termed rocking isolation, this new seismic design philosophy is investigated through a series of dynamic centrifuge experiments on properly scaled models of a modern reinforced concrete (RC) bridge pier. The experimental method reproduces the nonlinear and inelastic response of both the soil-footing interface and the structure. To this end, a novel scale model RC (1:50 scale) that simulates reasonably well the elastic response and the failure of prototype RC elements is utilized, along with realistic representation of the soil behavior in a geotechnical centrifuge. A variety of seismic ground motions are considered as excitations. They result in consistent demonstrably beneficial performance of the rocking-isolated pier in comparison with the one designed conventionally. Seismic demand is reduced in terms of both inertial load and deck drift. Furthermore, foundation uplifting has a self-centering potential, whereas soil yielding is shown to provide a particularly effective energy dissipation mechanism, exhibiting significant resistance to cumulative damage. Thanks to such mechanisms, the rocking pier survived, with no signs of structural distress, a deleterious sequence of seismic motions that caused collapse of the conventionally designed pier. © 2014 The Authors Earthquake Engineering & Structural Dynamics Published by John Wiley & Sons Ltd. PMID:26300573

Modeling and mining term association for improving biomedical information retrieval performance.

PubMed

Hu, Qinmin; Huang, Jimmy Xiangji; Hu, Xiaohua

2012-06-11

The growth of the biomedical information requires most information retrieval systems to provide short and specific answers in response to complex user queries. Semantic information in the form of free text that is structured in a way makes it straightforward for humans to read but more difficult for computers to interpret automatically and search efficiently. One of the reasons is that most traditional information retrieval models assume terms are conditionally independent given a document/passage. Therefore, we are motivated to consider term associations within different contexts to help the models understand semantic information and use it for improving biomedical information retrieval performance. We propose a term association approach to discover term associations among the keywords from a query. The experiments are conducted on the TREC 2004-2007 Genomics data sets and the TREC 2004 HARD data set. The proposed approach is promising and achieves superiority over the baselines and the GSP results. The parameter settings and different indices are investigated that the sentence-based index produces the best results in terms of the document-level, the word-based index for the best results in terms of the passage-level and the paragraph-based index for the best results in terms of the passage2-level. Furthermore, the best term association results always come from the best baseline. The tuning number k in the proposed recursive re-ranking algorithm is discussed and locally optimized to be 10. First, modelling term association for improving biomedical information retrieval using factor analysis, is one of the major contributions in our work. Second, the experiments confirm that term association considering co-occurrence and dependency among the keywords can produce better results than the baselines treating the keywords independently. Third, the baselines are re-ranked according to the importance and reliance of latent factors behind term associations. These latent factors are decided by the proposed model and their term appearances in the first round retrieved passages.

Modeling and mining term association for improving biomedical information retrieval performance

PubMed Central

2012-01-01

Background The growth of the biomedical information requires most information retrieval systems to provide short and specific answers in response to complex user queries. Semantic information in the form of free text that is structured in a way makes it straightforward for humans to read but more difficult for computers to interpret automatically and search efficiently. One of the reasons is that most traditional information retrieval models assume terms are conditionally independent given a document/passage. Therefore, we are motivated to consider term associations within different contexts to help the models understand semantic information and use it for improving biomedical information retrieval performance. Results We propose a term association approach to discover term associations among the keywords from a query. The experiments are conducted on the TREC 2004-2007 Genomics data sets and the TREC 2004 HARD data set. The proposed approach is promising and achieves superiority over the baselines and the GSP results. The parameter settings and different indices are investigated that the sentence-based index produces the best results in terms of the document-level, the word-based index for the best results in terms of the passage-level and the paragraph-based index for the best results in terms of the passage2-level. Furthermore, the best term association results always come from the best baseline. The tuning number k in the proposed recursive re-ranking algorithm is discussed and locally optimized to be 10. Conclusions First, modelling term association for improving biomedical information retrieval using factor analysis, is one of the major contributions in our work. Second, the experiments confirm that term association considering co-occurrence and dependency among the keywords can produce better results than the baselines treating the keywords independently. Third, the baselines are re-ranked according to the importance and reliance of latent factors behind term associations. These latent factors are decided by the proposed model and their term appearances in the first round retrieved passages. PMID:22901087

Fast Geometric Consensus Approach for Protein Model Quality Assessment

PubMed Central

Adamczak, Rafal; Pillardy, Jaroslaw; Vallat, Brinda K.

2011-01-01

Abstract Model quality assessment (MQA) is an integral part of protein structure prediction methods that typically generate multiple candidate models. The challenge lies in ranking and selecting the best models using a variety of physical, knowledge-based, and geometric consensus (GC)-based scoring functions. In particular, 3D-Jury and related GC methods assume that well-predicted (sub-)structures are more likely to occur frequently in a population of candidate models, compared to incorrectly folded fragments. While this approach is very successful in the context of diversified sets of models, identifying similar substructures is computationally expensive since all pairs of models need to be superimposed using MaxSub or related heuristics for structure-to-structure alignment. Here, we consider a fast alternative, in which structural similarity is assessed using 1D profiles, e.g., consisting of relative solvent accessibilities and secondary structures of equivalent amino acid residues in the respective models. We show that the new approach, dubbed 1D-Jury, allows to implicitly compare and rank N models in O(N) time, as opposed to quadratic complexity of 3D-Jury and related clustering-based methods. In addition, 1D-Jury avoids computationally expensive 3D superposition of pairs of models. At the same time, structural similarity scores based on 1D profiles are shown to correlate strongly with those obtained using MaxSub. In terms of the ability to select the best models as top candidates 1D-Jury performs on par with other GC methods. Other potential applications of the new approach, including fast clustering of large numbers of intermediate structures generated by folding simulations, are discussed as well. PMID:21244273

Modeling the Biodegradability of Chemical Compounds Using the Online CHEmical Modeling Environment (OCHEM)

PubMed Central

Vorberg, Susann

2013-01-01

Abstract Biodegradability describes the capacity of substances to be mineralized by free‐living bacteria. It is a crucial property in estimating a compound’s long‐term impact on the environment. The ability to reliably predict biodegradability would reduce the need for laborious experimental testing. However, this endpoint is difficult to model due to unavailability or inconsistency of experimental data. Our approach makes use of the Online Chemical Modeling Environment (OCHEM) and its rich supply of machine learning methods and descriptor sets to build classification models for ready biodegradability. These models were analyzed to determine the relationship between characteristic structural properties and biodegradation activity. The distinguishing feature of the developed models is their ability to estimate the accuracy of prediction for each individual compound. The models developed using seven individual descriptor sets were combined in a consensus model, which provided the highest accuracy. The identified overrepresented structural fragments can be used by chemists to improve the biodegradability of new chemical compounds. The consensus model, the datasets used, and the calculated structural fragments are publicly available at http://ochem.eu/article/31660. PMID:27485201

Highly diverse, massive organic data as explored by a composite QSPR strategy: an advanced study of boiling point.

PubMed

Ivanova, A A; Ivanov, A A; Oliferenko, A A; Palyulin, V A; Zefirov, N S

2005-06-01

An improved strategy of quantitative structure-property relationship (QSPR) studies of diverse and inhomogeneous organic datasets has been proposed. A molecular connectivity term was successively corrected for different structural features encoded in fragmental descriptors. The so-called solvation index 1chis (a weighted Randic index) was used as a "leading" variable and standardized molecular fragments were employed as "corrective" class-specific variables. Performance of the new approach was illustrated by modelling a dataset of experimental normal boiling points of 833 organic compounds belonging to 20 structural classes. Firstly, separate QSPR models were derived for each class and for eight groups of structurally similar classes. Finally, a general model formed by combining all the classes together was derived (r2=0.957, s=12.9degreesC). The strategy outlined can find application in QSPR analyses of massive, highly diverse databases of organic compounds.

A 1-D evolutionary model for icy satellites, applied to Enceladus

NASA Astrophysics Data System (ADS)

Malamud, Uri; Prialnik, Dina

2016-04-01

We develop a long-term 1-D evolution model for icy satellites that couples multiple processes: water migration and differentiation, geochemical reactions and silicate phase transitions, compaction by self-gravity, and ablation. The model further considers the following energy sources and sinks: tidal heating, radiogenic heating, geochemical energy released by serpentinization or absorbed by mineral dehydration, gravitational energy and insolation, and heat transport by conduction, convection, and advection. We apply the model to Enceladus, by guessing the initial conditions that would render a structure compatible with present-day observations, assuming the initial structure to have been homogeneous. Assuming the satellite has been losing water continually along its evolution, we postulate that it was formed as a more massive, more icy and more porous satellite, and gradually transformed into its present day state due to sustained long-term tidal heating. We consider several initial compositions and evolution scenarios and follow the evolution for the age of the Solar System, testing the present day model results against the available observational constraints. Our model shows the present configuration to be differentiated into a pure icy mantle, several tens of km thick, overlying a rocky core, composed of dehydrated rock at the center and hydrated rock in the outer part. For Enceladus, it predicts a higher rock/ice mass ratio than previously assumed and a thinner ice mantle, compatible with recent estimates based on gravity field measurements. Although, obviously, the model cannot be used to explain local phenomena, it sheds light on the internal structure invoked in explanations of localized features and activities.

Kondo necklace model in approximants of Fibonacci chains

NASA Astrophysics Data System (ADS)

Reyes, Daniel; Tarazona, H.; Cuba-Supanta, G.; Landauro, C. V.; Espinoza, R.; Quispe-Marcatoma, J.

2017-11-01

The low energy behavior of the one dimensional Kondo necklace model with structural aperiodicity is studied using a representation for the localized and conduction electron spins, in terms of local Kondo singlet and triplet operators at zero temperature. A decoupling scheme on the double time Green's functions is used to find the dispersion relation for the excitations of the system. We determine the dependence between the structural aperiodicity modulation and the spin gap in a Fibonacci approximant chain at zero temperature and in the paramagnetic side of the phase diagram.

Structural analysis of eyespots: dynamics of morphogenic signals that govern elemental positions in butterfly wings

PubMed Central

2012-01-01

Background To explain eyespot colour-pattern determination in butterfly wings, the induction model has been discussed based on colour-pattern analyses of various butterfly eyespots. However, a detailed structural analysis of eyespots that can serve as a foundation for future studies is still lacking. In this study, fundamental structural rules related to butterfly eyespots are proposed, and the induction model is elaborated in terms of the possible dynamics of morphogenic signals involved in the development of eyespots and parafocal elements (PFEs) based on colour-pattern analysis of the nymphalid butterfly Junonia almana. Results In a well-developed eyespot, the inner black core ring is much wider than the outer black ring; this is termed the inside-wide rule. It appears that signals are wider near the focus of the eyespot and become narrower as they expand. Although fundamental signal dynamics are likely to be based on a reaction-diffusion mechanism, they were described well mathematically as a type of simple uniformly decelerated motion in which signals associated with the outer and inner black rings of eyespots and PFEs are released at different time points, durations, intervals, and initial velocities into a two-dimensional field of fundamentally uniform or graded resistance; this produces eyespots and PFEs that are diverse in size and structure. The inside-wide rule, eyespot distortion, structural differences between small and large eyespots, and structural changes in eyespots and PFEs in response to physiological treatments were explained well using mathematical simulations. Natural colour patterns and previous experimental findings that are not easily explained by the conventional gradient model were also explained reasonably well by the formal mathematical simulations performed in this study. Conclusions In a mode free from speculative molecular interactions, the present study clarifies fundamental structural rules related to butterfly eyespots, delineates a theoretical basis for the induction model, and proposes a mathematically simple mode of long-range signalling that may reflect developmental mechanisms associated with butterfly eyespots. PMID:22409965

Structural analysis of eyespots: dynamics of morphogenic signals that govern elemental positions in butterfly wings.

PubMed

Otaki, Joji M

2012-03-13

To explain eyespot colour-pattern determination in butterfly wings, the induction model has been discussed based on colour-pattern analyses of various butterfly eyespots. However, a detailed structural analysis of eyespots that can serve as a foundation for future studies is still lacking. In this study, fundamental structural rules related to butterfly eyespots are proposed, and the induction model is elaborated in terms of the possible dynamics of morphogenic signals involved in the development of eyespots and parafocal elements (PFEs) based on colour-pattern analysis of the nymphalid butterfly Junonia almana. In a well-developed eyespot, the inner black core ring is much wider than the outer black ring; this is termed the inside-wide rule. It appears that signals are wider near the focus of the eyespot and become narrower as they expand. Although fundamental signal dynamics are likely to be based on a reaction-diffusion mechanism, they were described well mathematically as a type of simple uniformly decelerated motion in which signals associated with the outer and inner black rings of eyespots and PFEs are released at different time points, durations, intervals, and initial velocities into a two-dimensional field of fundamentally uniform or graded resistance; this produces eyespots and PFEs that are diverse in size and structure. The inside-wide rule, eyespot distortion, structural differences between small and large eyespots, and structural changes in eyespots and PFEs in response to physiological treatments were explained well using mathematical simulations. Natural colour patterns and previous experimental findings that are not easily explained by the conventional gradient model were also explained reasonably well by the formal mathematical simulations performed in this study. In a mode free from speculative molecular interactions, the present study clarifies fundamental structural rules related to butterfly eyespots, delineates a theoretical basis for the induction model, and proposes a mathematically simple mode of long-range signalling that may reflect developmental mechanisms associated with butterfly eyespots.

Error Covariance Penalized Regression: A novel multivariate model combining penalized regression with multivariate error structure.

PubMed

Allegrini, Franco; Braga, Jez W B; Moreira, Alessandro C O; Olivieri, Alejandro C

2018-06-29

A new multivariate regression model, named Error Covariance Penalized Regression (ECPR) is presented. Following a penalized regression strategy, the proposed model incorporates information about the measurement error structure of the system, using the error covariance matrix (ECM) as a penalization term. Results are reported from both simulations and experimental data based on replicate mid and near infrared (MIR and NIR) spectral measurements. The results for ECPR are better under non-iid conditions when compared with traditional first-order multivariate methods such as ridge regression (RR), principal component regression (PCR) and partial least-squares regression (PLS). Copyright © 2018 Elsevier B.V. All rights reserved.

Mapping the Structure and Dynamics of Genomics-Related MeSH Terms Complex Networks

PubMed Central

Siqueiros-García, Jesús M.; Hernández-Lemus, Enrique; García-Herrera, Rodrigo; Robina-Galatas, Andrea

2014-01-01

It has been proposed that the history and evolution of scientific ideas may reflect certain aspects of the underlying socio-cognitive frameworks in which science itself is developing. Systematic analyses of the development of scientific knowledge may help us to construct models of the collective dynamics of science. Aiming at scientific rigor, these models should be built upon solid empirical evidence, analyzed with formal tools leading to ever-improving results that support the related conclusions. Along these lines we studied the dynamics and structure of the development of research in genomics as represented by the entire collection of genomics-related scientific papers contained in the PubMed database. The analyzed corpus consisted in more than 49,000 articles published in the years 1987 (first appeareance of the term Genomics) to 2011, categorized by means of the Medical Subheadings (MeSH) content-descriptors. Complex networks were built where two MeSH terms were connected if they are descriptors of the same article(s). The analysis of such networks revealed a complex structure and dynamics that to certain extent resembled small-world networks. The evolution of such networks in time reflected interesting phenomena in the historical development of genomic research, including what seems to be a phase-transition in a period marked by the completion of the first draft of the Human Genome Project. We also found that different disciplinary areas have different dynamic evolution patterns in their MeSH connectivity networks. In the case of areas related to science, changes in topology were somewhat fast while retaining a certain core-stucture, whereas in the humanities, the evolution was pretty slow and the structure resulted highly redundant and in the case of technology related issues, the evolution was very fast and the structure remained tree-like with almost no overlapping terms. PMID:24699262

The Large-scale Coronal Structure of the 2017 August 21 Great American Eclipse: An Assessment of Solar Surface Flux Transport Model Enabled Predictions and Observations

NASA Astrophysics Data System (ADS)

Nandy, Dibyendu; Bhowmik, Prantika; Yeates, Anthony R.; Panda, Suman; Tarafder, Rajashik; Dash, Soumyaranjan

2018-01-01

On 2017 August 21, a total solar eclipse swept across the contiguous United States, providing excellent opportunities for diagnostics of the Sun’s corona. The Sun’s coronal structure is notoriously difficult to observe except during solar eclipses; thus, theoretical models must be relied upon for inferring the underlying magnetic structure of the Sun’s outer atmosphere. These models are necessary for understanding the role of magnetic fields in the heating of the corona to a million degrees and the generation of severe space weather. Here we present a methodology for predicting the structure of the coronal field based on model forward runs of a solar surface flux transport model, whose predicted surface field is utilized to extrapolate future coronal magnetic field structures. This prescription was applied to the 2017 August 21 solar eclipse. A post-eclipse analysis shows good agreement between model simulated and observed coronal structures and their locations on the limb. We demonstrate that slow changes in the Sun’s surface magnetic field distribution driven by long-term flux emergence and its evolution governs large-scale coronal structures with a (plausibly cycle-phase dependent) dynamical memory timescale on the order of a few solar rotations, opening up the possibility for large-scale, global corona predictions at least a month in advance.

Acoustic wave transmission through piezoelectric structured materials.

PubMed

Lam, M; Le Clézio, E; Amorín, H; Algueró, M; Holc, Janez; Kosec, Marija; Hladky-Hennion, A C; Feuillard, G

2009-05-01

This paper deals with the transmission of acoustic waves through multilayered piezoelectric materials. It is modeled in an octet formalism via the hybrid matrix of the structure. The theoretical evolution with the angle and frequency of the transmission coefficients of ultrasonic plane waves propagating through a partially depoled PZT plate is compared to finite element calculations showing that both methods are in very good agreement. The model is then used to study a periodic stack of 0.65 PMN-0.35 PT/0.90 PMN-0.10 PT layers. The transmission spectra are interpreted in terms of a dispersive behavior of the critical angles of longitudinal and transverse waves, and band gap structures are analysed. Transmission measurements confirm the theoretical calculations and deliver an experimental validation of the model.

