MODBASE, a database of annotated comparative protein structure models

PubMed Central

Pieper, Ursula; Eswar, Narayanan; Stuart, Ashley C.; Ilyin, Valentin A.; Sali, Andrej

2002-01-01

MODBASE (http://guitar.rockefeller.edu/modbase) is a relational database of annotated comparative protein structure models for all available protein sequences matched to at least one known protein structure. The models are calculated by MODPIPE, an automated modeling pipeline that relies on PSI-BLAST, IMPALA and MODELLER. MODBASE uses the MySQL relational database management system for flexible and efficient querying, and the MODVIEW Netscape plugin for viewing and manipulating multiple sequences and structures. It is updated regularly to reflect the growth of the protein sequence and structure databases, as well as improvements in the software for calculating the models. For ease of access, MODBASE is organized into different datasets. The largest dataset contains models for domains in 304 517 out of 539 171 unique protein sequences in the complete TrEMBL database (23 March 2001); only models based on significant alignments (PSI-BLAST E-value < 10–4) and models assessed to have the correct fold are included. Other datasets include models for target selection and structure-based annotation by the New York Structural Genomics Research Consortium, models for prediction of genes in the Drosophila melanogaster genome, models for structure determination of several ribosomal particles and models calculated by the MODWEB comparative modeling web server. PMID:11752309

Comparisons of Multilevel Modeling and Structural Equation Modeling Approaches to Actor-Partner Interdependence Model.

PubMed

Hong, Sehee; Kim, Soyoung

2018-01-01

There are basically two modeling approaches applicable to analyzing an actor-partner interdependence model: the multilevel modeling (hierarchical linear model) and the structural equation modeling. This article explains how to use these two models in analyzing an actor-partner interdependence model and how these two approaches work differently. As an empirical example, marital conflict data were used to analyze an actor-partner interdependence model. The multilevel modeling and the structural equation modeling produced virtually identical estimates for a basic model. However, the structural equation modeling approach allowed more realistic assumptions on measurement errors and factor loadings, rendering better model fit indices.

A Fast Surrogate-facilitated Data-driven Bayesian Approach to Uncertainty Quantification of a Regional Groundwater Flow Model with Structural Error

NASA Astrophysics Data System (ADS)

Xu, T.; Valocchi, A. J.; Ye, M.; Liang, F.

2016-12-01

Due to simplification and/or misrepresentation of the real aquifer system, numerical groundwater flow and solute transport models are usually subject to model structural error. During model calibration, the hydrogeological parameters may be overly adjusted to compensate for unknown structural error. This may result in biased predictions when models are used to forecast aquifer response to new forcing. In this study, we extend a fully Bayesian method [Xu and Valocchi, 2015] to calibrate a real-world, regional groundwater flow model. The method uses a data-driven error model to describe model structural error and jointly infers model parameters and structural error. In this study, Bayesian inference is facilitated using high performance computing and fast surrogate models. The surrogate models are constructed using machine learning techniques to emulate the response simulated by the computationally expensive groundwater model. We demonstrate in the real-world case study that explicitly accounting for model structural error yields parameter posterior distributions that are substantially different from those derived by the classical Bayesian calibration that does not account for model structural error. In addition, the Bayesian with error model method gives significantly more accurate prediction along with reasonable credible intervals.

Implementation of the nursing process in a health area: models and assessment structures used

PubMed Central

Huitzi-Egilegor, Joseba Xabier; Elorza-Puyadena, Maria Isabel; Urkia-Etxabe, Jose Maria; Asurabarrena-Iraola, Carmen

2014-01-01

OBJECTIVE: to analyze what nursing models and nursing assessment structures have been used in the implementation of the nursing process at the public and private centers in the health area Gipuzkoa (Basque Country). METHOD: a retrospective study was undertaken, based on the analysis of the nursing records used at the 158 centers studied. RESULTS: the Henderson model, Carpenito's bifocal structure, Gordon's assessment structure and the Resident Assessment Instrument Nursing Home 2.0 have been used as nursing models and assessment structures to implement the nursing process. At some centers, the selected model or assessment structure has varied over time. CONCLUSION: Henderson's model has been the most used to implement the nursing process. Furthermore, the trend is observed to complement or replace Henderson's model by nursing assessment structures. PMID:25493672

A Generative Angular Model of Protein Structure Evolution

PubMed Central

Golden, Michael; García-Portugués, Eduardo; Sørensen, Michael; Mardia, Kanti V.; Hamelryck, Thomas; Hein, Jotun

2017-01-01

Abstract Recently described stochastic models of protein evolution have demonstrated that the inclusion of structural information in addition to amino acid sequences leads to a more reliable estimation of evolutionary parameters. We present a generative, evolutionary model of protein structure and sequence that is valid on a local length scale. The model concerns the local dependencies between sequence and structure evolution in a pair of homologous proteins. The evolutionary trajectory between the two structures in the protein pair is treated as a random walk in dihedral angle space, which is modeled using a novel angular diffusion process on the two-dimensional torus. Coupling sequence and structure evolution in our model allows for modeling both “smooth” conformational changes and “catastrophic” conformational jumps, conditioned on the amino acid changes. The model has interpretable parameters and is comparatively more realistic than previous stochastic models, providing new insights into the relationship between sequence and structure evolution. For example, using the trained model we were able to identify an apparent sequence–structure evolutionary motif present in a large number of homologous protein pairs. The generative nature of our model enables us to evaluate its validity and its ability to simulate aspects of protein evolution conditioned on an amino acid sequence, a related amino acid sequence, a related structure or any combination thereof. PMID:28453724

Quality assessment of protein model-structures based on structural and functional similarities

PubMed Central

2012-01-01

Background Experimental determination of protein 3D structures is expensive, time consuming and sometimes impossible. A gap between number of protein structures deposited in the World Wide Protein Data Bank and the number of sequenced proteins constantly broadens. Computational modeling is deemed to be one of the ways to deal with the problem. Although protein 3D structure prediction is a difficult task, many tools are available. These tools can model it from a sequence or partial structural information, e.g. contact maps. Consequently, biologists have the ability to generate automatically a putative 3D structure model of any protein. However, the main issue becomes evaluation of the model quality, which is one of the most important challenges of structural biology. Results GOBA - Gene Ontology-Based Assessment is a novel Protein Model Quality Assessment Program. It estimates the compatibility between a model-structure and its expected function. GOBA is based on the assumption that a high quality model is expected to be structurally similar to proteins functionally similar to the prediction target. Whereas DALI is used to measure structure similarity, protein functional similarity is quantified using standardized and hierarchical description of proteins provided by Gene Ontology combined with Wang's algorithm for calculating semantic similarity. Two approaches are proposed to express the quality of protein model-structures. One is a single model quality assessment method, the other is its modification, which provides a relative measure of model quality. Exhaustive evaluation is performed on data sets of model-structures submitted to the CASP8 and CASP9 contests. Conclusions The validation shows that the method is able to discriminate between good and bad model-structures. The best of tested GOBA scores achieved 0.74 and 0.8 as a mean Pearson correlation to the observed quality of models in our CASP8 and CASP9-based validation sets. GOBA also obtained the best result for two targets of CASP8, and one of CASP9, compared to the contest participants. Consequently, GOBA offers a novel single model quality assessment program that addresses the practical needs of biologists. In conjunction with other Model Quality Assessment Programs (MQAPs), it would prove useful for the evaluation of single protein models. PMID:22998498

Eukaryotic major facilitator superfamily transporter modeling based on the prokaryotic GlpT crystal structure.

PubMed

Lemieux, M Joanne

2007-01-01

The major facilitator superfamily (MFS) of transporters represents the largest family of secondary active transporters and has a diverse range of substrates. With structural information for four MFS transporters, we can see a strong structural commonality suggesting, as predicted, a common architecture for MFS transporters. The rate for crystal structure determination of MFS transporters is slow, making modeling of both prokaryotic and eukaryotic transporters more enticing. In this review, models of eukaryotic transporters Glut1, G6PT, OCT1, OCT2 and Pho84, based on the crystal structures of the prokaryotic GlpT, based on the crystal structure of LacY are discussed. The techniques used to generate the different models are compared. In addition, the validity of these models and the strategy of using prokaryotic crystal structures to model eukaryotic proteins are discussed. For comparison, E. coli GlpT was modeled based on the E. coli LacY structure and compared to the crystal structure of GlpT demonstrating that experimental evidence is essential for accurate modeling of membrane proteins.

Structural Health Monitoring of Large Structures

NASA Technical Reports Server (NTRS)

Kim, Hyoung M.; Bartkowicz, Theodore J.; Smith, Suzanne Weaver; Zimmerman, David C.

1994-01-01

This paper describes a damage detection and health monitoring method that was developed for large space structures using on-orbit modal identification. After evaluating several existing model refinement and model reduction/expansion techniques, a new approach was developed to identify the location and extent of structural damage with a limited number of measurements. A general area of structural damage is first identified and, subsequently, a specific damaged structural component is located. This approach takes advantage of two different model refinement methods (optimal-update and design sensitivity) and two different model size matching methods (model reduction and eigenvector expansion). Performance of the proposed damage detection approach was demonstrated with test data from two different laboratory truss structures. This space technology can also be applied to structural inspection of aircraft, offshore platforms, oil tankers, ridges, and buildings. In addition, its applications to model refinement will improve the design of structural systems such as automobiles and electronic packaging.

Controlling flexible structures with second order actuator dynamics

NASA Technical Reports Server (NTRS)

Inman, Daniel J.; Umland, Jeffrey W.; Bellos, John

1989-01-01

The control of flexible structures for those systems with actuators that are modeled by second order dynamics is examined. Two modeling approaches are investigated. First a stability and performance analysis is performed using a low order finite dimensional model of the structure. Secondly, a continuum model of the flexible structure to be controlled, coupled with lumped parameter second order dynamic models of the actuators performing the control is used. This model is appropriate in the modeling of the control of a flexible panel by proof-mass actuators as well as other beam, plate and shell like structural numbers. The model is verified with experimental measurements.

The diagram of phase-field crystal structures: an influence of model parameters in a two-mode approximation

NASA Astrophysics Data System (ADS)

Ankudinov, V.; Galenko, P. K.

2017-04-01

Effect of phase-field crystal model (PFC-model) parameters on the structure diagram is analyzed. The PFC-model is taken in a two-mode approximation and the construction of structure diagram follows from the free energy minimization and Maxwell thermodynamic rule. The diagram of structure’s coexistence for three dimensional crystal structures [Body-Centered-Cubic (BCC), Face-Centered-Cubic (FCC) and homogeneous structures] are constructed. An influence of the model parameters, including the stability parameters, are discussed. A question about the structure diagram construction using the two-mode PFC-model with the application to real materials is established.

Accurate protein structure modeling using sparse NMR data and homologous structure information.

PubMed

Thompson, James M; Sgourakis, Nikolaos G; Liu, Gaohua; Rossi, Paolo; Tang, Yuefeng; Mills, Jeffrey L; Szyperski, Thomas; Montelione, Gaetano T; Baker, David

2012-06-19

While information from homologous structures plays a central role in X-ray structure determination by molecular replacement, such information is rarely used in NMR structure determination because it can be incorrect, both locally and globally, when evolutionary relationships are inferred incorrectly or there has been considerable evolutionary structural divergence. Here we describe a method that allows robust modeling of protein structures of up to 225 residues by combining (1)H(N), (13)C, and (15)N backbone and (13)Cβ chemical shift data, distance restraints derived from homologous structures, and a physically realistic all-atom energy function. Accurate models are distinguished from inaccurate models generated using incorrect sequence alignments by requiring that (i) the all-atom energies of models generated using the restraints are lower than models generated in unrestrained calculations and (ii) the low-energy structures converge to within 2.0 Å backbone rmsd over 75% of the protein. Benchmark calculations on known structures and blind targets show that the method can accurately model protein structures, even with very remote homology information, to a backbone rmsd of 1.2-1.9 Å relative to the conventional determined NMR ensembles and of 0.9-1.6 Å relative to X-ray structures for well-defined regions of the protein structures. This approach facilitates the accurate modeling of protein structures using backbone chemical shift data without need for side-chain resonance assignments and extensive analysis of NOESY cross-peak assignments.

Quality assessment of protein model-structures using evolutionary conservation.

PubMed

Kalman, Matan; Ben-Tal, Nir

2010-05-15

Programs that evaluate the quality of a protein structural model are important both for validating the structure determination procedure and for guiding the model-building process. Such programs are based on properties of native structures that are generally not expected for faulty models. One such property, which is rarely used for automatic structure quality assessment, is the tendency for conserved residues to be located at the structural core and for variable residues to be located at the surface. We present ConQuass, a novel quality assessment program based on the consistency between the model structure and the protein's conservation pattern. We show that it can identify problematic structural models, and that the scores it assigns to the server models in CASP8 correlate with the similarity of the models to the native structure. We also show that when the conservation information is reliable, the method's performance is comparable and complementary to that of the other single-structure quality assessment methods that participated in CASP8 and that do not use additional structural information from homologs. A perl implementation of the method, as well as the various perl and R scripts used for the analysis are available at http://bental.tau.ac.il/ConQuass/. nirb@tauex.tau.ac.il Supplementary data are available at Bioinformatics online.

Comparative Protein Structure Modeling Using MODELLER.

PubMed

Webb, Benjamin; Sali, Andrej

2014-09-08

Functional characterization of a protein sequence is one of the most frequent problems in biology. This task is usually facilitated by accurate three-dimensional (3-D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described. Copyright © 2014 John Wiley & Sons, Inc.

A sampling-based method for ranking protein structural models by integrating multiple scores and features.

PubMed

Shi, Xiaohu; Zhang, Jingfen; He, Zhiquan; Shang, Yi; Xu, Dong

2011-09-01

One of the major challenges in protein tertiary structure prediction is structure quality assessment. In many cases, protein structure prediction tools generate good structural models, but fail to select the best models from a huge number of candidates as the final output. In this study, we developed a sampling-based machine-learning method to rank protein structural models by integrating multiple scores and features. First, features such as predicted secondary structure, solvent accessibility and residue-residue contact information are integrated by two Radial Basis Function (RBF) models trained from different datasets. Then, the two RBF scores and five selected scoring functions developed by others, i.e., Opus-CA, Opus-PSP, DFIRE, RAPDF, and Cheng Score are synthesized by a sampling method. At last, another integrated RBF model ranks the structural models according to the features of sampling distribution. We tested the proposed method by using two different datasets, including the CASP server prediction models of all CASP8 targets and a set of models generated by our in-house software MUFOLD. The test result shows that our method outperforms any individual scoring function on both best model selection, and overall correlation between the predicted ranking and the actual ranking of structural quality.

Evaluation of protein-protein docking model structures using all-atom molecular dynamics simulations combined with the solution theory in the energy representation

NASA Astrophysics Data System (ADS)

Takemura, Kazuhiro; Guo, Hao; Sakuraba, Shun; Matubayasi, Nobuyuki; Kitao, Akio

2012-12-01

We propose a method to evaluate binding free energy differences among distinct protein-protein complex model structures through all-atom molecular dynamics simulations in explicit water using the solution theory in the energy representation. Complex model structures are generated from a pair of monomeric structures using the rigid-body docking program ZDOCK. After structure refinement by side chain optimization and all-atom molecular dynamics simulations in explicit water, complex models are evaluated based on the sum of their conformational and solvation free energies, the latter calculated from the energy distribution functions obtained from relatively short molecular dynamics simulations of the complex in water and of pure water based on the solution theory in the energy representation. We examined protein-protein complex model structures of two protein-protein complex systems, bovine trypsin/CMTI-1 squash inhibitor (PDB ID: 1PPE) and RNase SA/barstar (PDB ID: 1AY7), for which both complex and monomer structures were determined experimentally. For each system, we calculated the energies for the crystal complex structure and twelve generated model structures including the model most similar to the crystal structure and very different from it. In both systems, the sum of the conformational and solvation free energies tended to be lower for the structure similar to the crystal. We concluded that our energy calculation method is useful for selecting low energy complex models similar to the crystal structure from among a set of generated models.

Evaluation of protein-protein docking model structures using all-atom molecular dynamics simulations combined with the solution theory in the energy representation.

PubMed

Takemura, Kazuhiro; Guo, Hao; Sakuraba, Shun; Matubayasi, Nobuyuki; Kitao, Akio

2012-12-07

We propose a method to evaluate binding free energy differences among distinct protein-protein complex model structures through all-atom molecular dynamics simulations in explicit water using the solution theory in the energy representation. Complex model structures are generated from a pair of monomeric structures using the rigid-body docking program ZDOCK. After structure refinement by side chain optimization and all-atom molecular dynamics simulations in explicit water, complex models are evaluated based on the sum of their conformational and solvation free energies, the latter calculated from the energy distribution functions obtained from relatively short molecular dynamics simulations of the complex in water and of pure water based on the solution theory in the energy representation. We examined protein-protein complex model structures of two protein-protein complex systems, bovine trypsin/CMTI-1 squash inhibitor (PDB ID: 1PPE) and RNase SA/barstar (PDB ID: 1AY7), for which both complex and monomer structures were determined experimentally. For each system, we calculated the energies for the crystal complex structure and twelve generated model structures including the model most similar to the crystal structure and very different from it. In both systems, the sum of the conformational and solvation free energies tended to be lower for the structure similar to the crystal. We concluded that our energy calculation method is useful for selecting low energy complex models similar to the crystal structure from among a set of generated models.

Applying Meta-Analysis to Structural Equation Modeling

ERIC Educational Resources Information Center

Hedges, Larry V.

2016-01-01

Structural equation models play an important role in the social sciences. Consequently, there is an increasing use of meta-analytic methods to combine evidence from studies that estimate the parameters of structural equation models. Two approaches are used to combine evidence from structural equation models: A direct approach that combines…

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

NASA Astrophysics Data System (ADS)

Knoben, Wouter; Woods, Ross; Freer, Jim

2016-04-01

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

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

PubMed Central

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

2013-01-01

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

Thermal and structural analysis of the GOES scan mirror's on orbit performance

NASA Technical Reports Server (NTRS)

Zurmehly, G. E.; Hookman, R. A.

1991-01-01

The on-orbit performance of the GOES satellite's scan mirror has been predicted by means of thermal, structural, and optical models. A simpler-than-conventional thermal model was used to reduce the time required to obtain orbital predictions, and the structural model was used to predict on-earth gravity sag and on-orbit distortions. The transfer of data from the thermal model to the structural model was automated for a given set of thermal nodes and structural grids.

RNA 3D Structure Modeling by Combination of Template-Based Method ModeRNA, Template-Free Folding with SimRNA, and Refinement with QRNAS.

PubMed

Piatkowski, Pawel; Kasprzak, Joanna M; Kumar, Deepak; Magnus, Marcin; Chojnowski, Grzegorz; Bujnicki, Janusz M

2016-01-01

RNA encompasses an essential part of all known forms of life. The functions of many RNA molecules are dependent on their ability to form complex three-dimensional (3D) structures. However, experimental determination of RNA 3D structures is laborious and challenging, and therefore, the majority of known RNAs remain structurally uncharacterized. To address this problem, computational structure prediction methods were developed that either utilize information derived from known structures of other RNA molecules (by way of template-based modeling) or attempt to simulate the physical process of RNA structure formation (by way of template-free modeling). All computational methods suffer from various limitations that make theoretical models less reliable than high-resolution experimentally determined structures. This chapter provides a protocol for computational modeling of RNA 3D structure that overcomes major limitations by combining two complementary approaches: template-based modeling that is capable of predicting global architectures based on similarity to other molecules but often fails to predict local unique features, and template-free modeling that can predict the local folding, but is limited to modeling the structure of relatively small molecules. Here, we combine the use of a template-based method ModeRNA with a template-free method SimRNA. ModeRNA requires a sequence alignment of the target RNA sequence to be modeled with a template of the known structure; it generates a model that predicts the structure of a conserved core and provides a starting point for modeling of variable regions. SimRNA can be used to fold small RNAs (<80 nt) without any additional structural information, and to refold parts of models for larger RNAs that have a correctly modeled core. ModeRNA can be either downloaded, compiled and run locally or run through a web interface at http://genesilico.pl/modernaserver/ . SimRNA is currently available to download for local use as a precompiled software package at http://genesilico.pl/software/stand-alone/simrna and as a web server at http://genesilico.pl/SimRNAweb . For model optimization we use QRNAS, available at http://genesilico.pl/qrnas .

Rainfall runoff modelling of the Upper Ganga and Brahmaputra basins using PERSiST.

PubMed

Futter, M N; Whitehead, P G; Sarkar, S; Rodda, H; Crossman, J

2015-06-01

There are ongoing discussions about the appropriate level of complexity and sources of uncertainty in rainfall runoff models. Simulations for operational hydrology, flood forecasting or nutrient transport all warrant different levels of complexity in the modelling approach. More complex model structures are appropriate for simulations of land-cover dependent nutrient transport while more parsimonious model structures may be adequate for runoff simulation. The appropriate level of complexity is also dependent on data availability. Here, we use PERSiST; a simple, semi-distributed dynamic rainfall-runoff modelling toolkit to simulate flows in the Upper Ganges and Brahmaputra rivers. We present two sets of simulations driven by single time series of daily precipitation and temperature using simple (A) and complex (B) model structures based on uniform and hydrochemically relevant land covers respectively. Models were compared based on ensembles of Bayesian Information Criterion (BIC) statistics. Equifinality was observed for parameters but not for model structures. Model performance was better for the more complex (B) structural representations than for parsimonious model structures. The results show that structural uncertainty is more important than parameter uncertainty. The ensembles of BIC statistics suggested that neither structural representation was preferable in a statistical sense. Simulations presented here confirm that relatively simple models with limited data requirements can be used to credibly simulate flows and water balance components needed for nutrient flux modelling in large, data-poor basins.

Hierarchical mixture of experts and diagnostic modeling approach to reduce hydrologic model structural uncertainty: STRUCTURAL UNCERTAINTY DIAGNOSTICS

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

Moges, Edom; Demissie, Yonas; Li, Hong-Yi

2016-04-01

In most water resources applications, a single model structure might be inadequate to capture the dynamic multi-scale interactions among different hydrological processes. Calibrating single models for dynamic catchments, where multiple dominant processes exist, can result in displacement of errors from structure to parameters, which in turn leads to over-correction and biased predictions. An alternative to a single model structure is to develop local expert structures that are effective in representing the dominant components of the hydrologic process and adaptively integrate them based on an indicator variable. In this study, the Hierarchical Mixture of Experts (HME) framework is applied to integratemore » expert model structures representing the different components of the hydrologic process. Various signature diagnostic analyses are used to assess the presence of multiple dominant processes and the adequacy of a single model, as well as to identify the structures of the expert models. The approaches are applied for two distinct catchments, the Guadalupe River (Texas) and the French Broad River (North Carolina) from the Model Parameter Estimation Experiment (MOPEX), using different structures of the HBV model. The results show that the HME approach has a better performance over the single model for the Guadalupe catchment, where multiple dominant processes are witnessed through diagnostic measures. Whereas, the diagnostics and aggregated performance measures prove that French Broad has a homogeneous catchment response, making the single model adequate to capture the response.« less

Comparative Protein Structure Modeling Using MODELLER

PubMed Central

Webb, Benjamin; Sali, Andrej

2016-01-01

Comparative protein structure modeling predicts the three-dimensional structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and how to use the ModBase database of such models, and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described. PMID:27322406

Fundamental studies of structure borne noise for advanced turboprop applications

NASA Technical Reports Server (NTRS)

Eversman, W.; Koval, L. R.

1985-01-01

The transmission of sound generated by wing-mounted, advanced turboprop engines into the cabin interior via structural paths is considered. The structural model employed is a beam representation of the wing box carried into the fuselage via a representative frame type of carry through structure. The structure for the cabin cavity is a stiffened shell of rectangular or cylindrical geometry. The structure is modelled using a finite element formulation and the acoustic cavity is modelled using an analytical representation appropriate for the geometry. The structural and acoustic models are coupled by the use of hard wall cavity modes for the interior and vacuum structural modes for the shell. The coupling is accomplished using a combination of analytical and finite element models. The advantage is the substantial reduction in dimensionality achieved by modelling the interior analytically. The mathematical model for the interior noise problem is demonstrated with a simple plate/cavity system which has all of the features of the fuselage interior noise problem.

Flight-vehicle materials, structures, and dynamics - Assessment and future directions. Vol. 5 - Structural dynamics and aeroelasticity

NASA Technical Reports Server (NTRS)

Noor, Ahmed K. (Editor); Venneri, Samuel L. (Editor)

1993-01-01

Various papers on flight vehicle materials, structures, and dynamics are presented. Individual topics addressed include: general modeling methods, component modeling techniques, time-domain computational techniques, dynamics of articulated structures, structural dynamics in rotating systems, structural dynamics in rotorcraft, damping in structures, structural acoustics, structural design for control, structural modeling for control, control strategies for structures, system identification, overall assessment of needs and benefits in structural dynamics and controlled structures. Also discussed are: experimental aeroelasticity in wind tunnels, aeroservoelasticity, nonlinear aeroelasticity, aeroelasticity problems in turbomachines, rotary-wing aeroelasticity with application to VTOL vehicles, computational aeroelasticity, structural dynamic testing and instrumentation.

Model correlation and damage location for large space truss structures: Secant method development and evaluation

NASA Technical Reports Server (NTRS)

Smith, Suzanne Weaver; Beattie, Christopher A.

1991-01-01

On-orbit testing of a large space structure will be required to complete the certification of any mathematical model for the structure dynamic response. The process of establishing a mathematical model that matches measured structure response is referred to as model correlation. Most model correlation approaches have an identification technique to determine structural characteristics from the measurements of the structure response. This problem is approached with one particular class of identification techniques - matrix adjustment methods - which use measured data to produce an optimal update of the structure property matrix, often the stiffness matrix. New methods were developed for identification to handle problems of the size and complexity expected for large space structures. Further development and refinement of these secant-method identification algorithms were undertaken. Also, evaluation of these techniques is an approach for model correlation and damage location was initiated.

Exploring Human Diseases and Biological Mechanisms by Protein Structure Prediction and Modeling.

PubMed

Wang, Juexin; Luttrell, Joseph; Zhang, Ning; Khan, Saad; Shi, NianQing; Wang, Michael X; Kang, Jing-Qiong; Wang, Zheng; Xu, Dong

2016-01-01

Protein structure prediction and modeling provide a tool for understanding protein functions by computationally constructing protein structures from amino acid sequences and analyzing them. With help from protein prediction tools and web servers, users can obtain the three-dimensional protein structure models and gain knowledge of functions from the proteins. In this chapter, we will provide several examples of such studies. As an example, structure modeling methods were used to investigate the relation between mutation-caused misfolding of protein and human diseases including epilepsy and leukemia. Protein structure prediction and modeling were also applied in nucleotide-gated channels and their interaction interfaces to investigate their roles in brain and heart cells. In molecular mechanism studies of plants, rice salinity tolerance mechanism was studied via structure modeling on crucial proteins identified by systems biology analysis; trait-associated protein-protein interactions were modeled, which sheds some light on the roles of mutations in soybean oil/protein content. In the age of precision medicine, we believe protein structure prediction and modeling will play more and more important roles in investigating biomedical mechanism of diseases and drug design.

Piezoceramic devices and artificial intelligence time varying concepts in smart structures

NASA Technical Reports Server (NTRS)

Hanagud, S.; Calise, A. J.; Glass, B. J.

1990-01-01

The problem of development of smart structures and their vibration control by the use of piezoceramic sensors and actuators have been discussed. In particular, these structures are assumed to have time varying model form and parameters. The model form may change significantly and suddenly. Combined identification of the model from parameters of these structures and model adaptive control of these structures are discussed in this paper.

Three novel approaches to structural identifiability analysis in mixed-effects models.

PubMed

Janzén, David L I; Jirstrand, Mats; Chappell, Michael J; Evans, Neil D

2016-05-06

Structural identifiability is a concept that considers whether the structure of a model together with a set of input-output relations uniquely determines the model parameters. In the mathematical modelling of biological systems, structural identifiability is an important concept since biological interpretations are typically made from the parameter estimates. For a system defined by ordinary differential equations, several methods have been developed to analyse whether the model is structurally identifiable or otherwise. Another well-used modelling framework, which is particularly useful when the experimental data are sparsely sampled and the population variance is of interest, is mixed-effects modelling. However, established identifiability analysis techniques for ordinary differential equations are not directly applicable to such models. In this paper, we present and apply three different methods that can be used to study structural identifiability in mixed-effects models. The first method, called the repeated measurement approach, is based on applying a set of previously established statistical theorems. The second method, called the augmented system approach, is based on augmenting the mixed-effects model to an extended state-space form. The third method, called the Laplace transform mixed-effects extension, is based on considering the moment invariants of the systems transfer function as functions of random variables. To illustrate, compare and contrast the application of the three methods, they are applied to a set of mixed-effects models. Three structural identifiability analysis methods applicable to mixed-effects models have been presented in this paper. As method development of structural identifiability techniques for mixed-effects models has been given very little attention, despite mixed-effects models being widely used, the methods presented in this paper provides a way of handling structural identifiability in mixed-effects models previously not possible. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Model-based active control of a continuous structure subjected to moving loads

NASA Astrophysics Data System (ADS)

Stancioiu, D.; Ouyang, H.

2016-09-01

Modelling of a structure is an important preliminary step of structural control. The main objectives of the modelling, which are almost always antagonistic are accuracy and simplicity of the model. The first part of this study focuses on the experimental and theoretical modelling of a structure subjected to the action of one or two decelerating moving carriages modelled as masses. The aim of this part is to obtain a simple but accurate model which will include not only the structure-moving load interaction but also the actuators dynamics. A small scale rig is designed to represent a four-span continuous metallic bridge structure with miniature guiding rails. A series of tests are run subjecting the structure to the action of one or two minicarriages with different loads that were launched along the structure at different initial speeds. The second part is dedicated to model based control design where a feedback controller is designed and tested against the validated model. The study shows that a positive position feedback is able to improve system dynamics but also shows some of the limitations of state- space methods for this type of system.