Influence factors and forecast of carbon emission in China: structure adjustment for emission peak

NASA Astrophysics Data System (ADS)

Wang, B.; Cui, C. Q.; Li, Z. P.

2018-02-01

This paper introduced Principal Component Analysis and Multivariate Linear Regression Model to verify long-term balance relationships between Carbon Emissions and the impact factors. The integrated model of improved PCA and multivariate regression analysis model is attainable to figure out the pattern of carbon emission sources. Main empirical results indicate that among all selected variables, the role of energy consumption scale was largest. GDP and Population follow and also have significant impacts on carbon emission. Industrialization rate and fossil fuel proportion, which is the indicator of reflecting the economic structure and energy structure, have a higher importance than the factor of urbanization rate and the dweller consumption level of urban areas. In this way, some suggestions are put forward for government to achieve the peak of carbon emissions.

Multilocality and fusion rules on the generalized structure functions in two-dimensional and three-dimensional Navier-Stokes turbulence.

PubMed

Gkioulekas, Eleftherios

2016-09-01

Using the fusion-rules hypothesis for three-dimensional and two-dimensional Navier-Stokes turbulence, we generalize a previous nonperturbative locality proof to multiple applications of the nonlinear interactions operator on generalized structure functions of velocity differences. We call this generalization of nonperturbative locality to multiple applications of the nonlinear interactions operator "multilocality." The resulting cross terms pose a new challenge requiring a new argument and the introduction of a new fusion rule that takes advantage of rotational symmetry. Our main result is that the fusion-rules hypothesis implies both locality and multilocality in both the IR and UV limits for the downscale energy cascade of three-dimensional Navier-Stokes turbulence and the downscale enstrophy cascade and inverse energy cascade of two-dimensional Navier-Stokes turbulence. We stress that these claims relate to nonperturbative locality of generalized structure functions on all orders and not the term-by-term perturbative locality of diagrammatic theories or closure models that involve only two-point correlation and response functions.

European hospital reforms in times of crisis: aligning cost containment needs with plans for structural redesign?

PubMed

Clemens, Timo; Michelsen, Kai; Commers, Matt; Garel, Pascal; Dowdeswell, Barrie; Brand, Helmut

2014-07-01

Hospitals have become a focal point for health care reform strategies in many European countries during the current financial crisis. It has been called for both, short-term reforms to reduce costs and long-term changes to improve the performance in the long run. On the basis of a literature and document analysis this study analyses how EU member states align short-term and long-term pressures for hospital reforms in times of the financial crisis and assesses the EU's influence on the national reform agenda. The results reveal that there has been an emphasis on cost containment measures rather than embarking on structural redesign of the hospital sector and its position within the broader health care system. The EU influences hospital reform efforts through its enhanced economic framework governance which determines key aspects of the financial context for hospitals in some countries. In addition, the EU health policy agenda which increasingly addresses health system questions stimulates the process of structural hospital reforms by knowledge generation, policy advice and financial incentives. We conclude that successful reforms in such a period would arguably need to address both the organisational and financing sides to hospital care. Moreover, critical to structural reform is a widely held acknowledgement of shortfalls in the current system and belief that new models of hospital care can deliver solutions to overcome these deficits. Advancing the structural redesign of the hospital sector while pressured to contain cost in the short-term is not an easy task and only slowly emerging in Europe. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Basurto-IGPP. A manual-directed approach of integrative group psychotherapy in psychosis.

PubMed

Ruiz-Parra, Eduardo; González-Torres, M A; Eguiluz, I; de la Sierra, E; Trojaola, B; Catalán, A

2010-01-01

A manual on Integrative Group Psychotherapy for outpatients with schizophrenia and other psychoses (Basurto-PGIP) is presented. The model takes into account group specific therapeutic factors. It integrates influences from other integrative psychotherapeutic models, interpersonal group therapy, group analysis and recent developments in cognitive behavioural therapy for psychotic symptoms. The manual is structured in levels of different complexity that can be applied in a progressive manner. The intervention tries to adapt to patients features, therapists ability and training, and centres resources. It can be applied in two possible settings: a short term closed group and a long term open group. Advantages and disadvantages of the model are described.

“That model is sooooo last millennium!” Residential long term care as a system, not a place

PubMed Central

Ziemba, Rosemary; Perry, Tam E.; Takahashi, Beverly; Algase, Donna

2010-01-01

The current quandary with the design of existing long term care (LTC) settings results from focus on structures (“institutions”) instead of on a system of supports and services that transcends physical and traditional boundaries across settings, including nursing homes, assisted living residences and the home. Supported by analysis of the commonalities, socio-historical and political contexts, core values and fallacies of social and medical models in existing and emerging LTC options, a holistic model is proposed based on new core values which facilitate community and family integration, and which asserts dignity and personhood as universal attributes in an array of settings. PMID:20640176

Kinetic analysis of the effects of target structure on siRNA efficiency

NASA Astrophysics Data System (ADS)

Chen, Jiawen; Zhang, Wenbing

2012-12-01

RNAi efficiency for target cleavage and protein expression is related to the target structure. Considering the RNA-induced silencing complex (RISC) as a multiple turnover enzyme, we investigated the effect of target mRNA structure on siRNA efficiency with kinetic analysis. The 4-step model was used to study the target cleavage kinetic process: hybridization nucleation at an accessible target site, RISC-mRNA hybrid elongation along with mRNA target structure melting, target cleavage, and enzyme reactivation. At this model, the terms accounting for the target accessibility, stability, and the seed and the nucleation site effects are all included. The results are in good agreement with that of experiments which show different arguments about the structure effects on siRNA efficiency. It shows that the siRNA efficiency is influenced by the integrated factors of target's accessibility, stability, and the seed effects. To study the off-target effects, a simple model of one siRNA binding to two mRNA targets was designed. By using this model, the possibility for diminishing the off-target effects by the concentration of siRNA was discussed.

Load Diffusion in Composite and Smart Structures

NASA Technical Reports Server (NTRS)

Horgan, Cornelius O.; Ambur, D. (Technical Monitor); Nemeth, M. P. (Technical Monitor)

2003-01-01

The research carried out here builds on our previous NASA supported research on the general topic of edge effects and load diffusion in composite structures. Further fundamental solid mechanics studies were carried out to provide a basis for assessing the complicated modeling necessary for the multi-functional large scale structures used by NASA. An understanding of the fundamental mechanisms of load diffusion in composite subcomponents is essential in developing primary composite structures. Some specific problems recently considered were those of end effects in smart materials and structures, study of the stress response of pressurized linear piezoelectric cylinders for both static and steady rotating configurations, an analysis of the effect of pre-stressing and pre-polarization on the decay of end effects in piezoelectric solids and investigation of constitutive models for hardening rubber-like materials. Our goal in the study of load diffusion is the development of readily applicable results for the decay lengths in terms of non-dimensional material and geometric parameters. Analytical models of load diffusion behavior are extremely valuable in building an intuitive base for developing refined modeling strategies and assessing results from finite element analyses.

A LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATOR (LASSO) FOR NONLINEAR SYSTEM IDENTIFICATION

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.; Lofberg, Johan; Brenner, Martin J.

2006-01-01

Identification of parametric nonlinear models involves estimating unknown parameters and detecting its underlying structure. Structure computation is concerned with selecting a subset of parameters to give a parsimonious description of the system which may afford greater insight into the functionality of the system or a simpler controller design. In this study, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of nonlinear systems. The LASSO minimises the residual sum of squares by the addition of a 1 penalty term on the parameter vector of the traditional 2 minimisation problem. Its use for structure detection is a natural extension of this constrained minimisation approach to pseudolinear regression problems which produces some model parameters that are exactly zero and, therefore, yields a parsimonious system description. The performance of this LASSO structure detection method was evaluated by using it to estimate the structure of a nonlinear polynomial model. Applicability of the method to more complex systems such as those encountered in aerospace applications was shown by identifying a parsimonious system description of the F/A-18 Active Aeroelastic Wing using flight test data.

A Structured-Inquiry Approach to Teaching Neurophysiology Using Computer Simulation

PubMed Central

Crisp, Kevin M.

2012-01-01

Computer simulation is a valuable tool for teaching the fundamentals of neurophysiology in undergraduate laboratories where time and equipment limitations restrict the amount of course content that can be delivered through hands-on interaction. However, students often find such exercises to be tedious and unstimulating. In an effort to engage students in the use of computational modeling while developing a deeper understanding of neurophysiology, an attempt was made to use an educational neurosimulation environment as the basis for a novel, inquiry-based research project. During the semester, students in the class wrote a research proposal, used the Neurodynamix II simulator to generate a large data set, analyzed their modeling results statistically, and presented their findings at the Midbrains Neuroscience Consortium undergraduate poster session. Learning was assessed in the form of a series of short term papers and two 10-min in-class writing responses to the open-ended question, “How do ion channels influence neuronal firing?”, which they completed on weeks 6 and 15 of the semester. Students’ answers to this question showed a deeper understanding of neuronal excitability after the project; their term papers revealed evidence of critical thinking about computational modeling and neuronal excitability. Suggestions for the adaptation of this structured-inquiry approach into shorter term lab experiences are discussed. PMID:23494064

Network Ecology and Adolescent Social Structure

PubMed Central

McFarland, Daniel A.; Moody, James; Diehl, David; Smith, Jeffrey A.; Thomas, Reuben J.

2014-01-01

Adolescent societies—whether arising from weak, short-term classroom friendships or from close, long-term friendships—exhibit various levels of network clustering, segregation, and hierarchy. Some are rank-ordered caste systems and others are flat, cliquish worlds. Explaining the source of such structural variation remains a challenge, however, because global network features are generally treated as the agglomeration of micro-level tie-formation mechanisms, namely balance, homophily, and dominance. How do the same micro-mechanisms generate significant variation in global network structures? To answer this question we propose and test a network ecological theory that specifies the ways features of organizational environments moderate the expression of tie-formation processes, thereby generating variability in global network structures across settings. We develop this argument using longitudinal friendship data on schools (Add Health study) and classrooms (Classroom Engagement study), and by extending exponential random graph models to the study of multiple societies over time. PMID:25535409

Network Ecology and Adolescent Social Structure.

PubMed

McFarland, Daniel A; Moody, James; Diehl, David; Smith, Jeffrey A; Thomas, Reuben J

2014-12-01

Adolescent societies-whether arising from weak, short-term classroom friendships or from close, long-term friendships-exhibit various levels of network clustering, segregation, and hierarchy. Some are rank-ordered caste systems and others are flat, cliquish worlds. Explaining the source of such structural variation remains a challenge, however, because global network features are generally treated as the agglomeration of micro-level tie-formation mechanisms, namely balance, homophily, and dominance. How do the same micro-mechanisms generate significant variation in global network structures? To answer this question we propose and test a network ecological theory that specifies the ways features of organizational environments moderate the expression of tie-formation processes, thereby generating variability in global network structures across settings. We develop this argument using longitudinal friendship data on schools (Add Health study) and classrooms (Classroom Engagement study), and by extending exponential random graph models to the study of multiple societies over time.

A generative spike train model with time-structured higher order correlations.

PubMed

Trousdale, James; Hu, Yu; Shea-Brown, Eric; Josić, Krešimir

2013-01-01

Emerging technologies are revealing the spiking activity in ever larger neural ensembles. Frequently, this spiking is far from independent, with correlations in the spike times of different cells. Understanding how such correlations impact the dynamics and function of neural ensembles remains an important open problem. Here we describe a new, generative model for correlated spike trains that can exhibit many of the features observed in data. Extending prior work in mathematical finance, this generalized thinning and shift (GTaS) model creates marginally Poisson spike trains with diverse temporal correlation structures. We give several examples which highlight the model's flexibility and utility. For instance, we use it to examine how a neural network responds to highly structured patterns of inputs. We then show that the GTaS model is analytically tractable, and derive cumulant densities of all orders in terms of model parameters. The GTaS framework can therefore be an important tool in the experimental and theoretical exploration of neural dynamics.

Images as drivers of progress in cardiac computational modelling

PubMed Central

Lamata, Pablo; Casero, Ramón; Carapella, Valentina; Niederer, Steve A.; Bishop, Martin J.; Schneider, Jürgen E.; Kohl, Peter; Grau, Vicente

2014-01-01

Computational models have become a fundamental tool in cardiac research. Models are evolving to cover multiple scales and physical mechanisms. They are moving towards mechanistic descriptions of personalised structure and function, including effects of natural variability. These developments are underpinned to a large extent by advances in imaging technologies. This article reviews how novel imaging technologies, or the innovative use and extension of established ones, integrate with computational models and drive novel insights into cardiac biophysics. In terms of structural characterization, we discuss how imaging is allowing a wide range of scales to be considered, from cellular levels to whole organs. We analyse how the evolution from structural to functional imaging is opening new avenues for computational models, and in this respect we review methods for measurement of electrical activity, mechanics and flow. Finally, we consider ways in which combined imaging and modelling research is likely to continue advancing cardiac research, and identify some of the main challenges that remain to be solved. PMID:25117497

An Integrated Approach to Damage Accommodation in Flight Control

NASA Technical Reports Server (NTRS)

Boskovic, Jovan D.; Knoebel, Nathan; Mehra, Raman K.; Gregory, Irene

2008-01-01

In this paper we present an integrated approach to in-flight damage accommodation in flight control. The approach is based on Multiple Models, Switching and Tuning (MMST), and consists of three steps: In the first step the main objective is to acquire a realistic aircraft damage model. Modeling of in-flight damage is a highly complex problem since there is a large number of issues that need to be addressed. One of the most important one is that there is strong coupling between structural dynamics, aerodynamics, and flight control. These effects cannot be studied separately due to this coupling. Once a realistic damage model is available, in the second step a large number of models corresponding to different damage cases are generated. One possibility is to generate many linear models and interpolate between them to cover a large portion of the flight envelope. Once these models have been generated, we will implement a recently developed-Model Set Reduction (MSR) technique. The technique is based on parameterizing damage in terms of uncertain parameters, and uses concepts from robust control theory to arrive at a small number of "centered" models such that the controllers corresponding to these models assure desired stability and robustness properties over a subset in the parametric space. By devising a suitable model placement strategy, the entire parametric set is covered with a relatively small number of models and controllers. The third step consists of designing a Multiple Models, Switching and Tuning (MMST) strategy for estimating the current operating regime (damage case) of the aircraft, and switching to the corresponding controller to achieve effective damage accommodation and the desired performance. In the paper present a comprehensive approach to damage accommodation using Model Set Design,MMST, and Variable Structure compensation for coupling nonlinearities. The approach was evaluated on a model of F/A-18 aircraft dynamics under control effector damage, augmented by nonlinear cross-coupling terms and a structural dynamics model. The proposed approach achieved excellent performance under severe damage effects.

Seaway Information System Management and Control Requirements

DOT National Transportation Integrated Search

1973-10-01

This report examines in detail the control and information system requirements of the St. Lawrence Seaway development program in terms of the needs of the vessel traffic controllers and the management users. Structural control models of Seaway operat...

The difference between energy consumption and energy cost: Modelling energy tariff structures for water resource recovery facilities.

PubMed

Aymerich, I; Rieger, L; Sobhani, R; Rosso, D; Corominas, Ll

2015-09-15

The objective of this paper is to demonstrate the importance of incorporating more realistic energy cost models (based on current energy tariff structures) into existing water resource recovery facilities (WRRFs) process models when evaluating technologies and cost-saving control strategies. In this paper, we first introduce a systematic framework to model energy usage at WRRFs and a generalized structure to describe energy tariffs including the most common billing terms. Secondly, this paper introduces a detailed energy cost model based on a Spanish energy tariff structure coupled with a WRRF process model to evaluate several control strategies and provide insights into the selection of the contracted power structure. The results for a 1-year evaluation on a 115,000 population-equivalent WRRF showed monthly cost differences ranging from 7 to 30% when comparing the detailed energy cost model to an average energy price. The evaluation of different aeration control strategies also showed that using average energy prices and neglecting energy tariff structures may lead to biased conclusions when selecting operating strategies or comparing technologies or equipment. The proposed framework demonstrated that for cost minimization, control strategies should be paired with a specific optimal contracted power. Hence, the design of operational and control strategies must take into account the local energy tariff. Copyright © 2015 Elsevier Ltd. All rights reserved.

Use long short-term memory to enhance Internet of Things for combined sewer overflow monitoring

NASA Astrophysics Data System (ADS)

Zhang, Duo; Lindholm, Geir; Ratnaweera, Harsha

2018-01-01

Combined sewer overflow causes severe water pollution, urban flooding and reduced treatment plant efficiency. Understanding the behavior of CSO structures is vital for urban flooding prevention and overflow control. Neural networks have been extensively applied in water resource related fields. In this study, we collect data from an Internet of Things monitoring CSO structure and build different neural network models for simulating and predicting the water level of the CSO structure. Through a comparison of four different neural networks, namely multilayer perceptron (MLP), wavelet neural network (WNN), long short-term memory (LSTM) and gated recurrent unit (GRU), the LSTM and GRU present superior capabilities for multi-step-ahead time series prediction. Furthermore, GRU achieves prediction performances similar to LSTM with a quicker learning curve.

An Active Contour Model Based on Adaptive Threshold for Extraction of Cerebral Vascular Structures.

PubMed

Wang, Jiaxin; Zhao, Shifeng; Liu, Zifeng; Tian, Yun; Duan, Fuqing; Pan, Yutong

2016-01-01

Cerebral vessel segmentation is essential and helpful for the clinical diagnosis and the related research. However, automatic segmentation of brain vessels remains challenging because of the variable vessel shape and high complex of vessel geometry. This study proposes a new active contour model (ACM) implemented by the level-set method for segmenting vessels from TOF-MRA data. The energy function of the new model, combining both region intensity and boundary information, is composed of two region terms, one boundary term and one penalty term. The global threshold representing the lower gray boundary of the target object by maximum intensity projection (MIP) is defined in the first-region term, and it is used to guide the segmentation of the thick vessels. In the second term, a dynamic intensity threshold is employed to extract the tiny vessels. The boundary term is used to drive the contours to evolve towards the boundaries with high gradients. The penalty term is used to avoid reinitialization of the level-set function. Experimental results on 10 clinical brain data sets demonstrate that our method is not only able to achieve better Dice Similarity Coefficient than the global threshold based method and localized hybrid level-set method but also able to extract whole cerebral vessel trees, including the thin vessels.

Determinants of Multiple Semantic Priming: A Meta-Analysis and Spike Frequency Adaptive Model of a Cortical Network

ERIC Educational Resources Information Center

Lavigne, Frederic; Dumercy, Laurent; Darmon, Nelly

2011-01-01

Recall and language comprehension while processing sequences of words involves multiple semantic priming between several related and/or unrelated words. Accounting for multiple and interacting priming effects in terms of underlying neuronal structure and dynamics is a challenge for current models of semantic priming. Further elaboration of current…

Performance in Physical Science Education by Dint of Advance Organiser Model of Teaching

ERIC Educational Resources Information Center

Bency, P. B. Beulahbel; Raja, B. William Dharma

2010-01-01

Education should be made painless and the teaching must be made effective. Teaching is an activity, which is designed and performed for multiple objectives, in terms of changes in student behaviours. Models of teaching are just a blue print designed in advance for providing necessary structure and direction to the teacher for realizing the…

Analysis of CO2 trapping capacities and long-term migration for geological formations in the Norwegian North Sea using MRST-co2lab

NASA Astrophysics Data System (ADS)

Møll Nilsen, Halvor; Lie, Knut-Andreas; Andersen, Odd

2015-06-01

MRST-co2lab is a collection of open-source computational tools for modeling large-scale and long-time migration of CO2 in conductive aquifers, combining ideas from basin modeling, computational geometry, hydrology, and reservoir simulation. Herein, we employ the methods of MRST-co2lab to study long-term CO2 storage on the scale of hundreds of megatonnes. We consider public data sets of two aquifers from the Norwegian North Sea and use geometrical methods for identifying structural traps, percolation-type methods for identifying potential spill paths, and vertical-equilibrium methods for efficient simulation of structural, residual, and solubility trapping in a thousand-year perspective. In particular, we investigate how data resolution affects estimates of storage capacity and discuss workflows for identifying good injection sites and optimizing injection strategies.

The very low frequency power spectrum of Centaurus X-3

NASA Technical Reports Server (NTRS)

Gruber, D. E.

1988-01-01

The long-term variability of Cen X-3 on time scales ranging from days to years has been examined by combining data obtained by the HEAO 1 A-4 instrument with data from Vela 5B. A simple interpretation of the data is made in terms of the standard alpha-disk model of accretion disk structure and dynamics. Assuming that the low-frequency variance represents the inherent variability of the mass transfer from the companion, the decline in power at higher frequencies results from the leveling of radial structure in the accretion disk through viscous mixing. The shape of the observed power spectrum is shown to be in excellent agreement with a calculation based on a simplified form of this model. The observed low-frequency power spectrum of Cen X-3 is consistent with a disk in which viscous mixing occurs about as rapidly as possible and on the largest scale possible.

Structure and application of an interface program between a geographic-information system and a ground-water flow model

USGS Publications Warehouse

Van Metre, P.C.

1990-01-01

A computer-program interface between a geographic-information system and a groundwater flow model links two unrelated software systems for use in developing the flow models. The interface program allows the modeler to compile and manage geographic components of a groundwater model within the geographic information system. A significant savings of time and effort is realized in developing, calibrating, and displaying the groundwater flow model. Four major guidelines were followed in developing the interface program: (1) no changes to the groundwater flow model code were to be made; (2) a data structure was to be designed within the geographic information system that follows the same basic data structure as the groundwater flow model; (3) the interface program was to be flexible enough to support all basic data options available within the model; and (4) the interface program was to be as efficient as possible in terms of computer time used and online-storage space needed. Because some programs in the interface are written in control-program language, the interface will run only on a computer with the PRIMOS operating system. (USGS)

Modeling the economic outcomes of immuno-oncology drugs: alternative model frameworks to capture clinical outcomes.

PubMed

Gibson, E J; Begum, N; Koblbauer, I; Dranitsaris, G; Liew, D; McEwan, P; Tahami Monfared, A A; Yuan, Y; Juarez-Garcia, A; Tyas, D; Lees, M

2018-01-01

Economic models in oncology are commonly based on the three-state partitioned survival model (PSM) distinguishing between progression-free and progressive states. However, the heterogeneity of responses observed in immuno-oncology (I-O) suggests that new approaches may be appropriate to reflect disease dynamics meaningfully. This study explored the impact of incorporating immune-specific health states into economic models of I-O therapy. Two variants of the PSM and a Markov model were populated with data from one clinical trial in metastatic melanoma patients. Short-term modeled outcomes were benchmarked to the clinical trial data and a lifetime model horizon provided estimates of life years and quality adjusted life years (QALYs). The PSM-based models produced short-term outcomes closely matching the trial outcomes. Adding health states generated increased QALYs while providing a more granular representation of outcomes for decision making. The Markov model gave the greatest level of detail on outcomes but gave short-term results which diverged from those of the trial (overstating year 1 progression-free survival by around 60%). Increased sophistication in the representation of disease dynamics in economic models is desirable when attempting to model treatment response in I-O. However, the assumptions underlying different model structures and the availability of data for health state mapping may be important limiting factors.

Strategic directions for agent-based modeling: avoiding the YAAWN syndrome.

PubMed

O'Sullivan, David; Evans, Tom; Manson, Steven; Metcalf, Sara; Ligmann-Zielinska, Arika; Bone, Chris

In this short communication, we examine how agent-based modeling has become common in land change science and is increasingly used to develop case studies for particular times and places. There is a danger that the research community is missing a prime opportunity to learn broader lessons from the use of agent-based modeling (ABM), or at the very least not sharing these lessons more widely. How do we find an appropriate balance between empirically rich, realistic models and simpler theoretically grounded models? What are appropriate and effective approaches to model evaluation in light of uncertainties not only in model parameters but also in model structure? How can we best explore hybrid model structures that enable us to better understand the dynamics of the systems under study, recognizing that no single approach is best suited to this task? Under what circumstances - in terms of model complexity, model evaluation, and model structure - can ABMs be used most effectively to lead to new insight for stakeholders? We explore these questions in the hope of helping the growing community of land change scientists using models in their research to move from 'yet another model' to doing better science with models.

Spectral action models of gravity on packed swiss cheese cosmology

NASA Astrophysics Data System (ADS)

Ball, Adam; Marcolli, Matilde

2016-06-01

We present a model of (modified) gravity on spacetimes with fractal structure based on packing of spheres, which are (Euclidean) variants of the packed swiss cheese cosmology models. As the action functional for gravity we consider the spectral action of noncommutative geometry, and we compute its expansion on a space obtained as an Apollonian packing of three-dimensional spheres inside a four-dimensional ball. Using information from the zeta function of the Dirac operator of the spectral triple, we compute the leading terms in the asymptotic expansion of the spectral action. They consist of a zeta regularization of the divergent sum of the leading terms of the spectral actions of the individual spheres in the packing. This accounts for the contribution of points 1 and 3 in the dimension spectrum (as in the case of a 3-sphere). There is an additional term coming from the residue at the additional point in the real dimension spectrum that corresponds to the packing constant, as well as a series of fluctuations coming from log-periodic oscillations, created by the points of the dimension spectrum that are off the real line. These terms detect the fractality of the residue set of the sphere packing. We show that the presence of fractality influences the shape of the slow-roll potential for inflation, obtained from the spectral action. We also discuss the effect of truncating the fractal structure at a certain scale related to the energy scale in the spectral action.

Uncertainty in the fate of soil organic carbon: A comparison of three conceptually different soil decomposition models

USGS Publications Warehouse

He, Yujie; Yang, Jinyan; Zhuang, Qianlai; McGuire, A. David; Zhu, Qing; Liu, Yaling; Teskey, Robert O.

2014-01-01

Conventional Q10 soil organic matter decomposition models and more complex microbial models are available for making projections of future soil carbon dynamics. However, it is unclear (1) how well the conceptually different approaches can simulate observed decomposition and (2) to what extent the trajectories of long-term simulations differ when using the different approaches. In this study, we compared three structurally different soil carbon (C) decomposition models (one Q10 and two microbial models of different complexity), each with a one- and two-horizon version. The models were calibrated and validated using 4 years of measurements of heterotrophic soil CO2 efflux from trenched plots in a Dahurian larch (Larix gmelinii Rupr.) plantation. All models reproduced the observed heterotrophic component of soil CO2 efflux, but the trajectories of soil carbon dynamics differed substantially in 100 year simulations with and without warming and increased litterfall input, with microbial models that produced better agreement with observed changes in soil organic C in long-term warming experiments. Our results also suggest that both constant and varying carbon use efficiency are plausible when modeling future decomposition dynamics and that the use of a short-term (e.g., a few years) period of measurement is insufficient to adequately constrain model parameters that represent long-term responses of microbial thermal adaption. These results highlight the need to reframe the representation of decomposition models and to constrain parameters with long-term observations and multiple data streams. We urge caution in interpreting future soil carbon responses derived from existing decomposition models because both conceptual and parameter uncertainties are substantial.

Characterising RNA secondary structure space using information entropy

PubMed Central

2013-01-01

Comparative methods for RNA secondary structure prediction use evolutionary information from RNA alignments to increase prediction accuracy. The model is often described in terms of stochastic context-free grammars (SCFGs), which generate a probability distribution over secondary structures. It is, however, unclear how this probability distribution changes as a function of the input alignment. As prediction programs typically only return a single secondary structure, better characterisation of the underlying probability space of RNA secondary structures is of great interest. In this work, we show how to efficiently compute the information entropy of the probability distribution over RNA secondary structures produced for RNA alignments by a phylo-SCFG, and implement it for the PPfold model. We also discuss interpretations and applications of this quantity, including how it can clarify reasons for low prediction reliability scores. PPfold and its source code are available from http://birc.au.dk/software/ppfold/. PMID:23368905

A Standard-Driven Data Dictionary for Data Harmonization of Heterogeneous Datasets in Urban Geological Information Systems

NASA Astrophysics Data System (ADS)

Liu, G.; Wu, C.; Li, X.; Song, P.

2013-12-01

The 3D urban geological information system has been a major part of the national urban geological survey project of China Geological Survey in recent years. Large amount of multi-source and multi-subject data are to be stored in the urban geological databases. There are various models and vocabularies drafted and applied by industrial companies in urban geological data. The issues such as duplicate and ambiguous definition of terms and different coding structure increase the difficulty of information sharing and data integration. To solve this problem, we proposed a national standard-driven information classification and coding method to effectively store and integrate urban geological data, and we applied the data dictionary technology to achieve structural and standard data storage. The overall purpose of this work is to set up a common data platform to provide information sharing service. Research progresses are as follows: (1) A unified classification and coding method for multi-source data based on national standards. Underlying national standards include GB 9649-88 for geology and GB/T 13923-2006 for geography. Current industrial models are compared with national standards to build a mapping table. The attributes of various urban geological data entity models are reduced to several categories according to their application phases and domains. Then a logical data model is set up as a standard format to design data file structures for a relational database. (2) A multi-level data dictionary for data standardization constraint. Three levels of data dictionary are designed: model data dictionary is used to manage system database files and enhance maintenance of the whole database system; attribute dictionary organizes fields used in database tables; term and code dictionary is applied to provide a standard for urban information system by adopting appropriate classification and coding methods; comprehensive data dictionary manages system operation and security. (3) An extension to system data management function based on data dictionary. Data item constraint input function is making use of the standard term and code dictionary to get standard input result. Attribute dictionary organizes all the fields of an urban geological information database to ensure the consistency of term use for fields. Model dictionary is used to generate a database operation interface automatically with standard semantic content via term and code dictionary. The above method and technology have been applied to the construction of Fuzhou Urban Geological Information System, South-East China with satisfactory results.

Reduced Fragment Diversity for Alpha and Alpha-Beta Protein Structure Prediction using Rosetta.

PubMed

Abbass, Jad; Nebel, Jean-Christophe

2017-01-01

Protein structure prediction is considered a main challenge in computational biology. The biannual international competition, Critical Assessment of protein Structure Prediction (CASP), has shown in its eleventh experiment that free modelling target predictions are still beyond reliable accuracy, therefore, much effort should be made to improve ab initio methods. Arguably, Rosetta is considered as the most competitive method when it comes to targets with no homologues. Relying on fragments of length 9 and 3 from known structures, Rosetta creates putative structures by assembling candidate fragments. Generally, the structure with the lowest energy score, also known as first model, is chosen to be the "predicted one". A thorough study has been conducted on the role and diversity of 3-mers involved in Rosetta's model "refinement" phase. Usage of the standard number of 3-mers - i.e. 200 - has been shown to degrade alpha and alpha-beta protein conformations initially achieved by assembling 9-mers. Therefore, a new prediction pipeline is proposed for Rosetta where the "refinement" phase is customised according to a target's structural class prediction. Over 8% improvement in terms of first model structure accuracy is reported for alpha and alpha-beta classes when decreasing the number of 3- mers. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Homology Modeling of Dopamine D2 and D3 Receptors: Molecular Dynamics Refinement and Docking Evaluation

PubMed Central

Platania, Chiara Bianca Maria; Salomone, Salvatore; Leggio, Gian Marco; Drago, Filippo; Bucolo, Claudio

2012-01-01

Dopamine (DA) receptors, a class of G-protein coupled receptors (GPCRs), have been targeted for drug development for the treatment of neurological, psychiatric and ocular disorders. The lack of structural information about GPCRs and their ligand complexes has prompted the development of homology models of these proteins aimed at structure-based drug design. Crystal structure of human dopamine D3 (hD3) receptor has been recently solved. Based on the hD3 receptor crystal structure we generated dopamine D2 and D3 receptor models and refined them with molecular dynamics (MD) protocol. Refined structures, obtained from the MD simulations in membrane environment, were subsequently used in molecular docking studies in order to investigate potential sites of interaction. The structure of hD3 and hD2L receptors was differentiated by means of MD simulations and D3 selective ligands were discriminated, in terms of binding energy, by docking calculation. Robust correlation of computed and experimental Ki was obtained for hD3 and hD2L receptor ligands. In conclusion, the present computational approach seems suitable to build and refine structure models of homologous dopamine receptors that may be of value for structure-based drug discovery of selective dopaminergic ligands. PMID:22970199

Synthesis for Structure Rewriting Systems

NASA Astrophysics Data System (ADS)

Kaiser, Łukasz

The description of a single state of a modelled system is often complex in practice, but few procedures for synthesis address this problem in depth. We study systems in which a state is described by an arbitrary finite structure, and changes of the state are represented by structure rewriting rules, a generalisation of term and graph rewriting. Both the environment and the controller are allowed to change the structure in this way, and the question we ask is how a strategy for the controller that ensures a given property can be synthesised.

Structural mechanics of 3-D braided preforms for composites. IV - The 4-step tubular braiding

NASA Technical Reports Server (NTRS)

Hammad, M.; El-Messery, M.; El-Shiekh, A.

1991-01-01

This paper presents the fundamentals of the 4-step 3D tubular braiding process and the structure of the preforms produced. Based on an idealized structural model, geometric relations between the structural parameters of the preform are analytically established. The effects of machine arrangement and operating conditions are discussed. Yarn retraction, yarn surface angle, outside diameter, and yarn volume fraction of the preform in terms of the pitch length, the inner diameter, and the machine arrangement are theoretically predicted and experimentally verified.

Unfolding and melting of DNA (RNA) hairpins: the concept of structure-specific 2D dynamic landscapes.

PubMed

Lin, Milo M; Meinhold, Lars; Shorokhov, Dmitry; Zewail, Ahmed H

2008-08-07

A 2D free-energy landscape model is presented to describe the (un)folding transition of DNA/RNA hairpins, together with molecular dynamics simulations and experimental findings. The dependence of the (un)folding transition on the stem sequence and the loop length is shown in the enthalpic and entropic contributions to the free energy. Intermediate structures are well defined by the two coordinates of the landscape during (un)zipping. Both the free-energy landscape model and the extensive molecular dynamics simulations totaling over 10 mus predict the existence of temperature-dependent kinetic intermediate states during hairpin (un)zipping and provide the theoretical description of recent ultrafast temperature-jump studies which indicate that hairpin (un)zipping is, in general, not a two-state process. The model allows for lucid prediction of the collapsed state(s) in simple 2D space and we term it the kinetic intermediate structure (KIS) model.

A Self-Regulatory Model of Behavioral Disinhibition in Late Adolescence: Integrating Personality Traits, Externalizing Psychopathology, and Cognitive Capacity

PubMed Central

Bogg, Tim; Finn, Peter R.