Protein Structure Determination using Metagenome sequence data

PubMed Central

Ovchinnikov, Sergey; Park, Hahnbeom; Varghese, Neha; Huang, Po-Ssu; Pavlopoulos, Georgios A.; Kim, David E.; Kamisetty, Hetunandan; Kyrpides, Nikos C.; Baker, David

2017-01-01

Despite decades of work by structural biologists, there are still ~5200 protein families with unknown structure outside the range of comparative modeling. We show that Rosetta structure prediction guided by residue-residue contacts inferred from evolutionary information can accurately model proteins that belong to large families, and that metagenome sequence data more than triples the number of protein families with sufficient sequences for accurate modeling. We then integrate metagenome data, contact based structure matching and Rosetta structure calculations to generate models for 614 protein families with currently unknown structures; 206 are membrane proteins and 137 have folds not represented in the PDB. This approach provides the representative models for large protein families originally envisioned as the goal of the protein structure initiative at a fraction of the cost. PMID:28104891

Structural Modeling Using "Scanning and Mapping" Technique

NASA Technical Reports Server (NTRS)

Amos, Courtney L.; Dash, Gerald S.; Shen, J. Y.; Ferguson, Frederick; Noga, Donald F. (Technical Monitor)

2000-01-01

Supported by NASA Glenn Center, we are in the process developing a structural damage diagnostic and monitoring system for rocket engines, which consists of five modules: Structural Modeling, Measurement Data Pre-Processor, Structural System Identification, Damage Detection Criterion, and Computer Visualization. The function of the system is to detect damage as it is incurred by the engine structures. The scientific principle to identify damage is to utilize the changes in the vibrational properties between the pre-damaged and post-damaged structures. The vibrational properties of the pre-damaged structure can be obtained based on an analytic computer model of the structure. Thus, as the first stage of the whole research plan, we currently focus on the first module - Structural Modeling. Three computer software packages are selected, and will be integrated for this purpose. They are PhotoModeler-Pro, AutoCAD-R14, and MSC/NASTRAN. AutoCAD is the most popular PC-CAD system currently available in the market. For our purpose, it plays like an interface to generate structural models of any particular engine parts or assembly, which is then passed to MSC/NASTRAN for extracting structural dynamic properties. Although AutoCAD is a powerful structural modeling tool, the complexity of engine components requires a further improvement in structural modeling techniques. We are working on a so-called "scanning and mapping" technique, which is a relatively new technique. The basic idea is to producing a full and accurate 3D structural model by tracing on multiple overlapping photographs taken from different angles. There is no need to input point positions, angles, distances or axes. Photographs can be taken by any types of cameras with different lenses. With the integration of such a modeling technique, the capability of structural modeling will be enhanced. The prototypes of any complex structural components will be produced by PhotoModeler first based on existing similar components, then passed to AutoCAD for modification and correction of any discrepancies seen in the Photomodeler version of the 3Dmodel. These three software packages are fully compatible. The DXF file can be used to transfer drawings among those packages. To begin this entire process, we are using a small replica of an actual engine blade as a test object. This paper introduces the accomplishment of our recent work.

Ensemble-based evaluation for protein structure models.

PubMed

Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke

2016-06-15

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

Ensemble-based evaluation for protein structure models

PubMed Central

Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke

2016-01-01

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

Predicting RNA 3D structure using a coarse-grain helix-centered model

PubMed Central

Kerpedjiev, Peter; Höner zu Siederdissen, Christian; Hofacker, Ivo L.

2015-01-01

A 3D model of RNA structure can provide information about its function and regulation that is not possible with just the sequence or secondary structure. Current models suffer from low accuracy and long running times and either neglect or presume knowledge of the long-range interactions which stabilize the tertiary structure. Our coarse-grained, helix-based, tertiary structure model operates with only a few degrees of freedom compared with all-atom models while preserving the ability to sample tertiary structures given a secondary structure. It strikes a balance between the precision of an all-atom tertiary structure model and the simplicity and effectiveness of a secondary structure representation. It provides a simplified tool for exploring global arrangements of helices and loops within RNA structures. We provide an example of a novel energy function relying only on the positions of stems and loops. We show that coupling our model to this energy function produces predictions as good as or better than the current state of the art tools. We propose that given the wide range of conformational space that needs to be explored, a coarse-grain approach can explore more conformations in less iterations than an all-atom model coupled to a fine-grain energy function. Finally, we emphasize the overarching theme of providing an ensemble of predicted structures, something which our tool excels at, rather than providing a handful of the lowest energy structures. PMID:25904133

Large-scale model quality assessment for improving protein tertiary structure prediction.

PubMed

Cao, Renzhi; Bhattacharya, Debswapna; Adhikari, Badri; Li, Jilong; Cheng, Jianlin

2015-06-15

Sampling structural models and ranking them are the two major challenges of protein structure prediction. Traditional protein structure prediction methods generally use one or a few quality assessment (QA) methods to select the best-predicted models, which cannot consistently select relatively better models and rank a large number of models well. Here, we develop a novel large-scale model QA method in conjunction with model clustering to rank and select protein structural models. It unprecedentedly applied 14 model QA methods to generate consensus model rankings, followed by model refinement based on model combination (i.e. averaging). Our experiment demonstrates that the large-scale model QA approach is more consistent and robust in selecting models of better quality than any individual QA method. Our method was blindly tested during the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) as MULTICOM group. It was officially ranked third out of all 143 human and server predictors according to the total scores of the first models predicted for 78 CASP11 protein domains and second according to the total scores of the best of the five models predicted for these domains. MULTICOM's outstanding performance in the extremely competitive 2014 CASP11 experiment proves that our large-scale QA approach together with model clustering is a promising solution to one of the two major problems in protein structure modeling. The web server is available at: http://sysbio.rnet.missouri.edu/multicom_cluster/human/. © The Author 2015. Published by Oxford University Press.

Comparing model-based adaptive LMS filters and a model-free hysteresis loop analysis method for structural health monitoring

NASA Astrophysics Data System (ADS)

Zhou, Cong; Chase, J. Geoffrey; Rodgers, Geoffrey W.; Xu, Chao

2017-02-01

The model-free hysteresis loop analysis (HLA) method for structural health monitoring (SHM) has significant advantages over the traditional model-based SHM methods that require a suitable baseline model to represent the actual system response. This paper provides a unique validation against both an experimental reinforced concrete (RC) building and a calibrated numerical model to delineate the capability of the model-free HLA method and the adaptive least mean squares (LMS) model-based method in detecting, localizing and quantifying damage that may not be visible, observable in overall structural response. Results clearly show the model-free HLA method is capable of adapting to changes in how structures transfer load or demand across structural elements over time and multiple events of different size. However, the adaptive LMS model-based method presented an image of greater spread of lesser damage over time and story when the baseline model is not well defined. Finally, the two algorithms are tested over a simpler hysteretic behaviour typical steel structure to quantify the impact of model mismatch between the baseline model used for identification and the actual response. The overall results highlight the need for model-based methods to have an appropriate model that can capture the observed response, in order to yield accurate results, even in small events where the structure remains linear.

Taxometric Analysis as a General Strategy for Distinguishing Categorical from Dimensional Latent Structure

ERIC Educational Resources Information Center

McGrath, Robert E.; Walters, Glenn D.

2012-01-01

Statistical analyses investigating latent structure can be divided into those that estimate structural model parameters and those that detect the structural model type. The most basic distinction among structure types is between categorical (discrete) and dimensional (continuous) models. It is a common, and potentially misleading, practice to…

DIVWAG Model Documentation. Volume II. Programmer/Analyst Manual. Part 4.

DTIC Science & Technology

1976-07-01

Model Constant Data Deck Structure . .. .... IV-13-A-40 Appendix B. Movement Model Program Descriptions . .. .. . .IV-13-B-1 1. Introduction...Data ................ IV-15-A-17 11. Airmobile Constant Data Deck Structure .. ...... .. IV-15-A-30 Appendix B. Airmobile Model Program Descriptions...Make no changes. 12. AIRMOBILE CONSTANT DATA DECK STRUCTURE . The deck structure required by the Airmobile Model constant data load program and the data

Model reference, sliding mode adaptive control for flexible structures

NASA Technical Reports Server (NTRS)

Yurkovich, S.; Ozguner, U.; Al-Abbass, F.

1988-01-01

A decentralized model reference adaptive approach using a variable-structure sliding model control has been developed for the vibration suppression of large flexible structures. Local models are derived based upon the desired damping and response time in a model-following scheme, and variable structure controllers are then designed which employ colocated angular rate and position feedback. Numerical simulations have been performed using NASA's flexible grid experimental apparatus.

Advances in Homology Protein Structure Modeling

PubMed Central

Xiang, Zhexin

2007-01-01

Homology modeling plays a central role in determining protein structure in the structural genomics project. The importance of homology modeling has been steadily increasing because of the large gap that exists between the overwhelming number of available protein sequences and experimentally solved protein structures, and also, more importantly, because of the increasing reliability and accuracy of the method. In fact, a protein sequence with over 30% identity to a known structure can often be predicted with an accuracy equivalent to a low-resolution X-ray structure. The recent advances in homology modeling, especially in detecting distant homologues, aligning sequences with template structures, modeling of loops and side chains, as well as detecting errors in a model, have contributed to reliable prediction of protein structure, which was not possible even several years ago. The ongoing efforts in solving protein structures, which can be time-consuming and often difficult, will continue to spur the development of a host of new computational methods that can fill in the gap and further contribute to understanding the relationship between protein structure and function. PMID:16787261

Intelligent-based Structural Damage Detection Model

NASA Astrophysics Data System (ADS)

Lee, Eric Wai Ming; Yu, Kin Fung

2010-05-01

This paper presents the application of a novel Artificial Neural Network (ANN) model for the diagnosis of structural damage. The ANN model, denoted as the GRNNFA, is a hybrid model combining the General Regression Neural Network Model (GRNN) and the Fuzzy ART (FA) model. It not only retains the important features of the GRNN and FA models (i.e. fast and stable network training and incremental growth of network structure) but also facilitates the removal of the noise embedded in the training samples. Structural damage alters the stiffness distribution of the structure and so as to change the natural frequencies and mode shapes of the system. The measured modal parameter changes due to a particular damage are treated as patterns for that damage. The proposed GRNNFA model was trained to learn those patterns in order to detect the possible damage location of the structure. Simulated data is employed to verify and illustrate the procedures of the proposed ANN-based damage diagnosis methodology. The results of this study have demonstrated the feasibility of applying the GRNNFA model to structural damage diagnosis even when the training samples were noise contaminated.

Conformational Sampling in Template-Free Protein Loop Structure Modeling: An Overview

PubMed Central

Li, Yaohang

2013-01-01

Accurately modeling protein loops is an important step to predict three-dimensional structures as well as to understand functions of many proteins. Because of their high flexibility, modeling the three-dimensional structures of loops is difficult and is usually treated as a “mini protein folding problem” under geometric constraints. In the past decade, there has been remarkable progress in template-free loop structure modeling due to advances of computational methods as well as stably increasing number of known structures available in PDB. This mini review provides an overview on the recent computational approaches for loop structure modeling. In particular, we focus on the approaches of sampling loop conformation space, which is a critical step to obtain high resolution models in template-free methods. We review the potential energy functions for loop modeling, loop buildup mechanisms to satisfy geometric constraints, and loop conformation sampling algorithms. The recent loop modeling results are also summarized. PMID:24688696

Conformational sampling in template-free protein loop structure modeling: an overview.

PubMed

Li, Yaohang

2013-01-01

Accurately modeling protein loops is an important step to predict three-dimensional structures as well as to understand functions of many proteins. Because of their high flexibility, modeling the three-dimensional structures of loops is difficult and is usually treated as a "mini protein folding problem" under geometric constraints. In the past decade, there has been remarkable progress in template-free loop structure modeling due to advances of computational methods as well as stably increasing number of known structures available in PDB. This mini review provides an overview on the recent computational approaches for loop structure modeling. In particular, we focus on the approaches of sampling loop conformation space, which is a critical step to obtain high resolution models in template-free methods. We review the potential energy functions for loop modeling, loop buildup mechanisms to satisfy geometric constraints, and loop conformation sampling algorithms. The recent loop modeling results are also summarized.

Automated determination of fibrillar structures by simultaneous model building and fiber diffraction refinement.

PubMed

Potrzebowski, Wojciech; André, Ingemar

2015-07-01

For highly oriented fibrillar molecules, three-dimensional structures can often be determined from X-ray fiber diffraction data. However, because of limited information content, structure determination and validation can be challenging. We demonstrate that automated structure determination of protein fibers can be achieved by guiding the building of macromolecular models with fiber diffraction data. We illustrate the power of our approach by determining the structures of six bacteriophage viruses de novo using fiber diffraction data alone and together with solid-state NMR data. Furthermore, we demonstrate the feasibility of molecular replacement from monomeric and fibrillar templates by solving the structure of a plant virus using homology modeling and protein-protein docking. The generated models explain the experimental data to the same degree as deposited reference structures but with improved structural quality. We also developed a cross-validation method for model selection. The results highlight the power of fiber diffraction data as structural constraints.

Coverage of whole proteome by structural genomics observed through protein homology modeling database

PubMed Central

Yamaguchi, Akihiro; Go, Mitiko

2006-01-01

We have been developing FAMSBASE, a protein homology-modeling database of whole ORFs predicted from genome sequences. The latest update of FAMSBASE (http://daisy.nagahama-i-bio.ac.jp/Famsbase/), which is based on the protein three-dimensional (3D) structures released by November 2003, contains modeled 3D structures for 368,724 open reading frames (ORFs) derived from genomes of 276 species, namely 17 archaebacterial, 130 eubacterial, 18 eukaryotic and 111 phage genomes. Those 276 genomes are predicted to have 734,193 ORFs in total and the current FAMSBASE contains protein 3D structure of approximately 50% of the ORF products. However, cases that a modeled 3D structure covers the whole part of an ORF product are rare. When portion of an ORF with 3D structure is compared in three kingdoms of life, in archaebacteria and eubacteria, approximately 60% of the ORFs have modeled 3D structures covering almost the entire amino acid sequences, however, the percentage falls to about 30% in eukaryotes. When annual differences in the number of ORFs with modeled 3D structure are calculated, the fraction of modeled 3D structures of soluble protein for archaebacteria is increased by 5%, and that for eubacteria by 7% in the last 3 years. Assuming that this rate would be maintained and that determination of 3D structures for predicted disordered regions is unattainable, whole soluble protein model structures of prokaryotes without the putative disordered regions will be in hand within 15 years. For eukaryotic proteins, they will be in hand within 25 years. The 3D structures we will have at those times are not the 3D structure of the entire proteins encoded in single ORFs, but the 3D structures of separate structural domains. Measuring or predicting spatial arrangements of structural domains in an ORF will then be a coming issue of structural genomics. PMID:17146617

Method of performing computational aeroelastic analyses

NASA Technical Reports Server (NTRS)

Silva, Walter A. (Inventor)

2011-01-01

Computational aeroelastic analyses typically use a mathematical model for the structural modes of a flexible structure and a nonlinear aerodynamic model that can generate a plurality of unsteady aerodynamic responses based on the structural modes for conditions defining an aerodynamic condition of the flexible structure. In the present invention, a linear state-space model is generated using a single execution of the nonlinear aerodynamic model for all of the structural modes where a family of orthogonal functions is used as the inputs. Then, static and dynamic aeroelastic solutions are generated using computational interaction between the mathematical model and the linear state-space model for a plurality of periodic points in time.

Modeling the Structure of Helical Assemblies with Experimental Constraints in Rosetta.

PubMed

André, Ingemar

2018-01-01

Determining high-resolution structures of proteins with helical symmetry can be challenging due to limitations in experimental data. In such instances, structure-based protein simulations driven by experimental data can provide a valuable approach for building models of helical assemblies. This chapter describes how the Rosetta macromolecular package can be used to model homomeric protein assemblies with helical symmetry in a range of modeling scenarios including energy refinement, symmetrical docking, comparative modeling, and de novo structure prediction. Data-guided structure modeling of helical assemblies with experimental information from electron density, X-ray fiber diffraction, solid-state NMR, and chemical cross-linking mass spectrometry is also described.

Model representations of kerogen structures: An insight from density functional theory calculations and spectroscopic measurements

DOE PAGES

Weck, Philippe F.; Kim, Eunja; Wang, Yifeng; ...

2017-08-01

Molecular structures of kerogen control hydrocarbon production in unconventional reservoirs. Significant progress has been made in developing model representations of various kerogen structures. These models have been widely used for the prediction of gas adsorption and migration in shale matrix. However, using density functional perturbation theory (DFPT) calculations and vibrational spectroscopic measurements, we here show that a large gap may still remain between the existing model representations and actual kerogen structures, therefore calling for new model development. Using DFPT, we calculated Fourier transform infrared (FTIR) spectra for six most widely used kerogen structure models. The computed spectra were then systematicallymore » compared to the FTIR absorption spectra collected for kerogen samples isolated from Mancos, Woodford and Marcellus formations representing a wide range of kerogen origin and maturation conditions. Limited agreement between the model predictions and the measurements highlights that the existing kerogen models may still miss some key features in structural representation. A combination of DFPT calculations with spectroscopic measurements may provide a useful diagnostic tool for assessing the adequacy of a proposed structural model as well as for future model development. This approach may eventually help develop comprehensive infrared (IR)-fingerprints for tracing kerogen evolution.« less

Model representations of kerogen structures: An insight from density functional theory calculations and spectroscopic measurements.

PubMed

Weck, Philippe F; Kim, Eunja; Wang, Yifeng; Kruichak, Jessica N; Mills, Melissa M; Matteo, Edward N; Pellenq, Roland J-M

2017-08-01

Molecular structures of kerogen control hydrocarbon production in unconventional reservoirs. Significant progress has been made in developing model representations of various kerogen structures. These models have been widely used for the prediction of gas adsorption and migration in shale matrix. However, using density functional perturbation theory (DFPT) calculations and vibrational spectroscopic measurements, we here show that a large gap may still remain between the existing model representations and actual kerogen structures, therefore calling for new model development. Using DFPT, we calculated Fourier transform infrared (FTIR) spectra for six most widely used kerogen structure models. The computed spectra were then systematically compared to the FTIR absorption spectra collected for kerogen samples isolated from Mancos, Woodford and Marcellus formations representing a wide range of kerogen origin and maturation conditions. Limited agreement between the model predictions and the measurements highlights that the existing kerogen models may still miss some key features in structural representation. A combination of DFPT calculations with spectroscopic measurements may provide a useful diagnostic tool for assessing the adequacy of a proposed structural model as well as for future model development. This approach may eventually help develop comprehensive infrared (IR)-fingerprints for tracing kerogen evolution.

Model representations of kerogen structures: An insight from density functional theory calculations and spectroscopic measurements

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

Weck, Philippe F.; Kim, Eunja; Wang, Yifeng

Molecular structures of kerogen control hydrocarbon production in unconventional reservoirs. Significant progress has been made in developing model representations of various kerogen structures. These models have been widely used for the prediction of gas adsorption and migration in shale matrix. However, using density functional perturbation theory (DFPT) calculations and vibrational spectroscopic measurements, we here show that a large gap may still remain between the existing model representations and actual kerogen structures, therefore calling for new model development. Using DFPT, we calculated Fourier transform infrared (FTIR) spectra for six most widely used kerogen structure models. The computed spectra were then systematicallymore » compared to the FTIR absorption spectra collected for kerogen samples isolated from Mancos, Woodford and Marcellus formations representing a wide range of kerogen origin and maturation conditions. Limited agreement between the model predictions and the measurements highlights that the existing kerogen models may still miss some key features in structural representation. A combination of DFPT calculations with spectroscopic measurements may provide a useful diagnostic tool for assessing the adequacy of a proposed structural model as well as for future model development. This approach may eventually help develop comprehensive infrared (IR)-fingerprints for tracing kerogen evolution.« less

The Specific Analysis of Structural Equation Models

ERIC Educational Resources Information Center

McDonald, Roderick P.

2004-01-01

Conventional structural equation modeling fits a covariance structure implied by the equations of the model. This treatment of the model often gives misleading results because overall goodness of fit tests do not focus on the specific constraints implied by the model. An alternative treatment arising from Pearl's directed acyclic graph theory…

Data-assisted protein structure modeling by global optimization in CASP12.

PubMed

Joo, Keehyoung; Heo, Seungryong; Joung, InSuk; Hong, Seung Hwan; Lee, Sung Jong; Lee, Jooyoung

2018-03-01

In CASP12, 2 types of data-assisted protein structure modeling were experimented. Either SAXS experimental data or cross-linking experimental data was provided for a selected number of CASP12 targets that the CASP12 predictor could utilize for better protein structure modeling. We devised 2 separate energy terms for SAXS data and cross-linking data to drive the model structures into more native-like structures that satisfied the given experimental data as much as possible. In CASP11, we successfully performed protein structure modeling using simulated sparse and ambiguously assigned NOE data and/or correct residue-residue contact information, where the only energy term that folded the protein into its native structure was the term which was originated from the given experimental data. However, the 2 types of experimental data provided in CASP12 were far from being sufficient enough to fold the target protein into its native structure because SAXS data provides only the overall shape of the molecule and the cross-linking contact information provides only very low-resolution distance information. For this reason, we combined the SAXS or cross-linking energy term with our regular modeling energy function that includes both the template energy term and the de novo energy terms. By optimizing the newly formulated energy function, we obtained protein models that fit better with provided SAXS data than the X-ray structure of the target. However, the improvement of the model relative to the 1 modeled without the SAXS data, was not significant. Consistent structural improvement was achieved by incorporating cross-linking data into the protein structure modeling. © 2018 Wiley Periodicals, Inc.

Calibration of aero-structural reduced order models using full-field experimental measurements

NASA Astrophysics Data System (ADS)

Perez, R.; Bartram, G.; Beberniss, T.; Wiebe, R.; Spottswood, S. M.

2017-03-01

The structural response of hypersonic aircraft panels is a multi-disciplinary problem, where the nonlinear structural dynamics, aerodynamics, and heat transfer models are coupled. A clear understanding of the impact of high-speed flow effects on the structural response, and the potential influence of the structure on the local environment, is needed in order to prevent the design of overly-conservative structures, a common problem in past hypersonic programs. The current work investigates these challenges from a structures perspective. To this end, the first part of this investigation looks at the modeling of the response of a rectangular panel to an external heating source (thermo-structural coupling) where the temperature effect on the structure is obtained from forward looking infrared (FLIR) measurements and the displacement via 3D-digital image correlation (DIC). The second part of the study uses data from a previous series of wind-tunnel experiments, performed to investigate the response of a compliant panel to the effects of high-speed flow, to train a pressure surrogate model. In this case, the panel aero-loading is obtained from fast-response pressure sensitive paint (PSP) measurements, both directly and from the pressure surrogate model. The result of this investigation is the use of full-field experimental measurements to update the structural model and train a computational efficient model of the loading environment. The use of reduced order models, informed by these full-field physical measurements, is a significant step toward the development of accurate simulation models of complex structures that are computationally tractable.

Homology modeling a fast tool for drug discovery: current perspectives.

PubMed

Vyas, V K; Ukawala, R D; Ghate, M; Chintha, C

2012-01-01

Major goal of structural biology involve formation of protein-ligand complexes; in which the protein molecules act energetically in the course of binding. Therefore, perceptive of protein-ligand interaction will be very important for structure based drug design. Lack of knowledge of 3D structures has hindered efforts to understand the binding specificities of ligands with protein. With increasing in modeling software and the growing number of known protein structures, homology modeling is rapidly becoming the method of choice for obtaining 3D coordinates of proteins. Homology modeling is a representation of the similarity of environmental residues at topologically corresponding positions in the reference proteins. In the absence of experimental data, model building on the basis of a known 3D structure of a homologous protein is at present the only reliable method to obtain the structural information. Knowledge of the 3D structures of proteins provides invaluable insights into the molecular basis of their functions. The recent advances in homology modeling, particularly in detecting and aligning sequences with template structures, distant homologues, modeling of loops and side chains as well as detecting errors in a model contributed to consistent prediction of protein structure, which was not possible even several years ago. This review focused on the features and a role of homology modeling in predicting protein structure and described current developments in this field with victorious applications at the different stages of the drug design and discovery.

Homology Modeling a Fast Tool for Drug Discovery: Current Perspectives

PubMed Central

Vyas, V. K.; Ukawala, R. D.; Ghate, M.; Chintha, C.

2012-01-01

Major goal of structural biology involve formation of protein-ligand complexes; in which the protein molecules act energetically in the course of binding. Therefore, perceptive of protein-ligand interaction will be very important for structure based drug design. Lack of knowledge of 3D structures has hindered efforts to understand the binding specificities of ligands with protein. With increasing in modeling software and the growing number of known protein structures, homology modeling is rapidly becoming the method of choice for obtaining 3D coordinates of proteins. Homology modeling is a representation of the similarity of environmental residues at topologically corresponding positions in the reference proteins. In the absence of experimental data, model building on the basis of a known 3D structure of a homologous protein is at present the only reliable method to obtain the structural information. Knowledge of the 3D structures of proteins provides invaluable insights into the molecular basis of their functions. The recent advances in homology modeling, particularly in detecting and aligning sequences with template structures, distant homologues, modeling of loops and side chains as well as detecting errors in a model contributed to consistent prediction of protein structure, which was not possible even several years ago. This review focused on the features and a role of homology modeling in predicting protein structure and described current developments in this field with victorious applications at the different stages of the drug design and discovery. PMID:23204616

Optimization of a Simple Ship Structural Model Using MAESTRO

DTIC Science & Technology

1999-03-01

Substructures MAESTRO Model Modules . . . MAESTRO Model Girders . . . . MAESTRO Model Tranverse Frames 9 10 11 12 13 Structural and Non-Structural...Weight Distribution 14 Longitudinal Load Distribution on the Model . 15 Tranverse Load Distribution on the Model . . . 16 Hogging Displacement of...Compression, Flange PYCP Panel Yield - Compression, Plate PSPBT Panel Serviceability- Plate Bending Tranverse PSPBL Panel Serviceability - Plate

A semi-supervised learning approach for RNA secondary structure prediction.

PubMed

Yonemoto, Haruka; Asai, Kiyoshi; Hamada, Michiaki

2015-08-01

RNA secondary structure prediction is a key technology in RNA bioinformatics. Most algorithms for RNA secondary structure prediction use probabilistic models, in which the model parameters are trained with reliable RNA secondary structures. Because of the difficulty of determining RNA secondary structures by experimental procedures, such as NMR or X-ray crystal structural analyses, there are still many RNA sequences that could be useful for training whose secondary structures have not been experimentally determined. In this paper, we introduce a novel semi-supervised learning approach for training parameters in a probabilistic model of RNA secondary structures in which we employ not only RNA sequences with annotated secondary structures but also ones with unknown secondary structures. Our model is based on a hybrid of generative (stochastic context-free grammars) and discriminative models (conditional random fields) that has been successfully applied to natural language processing. Computational experiments indicate that the accuracy of secondary structure prediction is improved by incorporating RNA sequences with unknown secondary structures into training. To our knowledge, this is the first study of a semi-supervised learning approach for RNA secondary structure prediction. This technique will be useful when the number of reliable structures is limited. Copyright © 2015 Elsevier Ltd. All rights reserved.

Predicting nucleic acid binding interfaces from structural models of proteins

PubMed Central

Dror, Iris; Shazman, Shula; Mukherjee, Srayanta; Zhang, Yang; Glaser, Fabian; Mandel-Gutfreund, Yael

2011-01-01

The function of DNA- and RNA-binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However the main pitfall of various structure-based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high-resolution three dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I-TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high-resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I-TASSER produces high-quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared to patches extracted from independent models. Overall, these results suggest that combining information from a collection of low-resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure. PMID:22086767

Modelling Spatial Dependence Structures Between Climate Variables by Combining Mixture Models with Copula Models

NASA Astrophysics Data System (ADS)

Khan, F.; Pilz, J.; Spöck, G.

2017-12-01

Spatio-temporal dependence structures play a pivotal role in understanding the meteorological characteristics of a basin or sub-basin. This further affects the hydrological conditions and consequently will provide misleading results if these structures are not taken into account properly. In this study we modeled the spatial dependence structure between climate variables including maximum, minimum temperature and precipitation in the Monsoon dominated region of Pakistan. For temperature, six, and for precipitation four meteorological stations have been considered. For modelling the dependence structure between temperature and precipitation at multiple sites, we utilized C-Vine, D-Vine and Student t-copula models. For temperature, multivariate mixture normal distributions and for precipitation gamma distributions have been used as marginals under the copula models. A comparison was made between C-Vine, D-Vine and Student t-copula by observational and simulated spatial dependence structure to choose an appropriate model for the climate data. The results show that all copula models performed well, however, there are subtle differences in their performances. The copula models captured the patterns of spatial dependence structures between climate variables at multiple meteorological sites, however, the t-copula showed poor performance in reproducing the dependence structure with respect to magnitude. It was observed that important statistics of observed data have been closely approximated except of maximum values for temperature and minimum values for minimum temperature. Probability density functions of simulated data closely follow the probability density functions of observational data for all variables. C and D-Vines are better tools when it comes to modelling the dependence between variables, however, Student t-copulas compete closely for precipitation. Keywords: Copula model, C-Vine, D-Vine, Spatial dependence structure, Monsoon dominated region of Pakistan, Mixture models, EM algorithm.

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

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.