2011-01-01

Two samples with heterogeneous prevalence of externalizing psychopathology were used to investigate the structure of self-regulatory models of behavioral disinhibition and cognitive capacity. Consistent with expectations, structural equation modeling in the first sample (N = 541) showed a hierarchical model with three lower-order factors of impulsive sensation-seeking, anti-sociality/unconventionality, and lifetime externalizing problem counts, with a behavioral disinhibition superfactor best accounted for the pattern of covariation among six disinhibited personality trait indicators and four externalizing problem indicators. The structure was replicated in a second sample (N = 463) and showed that the behavioral disinhibition superfactor, and not the lower-order impulsive sensation-seeking, anti-sociality/unconventionality, and externalizing problem factors, was associated with lower IQ, reduced short-term memory capacity, and reduced working memory capacity. The results provide a systemic and meaningful integration of major self-regulatory influences during a developmentally important stage of life. PMID:20433626

Confirmatory factor analysis of the Early Arithmetic, Reading, and Learning Indicators (EARLI)☆

PubMed Central

Norwalk, Kate E.; DiPerna, James Clyde; Lei, Pui-Wa

2015-01-01

Despite growing interest in early intervention, there are few measures available to monitor the progress of early academic skills in preschoolers. The Early Arithmetic, Reading, and Learning Indicators (EARLI; DiPerna, Morgan, & Lei, 2007) were developed as brief assessments of critical early literacy and numeracy skills. The purpose of the current study was to examine the factor structure of the EARLI probes via confirmatory factor analysis (CFA) in a sample of Head Start preschoolers (N = 289). A two-factor model with correlated error terms and a bifactor model provided comparable fit to the data, although there were some structural problems with the latter model. The utility of the bifactor model for explaining the structure of early academic skills as well as the utility of the EARLI probes as measures of literacy and numeracy skills in preschool are discussed. PMID:24495496

Market Efficiency and the Risks and Returns of Dynamic Trading Strategies with Commodity Futures

NASA Astrophysics Data System (ADS)

Switzer, Lorne N.; Jiang, Hui

This paper investigates relationships between profits from dynamic trading strategies, risk premium, convenience yields, and net hedging pressures for commodity futures. As a market efficiency study, it crosses a number of disciplines, including traditional finance, behavioral finance, and behavioral psychology. The term structure of oil, gold, copper and soybeans futures markets contains predictive power for the corresponding term premium. However, only oil futures and soybean futures lead their spot premium. Significant momentum profits are identified in both outright futures and spread trading strategies when the spot premium and the term premium are used to form winner and loser portfolios. Profits from active strategies based on winner and loser portfolios are conditioned on market structure and net hedging pressure effects. Dynamic trading strategies based on contracts with extreme backwardation, extreme contango, and extreme hedging pressures are also tested. On average, spread trading outperforms outright futures trading in capturing the term structure risk and hedging pressure risk. For such strategies, long-short the long-term spread offers the greatest and most significant return and it offers the only exploitable trading profits built on the past hedging pressure. The existence of profits from active trading strategies based on winners is consistent with behavioral finance and behavioral psychology models in which market participants irrationally overreact to information and trends.

Strategic directions for agent-based modeling: avoiding the YAAWN syndrome

PubMed Central

O’Sullivan, David; Evans, Tom; Manson, Steven; Metcalf, Sara; Ligmann-Zielinska, Arika; Bone, Chris

2015-01-01

In this short communication, we examine how agent-based modeling has become common in land change science and is increasingly used to develop case studies for particular times and places. There is a danger that the research community is missing a prime opportunity to learn broader lessons from the use of agent-based modeling (ABM), or at the very least not sharing these lessons more widely. How do we find an appropriate balance between empirically rich, realistic models and simpler theoretically grounded models? What are appropriate and effective approaches to model evaluation in light of uncertainties not only in model parameters but also in model structure? How can we best explore hybrid model structures that enable us to better understand the dynamics of the systems under study, recognizing that no single approach is best suited to this task? Under what circumstances – in terms of model complexity, model evaluation, and model structure – can ABMs be used most effectively to lead to new insight for stakeholders? We explore these questions in the hope of helping the growing community of land change scientists using models in their research to move from ‘yet another model’ to doing better science with models. PMID:27158257

Advances in Chemical and Structural Characterization of Concretion with Implications for Modeling Marine Corrosion

NASA Astrophysics Data System (ADS)

Johnson, Donald L.; DeAngelis, Robert J.; Medlin, Dana J.; Carr, James D.; Conlin, David L.

2014-05-01

The Weins number model and concretion equivalent corrosion rate methodology were developed as potential minimum-impact, cost-effective techniques to determine corrosion damage on submerged steel structures. To apply the full potential of these technologies, a detailed chemical and structural characterization of the concretion (hard biofouling) that transforms into iron bearing minerals is required. The fractions of existing compounds and the quantitative chemistries are difficult to determine from x-ray diffraction. Environmental scanning electron microscopy was used to present chemical compositions by means of energy-dispersive spectroscopy (EDS). EDS demonstrates the chemical data in mapping format or in point or selected area chemistries. Selected-area EDS data collection at precise locations is presented in terms of atomic percent. The mechanism of formation and distribution of the iron-bearing mineral species at specific locations will be presented. Based on water retention measurements, porosity in terms of void volume varies from 15 v/o to 30 v/o (vol.%). The void path displayed by scanning electron microscopy imaging illustrates the tortuous path by which oxygen migrates in the water phase within the concretion from seaside to metalside.

The Phase Space Structure Near Neptune Resonances in the Kuiper Belt

NASA Technical Reports Server (NTRS)

Malhotra, Renu

1996-01-01

The Solar system beyond Neptune is believed to house a population of small primordial bodies left over from the planet formation process. The region up to heliocentric distance -50 AU (a.k.a. the Kuiper Belt) may be the source of the observed short-period comets. In this region, the phase space structure near orbital resonances with Neptune is of special interest for the long-term stability of orbits. There is reason to believe that a significant fraction (perhaps most) of the Kuiper Belt objects reside preferentially in these resonance locations. This paper describes the dynamics of small objects near the major orbital resonances with Neptune. Estimates of the widths of stable resonance zones as well as the properties of resonant orbits are obtained from the circular, planar restricted three-body model. Although this model does not contain the full complexity of the long-term orbital dynamics of Kuiper Belt objects subject to the full N-body perturbations of all the planets, it does provide a baseline for the phase space structure and properties of resonant orbits in the trans-Neptunian Solar system.

A supersymmetric grand unified model with noncompact horizontal symmetry

NASA Astrophysics Data System (ADS)

Yamatsu, Naoki

2013-12-01

In a supersymmetric SU(5) grand unified model with a horizontal symmetry SU(1,1), we discuss spontaneous generation of generations to produce three chiral generations of quarks and leptons and one generation of Higgses by using one structure field with a half-integer spin of SU(1,1) and two structure fields with integer spins. In particular, the colored Higgses can disappear without fine-tuning. The difference of the Yukawa coupling matrices between the down-type quarks and charged leptons is discussed. We show that some special SU(1,1) weight assignments include R-parity as a discrete subgroup, and R-parity remains even after we take into account the SU(1,1) breaking effects from all the vacuum expectation values of the structure and matter fields. The assignments forbid the baryon and/or lepton number violating terms except a superpotential quartic term including a coupling of two lepton doublets and two up-type Higgses. We discuss how to generate sizable neutrino masses. We show that the proton decay derived from the colored Higgses is highly suppressed.

Introduction and application of the multiscale coefficient of variation analysis.

PubMed

Abney, Drew H; Kello, Christopher T; Balasubramaniam, Ramesh

2017-10-01

Quantifying how patterns of behavior relate across multiple levels of measurement typically requires long time series for reliable parameter estimation. We describe a novel analysis that estimates patterns of variability across multiple scales of analysis suitable for time series of short duration. The multiscale coefficient of variation (MSCV) measures the distance between local coefficient of variation estimates within particular time windows and the overall coefficient of variation across all time samples. We first describe the MSCV analysis and provide an example analytical protocol with corresponding MATLAB implementation and code. Next, we present a simulation study testing the new analysis using time series generated by ARFIMA models that span white noise, short-term and long-term correlations. The MSCV analysis was observed to be sensitive to specific parameters of ARFIMA models varying in the type of temporal structure and time series length. We then apply the MSCV analysis to short time series of speech phrases and musical themes to show commonalities in multiscale structure. The simulation and application studies provide evidence that the MSCV analysis can discriminate between time series varying in multiscale structure and length.

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

Field, Kevin G.; Yang, Ying; Busby, Jeremy T.

Radiation induced segregation (RIS) is a well-studied phenomena which occurs in many structurally relevant nuclear materials including austenitic stainless steels. RIS occurs due to solute atoms preferentially coupling to mobile point defect fluxes that migrate and interact with defect sinks. Here, a 304 stainless steel was neutron irradiated up to 47.1 dpa at 320 °C. Investigations into the RIS response at specific grain boundary types were utilized to determine the sink characteristics of different boundary types as a function of irradiation dose. A rate theory model built on the foundation of the modified inverse Kirkendall (MIK) model is proposed andmore » benchmarked to the experimental results. This model, termed the GiMIK model, includes alterations in the boundary conditions based on grain boundary structure and includes expressions for interstitial binding. This investigation, through experiment and modeling, found specific grain boundary structures exhibit unique defect sink characteristics depending on their local structure. Furthermore, such interactions were found to be consistent across all doses investigated and had larger global implications including precipitation of Ni-Si clusters near different grain boundary types.« less

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

Field, Kevin G.; Yang, Ying; Allen, Todd R.

Radiation induced segregation (RIS) is a well-studied phenomena which occurs in many structurally relevant nuclear materials including austenitic stainless steels. RIS occurs due to solute atoms preferentially coupling to mobile point defect fluxes that migrate and interact with defect sinks. Here, a 304 stainless steel was neutron irradiated up to 47.1 dpa at 320 °C. Investigations into the RIS response at specific grain boundary types were utilized to determine the sink characteristics of different boundary types as a function of irradiation dose. A rate theory model built on the foundation of the modified inverse Kirkendall (MIK) model is proposed andmore » benchmarked to the experimental results. This model, termed the GiMIK model, includes alterations in the boundary conditions based on grain boundary structure and includes expressions for interstitial binding. This investigation, through experiment and modeling, found specific grain boundary structures exhibit unique defect sink characteristics depending on their local structure. Such interactions were found to be consistent across all doses investigated and had larger global implications including precipitation of Ni-Si clusters near different grain boundary types.« less

The anatomy of group dysfunction.

PubMed

Hayes, David F

2014-04-01

The dysfunction of the radiology group has 2 components: (1) the thinking component-the governance structure of the radiology group; how we manage the group; and (2) the structural component-the group's business model and its conflict with the partner's personal business model. Of the 2 components, governance is more important. Governance must be structured on classic, immutable business management principles. The structural component, the business model, is not immutable. In fact, it must continually change in response to the marketplace. Changes in the business model should occur only if demanded or permitted by the marketplace; instituting changes for other reasons, including personal interests or deficient knowledge of the deciders, is fundamentally contrary to the long-term interests of the group and its owners. First, we must learn basic business management concepts to appreciate the function and necessity of standard business models and standard business governance. Peter Drucker's The Effective Executive is an excellent primer on the subjects of standard business practices and the importance of a functional, authorized, and fully accountable chief executive officer. Copyright © 2014 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Track structure in biological models.

PubMed

Curtis, S B

1986-01-01

High-energy heavy ions in the galactic cosmic radiation (HZE particles) may pose a special risk during long term manned space flights outside the sheltering confines of the earth's geomagnetic field. These particles are highly ionizing, and they and their nuclear secondaries can penetrate many centimeters of body tissue. The three dimensional patterns of ionizations they create as they lose energy are referred to as their track structure. Several models of biological action on mammalian cells attempt to treat track structure or related quantities in their formulation. The methods by which they do this are reviewed. The proximity function is introduced in connection with the theory of Dual Radiation Action (DRA). The ion-gamma kill (IGK) model introduces the radial energy-density distribution, which is a smooth function characterizing both the magnitude and extension of a charged particle track. The lethal, potentially lethal (LPL) model introduces lambda, the mean distance between relevant ion clusters or biochemical species along the track. Since very localized energy depositions (within approximately 10 nm) are emphasized, the proximity function as defined in the DRA model is not of utility in characterizing track structure in the LPL formulation.

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.

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.

Two-dimensional joint inversion of Magnetotelluric and local earthquake data: Discussion on the contribution to the solution of deep subsurface structures

NASA Astrophysics Data System (ADS)

Demirci, İsmail; Dikmen, Ünal; Candansayar, M. Emin

2018-02-01

Joint inversion of data sets collected by using several geophysical exploration methods has gained importance and associated algorithms have been developed. To explore the deep subsurface structures, Magnetotelluric and local earthquake tomography algorithms are generally used individually. Due to the usage of natural resources in both methods, it is not possible to increase data quality and resolution of model parameters. For this reason, the solution of the deep structures with the individual usage of the methods cannot be fully attained. In this paper, we firstly focused on the effects of both Magnetotelluric and local earthquake data sets on the solution of deep structures and discussed the results on the basis of the resolving power of the methods. The presence of deep-focus seismic sources increase the resolution of deep structures. Moreover, conductivity distribution of relatively shallow structures can be solved with high resolution by using MT algorithm. Therefore, we developed a new joint inversion algorithm based on the cross gradient function in order to jointly invert Magnetotelluric and local earthquake data sets. In the study, we added a new regularization parameter into the second term of the parameter correction vector of Gallardo and Meju (2003). The new regularization parameter is enhancing the stability of the algorithm and controls the contribution of the cross gradient term in the solution. The results show that even in cases where resistivity and velocity boundaries are different, both methods influence each other positively. In addition, the region of common structural boundaries of the models are clearly mapped compared with original models. Furthermore, deep structures are identified satisfactorily even with using the minimum number of seismic sources. In this paper, in order to understand the future studies, we discussed joint inversion of Magnetotelluric and local earthquake data sets only in two-dimensional space. In the light of these results and by means of the acceleration on the three-dimensional modelling and inversion algorithms, it is thought that it may be easier to identify underground structures with high resolution.

Tunable assembly of amyloid-forming peptides into nanosheets as a retrovirus carrier.

PubMed

Dai, Bin; Li, Dan; Xi, Wenhui; Luo, Fang; Zhang, Xiang; Zou, Man; Cao, Mi; Hu, Jun; Wang, Wenyuan; Wei, Guanghong; Zhang, Yi; Liu, Cong

2015-03-10

Using and engineering amyloid as nanomaterials are blossoming trends in bionanotechnology. Here, we show our discovery of an amyloid structure, termed "amyloid-like nanosheet," formed by a key amyloid-forming segment of Alzheimer's Aβ. Combining multiple biophysical and computational approaches, we proposed a structural model for the nanosheet that is formed by stacking the amyloid fibril spines perpendicular to the fibril axis. We further used the nanosheet for laboratorial retroviral transduction enhancement and directly visualized the presence of virus on the nanosheet surface by electron microscopy. Furthermore, based on our structural model, we designed nanosheet-forming peptides with different functionalities, elucidating the potential of rational design for amyloid-based materials with novel architecture and function.

IT vendor selection model by using structural equation model & analytical hierarchy process

NASA Astrophysics Data System (ADS)

Maitra, Sarit; Dominic, P. D. D.

2012-11-01

Selecting and evaluating the right vendors is imperative for an organization's global marketplace competitiveness. Improper selection and evaluation of potential vendors can dwarf an organization's supply chain performance. Numerous studies have demonstrated that firms consider multiple criteria when selecting key vendors. This research intends to develop a new hybrid model for vendor selection process with better decision making. The new proposed model provides a suitable tool for assisting decision makers and managers to make the right decisions and select the most suitable vendor. This paper proposes a Hybrid model based on Structural Equation Model (SEM) and Analytical Hierarchy Process (AHP) for long-term strategic vendor selection problems. The five steps framework of the model has been designed after the thorough literature study. The proposed hybrid model will be applied using a real life case study to assess its effectiveness. In addition, What-if analysis technique will be used for model validation purpose.

Kinklike structures in models of the Dirac-Born-Infeld type

NASA Astrophysics Data System (ADS)

Bazeia, D.; Lima, Elisama E. M.; Losano, L.

2018-01-01

The present work investigates several models of a single real scalar field, engendering kinetic term of the Dirac-Born- Infeld type. Such theories introduce nonlinearities to the kinetic part of the Lagrangian, which presents a square root restricting the field evolution and including additional powers in derivatives of the scalar field, controlled by a real parameter. In order to obtain topological solutions analytically, we propose a first-order framework that simplifies the equation of motion ensuring solutions that are linearly stable. This is implemented using the deformation method, and we introduce examples presenting two categories of potentials, one having polynomial interactions and the other with nonpolynomial interactions. We also explore how the Dirac-Born-Infeld kinetic term affects the properties of the solutions. In particular, we note that the kinklike solutions are similar to the ones obtained through models with standard kinetic term and canonical potential, but their energy densities and stability potentials vary according to the parameter introduced to control the new models.

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

Impact of model structure on flow simulation and hydrological realism: from a lumped to a semi-distributed approach

NASA Astrophysics Data System (ADS)

Garavaglia, Federico; Le Lay, Matthieu; Gottardi, Fréderic; Garçon, Rémy; Gailhard, Joël; Paquet, Emmanuel; Mathevet, Thibault

2017-08-01

Model intercomparison experiments are widely used to investigate and improve hydrological model performance. However, a study based only on runoff simulation is not sufficient to discriminate between different model structures. Hence, there is a need to improve hydrological models for specific streamflow signatures (e.g., low and high flow) and multi-variable predictions (e.g., soil moisture, snow and groundwater). This study assesses the impact of model structure on flow simulation and hydrological realism using three versions of a hydrological model called MORDOR: the historical lumped structure and a revisited formulation available in both lumped and semi-distributed structures. In particular, the main goal of this paper is to investigate the relative impact of model equations and spatial discretization on flow simulation, snowpack representation and evapotranspiration estimation. Comparison of the models is based on an extensive dataset composed of 50 catchments located in French mountainous regions. The evaluation framework is founded on a multi-criterion split-sample strategy. All models were calibrated using an automatic optimization method based on an efficient genetic algorithm. The evaluation framework is enriched by the assessment of snow and evapotranspiration modeling against in situ and satellite data. The results showed that the new model formulations perform significantly better than the initial one in terms of the various streamflow signatures, snow and evapotranspiration predictions. The semi-distributed approach provides better calibration-validation performance for the snow cover area, snow water equivalent and runoff simulation, especially for nival catchments.

Ontology-based structured cosine similarity in document summarization: with applications to mobile audio-based knowledge management.

PubMed

Yuan, Soe-Tsyr; Sun, Jerry

2005-10-01

Development of algorithms for automated text categorization in massive text document sets is an important research area of data mining and knowledge discovery. Most of the text-clustering methods were grounded in the term-based measurement of distance or similarity, ignoring the structure of the documents. In this paper, we present a novel method named structured cosine similarity (SCS) that furnishes document clustering with a new way of modeling on document summarization, considering the structure of the documents so as to improve the performance of document clustering in terms of quality, stability, and efficiency. This study was motivated by the problem of clustering speech documents (of no rich document features) attained from the wireless experience oral sharing conducted by mobile workforce of enterprises, fulfilling audio-based knowledge management. In other words, this problem aims to facilitate knowledge acquisition and sharing by speech. The evaluations also show fairly promising results on our method of structured cosine similarity.

The impact of experimental measurement errors on long-term viscoelastic predictions. [of structural materials

NASA Technical Reports Server (NTRS)

Tuttle, M. E.; Brinson, H. F.

1986-01-01

The impact of flight error in measured viscoelastic parameters on subsequent long-term viscoelastic predictions is numerically evaluated using the Schapery nonlinear viscoelastic model. Of the seven Schapery parameters, the results indicated that long-term predictions were most sensitive to errors in the power law parameter n. Although errors in the other parameters were significant as well, errors in n dominated all other factors at long times. The process of selecting an appropriate short-term test cycle so as to insure an accurate long-term prediction was considered, and a short-term test cycle was selected using material properties typical for T300/5208 graphite-epoxy at 149 C. The process of selection is described, and its individual steps are itemized.

Evaluation of the UnTRIM model for 3-D tidal circulation

USGS Publications Warehouse

Cheng, R.T.; Casulli, V.; ,

2001-01-01

A family of numerical models, known as the TRIM models, shares the same modeling philosophy for solving the shallow water equations. A characteristic analysis of the shallow water equations points out that the numerical instability is controlled by the gravity wave terms in the momentum equations and by the transport terms in the continuity equation. A semi-implicit finite-difference scheme has been formulated so that these terms and the vertical diffusion terms are treated implicitly and the remaining terms explicitly to control the numerical stability and the computations are carried out over a uniform finite-difference computational mesh without invoking horizontal or vertical coordinate transformations. An unstructured grid version of TRIM model is introduced, or UnTRIM (pronounces as "you trim"), which preserves these basic numerical properties and modeling philosophy, only the computations are carried out over an unstructured orthogonal grid. The unstructured grid offers the flexibilities in representing complex study areas so that fine grid resolution can be placed in regions of interest, and coarse grids are used to cover the remaining domain. Thus, the computational efforts are concentrated in areas of importance, and an overall computational saving can be achieved because the total number of grid-points is dramatically reduced. To use this modeling approach, an unstructured grid mesh must be generated to properly reflect the properties of the domain of the investigation. The new modeling flexibility in grid structure is accompanied by new challenges associated with issues of grid generation. To take full advantage of this new model flexibility, the model grid generation should be guided by insights into the physics of the problems; and the insights needed may require a higher degree of modeling skill.

The Social Structuring of Mental Health over the Adult Life Course: Advancing Theory in the Sociology of Aging

ERIC Educational Resources Information Center

Clarke, Philippa; Marshall, Victor; House, James; Lantz, Paula

2011-01-01

The sociology of aging draws on a broad array of theoretical perspectives and social theories from several disciplines, but rarely has it developed its own theories or theoretical perspectives. We build on past work to further advance and empirically test a model of mental health framed in terms of structural theorizing and situated within the…

Modifiability Tactics

DTIC Science & Technology

2007-09-01

The Pattern Understood in Terms of Tactics 44 13.4 Variants 44 14 Microkernel Pattern 45 14.1 Problem 45 14.2 Solution 45 14.3 The Pattern...Figure 12: Model-View-Controller Pattern Structure 42 Figure 13: Presentation-Abstraction-Control Pattern Structure 43 Figure 14: Microkernel ...Presentation- Abstraction- Control X X X X Microkernel X X X X X Reflection X X Each pattern is described in more detail in the

Testing inhomogeneous solvation theory in structure-based ligand discovery.

PubMed

Balius, Trent E; Fischer, Marcus; Stein, Reed M; Adler, Thomas B; Nguyen, Crystal N; Cruz, Anthony; Gilson, Michael K; Kurtzman, Tom; Shoichet, Brian K

2017-08-15

Binding-site water is often displaced upon ligand recognition, but is commonly neglected in structure-based ligand discovery. Inhomogeneous solvation theory (IST) has become popular for treating this effect, but it has not been tested in controlled experiments at atomic resolution. To do so, we turned to a grid-based version of this method, GIST, readily implemented in molecular docking. Whereas the term only improves docking modestly in retrospective ligand enrichment, it could be added without disrupting performance. We thus turned to prospective docking of large libraries to investigate GIST's impact on ligand discovery, geometry, and water structure in a model cavity site well-suited to exploring these terms. Although top-ranked docked molecules with and without the GIST term often overlapped, many ligands were meaningfully prioritized or deprioritized; some of these were selected for testing. Experimentally, 13/14 molecules prioritized by GIST did bind, whereas none of the molecules that it deprioritized were observed to bind. Nine crystal complexes were determined. In six, the ligand geometry corresponded to that predicted by GIST, for one of these the pose without the GIST term was wrong, and three crystallographic poses differed from both predictions. Notably, in one structure, an ordered water molecule with a high GIST displacement penalty was observed to stay in place. Inclusion of this water-displacement term can substantially improve the hit rates and ligand geometries from docking screens, although the magnitude of its effects can be small and its impact in drug binding sites merits further controlled studies.

An evaluation of Bayesian techniques for controlling model complexity and selecting inputs in a neural network for short-term load forecasting.

PubMed

Hippert, Henrique S; Taylor, James W

2010-04-01

Artificial neural networks have frequently been proposed for electricity load forecasting because of their capabilities for the nonlinear modelling of large multivariate data sets. Modelling with neural networks is not an easy task though; two of the main challenges are defining the appropriate level of model complexity, and choosing the input variables. This paper evaluates techniques for automatic neural network modelling within a Bayesian framework, as applied to six samples containing daily load and weather data for four different countries. We analyse input selection as carried out by the Bayesian 'automatic relevance determination', and the usefulness of the Bayesian 'evidence' for the selection of the best structure (in terms of number of neurones), as compared to methods based on cross-validation. Copyright 2009 Elsevier Ltd. All rights reserved.

Unified dead-time compensation structure for SISO processes with multiple dead times.

PubMed

Normey-Rico, Julio E; Flesch, Rodolfo C C; Santos, Tito L M

2014-11-01

This paper proposes a dead-time compensation structure for processes with multiple dead times. The controller is based on the filtered Smith predictor (FSP) dead-time compensator structure and it is able to control stable, integrating, and unstable processes with multiple input/output dead times. An equivalent model of the process is first computed in order to define the predictor structure. Using this equivalent model, the primary controller and the predictor filter are tuned to obtain an internally stable closed-loop system which also attempts some closed-loop specifications in terms of set-point tracking, disturbance rejection, and robustness. Some simulation case studies are used to illustrate the good properties of the proposed approach. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Nonlinear Shell Modeling of Thin Membranes with Emphasis on Structural Wrinkling

NASA Technical Reports Server (NTRS)

Tessler, Alexander; Sleight, David W.; Wang, John T.

2003-01-01

Thin solar sail membranes of very large span are being envisioned for near-term space missions. One major design issue that is inherent to these very flexible structures is the formation of wrinkling patterns. Structural wrinkles may deteriorate a solar sail's performance and, in certain cases, structural integrity. In this paper, a geometrically nonlinear, updated Lagrangian shell formulation is employed using the ABAQUS finite element code to simulate the formation of wrinkled deformations in thin-film membranes. The restrictive assumptions of true membranes, i.e. Tension Field theory (TF), are not invoked. Two effective modeling strategies are introduced to facilitate convergent solutions of wrinkled equilibrium states. Several numerical studies are carried out, and the results are compared with recent experimental data. Good agreement is observed between the numerical simulations and experimental data.

Comparative analysis of predictive models for nongenotoxic hepatocarcinogenicity using both toxicogenomics and quantitative structure-activity relationships.

PubMed

Liu, Zhichao; Kelly, Reagan; Fang, Hong; Ding, Don; Tong, Weida

2011-07-18

The primary testing strategy to identify nongenotoxic carcinogens largely relies on the 2-year rodent bioassay, which is time-consuming and labor-intensive. There is an increasing effort to develop alternative approaches to prioritize the chemicals for, supplement, or even replace the cancer bioassay. In silico approaches based on quantitative structure-activity relationships (QSAR) are rapid and inexpensive and thus have been investigated for such purposes. A slightly more expensive approach based on short-term animal studies with toxicogenomics (TGx) represents another attractive option for this application. Thus, the primary questions are how much better predictive performance using short-term TGx models can be achieved compared to that of QSAR models, and what length of exposure is sufficient for high quality prediction based on TGx. In this study, we developed predictive models for rodent liver carcinogenicity using gene expression data generated from short-term animal models at different time points and QSAR. The study was focused on the prediction of nongenotoxic carcinogenicity since the genotoxic chemicals can be inexpensively removed from further development using various in vitro assays individually or in combination. We identified 62 chemicals whose hepatocarcinogenic potential was available from the National Center for Toxicological Research liver cancer database (NCTRlcdb). The gene expression profiles of liver tissue obtained from rats treated with these chemicals at different time points (1 day, 3 days, and 5 days) are available from the Gene Expression Omnibus (GEO) database. Both TGx and QSAR models were developed on the basis of the same set of chemicals using the same modeling approach, a nearest-centroid method with a minimum redundancy and maximum relevancy-based feature selection with performance assessed using compound-based 5-fold cross-validation. We found that the TGx models outperformed QSAR in every aspect of modeling. For example, the TGx models' predictive accuracy (0.77, 0.77, and 0.82 for the 1-day, 3-day, and 5-day models, respectively) was much higher for an independent validation set than that of a QSAR model (0.55). Permutation tests confirmed the statistical significance of the model's prediction performance. The study concluded that a short-term 5-day TGx animal model holds the potential to predict nongenotoxic hepatocarcinogenicity. © 2011 American Chemical Society

Multiple model self-tuning control for a class of nonlinear systems

NASA Astrophysics Data System (ADS)

Huang, Miao; Wang, Xin; Wang, Zhenlei

2015-10-01

This study develops a novel nonlinear multiple model self-tuning control method for a class of nonlinear discrete-time systems. An increment system model and a modified robust adaptive law are proposed to expand the application range, thus eliminating the assumption that either the nonlinear term of the nonlinear system or its differential term is global-bounded. The nonlinear self-tuning control method can address the situation wherein the nonlinear system is not subject to a globally uniformly asymptotically stable zero dynamics by incorporating the pole-placement scheme. A novel, nonlinear control structure based on this scheme is presented to improve control precision. Stability and convergence can be confirmed when the proposed multiple model self-tuning control method is applied. Furthermore, simulation results demonstrate the effectiveness of the proposed method.

A general description of detachment for multidimensional modelling of biofilms.

PubMed

Xavier, Joao de Bivar; Picioreanu, Cristian; van Loosdrecht, Mark C M

2005-09-20

A general method for describing biomass detachment in multidimensional biofilm modelling is introduced. Biomass losses from processes acting on the entire surface of the biofilm, such as erosion, are modelled using a continuous detachment speed function F(det). Discrete detachment events, i.e. sloughing, are implicitly derived from simulations. The method is flexible to allow F(det) to take several forms, including expressions dependent on any state variables such as the local biofilm density. This methodology for biomass detachment was integrated with multidimensional (2D and 3D) particle-based multispecies biofilm models by using a novel application of the level set method. Application of the method is illustrated by trends in the dynamics of biofilms structure and activity derived from simulations performed on a simple model considering uniform biomass (case study I) and a model discriminating biomass composition in heterotrophic active mass, extracellular polymeric substances (EPS) and inert mass (case study II). Results from case study I demonstrate the effect of applied detachment forces as a fundamental factor influencing steady-state biofilm activity and structure. Trends from experimental observations reported in literature were correctly described. For example, simulation results indicated that biomass sloughing is reduced when erosion forces are increased. Case study II illustrates the application of the detachment methodology to systems with non-uniform biomass composition. Simulations carried out at different bulk concentrations of substrate show changes in biofilm structure (in terms of shape, density and spatial distribution of biomass components) and activity (in terms of oxygen and substrate consumption) as a consequence of either oxygen-limited or substrate-limited growth. (c) 2005 Wiley Periodicals, Inc.

Oral LD50 toxicity modeling and prediction of per- and polyfluorinated chemicals on rat and mouse.

PubMed

Bhhatarai, Barun; Gramatica, Paola

2011-05-01

Quantitative structure-activity relationship (QSAR) analyses were performed using the LD(50) oral toxicity data of per- and polyfluorinated chemicals (PFCs) on rodents: rat and mouse. PFCs are studied under the EU project CADASTER which uses the available experimental data for prediction and prioritization of toxic chemicals for risk assessment by using the in silico tools. The methodology presented here applies chemometrical analysis on the existing experimental data and predicts the toxicity of new compounds. QSAR analyses were performed on the available 58 mouse and 50 rat LD(50) oral data using multiple linear regression (MLR) based on theoretical molecular descriptors selected by genetic algorithm (GA). Training and prediction sets were prepared a priori from available experimental datasets in terms of structure and response. These sets were used to derive statistically robust and predictive (both internally and externally) models. The structural applicability domain (AD) of the models were verified on 376 per- and polyfluorinated chemicals including those in REACH preregistration list. The rat and mouse endpoints were predicted by each model for the studied compounds, and finally 30 compounds, all perfluorinated, were prioritized as most important for experimental toxicity analysis under the project. In addition, cumulative study on compounds within the AD of all four models, including two earlier published models on LC(50) rodent analysis was studied and the cumulative toxicity trend was observed using principal component analysis (PCA). The similarities and the differences observed in terms of descriptors and chemical/mechanistic meaning encoded by descriptors to prioritize the most toxic compounds are highlighted.

Phase-Field Modeling of Polycrystalline Solidification: From Needle Crystals to Spherulites—A Review

NASA Astrophysics Data System (ADS)

Gránásy, László; Rátkai, László; Szállás, Attila; Korbuly, Bálint; Tóth, Gyula I.; Környei, László; Pusztai, Tamás

2014-04-01

Advances in the orientation-field-based phase-field (PF) models made in the past are reviewed. The models applied incorporate homogeneous and heterogeneous nucleation of growth centers and several mechanisms to form new grains at the perimeter of growing crystals, a phenomenon termed growth front nucleation. Examples for PF modeling of such complex polycrystalline structures are shown as impinging symmetric dendrites, polycrystalline growth forms (ranging from disordered dendrites to spherulitic patterns), and various eutectic structures, including spiraling two-phase dendrites. Simulations exploring possible control of solidification patterns in thin films via external fields, confined geometry, particle additives, scratching/piercing the films, etc. are also displayed. Advantages, problems, and possible solutions associated with quantitative PF simulations are discussed briefly.

Importance of Kier-Hall topological indices in the QSAR of anticancer drug design.

PubMed

Nandi, Sisir; Bagchi, Manish C

2012-06-01

An important area of theoretical drug design research is quantitative structure activity relationship (QSAR) using structural invariants. The impetus for this research trend comes from various directions. Researchers in chemical documentation have searched for a set of invariants which will be more convenient than the adjacency matrix (or connection table) for the storage and comparison of chemical structures. Molecular structure can be looked upon as the representation of the relationship among its various constituents. The term molecular structure represents a set of nonequivalent and probably disjoint concepts. There is no reason to believe that when we discuss diverse topics (e.g. chemical synthesis, reaction rates, spectroscopic transitions, reaction mechanisms, and ab initio calculations) using the notion of molecular structure, the different meanings we attach to the single term molecular structure originate from the same fundamental concept. On the contrary, there is a theoretical and philosophical basis for the non-homogeneity of concepts covered by the term molecular structure. In the context of molecular science, the various concepts of molecular structure (e.g. classical valence bond representations, various chemical graph-theoretic representations, ball and spoke model of a molecule, representation of a molecule by minimum energy conformation, semi symbolic contour map of a molecule, or symbolic representation of chemical species by Hamiltonian operators) are model objects derived through different abstractions of the same chemical reality. In each instance, the equivalence class (concept or model of molecular structure) is generated by selecting certain aspects while ignoring some unique properties of those actual events. This explains the plurality of the concept of molecular structure and their autonomous nature, the word autonomous being used in the same sense that one concept is not logically derived from the other. At the most fundamental level, the structural model of an assembled entity (e.g. a molecule consisting of atoms) may be defined as the pattern of relationship among its parts as distinct from the values associated with them. Constitutional formulae of molecules are graphs where vertices represent the set of atoms and edges represent chemical bonds. The pattern of connectedness of atoms in a molecule is preserved by constitutional graphs. A graph (more correctly a non-directed graph) G = [V, E] consists of a finite non-empty set V of points together with a prescribed set E of unordered pairs of distinct points of V. Thus the mathematical characterization of structures represents structural invariants having successful applications in chemical documentation, characterization of molecular branching, enumeration of molecular constitutional associated with a particular empirical formula, calculation of quantum chemical parameters for the generation of quantitative structure-property-activity correlations. Kier developed a number of structural invariants which are now-a-days called as topological indices with wide range of practical applications for QSAR and drug design. The present paper is restricted to the review of Kier-Hall topological indices for QSAR and anticancer drug design for 2,5-bis(1-aziridinyl) 1,4-benzoquinone (BABQ), pyridopyrimidine, 4-anilinoquinazoline and 2-Phenylindoles compounds utilizing various statistical multivariate regression analyses.