An elastic-plastic contact model for line contact structures

NASA Astrophysics Data System (ADS)

Zhu, Haibin; Zhao, Yingtao; He, Zhifeng; Zhang, Ruinan; Ma, Shaopeng

2018-06-01

Although numerical simulation tools are now very powerful, the development of analytical models is very important for the prediction of the mechanical behaviour of line contact structures for deeply understanding contact problems and engineering applications. For the line contact structures widely used in the engineering field, few analytical models are available for predicting the mechanical behaviour when the structures deform plastically, as the classic Hertz's theory would be invalid. Thus, the present study proposed an elastic-plastic model for line contact structures based on the understanding of the yield mechanism. A mathematical expression describing the global relationship between load history and contact width evolution of line contact structures was obtained. The proposed model was verified through an actual line contact test and a corresponding numerical simulation. The results confirmed that this model can be used to accurately predict the elastic-plastic mechanical behaviour of a line contact structure.

The origin of consistent protein structure refinement from structural averaging.

PubMed

Park, Hahnbeom; DiMaio, Frank; Baker, David

2015-06-02

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

CAMD studies of coal structure and coal liquefaction

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

Faulon, J.L.; Carlson, G.A.

The macromolecular structure of coal is essential to understand the mechanisms occurring during coal liquefaction. Many attempts to model coal structure can be found in the literature. More specifically for high volatile bituminous coal, the subject of interest the most commonly quoted models are the models of Given, Wiser, Solomon, and Shinn. In past work, the authors`s have used computer-aided molecular design (CAMD) to develop three-dimensional representations for the above coal models. The three-dimensional structures were energy minimized using molecular mechanics and molecular dynamics. True density and micopore volume were evaluated for each model. With the exception of Given`s model,more » the computed density values were found to be in agreement with the corresponding experimental results. The above coal models were constructed by a trial and error technique consisting of a manual fitting of the-analytical data. It is obvious that for each model the amount of data is small compared to the actual complexity of coal, and for all of the models more than one structure can be built. Hence, the process by which one structure is chosen instead of another is not clear. In fact, all the authors agree that the structure they derived was only intended to represent an {open_quotes}average{close_quotes} coal model rather than a unique correct structure. The purpose of this program is further develop CAMD techniques to increase the understanding of coal structure and its relationship to coal liquefaction.« less

Engine Structures Modeling Software System (ESMOSS)

NASA Technical Reports Server (NTRS)

1991-01-01

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

Model verification of large structural systems. [space shuttle model response

NASA Technical Reports Server (NTRS)

Lee, L. T.; Hasselman, T. K.

1978-01-01

A computer program for the application of parameter identification on the structural dynamic models of space shuttle and other large models with hundreds of degrees of freedom is described. Finite element, dynamic, analytic, and modal models are used to represent the structural system. The interface with math models is such that output from any structural analysis program applied to any structural configuration can be used directly. Processed data from either sine-sweep tests or resonant dwell tests are directly usable. The program uses measured modal data to condition the prior analystic model so as to improve the frequency match between model and test. A Bayesian estimator generates an improved analytical model and a linear estimator is used in an iterative fashion on highly nonlinear equations. Mass and stiffness scaling parameters are generated for an improved finite element model, and the optimum set of parameters is obtained in one step.

Do gender and directness of trauma exposure moderate PTSD's latent structure?

PubMed

Frankfurt, Sheila B; Armour, Cherie; Contractor, Ateka A; Elhai, Jon D

2016-11-30

The PTSD diagnosis and latent structure were substantially revised in the transition from DSM-IV to DSM-5. However, three alternative models (i.e., anhedonia model, externalizing behavior model, and hybrid model) of PTSD fit the DSM-5 symptom criteria better than the DSM-5 factor model. Thus, the psychometric performance of the DSM-5 and alternative models' PTSD factor structure needs to be critically evaluated. The current study examined whether gender or trauma directness (i.e., direct or indirect trauma exposure) moderates the PTSD latent structure when using the DSM-5 or alternative models. Model performance was evaluated with measurement invariance testing procedures on a large undergraduate sample (n=455). Gender and trauma directness moderated the DSM-5 PTSD and externalizing behavior model and did not moderate the anhedonia and hybrid models' latent structure. Clinical implications and directions for future research are discussed. Published by Elsevier Ireland Ltd.

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

NASA Astrophysics Data System (ADS)

Siregar, R. I.

2018-02-01

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

New reflective symmetry design capability in the JPL-IDEAS Structure Optimization Program

NASA Technical Reports Server (NTRS)

Strain, D.; Levy, R.

1986-01-01

The JPL-IDEAS antenna structure analysis and design optimization computer program was modified to process half structure models of symmetric structures subjected to arbitrary external static loads, synthesize the performance, and optimize the design of the full structure. Significant savings in computation time and cost (more than 50%) were achieved compared to the cost of full model computer runs. The addition of the new reflective symmetry analysis design capabilities to the IDEAS program allows processing of structure models whose size would otherwise prevent automated design optimization. The new program produced synthesized full model iterative design results identical to those of actual full model program executions at substantially reduced cost, time, and computer storage.

TED analysis of the Si(113) surface structure

NASA Astrophysics Data System (ADS)

Suzuki, T.; Minoda, H.; Tanishiro, Y.; Yagi, K.

1999-09-01

We carried out a TED (transmission electron diffraction) analysis of the Si(113) surface structure. The TED patterns taken at room temperature showed reflections due to the 3×2 reconstructed structure. The TED pattern indicated that a glide plane parallel to the <332> direction suggested in some models is excluded. We calculated the R-factors (reliability factors) for six surface structure models proposed previously. All structure models with energy-optimized atomic positions have large R-factors. After revision of the atomic positions, the R-factors of all the structure models decreased below 0.3, and the revised version of Dabrowski's 3×2 model has the smallest R-factor of 0.17.

Modelling the social and structural determinants of tuberculosis: opportunities and challenges

PubMed Central

Boccia, D.; Dodd, P. J.; Lönnroth, K.; Dowdy, D. W.; Siroka, A.; Kimerling, M. E.; White, R. G.; Houben, R. M. G. J.

2017-01-01

INTRODUCTION: Despite the close link between tuberculosis (TB) and poverty, most mathematical models of TB have not addressed underlying social and structural determinants. OBJECTIVE: To review studies employing mathematical modelling to evaluate the epidemiological impact of the structural determinants of TB. METHODS: We systematically searched PubMed and personal libraries to identify eligible articles. We extracted data on the modelling techniques employed, research question, types of structural determinants modelled and setting. RESULTS: From 232 records identified, we included eight articles published between 2008 and 2015; six employed population-based dynamic TB transmission models and two non-dynamic analytic models. Seven studies focused on proximal TB determinants (four on nutritional status, one on wealth, one on indoor air pollution, and one examined overcrowding, socioeconomic and nutritional status), and one focused on macro-economic influences. CONCLUSIONS: Few modelling studies have attempted to evaluate structural determinants of TB, resulting in key knowledge gaps. Despite the challenges of modelling such a complex system, models must broaden their scope to remain useful for policy making. Given the intersectoral nature of the interrelations between structural determinants and TB outcomes, this work will require multidisciplinary collaborations. A useful starting point would be to focus on developing relatively simple models that can strengthen our knowledge regarding the potential effect of the structural determinants on TB outcomes. PMID:28826444

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

Epidemic spreading on complex networks with community structures

PubMed Central

Stegehuis, Clara; van der Hofstad, Remco; van Leeuwaarden, Johan S. H.

2016-01-01

Many real-world networks display a community structure. We study two random graph models that create a network with similar community structure as a given network. One model preserves the exact community structure of the original network, while the other model only preserves the set of communities and the vertex degrees. These models show that community structure is an important determinant of the behavior of percolation processes on networks, such as information diffusion or virus spreading: the community structure can both enforce as well as inhibit diffusion processes. Our models further show that it is the mesoscopic set of communities that matters. The exact internal structures of communities barely influence the behavior of percolation processes across networks. This insensitivity is likely due to the relative denseness of the communities. PMID:27440176

Finite Element Model Development For Aircraft Fuselage Structures

NASA Technical Reports Server (NTRS)

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

2000-01-01

The ability to extend the valid frequency range for finite element based structural dynamic predictions using detailed models of the structural components and attachment interfaces is examined for several stiffened aircraft fuselage structures. This extended dynamic prediction capability is needed for the integration of mid-frequency noise control technology. Beam, plate and solid element models of the stiffener components are evaluated. Attachment models between the stiffener and panel skin range from a line along the rivets of the physical structure to a constraint over the entire contact surface. The finite element models are validated using experimental modal analysis results.

Modeling repetitive, non‐globular proteins

PubMed Central

Basu, Koli; Campbell, Robert L.; Guo, Shuaiqi; Sun, Tianjun

2016-01-01

Abstract While ab initio modeling of protein structures is not routine, certain types of proteins are more straightforward to model than others. Proteins with short repetitive sequences typically exhibit repetitive structures. These repetitive sequences can be more amenable to modeling if some information is known about the predominant secondary structure or other key features of the protein sequence. We have successfully built models of a number of repetitive structures with novel folds using knowledge of the consensus sequence within the sequence repeat and an understanding of the likely secondary structures that these may adopt. Our methods for achieving this success are reviewed here. PMID:26914323

Integrated Modeling Activities for the James Webb Space Telescope: Optical Jitter Analysis

NASA Technical Reports Server (NTRS)

Hyde, T. Tupper; Ha, Kong Q.; Johnston, John D.; Howard, Joseph M.; Mosier, Gary E.

2004-01-01

This is a continuation of a series of papers on the integrated modeling activities for the James Webb Space Telescope(JWST). Starting with the linear optical model discussed in part one, and using the optical sensitivities developed in part two, we now assess the optical image motion and wavefront errors from the structural dynamics. This is often referred to as "jitter: analysis. The optical model is combined with the structural model and the control models to create a linear structural/optical/control model. The largest jitter is due to spacecraft reaction wheel assembly disturbances which are harmonic in nature and will excite spacecraft and telescope structural. The structural/optic response causes image quality degradation due to image motion (centroid error) as well as dynamic wavefront error. Jitter analysis results are used to predict imaging performance, improve the structural design, and evaluate the operational impact of the disturbance sources.

Optimum structural sizing of conventional cantilever and joined wing configurations using equivalent beam models

NASA Technical Reports Server (NTRS)

Hajela, P.; Chen, J. L.

1986-01-01

The present paper describes an approach for the optimum sizing of single and joined wing structures that is based on representing the built-up finite element model of the structure by an equivalent beam model. The low order beam model is computationally more efficient in an environment that requires repetitive analysis of several trial designs. The design procedure is implemented in a computer program that requires geometry and loading data typically available from an aerodynamic synthesis program, to create the finite element model of the lifting surface and an equivalent beam model. A fully stressed design procedure is used to obtain rapid estimates of the optimum structural weight for the beam model for a given geometry, and a qualitative description of the material distribution over the wing structure. The synthesis procedure is demonstrated for representative single wing and joined wing structures.

Fitting ARMA Time Series by Structural Equation Models.

ERIC Educational Resources Information Center

van Buuren, Stef

1997-01-01

This paper outlines how the stationary ARMA (p,q) model (G. Box and G. Jenkins, 1976) can be specified as a structural equation model. Maximum likelihood estimates for the parameters in the ARMA model can be obtained by software for fitting structural equation models. The method is applied to three problem types. (SLD)

Effects of model structure and catchment discretization on discharge simulation in a small forest catchment

NASA Astrophysics Data System (ADS)

Spieler, Diana; Schwarze, Robert; Schütze, Niels

2017-04-01

In the past a variety of different modeling approaches has been developed in catchment hydrology. Even though there is no argument on the relevant processes taking place, there is no unified theory on how best to represent them computationally. Thus a vast number of models has been developed, varying from lumped models to physically based models. Most of them have a more or less fixed model structure and follow the "one fits all" paradigm. However, a more flexible approach could improve model realism by designing catchment specific model structures based on data availability. This study focuses on applying the flexible hydrological modelling framework RAVEN (Craig et al., 2013), to systematically test several conceptual model structures on the 19 km2 Große Ohe Catchment in the Bavarian Forest (Germany). By combining RAVEN with the DREAM algorithm (Vrugt et al., 2009), the relationship between catchment characteristics, model structure, parameter uncertainty and data availability are analyzed. The model structure is progressively developed based on the available data of the well observed forested catchment area. In a second step, the impact of the catchment discretization is analyzed by testing different spatial resolutions of topographic input data.

Vibration attenuation of the NASA Langley evolutionary structure experiment using H(sub infinity) and structured singular value (micron) robust multivariable control techniques

NASA Technical Reports Server (NTRS)

Balas, Gary J.

1992-01-01

The use is studied of active control to attenuate structural vibrations of the NASA Langley Phase Zero Evolutionary Structure due to external disturbance excitations. H sub infinity and structured singular value (mu) based control techniques are used to analyze and synthesize control laws for the NASA Langley Controls Structures Interaction (CSI) Evolutionary Model (CEM). The CEM structure experiment provides an excellent test bed to address control design issues for large space structures. Specifically, control design for structures with numerous lightly damped, coupled flexible modes, collocated and noncollocated sensors and actuators and stringent performance specifications. The performance objectives are to attenuate the vibration of the structure due to external disturbances, and minimize the actuator control force. The control design problem formulation for the CEM Structure uses a mathematical model developed with finite element techniques. A reduced order state space model for the control design is formulated from the finite element model. It is noted that there are significant variations between the design model and the experimentally derived transfer function data.

Modeling of serial data acquisition structure for GEM detector system in Matlab

NASA Astrophysics Data System (ADS)

Kolasinski, Piotr; Pozniak, Krzysztof T.; Czarski, Tomasz; Chernyshova, Maryna; Kasprowicz, Grzegorz; Krawczyk, Rafal D.; Wojenski, Andrzej; Zabolotny, Wojciech; Byszuk, Adrian

2016-09-01

This article presents method of modeling in Matlab hardware architecture dedicated for FPGA created by languages like VHDL or Verilog. Purposes of creating such type of model with its advantages and disadvantages are described. Rules presented in this article were exploited to create model of Serial Data Acquisition algorithm used in X-ray GEM detector system. Result were compared to real working model implemented in VHDL. After testing of basic structure, other two structures were modeled to see influence parameters of the structure on its behavior.

Structural mode significance using INCA. [Interactive Controls Analysis computer program

NASA Technical Reports Server (NTRS)

Bauer, Frank H.; Downing, John P.; Thorpe, Christopher J.

1990-01-01

Structural finite element models are often too large to be used in the design and analysis of control systems. Model reduction techniques must be applied to reduce the structural model to manageable size. In the past, engineers either performed the model order reduction by hand or used distinct computer programs to retrieve the data, to perform the significance analysis and to reduce the order of the model. To expedite this process, the latest version of INCA has been expanded to include an interactive graphical structural mode significance and model order reduction capability.

Knowledge-based model building of proteins: concepts and examples.

PubMed Central

Bajorath, J.; Stenkamp, R.; Aruffo, A.

1993-01-01

We describe how to build protein models from structural templates. Methods to identify structural similarities between proteins in cases of significant, moderate to low, or virtually absent sequence similarity are discussed. The detection and evaluation of structural relationships is emphasized as a central aspect of protein modeling, distinct from the more technical aspects of model building. Computational techniques to generate and complement comparative protein models are also reviewed. Two examples, P-selectin and gp39, are presented to illustrate the derivation of protein model structures and their use in experimental studies. PMID:7505680

Oscillating water column structural model

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

Copeland, Guild; Bull, Diana L; Jepsen, Richard Alan

2014-09-01

An oscillating water column (OWC) wave energy converter is a structure with an opening to the ocean below the free surface, i.e. a structure with a moonpool. Two structural models for a non-axisymmetric terminator design OWC, the Backward Bent Duct Buoy (BBDB) are discussed in this report. The results of this structural model design study are intended to inform experiments and modeling underway in support of the U.S. Department of Energy (DOE) initiated Reference Model Project (RMP). A detailed design developed by Re Vision Consulting used stiffeners and girders to stabilize the structure against the hydrostatic loads experienced by amore » BBDB device. Additional support plates were added to this structure to account for loads arising from the mooring line attachment points. A simplified structure was designed in a modular fashion. This simplified design allows easy alterations to the buoyancy chambers and uncomplicated analysis of resulting changes in buoyancy.« less

Nonlinear Thermoelastic Model for SMAs and SMA Hybrid Composites

NASA Technical Reports Server (NTRS)

Turner, Travis L.

2004-01-01

A constitutive mathematical model has been developed that predicts the nonlinear thermomechanical behaviors of shape-memory-alloys (SMAs) and of shape-memory-alloy hybrid composite (SMAHC) structures, which are composite-material structures that contain embedded SMA actuators. SMAHC structures have been investigated for their potential utility in a variety of applications in which there are requirements for static or dynamic control of the shapes of structures, control of the thermoelastic responses of structures, or control of noise and vibrations. The present model overcomes deficiencies of prior, overly simplistic or qualitative models that have proven ineffective or intractable for engineering of SMAHC structures. The model is sophisticated enough to capture the essential features of the mechanics of SMAHC structures yet simple enough to accommodate input from fundamental engineering measurements and is in a form that is amenable to implementation in general-purpose structural analysis environments.

Alignment of the system's chief nursing officer: staff or direct line structure?

PubMed

Kerfoot, Karlene M; Luquire, Rosemary

2012-01-01

The role of the system chief nursing officer nationally and internationally has been traditionally structured as a staff model, a direct line model, or a hybrid that includes parts of each model. The choice of structure should be made after a thorough investigation of what outcomes the system wants this position to accomplish, developing the appropriate structure to achieve these outcomes, and then engaging a chief nursing officer with the skills indicated by the type of structure chosen. This article describes these 3 structures and the support infrastructure necessary for each model.

Rosetta Structure Prediction as a Tool for Solving Difficult Molecular Replacement Problems.

PubMed

DiMaio, Frank

2017-01-01

Molecular replacement (MR), a method for solving the crystallographic phase problem using phases derived from a model of the target structure, has proven extremely valuable, accounting for the vast majority of structures solved by X-ray crystallography. However, when the resolution of data is low, or the starting model is very dissimilar to the target protein, solving structures via molecular replacement may be very challenging. In recent years, protein structure prediction methodology has emerged as a powerful tool in model building and model refinement for difficult molecular replacement problems. This chapter describes some of the tools available in Rosetta for model building and model refinement specifically geared toward difficult molecular replacement cases.

A statistical learning approach to the modeling of chromatographic retention of oligonucleotides incorporating sequence and secondary structure data

PubMed Central

Sturm, Marc; Quinten, Sascha; Huber, Christian G.; Kohlbacher, Oliver

2007-01-01

We propose a new model for predicting the retention time of oligonucleotides. The model is based on ν support vector regression using features derived from base sequence and predicted secondary structure of oligonucleotides. Because of the secondary structure information, the model is applicable even at relatively low temperatures where the secondary structure is not suppressed by thermal denaturing. This makes the prediction of oligonucleotide retention time for arbitrary temperatures possible, provided that the target temperature lies within the temperature range of the training data. We describe different possibilities of feature calculation from base sequence and secondary structure, present the results and compare our model to existing models. PMID:17567619

A Stochastic Evolutionary Model for Protein Structure Alignment and Phylogeny

PubMed Central

Challis, Christopher J.; Schmidler, Scott C.

2012-01-01

We present a stochastic process model for the joint evolution of protein primary and tertiary structure, suitable for use in alignment and estimation of phylogeny. Indels arise from a classic Links model, and mutations follow a standard substitution matrix, whereas backbone atoms diffuse in three-dimensional space according to an Ornstein–Uhlenbeck process. The model allows for simultaneous estimation of evolutionary distances, indel rates, structural drift rates, and alignments, while fully accounting for uncertainty. The inclusion of structural information enables phylogenetic inference on time scales not previously attainable with sequence evolution models. The model also provides a tool for testing evolutionary hypotheses and improving our understanding of protein structural evolution. PMID:22723302

Modelling Size Structured Food Webs Using a Modified Niche Model with Two Predator Traits

PubMed Central

Klecka, Jan

2014-01-01

The structure of food webs is frequently described using phenomenological stochastic models. A prominent example, the niche model, was found to produce artificial food webs resembling real food webs according to a range of summary statistics. However, the size structure of food webs generated by the niche model and real food webs has not yet been rigorously compared. To fill this void, I use a body mass based version of the niche model and compare prey-predator body mass allometry and predator-prey body mass ratios predicted by the model to empirical data. The results show that the model predicts weaker size structure than observed in many real food webs. I introduce a modified version of the niche model which allows to control the strength of size-dependence of predator-prey links. In this model, optimal prey body mass depends allometrically on predator body mass and on a second trait, such as foraging mode. These empirically motivated extensions of the model allow to represent size structure of real food webs realistically and can be used to generate artificial food webs varying in several aspects of size structure in a controlled way. Hence, by explicitly including the role of species traits, this model provides new opportunities for simulating the consequences of size structure for food web dynamics and stability. PMID:25119999

Generation of 3-D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error

USGS Publications Warehouse

Christensen, Nikolaj K; Minsley, Burke J.; Christensen, Steen

2017-01-01

We present a new methodology to combine spatially dense high-resolution airborne electromagnetic (AEM) data and sparse borehole information to construct multiple plausible geological structures using a stochastic approach. The method developed allows for quantification of the performance of groundwater models built from different geological realizations of structure. Multiple structural realizations are generated using geostatistical Monte Carlo simulations that treat sparse borehole lithological observations as hard data and dense geophysically derived structural probabilities as soft data. Each structural model is used to define 3-D hydrostratigraphical zones of a groundwater model, and the hydraulic parameter values of the zones are estimated by using nonlinear regression to fit hydrological data (hydraulic head and river discharge measurements). Use of the methodology is demonstrated for a synthetic domain having structures of categorical deposits consisting of sand, silt, or clay. It is shown that using dense AEM data with the methodology can significantly improve the estimated accuracy of the sediment distribution as compared to when borehole data are used alone. It is also shown that this use of AEM data can improve the predictive capability of a calibrated groundwater model that uses the geological structures as zones. However, such structural models will always contain errors because even with dense AEM data it is not possible to perfectly resolve the structures of a groundwater system. It is shown that when using such erroneous structures in a groundwater model, they can lead to biased parameter estimates and biased model predictions, therefore impairing the model's predictive capability.

Generation of 3-D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error

NASA Astrophysics Data System (ADS)

Christensen, N. K.; Minsley, B. J.; Christensen, S.

2017-02-01

We present a new methodology to combine spatially dense high-resolution airborne electromagnetic (AEM) data and sparse borehole information to construct multiple plausible geological structures using a stochastic approach. The method developed allows for quantification of the performance of groundwater models built from different geological realizations of structure. Multiple structural realizations are generated using geostatistical Monte Carlo simulations that treat sparse borehole lithological observations as hard data and dense geophysically derived structural probabilities as soft data. Each structural model is used to define 3-D hydrostratigraphical zones of a groundwater model, and the hydraulic parameter values of the zones are estimated by using nonlinear regression to fit hydrological data (hydraulic head and river discharge measurements). Use of the methodology is demonstrated for a synthetic domain having structures of categorical deposits consisting of sand, silt, or clay. It is shown that using dense AEM data with the methodology can significantly improve the estimated accuracy of the sediment distribution as compared to when borehole data are used alone. It is also shown that this use of AEM data can improve the predictive capability of a calibrated groundwater model that uses the geological structures as zones. However, such structural models will always contain errors because even with dense AEM data it is not possible to perfectly resolve the structures of a groundwater system. It is shown that when using such erroneous structures in a groundwater model, they can lead to biased parameter estimates and biased model predictions, therefore impairing the model's predictive capability.

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.

Modeling complexes of modeled proteins.

PubMed

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

2017-03-01

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

Predicting nucleic acid binding interfaces from structural models of proteins.

PubMed

Dror, Iris; Shazman, Shula; Mukherjee, Srayanta; Zhang, Yang; Glaser, Fabian; Mandel-Gutfreund, Yael

2012-02-01

The function of DNA- and RNA-binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However, the main pitfall of various structure-based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high-resolution three-dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I-TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high-resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I-TASSER produces high-quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared with patches extracted from independent models. Overall, these results suggest that combining information from a collection of low-resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure. Copyright © 2011 Wiley Periodicals, Inc.

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.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

The impact of structural uncertainty on cost-effectiveness models for adjuvant endocrine breast cancer treatments: the need for disease-specific model standardization and improved guidance.

PubMed

Frederix, Gerardus W J; van Hasselt, Johan G C; Schellens, Jan H M; Hövels, Anke M; Raaijmakers, Jan A M; Huitema, Alwin D R; Severens, Johan L

2014-01-01

Structural uncertainty relates to differences in model structure and parameterization. For many published health economic analyses in oncology, substantial differences in model structure exist, leading to differences in analysis outcomes and potentially impacting decision-making processes. The objectives of this analysis were (1) to identify differences in model structure and parameterization for cost-effectiveness analyses (CEAs) comparing tamoxifen and anastrazole for adjuvant breast cancer (ABC) treatment; and (2) to quantify the impact of these differences on analysis outcome metrics. The analysis consisted of four steps: (1) review of the literature for identification of eligible CEAs; (2) definition and implementation of a base model structure, which included the core structural components for all identified CEAs; (3) definition and implementation of changes or additions in the base model structure or parameterization; and (4) quantification of the impact of changes in model structure or parameterizations on the analysis outcome metrics life-years gained (LYG), incremental costs (IC) and the incremental cost-effectiveness ratio (ICER). Eleven CEA analyses comparing anastrazole and tamoxifen as ABC treatment were identified. The base model consisted of the following health states: (1) on treatment; (2) off treatment; (3) local recurrence; (4) metastatic disease; (5) death due to breast cancer; and (6) death due to other causes. The base model estimates of anastrazole versus tamoxifen for the LYG, IC and ICER were 0.263 years, €3,647 and €13,868/LYG, respectively. In the published models that were evaluated, differences in model structure included the addition of different recurrence health states, and associated transition rates were identified. Differences in parameterization were related to the incidences of recurrence, local recurrence to metastatic disease, and metastatic disease to death. The separate impact of these model components on the LYG ranged from 0.207 to 0.356 years, while incremental costs ranged from €3,490 to €3,714 and ICERs ranged from €9,804/LYG to €17,966/LYG. When we re-analyzed the published CEAs in our framework by including their respective model properties, the LYG ranged from 0.207 to 0.383 years, IC ranged from €3,556 to €3,731 and ICERs ranged from €9,683/LYG to €17,570/LYG. Differences in model structure and parameterization lead to substantial differences in analysis outcome metrics. This analysis supports the need for more guidance regarding structural uncertainty and the use of standardized disease-specific models for health economic analyses of adjuvant endocrine breast cancer therapies. The developed approach in the current analysis could potentially serve as a template for further evaluations of structural uncertainty and development of disease-specific models.

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.

Fitting Data to Model: Structural Equation Modeling Diagnosis Using Two Scatter Plots

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Hayashi, Kentaro

2010-01-01

This article introduces two simple scatter plots for model diagnosis in structural equation modeling. One plot contrasts a residual-based M-distance of the structural model with the M-distance for the factor score. It contains information on outliers, good leverage observations, bad leverage observations, and normal cases. The other plot contrasts…

A Comparative Structural Equation Modeling Investigation of the Relationships among Teaching, Cognitive and Social Presence

ERIC Educational Resources Information Center

Kozan, Kadir

2016-01-01

The present study investigated the relationships among teaching, cognitive, and social presence through several structural equation models to see which model would better fit the data. To this end, the present study employed and compared several different structural equation models because different models could fit the data equally well. Among…

Mechanical properties of multifunctional structure with viscoelastic components based on FVE model

NASA Astrophysics Data System (ADS)

Hao, Dong; Zhang, Lin; Yu, Jing; Mao, Daiyong

2018-02-01

Based on the models of Lion and Kardelky (2004) and Hofer and Lion (2009), a finite viscoelastic (FVE) constitutive model, considering the predeformation-, frequency- and amplitude-dependent properties, has been proposed in our earlier paper [1]. FVE model is applied to investigating the dynamic characteristics of the multifunctional structure with the viscoelastic components. Combing FVE model with the finite element theory, the dynamic model of the multifunctional structure could be obtained. Additionally, the parametric identification and the experimental verification are also given via the frequency-sweep tests. The results show that the computational data agree well with the experimental data. FVE model has made a success of expressing the dynamic characteristics of the viscoelastic materials utilized in the multifunctional structure. The multifunctional structure technology has been verified by in-orbit experiments.

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

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

Preliminary shuttle structural dynamics modeling design study

NASA Technical Reports Server (NTRS)

1972-01-01

The design and development of a structural dynamics model of the space shuttle are discussed. The model provides for early study of structural dynamics problems, permits evaluation of the accuracy of the structural and hydroelastic analysis methods used on test vehicles, and provides for efficiently evaluating potential cost savings in structural dynamic testing techniques. The discussion is developed around the modes in which major input forces and responses occur and the significant structural details in these modes.

A Corner-Point-Grid-Based Voxelization Method for Complex Geological Structure Model with Folds

NASA Astrophysics Data System (ADS)

Chen, Qiyu; Mariethoz, Gregoire; Liu, Gang

2017-04-01

3D voxelization is the foundation of geological property modeling, and is also an effective approach to realize the 3D visualization of the heterogeneous attributes in geological structures. The corner-point grid is a representative data model among all voxel models, and is a structured grid type that is widely applied at present. When carrying out subdivision for complex geological structure model with folds, we should fully consider its structural morphology and bedding features to make the generated voxels keep its original morphology. And on the basis of which, they can depict the detailed bedding features and the spatial heterogeneity of the internal attributes. In order to solve the shortage of the existing technologies, this work puts forward a corner-point-grid-based voxelization method for complex geological structure model with folds. We have realized the fast conversion from the 3D geological structure model to the fine voxel model according to the rule of isocline in Ramsay's fold classification. In addition, the voxel model conforms to the spatial features of folds, pinch-out and other complex geological structures, and the voxels of the laminas inside a fold accords with the result of geological sedimentation and tectonic movement. This will provide a carrier and model foundation for the subsequent attribute assignment as well as the quantitative analysis and evaluation based on the spatial voxels. Ultimately, we use examples and the contrastive analysis between the examples and the Ramsay's description of isoclines to discuss the effectiveness and advantages of the method proposed in this work when dealing with the voxelization of 3D geologic structural model with folds based on corner-point grids.