Modelling the influence of ionic and fluid transport on rebars corrosion in unsaturated cement systems

NASA Astrophysics Data System (ADS)

Dridi, W.; Dangla, P.; Foct, F.; Petre-Lazar, I.

2006-11-01

This paper deals with numerical modelling of rebar corrosion kinetics in unsaturated concrete structures. The corrosion kinetics is investigated in terms of mechanistic coupling between reaction rates at the steel surface and the ionic transport processes in the concrete pore system. The ionic and mass transport model consists of time-dependent equations for the concentration of dissolved species, the liquid pressure and the electrical potential. The complete set of nonlinear equations is solved using the finite-volume method. The nonlinear boundary conditions dealing with corrosion are introduced at the steel-concrete interface where they are implicitly coupled with the mass transport model in the concrete structure. Both the case of free corrosion and potentiostatic polarisation are discussed in a one dimensional model.

Evaluation of different inertial control methods for variable-speed wind turbines simulated by fatigue, aerodynamic, structures and turbulence (FAST)

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

Wang, Xiao; Gao, Wenzhong; Scholbrock, Andrew

To mitigate the degraded power system inertia and undesirable primary frequency response caused by large-scale wind power integration, the frequency support capabilities of variable-speed wind turbines is studied in this work. This is made possible by controlled inertial response, which is demonstrated on a research turbine - controls advanced research turbine, 3-bladed (CART3). Two distinct inertial control (IC) methods are analysed in terms of their impacts on the grids and the response of the turbine itself. The released kinetic energy in the IC methods are determined by the frequency measurement or shaped active power reference in the turbine speed-power plane.more » The wind turbine model is based on the high-fidelity turbine simulator fatigue, aerodynamic, structures and turbulence, which constitutes the aggregated wind power plant model with the simplified power converter model. The IC methods are implemented over the baseline CART3 controller, evaluated in the modified 9-bus and 14-bus testing power grids considering different wind speeds and different wind power penetration levels. The simulation results provide various insights on designing such kinds of ICs. The authors calculate the short-term dynamic equivalent loads and give a discussion about the turbine structural loadings related to the inertial response.« less

Stochastic model stationarization by eliminating the periodic term and its effect on time series prediction

NASA Astrophysics Data System (ADS)

Moeeni, Hamid; Bonakdari, Hossein; Fatemi, Seyed Ehsan

2017-04-01

Because time series stationarization has a key role in stochastic modeling results, three methods are analyzed in this study. The methods are seasonal differencing, seasonal standardization and spectral analysis to eliminate the periodic effect on time series stationarity. First, six time series including 4 streamflow series and 2 water temperature series are stationarized. The stochastic term for these series obtained with ARIMA is subsequently modeled. For the analysis, 9228 models are introduced. It is observed that seasonal standardization and spectral analysis eliminate the periodic term completely, while seasonal differencing maintains seasonal correlation structures. The obtained results indicate that all three methods present acceptable performance overall. However, model accuracy in monthly streamflow prediction is higher with seasonal differencing than with the other two methods. Another advantage of seasonal differencing over the other methods is that the monthly streamflow is never estimated as negative. Standardization is the best method for predicting monthly water temperature although it is quite similar to seasonal differencing, while spectral analysis performed the weakest in all cases. It is concluded that for each monthly seasonal series, seasonal differencing is the best stationarization method in terms of periodic effect elimination. Moreover, the monthly water temperature is predicted with more accuracy than monthly streamflow. The criteria of the average stochastic term divided by the amplitude of the periodic term obtained for monthly streamflow and monthly water temperature were 0.19 and 0.30, 0.21 and 0.13, and 0.07 and 0.04 respectively. As a result, the periodic term is more dominant than the stochastic term for water temperature in the monthly water temperature series compared to streamflow series.

Neonatal Pulmonary MRI of Bronchopulmonary Dysplasia Predicts Short-term Clinical Outcomes.

PubMed

Higano, Nara S; Spielberg, David R; Fleck, Robert J; Schapiro, Andrew H; Walkup, Laura L; Hahn, Andrew D; Tkach, Jean A; Kingma, Paul S; Merhar, Stephanie L; Fain, Sean B; Woods, Jason C

2018-05-23

Bronchopulmonary dysplasia (BPD) is a serious neonatal pulmonary condition associated with premature birth, but the underlying parenchymal disease and trajectory are poorly characterized. The current NICHD/NHLBI definition of BPD severity is based on degree of prematurity and extent of oxygen requirement. However, no clear link exists between initial diagnosis and clinical outcomes. We hypothesized that magnetic resonance imaging (MRI) of structural parenchymal abnormalities will correlate with NICHD-defined BPD disease severity and predict short-term respiratory outcomes. Forty-two neonates (20 severe BPD, 6 moderate, 7 mild, 9 non-BPD controls; 40±3 weeks post-menstrual age) underwent quiet-breathing structural pulmonary MRI (ultrashort echo-time and gradient echo) in a NICU-sited, neonatal-sized 1.5T scanner, without sedation or respiratory support unless already clinically prescribed. Disease severity was scored independently by two radiologists. Mean scores were compared to clinical severity and short-term respiratory outcomes. Outcomes were predicted using univariate and multivariable models including clinical data and scores. MRI scores significantly correlated with severities and predicted respiratory support at NICU discharge (P<0.0001). In multivariable models, MRI scores were by far the strongest predictor of respiratory support duration over clinical data, including birth weight and gestational age. Notably, NICHD severity level was not predictive of discharge support. Quiet-breathing neonatal pulmonary MRI can independently assess structural abnormalities of BPD, describe disease severity, and predict short-term outcomes more accurately than any individual standard clinical measure. Importantly, this non-ionizing technique can be implemented to phenotype disease and has potential to serially assess efficacy of individualized therapies.

Equivalent circuit models for interpreting impedance perturbation spectroscopy data

NASA Astrophysics Data System (ADS)

Smith, R. Lowell

2004-07-01

As in-situ structural integrity monitoring disciplines mature, there is a growing need to process sensor/actuator data efficiently in real time. Although smaller, faster embedded processors will contribute to this, it is also important to develop straightforward, robust methods to reduce the overall computational burden for practical applications of interest. This paper addresses the use of equivalent circuit modeling techniques for inferring structure attributes monitored using impedance perturbation spectroscopy. In pioneering work about ten years ago significant progress was associated with the development of simple impedance models derived from the piezoelectric equations. Using mathematical modeling tools currently available from research in ultrasonics and impedance spectroscopy is expected to provide additional synergistic benefits. For purposes of structural health monitoring the objective is to use impedance spectroscopy data to infer the physical condition of structures to which small piezoelectric actuators are bonded. Features of interest include stiffness changes, mass loading, and damping or mechanical losses. Equivalent circuit models are typically simple enough to facilitate the development of practical analytical models of the actuator-structure interaction. This type of parametric structure model allows raw impedance/admittance data to be interpreted optimally using standard multiple, nonlinear regression analysis. One potential long-term outcome is the possibility of cataloging measured viscoelastic properties of the mechanical subsystems of interest as simple lists of attributes and their statistical uncertainties, whose evolution can be followed in time. Equivalent circuit models are well suited for addressing calibration and self-consistency issues such as temperature corrections, Poisson mode coupling, and distributed relaxation processes.

End Effects and Load Diffusion in Composite Structures

NASA Technical Reports Server (NTRS)

Horgan, Cornelius O.; Ambur, D. (Technical Monitor); Nemeth, M. P. (Technical Monitor)

2002-01-01

The research carried out here builds on our previous NASA supported research on the general topic of edge effects and load diffusion in composite structures. Further fundamental solid mechanics studies were carried out to provide a basis for assessing the complicated modeling necessary for large scale structures used by NASA. An understanding of the fundamental mechanisms of load diffusion in composite subcomponents is essential in developing primary composite structures. Specific problems recently considered were focussed on end effects in sandwich structures and for functionally graded materials. Both linear and nonlinear (geometric and material) problems have been addressed. Our goal is the development of readily applicable design formulas for the decay lengths in terms of non-dimensional material and geometric parameters. Analytical models of load diffusion behavior are extremely valuable in building an intuitive base for developing refined modeling strategies and assessing results from finite element analyses. The decay behavior of stresses and other field quantities provides a significant aid towards this process. The analysis is also amenable to parameter study with a large parameter space and should be useful in structural tailoring studies.

Adaptive fuzzy logic controller with direct action type structures for InnoSAT attitude control system

NASA Astrophysics Data System (ADS)

Bakri, F. A.; Mashor, M. Y.; Sharun, S. M.; Bibi Sarpinah, S. N.; Abu Bakar, Z.

2016-10-01

This study proposes an adaptive fuzzy controller for attitude control system (ACS) of Innovative Satellite (InnoSAT) based on direct action type structure. In order to study new methods used in satellite attitude control, this paper presents three structures of controllers: Fuzzy PI, Fuzzy PD and conventional Fuzzy PID. The objective of this work is to compare the time response and tracking performance among the three different structures of controllers. The parameters of controller were tuned on-line by adjustment mechanism, which was an approach similar to a PID error that could minimize errors between actual and model reference output. This paper also presents a Model References Adaptive Control (MRAC) as a control scheme to control time varying systems where the performance specifications were given in terms of the reference model. All the controllers were tested using InnoSAT system under some operating conditions such as disturbance, varying gain, measurement noise and time delay. In conclusion, among all considered DA-type structures, AFPID controller was observed as the best structure since it outperformed other controllers in most conditions.

Protein side chain conformation predictions with an MMGBSA energy function.

PubMed

Gaillard, Thomas; Panel, Nicolas; Simonson, Thomas

2016-06-01

The prediction of protein side chain conformations from backbone coordinates is an important task in structural biology, with applications in structure prediction and protein design. It is a difficult problem due to its combinatorial nature. We study the performance of an "MMGBSA" energy function, implemented in our protein design program Proteus, which combines molecular mechanics terms, a Generalized Born and Surface Area (GBSA) solvent model, with approximations that make the model pairwise additive. Proteus is not a competitor to specialized side chain prediction programs due to its cost, but it allows protein design applications, where side chain prediction is an important step and MMGBSA an effective energy model. We predict the side chain conformations for 18 proteins. The side chains are first predicted individually, with the rest of the protein in its crystallographic conformation. Next, all side chains are predicted together. The contributions of individual energy terms are evaluated and various parameterizations are compared. We find that the GB and SA terms, with an appropriate choice of the dielectric constant and surface energy coefficients, are beneficial for single side chain predictions. For the prediction of all side chains, however, errors due to the pairwise additive approximation overcome the improvement brought by these terms. We also show the crucial contribution of side chain minimization to alleviate the rigid rotamer approximation. Even without GB and SA terms, we obtain accuracies comparable to SCWRL4, a specialized side chain prediction program. In particular, we obtain a better RMSD than SCWRL4 for core residues (at a higher cost), despite our simpler rotamer library. Proteins 2016; 84:803-819. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A new adaptive L1-norm for optimal descriptor selection of high-dimensional QSAR classification model for anti-hepatitis C virus activity of thiourea derivatives.

PubMed

Algamal, Z Y; Lee, M H

2017-01-01

A high-dimensional quantitative structure-activity relationship (QSAR) classification model typically contains a large number of irrelevant and redundant descriptors. In this paper, a new design of descriptor selection for the QSAR classification model estimation method is proposed by adding a new weight inside L1-norm. The experimental results of classifying the anti-hepatitis C virus activity of thiourea derivatives demonstrate that the proposed descriptor selection method in the QSAR classification model performs effectively and competitively compared with other existing penalized methods in terms of classification performance on both the training and the testing datasets. Moreover, it is noteworthy that the results obtained in terms of stability test and applicability domain provide a robust QSAR classification model. It is evident from the results that the developed QSAR classification model could conceivably be employed for further high-dimensional QSAR classification studies.

Modeling of Mixing Behavior in a Combined Blowing Steelmaking Converter with a Filter-Based Euler-Lagrange Model

NASA Astrophysics Data System (ADS)

Li, Mingming; Li, Lin; Li, Qiang; Zou, Zongshu

2018-05-01

A filter-based Euler-Lagrange multiphase flow model is used to study the mixing behavior in a combined blowing steelmaking converter. The Euler-based volume of fluid approach is employed to simulate the top blowing, while the Lagrange-based discrete phase model that embeds the local volume change of rising bubbles for the bottom blowing. A filter-based turbulence method based on the local meshing resolution is proposed aiming to improve the modeling of turbulent eddy viscosities. The model validity is verified through comparison with physical experiments in terms of mixing curves and mixing times. The effects of the bottom gas flow rate on bath flow and mixing behavior are investigated and the inherent reasons for the mixing result are clarified in terms of the characteristics of bottom-blowing plumes, the interaction between plumes and top-blowing jets, and the change of bath flow structure.

Generalization Technique for 2D+SCALE Dhe Data Model

NASA Astrophysics Data System (ADS)

Karim, Hairi; Rahman, Alias Abdul; Boguslawski, Pawel

2016-10-01

Different users or applications need different scale model especially in computer application such as game visualization and GIS modelling. Some issues has been raised on fulfilling GIS requirement of retaining the details while minimizing the redundancy of the scale datasets. Previous researchers suggested and attempted to add another dimension such as scale or/and time into a 3D model, but the implementation of scale dimension faces some problems due to the limitations and availability of data structures and data models. Nowadays, various data structures and data models have been proposed to support variety of applications and dimensionality but lack research works has been conducted in terms of supporting scale dimension. Generally, the Dual Half Edge (DHE) data structure was designed to work with any perfect 3D spatial object such as buildings. In this paper, we attempt to expand the capability of the DHE data structure toward integration with scale dimension. The description of the concept and implementation of generating 3D-scale (2D spatial + scale dimension) for the DHE data structure forms the major discussion of this paper. We strongly believed some advantages such as local modification and topological element (navigation, query and semantic information) in scale dimension could be used for the future 3D-scale applications.

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.

Active vision and image/video understanding with decision structures based on the network-symbolic models

NASA Astrophysics Data System (ADS)

Kuvich, Gary

2003-08-01

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. The ability of human brain to emulate knowledge structures in the form of networks-symbolic models is found. And that means an important shift of paradigm in our knowledge about brain from neural networks to "cortical software". Symbols, predicates and grammars naturally emerge in such active multilevel hierarchical networks, and logic is simply a way of restructuring such models. Brain analyzes an image as a graph-type decision structure created via multilevel hierarchical compression of visual information. Mid-level vision processes like clustering, perceptual grouping, separation of figure from ground, 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 are results of such analysis. Composition of network-symbolic models works similar to frames and agents, combines learning, classification, analogy together with higher-level model-based reasoning into a single framework. Such models do not require supercomputers. Based on such principles, and using methods of Computational intelligence, an Image Understanding system can convert images into the network-symbolic knowledge models, and effectively resolve uncertainty and ambiguity, providing unifying representation for perception and cognition. That allows creating new intelligent computer vision systems for robotic and defense industries.

A Simultaneous Equation Demand Model for Block Rates

NASA Astrophysics Data System (ADS)

Agthe, Donald E.; Billings, R. Bruce; Dobra, John L.; Raffiee, Kambiz

1986-01-01

This paper examines the problem of simultaneous-equations bias in estimation of the water demand function under an increasing block rate structure. The Hausman specification test is used to detect the presence of simultaneous-equations bias arising from correlation of the price measures with the regression error term in the results of a previously published study of water demand in Tucson, Arizona. An alternative simultaneous equation model is proposed for estimating the elasticity of demand in the presence of block rate pricing structures and availability of service charges. This model is used to reestimate the price and rate premium elasticities of demand in Tucson, Arizona for both the usual long-run static model and for a simple short-run demand model. The results from these simultaneous equation models are consistent with a priori expectations and are unbiased.

Back to the basics: Using observations and interpretation to define watershed model structure. A case study in the Upper Coastal Plain, US.

NASA Astrophysics Data System (ADS)

Vache, K. B.

2015-12-01

This study outlines the development and use of an integrated catchment model that has been developed as part of a long-term project focused on impacts of short-rotation loblolly pine production as a biofuel feedstock. The field-related aspects of the project were initiated in 2009 and focused on the development of a baseline dataset developed from hydrometric, isotopic, and water quality monitoring of a set of small paired catchments. In the winter of 2013 a series of treatments, representing typical forest management strategies in the southeastern US were implemented, and monitoring will continue through 2018. We have used the available long-term measurements to outline a conceptual model of catchment hydrology in this region which is characterized by low gradient slopes and deep sandy soils. The conceptual model has been translated into an object-oriented landscape modeling framework, allowing for the development of a set of long term landuse scenarios which serve as temporally-varying boundaries conditions for the catchment model. The presentation focuses primarily on these modeling results, with particular emphasis on the influence of short rotation harvest on groundwater recharge and stream water quantity over decadal scales.

A dynamic ecosystem growth model for forests at high complexity structure

NASA Astrophysics Data System (ADS)

Collalti, A.; Perugini, L.; Chiti, T.; Matteucci, G.; Oriani, A.; Santini, M.; Papale, D.; Valentini, R.

2012-04-01

Forests ecosystem play an important role in carbon cycle, biodiversity conservation and for other ecosystem services and changes in their structure and status perturb a delicate equilibrium that involves not only vegetation components but also biogeochemical cycles and global climate. The approaches to determine the magnitude of these effects are nowadays various and one of those include the use of models able to simulate structural changes and the variations in forests yield The present work shows the development of a forest dynamic model, on ecosystem spatial scale using the well known light use efficiency to determine Gross Primary Production. The model is predictive and permits to simulate processes that determine forest growth, its dynamic and the effects of forest management using eco-physiological parameters easy to be assessed and to be measured. The model has been designed to consider a tri-dimensional cell structure composed by different vertical layers depending on the forest type that has to be simulated. These features enable the model to work on multi-layer and multi-species forest types, typical of Mediterranean environment, at the resolution of one hectare and at monthly time-step. The model simulates, for each layer, a value of available Photosynthetic Active Radiation (PAR) through Leaf Area Index, Light Extinction Coefficient and cell coverage, the transpiration rate that is closely linked to the intercepted light and the evaporation from soil. Using this model it is possible to evaluate the possible impacts of climate change on forests that may result in decrease or increase of productivity as well as the feedback of one or more dominated layers in terms of CO2 uptake in a forest stand and the effects of forest management activities during the forest harvesting cycle. The model has been parameterised, validated and applied in a multi-layer, multi-age and multi-species Italian turkey oak forest (Q. cerris L., C. betulus L. and C. avellana L.) where the medium-term (10 years) development of forest parameters were simulated. The results obtained for net primary production and for stem, root and foliage compartments as well as for forest structure i.e. Diameter at Breast Height, height and canopy cover are in good accordance with field data (R2>0.95). These results show how the model is able to predict forest yield as well as forest dynamic with good accuracy and encourage testing the model capability on other sites with a more complex forest structure and for long-time period with an higher spatial resolution.

Some Implications of a Behavioral Analysis of Verbal Behavior for Logic and Mathematics

PubMed Central

2013-01-01

The evident power and utility of the formal models of logic and mathematics pose a puzzle: Although such models are instances of verbal behavior, they are also essentialistic. But behavioral terms, and indeed all products of selection contingencies, are intrinsically variable and in this respect appear to be incommensurate with essentialism. A distinctive feature of verbal contingencies resolves this puzzle: The control of behavior by the nonverbal environment is often mediated by the verbal behavior of others, and behavior under control of verbal stimuli is blind to the intrinsic variability of the stimulating environment. Thus, words and sentences serve as filters of variability and thereby facilitate essentialistic model building and the formal structures of logic, mathematics, and science. Autoclitic frames, verbal chains interrupted by interchangeable variable terms, are ubiquitous in verbal behavior. Variable terms can be substituted in such frames almost without limit, a feature fundamental to formal models. Consequently, our fluency with autoclitic frames fosters generalization to formal models, which in turn permit deduction and other kinds of logical and mathematical inference. PMID:28018038

Managing maritime automobile terminals: an approach toward decision-support model for higher productivity

NASA Astrophysics Data System (ADS)

Beškovnik, Bojan; Twrdy, Elen

2011-12-01

The article describes actions and strategies to obtain higher productivity on maritime automobile terminals. The main focus is on elaboration of efficient and effective organizational structure to model and implement short-term, mid-term and long-term strategies. In addition, with an empiric approach we combined the analyses of current findings in important scientific papers and our acknowledgments in practical research of north Adriatic maritime automobile terminals. The main goal is to propose actions towards increasing system's productivity. Based on our research of the north Adriatic maritime automobile terminals and with Lambert's model an in-deep analysis of limiting factors, user's expectations and possibilities for productivity increase has been performed. Moreover, with our acknowledgments a three-level decision-support model is presented. With an adequate model implementation it is possible to efficiently develop and implement different strategies of productivity measurement and productivity increase, especially in the fields of internal transport productivity, entrance/exit truck gates operations and wagon manipulations. According to our observation a significant increase might be achieved in all three fields.

Mathematical model of the heat transfer process taking into account the consequences of nonlocality in structurally sensitive materials

NASA Astrophysics Data System (ADS)

Kuvyrkin, G. N.; Savelyeva, I. Y.; Kuvshynnikova, D. A.

2018-04-01

Creation of new materials based on nanotechnology is an important direction of modern materials science development. Materials obtained using nanotechnology can possess unique physical-mechanical and thermophysical properties, allowing their effective use in structures exposed to high-intensity thermomechanical effects. An important step in creation and use of new materials is the construction of mathematical models to describe the behavior of these materials in a wide range of changes under external effects. The model of heat conduction of structural-sensitive materials is considered with regard to the medium nonlocality effects. The relations of the mathematical model include an integral term describing the spatial nonlocality of the medium. A difference scheme, which makes it possible to obtain a numerical solution of the problem of nonstationary heat conduction with regard to the influence of the medium nonlocality on space, has been developed. The influence of the model parameters on the temperature distributions is analyzed.

Model parameter extraction of lateral propagating surface acoustic waves with coupling on SiO2/grating/LiNbO3 structure

NASA Astrophysics Data System (ADS)

Zhang, Benfeng; Han, Tao; Li, Xinyi; Huang, Yulin; Omori, Tatsuya; Hashimoto, Ken-ya

2018-07-01

This paper investigates how lateral propagation of Rayleigh and shear horizontal (SH) surface acoustic waves (SAWs) changes with rotation angle θ and SiO2 and electrode thicknesses, h SiO2 and h Cu, respectively. The extended thin plate model is used for purpose. First, the extraction method is presented for determining parameters appearing in the extended thin plate model. Then, the model parameters are expressed in polynomials in terms of h SiO2, h Cu, and θ. Finally, a piston mode structure without phase shifters is designed using the extracted parameters. The possible piston mode structures can be searched automatically by use of the polynomial expression. The resonance characteristics are analyzed by both the extended thin plate model and three-dimensional (3D) finite element method (FEM). Agreement between the results of both methods confirms validity and effectiveness of the parameter extraction process and the design technique.

QSAR Methods.

PubMed

Gini, Giuseppina

2016-01-01

In this chapter, we introduce the basis of computational chemistry and discuss how computational methods have been extended to some biological properties and toxicology, in particular. Since about 20 years, chemical experimentation is more and more replaced by modeling and virtual experimentation, using a large core of mathematics, chemistry, physics, and algorithms. Then we see how animal experiments, aimed at providing a standardized result about a biological property, can be mimicked by new in silico methods. Our emphasis here is on toxicology and on predicting properties through chemical structures. Two main streams of such models are available: models that consider the whole molecular structure to predict a value, namely QSAR (Quantitative Structure Activity Relationships), and models that find relevant substructures to predict a class, namely SAR. The term in silico discovery is applied to chemical design, to computational toxicology, and to drug discovery. We discuss how the experimental practice in biological science is moving more and more toward modeling and simulation. Such virtual experiments confirm hypotheses, provide data for regulation, and help in designing new chemicals.

A machine learning approach to the potential-field method for implicit modeling of geological structures

NASA Astrophysics Data System (ADS)

Gonçalves, Ítalo Gomes; Kumaira, Sissa; Guadagnin, Felipe

2017-06-01

Implicit modeling has experienced a rise in popularity over the last decade due to its advantages in terms of speed and reproducibility in comparison with manual digitization of geological structures. The potential-field method consists in interpolating a scalar function that indicates to which side of a geological boundary a given point belongs to, based on cokriging of point data and structural orientations. This work proposes a vector potential-field solution from a machine learning perspective, recasting the problem as multi-class classification, which alleviates some of the original method's assumptions. The potentials related to each geological class are interpreted in a compositional data framework. Variogram modeling is avoided through the use of maximum likelihood to train the model, and an uncertainty measure is introduced. The methodology was applied to the modeling of a sample dataset provided with the software Move™. The calculations were implemented in the R language and 3D visualizations were prepared with the rgl package.

A probabilistic model for detecting rigid domains in protein structures.

PubMed

Nguyen, Thach; Habeck, Michael

2016-09-01

Large-scale conformational changes in proteins are implicated in many important biological functions. These structural transitions can often be rationalized in terms of relative movements of rigid domains. There is a need for objective and automated methods that identify rigid domains in sets of protein structures showing alternative conformational states. We present a probabilistic model for detecting rigid-body movements in protein structures. Our model aims to approximate alternative conformational states by a few structural parts that are rigidly transformed under the action of a rotation and a translation. By using Bayesian inference and Markov chain Monte Carlo sampling, we estimate all parameters of the model, including a segmentation of the protein into rigid domains, the structures of the domains themselves, and the rigid transformations that generate the observed structures. We find that our Gibbs sampling algorithm can also estimate the optimal number of rigid domains with high efficiency and accuracy. We assess the power of our method on several thousand entries of the DynDom database and discuss applications to various complex biomolecular systems. The Python source code for protein ensemble analysis is available at: https://github.com/thachnguyen/motion_detection : mhabeck@gwdg.de. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Incorporating modeling and simulations in undergraduate biophysical chemistry course to promote understanding of structure-dynamics-function relationships in proteins.

PubMed

Hati, Sanchita; Bhattacharyya, Sudeep

2016-01-01

A project-based biophysical chemistry laboratory course, which is offered to the biochemistry and molecular biology majors in their senior year, is described. In this course, the classroom study of the structure-function of biomolecules is integrated with the discovery-guided laboratory study of these molecules using computer modeling and simulations. In particular, modern computational tools are employed to elucidate the relationship between structure, dynamics, and function in proteins. Computer-based laboratory protocols that we introduced in three modules allow students to visualize the secondary, super-secondary, and tertiary structures of proteins, analyze non-covalent interactions in protein-ligand complexes, develop three-dimensional structural models (homology model) for new protein sequences and evaluate their structural qualities, and study proteins' intrinsic dynamics to understand their functions. In the fourth module, students are assigned to an authentic research problem, where they apply their laboratory skills (acquired in modules 1-3) to answer conceptual biophysical questions. Through this process, students gain in-depth understanding of protein dynamics-the missing link between structure and function. Additionally, the requirement of term papers sharpens students' writing and communication skills. Finally, these projects result in new findings that are communicated in peer-reviewed journals. © 2016 The International Union of Biochemistry and Molecular Biology.

Predictive modeling of composite material degradation using piezoelectric wafer sensors electromechanical impedance spectroscopy

NASA Astrophysics Data System (ADS)

Gresil, Matthieu; Yu, Lingyu; Sutton, Mike; Guo, Siming; Pollock, Patrick

2012-04-01

The advancement of composite materials in aircraft structures has led to on increased need for effective structural health monitoring (SHM) technologies that are able to detect and assess damage present in composites structures. The work presented in this paper is interested in understanding using self-sensing piezoelectric wafer active sensors (PWAS) to conduct electromechanical impedance spectroscopy (EMIS) in glass fiber reinforced plastic (GFRP) to perform structures health monitoring. PWAS are bonded to the composite material and the EMIS method is used to analyze the changes in the structural resonance and anti-resonance. As the damage progresses in the specimen, the impedance spectrum will change. In addition, multi-physics based finite element method (MP-FEM) is used to model the electromechanical behavior of a free PWAS and its interaction with the host structure on which it is bonded. The MPFEM permits the input and the output variables to be expressed directly in electric terms while the two way electromechanical conversion is done internally in the MP_FEM formulation. To reach the goal of using the EMIS approach to detect damage, several damages models are generated on laminated GFRP structures. The effects of the modeling are carefully studied through experimental validation. A good match has been observed for low and very high frequencies.

Modeling Structural Dynamics of Biomolecular Complexes by Coarse-Grained Molecular Simulations.

PubMed

Takada, Shoji; Kanada, Ryo; Tan, Cheng; Terakawa, Tsuyoshi; Li, Wenfei; Kenzaki, Hiroo

2015-12-15

Due to hierarchic nature of biomolecular systems, their computational modeling calls for multiscale approaches, in which coarse-grained (CG) simulations are used to address long-time dynamics of large systems. Here, we review recent developments and applications of CG modeling methods, focusing on our methods primarily for proteins, DNA, and their complexes. These methods have been implemented in the CG biomolecular simulator, CafeMol. Our CG model has resolution such that ∼10 non-hydrogen atoms are grouped into one CG particle on average. For proteins, each amino acid is represented by one CG particle. For DNA, one nucleotide is simplified by three CG particles, representing sugar, phosphate, and base. The protein modeling is based on the idea that proteins have a globally funnel-like energy landscape, which is encoded in the structure-based potential energy function. We first describe two representative minimal models of proteins, called the elastic network model and the classic Go̅ model. We then present a more elaborate protein model, which extends the minimal model to incorporate sequence and context dependent local flexibility and nonlocal contacts. For DNA, we describe a model developed by de Pablo's group that was tuned to well reproduce sequence-dependent structural and thermodynamic experimental data for single- and double-stranded DNAs. Protein-DNA interactions are modeled either by the structure-based term for specific cases or by electrostatic and excluded volume terms for nonspecific cases. We also discuss the time scale mapping in CG molecular dynamics simulations. While the apparent single time step of our CGMD is about 10 times larger than that in the fully atomistic molecular dynamics for small-scale dynamics, large-scale motions can be further accelerated by two-orders of magnitude with the use of CG model and a low friction constant in Langevin dynamics. Next, we present four examples of applications. First, the classic Go̅ model was used to emulate one ATP cycle of a molecular motor, kinesin. Second, nonspecific protein-DNA binding was studied by a combination of elaborate protein and DNA models. Third, a transcription factor, p53, that contains highly fluctuating regions was simulated on two perpendicularly arranged DNA segments, addressing intersegmental transfer of p53. Fourth, we simulated structural dynamics of dinucleosomes connected by a linker DNA finding distinct types of internucleosome docking and salt-concentration-dependent compaction. Finally, we discuss many of limitations in the current approaches and future directions. Especially, more accurate electrostatic treatment and a phospholipid model that matches our CG resolutions are of immediate importance.

A multiple-scales model of the shock-cell structure of imperfectly expanded supersonic jets

NASA Technical Reports Server (NTRS)

Tam, C. K. W.; Jackson, J. A.; Seiner, J. M.

1985-01-01

The present investigation is concerned with the development of an analytical model of the quasi-periodic shock-cell structure of an imperfectly expanded supersonic jet. The investigation represents a part of a program to develop a mathematical theory of broadband shock-associated noise of supersonic jets. Tam and Tanna (1982) have suggested that this type of noise is generated by the weak interaction between the quasi-periodic shock cells and the downstream-propagating large turbulence structures in the mixing layer of the jet. In the model developed in this paper, the effect of turbulence in the mixing layer of the jet is simulated by the addition of turbulent eddy-viscosity terms to the momentum equation. Attention is given to the mean-flow profile and the numerical solution, and a comparison of the numerical results with experimental data.

Close-packed structure dynamics with finite-range interaction: computational mechanics with individual layer interaction.

PubMed

Rodriguez-Horta, Edwin; Estevez-Rams, Ernesto; Lora-Serrano, Raimundo; Neder, Reinhard

2017-09-01

This is the second contribution in a series of papers dealing with dynamical models in equilibrium theories of polytypism. A Hamiltonian introduced by Ahmad & Khan [Phys. Status Solidi B (2000), 218, 425-430] avoids the unphysical assignment of interaction terms to fictitious entities given by spins in the Hägg coding of the stacking arrangement. In this paper an analysis of polytype generation and disorder in close-packed structures is made for such a Hamiltonian. Results are compared with a previous analysis using the Ising model. Computational mechanics is the framework under which the analysis is performed. The competing effects of disorder and structure, as given by entropy density and excess entropy, respectively, are discussed. It is argued that the Ahmad & Khan model is simpler and predicts a larger set of polytypes than previous treatments.

Structure-based control of complex networks with nonlinear dynamics.

PubMed

Zañudo, Jorge Gomez Tejeda; Yang, Gang; Albert, Réka

2017-07-11

What can we learn about controlling a system solely from its underlying network structure? Here we adapt a recently developed framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes. This feedback-based framework provides realizable node overrides that steer a system toward any of its natural long-term dynamic behaviors, regardless of the specific functional forms and system parameters. We use this framework on several real networks, identify the topological characteristics that underlie the predicted node overrides, and compare its predictions to those of structural controllability in control theory. Finally, we demonstrate this framework's applicability in dynamic models of gene regulatory networks and identify nodes whose override is necessary for control in the general case but not in specific model instances.

Evaluating measurement models in clinical research: covariance structure analysis of latent variable models of self-conception.

PubMed

Hoyle, R H

1991-02-01

Indirect measures of psychological constructs are vital to clinical research. On occasion, however, the meaning of indirect measures of psychological constructs is obfuscated by statistical procedures that do not account for the complex relations between items and latent variables and among latent variables. Covariance structure analysis (CSA) is a statistical procedure for testing hypotheses about the relations among items that indirectly measure a psychological construct and relations among psychological constructs. This article introduces clinical researchers to the strengths and limitations of CSA as a statistical procedure for conceiving and testing structural hypotheses that are not tested adequately with other statistical procedures. The article is organized around two empirical examples that illustrate the use of CSA for evaluating measurement models with correlated error terms, higher-order factors, and measured and latent variables.

Structure and modeling of turbulence

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

Novikov, E.A.

The {open_quotes}vortex strings{close_quotes} scale l{sub s} {approximately} LRe{sup -3/10} (L-external scale, Re - Reynolds number) is suggested as a grid scale for the large-eddy simulation. Various aspects of the structure of turbulence and subgrid modeling are described in terms of conditional averaging, Markov processes with dependent increments and infinitely divisible distributions. The major request from the energy, naval, aerospace and environmental engineering communities to the theory of turbulence is to reduce the enormous number of degrees of freedom in turbulent flows to a level manageable by computer simulations. The vast majority of these degrees of freedom is in the small-scalemore » motion. The study of the structure of turbulence provides a basis for subgrid-scale (SGS) models, which are necessary for the large-eddy simulations (LES).« less

Automated method to differentiate between native and mirror protein models obtained from contact maps.