Configurable product design considering the transition of multi-hierarchical models

NASA Astrophysics Data System (ADS)

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

2013-03-01

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

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.

Data Mining of Macromolecular Structures.

PubMed

van Beusekom, Bart; Perrakis, Anastassis; Joosten, Robbie P

2016-01-01

The use of macromolecular structures is widespread for a variety of applications, from teaching protein structure principles all the way to ligand optimization in drug development. Applying data mining techniques on these experimentally determined structures requires a highly uniform, standardized structural data source. The Protein Data Bank (PDB) has evolved over the years toward becoming the standard resource for macromolecular structures. However, the process selecting the data most suitable for specific applications is still very much based on personal preferences and understanding of the experimental techniques used to obtain these models. In this chapter, we will first explain the challenges with data standardization, annotation, and uniformity in the PDB entries determined by X-ray crystallography. We then discuss the specific effect that crystallographic data quality and model optimization methods have on structural models and how validation tools can be used to make informed choices. We also discuss specific advantages of using the PDB_REDO databank as a resource for structural data. Finally, we will provide guidelines on how to select the most suitable protein structure models for detailed analysis and how to select a set of structure models suitable for data mining.

Combining Thermal And Structural Analyses

NASA Technical Reports Server (NTRS)

Winegar, Steven R.

1990-01-01

Computer code makes programs compatible so stresses and deformations calculated. Paper describes computer code combining thermal analysis with structural analysis. Called SNIP (for SINDA-NASTRAN Interfacing Program), code provides interface between finite-difference thermal model of system and finite-element structural model when no node-to-element correlation between models. Eliminates much manual work in converting temperature results of SINDA (Systems Improved Numerical Differencing Analyzer) program into thermal loads for NASTRAN (NASA Structural Analysis) program. Used to analyze concentrating reflectors for solar generation of electric power. Large thermal and structural models needed to predict distortion of surface shapes, and SNIP saves considerable time and effort in combining models.

Hydrologic consistency as a basis for assessing complexity of monthly water balance models for the continental United States

NASA Astrophysics Data System (ADS)

Martinez, Guillermo F.; Gupta, Hoshin V.

2011-12-01

Methods to select parsimonious and hydrologically consistent model structures are useful for evaluating dominance of hydrologic processes and representativeness of data. While information criteria (appropriately constrained to obey underlying statistical assumptions) can provide a basis for evaluating appropriate model complexity, it is not sufficient to rely upon the principle of maximum likelihood (ML) alone. We suggest that one must also call upon a "principle of hydrologic consistency," meaning that selected ML structures and parameter estimates must be constrained (as well as possible) to reproduce desired hydrological characteristics of the processes under investigation. This argument is demonstrated in the context of evaluating the suitability of candidate model structures for lumped water balance modeling across the continental United States, using data from 307 snow-free catchments. The models are constrained to satisfy several tests of hydrologic consistency, a flow space transformation is used to ensure better consistency with underlying statistical assumptions, and information criteria are used to evaluate model complexity relative to the data. The results clearly demonstrate that the principle of consistency provides a sensible basis for guiding selection of model structures and indicate strong spatial persistence of certain model structures across the continental United States. Further work to untangle reasons for model structure predominance can help to relate conceptual model structures to physical characteristics of the catchments, facilitating the task of prediction in ungaged basins.

Modelling road accidents: An approach using structural time series

NASA Astrophysics Data System (ADS)

Junus, Noor Wahida Md; Ismail, Mohd Tahir

2014-09-01

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

Mixture models for protein structure ensembles.

PubMed

Hirsch, Michael; Habeck, Michael

2008-10-01

Protein structure ensembles provide important insight into the dynamics and function of a protein and contain information that is not captured with a single static structure. However, it is not clear a priori to what extent the variability within an ensemble is caused by internal structural changes. Additional variability results from overall translations and rotations of the molecule. And most experimental data do not provide information to relate the structures to a common reference frame. To report meaningful values of intrinsic dynamics, structural precision, conformational entropy, etc., it is therefore important to disentangle local from global conformational heterogeneity. We consider the task of disentangling local from global heterogeneity as an inference problem. We use probabilistic methods to infer from the protein ensemble missing information on reference frames and stable conformational sub-states. To this end, we model a protein ensemble as a mixture of Gaussian probability distributions of either entire conformations or structural segments. We learn these models from a protein ensemble using the expectation-maximization algorithm. Our first model can be used to find multiple conformers in a structure ensemble. The second model partitions the protein chain into locally stable structural segments or core elements and less structured regions typically found in loops. Both models are simple to implement and contain only a single free parameter: the number of conformers or structural segments. Our models can be used to analyse experimental ensembles, molecular dynamics trajectories and conformational change in proteins. The Python source code for protein ensemble analysis is available from the authors upon request.

Static Aeroelastic Analysis with an Inviscid Cartesian Method

NASA Technical Reports Server (NTRS)

Rodriguez, David L.; Aftosmis, Michael J.; Nemec, Marian; Smith, Stephen C.

2014-01-01

An embedded-boundary Cartesian-mesh flow solver is coupled with a three degree-offreedom structural model to perform static, aeroelastic analysis of complex aircraft geometries. The approach solves the complete system of aero-structural equations using a modular, loosely-coupled strategy which allows the lower-fidelity structural model to deform the highfidelity CFD model. The approach uses an open-source, 3-D discrete-geometry engine to deform a triangulated surface geometry according to the shape predicted by the structural model under the computed aerodynamic loads. The deformation scheme is capable of modeling large deflections and is applicable to the design of modern, very-flexible transport wings. The interface is modular so that aerodynamic or structural analysis methods can be easily swapped or enhanced. This extended abstract includes a brief description of the architecture, along with some preliminary validation of underlying assumptions and early results on a generic 3D transport model. The final paper will present more concrete cases and validation of the approach. Preliminary results demonstrate convergence of the complete aero-structural system and investigate the accuracy of the approximations used in the formulation of the structural model.

A 3D puzzle approach to building protein-DNA structures.

PubMed

Hinton, Deborah M

2017-03-15

Despite recent advances in structural analysis, it is still challenging to obtain a high-resolution structure for a complex of RNA polymerase, transcriptional factors, and DNA. However, using biochemical constraints, 3D printed models of available structures, and computer modeling, one can build biologically relevant models of such supramolecular complexes.

Using instability to reconfigure smart structures in a spring-mass model

NASA Astrophysics Data System (ADS)

Zhang, Jiaying; McInnes, Colin R.

2017-07-01

Multistable phenomenon have long been used in mechanism design. In this paper a subset of unstable configurations of a smart structure model will be used to develop energy-efficient schemes to reconfigure the structure. This new concept for reconfiguration uses heteroclinic connections to transition the structure between different unstable equal-energy states. In an ideal structure model zero net energy input is required for the reconfiguration, compared to transitions between stable equilibria across a potential barrier. A simple smart structure model is firstly used to identify sets of equal-energy unstable configurations using dynamical systems theory. Dissipation is then added to be more representative of a practical structure. A range of strategies are then used to reconfigure the smart structure using heteroclinic connections with different approaches to handle dissipation.

Two Aspects of the Simplex Model: Goodness of Fit to Linear Growth Curve Structures and the Analysis of Mean Trends.

ERIC Educational Resources Information Center

Mandys, Frantisek; Dolan, Conor V.; Molenaar, Peter C. M.

1994-01-01

Studied the conditions under which the quasi-Markov simplex model fits a linear growth curve covariance structure and determined when the model is rejected. Presents a quasi-Markov simplex model with structured means and gives an example. (SLD)

A model structure for identification of linear models of the UH-60 helicopter in hover and forward flight

DOT National Transportation Integrated Search

1995-08-01

A linear model structure applicable to identification of the UH-60 flight : dynamics in hover and forward flight without rotor-state data is developed. The : structure of the model is determined through consideration of the important : dynamic modes ...

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

Study on model design and dynamic similitude relations of vibro-acoustic experiment for elastic cavity

NASA Astrophysics Data System (ADS)

Shi, Ao; Lu, Bo; Yang, Dangguo; Wang, Xiansheng; Wu, Junqiang; Zhou, Fangqi

2018-05-01

Coupling between aero-acoustic noise and structural vibration under high-speed open cavity flow-induced oscillation may bring about severe random vibration of the structure, and even cause structure to fatigue destruction, which threatens the flight safety. Carrying out the research on vibro-acoustic experiments of scaled down model is an effective means to clarify the effects of high-intensity noise of cavity on structural vibration. Therefore, in allusion to the vibro-acoustic experiments of cavity in wind tunnel, taking typical elastic cavity as the research object, dimensional analysis and finite element method were adopted to establish the similitude relations of structural inherent characteristics and dynamics for distorted model, and verifying the proposed similitude relations by means of experiments and numerical simulation. Research shows that, according to the analysis of scale-down model, the established similitude relations can accurately simulate the structural dynamic characteristics of actual model, which provides theoretic guidance for structural design and vibro-acoustic experiments of scaled down elastic cavity model.

Network structure exploration in networks with node attributes

NASA Astrophysics Data System (ADS)

Chen, Yi; Wang, Xiaolong; Bu, Junzhao; Tang, Buzhou; Xiang, Xin

2016-05-01

Complex networks provide a powerful way to represent complex systems and have been widely studied during the past several years. One of the most important tasks of network analysis is to detect structures (also called structural regularities) embedded in networks by determining group number and group partition. Most of network structure exploration models only consider network links. However, in real world networks, nodes may have attributes that are useful for network structure exploration. In this paper, we propose a novel Bayesian nonparametric (BNP) model to explore structural regularities in networks with node attributes, called Bayesian nonparametric attribute (BNPA) model. This model does not only take full advantage of both links between nodes and node attributes for group partition via shared hidden variables, but also determine group number automatically via the Bayesian nonparametric theory. Experiments conducted on a number of real and synthetic networks show that our BNPA model is able to automatically explore structural regularities in networks with node attributes and is competitive with other state-of-the-art models.

Coarse-Grained Simulations of Membrane Insertion and Folding of Small Helical Proteins Using the CABS Model.

PubMed

Pulawski, Wojciech; Jamroz, Michal; Kolinski, Michal; Kolinski, Andrzej; Kmiecik, Sebastian

2016-11-28

The CABS coarse-grained model is a well-established tool for modeling globular proteins (predicting their structure, dynamics, and interactions). Here we introduce an extension of the CABS representation and force field (CABS-membrane) to the modeling of the effect of the biological membrane environment on the structure of membrane proteins. We validate the CABS-membrane model in folding simulations of 10 short helical membrane proteins not using any knowledge about their structure. The simulations start from random protein conformations placed outside the membrane environment and allow for full flexibility of the modeled proteins during their spontaneous insertion into the membrane. In the resulting trajectories, we have found models close to the experimental membrane structures. We also attempted to select the correctly folded models using simple filtering followed by structural clustering combined with reconstruction to the all-atom representation and all-atom scoring. The CABS-membrane model is a promising approach for further development toward modeling of large protein-membrane systems.

Inhibitor-based validation of a homology model of the active-site of tripeptidyl peptidase II.

PubMed

De Winter, Hans; Breslin, Henry; Miskowski, Tamara; Kavash, Robert; Somers, Marijke

2005-04-01

A homology model of the active site region of tripeptidyl peptidase II (TPP II) was constructed based on the crystal structures of four subtilisin-like templates. The resulting model was subsequently validated by judging expectations of the model versus observed activities for a broad set of prepared TPP II inhibitors. The structure-activity relationships observed for the prepared TPP II inhibitors correlated nicely with the structural details of the TPP II active site model, supporting the validity of this model and its usefulness for structure-based drug design and pharmacophore searching experiments.

Solving local structure around dopants in metal nanoparticles with ab initio modeling of X-ray absorption near edge structure

DOE PAGES

Timoshenko, J.; Shivhare, A.; Scott, R. W.; ...

2016-06-30

We adopted ab-initio X-ray Absorption Near Edge Structure (XANES) modelling for structural refinement of local environments around metal impurities in a large variety of materials. Our method enables both direct modelling, where the candidate structures are known, and the inverse modelling, where the unknown structural motifs are deciphered from the experimental spectra. We present also estimates of systematic errors, and their influence on the stability and accuracy of the obtained results. We illustrate our approach by following the evolution of local environment of palladium atoms in palladium-doped gold thiolate clusters upon chemical and thermal treatments.

Simulation Analysis and Performance Study of CoCrMo Porous Structure Manufactured by Selective Laser Melting

NASA Astrophysics Data System (ADS)

Guoqing, Zhang; Junxin, Li; Jin, Li; Chengguang, Zhang; Zefeng, Xiao

2018-04-01

To fabricate porous implants with improved biocompatibility and mechanical properties that are matched to their application using selective laser melting (SLM), flow within the mold and compressive properties and performance of the porous structures must be comprehensively studied. Parametric modeling was used to build 3D models of octahedron and hexahedron structures. Finite element analysis was used to evaluate the mold flow and compressive properties of the parametric porous structures. A DiMetal-100 SLM molding apparatus was used to manufacture the porous structures and the results evaluated by light microscopy. The results showed that parametric modeling can produce robust models. Square structures caused higher blood cell adhesion than cylindrical structures. "Vortex" flow in square structures resulted in chaotic distribution of blood elements, whereas they were mostly distributed around the connecting parts in the cylindrical structures. No significant difference in elastic moduli or compressive strength was observed in square and cylindrical porous structures of identical characteristics. Hexahedron, square and cylindrical porous structures had the same stress-strain properties. For octahedron porous structures, cylindrical structures had higher stress-strain properties. Using these modeling and molding results, an important basis for designing and the direct manufacture of fixed biological implants is provided.

Simulation Analysis and Performance Study of CoCrMo Porous Structure Manufactured by Selective Laser Melting

NASA Astrophysics Data System (ADS)

Guoqing, Zhang; Junxin, Li; Jin, Li; Chengguang, Zhang; Zefeng, Xiao

2018-05-01

To fabricate porous implants with improved biocompatibility and mechanical properties that are matched to their application using selective laser melting (SLM), flow within the mold and compressive properties and performance of the porous structures must be comprehensively studied. Parametric modeling was used to build 3D models of octahedron and hexahedron structures. Finite element analysis was used to evaluate the mold flow and compressive properties of the parametric porous structures. A DiMetal-100 SLM molding apparatus was used to manufacture the porous structures and the results evaluated by light microscopy. The results showed that parametric modeling can produce robust models. Square structures caused higher blood cell adhesion than cylindrical structures. "Vortex" flow in square structures resulted in chaotic distribution of blood elements, whereas they were mostly distributed around the connecting parts in the cylindrical structures. No significant difference in elastic moduli or compressive strength was observed in square and cylindrical porous structures of identical characteristics. Hexahedron, square and cylindrical porous structures had the same stress-strain properties. For octahedron porous structures, cylindrical structures had higher stress-strain properties. Using these modeling and molding results, an important basis for designing and the direct manufacture of fixed biological implants is provided.

A structural model of polyglutamine determined from a host-guest method combining experiments and landscape theory.

PubMed

Finke, John M; Cheung, Margaret S; Onuchic, José N

2004-09-01

Modeling the structure of natively disordered peptides has proved difficult due to the lack of structural information on these peptides. In this work, we use a novel application of the host-guest method, combining folding theory with experiments, to model the structure of natively disordered polyglutamine peptides. Initially, a minimalist molecular model (C(alpha)C(beta)) of CI2 is developed with a structurally based potential and captures many of the folding properties of CI2 determined from experiments. Next, polyglutamine "guest" inserts of increasing length are introduced into the CI2 "host" model and the polyglutamine is modeled to match the resultant change in CI2 thermodynamic stability between simulations and experiments. The polyglutamine model that best mimics the experimental changes in CI2 thermodynamic stability has 1), a beta-strand dihedral preference and 2), an attractive energy between polyglutamine atoms 0.75-times the attractive energy between the CI2 host Go-contacts. When free-energy differences in the CI2 host-guest system are correctly modeled at varying lengths of polyglutamine guest inserts, the kinetic folding rates and structural perturbation of these CI2 insert mutants are also correctly captured in simulations without any additional parameter adjustment. In agreement with experiments, the residues showing structural perturbation are located in the immediate vicinity of the loop insert. The simulated polyglutamine loop insert predominantly adopts extended random coil conformations, a structural model consistent with low resolution experimental methods. The agreement between simulation and experimental CI2 folding rates, CI2 structural perturbation, and polyglutamine insert structure show that this host-guest method can select a physically realistic model for inserted polyglutamine. If other amyloid peptides can be inserted into stable protein hosts and the stabilities of these host-guest mutants determined, this novel host-guest method may prove useful to determine structural preferences of these intractable but biologically relevant protein fragments.

Control Oriented Modeling and Validation of Aeroservoelastic Systems

NASA Technical Reports Server (NTRS)

Crowder, Marianne; deCallafon, Raymond (Principal Investigator)

2002-01-01

Lightweight aircraft design emphasizes the reduction of structural weight to maximize aircraft efficiency and agility at the cost of increasing the likelihood of structural dynamic instabilities. To ensure flight safety, extensive flight testing and active structural servo control strategies are required to explore and expand the boundary of the flight envelope. Aeroservoelastic (ASE) models can provide online flight monitoring of dynamic instabilities to reduce flight time testing and increase flight safety. The success of ASE models is determined by the ability to take into account varying flight conditions and the possibility to perform flight monitoring under the presence of active structural servo control strategies. In this continued study, these aspects are addressed by developing specific methodologies and algorithms for control relevant robust identification and model validation of aeroservoelastic structures. The closed-loop model robust identification and model validation are based on a fractional model approach where the model uncertainties are characterized in a closed-loop relevant way.

Iterative model building, structure refinement and density modification with the PHENIX AutoBuild wizard.

PubMed

Terwilliger, Thomas C; Grosse-Kunstleve, Ralf W; Afonine, Pavel V; Moriarty, Nigel W; Zwart, Peter H; Hung, Li Wei; Read, Randy J; Adams, Paul D

2008-01-01

The PHENIX AutoBuild wizard is a highly automated tool for iterative model building, structure refinement and density modification using RESOLVE model building, RESOLVE statistical density modification and phenix.refine structure refinement. Recent advances in the AutoBuild wizard and phenix.refine include automated detection and application of NCS from models as they are built, extensive model-completion algorithms and automated solvent-molecule picking. Model-completion algorithms in the AutoBuild wizard include loop building, crossovers between chains in different models of a structure and side-chain optimization. The AutoBuild wizard has been applied to a set of 48 structures at resolutions ranging from 1.1 to 3.2 A, resulting in a mean R factor of 0.24 and a mean free R factor of 0.29. The R factor of the final model is dependent on the quality of the starting electron density and is relatively independent of resolution.

Recent literature on structural modeling, identification, and analysis

NASA Technical Reports Server (NTRS)

Craig, Roy R., Jr.

1990-01-01

The literature on the mathematical modeling of large space structures is first reviewed, with attention given to continuum models, model order reduction, substructuring, and computational techniques. System identification and mode verification are then discussed with reference to the verification of mathematical models of large space structures. In connection with analysis, the paper surveys recent research on eigensolvers and dynamic response solvers for large-order finite-element-based models.

Integrating centralized and decentralized organization structures: an education and development model.

PubMed

Sheriff, R; Banks, A

2001-01-01

Organization change efforts have led to critically examining the structure of education and development departments within hospitals. This qualitative study evaluated an education and development model in an academic health sciences center. The model combines centralization and decentralization. The study results can be used by staff development educators and administrators when organization structure is questioned. This particular model maximizes the benefits and minimizes the limitations of centralized and decentralized structures.

Dam-Break Flooding and Structural Damage in a Residential Neighborhood: Performance of a coupled hydrodynamic-damage model

NASA Astrophysics Data System (ADS)

Sanders, B. F.; Gallegos, H. A.; Schubert, J. E.

2011-12-01

The Baldwin Hills dam-break flood and associated structural damage is investigated in this study. The flood caused high velocity flows exceeding 5 m/s which destroyed 41 wood-framed residential structures, 16 of which were completed washed out. Damage is predicted by coupling a calibrated hydrodynamic flood model based on the shallow-water equations to structural damage models. The hydrodynamic and damage models are two-way coupled so building failure is predicted upon exceedance of a hydraulic intensity parameter, which in turn triggers a localized reduction in flow resistance which affects flood intensity predictions. Several established damage models and damage correlations reported in the literature are tested to evaluate the predictive skill for two damage states defined by destruction (Level 2) and washout (Level 3). Results show that high-velocity structural damage can be predicted with a remarkable level of skill using established damage models, but only with two-way coupling of the hydrodynamic and damage models. In contrast, when structural failure predictions have no influence on flow predictions, there is a significant reduction in predictive skill. Force-based damage models compare well with a subset of the damage models which were devised for similar types of structures. Implications for emergency planning and preparedness as well as monetary damage estimation are discussed.

A new modal-based approach for modelling the bump foil structure in the simultaneous solution of foil-air bearing rotor dynamic problems

NASA Astrophysics Data System (ADS)

Bin Hassan, M. F.; Bonello, P.

2017-05-01

Recently-proposed techniques for the simultaneous solution of foil-air bearing (FAB) rotor dynamic problems have been limited to a simple bump foil model in which the individual bumps were modelled as independent spring-damper (ISD) subsystems. The present paper addresses this limitation by introducing a modal model of the bump foil structure into the simultaneous solution scheme. The dynamics of the corrugated bump foil structure are first studied using the finite element (FE) technique. This study is experimentally validated using a purpose-made corrugated foil structure. Based on the findings of this study, it is proposed that the dynamics of the full foil structure, including bump interaction and foil inertia, can be represented by a modal model comprising a limited number of modes. This full foil structure modal model (FFSMM) is then adapted into the rotordynamic FAB problem solution scheme, instead of the ISD model. Preliminary results using the FFSMM under static and unbalance excitation conditions are proven to be reliable by comparison against the corresponding ISD foil model results and by cross-correlating different methods for computing the deflection of the full foil structure. The rotor-bearing model is also validated against experimental and theoretical results in the literature.

Validation of clay modeling as a learning tool for the periventricular structures of the human brain.

PubMed

Akle, Veronica; Peña-Silva, Ricardo A; Valencia, Diego M; Rincón-Perez, Carlos W

2018-03-01

Visualizing anatomical structures and functional processes in three dimensions (3D) are important skills for medical students. However, contemplating 3D structures mentally and interpreting biomedical images can be challenging. This study examines the impact of a new pedagogical approach to teaching neuroanatomy, specifically how building a 3D-model from oil-based modeling clay affects learners' understanding of periventricular structures of the brain among undergraduate medical students in Colombia. Students were provided with an instructional video before building the models of the structures, and thereafter took a computer-based quiz. They then brought their clay models to class where they answered questions about the structures via interactive response cards. Their knowledge of periventricular structures was assessed with a paper-based quiz. Afterward, a focus group was conducted and a survey was distributed to understand students' perceptions of the activity, as well as the impact of the intervention on their understanding of anatomical structures in 3D. Quiz scores of students that constructed the models were significantly higher than those taught the material in a more traditional manner (P < 0.05). Moreover, the modeling activity reduced time spent studying the topic and increased understanding of spatial relationships between structures in the brain. The results demonstrated a significant difference between genders in their self-perception of their ability to contemplate and rotate structures mentally (P < 0.05). The study demonstrated that the construction of 3D clay models in combination with autonomous learning activities was a valuable and efficient learning tool in the anatomy course, and that additional models could be designed to promote deeper learning of other neuroanatomy topics. Anat Sci Educ 11: 137-145. © 2017 American Association of Anatomists. © 2017 American Association of Anatomists.

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.

Tree-Structured Infinite Sparse Factor Model

PubMed Central

Zhang, XianXing; Dunson, David B.; Carin, Lawrence

2013-01-01

A tree-structured multiplicative gamma process (TMGP) is developed, for inferring the depth of a tree-based factor-analysis model. This new model is coupled with the nested Chinese restaurant process, to nonparametrically infer the depth and width (structure) of the tree. In addition to developing the model, theoretical properties of the TMGP are addressed, and a novel MCMC sampler is developed. The structure of the inferred tree is used to learn relationships between high-dimensional data, and the model is also applied to compressive sensing and interpolation of incomplete images. PMID:25279389

Action detection by double hierarchical multi-structure space-time statistical matching model

NASA Astrophysics Data System (ADS)

Han, Jing; Zhu, Junwei; Cui, Yiyin; Bai, Lianfa; Yue, Jiang

2018-03-01

Aimed at the complex information in videos and low detection efficiency, an actions detection model based on neighboring Gaussian structure and 3D LARK features is put forward. We exploit a double hierarchical multi-structure space-time statistical matching model (DMSM) in temporal action localization. First, a neighboring Gaussian structure is presented to describe the multi-scale structural relationship. Then, a space-time statistical matching method is proposed to achieve two similarity matrices on both large and small scales, which combines double hierarchical structural constraints in model by both the neighboring Gaussian structure and the 3D LARK local structure. Finally, the double hierarchical similarity is fused and analyzed to detect actions. Besides, the multi-scale composite template extends the model application into multi-view. Experimental results of DMSM on the complex visual tracker benchmark data sets and THUMOS 2014 data sets show the promising performance. Compared with other state-of-the-art algorithm, DMSM achieves superior performances.

Action detection by double hierarchical multi-structure space–time statistical matching model

NASA Astrophysics Data System (ADS)

Han, Jing; Zhu, Junwei; Cui, Yiyin; Bai, Lianfa; Yue, Jiang

2018-06-01

Aimed at the complex information in videos and low detection efficiency, an actions detection model based on neighboring Gaussian structure and 3D LARK features is put forward. We exploit a double hierarchical multi-structure space-time statistical matching model (DMSM) in temporal action localization. First, a neighboring Gaussian structure is presented to describe the multi-scale structural relationship. Then, a space-time statistical matching method is proposed to achieve two similarity matrices on both large and small scales, which combines double hierarchical structural constraints in model by both the neighboring Gaussian structure and the 3D LARK local structure. Finally, the double hierarchical similarity is fused and analyzed to detect actions. Besides, the multi-scale composite template extends the model application into multi-view. Experimental results of DMSM on the complex visual tracker benchmark data sets and THUMOS 2014 data sets show the promising performance. Compared with other state-of-the-art algorithm, DMSM achieves superior performances.

PDEMOD: Software for control/structures optimization

NASA Technical Reports Server (NTRS)

Taylor, Lawrence W., Jr.; Zimmerman, David

1991-01-01

Because of the possibility of adverse interaction between the control system and the structural dynamics of large, flexible spacecraft, great care must be taken to ensure stability and system performance. Because of the high cost of insertion of mass into low earth orbit, it is prudent to optimize the roles of structure and control systems simultaneously. Because of the difficulty and the computational burden in modeling and analyzing the control structure system dynamics, the total problem is often split and treated iteratively. It would aid design if the control structure system dynamics could be represented in a single system of equations. With the use of the software PDEMOD (Partial Differential Equation Model), it is now possible to optimize structure and control systems simultaneously. The distributed parameter modeling approach enables embedding the control system dynamics into the same equations for the structural dynamics model. By doing this, the current difficulties involved in model order reduction are avoided. The NASA Mini-MAST truss is used an an example for studying integrated control structure design.

Membrane dish analysis: A summary of structural and optical analysis capabilities

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

Steele, C.R.; Balch, C.D.; Jorgensen, G.J.

Research at SERI within the Department of Energy's Solar Thermal Technology Program has focused on the development of membrane dish concentrators for space and terrestrial power applications. As potentially lightweight, inexpensive, high-performance structures, they are excellent candidates for space-deployable energy sources as well as cost-effective terrestrial energy concepts. A thorough engineering research treatment of these types of structures consists primarily of two parts: (1) structural mechanics of the membrane and ring support and (2) analysis and characterization of the concentrator optical performance. It is important to understand the effects of the membrane's structure and support system on the optical performancemore » of the concentrator. This requires an interface between appropriate structural and optical models. Until recently, such models and the required interface have not existed. This report documents research that has been conducted at SERI in this area. It is a compilation of several papers describing structural models of membrane dish structures and optical models used to predict dish concentrator optical and thermal performance. The structural models were developed under SERI subcontract by Dr. Steele and Dr. Balch of Stanford University. The optical model was developed in-house by SERI staff. In addition, the interface between the models is described. It allows easy and thorough characterization of membrane dish systems from the mechanics to the resulting optical performance. The models described herein have been and continue to be extremely useful to SERI, industry, and universities involved with the modeling and analysis of lightweight membrane concentrators for solar thermal applications.« less

Nonlinear structural joint model updating based on instantaneous characteristics of dynamic responses

NASA Astrophysics Data System (ADS)

Wang, Zuo-Cai; Xin, Yu; Ren, Wei-Xin

2016-08-01

This paper proposes a new nonlinear joint model updating method for shear type structures based on the instantaneous characteristics of the decomposed structural dynamic responses. To obtain an accurate representation of a nonlinear system's dynamics, the nonlinear joint model is described as the nonlinear spring element with bilinear stiffness. The instantaneous frequencies and amplitudes of the decomposed mono-component are first extracted by the analytical mode decomposition (AMD) method. Then, an objective function based on the residuals of the instantaneous frequencies and amplitudes between the experimental structure and the nonlinear model is created for the nonlinear joint model updating. The optimal values of the nonlinear joint model parameters are obtained by minimizing the objective function using the simulated annealing global optimization method. To validate the effectiveness of the proposed method, a single-story shear type structure subjected to earthquake and harmonic excitations is simulated as a numerical example. Then, a beam structure with multiple local nonlinear elements subjected to earthquake excitation is also simulated. The nonlinear beam structure is updated based on the global and local model using the proposed method. The results show that the proposed local nonlinear model updating method is more effective for structures with multiple local nonlinear elements. Finally, the proposed method is verified by the shake table test of a real high voltage switch structure. The accuracy of the proposed method is quantified both in numerical and experimental applications using the defined error indices. Both the numerical and experimental results have shown that the proposed method can effectively update the nonlinear joint model.