PubMed

Kurczynska, Monika; Kotulska, Malgorzata

2018-01-01

Mirror protein structures are often considered as artifacts in modeling protein structures. However, they may soon become a new branch of biochemistry. Moreover, methods of protein structure reconstruction, based on their residue-residue contact maps, need methodology to differentiate between models of native and mirror orientation, especially regarding the reconstructed backbones. We analyzed 130 500 structural protein models obtained from contact maps of 1 305 SCOP domains belonging to all 7 structural classes. On average, the same numbers of native and mirror models were obtained among 100 models generated for each domain. Since their structural features are often not sufficient for differentiating between the two types of model orientations, we proposed to apply various energy terms (ETs) from PyRosetta to separate native and mirror models. To automate the procedure for differentiating these models, the k-means clustering algorithm was applied. Using total energy did not allow to obtain appropriate clusters-the accuracy of the clustering for class A (all helices) was no more than 0.52. Therefore, we tested a series of different k-means clusterings based on various combinations of ETs. Finally, applying two most differentiating ETs for each class allowed to obtain satisfying results. To unify the method for differentiating between native and mirror models, independent of their structural class, the two best ETs for each class were considered. Finally, the k-means clustering algorithm used three common ETs: probability of amino acid assuming certain values of dihedral angles Φ and Ψ, Ramachandran preferences and Coulomb interactions. The accuracies of clustering with these ETs were in the range between 0.68 and 0.76, with sensitivity and selectivity in the range between 0.68 and 0.87, depending on the structural class. The method can be applied to all fully-automated tools for protein structure reconstruction based on contact maps, especially those analyzing big sets of models.

Automated method to differentiate between native and mirror protein models obtained from contact maps

PubMed Central

Kurczynska, Monika

2018-01-01

Mirror protein structures are often considered as artifacts in modeling protein structures. However, they may soon become a new branch of biochemistry. Moreover, methods of protein structure reconstruction, based on their residue-residue contact maps, need methodology to differentiate between models of native and mirror orientation, especially regarding the reconstructed backbones. We analyzed 130 500 structural protein models obtained from contact maps of 1 305 SCOP domains belonging to all 7 structural classes. On average, the same numbers of native and mirror models were obtained among 100 models generated for each domain. Since their structural features are often not sufficient for differentiating between the two types of model orientations, we proposed to apply various energy terms (ETs) from PyRosetta to separate native and mirror models. To automate the procedure for differentiating these models, the k-means clustering algorithm was applied. Using total energy did not allow to obtain appropriate clusters–the accuracy of the clustering for class A (all helices) was no more than 0.52. Therefore, we tested a series of different k-means clusterings based on various combinations of ETs. Finally, applying two most differentiating ETs for each class allowed to obtain satisfying results. To unify the method for differentiating between native and mirror models, independent of their structural class, the two best ETs for each class were considered. Finally, the k-means clustering algorithm used three common ETs: probability of amino acid assuming certain values of dihedral angles Φ and Ψ, Ramachandran preferences and Coulomb interactions. The accuracies of clustering with these ETs were in the range between 0.68 and 0.76, with sensitivity and selectivity in the range between 0.68 and 0.87, depending on the structural class. The method can be applied to all fully-automated tools for protein structure reconstruction based on contact maps, especially those analyzing big sets of models. PMID:29787567

Crash Frequency Analysis Using Hurdle Models with Random Effects Considering Short-Term Panel Data

PubMed Central

Chen, Feng; Ma, Xiaoxiang; Chen, Suren; Yang, Lin

2016-01-01

Random effect panel data hurdle models are established to research the daily crash frequency on a mountainous section of highway I-70 in Colorado. Road Weather Information System (RWIS) real-time traffic and weather and road surface conditions are merged into the models incorporating road characteristics. The random effect hurdle negative binomial (REHNB) model is developed to study the daily crash frequency along with three other competing models. The proposed model considers the serial correlation of observations, the unbalanced panel-data structure, and dominating zeroes. Based on several statistical tests, the REHNB model is identified as the most appropriate one among four candidate models for a typical mountainous highway. The results show that: (1) the presence of over-dispersion in the short-term crash frequency data is due to both excess zeros and unobserved heterogeneity in the crash data; and (2) the REHNB model is suitable for this type of data. Moreover, time-varying variables including weather conditions, road surface conditions and traffic conditions are found to play importation roles in crash frequency. Besides the methodological advancements, the proposed technology bears great potential for engineering applications to develop short-term crash frequency models by utilizing detailed data from field monitoring data such as RWIS, which is becoming more accessible around the world. PMID:27792209

Simulation of physiological systems in order to evaluate and predict the human condition in a space flight

NASA Technical Reports Server (NTRS)

Verigo, V. V.

1979-01-01

Simulation models were used to study theoretical problems of space biology and medicine. The reaction and adaptation of the main physiological systems to the complex effects of space flight were investigated. Mathematical models were discussed in terms of their significance in the selection of the structure and design of biological life support systems.

Zebrafish Model of NF1 for Structure-Function Analysis, Mechanisms of Glial Tumorigenesis, and Chemical Biology

DTIC Science & Technology

2014-05-01

identify modulators of this important disease. 15. SUBJECT TERMS Neurofibromatosis ; learning and memory; glioma; MPNST 16. SECURITY CLASSIFICATION...12-13 Page 3 INTRODUCTION Neurofibromatosis type 1...result indicates that sox10 is highly expressed in high-grade gliomas and MPNSTs in our zebrafish model of type I neurofibromatosis . Figure 4. Sox10

The Performance of ML, GLS, and WLS Estimation in Structural Equation Modeling under Conditions of Misspecification and Nonnormality.

ERIC Educational Resources Information Center

Olsson, Ulf Henning; Foss, Tron; Troye, Sigurd V.; Howell, Roy D.

2000-01-01

Used simulation to demonstrate how the choice of estimation method affects indexes of fit and parameter bias for different sample sizes when nested models vary in terms of specification error and the data demonstrate different levels of kurtosis. Discusses results for maximum likelihood (ML), generalized least squares (GLS), and weighted least…

Performance range of SMA actuator wires and SMA-FRP structure in terms of manufacturing, modeling and actuation

NASA Astrophysics Data System (ADS)

Hübler, M.; Gurka, M.; Schmeer, S.; Breuer, U. P.

2013-09-01

In this contribution we present a comprehensive theoretical and experimental description of an active shape memory alloy (SMA) fiber reinforced composite (FRP) hybrid structure. The major influences on actuation performance arising from variations in the design and manufacturing process are discussed, utilizing a new phenomenological model to describe the actuating SMA material. The different material properties for the activated, respective the unactivated, SMA as well as the influence of different loading conditions or pre-treatment of the material are taken into account in this model. To validate our material model we performed new actuation experiments with an exemplary SMA-FRP structure, which we compared to finite element (FE) simulation results. Our FE-model is based on a material model for the actuating SMA elements derived from experiments and data on the actual microscopic geometry of the hybrid composite. Therefore it is able to predict very precisely the actuation behavior of a typical FRP structure for industrial use cases: a thin walled CFRP sheet with SMA wires attached to the top for performing a bending motion with a maximum deflection of approx. 25% of its length.

Principal elementary mode analysis (PEMA).

PubMed

Folch-Fortuny, Abel; Marques, Rodolfo; Isidro, Inês A; Oliveira, Rui; Ferrer, Alberto

2016-03-01

Principal component analysis (PCA) has been widely applied in fluxomics to compress data into a few latent structures in order to simplify the identification of metabolic patterns. These latent structures lack a direct biological interpretation due to the intrinsic constraints associated with a PCA model. Here we introduce a new method that significantly improves the interpretability of the principal components with a direct link to metabolic pathways. This method, called principal elementary mode analysis (PEMA), establishes a bridge between a PCA-like model, aimed at explaining the maximum variance in flux data, and the set of elementary modes (EMs) of a metabolic network. It provides an easy way to identify metabolic patterns in large fluxomics datasets in terms of the simplest pathways of the organism metabolism. The results using a real metabolic model of Escherichia coli show the ability of PEMA to identify the EMs that generated the different simulated flux distributions. Actual flux data of E. coli and Pichia pastoris cultures confirm the results observed in the simulated study, providing a biologically meaningful model to explain flux data of both organisms in terms of the EM activation. The PEMA toolbox is freely available for non-commercial purposes on http://mseg.webs.upv.es.

Engineering model of the electric drives of separation device for simulation of automatic control systems of reactive power compensation by means of serially connected capacitors

NASA Astrophysics Data System (ADS)

Juromskiy, V. M.

2016-09-01

It is developed a mathematical model for an electric drive of high-speed separation device in terms of the modeling dynamic systems Simulink, MATLAB. The model is focused on the study of the automatic control systems of the power factor (Cosφ) of an actuator by compensating the reactive component of the total power by switching a capacitor bank in series with the actuator. The model is based on the methodology of the structural modeling of dynamic processes.

Models for short-wave instability in inviscid shear flows

NASA Astrophysics Data System (ADS)

Grimshaw, Roger

1999-11-01

The generation of instability in an invsicid fluid occurs by a resonance between two wave modes, where here the resonance occurs by a coincidence of phase speeds for a finite, non-zero wavenumber. We show that in the weakly nonlinear limit, the appropriate model consists of two coupled equations for the envelopes of the wave modes, in which the nonlinear terms are balanced with low-order cross-coupling linear dispersive terms rather than the more familiar high-order terms which arise in the nonlinear Schrodinger equation, for instance. We will show that this system may either contain gap solitons as solutions in the linearly stable case, or wave breakdown in the linearly unstable case. In this latter circumstance, the system either exhibits wave collapse in finite time, or disintegration into fine-scale structures.

Changes at work and employee reactions: organizational elements, job insecurity, and short-term stress as predictors for employee health and safety.

PubMed

Størseth, Fred

2006-12-01

The objective was to identify focus areas for possible reduction of job insecurity and its outcomes. A model was specified and tested as a prediction model for health and safety. First, a parsimonious model was specified. The model consisted of perceived job insecurity (as a stressor), organizational factors (information quality, leadership style, work task administration), and short-term stress reactions (job dissatisfaction, reduced work motivation). Second, the model was tested as a prediction model in three separate path analyses, in order to examine the model's contribution in explaining (1) physical health complaints, (2) mental health complaints, and (3) risk taking behavior. A quota sample of Norwegian employees (N= 1,002) was obtained by means of a self-completion questionnaire survey. The results of the structural equation modeling (path analyses) supported the hypothesized model. Mental health complaints and employee risk taking behavior were significantly predicted (not physical health complaints).

Comparative Study of Shrinkage and Non-Shrinkage Model of Food Drying

NASA Astrophysics Data System (ADS)

Shahari, N.; Jamil, N.; Rasmani, KA.

2016-08-01

A single phase heat and mass model has always been used to represent the moisture and temperature distribution during the drying of food. Several effects of the drying process, such as physical and structural changes, have been considered in order to increase understanding of the movement of water and temperature. However, the comparison between the heat and mass equation with and without structural change (in terms of shrinkage), which can affect the accuracy of the prediction model, has been little investigated. In this paper, two mathematical models to describe the heat and mass transfer in food, with and without the assumption of structural change, were analysed. The equations were solved using the finite difference method. The converted coordinate system was introduced within the numerical computations for the shrinkage model. The result shows that the temperature with shrinkage predicts a higher temperature at a specific time compared to that of the non-shrinkage model. Furthermore, the predicted moisture content decreased faster at a specific time when the shrinkage effect was included in the model.

Family Environment and Childhood Obesity: A New Framework with Structural Equation Modeling

PubMed Central

Huang, Hui; Wan Mohamed Radzi, Che Wan Jasimah bt; Salarzadeh Jenatabadi, Hashem

2017-01-01

The main purpose of the current article is to introduce a framework of the complexity of childhood obesity based on the family environment. A conceptual model that quantifies the relationships and interactions among parental socioeconomic status, family food security level, child’s food intake and certain aspects of parental feeding behaviour is presented using the structural equation modeling (SEM) concept. Structural models are analysed in terms of the direct and indirect connections among latent and measurement variables that lead to the child weight indicator. To illustrate the accuracy, fit, reliability and validity of the introduced framework, real data collected from 630 families from Urumqi (Xinjiang, China) were considered. The framework includes two categories of data comprising the normal body mass index (BMI) range and obesity data. The comparison analysis between two models provides some evidence that in obesity modeling, obesity data must be extracted from the dataset and analysis must be done separately from the normal BMI range. This study may be helpful for researchers interested in childhood obesity modeling based on family environment. PMID:28208833

Family Environment and Childhood Obesity: A New Framework with Structural Equation Modeling.

PubMed

Huang, Hui; Wan Mohamed Radzi, Che Wan Jasimah Bt; Salarzadeh Jenatabadi, Hashem

2017-02-13

The main purpose of the current article is to introduce a framework of the complexity of childhood obesity based on the family environment. A conceptual model that quantifies the relationships and interactions among parental socioeconomic status, family food security level, child's food intake and certain aspects of parental feeding behaviour is presented using the structural equation modeling (SEM) concept. Structural models are analysed in terms of the direct and indirect connections among latent and measurement variables that lead to the child weight indicator. To illustrate the accuracy, fit, reliability and validity of the introduced framework, real data collected from 630 families from Urumqi (Xinjiang, China) were considered. The framework includes two categories of data comprising the normal body mass index (BMI) range and obesity data. The comparison analysis between two models provides some evidence that in obesity modeling, obesity data must be extracted from the dataset and analysis must be done separately from the normal BMI range. This study may be helpful for researchers interested in childhood obesity modeling based on family environment.

Shape determination and control for large space structures

NASA Technical Reports Server (NTRS)

Weeks, C. J.

1981-01-01

An integral operator approach is used to derive solutions to static shape determination and control problems associated with large space structures. Problem assumptions include a linear self-adjoint system model, observations and control forces at discrete points, and performance criteria for the comparison of estimates or control forms. Results are illustrated by simulations in the one dimensional case with a flexible beam model, and in the multidimensional case with a finite model of a large space antenna. Modal expansions for terms in the solution algorithms are presented, using modes from the static or associated dynamic mode. These expansions provide approximated solutions in the event that a used form analytical solution to the system boundary value problem is not available.

Multiple Drug Treatments That Increase cAMP Signaling Restore Long-Term Memory and Aberrant Signaling in Fragile X Syndrome Models.

PubMed

Choi, Catherine H; Schoenfeld, Brian P; Bell, Aaron J; Hinchey, Joseph; Rosenfelt, Cory; Gertner, Michael J; Campbell, Sean R; Emerson, Danielle; Hinchey, Paul; Kollaros, Maria; Ferrick, Neal J; Chambers, Daniel B; Langer, Steven; Sust, Steven; Malik, Aatika; Terlizzi, Allison M; Liebelt, David A; Ferreiro, David; Sharma, Ali; Koenigsberg, Eric; Choi, Richard J; Louneva, Natalia; Arnold, Steven E; Featherstone, Robert E; Siegel, Steven J; Zukin, R Suzanne; McDonald, Thomas V; Bolduc, Francois V; Jongens, Thomas A; McBride, Sean M J

2016-01-01

Fragile X is the most common monogenic disorder associated with intellectual disability (ID) and autism spectrum disorders (ASD). Additionally, many patients are afflicted with executive dysfunction, ADHD, seizure disorder and sleep disturbances. Fragile X is caused by loss of FMRP expression, which is encoded by the FMR1 gene. Both the fly and mouse models of fragile X are also based on having no functional protein expression of their respective FMR1 homologs. The fly model displays well defined cognitive impairments and structural brain defects and the mouse model, although having subtle behavioral defects, has robust electrophysiological phenotypes and provides a tool to do extensive biochemical analysis of select brain regions. Decreased cAMP signaling has been observed in samples from the fly and mouse models of fragile X as well as in samples derived from human patients. Indeed, we have previously demonstrated that strategies that increase cAMP signaling can rescue short term memory in the fly model and restore DHPG induced mGluR mediated long term depression (LTD) in the hippocampus to proper levels in the mouse model (McBride et al., 2005; Choi et al., 2011, 2015). Here, we demonstrate that the same three strategies used previously with the potential to be used clinically, lithium treatment, PDE-4 inhibitor treatment or mGluR antagonist treatment can rescue long term memory in the fly model and alter the cAMP signaling pathway in the hippocampus of the mouse model.

Three-dimensional Cascaded Lattice Boltzmann Model for Thermal Convective Flows

NASA Astrophysics Data System (ADS)

Hajabdollahi, Farzaneh; Premnath, Kannan

2017-11-01

Fluid motion driven by thermal effects, such as due to buoyancy in differentially heated enclosures arise in several natural and industrial settings, whose understanding can be achieved via numerical simulations. Lattice Boltzmann (LB) methods are efficient kinetic computational approaches for coupled flow physics problems. In this study, we develop three-dimensional (3D) LB models based on central moments and multiple relaxation times for D3Q7 and D3Q15 lattices to solve the energy transport equations in a double distribution function approach. Their collision operators lead to a cascaded structure involving higher order terms resulting in improved stability. This is coupled to a central moment based LB flow solver with source terms. The new 3D cascaded LB models for the convective flows are first validated for natural convection of air driven thermally on two vertically opposite faces in a cubic cavity at different Rayleigh numbers against prior numerical and experimental data, which show good quantitative agreement. Then, the detailed structure of the 3D flow and thermal fields and the heat transfer rates at different Rayleigh numbers are analyzed and interpreted.

Default risk modeling with position-dependent killing

NASA Astrophysics Data System (ADS)

Katz, Yuri A.

2013-04-01

Diffusion in a linear potential in the presence of position-dependent killing is used to mimic a default process. Different assumptions regarding transport coefficients, initial conditions, and elasticity of the killing measure lead to diverse models of bankruptcy. One “stylized fact” is fundamental for our consideration: empirically default is a rather rare event, especially in the investment grade categories of credit ratings. Hence, the action of killing may be considered as a small parameter. In a number of special cases we derive closed-form expressions for the entire term structure of the cumulative probability of default, its hazard rate, and intensity. Comparison with historical data on aggregate global corporate defaults confirms the validity of the perturbation method for estimations of long-term probability of default for companies with high credit quality. On a single company level, we implement the derived formulas to estimate the one-year likelihood of default of Enron on a daily basis from August 2000 to August 2001, three months before its default, and compare the obtained results with forecasts of traditional structural models.