Structural insight into the binding interactions of modeled structure of Arabidopsis thaliana urease with urea: an in silico study.

PubMed

Yata, Vinod Kumar; Thapa, Arun; Mattaparthi, Venkata Satish Kumar

2015-01-01

Urease (EC 3.5.1.5., urea amidohydrolase) catalyzes the hydrolysis of urea to ammonia and carbon dioxide. Urease is present to a greater abundance in plants and plays significant role related to nitrogen recycling from urea. But little is known about the structure and function of the urease derived from the Arabidopsis thaliana, the model system of choice for research in plant biology. In this study, a three-dimensional structural model of A. thaliana urease was constructed using computer-aided molecular modeling technique. The characteristic structural features of the modeled structure were then studied using atomistic molecular dynamics simulation. It was observed that the modeled structure was stable and regions between residues index (50-80, 500-700) to be significantly flexible. From the docking studies, we detected the possible binding interactions of modeled urease with urea. Ala399, Ile675, Thr398, and Thr679 residues of A. thaliana urease were observed to be significantly involved in binding with the substrate urea. We also compared the docking studies of ureases from other sources such as Canavalia ensiformis, Helicobacter pylori, and Bacillus pasteurii. In addition, we carried out mutation analysis to find the highly mutable amino acid residues of modeled A. thaliana urease. In this particular study, we observed Met485, Tyr510, Ser786, Val426, and Lys765 to be highly mutable amino acids. These results are significant for the mutagenesis analysis. As a whole, this study expounds the salient structural features as well the binding interactions of the modeled structure of A. thaliana urease.

Fluid-Structure Interaction and Structural Analyses using a Comprehensive Mitral Valve Model with 3D Chordal Structure

PubMed Central

Toma, Milan; Einstein, Daniel R.; Bloodworth, Charles H.; Cochran, Richard P.; Yoganathan, Ajit P.; Kunzelman, Karyn S.

2016-01-01

Over the years, three-dimensional models of the mitral valve have generally been organized around a simplified anatomy. Leaflets have been typically modeled as membranes, tethered to discrete chordae typically modeled as one-dimensional, non-linear cables. Yet, recent, high-resolution medical images have revealed that there is no clear boundary between the chordae and the leaflets. In fact, the mitral valve has been revealed to be more of a webbed structure whose architecture is continuous with the chordae and their extensions into the leaflets. Such detailed images can serve as the basis of anatomically accurate, subject-specific models, wherein the entire valve is modeled with solid elements that more faithfully represent the chordae, the leaflets, and the transition between the two. These models have the potential to enhance our understanding of mitral valve mechanics, and to re-examine the role of the mitral valve chordae, which heretofore have been considered to be “invisible” to the fluid and to be of secondary importance to the leaflets. However, these new models also require a rethinking of modeling assumptions. In this study, we examine the conventional practice of loading the leaflets only and not the chordae in order to study the structural response of the mitral valve apparatus. Specifically, we demonstrate that fully resolved 3D models of the mitral valve require a fluid-structure interaction analysis to correctly load the valve even in the case of quasi-static mechanics. While a fluid-structure interaction mode is still more computationally expensive than a structural-only model, we also show that advances in GPU computing have made such models tractable. PMID:27342229

Fluid-structure interaction and structural analyses using a comprehensive mitral valve model with 3D chordal structure.

PubMed

Toma, Milan; Einstein, Daniel R; Bloodworth, Charles H; Cochran, Richard P; Yoganathan, Ajit P; Kunzelman, Karyn S

2017-04-01

Over the years, three-dimensional models of the mitral valve have generally been organized around a simplified anatomy. Leaflets have been typically modeled as membranes, tethered to discrete chordae typically modeled as one-dimensional, non-linear cables. Yet, recent, high-resolution medical images have revealed that there is no clear boundary between the chordae and the leaflets. In fact, the mitral valve has been revealed to be more of a webbed structure whose architecture is continuous with the chordae and their extensions into the leaflets. Such detailed images can serve as the basis of anatomically accurate, subject-specific models, wherein the entire valve is modeled with solid elements that more faithfully represent the chordae, the leaflets, and the transition between the two. These models have the potential to enhance our understanding of mitral valve mechanics and to re-examine the role of the mitral valve chordae, which heretofore have been considered to be 'invisible' to the fluid and to be of secondary importance to the leaflets. However, these new models also require a rethinking of modeling assumptions. In this study, we examine the conventional practice of loading the leaflets only and not the chordae in order to study the structural response of the mitral valve apparatus. Specifically, we demonstrate that fully resolved 3D models of the mitral valve require a fluid-structure interaction analysis to correctly load the valve even in the case of quasi-static mechanics. While a fluid-structure interaction mode is still more computationally expensive than a structural-only model, we also show that advances in GPU computing have made such models tractable. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A fragmentation and reassembly method for ab initio phasing.

PubMed

Shrestha, Rojan; Zhang, Kam Y J

2015-02-01

Ab initio phasing with de novo models has become a viable approach for structural solution from protein crystallographic diffraction data. This approach takes advantage of the known protein sequence information, predicts de novo models and uses them for structure determination by molecular replacement. However, even the current state-of-the-art de novo modelling method has a limit as to the accuracy of the model predicted, which is sometimes insufficient to be used as a template for successful molecular replacement. A fragment-assembly phasing method has been developed that starts from an ensemble of low-accuracy de novo models, disassembles them into fragments, places them independently in the crystallographic unit cell by molecular replacement and then reassembles them into a whole structure that can provide sufficient phase information to enable complete structure determination by automated model building. Tests on ten protein targets showed that the method could solve structures for eight of these targets, although the predicted de novo models cannot be used as templates for successful molecular replacement since the best model for each target is on average more than 4.0 Å away from the native structure. The method has extended the applicability of the ab initio phasing by de novo models approach. The method can be used to solve structures when the best de novo models are still of low accuracy.

Kinematics, structural mechanics, and design of origami structures with smooth folds

NASA Astrophysics Data System (ADS)

Peraza Hernandez, Edwin Alexander

Origami provides novel approaches to the fabrication, assembly, and functionality of engineering structures in various fields such as aerospace, robotics, etc. With the increase in complexity of the geometry and materials for origami structures that provide engineering utility, computational models and design methods for such structures have become essential. Currently available models and design methods for origami structures are generally limited to the idealization of the folds as creases of zeroth-order geometric continuity. Such an idealization is not proper for origami structures having non-negligible thickness or maximum curvature at the folds restricted by material limitations. Thus, for general structures, creased folds of merely zeroth-order geometric continuity are not appropriate representations of structural response and a new approach is needed. The first contribution of this dissertation is a model for the kinematics of origami structures having realistic folds of non-zero surface area and exhibiting higher-order geometric continuity, here termed smooth folds. The geometry of the smooth folds and the constraints on their associated kinematic variables are presented. A numerical implementation of the model allowing for kinematic simulation of structures having arbitrary fold patterns is also described. Examples illustrating the capability of the model to capture realistic structural folding response are provided. Subsequently, a method for solving the origami design problem of determining the geometry of a single planar sheet and its pattern of smooth folds that morphs into a given three-dimensional goal shape, discretized as a polygonal mesh, is presented. The design parameterization of the planar sheet and the constraints that allow for a valid pattern of smooth folds and approximation of the goal shape in a known folded configuration are presented. Various testing examples considering goal shapes of diverse geometries are provided. Afterwards, a model for the structural mechanics of origami continuum bodies with smooth folds is presented. Such a model entails the integration of the presented kinematic model and existing plate theories in order to obtain a structural representation for folds having non-zero thickness and comprised of arbitrary materials. The model is validated against finite element analysis. The last contribution addresses the design and analysis of active material-based self-folding structures that morph via simultaneous folding towards a given three-dimensional goal shape starting from a planar configuration. Implementation examples including shape memory alloy (SMA)-based self-folding structures are provided.

Protein Modelling: What Happened to the “Protein Structure Gap”?

PubMed Central

Schwede, Torsten

2013-01-01

Computational modeling and prediction of three-dimensional macromolecular structures and complexes from their sequence has been a long standing vision in structural biology as it holds the promise to bypass part of the laborious process of experimental structure solution. Over the last two decades, a paradigm shift has occurred: starting from a situation where the “structure knowledge gap” between the huge number of protein sequences and small number of known structures has hampered the widespread use of structure-based approaches in life science research, today some form of structural information – either experimental or computational – is available for the majority of amino acids encoded by common model organism genomes. Template based homology modeling techniques have matured to a point where they are now routinely used to complement experimental techniques. With the scientific focus of interest moving towards larger macromolecular complexes and dynamic networks of interactions, the integration of computational modeling methods with low-resolution experimental techniques allows studying large and complex molecular machines. Computational modeling and prediction techniques are still facing a number of challenges which hamper the more widespread use by the non-expert scientist. For example, it is often difficult to convey the underlying assumptions of a computational technique, as well as the expected accuracy and structural variability of a specific model. However, these aspects are crucial to understand the limitations of a model, and to decide which interpretations and conclusions can be supported. PMID:24010712

Empirical Analysis of Farm Credit Risk under the Structure Model

ERIC Educational Resources Information Center

Yan, Yan

2009-01-01

The study measures farm credit risk by using farm records collected by Farm Business Farm Management (FBFM) during the period 1995-2004. The study addresses the following questions: (1) whether farm's financial position is fully described by the structure model, (2) what are the determinants of farm capital structure under the structure model, (3)…

Modelling of nanoscale quantum tunnelling structures using algebraic topology method

NASA Astrophysics Data System (ADS)

Sankaran, Krishnaswamy; Sairam, B.

2018-05-01

We have modelled nanoscale quantum tunnelling structures using Algebraic Topology Method (ATM). The accuracy of ATM is compared to the analytical solution derived based on the wave nature of tunnelling electrons. ATM provides a versatile, fast, and simple model to simulate complex structures. We are currently expanding the method for modelling electrodynamic systems.

METSAT: Advanced Microwave Sounding Unit-A2 (AMSU-A2) structural mathematical model

NASA Technical Reports Server (NTRS)

Ely, Wayne

1995-01-01

This plan describes the Structural Mathematical Model of the METSAT AMSU-A2 instrument. The model is used to verify the structural adequacy of the AMSU-A2 instrument for the specified loading environments.

Model structures amplify uncertainty in predicted soil carbon responses to climate change.

PubMed

Shi, Zheng; Crowell, Sean; Luo, Yiqi; Moore, Berrien

2018-06-04

Large model uncertainty in projected future soil carbon (C) dynamics has been well documented. However, our understanding of the sources of this uncertainty is limited. Here we quantify the uncertainties arising from model parameters, structures and their interactions, and how those uncertainties propagate through different models to projections of future soil carbon stocks. Both the vertically resolved model and the microbial explicit model project much greater uncertainties to climate change than the conventional soil C model, with both positive and negative C-climate feedbacks, whereas the conventional model consistently predicts positive soil C-climate feedback. Our findings suggest that diverse model structures are necessary to increase confidence in soil C projection. However, the larger uncertainty in the complex models also suggests that we need to strike a balance between model complexity and the need to include diverse model structures in order to forecast soil C dynamics with high confidence and low uncertainty.

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

PubMed Central

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

2011-01-01

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

F-RAG: Generating Atomic Coordinates from RNA Graphs by Fragment Assembly.

PubMed

Jain, Swati; Schlick, Tamar

2017-11-24

Coarse-grained models represent attractive approaches to analyze and simulate ribonucleic acid (RNA) molecules, for example, for structure prediction and design, as they simplify the RNA structure to reduce the conformational search space. Our structure prediction protocol RAGTOP (RNA-As-Graphs Topology Prediction) represents RNA structures as tree graphs and samples graph topologies to produce candidate graphs. However, for a more detailed study and analysis, construction of atomic from coarse-grained models is required. Here we present our graph-based fragment assembly algorithm (F-RAG) to convert candidate three-dimensional (3D) tree graph models, produced by RAGTOP into atomic structures. We use our related RAG-3D utilities to partition graphs into subgraphs and search for structurally similar atomic fragments in a data set of RNA 3D structures. The fragments are edited and superimposed using common residues, full atomic models are scored using RAGTOP's knowledge-based potential, and geometries of top scoring models is optimized. To evaluate our models, we assess all-atom RMSDs and Interaction Network Fidelity (a measure of residue interactions) with respect to experimentally solved structures and compare our results to other fragment assembly programs. For a set of 50 RNA structures, we obtain atomic models with reasonable geometries and interactions, particularly good for RNAs containing junctions. Additional improvements to our protocol and databases are outlined. These results provide a good foundation for further work on RNA structure prediction and design applications. Copyright © 2017 Elsevier Ltd. All rights reserved.

Equivalent-Continuum Modeling of Nano-Structured Materials

NASA Technical Reports Server (NTRS)

Odegard, Gregory M.; Gates, Thomas S.; Nicholson, Lee M.; Wise, Kristopher E.

2001-01-01

A method has been developed for modeling structure-property relationships of nano-structured materials. This method serves as a link between computational chemistry and solid mechanics by substituting discrete molecular structures with an equivalent-continuum model. It has been shown that this substitution may be accomplished by equating the vibrational potential energy of a nano-structured material with the strain energy of representative truss and continuum models. As an important example with direct application to the development and characterization of single-walled carbon nanotubes, the model has been applied to determine the effective continuum geometry of a graphene sheet. A representative volume element of the equivalent-continuum model has been developed with an effective thickness. This effective thickness has been shown to be similar to, but slightly smaller than, the interatomic spacing of graphite.

Structure-based Markov random field model for representing evolutionary constraints on functional sites.

PubMed

Jeong, Chan-Seok; Kim, Dongsup

2016-02-24

Elucidating the cooperative mechanism of interconnected residues is an important component toward understanding the biological function of a protein. Coevolution analysis has been developed to model the coevolutionary information reflecting structural and functional constraints. Recently, several methods have been developed based on a probabilistic graphical model called the Markov random field (MRF), which have led to significant improvements for coevolution analysis; however, thus far, the performance of these models has mainly been assessed by focusing on the aspect of protein structure. In this study, we built an MRF model whose graphical topology is determined by the residue proximity in the protein structure, and derived a novel positional coevolution estimate utilizing the node weight of the MRF model. This structure-based MRF method was evaluated for three data sets, each of which annotates catalytic site, allosteric site, and comprehensively determined functional site information. We demonstrate that the structure-based MRF architecture can encode the evolutionary information associated with biological function. Furthermore, we show that the node weight can more accurately represent positional coevolution information compared to the edge weight. Lastly, we demonstrate that the structure-based MRF model can be reliably built with only a few aligned sequences in linear time. The results show that adoption of a structure-based architecture could be an acceptable approximation for coevolution modeling with efficient computation complexity.

Designing and evaluating the MULTICOM protein local and global model quality prediction methods in the CASP10 experiment

PubMed Central

2014-01-01

Background Protein model quality assessment is an essential component of generating and using protein structural models. During the Tenth Critical Assessment of Techniques for Protein Structure Prediction (CASP10), we developed and tested four automated methods (MULTICOM-REFINE, MULTICOM-CLUSTER, MULTICOM-NOVEL, and MULTICOM-CONSTRUCT) that predicted both local and global quality of protein structural models. Results MULTICOM-REFINE was a clustering approach that used the average pairwise structural similarity between models to measure the global quality and the average Euclidean distance between a model and several top ranked models to measure the local quality. MULTICOM-CLUSTER and MULTICOM-NOVEL were two new support vector machine-based methods of predicting both the local and global quality of a single protein model. MULTICOM-CONSTRUCT was a new weighted pairwise model comparison (clustering) method that used the weighted average similarity between models in a pool to measure the global model quality. Our experiments showed that the pairwise model assessment methods worked better when a large portion of models in the pool were of good quality, whereas single-model quality assessment methods performed better on some hard targets when only a small portion of models in the pool were of reasonable quality. Conclusions Since digging out a few good models from a large pool of low-quality models is a major challenge in protein structure prediction, single model quality assessment methods appear to be poised to make important contributions to protein structure modeling. The other interesting finding was that single-model quality assessment scores could be used to weight the models by the consensus pairwise model comparison method to improve its accuracy. PMID:24731387

Designing and evaluating the MULTICOM protein local and global model quality prediction methods in the CASP10 experiment.

PubMed

Cao, Renzhi; Wang, Zheng; Cheng, Jianlin

2014-04-15

Protein model quality assessment is an essential component of generating and using protein structural models. During the Tenth Critical Assessment of Techniques for Protein Structure Prediction (CASP10), we developed and tested four automated methods (MULTICOM-REFINE, MULTICOM-CLUSTER, MULTICOM-NOVEL, and MULTICOM-CONSTRUCT) that predicted both local and global quality of protein structural models. MULTICOM-REFINE was a clustering approach that used the average pairwise structural similarity between models to measure the global quality and the average Euclidean distance between a model and several top ranked models to measure the local quality. MULTICOM-CLUSTER and MULTICOM-NOVEL were two new support vector machine-based methods of predicting both the local and global quality of a single protein model. MULTICOM-CONSTRUCT was a new weighted pairwise model comparison (clustering) method that used the weighted average similarity between models in a pool to measure the global model quality. Our experiments showed that the pairwise model assessment methods worked better when a large portion of models in the pool were of good quality, whereas single-model quality assessment methods performed better on some hard targets when only a small portion of models in the pool were of reasonable quality. Since digging out a few good models from a large pool of low-quality models is a major challenge in protein structure prediction, single model quality assessment methods appear to be poised to make important contributions to protein structure modeling. The other interesting finding was that single-model quality assessment scores could be used to weight the models by the consensus pairwise model comparison method to improve its accuracy.

Development of vehicle model test-bending of a simple structural surfaces model for automotive vehicle sedan

NASA Astrophysics Data System (ADS)

Nor, M. K. Mohd; Noordin, A.; Ruzali, M. F. S.; Hussen, M. H.; Mustapa@Othman, N.

2017-04-01

Simple Structural Surfaces (SSS) method is offered as a means of organizing the process for rationalizing the basic vehicle body structure load paths. The application of this simplified approach is highly beneficial in the development of modern passenger car structure design. In Malaysia, the SSS topic has been widely adopted and seems compulsory in various automotive programs related to automotive vehicle structures in many higher education institutions. However, there is no real physical model of SSS available to gain considerable insight and understanding into the function of each major subassembly in the whole vehicle structures. Based on this motivation, a real physical SSS of sedan model and the corresponding model vehicle tests of bending is proposed in this work. The proposed approach is relatively easy to understand as compared to Finite Element Method (FEM). The results prove that the proposed vehicle model test is useful to physically demonstrate the importance of providing continuous load path using the necessary structural components within the vehicle structures. It is clearly observed that the global bending stiffness reduce significantly when more panels are removed from the complete SSS model. The analysis shows the front parcel shelf is an important subassembly to sustain bending load.

The effect of row structure on soil moisture retrieval accuracy from passive microwave data.

PubMed

Xingming, Zheng; Kai, Zhao; Yangyang, Li; Jianhua, Ren; Yanling, Ding

2014-01-01

Row structure causes the anisotropy of microwave brightness temperature (TB) of soil surface, and it also can affect soil moisture retrieval accuracy when its influence is ignored in the inversion model. To study the effect of typical row structure on the retrieved soil moisture and evaluate if there is a need to introduce this effect into the inversion model, two ground-based experiments were carried out in 2011. Based on the observed C-band TB, field soil and vegetation parameters, row structure rough surface assumption (Q p model and discrete model), including the effect of row structure, and flat rough surface assumption (Q p model), ignoring the effect of row structure, are used to model microwave TB of soil surface. Then, soil moisture can be retrieved, respectively, by minimizing the difference of the measured and modeled TB. The results show that soil moisture retrieval accuracy based on the row structure rough surface assumption is approximately 0.02 cm(3)/cm(3) better than the flat rough surface assumption for vegetated soil, as well as 0.015 cm(3)/cm(3) better for bare and wet soil. This result indicates that the effect of row structure cannot be ignored for accurately retrieving soil moisture of farmland surface when C-band is used.

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

PubMed Central

Kobayashi, Yukio

2016-01-01

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

A curved piezo-structure model: implications on active structural acoustic control.

PubMed

Henry, J K; Clark, R L

1999-09-01

Current research in Active Structural Acoustic Control (ASAC) relies heavily upon accurately capturing the application physics associated with the structure being controlled. The application of ASAC to aircraft interior noise requires a greater understanding of the dynamics of the curved panels which compose the skin of an aircraft fuselage. This paper presents a model of a simply supported curved panel with attached piezoelectric transducers. The model is validated by comparison to previous work. Further, experimental results for a simply supported curved panel test structure are presented in support of the model. The curvature is shown to affect substantially the dynamics of the panel, the integration of transducers, and the bandwidth required for structural acoustic control.

Massive integration of diverse protein quality assessment methods to improve template based modeling in CASP11

PubMed Central

Cao, Renzhi; Bhattacharya, Debswapna; Adhikari, Badri; Li, Jilong; Cheng, Jianlin

2015-01-01

Model evaluation and selection is an important step and a big challenge in template-based protein structure prediction. Individual model quality assessment methods designed for recognizing some specific properties of protein structures often fail to consistently select good models from a model pool because of their limitations. Therefore, combining multiple complimentary quality assessment methods is useful for improving model ranking and consequently tertiary structure prediction. Here, we report the performance and analysis of our human tertiary structure predictor (MULTICOM) based on the massive integration of 14 diverse complementary quality assessment methods that was successfully benchmarked in the 11th Critical Assessment of Techniques of Protein Structure prediction (CASP11). The predictions of MULTICOM for 39 template-based domains were rigorously assessed by six scoring metrics covering global topology of Cα trace, local all-atom fitness, side chain quality, and physical reasonableness of the model. The results show that the massive integration of complementary, diverse single-model and multi-model quality assessment methods can effectively leverage the strength of single-model methods in distinguishing quality variation among similar good models and the advantage of multi-model quality assessment methods of identifying reasonable average-quality models. The overall excellent performance of the MULTICOM predictor demonstrates that integrating a large number of model quality assessment methods in conjunction with model clustering is a useful approach to improve the accuracy, diversity, and consequently robustness of template-based protein structure prediction. PMID:26369671

Molecular models of NS3 protease variants of the Hepatitis C virus.

PubMed

da Silveira, Nelson J F; Arcuri, Helen A; Bonalumi, Carlos E; de Souza, Fátima P; Mello, Isabel M V G C; Rahal, Paula; Pinho, João R R; de Azevedo, Walter F

2005-01-21

Hepatitis C virus (HCV) currently infects approximately three percent of the world population. In view of the lack of vaccines against HCV, there is an urgent need for an efficient treatment of the disease by an effective antiviral drug. Rational drug design has not been the primary way for discovering major therapeutics. Nevertheless, there are reports of success in the development of inhibitor using a structure-based approach. One of the possible targets for drug development against HCV is the NS3 protease variants. Based on the three-dimensional structure of these variants we expect to identify new NS3 protease inhibitors. In order to speed up the modeling process all NS3 protease variant models were generated in a Beowulf cluster. The potential of the structural bioinformatics for development of new antiviral drugs is discussed. The atomic coordinates of crystallographic structure 1CU1 and 1DY9 were used as starting model for modeling of the NS3 protease variant structures. The NS3 protease variant structures are composed of six subdomains, which occur in sequence along the polypeptide chain. The protease domain exhibits the dual beta-barrel fold that is common among members of the chymotrypsin serine protease family. The helicase domain contains two structurally related beta-alpha-beta subdomains and a third subdomain of seven helices and three short beta strands. The latter domain is usually referred to as the helicase alpha-helical subdomain. The rmsd value of bond lengths and bond angles, the average G-factor and Verify 3D values are presented for NS3 protease variant structures. This project increases the certainty that homology modeling is an useful tool in structural biology and that it can be very valuable in annotating genome sequence information and contributing to structural and functional genomics from virus. The structural models will be used to guide future efforts in the structure-based drug design of a new generation of NS3 protease variants inhibitors. All models in the database are publicly accessible via our interactive website, providing us with large amount of structural models for use in protein-ligand docking analysis.

Multi-model approach to assess the impact of climate change on runoff

NASA Astrophysics Data System (ADS)

Dams, J.; Nossent, J.; Senbeta, T. B.; Willems, P.; Batelaan, O.

2015-10-01

The assessment of climate change impacts on hydrology is subject to uncertainties related to the climate change scenarios, stochastic uncertainties of the hydrological model and structural uncertainties of the hydrological model. This paper focuses on the contribution of structural uncertainty of hydrological models to the overall uncertainty of the climate change impact assessment. To quantify the structural uncertainty of hydrological models, four physically based hydrological models (SWAT, PRMS and a semi- and fully distributed version of the WetSpa model) are set up for a catchment in Belgium. Each model is calibrated using four different objective functions. Three climate change scenarios with a high, mean and low hydrological impact are statistically perturbed from a large ensemble of climate change scenarios and are used to force the hydrological models. This methodology allows assessing and comparing the uncertainty introduced by the climate change scenarios with the uncertainty introduced by the hydrological model structure. Results show that the hydrological model structure introduces a large uncertainty on both the average monthly discharge and the extreme peak and low flow predictions under the climate change scenarios. For the low impact climate change scenario, the uncertainty range of the mean monthly runoff is comparable to the range of these runoff values in the reference period. However, for the mean and high impact scenarios, this range is significantly larger. The uncertainty introduced by the climate change scenarios is larger than the uncertainty due to the hydrological model structure for the low and mean hydrological impact scenarios, but the reverse is true for the high impact climate change scenario. The mean and high impact scenarios project increasing peak discharges, while the low impact scenario projects increasing peak discharges only for peak events with return periods larger than 1.6 years. All models suggest for all scenarios a decrease of the lowest flows, except for the SWAT model with the mean hydrological impact climate change scenario. The results of this study indicate that besides the uncertainty introduced by the climate change scenarios also the hydrological model structure uncertainty should be taken into account in the assessment of climate change impacts on hydrology. To make it more straightforward and transparent to include model structural uncertainty in hydrological impact studies, there is a need for hydrological modelling tools that allow flexible structures and methods to validate model structures in their ability to assess impacts under unobserved future climatic conditions.

A General Interface Method for Aeroelastic Analysis of Aircraft

NASA Technical Reports Server (NTRS)

Tzong, T.; Chen, H. H.; Chang, K. C.; Wu, T.; Cebeci, T.

1996-01-01

The aeroelastic analysis of an aircraft requires an accurate and efficient procedure to couple aerodynamics and structures. The procedure needs an interface method to bridge the gap between the aerodynamic and structural models in order to transform loads and displacements. Such an interface method is described in this report. This interface method transforms loads computed by any aerodynamic code to a structural finite element (FE) model and converts the displacements from the FE model to the aerodynamic model. The approach is based on FE technology in which virtual work is employed to transform the aerodynamic pressures into FE nodal forces. The displacements at the FE nodes are then converted back to aerodynamic grid points on the aircraft surface through the reciprocal theorem in structural engineering. The method allows both high and crude fidelities of both models and does not require an intermediate modeling. In addition, the method performs the conversion of loads and displacements directly between individual aerodynamic grid point and its corresponding structural finite element and, hence, is very efficient for large aircraft models. This report also describes the application of this aero-structure interface method to a simple wing and an MD-90 wing. The results show that the aeroelastic effect is very important. For the simple wing, both linear and nonlinear approaches are used. In the linear approach, the deformation of the structural model is considered small, and the loads from the deformed aerodynamic model are applied to the original geometry of the structure. In the nonlinear approach, the geometry of the structure and its stiffness matrix are updated in every iteration and the increments of loads from the previous iteration are applied to the new structural geometry in order to compute the displacement increments. Additional studies to apply the aero-structure interaction procedure to more complicated geometry will be conducted in the second phase of the present contract.

Creating a Test Validated Structural Dynamic Finite Element Model of the Multi-Utility Technology Test Bed Aircraft

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi; Truong, Samson S.

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 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 X-56A. The ground vibration test validated structural dynamic finite element model of the X-56A is created in this study. The structural dynamic finite element model of the X-56A is improved using a model tuning tool. In this study, two different weight configurations of the X-56A have been improved in a single optimization run.

Gaia: automated quality assessment of protein structure models.

PubMed

Kota, Pradeep; Ding, Feng; Ramachandran, Srinivas; Dokholyan, Nikolay V

2011-08-15

Increasing use of structural modeling for understanding structure-function relationships in proteins has led to the need to ensure that the protein models being used are of acceptable quality. Quality of a given protein structure can be assessed by comparing various intrinsic structural properties of the protein to those observed in high-resolution protein structures. In this study, we present tools to compare a given structure to high-resolution crystal structures. We assess packing by calculating the total void volume, the percentage of unsatisfied hydrogen bonds, the number of steric clashes and the scaling of the accessible surface area. We assess covalent geometry by determining bond lengths, angles, dihedrals and rotamers. The statistical parameters for the above measures, obtained from high-resolution crystal structures enable us to provide a quality-score that points to specific areas where a given protein structural model needs improvement. We provide these tools that appraise protein structures in the form of a web server Gaia (http://chiron.dokhlab.org). Gaia evaluates the packing and covalent geometry of a given protein structure and provides quantitative comparison of the given structure to high-resolution crystal structures. dokh@unc.edu Supplementary data are available at Bioinformatics online.

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

CONFOLD2: improved contact-driven ab initio protein structure modeling.

PubMed

Adhikari, Badri; Cheng, Jianlin

2018-01-25

Contact-guided protein structure prediction methods are becoming more and more successful because of the latest advances in residue-residue contact prediction. To support contact-driven structure prediction, effective tools that can quickly build tertiary structural models of good quality from predicted contacts need to be developed. We develop an improved contact-driven protein modelling method, CONFOLD2, and study how it may be effectively used for ab initio protein structure prediction with predicted contacts as input. It builds models using various subsets of input contacts to explore the fold space under the guidance of a soft square energy function, and then clusters the models to obtain the top five models. CONFOLD2 obtains an average reconstruction accuracy of 0.57 TM-score for the 150 proteins in the PSICOV contact prediction dataset. When benchmarked on the CASP11 contacts predicted using CONSIP2 and CASP12 contacts predicted using Raptor-X, CONFOLD2 achieves a mean TM-score of 0.41 on both datasets. CONFOLD2 allows to quickly generate top five structural models for a protein sequence when its secondary structures and contacts predictions at hand. The source code of CONFOLD2 is publicly available at https://github.com/multicom-toolbox/CONFOLD2/ .

Investigating the Theoretical Structure of the DAS-II Core Battery at School Age Using Bayesian Structural Equation Modeling

ERIC Educational Resources Information Center

Dombrowski, Stefan C.; Golay, Philippe; McGill, Ryan J.; Canivez, Gary L.

2018-01-01

Bayesian structural equation modeling (BSEM) was used to investigate the latent structure of the Differential Ability Scales-Second Edition core battery using the standardization sample normative data for ages 7-17. Results revealed plausibility of a three-factor model, consistent with publisher theory, expressed as either a higher-order (HO) or a…

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

ERIC Educational Resources Information Center

Park, Jungkyu; Yu, Hsiu-Ting

2016-01-01

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

Nonlocal continuum-based modeling of mechanical characteristics of nanoscopic structures

NASA Astrophysics Data System (ADS)

Rafii-Tabar, Hashem; Ghavanloo, Esmaeal; Fazelzadeh, S. Ahmad

2016-06-01

Insight into the mechanical characteristics of nanoscopic structures is of fundamental interest and indeed poses a great challenge to the research communities around the world. These structures are ultra fine in size and consequently performing standard experiments to measure their various properties is an extremely difficult and expensive endeavor. Hence, to predict the mechanical characteristics of the nanoscopic structures, different theoretical models, numerical modeling techniques, and computer-based simulation methods have been developed. Among several proposed approaches, the nonlocal continuum-based modeling is of particular significance because the results obtained from this modeling for different nanoscopic structures are in very good agreement with the data obtained from both experimental and atomistic-based studies. A review of the essentials of this model together with its applications is presented here. Our paper is a self contained presentation of the nonlocal elasticity theory and contains the analysis of the recent works employing this model within the field of nanoscopic structures. In this review, the concepts from both the classical (local) and the nonlocal elasticity theories are presented and their applications to static and dynamic behavior of nanoscopic structures with various morphologies are discussed. We first introduce the various nanoscopic structures, both carbon-based and non carbon-based types, and then after a brief review of the definitions and concepts from classical elasticity theory, and the basic assumptions underlying size-dependent continuum theories, the mathematical details of the nonlocal elasticity theory are presented. A comprehensive discussion on the nonlocal version of the beam, the plate and the shell theories that are employed in modeling of the mechanical properties and behavior of nanoscopic structures is then provided. Next, an overview of the current literature discussing the application of the nonlocal models of nanoscopic carbon allotropes is presented. We then discuss the application of the models to the investigation of the properties of nanoscopic structures from different materials and with different types of morphologies. Furthermore, we also present recent developments in the application of the nonlocal models. Finally, conclusions and discussions regarding the potentiality of these models for future research are provided.

Quantitative structure-property relationship (correlation analysis) of phosphonic acid-based chelates in design of MRI contrast agent.

PubMed

Tiwari, Anjani K; Ojha, Himanshu; Kaul, Ankur; Dutta, Anupama; Srivastava, Pooja; Shukla, Gauri; Srivastava, Rakesh; Mishra, Anil K

2009-07-01

Nuclear magnetic resonance imaging is a very useful tool in modern medical diagnostics, especially when gadolinium (III)-based contrast agents are administered to the patient with the aim of increasing the image contrast between normal and diseased tissues. With the use of soft modelling techniques such as quantitative structure-activity relationship/quantitative structure-property relationship after a suitable description of their molecular structure, we have studied a series of phosphonic acid for designing new MRI contrast agent. Quantitative structure-property relationship studies with multiple linear regression analysis were applied to find correlation between different calculated molecular descriptors of the phosphonic acid-based chelating agent and their stability constants. The final quantitative structure-property relationship mathematical models were found as--quantitative structure-property relationship Model for phosphonic acid series (Model 1)--log K(ML) = {5.00243(+/-0.7102)}- MR {0.0263(+/-0.540)}n = 12 l r l = 0.942 s = 0.183 F = 99.165 quantitative structure-property relationship Model for phosphonic acid series (Model 2)--log K(ML) = {5.06280(+/-0.3418)}- MR {0.0252(+/- .198)}n = 12 l r l = 0.956 s = 0.186 F = 99.256.

Structural changes and out-of-sample prediction of realized range-based variance in the stock market

NASA Astrophysics Data System (ADS)

Gong, Xu; Lin, Boqiang

2018-03-01

This paper aims to examine the effects of structural changes on forecasting the realized range-based variance in the stock market. Considering structural changes in variance in the stock market, we develop the HAR-RRV-SC model on the basis of the HAR-RRV model. Subsequently, the HAR-RRV and HAR-RRV-SC models are used to forecast the realized range-based variance of S&P 500 Index. We find that there are many structural changes in variance in the U.S. stock market, and the period after the financial crisis contains more structural change points than the period before the financial crisis. The out-of-sample results show that the HAR-RRV-SC model significantly outperforms the HAR-BV model when they are employed to forecast the 1-day, 1-week, and 1-month realized range-based variances, which means that structural changes can improve out-of-sample prediction of realized range-based variance. The out-of-sample results remain robust across the alternative rolling fixed-window, the alternative threshold value in ICSS algorithm, and the alternative benchmark models. More importantly, we believe that considering structural changes can help improve the out-of-sample performances of most of other existing HAR-RRV-type models in addition to the models used in this paper.

Combining a popularity-productivity stochastic block model with a discriminative-content model for general structure detection.

PubMed

Chai, Bian-fang; Yu, Jian; Jia, Cai-Yan; Yang, Tian-bao; Jiang, Ya-wen

2013-07-01

Latent community discovery that combines links and contents of a text-associated network has drawn more attention with the advance of social media. Most of the previous studies aim at detecting densely connected communities and are not able to identify general structures, e.g., bipartite structure. Several variants based on the stochastic block model are more flexible for exploring general structures by introducing link probabilities between communities. However, these variants cannot identify the degree distributions of real networks due to a lack of modeling of the differences among nodes, and they are not suitable for discovering communities in text-associated networks because they ignore the contents of nodes. In this paper, we propose a popularity-productivity stochastic block (PPSB) model by introducing two random variables, popularity and productivity, to model the differences among nodes in receiving links and producing links, respectively. This model has the flexibility of existing stochastic block models in discovering general community structures and inherits the richness of previous models that also exploit popularity and productivity in modeling the real scale-free networks with power law degree distributions. To incorporate the contents in text-associated networks, we propose a combined model which combines the PPSB model with a discriminative model that models the community memberships of nodes by their contents. We then develop expectation-maximization (EM) algorithms to infer the parameters in the two models. Experiments on synthetic and real networks have demonstrated that the proposed models can yield better performances than previous models, especially on networks with general structures.

Combining a popularity-productivity stochastic block model with a discriminative-content model for general structure detection

NASA Astrophysics Data System (ADS)

Chai, Bian-fang; Yu, Jian; Jia, Cai-yan; Yang, Tian-bao; Jiang, Ya-wen

2013-07-01

Latent community discovery that combines links and contents of a text-associated network has drawn more attention with the advance of social media. Most of the previous studies aim at detecting densely connected communities and are not able to identify general structures, e.g., bipartite structure. Several variants based on the stochastic block model are more flexible for exploring general structures by introducing link probabilities between communities. However, these variants cannot identify the degree distributions of real networks due to a lack of modeling of the differences among nodes, and they are not suitable for discovering communities in text-associated networks because they ignore the contents of nodes. In this paper, we propose a popularity-productivity stochastic block (PPSB) model by introducing two random variables, popularity and productivity, to model the differences among nodes in receiving links and producing links, respectively. This model has the flexibility of existing stochastic block models in discovering general community structures and inherits the richness of previous models that also exploit popularity and productivity in modeling the real scale-free networks with power law degree distributions. To incorporate the contents in text-associated networks, we propose a combined model which combines the PPSB model with a discriminative model that models the community memberships of nodes by their contents. We then develop expectation-maximization (EM) algorithms to infer the parameters in the two models. Experiments on synthetic and real networks have demonstrated that the proposed models can yield better performances than previous models, especially on networks with general structures.

A Maximum Likelihood Approach for Multisample Nonlinear Structural Equation Models with Missing Continuous and Dichotomous Data

ERIC Educational Resources Information Center

Song, Xin-Yuan; Lee, Sik-Yum

2006-01-01

Structural equation models are widely appreciated in social-psychological research and other behavioral research to model relations between latent constructs and manifest variables and to control for measurement error. Most applications of SEMs are based on fully observed continuous normal data and models with a linear structural equation.…

77 FR 70941 - Special Conditions: Embraer S.A., Model EMB-550 Airplane; Interaction of Systems and Structures

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-28

... primary structure is metal with composite empennage and control surfaces. The Model EMB-550 airplane is...., Model EMB-550 Airplane; Interaction of Systems and Structures AGENCY: Federal Aviation Administration... conditions for the Embraer S.A. Model EMB-550 airplane. This airplane will have a novel or unusual design...

Applying Structural Equation Modeling in the Context of the Theory of Reasoned Action: Some Problems and Solutions.

ERIC Educational Resources Information Center

van den Putte, Bas; Hoogstraten, Johan

1997-01-01

Problems found in the application of structural equation modeling to the theory of reasoned action are explored, and an alternative model specification is proposed that improves the fit of the data while leaving intact the structural part of the model being tested. Problems and the proposed alternative are illustrated. (SLD)

Tactile Teaching: Exploring Protein Structure/Function Using Physical Models

ERIC Educational Resources Information Center

Herman, Tim; Morris, Jennifer; Colton, Shannon; Batiza, Ann; Patrick, Michael; Franzen, Margaret; Goodsell, David S.

2006-01-01

The technology now exists to construct physical models of proteins based on atomic coordinates of solved structures. We review here our recent experiences in using physical models to teach concepts of protein structure and function at both the high school and the undergraduate levels. At the high school level, physical models are used in a…

Direct and Indirect Effects of Parental Influence upon Adolescent Alcohol Use: A Structural Equation Modeling Analysis

ERIC Educational Resources Information Center

Kim, Young-Mi; Neff, James Alan

2010-01-01

A model incorporating the direct and indirect effects of parental monitoring on adolescent alcohol use was evaluated by applying structural equation modeling (SEM) techniques to data on 4,765 tenth-graders in the 2001 Monitoring the Future Study. Analyses indicated good fit of hypothesized measurement and structural models. Analyses supported both…

Analysis of Wave Propagation in Stratified Structures Using Circuit Analogues, with Application to Electromagnetic Absorbers

ERIC Educational Resources Information Center

Sjoberg, Daniel

2008-01-01

This paper presents an overview of how circuit models can be used for analysing wave propagation in stratified structures. Relatively complex structures can be analysed using models which are accessible to undergraduate students. Homogeneous slabs are modelled as transmission lines, and thin sheets between the slabs are modelled as lumped…

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…

Highly efficient model updating for structural condition assessment of large-scale bridges.

DOT National Transportation Integrated Search

2015-02-01

For eciently updating models of large-scale structures, the response surface (RS) method based on radial basis : functions (RBFs) is proposed to model the input-output relationship of structures. The key issues for applying : the proposed method a...

Integrated Modeling for the James Webb Space Telescope (JWST) Project: Structural Analysis Activities

NASA Technical Reports Server (NTRS)

Johnston, John; Mosier, Mark; Howard, Joe; Hyde, Tupper; Parrish, Keith; Ha, Kong; Liu, Frank; McGinnis, Mark

2004-01-01

This paper presents viewgraphs about structural analysis activities and integrated modeling for the James Webb Space Telescope (JWST). The topics include: 1) JWST Overview; 2) Observatory Structural Models; 3) Integrated Performance Analysis; and 4) Future Work and Challenges.

Experiment and simulation for CSI: What are the missing links?

NASA Technical Reports Server (NTRS)

Belvin, W. Keith; Park, K. C.

1989-01-01

Viewgraphs on experiment and simulation for control structure interaction (CSI) are presented. Topics covered include: control structure interaction; typical control/structure interaction system; CSI problem classification; actuator/sensor models; modeling uncertainty; noise models; real-time computations; and discrete versus continuous.

Epidemics in adaptive networks with community structure

NASA Astrophysics Data System (ADS)

Shaw, Leah; Tunc, Ilker

2010-03-01

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

Experimental and operational modal analysis of a laboratory scale model of a tripod support structure.

NASA Astrophysics Data System (ADS)

Luczak, M. M.; Mucchi, E.; Telega, J.

2016-09-01

The goal of the research is to develop a vibration-based procedure for the identification of structural failures in a laboratory scale model of a tripod supporting structure of an offshore wind turbine. In particular, this paper presents an experimental campaign on the scale model tested in two stages. Stage one encompassed the model tripod structure tested in air. The second stage was done in water. The tripod model structure allows to investigate the propagation of a circumferential representative crack of a cylindrical upper brace. The in-water test configuration included the tower with three bladed rotor. The response of the structure to the different waves loads were measured with accelerometers. Experimental and operational modal analysis was applied to identify the dynamic properties of the investigated scale model for intact and damaged state with different excitations and wave patterns. A comprehensive test matrix allows to assess the differences in estimated modal parameters due to damage or as potentially introduced by nonlinear structural response. The presented technique proves to be effective for detecting and assessing the presence of representative cracks.

Image-based models of cardiac structure in health and disease

PubMed Central

Vadakkumpadan, Fijoy; Arevalo, Hermenegild; Prassl, Anton J.; Chen, Junjie; Kickinger, Ferdinand; Kohl, Peter; Plank, Gernot; Trayanova, Natalia

2010-01-01

Computational approaches to investigating the electromechanics of healthy and diseased hearts are becoming essential for the comprehensive understanding of cardiac function. In this article, we first present a brief review of existing image-based computational models of cardiac structure. We then provide a detailed explanation of a processing pipeline which we have recently developed for constructing realistic computational models of the heart from high resolution structural and diffusion tensor (DT) magnetic resonance (MR) images acquired ex vivo. The presentation of the pipeline incorporates a review of the methodologies that can be used to reconstruct models of cardiac structure. In this pipeline, the structural image is segmented to reconstruct the ventricles, normal myocardium, and infarct. A finite element mesh is generated from the segmented structural image, and fiber orientations are assigned to the elements based on DTMR data. The methods were applied to construct seven different models of healthy and diseased hearts. These models contain millions of elements, with spatial resolutions in the order of hundreds of microns, providing unprecedented detail in the representation of cardiac structure for simulation studies. PMID:20582162

Identification of walking human model using agent-based modelling

NASA Astrophysics Data System (ADS)

Shahabpoor, Erfan; Pavic, Aleksandar; Racic, Vitomir

2018-03-01

The interaction of walking people with large vibrating structures, such as footbridges and floors, in the vertical direction is an important yet challenging phenomenon to describe mathematically. Several different models have been proposed in the literature to simulate interaction of stationary people with vibrating structures. However, the research on moving (walking) human models, explicitly identified for vibration serviceability assessment of civil structures, is still sparse. In this study, the results of a comprehensive set of FRF-based modal tests were used, in which, over a hundred test subjects walked in different group sizes and walking patterns on a test structure. An agent-based model was used to simulate discrete traffic-structure interactions. The occupied structure modal parameters found in tests were used to identify the parameters of the walking individual's single-degree-of-freedom (SDOF) mass-spring-damper model using 'reverse engineering' methodology. The analysis of the results suggested that the normal distribution with the average of μ = 2.85Hz and standard deviation of σ = 0.34Hz can describe human SDOF model natural frequency. Similarly, the normal distribution with μ = 0.295 and σ = 0.047 can describe the human model damping ratio. Compared to the previous studies, the agent-based modelling methodology proposed in this paper offers significant flexibility in simulating multi-pedestrian walking traffics, external forces and simulating different mechanisms of human-structure and human-environment interaction at the same time.

Bayesian Data-Model Fit Assessment for Structural Equation Modeling

ERIC Educational Resources Information Center

Levy, Roy

2011-01-01

Bayesian approaches to modeling are receiving an increasing amount of attention in the areas of model construction and estimation in factor analysis, structural equation modeling (SEM), and related latent variable models. However, model diagnostics and model criticism remain relatively understudied aspects of Bayesian SEM. This article describes…

Development of Novel Repellents Using Structure - Activity Modeling of Compounds in the USDA Archival Database

DTIC Science & Technology

2011-01-01

used in efforts to develop QSAR models. Measurement of Repellent Efficacy Screening for Repellency of Compounds with Unknown Toxicology In screening...CPT) were used to develop Quantitative Structure Activity Relationship ( QSAR ) models to predict repellency. Successful prediction of novel...acylpiperidine QSAR models employed 4 descriptors to describe the relationship between structure and repellent duration. The ANN model of the carboxamides did not

Local Crystal Structure of Antiferroelectric Bi2Mn4/3Ni2/3O6 in Commensurate and Incommensurate Phases Described by Pair Distribution Function (PDF) and Reverse Monte Carlo (RMC) Modeling.

PubMed

Szczecinski, Robert J; Chong, Samantha Y; Chater, Philip A; Hughes, Helen; Tucker, Matthew G; Claridge, John B; Rosseinsky, Matthew J

2014-04-08

The functional properties of materials can arise from local structural features that are not well determined or described by crystallographic methods based on long-range average structural models. The room temperature (RT) structure of the Bi perovskite Bi 2 Mn 4/3 Ni 2/3 O 6 has previously been modeled as a locally polar structure where polarization is suppressed by a long-range incommensurate antiferroelectric modulation. In this study we investigate the short-range local structure of Bi 2 Mn 4/3 Ni 2/3 O 6 , determined through reverse Monte Carlo (RMC) modeling of neutron total scattering data, and compare the results with the long-range incommensurate structure description. While the incommensurate structure has equivalent B site environments for Mn and Ni, the local structure displays a significantly Jahn-Teller distorted environment for Mn 3+ . The local structure displays the rock-salt-type Mn/Ni ordering of the related Bi 2 MnNiO 6 high pressure phase, as opposed to Mn/Ni clustering observed in the long-range average incommensurate model. RMC modeling reveals short-range ferroelectric correlations between Bi 3+ cations, giving rise to polar regions that are quantified for the first time as existing within a distance of approximately 12 Å. These local correlations persist in the commensurate high temperature (HT) phase, where the long-range average structure is nonpolar. The local structure thus provides information about cation ordering and B site structural flexibility that may stabilize Bi 3+ on the A site of the perovskite structure and reveals the extent of the local polar regions created by this cation.

Sequence-structure relationships in RNA loops: establishing the basis for loop homology modeling.

PubMed

Schudoma, Christian; May, Patrick; Nikiforova, Viktoria; Walther, Dirk

2010-01-01

The specific function of RNA molecules frequently resides in their seemingly unstructured loop regions. We performed a systematic analysis of RNA loops extracted from experimentally determined three-dimensional structures of RNA molecules. A comprehensive loop-structure data set was created and organized into distinct clusters based on structural and sequence similarity. We detected clear evidence of the hallmark of homology present in the sequence-structure relationships in loops. Loops differing by <25% in sequence identity fold into very similar structures. Thus, our results support the application of homology modeling for RNA loop model building. We established a threshold that may guide the sequence divergence-based selection of template structures for RNA loop homology modeling. Of all possible sequences that are, under the assumption of isosteric relationships, theoretically compatible with actual sequences observed in RNA structures, only a small fraction is contained in the Rfam database of RNA sequences and classes implying that the actual RNA loop space may consist of a limited number of unique loop structures and conserved sequences. The loop-structure data sets are made available via an online database, RLooM. RLooM also offers functionalities for the modeling of RNA loop structures in support of RNA engineering and design efforts.

ORION: a web server for protein fold recognition and structure prediction using evolutionary hybrid profiles

PubMed Central

Ghouzam, Yassine; Postic, Guillaume; Guerin, Pierre-Edouard; de Brevern, Alexandre G.; Gelly, Jean-Christophe

2016-01-01

Protein structure prediction based on comparative modeling is the most efficient way to produce structural models when it can be performed. ORION is a dedicated webserver based on a new strategy that performs this task. The identification by ORION of suitable templates is performed using an original profile-profile approach that combines sequence and structure evolution information. Structure evolution information is encoded into profiles using structural features, such as solvent accessibility and local conformation —with Protein Blocks—, which give an accurate description of the local protein structure. ORION has recently been improved, increasing by 5% the quality of its results. The ORION web server accepts a single protein sequence as input and searches homologous protein structures within minutes. Various databases such as PDB, SCOP and HOMSTRAD can be mined to find an appropriate structural template. For the modeling step, a protein 3D structure can be directly obtained from the selected template by MODELLER and displayed with global and local quality model estimation measures. The sequence and the predicted structure of 4 examples from the CAMEO server and a recent CASP11 target from the ‘Hard’ category (T0818-D1) are shown as pertinent examples. Our web server is accessible at http://www.dsimb.inserm.fr/ORION/. PMID:27319297

ORION: a web server for protein fold recognition and structure prediction using evolutionary hybrid profiles.

PubMed

Ghouzam, Yassine; Postic, Guillaume; Guerin, Pierre-Edouard; de Brevern, Alexandre G; Gelly, Jean-Christophe

2016-06-20

Protein structure prediction based on comparative modeling is the most efficient way to produce structural models when it can be performed. ORION is a dedicated webserver based on a new strategy that performs this task. The identification by ORION of suitable templates is performed using an original profile-profile approach that combines sequence and structure evolution information. Structure evolution information is encoded into profiles using structural features, such as solvent accessibility and local conformation -with Protein Blocks-, which give an accurate description of the local protein structure. ORION has recently been improved, increasing by 5% the quality of its results. The ORION web server accepts a single protein sequence as input and searches homologous protein structures within minutes. Various databases such as PDB, SCOP and HOMSTRAD can be mined to find an appropriate structural template. For the modeling step, a protein 3D structure can be directly obtained from the selected template by MODELLER and displayed with global and local quality model estimation measures. The sequence and the predicted structure of 4 examples from the CAMEO server and a recent CASP11 target from the 'Hard' category (T0818-D1) are shown as pertinent examples. Our web server is accessible at http://www.dsimb.inserm.fr/ORION/.

A validated approach for modeling collapse of steel structures

NASA Astrophysics Data System (ADS)

Saykin, Vitaliy Victorovich

A civil engineering structure is faced with many hazardous conditions such as blasts, earthquakes, hurricanes, tornadoes, floods, and fires during its lifetime. Even though structures are designed for credible events that can happen during a lifetime of the structure, extreme events do happen and cause catastrophic failures. Understanding the causes and effects of structural collapse is now at the core of critical areas of national need. One factor that makes studying structural collapse difficult is the lack of full-scale structural collapse experimental test results against which researchers could validate their proposed collapse modeling approaches. The goal of this work is the creation of an element deletion strategy based on fracture models for use in validated prediction of collapse of steel structures. The current work reviews the state-of-the-art of finite element deletion strategies for use in collapse modeling of structures. It is shown that current approaches to element deletion in collapse modeling do not take into account stress triaxiality in vulnerable areas of the structure, which is important for proper fracture and element deletion modeling. The report then reviews triaxiality and its role in fracture prediction. It is shown that fracture in ductile materials is a function of triaxiality. It is also shown that, depending on the triaxiality range, different fracture mechanisms are active and should be accounted for. An approach using semi-empirical fracture models as a function of triaxiality are employed. The models to determine fracture initiation, softening and subsequent finite element deletion are outlined. This procedure allows for stress-displacement softening at an integration point of a finite element in order to subsequently remove the element. This approach avoids abrupt changes in the stress that would create dynamic instabilities, thus making the results more reliable and accurate. The calibration and validation of these models are shown. The calibration is performed using a particle swarm optimization algorithm to establish accurate parameters when calibrated to circumferentially notched tensile coupons. It is shown that consistent, accurate predictions are attained using the chosen models. The variation of triaxiality in steel material during plastic hardening and softening is reported. The range of triaxiality in steel structures undergoing collapse is investigated in detail and the accuracy of the chosen finite element deletion approaches is discussed. This is done through validation of different structural components and structural frames undergoing severe fracture and collapse.

Recursive formulae and performance comparisons for first mode dynamics of periodic structures

NASA Astrophysics Data System (ADS)

Hobeck, Jared D.; Inman, Daniel J.

2017-05-01

Periodic structures are growing in popularity especially in the energy harvesting and metastructures communities. Common types of these unique structures are referred to in the literature as zigzag, orthogonal spiral, fan-folded, and longitudinal zigzag structures. Many of these studies on periodic structures have two competing goals in common: (a) minimizing natural frequency, and (b) minimizing mass or volume. These goals suggest that no single design is best for all applications; therefore, there is a need for design optimization and comparison tools which first require efficient easy-to-implement models. All available structural dynamics models for these types of structures do provide exact analytical solutions; however, they are complex requiring tedious implementation and providing more information than necessary for practical applications making them computationally inefficient. This paper presents experimentally validated recursive models that are able to very accurately and efficiently predict the dynamics of the four most common types of periodic structures. The proposed modeling technique employs a combination of static deflection formulae and Rayleigh’s Quotient to estimate the first mode shape and natural frequency of periodic structures having any number of beams. Also included in this paper are the results of an extensive experimental validation study which show excellent agreement between model prediction and measurement. Lastly, the proposed models are used to evaluate the performance of each type of structure. Results of this performance evaluation reveal key advantages and disadvantages associated with each type of structure.

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

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

PubMed

Mehta, Paras D

2018-01-01

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

Iterative model building, structure refinement and density modification with the PHENIX AutoBuild wizard

PubMed Central

Terwilliger, Thomas C.; Grosse-Kunstleve, Ralf W.; Afonine, Pavel V.; Moriarty, Nigel W.; Zwart, Peter H.; Hung, Li-Wei; Read, Randy J.; Adams, Paul D.

2008-01-01

The PHENIX AutoBuild wizard is a highly automated tool for iterative model building, structure refinement and density modification using RESOLVE model building, RESOLVE statistical density modification and phenix.refine structure refinement. Recent advances in the AutoBuild wizard and phenix.refine include automated detection and application of NCS from models as they are built, extensive model-completion algorithms and automated solvent-molecule picking. Model-completion algorithms in the AutoBuild wizard include loop building, crossovers between chains in different models of a structure and side-chain optimization. The AutoBuild wizard has been applied to a set of 48 structures at resolutions ranging from 1.1 to 3.2 Å, resulting in a mean R factor of 0.24 and a mean free R factor of 0.29. The R factor of the final model is dependent on the quality of the starting electron density and is relatively independent of resolution. PMID:18094468

Modeling of protein binary complexes using structural mass spectrometry data

PubMed Central

Kamal, J.K. Amisha; Chance, Mark R.

2008-01-01

In this article, we describe a general approach to modeling the structure of binary protein complexes using structural mass spectrometry data combined with molecular docking. In the first step, hydroxyl radical mediated oxidative protein footprinting is used to identify residues that experience conformational reorganization due to binding or participate in the binding interface. In the second step, a three-dimensional atomic structure of the complex is derived by computational modeling. Homology modeling approaches are used to define the structures of the individual proteins if footprinting detects significant conformational reorganization as a function of complex formation. A three-dimensional model of the complex is constructed from these binary partners using the ClusPro program, which is composed of docking, energy filtering, and clustering steps. Footprinting data are used to incorporate constraints—positive and/or negative—in the docking step and are also used to decide the type of energy filter—electrostatics or desolvation—in the successive energy-filtering step. By using this approach, we examine the structure of a number of binary complexes of monomeric actin and compare the results to crystallographic data. Based on docking alone, a number of competing models with widely varying structures are observed, one of which is likely to agree with crystallographic data. When the docking steps are guided by footprinting data, accurate models emerge as top scoring. We demonstrate this method with the actin/gelsolin segment-1 complex. We also provide a structural model for the actin/cofilin complex using this approach which does not have a crystal or NMR structure. PMID:18042684

High-Fidelity Modeling for Health Monitoring in Honeycomb Sandwich Structures

NASA Technical Reports Server (NTRS)

Luchinsky, Dimitry G.; Hafiychuk, Vasyl; Smelyanskiy, Vadim; Tyson, Richard W.; Walker, James L.; Miller, Jimmy L.

2011-01-01

High-Fidelity Model of the sandwich composite structure with real geometry is reported. The model includes two composite facesheets, honeycomb core, piezoelectric actuator/sensors, adhesive layers, and the impactor. The novel feature of the model is that it includes modeling of the impact and wave propagation in the structure before and after the impact. Results of modeling of the wave propagation, impact, and damage detection in sandwich honeycomb plates using piezoelectric actuator/sensor scheme are reported. The results of the simulations are compared with the experimental results. It is shown that the model is suitable for analysis of the physics of failure due to the impact and for testing structural health monitoring schemes based on guided wave propagation.

MMM: A toolbox for integrative structure modeling.

PubMed

Jeschke, Gunnar

2018-01-01

Structural characterization of proteins and their complexes may require integration of restraints from various experimental techniques. MMM (Multiscale Modeling of Macromolecules) is a Matlab-based open-source modeling toolbox for this purpose with a particular emphasis on distance distribution restraints obtained from electron paramagnetic resonance experiments on spin-labelled proteins and nucleic acids and their combination with atomistic structures of domains or whole protomers, small-angle scattering data, secondary structure information, homology information, and elastic network models. MMM does not only integrate various types of restraints, but also various existing modeling tools by providing a common graphical user interface to them. The types of restraints that can support such modeling and the available model types are illustrated by recent application examples. © 2017 The Protein Society.

Optimal estimation of large structure model errors. [in Space Shuttle controller design

NASA Technical Reports Server (NTRS)

Rodriguez, G.

1979-01-01

In-flight estimation of large structure model errors is usually required as a means of detecting inevitable deficiencies in large structure controller/estimator models. The present paper deals with a least-squares formulation which seeks to minimize a quadratic functional of the model errors. The properties of these error estimates are analyzed. It is shown that an arbitrary model error can be decomposed as the sum of two components that are orthogonal in a suitably defined function space. Relations between true and estimated errors are defined. The estimates are found to be approximations that retain many of the significant dynamics of the true model errors. Current efforts are directed toward application of the analytical results to a reference large structure model.

A range of complex probabilistic models for RNA secondary structure prediction that includes the nearest-neighbor model and more.

PubMed

Rivas, Elena; Lang, Raymond; Eddy, Sean R

2012-02-01

The standard approach for single-sequence RNA secondary structure prediction uses a nearest-neighbor thermodynamic model with several thousand experimentally determined energy parameters. An attractive alternative is to use statistical approaches with parameters estimated from growing databases of structural RNAs. Good results have been reported for discriminative statistical methods using complex nearest-neighbor models, including CONTRAfold, Simfold, and ContextFold. Little work has been reported on generative probabilistic models (stochastic context-free grammars [SCFGs]) of comparable complexity, although probabilistic models are generally easier to train and to use. To explore a range of probabilistic models of increasing complexity, and to directly compare probabilistic, thermodynamic, and discriminative approaches, we created TORNADO, a computational tool that can parse a wide spectrum of RNA grammar architectures (including the standard nearest-neighbor model and more) using a generalized super-grammar that can be parameterized with probabilities, energies, or arbitrary scores. By using TORNADO, we find that probabilistic nearest-neighbor models perform comparably to (but not significantly better than) discriminative methods. We find that complex statistical models are prone to overfitting RNA structure and that evaluations should use structurally nonhomologous training and test data sets. Overfitting has affected at least one published method (ContextFold). The most important barrier to improving statistical approaches for RNA secondary structure prediction is the lack of diversity of well-curated single-sequence RNA secondary structures in current RNA databases.

A range of complex probabilistic models for RNA secondary structure prediction that includes the nearest-neighbor model and more

PubMed Central

Rivas, Elena; Lang, Raymond; Eddy, Sean R.

2012-01-01

The standard approach for single-sequence RNA secondary structure prediction uses a nearest-neighbor thermodynamic model with several thousand experimentally determined energy parameters. An attractive alternative is to use statistical approaches with parameters estimated from growing databases of structural RNAs. Good results have been reported for discriminative statistical methods using complex nearest-neighbor models, including CONTRAfold, Simfold, and ContextFold. Little work has been reported on generative probabilistic models (stochastic context-free grammars [SCFGs]) of comparable complexity, although probabilistic models are generally easier to train and to use. To explore a range of probabilistic models of increasing complexity, and to directly compare probabilistic, thermodynamic, and discriminative approaches, we created TORNADO, a computational tool that can parse a wide spectrum of RNA grammar architectures (including the standard nearest-neighbor model and more) using a generalized super-grammar that can be parameterized with probabilities, energies, or arbitrary scores. By using TORNADO, we find that probabilistic nearest-neighbor models perform comparably to (but not significantly better than) discriminative methods. We find that complex statistical models are prone to overfitting RNA structure and that evaluations should use structurally nonhomologous training and test data sets. Overfitting has affected at least one published method (ContextFold). The most important barrier to improving statistical approaches for RNA secondary structure prediction is the lack of diversity of well-curated single-sequence RNA secondary structures in current RNA databases. PMID:22194308

Bayesian nonlinear structural FE model and seismic input identification for damage assessment of civil structures

NASA Astrophysics Data System (ADS)

Astroza, Rodrigo; Ebrahimian, Hamed; Li, Yong; Conte, Joel P.

2017-09-01

A methodology is proposed to update mechanics-based nonlinear finite element (FE) models of civil structures subjected to unknown input excitation. The approach allows to jointly estimate unknown time-invariant model parameters of a nonlinear FE model of the structure and the unknown time histories of input excitations using spatially-sparse output response measurements recorded during an earthquake event. The unscented Kalman filter, which circumvents the computation of FE response sensitivities with respect to the unknown model parameters and unknown input excitations by using a deterministic sampling approach, is employed as the estimation tool. The use of measurement data obtained from arrays of heterogeneous sensors, including accelerometers, displacement sensors, and strain gauges is investigated. Based on the estimated FE model parameters and input excitations, the updated nonlinear FE model can be interrogated to detect, localize, classify, and assess damage in the structure. Numerically simulated response data of a three-dimensional 4-story 2-by-1 bay steel frame structure with six unknown model parameters subjected to unknown bi-directional horizontal seismic excitation, and a three-dimensional 5-story 2-by-1 bay reinforced concrete frame structure with nine unknown model parameters subjected to unknown bi-directional horizontal seismic excitation are used to illustrate and validate the proposed methodology. The results of the validation studies show the excellent performance and robustness of the proposed algorithm to jointly estimate unknown FE model parameters and unknown input excitations.

Integral equation model for warm and hot dense mixtures.

PubMed

Starrett, C E; Saumon, D; Daligault, J; Hamel, S

2014-09-01

In a previous work [C. E. Starrett and D. Saumon, Phys. Rev. E 87, 013104 (2013)] a model for the calculation of electronic and ionic structures of warm and hot dense matter was described and validated. In that model the electronic structure of one atom in a plasma is determined using a density-functional-theory-based average-atom (AA) model and the ionic structure is determined by coupling the AA model to integral equations governing the fluid structure. That model was for plasmas with one nuclear species only. Here we extend it to treat plasmas with many nuclear species, i.e., mixtures, and apply it to a carbon-hydrogen mixture relevant to inertial confinement fusion experiments. Comparison of the predicted electronic and ionic structures with orbital-free and Kohn-Sham molecular dynamics simulations reveals excellent agreement wherever chemical bonding is not significant.

ProTSAV: A protein tertiary structure analysis and validation server.

PubMed

Singh, Ankita; Kaushik, Rahul; Mishra, Avinash; Shanker, Asheesh; Jayaram, B

2016-01-01

Quality assessment of predicted model structures of proteins is as important as the protein tertiary structure prediction. A highly efficient quality assessment of predicted model structures directs further research on function. Here we present a new server ProTSAV, capable of evaluating predicted model structures based on some popular online servers and standalone tools. ProTSAV furnishes the user with a single quality score in case of individual protein structure along with a graphical representation and ranking in case of multiple protein structure assessment. The server is validated on ~64,446 protein structures including experimental structures from RCSB and predicted model structures for CASP targets and from public decoy sets. ProTSAV succeeds in predicting quality of protein structures with a specificity of 100% and a sensitivity of 98% on experimentally solved structures and achieves a specificity of 88%and a sensitivity of 91% on predicted protein structures of CASP11 targets under 2Å.The server overcomes the limitations of any single server/method and is seen to be robust in helping in quality assessment. ProTSAV is freely available at http://www.scfbio-iitd.res.in/software/proteomics/protsav.jsp. Copyright © 2015 Elsevier B.V. All rights reserved.

Template-based structure modeling of protein-protein interactions

PubMed Central

Szilagyi, Andras; Zhang, Yang

2014-01-01

The structure of protein-protein complexes can be constructed by using the known structure of other protein complexes as a template. The complex structure templates are generally detected either by homology-based sequence alignments or, given the structure of monomer components, by structure-based comparisons. Critical improvements have been made in recent years by utilizing interface recognition and by recombining monomer and complex template libraries. Encouraging progress has also been witnessed in genome-wide applications of template-based modeling, with modeling accuracy comparable to high-throughput experimental data. Nevertheless, bottlenecks exist due to the incompleteness of the proteinprotein complex structure library and the lack of methods for distant homologous template identification and full-length complex structure refinement. PMID:24721449

A Paper Model of DNA Structure and Replication.

ERIC Educational Resources Information Center

Sigismondi, Linda A.

1989-01-01

A paper model which is designed to give students a hands-on experience during lecture and blackboard instruction on DNA structure is provided. A list of materials, paper patterns, and procedures for using the models to teach DNA structure and replication are given. (CW)

Residual Structures in Latent Growth Curve Modeling

ERIC Educational Resources Information Center

Grimm, Kevin J.; Widaman, Keith F.

2010-01-01

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

Formulation of human-structure interaction system models for vertical vibration

NASA Astrophysics Data System (ADS)

Caprani, Colin C.; Ahmadi, Ehsan

2016-09-01

In this paper, human-structure interaction system models for vibration in the vertical direction are considered. This work assembles various moving load models from the literature and proposes extension of the single pedestrian to a crowd of pedestrians for the FE formulation for crowd-structure interaction systems. The walking pedestrian vertical force is represented as a general time-dependent force, and the pedestrian is in turn modelled as moving force, moving mass, and moving spring-mass-damper. The arbitrary beam structure is modelled using either a formulation in modal coordinates or finite elements. In each case, the human-structure interaction (HSI) system is first formulated for a single walking pedestrian and then extended to consider a crowd of pedestrians. Finally, example applications for single pedestrian and crowd loading scenarios are examined. It is shown how the models can be used to quantify the interaction between the crowd and bridge structure. This work should find use for the evaluation of existing and new footbridges.

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

Bayesian Network Webserver: a comprehensive tool for biological network modeling.

PubMed

Ziebarth, Jesse D; Bhattacharya, Anindya; Cui, Yan

2013-11-01

The Bayesian Network Webserver (BNW) is a platform for comprehensive network modeling of systems genetics and other biological datasets. It allows users to quickly and seamlessly upload a dataset, learn the structure of the network model that best explains the data and use the model to understand relationships between network variables. Many datasets, including those used to create genetic network models, contain both discrete (e.g. genotype) and continuous (e.g. gene expression traits) variables, and BNW allows for modeling hybrid datasets. Users of BNW can incorporate prior knowledge during structure learning through an easy-to-use structural constraint interface. After structure learning, users are immediately presented with an interactive network model, which can be used to make testable hypotheses about network relationships. BNW, including a downloadable structure learning package, is available at http://compbio.uthsc.edu/BNW. (The BNW interface for adding structural constraints uses HTML5 features that are not supported by current version of Internet Explorer. We suggest using other browsers (e.g. Google Chrome or Mozilla Firefox) when accessing BNW). ycui2@uthsc.edu. Supplementary data are available at Bioinformatics online.

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

NASA Technical Reports Server (NTRS)

1977-01-01

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

Efficient finite element modelling for the investigation of the dynamic behaviour of a structure with bolted joints

NASA Astrophysics Data System (ADS)

Omar, R.; Rani, M. N. Abdul; Yunus, M. A.; Mirza, W. I. I. Wan Iskandar; Zin, M. S. Mohd

2018-04-01

A simple structure with bolted joints consists of the structural components, bolts and nuts. There are several methods to model the structures with bolted joints, however there is no reliable, efficient and economic modelling methods that can accurately predict its dynamics behaviour. Explained in this paper is an investigation that was conducted to obtain an appropriate modelling method for bolted joints. This was carried out by evaluating four different finite element (FE) models of the assembled plates and bolts namely the solid plates-bolts model, plates without bolt model, hybrid plates-bolts model and simplified plates-bolts model. FE modal analysis was conducted for all four initial FE models of the bolted joints. Results of the FE modal analysis were compared with the experimental modal analysis (EMA) results. EMA was performed to extract the natural frequencies and mode shapes of the test physical structure with bolted joints. Evaluation was made by comparing the number of nodes, number of elements, elapsed computer processing unit (CPU) time, and the total percentage of errors of each initial FE model when compared with EMA result. The evaluation showed that the simplified plates-bolts model could most accurately predict the dynamic behaviour of the structure with bolted joints. This study proved that the reliable, efficient and economic modelling of bolted joints, mainly the representation of the bolting, has played a crucial element in ensuring the accuracy of the dynamic behaviour prediction.

Quantitative Understanding of SHAPE Mechanism from RNA Structure and Dynamics Analysis.

PubMed

Hurst, Travis; Xu, Xiaojun; Zhao, Peinan; Chen, Shi-Jie

2018-05-10

The selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) method probes RNA local structural and dynamic information at single nucleotide resolution. To gain quantitative insights into the relationship between nucleotide flexibility, RNA 3D structure, and SHAPE reactivity, we develop a 3D Structure-SHAPE Relationship model (3DSSR) to rebuild SHAPE profiles from 3D structures. The model starts from RNA structures and combines nucleotide interaction strength and conformational propensity, ligand (SHAPE reagent) accessibility, and base-pairing pattern through a composite function to quantify the correlation between SHAPE reactivity and nucleotide conformational stability. The 3DSSR model shows the relationship between SHAPE reactivity and RNA structure and energetics. Comparisons between the 3DSSR-predicted SHAPE profile and the experimental SHAPE data show correlation, suggesting that the extracted analytical function may have captured the key factors that determine the SHAPE reactivity profile. Furthermore, the theory offers an effective method to sieve RNA 3D models and exclude models that are incompatible with experimental SHAPE data.

Moving Toward Improved Acquisition Outcomes: The Interrelationships Between Culture, Commitment, and Leadership

DTIC Science & Technology

2011-04-01

structure modeling . Psychological Methods, 1, 130–149. Mowday, R. T., Porter , L. W., & Steers, R. M. (1982). Organizational linkages: The psychology of...Leadership, Structural Equation Modeling , Analysis of Moment Structures (AMOS), Organizational Productivity MOVING TOWARD IMPROVED ACQUISITION OUTCOMES...greater than the sum of their individual elements. A conceptual model was identified and used as the foundation for building hypotheses. Structural

Integration of QUARK and I-TASSER for ab initio protein structure prediction in CASP11

PubMed Central

Zhang, Wenxuan; Yang, Jianyi; He, Baoji; Walker, Sara Elizabeth; Zhang, Hongjiu; Govindarajoo, Brandon; Virtanen, Jouko; Xue, Zhidong; Shen, Hong-Bin; Zhang, Yang

2015-01-01

We tested two pipelines developed for template-free protein structure prediction in the CASP11 experiment. First, the QUARK pipeline constructs structure models by reassembling fragments of continuously distributed lengths excised from unrelated proteins. Five free-modeling (FM) targets have the model successfully constructed by QUARK with a TM-score above 0.4, including the first model of T0837-D1, which has a TM-score=0.736 and RMSD=2.9 Å to the native. Detailed analysis showed that the success is partly attributed to the high-resolution contact map prediction derived from fragment-based distance-profiles, which are mainly located between regular secondary structure elements and loops/turns and help guide the orientation of secondary structure assembly. In the Zhang-Server pipeline, weakly scoring threading templates are re-ordered by the structural similarity to the ab initio folding models, which are then reassembled by I-TASSER based structure assembly simulations; 60% more domains with length up to 204 residues, compared to the QUARK pipeline, were successfully modeled by the I-TASSER pipeline with a TM-score above 0.4. The robustness of the I-TASSER pipeline can stem from the composite fragment-assembly simulations that combine structures from both ab initio folding and threading template refinements. Despite the promising cases, challenges still exist in long-range beta-strand folding, domain parsing, and the uncertainty of secondary structure prediction; the latter of which was found to affect nearly all aspects of FM structure predictions, from fragment identification, target classification, structure assembly, to final model selection. Significant efforts are needed to solve these problems before real progress on FM could be made. PMID:26370505

Integration of QUARK and I-TASSER for Ab Initio Protein Structure Prediction in CASP11.

PubMed

Zhang, Wenxuan; Yang, Jianyi; He, Baoji; Walker, Sara Elizabeth; Zhang, Hongjiu; Govindarajoo, Brandon; Virtanen, Jouko; Xue, Zhidong; Shen, Hong-Bin; Zhang, Yang

2016-09-01

We tested two pipelines developed for template-free protein structure prediction in the CASP11 experiment. First, the QUARK pipeline constructs structure models by reassembling fragments of continuously distributed lengths excised from unrelated proteins. Five free-modeling (FM) targets have the model successfully constructed by QUARK with a TM-score above 0.4, including the first model of T0837-D1, which has a TM-score = 0.736 and RMSD = 2.9 Å to the native. Detailed analysis showed that the success is partly attributed to the high-resolution contact map prediction derived from fragment-based distance-profiles, which are mainly located between regular secondary structure elements and loops/turns and help guide the orientation of secondary structure assembly. In the Zhang-Server pipeline, weakly scoring threading templates are re-ordered by the structural similarity to the ab initio folding models, which are then reassembled by I-TASSER based structure assembly simulations; 60% more domains with length up to 204 residues, compared to the QUARK pipeline, were successfully modeled by the I-TASSER pipeline with a TM-score above 0.4. The robustness of the I-TASSER pipeline can stem from the composite fragment-assembly simulations that combine structures from both ab initio folding and threading template refinements. Despite the promising cases, challenges still exist in long-range beta-strand folding, domain parsing, and the uncertainty of secondary structure prediction; the latter of which was found to affect nearly all aspects of FM structure predictions, from fragment identification, target classification, structure assembly, to final model selection. Significant efforts are needed to solve these problems before real progress on FM could be made. Proteins 2016; 84(Suppl 1):76-86. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Combinatorial structures to modeling simple games and applications

NASA Astrophysics Data System (ADS)

Molinero, Xavier

2017-09-01

We connect three different topics: combinatorial structures, game theory and chemistry. In particular, we establish the bases to represent some simple games, defined as influence games, and molecules, defined from atoms, by using combinatorial structures. First, we characterize simple games as influence games using influence graphs. It let us to modeling simple games as combinatorial structures (from the viewpoint of structures or graphs). Second, we formally define molecules as combinations of atoms. It let us to modeling molecules as combinatorial structures (from the viewpoint of combinations). It is open to generate such combinatorial structures using some specific techniques as genetic algorithms, (meta-)heuristics algorithms and parallel programming, among others.

Protein docking by the interface structure similarity: how much structure is needed?

PubMed

Sinha, Rohita; Kundrotas, Petras J; Vakser, Ilya A

2012-01-01

The increasing availability of co-crystallized protein-protein complexes provides an opportunity to use template-based modeling for protein-protein docking. Structure alignment techniques are useful in detection of remote target-template similarities. The size of the structure involved in the alignment is important for the success in modeling. This paper describes a systematic large-scale study to find the optimal definition/size of the interfaces for the structure alignment-based docking applications. The results showed that structural areas corresponding to the cutoff values <12 Å across the interface inadequately represent structural details of the interfaces. With the increase of the cutoff beyond 12 Å, the success rate for the benchmark set of 99 protein complexes, did not increase significantly for higher accuracy models, and decreased for lower-accuracy models. The 12 Å cutoff was optimal in our interface alignment-based docking, and a likely best choice for the large-scale (e.g., on the scale of the entire genome) applications to protein interaction networks. The results provide guidelines for the docking approaches, including high-throughput applications to modeled structures.

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.

VITAL NMR: Using Chemical Shift Derived Secondary Structure Information for a Limited Set of Amino Acids to Assess Homology Model Accuracy

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

Brothers, Michael C; Nesbitt, Anna E; Hallock, Michael J

2011-01-01

Homology modeling is a powerful tool for predicting protein structures, whose success depends on obtaining a reasonable alignment between a given structural template and the protein sequence being analyzed. In order to leverage greater predictive power for proteins with few structural templates, we have developed a method to rank homology models based upon their compliance to secondary structure derived from experimental solid-state NMR (SSNMR) data. Such data is obtainable in a rapid manner by simple SSNMR experiments (e.g., (13)C-(13)C 2D correlation spectra). To test our homology model scoring procedure for various amino acid labeling schemes, we generated a library ofmore » 7,474 homology models for 22 protein targets culled from the TALOS+/SPARTA+ training set of protein structures. Using subsets of amino acids that are plausibly assigned by SSNMR, we discovered that pairs of the residues Val, Ile, Thr, Ala and Leu (VITAL) emulate an ideal dataset where all residues are site specifically assigned. Scoring the models with a predicted VITAL site-specific dataset and calculating secondary structure with the Chemical Shift Index resulted in a Pearson correlation coefficient (-0.75) commensurate to the control (-0.77), where secondary structure was scored site specifically for all amino acids (ALL 20) using STRIDE. This method promises to accelerate structure procurement by SSNMR for proteins with unknown folds through guiding the selection of remotely homologous protein templates and assessing model quality.« less

Attitude error response of structures to actuator/sensor noise

NASA Technical Reports Server (NTRS)

Balakrishnan, A. V.

1991-01-01

Explicit closed-form formulas are presented for the RMS attitude-error response to sensor and actuator noise for co-located actuators/sensors as a function of both control-gain parameters and structure parameters. The main point of departure is the use of continuum models. In particular the anisotropic Timoshenko model is used for lattice trusses typified by the NASA EPS Structure Model and the Evolutionary Model. One conclusion is that the maximum attainable improvement in the attitude error varying either structure parameters or control gains is 3 dB for the axial and torsion modes, the bending being essentially insensitive. The results are similar whether the Bernoulli model or the anisotropic Timoshenko model is used.

Coopersmith Self-Esteem: Two Different Hypothesized Factor Models--Both Acceptable for the Same Data Structure.

ERIC Educational Resources Information Center

Hofmann, Rich; Sherman, Larry

Using data from 135 sixth-, seventh-, and eighth-graders between 11 and 15 years old attending a middle school in a suburban Southwest Ohio school district, two hypothesized models of the factor structures for the Coopersmith Self-Esteem Inventory were tested. One model represents the original Coopersmith factor structure, and the other model is…

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.

Massive integration of diverse protein quality assessment methods to improve template based modeling in CASP11.

PubMed

Cao, Renzhi; Bhattacharya, Debswapna; Adhikari, Badri; Li, Jilong; Cheng, Jianlin

2016-09-01

Model evaluation and selection is an important step and a big challenge in template-based protein structure prediction. Individual model quality assessment methods designed for recognizing some specific properties of protein structures often fail to consistently select good models from a model pool because of their limitations. Therefore, combining multiple complimentary quality assessment methods is useful for improving model ranking and consequently tertiary structure prediction. Here, we report the performance and analysis of our human tertiary structure predictor (MULTICOM) based on the massive integration of 14 diverse complementary quality assessment methods that was successfully benchmarked in the 11th Critical Assessment of Techniques of Protein Structure prediction (CASP11). The predictions of MULTICOM for 39 template-based domains were rigorously assessed by six scoring metrics covering global topology of Cα trace, local all-atom fitness, side chain quality, and physical reasonableness of the model. The results show that the massive integration of complementary, diverse single-model and multi-model quality assessment methods can effectively leverage the strength of single-model methods in distinguishing quality variation among similar good models and the advantage of multi-model quality assessment methods of identifying reasonable average-quality models. The overall excellent performance of the MULTICOM predictor demonstrates that integrating a large number of model quality assessment methods in conjunction with model clustering is a useful approach to improve the accuracy, diversity, and consequently robustness of template-based protein structure prediction. Proteins 2016; 84(Suppl 1):247-259. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

[Primary branch size of Pinus koraiensis plantation: a prediction based on linear mixed effect model].

PubMed

Dong, Ling-Bo; Liu, Zhao-Gang; Li, Feng-Ri; Jiang, Li-Chun

2013-09-01

By using the branch analysis data of 955 standard branches from 60 sampled trees in 12 sampling plots of Pinus koraiensis plantation in Mengjiagang Forest Farm in Heilongjiang Province of Northeast China, and based on the linear mixed-effect model theory and methods, the models for predicting branch variables, including primary branch diameter, length, and angle, were developed. Considering tree effect, the MIXED module of SAS software was used to fit the prediction models. The results indicated that the fitting precision of the models could be improved by choosing appropriate random-effect parameters and variance-covariance structure. Then, the correlation structures including complex symmetry structure (CS), first-order autoregressive structure [AR(1)], and first-order autoregressive and moving average structure [ARMA(1,1)] were added to the optimal branch size mixed-effect model. The AR(1) improved the fitting precision of branch diameter and length mixed-effect model significantly, but all the three structures didn't improve the precision of branch angle mixed-effect model. In order to describe the heteroscedasticity during building mixed-effect model, the CF1 and CF2 functions were added to the branch mixed-effect model. CF1 function improved the fitting effect of branch angle mixed model significantly, whereas CF2 function improved the fitting effect of branch diameter and length mixed model significantly. Model validation confirmed that the mixed-effect model could improve the precision of prediction, as compare to the traditional regression model for the branch size prediction of Pinus koraiensis plantation.

Automated dynamic analytical model improvement for damped structures

NASA Technical Reports Server (NTRS)

Fuh, J. S.; Berman, A.

1985-01-01

A method is described to improve a linear nonproportionally damped analytical model of a structure. The procedure finds the smallest changes in the analytical model such that the improved model matches the measured modal parameters. Features of the method are: (1) ability to properly treat complex valued modal parameters of a damped system; (2) applicability to realistically large structural models; and (3) computationally efficiency without involving eigensolutions and inversion of a large matrix.

Trajectory-Based Loads for the Ares I-X Test Flight Vehicle

NASA Technical Reports Server (NTRS)

Vause, Roland F.; Starr, Brett R.

2011-01-01

In trajectory-based loads, the structural engineer treats each point on the trajectory as a load case. Distributed aero, inertial, and propulsion forces are developed for the structural model which are equivalent to the integrated values of the trajectory model. Free-body diagrams are then used to solve for the internal forces, or loads, that keep the applied aero, inertial, and propulsion forces in dynamic equilibrium. There are several advantages to using trajectory-based loads. First, consistency is maintained between the integrated equilibrium equations of the trajectory analysis and the distributed equilibrium equations of the structural analysis. Second, the structural loads equations are tied to the uncertainty model for the trajectory systems analysis model. Atmosphere, aero, propulsion, mass property, and controls uncertainty models all feed into the dispersions that are generated for the trajectory systems analysis model. Changes in any of these input models will affect structural loads response. The trajectory systems model manages these inputs as well as the output from the structural model over thousands of dispersed cases. Large structural models with hundreds of thousands of degrees of freedom would execute too slowly to be an efficient part of several thousand system analyses. Trajectory-based loads provide a means for the structures discipline to be included in the integrated systems analysis. Successful applications of trajectory-based loads methods for the Ares I-X vehicle are covered in this paper. Preliminary design loads were based on 2000 trajectories using Monte Carlo dispersions. Range safety loads were tied to 8423 malfunction turn trajectories. In addition, active control system loads were based on 2000 preflight trajectories using Monte Carlo dispersions.

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 sponsored by JPL and other organizations to develop a unified control/structures modeling and design capability for large space structures is 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. 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. Recommendations are also presented for near term research activities at JPL. The key recommendation is to continue the development of integrated dynamic modeling/control design techniques, with special attention given to the development of structural models specially tailored to support design.

Deformable complex network for refining low-resolution X-ray structures

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

Zhang, Chong; Wang, Qinghua; Ma, Jianpeng, E-mail: jpma@bcm.edu

2015-10-27

A new refinement algorithm called the deformable complex network that combines a novel angular network-based restraint with a deformable elastic network model in the target function has been developed to aid in structural refinement in macromolecular X-ray crystallography. In macromolecular X-ray crystallography, building more accurate atomic models based on lower resolution experimental diffraction data remains a great challenge. Previous studies have used a deformable elastic network (DEN) model to aid in low-resolution structural refinement. In this study, the development of a new refinement algorithm called the deformable complex network (DCN) is reported that combines a novel angular network-based restraint withmore » the DEN model in the target function. Testing of DCN on a wide range of low-resolution structures demonstrated that it constantly leads to significantly improved structural models as judged by multiple refinement criteria, thus representing a new effective refinement tool for low-resolution structural determination.« less

A structural model for surface-enhanced stabilization in some metallic glass formers

NASA Astrophysics Data System (ADS)

Levchenko, Elena V.; Evteev, Alexander V.; Yavari, Alain R.; Louzguine-Luzgin, Dmitri V.; Belova, Irina V.; Murch, Graeme E.

2013-01-01

A structural model for surface-enhanced stabilization in some metallic glass formers is proposed. In this model, the alloy surface structure is represented by five-layer Kagomé-net-based lateral ordering. Such surface structure has intrinsic abilities to stabilize icosahedral-like short-range order in the bulk, acting as 'a cloak of liquidity'. In particular, recent experimental observations of surface-induced lateral ordering and a very high glass forming ability of the liquid alloy Au49Ag5.5Pd2.3Cu26.9Si16.3 can be united using this structural model. This model may be useful for the interpretation of surface structure of other liquid alloys with a high glass forming ability. In addition, it suggests the possibility of guiding the design of the surface coating of solid containers for the stabilization of undercooled liquids.

Revised Atomistic Models of the Crystal Structure of C-S-H with high C/S Ratio

NASA Astrophysics Data System (ADS)

Kovačević, Goran; Nicoleau, Luc; Nonat, André; Veryazov, Valera

2016-09-01

The atomic structure of calcium-silicate-hydrate (C1.67-S-Hx) has been studied. Atomistic C-S-H models suggested in our previous study have been revised in order to perform a direct comparison of energetic stability of the different structures. An extensive set of periodic structures of C-S-H with variation of water content was created, and then optimized using molecular dynamics with reactive force field ReaxFF and quantum chemical semiempirical method PM6. All models show organization of water molecules inside the structure of C-S-H. The new geometries of C-S-H, reported in this paper, show lower relative energy with respect to the geometries from the original definition of C-S-H models. Model that corresponds to calcium enriched tobermorite structure has the lowest relative energy and the density closest to the experimental values.

Bayesian comparison of protein structures using partial Procrustes distance.

PubMed

Ejlali, Nasim; Faghihi, Mohammad Reza; Sadeghi, Mehdi

2017-09-26

An important topic in bioinformatics is the protein structure alignment. Some statistical methods have been proposed for this problem, but most of them align two protein structures based on the global geometric information without considering the effect of neighbourhood in the structures. In this paper, we provide a Bayesian model to align protein structures, by considering the effect of both local and global geometric information of protein structures. Local geometric information is incorporated to the model through the partial Procrustes distance of small substructures. These substructures are composed of β-carbon atoms from the side chains. Parameters are estimated using a Markov chain Monte Carlo (MCMC) approach. We evaluate the performance of our model through some simulation studies. Furthermore, we apply our model to a real dataset and assess the accuracy and convergence rate. Results show that our model is much more efficient than previous approaches.

Model reduction in integrated controls-structures design

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.

1993-01-01

It is the objective of this paper to present a model reduction technique developed for the integrated controls-structures design of flexible structures. Integrated controls-structures design problems are typically posed as nonlinear mathematical programming problems, where the design variables consist of both structural and control parameters. In the solution process, both structural and control design variables are constantly changing; therefore, the dynamic characteristics of the structure are also changing. This presents a problem in obtaining a reduced-order model for active control design and analysis which will be valid for all design points within the design space. In other words, the frequency and number of the significant modes of the structure (modes that should be included) may vary considerably throughout the design process. This is also true as the locations and/or masses of the sensors and actuators change. Moreover, since the number of design evaluations in the integrated design process could easily run into thousands, any feasible order-reduction method should not require model reduction analysis at every design iteration. In this paper a novel and efficient technique for model reduction in the integrated controls-structures design process, which addresses these issues, is presented.

Hands-On Exercise in Environmental Structural Geology Using a Fracture Block Model.

ERIC Educational Resources Information Center

Gates, Alexander E.

2001-01-01

Describes the use of a scale analog model of an actual fractured rock reservoir to replace paper copies of fracture maps in the structural geology curriculum. Discusses the merits of the model in enabling students to gain experience performing standard structural analyses. (DDR)

Bayesian Semiparametric Structural Equation Models with Latent Variables

ERIC Educational Resources Information Center

Yang, Mingan; Dunson, David B.

2010-01-01

Structural equation models (SEMs) with latent variables are widely useful for sparse covariance structure modeling and for inferring relationships among latent variables. Bayesian SEMs are appealing in allowing for the incorporation of prior information and in providing exact posterior distributions of unknowns, including the latent variables. In…

Meta-Analytic Structural Equation Modeling (MASEM): Comparison of the Multivariate Methods

ERIC Educational Resources Information Center

Zhang, Ying

2011-01-01

Meta-analytic Structural Equation Modeling (MASEM) has drawn interest from many researchers recently. In doing MASEM, researchers usually first synthesize correlation matrices across studies using meta-analysis techniques and then analyze the pooled correlation matrix using structural equation modeling techniques. Several multivariate methods of…

A Teaching Model for Truss Structures

ERIC Educational Resources Information Center

Bigoni, Davide; Dal Corso, Francesco; Misseroni, Diego; Tommasini, Mirko

2012-01-01

A classroom demonstration model has been designed, machined and successfully tested in different learning environments to facilitate understanding of the mechanics of truss structures, in which struts are subject to purely axial load and deformation. Gaining confidence with these structures is crucial for the development of lattice models, which…

Structural Equation Modeling of School Violence Data: Methodological Considerations

ERIC Educational Resources Information Center

Mayer, Matthew J.

2004-01-01

Methodological challenges associated with structural equation modeling (SEM) and structured means modeling (SMM) in research on school violence and related topics in the social and behavioral sciences are examined. Problems associated with multiyear implementations of large-scale surveys are discussed. Complex sample designs, part of any…

Status of DSMT research program

NASA Technical Reports Server (NTRS)

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

1991-01-01

The status of the Dynamic Scale Model Technology (DSMT) research program is presented. DSMT is developing scale model technology for large space structures as part of the Control Structure Interaction (CSI) program at NASA Langley Research Center (LaRC). Under DSMT a hybrid-scale structural dynamics model of Space Station Freedom was developed. Space Station Freedom was selected as the focus structure for DSMT since the station represents the first opportunity to obtain flight data on a complex, three-dimensional space structure. Included is an overview of DSMT including the development of the space station scale model and the resulting hardware. Scaling technology was developed for this model to achieve a ground test article which existing test facilities can accommodate while employing realistically scaled hardware. The model was designed and fabricated by the Lockheed Missile and Space Co., and is assembled at LaRc for dynamic testing. Also, results from ground tests and analyses of the various model components are presented along with plans for future subassembly and matted model tests. Finally, utilization of the scale model for enhancing analysis verification of the full-scale space station is also considered.

Using SAS PROC CALIS to fit Level-1 error covariance structures of latent growth models.

PubMed

Ding, Cherng G; Jane, Ten-Der

2012-09-01

In the present article, we demonstrates the use of SAS PROC CALIS to fit various types of Level-1 error covariance structures of latent growth models (LGM). Advantages of the SEM approach, on which PROC CALIS is based, include the capabilities of modeling the change over time for latent constructs, measured by multiple indicators; embedding LGM into a larger latent variable model; incorporating measurement models for latent predictors; and better assessing model fit and the flexibility in specifying error covariance structures. The strength of PROC CALIS is always accompanied with technical coding work, which needs to be specifically addressed. We provide a tutorial on the SAS syntax for modeling the growth of a manifest variable and the growth of a latent construct, focusing the documentation on the specification of Level-1 error covariance structures. Illustrations are conducted with the data generated from two given latent growth models. The coding provided is helpful when the growth model has been well determined and the Level-1 error covariance structure is to be identified.

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

PubMed

Guenole, Nigel

2016-01-01

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

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

PubMed Central

Guenole, Nigel

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

Gao, Ji; Zhang, Haijiang

2018-05-01

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

QSAR modeling of human serum protein binding with several modeling techniques utilizing structure-information representation.

PubMed

Votano, Joseph R; Parham, Marc; Hall, L Mark; Hall, Lowell H; Kier, Lemont B; Oloff, Scott; Tropsha, Alexander

2006-11-30

Four modeling techniques, using topological descriptors to represent molecular structure, were employed to produce models of human serum protein binding (% bound) on a data set of 1008 experimental values, carefully screened from publicly available sources. To our knowledge, this data is the largest set on human serum protein binding reported for QSAR modeling. The data was partitioned into a training set of 808 compounds and an external validation test set of 200 compounds. Partitioning was accomplished by clustering the compounds in a structure descriptor space so that random sampling of 20% of the whole data set produced an external test set that is a good representative of the training set with respect to both structure and protein binding values. The four modeling techniques include multiple linear regression (MLR), artificial neural networks (ANN), k-nearest neighbors (kNN), and support vector machines (SVM). With the exception of the MLR model, the ANN, kNN, and SVM QSARs were ensemble models. Training set correlation coefficients and mean absolute error ranged from r2=0.90 and MAE=7.6 for ANN to r2=0.61 and MAE=16.2 for MLR. Prediction results from the validation set yielded correlation coefficients and mean absolute errors which ranged from r2=0.70 and MAE=14.1 for ANN to a low of r2=0.59 and MAE=18.3 for the SVM model. Structure descriptors that contribute significantly to the models are discussed and compared with those found in other published models. For the ANN model, structure descriptor trends with respect to their affects on predicted protein binding can assist the chemist in structure modification during the drug design process.

Reducing structural uncertainty in conceptual hydrological modeling in the semi-arid Andes

NASA Astrophysics Data System (ADS)

Hublart, P.; Ruelland, D.; Dezetter, A.; Jourde, H.

2014-10-01

The use of lumped, conceptual models in hydrological impact studies requires placing more emphasis on the uncertainty arising from deficiencies and/or ambiguities in the model structure. This study provides an opportunity to combine a multiple-hypothesis framework with a multi-criteria assessment scheme to reduce structural uncertainty in the conceptual modeling of a meso-scale Andean catchment (1515 km2) over a 30 year period (1982-2011). The modeling process was decomposed into six model-building decisions related to the following aspects of the system behavior: snow accumulation and melt, runoff generation, redistribution and delay of water fluxes, and natural storage effects. Each of these decisions was provided with a set of alternative modeling options, resulting in a total of 72 competing model structures. These structures were calibrated using the concept of Pareto optimality with three criteria pertaining to streamflow simulations and one to the seasonal dynamics of snow processes. The results were analyzed in the four-dimensional space of performance measures using a fuzzy c-means clustering technique and a differential split sample test, leading to identify 14 equally acceptable model hypotheses. A filtering approach was then applied to these best-performing structures in order to minimize the overall uncertainty envelope while maximizing the number of enclosed observations. This led to retain 8 model hypotheses as a representation of the minimum structural uncertainty that could be obtained with this modeling framework. Future work to better consider model predictive uncertainty should include a proper assessment of parameter equifinality and data errors, as well as the testing of new or refined hypotheses to allow for the use of additional auxiliary observations.

Reducing structural uncertainty in conceptual hydrological modelling in the semi-arid Andes

NASA Astrophysics Data System (ADS)

Hublart, P.; Ruelland, D.; Dezetter, A.; Jourde, H.

2015-05-01

The use of lumped, conceptual models in hydrological impact studies requires placing more emphasis on the uncertainty arising from deficiencies and/or ambiguities in the model structure. This study provides an opportunity to combine a multiple-hypothesis framework with a multi-criteria assessment scheme to reduce structural uncertainty in the conceptual modelling of a mesoscale Andean catchment (1515 km2) over a 30-year period (1982-2011). The modelling process was decomposed into six model-building decisions related to the following aspects of the system behaviour: snow accumulation and melt, runoff generation, redistribution and delay of water fluxes, and natural storage effects. Each of these decisions was provided with a set of alternative modelling options, resulting in a total of 72 competing model structures. These structures were calibrated using the concept of Pareto optimality with three criteria pertaining to streamflow simulations and one to the seasonal dynamics of snow processes. The results were analyzed in the four-dimensional (4-D) space of performance measures using a fuzzy c-means clustering technique and a differential split sample test, leading to identify 14 equally acceptable model hypotheses. A filtering approach was then applied to these best-performing structures in order to minimize the overall uncertainty envelope while maximizing the number of enclosed observations. This led to retain eight model hypotheses as a representation of the minimum structural uncertainty that could be obtained with this modelling framework. Future work to better consider model predictive uncertainty should include a proper assessment of parameter equifinality and data errors, as well as the testing of new or refined hypotheses to allow for the use of additional auxiliary observations.

Functional insights from proteome-wide structural modeling of Treponema pallidum subspecies pallidum, the causative agent of syphilis.

PubMed

Houston, Simon; Lithgow, Karen Vivien; Osbak, Kara Krista; Kenyon, Chris Richard; Cameron, Caroline E

2018-05-16

Syphilis continues to be a major global health threat with 11 million new infections each year, and a global burden of 36 million cases. The causative agent of syphilis, Treponema pallidum subspecies pallidum, is a highly virulent bacterium, however the molecular mechanisms underlying T. pallidum pathogenesis remain to be definitively identified. This is due to the fact that T. pallidum is currently uncultivatable, inherently fragile and thus difficult to work with, and phylogenetically distinct with no conventional virulence factor homologs found in other pathogens. In fact, approximately 30% of its predicted protein-coding genes have no known orthologs or assigned functions. Here we employed a structural bioinformatics approach using Phyre2-based tertiary structure modeling to improve our understanding of T. pallidum protein function on a proteome-wide scale. Phyre2-based tertiary structure modeling generated high-confidence predictions for 80% of the T. pallidum proteome (780/978 predicted proteins). Tertiary structure modeling also inferred the same function as primary structure-based annotations from genome sequencing pipelines for 525/605 proteins (87%), which represents 54% (525/978) of all T. pallidum proteins. Of the 175 T. pallidum proteins modeled with high confidence that were not assigned functions in the previously annotated published proteome, 167 (95%) were able to be assigned predicted functions. Twenty-one of the 175 hypothetical proteins modeled with high confidence were also predicted to exhibit significant structural similarity with proteins experimentally confirmed to be required for virulence in other pathogens. Phyre2-based structural modeling is a powerful bioinformatics tool that has provided insight into the potential structure and function of the majority of T. pallidum proteins and helped validate the primary structure-based annotation of more than 50% of all T. pallidum proteins with high confidence. This work represents the first T. pallidum proteome-wide structural modeling study and is one of few studies to apply this approach for the functional annotation of a whole proteome.

Structured statistical models of inductive reasoning.

PubMed

Kemp, Charles; Tenenbaum, Joshua B

2009-01-01

Everyday inductive inferences are often guided by rich background knowledge. Formal models of induction should aim to incorporate this knowledge and should explain how different kinds of knowledge lead to the distinctive patterns of reasoning found in different inductive contexts. This article presents a Bayesian framework that attempts to meet both goals and describes [corrected] 4 applications of the framework: a taxonomic model, a spatial model, a threshold model, and a causal model. Each model makes probabilistic inferences about the extensions of novel properties, but the priors for the 4 models are defined over different kinds of structures that capture different relationships between the categories in a domain. The framework therefore shows how statistical inference can operate over structured background knowledge, and the authors argue that this interaction between structure and statistics is critical for explaining the power and flexibility of human reasoning.

A Taxonomy-Based Approach to Shed Light on the Babel of Mathematical Models for Rice Simulation

NASA Technical Reports Server (NTRS)

Confalonieri, Roberto; Bregaglio, Simone; Adam, Myriam; Ruget, Francoise; Li, Tao; Hasegawa, Toshihiro; Yin, Xinyou; Zhu, Yan; Boote, Kenneth; Buis, Samuel;

FAST Mast Structural Response to Axial Loading: Modeling and Verification

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.; Elliott, Kenny B.; Templeton, Justin D.; Song, Kyongchan; Rayburn, Jeffery T.

2012-01-01

The International Space Station s solar array wing mast shadowing problem is the focus of this paper. A building-block approach to modeling and analysis is pursued for the primary structural components of the solar array wing mast structure. Starting with an ANSYS (Registered Trademark) finite element model, a verified MSC.Nastran (Trademark) model is established for a single longeron. This finite element model translation requires the conversion of several modeling and analysis features for the two structural analysis tools to produce comparable results for the single-longeron configuration. The model is then reconciled using test data. The resulting MSC.Nastran (Trademark) model is then extended to a single-bay configuration and verified using single-bay test data. Conversion of the MSC. Nastran (Trademark) single-bay model to Abaqus (Trademark) is also performed to simulate the elastic-plastic longeron buckling response of the single bay prior to folding.

A resource for benchmarking the usefulness of protein structure models.

PubMed

Carbajo, Daniel; Tramontano, Anna

2012-08-02

Increasingly, biologists and biochemists use computational tools to design experiments to probe the function of proteins and/or to engineer them for a variety of different purposes. The most effective strategies rely on the knowledge of the three-dimensional structure of the protein of interest. However it is often the case that an experimental structure is not available and that models of different quality are used instead. On the other hand, the relationship between the quality of a model and its appropriate use is not easy to derive in general, and so far it has been analyzed in detail only for specific application. This paper describes a database and related software tools that allow testing of a given structure based method on models of a protein representing different levels of accuracy. The comparison of the results of a computational experiment on the experimental structure and on a set of its decoy models will allow developers and users to assess which is the specific threshold of accuracy required to perform the task effectively. The ModelDB server automatically builds decoy models of different accuracy for a given protein of known structure and provides a set of useful tools for their analysis. Pre-computed data for a non-redundant set of deposited protein structures are available for analysis and download in the ModelDB database. IMPLEMENTATION, AVAILABILITY AND REQUIREMENTS: Project name: A resource for benchmarking the usefulness of protein structure models. Project home page: http://bl210.caspur.it/MODEL-DB/MODEL-DB_web/MODindex.php.Operating system(s): Platform independent. Programming language: Perl-BioPerl (program); mySQL, Perl DBI and DBD modules (database); php, JavaScript, Jmol scripting (web server). Other requirements: Java Runtime Environment v1.4 or later, Perl, BioPerl, CPAN modules, HHsearch, Modeller, LGA, NCBI Blast package, DSSP, Speedfill (Surfnet) and PSAIA. License: Free. Any restrictions to use by non-academics: No.

The contrasting response of Hadley circulation to different meridional structure of sea surface temperature in CMIP5

NASA Astrophysics Data System (ADS)

Feng, Juan; Li, Jianping; Zhu, Jianlei; Li, Yang; Li, Fei

2018-02-01

The response of the Hadley circulation (HC) to the sea surface temperature (SST) is determined by the meridional structure of SST and varies according to the changing nature of this meridional structure. The capability of the models from the phase 5 of the Coupled Model Intercomparison Project (CMIP5) is utilized to represent the contrast response of the HC to different meridional SST structures. To evaluate the responses, the variations of HC and SST were linearly decomposed into two components: the equatorially asymmetric (HEA for HC, and SEA for SST) and equatorially symmetric (HES for HC, and SES for SST) components. The result shows that the climatological features of HC and tropical SST (including the spatial structures and amplitude) are reasonably simulated in all the models. However, the response contrast of HC to different SST meridional structures shows uncertainties among models. This may be due to the fact that the long-term temporal variabilities of HEA, HES, and SEA are limited reproduced in the models, although the spatial structures of their long-term variabilities are relatively reasonably simulated. These results indicate that the performance of the CMIP5 models to simulate long-term temporal variability of different meridional SST structures and related HC variations plays a fundamental role in the successful reproduction of the response of HC to different meridional SST structures.

An Efficient Analysis Methodology for Fluted-Core Composite Structures

NASA Technical Reports Server (NTRS)

Oremont, Leonard; Schultz, Marc R.

2012-01-01

The primary loading condition in launch-vehicle barrel sections is axial compression, and it is therefore important to understand the compression behavior of any structures, structural concepts, and materials considered in launch-vehicle designs. This understanding will necessarily come from a combination of test and analysis. However, certain potentially beneficial structures and structural concepts do not lend themselves to commonly used simplified analysis methods, and therefore innovative analysis methodologies must be developed if these structures and structural concepts are to be considered. This paper discusses such an analysis technique for the fluted-core sandwich composite structural concept. The presented technique is based on commercially available finite-element codes, and uses shell elements to capture behavior that would normally require solid elements to capture the detailed mechanical response of the structure. The shell thicknesses and offsets using this analysis technique are parameterized, and the parameters are adjusted through a heuristic procedure until this model matches the mechanical behavior of a more detailed shell-and-solid model. Additionally, the detailed shell-and-solid model can be strategically placed in a larger, global shell-only model to capture important local behavior. Comparisons between shell-only models, experiments, and more detailed shell-and-solid models show excellent agreement. The discussed analysis methodology, though only discussed in the context of fluted-core composites, is widely applicable to other concepts.

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.

Development of Vehicle Model Test for Road Loading Analysis of Sedan Model

NASA Astrophysics Data System (ADS)

Mohd Nor, M. K.; Noordin, A.; Ruzali, M. F. S.; Hussen, M. H.

2016-11-01

Simple Structural Surfaces (SSS) method is offered as a means of organizing the process for rationalizing the basic vehicle body structure load paths. The application of this simplified approach is highly beneficial in the design development of modern passenger car structure especially during the conceptual stage. In Malaysia, however, there is no real physical model of SSS available to gain considerable insight and understanding into the function of each major subassembly in the whole vehicle structures. Based on this motivation, a physical model of SSS for sedan model with the corresponding model vehicle tests of bending and torsion is proposed in this work. The proposed approach is relatively easy to understand as compared to Finite Element Method (FEM). The results show that the proposed vehicle model test is capable to show that satisfactory load paths can give a sufficient structural stiffness within the vehicle structure. It is clearly observed that the global bending stiffness reduce significantly when more panels are removed from a complete SSS model. It is identified that parcel shelf is an important subassembly to sustain bending load. The results also match with the theoretical hypothesis, as the stiffness of the structure in an open section condition is shown weak when subjected to torsion load compared to bending load. The proposed approach can potentially be integrated with FEM to speed up the design process of automotive vehicle.

Vision-based stress estimation model for steel frame structures with rigid links

NASA Astrophysics Data System (ADS)

Park, Hyo Seon; Park, Jun Su; Oh, Byung Kwan

2017-07-01

This paper presents a stress estimation model for the safety evaluation of steel frame structures with rigid links using a vision-based monitoring system. In this model, the deformed shape of a structure under external loads is estimated via displacements measured by a motion capture system (MCS), which is a non-contact displacement measurement device. During the estimation of the deformed shape, the effective lengths of the rigid link ranges in the frame structure are identified. The radius of the curvature of the structural member to be monitored is calculated using the estimated deformed shape and is employed to estimate stress. Using MCS in the presented model, the safety of a structure can be assessed gauge-freely. In addition, because the stress is directly extracted from the radius of the curvature obtained from the measured deformed shape, information on the loadings and boundary conditions of the structure are not required. Furthermore, the model, which includes the identification of the effective lengths of the rigid links, can consider the influences of the stiffness of the connection and support on the deformation in the stress estimation. To verify the applicability of the presented model, static loading tests for a steel frame specimen were conducted. By comparing the stress estimated by the model with the measured stress, the validity of the model was confirmed.

ModeRNA: a tool for comparative modeling of RNA 3D structure

PubMed Central

Rother, Magdalena; Rother, Kristian; Puton, Tomasz; Bujnicki, Janusz M.

2011-01-01

RNA is a large group of functionally important biomacromolecules. In striking analogy to proteins, the function of RNA depends on its structure and dynamics, which in turn is encoded in the linear sequence. However, while there are numerous methods for computational prediction of protein three-dimensional (3D) structure from sequence, with comparative modeling being the most reliable approach, there are very few such methods for RNA. Here, we present ModeRNA, a software tool for comparative modeling of RNA 3D structures. As an input, ModeRNA requires a 3D structure of a template RNA molecule, and a sequence alignment between the target to be modeled and the template. It must be emphasized that a good alignment is required for successful modeling, and for large and complex RNA molecules the development of a good alignment usually requires manual adjustments of the input data based on previous expertise of the respective RNA family. ModeRNA can model post-transcriptional modifications, a functionally important feature analogous to post-translational modifications in proteins. ModeRNA can also model DNA structures or use them as templates. It is equipped with many functions for merging fragments of different nucleic acid structures into a single model and analyzing their geometry. Windows and UNIX implementations of ModeRNA with comprehensive documentation and a tutorial are freely available. PMID:21300639

Crystal structures of η''-Cu3+xSi and η'''-Cu3+xSi.

PubMed

Corrêa, Cinthia Antunes; Perez, Olivier; Kopeček, Jaromír; Brázda, Petr; Klementová, Mariana; Palatinus, Lukáš

2017-08-01

The binary phase diagram of Cu-Si is unexpectedly complex in the vicinity of Cu 3+x Si. The low-temperature region contains three closely related incommensurately modulated phases denoted, in order of increasing temperature of stability, η''', η'' and η'. The structure analysis of η' has been reported previously [Palatinus et al. (2011). Inorg. Chem. 50, 3743]. Here the structure model for the phases η'' and η''' is reported. The structures could be solved in superspace, but no superspace structure model could be constructed due to the complexity of the modulation functions. Therefore, the structures were described in a supercell approximation, which involved a 4 × 4 × 3 supercell for the η'' phase and a 14 × 14 × 3 supercell for the η''' phase. Both structures are very similar and differ only by a subtle symmetry lowering from η'' to η'''. A comparison of the structure models of η'' and η''' with the reported structure of η' suggests that the reported structure model of η' contains an incorrect assignment of atomic types.

Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation.

PubMed

Villaverde, Alejandro F; Banga, Julio R

2017-11-01

The concept of dynamical compensation has been recently introduced to describe the ability of a biological system to keep its output dynamics unchanged in the face of varying parameters. However, the original definition of dynamical compensation amounts to lack of structural identifiability. This is relevant if model parameters need to be estimated, as is often the case in biological modelling. Care should we taken when using an unidentifiable model to extract biological insight: the estimated values of structurally unidentifiable parameters are meaningless, and model predictions about unmeasured state variables can be wrong. Taking this into account, we explore alternative definitions of dynamical compensation that do not necessarily imply structural unidentifiability. Accordingly, we show different ways in which a model can be made identifiable while exhibiting dynamical compensation. Our analyses enable the use of the new concept of dynamical compensation in the context of parameter identification, and reconcile it with the desirable property of structural identifiability.

Analysis of Challenges for Management Education in India Using Total Interpretive Structural Modelling

ERIC Educational Resources Information Center

Mahajan, Ritika; Agrawal, Rajat; Sharma, Vinay; Nangia, Vinay

2016-01-01

Purpose: The purpose of this paper is to identify challenges for management education in India and explain their nature, significance and interrelations using total interpretive structural modelling (TISM), an innovative version of Warfield's interpretive structural modelling (ISM). Design/methodology/approach: The challenges have been drawn from…

Sensitivity of Fit Indices to Misspecification in Growth Curve Models

ERIC Educational Resources Information Center

Wu, Wei; West, Stephen G.

2010-01-01

This study investigated the sensitivity of fit indices to model misspecification in within-individual covariance structure, between-individual covariance structure, and marginal mean structure in growth curve models. Five commonly used fit indices were examined, including the likelihood ratio test statistic, root mean square error of…

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

ERIC Educational Resources Information Center

Bindel, Thomas H.

2008-01-01

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

On Structural Equation Model Equivalence.

ERIC Educational Resources Information Center

Raykov, Tenko; Penev, Spiridon

1999-01-01

Presents a necessary and sufficient condition for the equivalence of structural-equation models that is applicable to models with parameter restrictions and models that may or may not fulfill assumptions of the rules. Illustrates the application of the approach for studying model equivalence. (SLD)

Method for Real-Time Model Based Structural Anomaly Detection

NASA Technical Reports Server (NTRS)

Urnes, James M., Sr. (Inventor); Smith, Timothy A. (Inventor); Reichenbach, Eric Y. (Inventor)

2015-01-01

A system and methods for real-time model based vehicle structural anomaly detection are disclosed. A real-time measurement corresponding to a location on a vehicle structure during an operation of the vehicle is received, and the real-time measurement is compared to expected operation data for the location to provide a modeling error signal. A statistical significance of the modeling error signal to provide an error significance is calculated, and a persistence of the error significance is determined. A structural anomaly is indicated, if the persistence exceeds a persistence threshold value.

Finite element analysis of structural engineering problems using a viscoplastic model incorporating two back stresses

NASA Technical Reports Server (NTRS)

Arya, Vinod K.; Halford, Gary R.

1993-01-01

The feasibility of a viscoplastic model incorporating two back stresses and a drag strength is investigated for performing nonlinear finite element analyses of structural engineering problems. To demonstrate suitability for nonlinear structural analyses, the model is implemented into a finite element program and analyses for several uniaxial and multiaxial problems are performed. Good agreement is shown between the results obtained using the finite element implementation and those obtained experimentally. The advantages of using advanced viscoplastic models for performing nonlinear finite element analyses of structural components are indicated.

Stellar Structure Models of Deformed Neutron Stars

NASA Astrophysics Data System (ADS)

Zubairi, Omair; Wigley, David; Weber, Fridolin

Traditional stellar structure models of non-rotating neutron stars work under the assumption that these stars are perfect spheres. This assumption of perfect spherical symmetry is not correct if the matter inside neutron stars is described by an anisotropic model for the equation of state. Certain classes of neutron stars such as Magnetars and neutron stars which contain color-superconducting quark matter cores are expected to be deformed making them oblong spheroids. In this work, we investigate the stellar structure of these deformed neutron stars by deriving stellar structure equations in the framework of general relativity. Using a non-isotropic equation of state model, we solve these structure equations numerically in two dimensions. We calculate stellar properties such as masses and radii along with pressure profiles and investigate changes from standard spherical models.

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

Magnetohydrodynamic (MHD) Magnet Modeling

DTIC Science & Technology

1979-06-01

Relationship /4 to Structural Teeth and Cold Bore Tube 56 Force Cý.mponents on Saddlc Winding 84 57 Quarter Section of Magnet nesign at Midplane 85 58...Graphite/Epoxy Filament Wound 184 A-2 Concept B - Boron /Aluminum Structure 186 A-3 Concept i - Graphite/Epoxy Structure 187 A-4 Initial Stress Analysis...Wound A-15 MHD Magnet Modeling Manufacturing Sequence 205 Concept B - Boron /Aluminum Structure A-16 MHD Magnet Modeling Manufacturing Sequence 206

On the Model-Based Bootstrap with Missing Data: Obtaining a "P"-Value for a Test of Exact Fit

ERIC Educational Resources Information Center

Savalei, Victoria; Yuan, Ke-Hai

2009-01-01

Evaluating the fit of a structural equation model via bootstrap requires a transformation of the data so that the null hypothesis holds exactly in the sample. For complete data, such a transformation was proposed by Beran and Srivastava (1985) for general covariance structure models and applied to structural equation modeling by Bollen and Stine…

Python package for model STructure ANalysis (pySTAN)

NASA Astrophysics Data System (ADS)

Van Hoey, Stijn; van der Kwast, Johannes; Nopens, Ingmar; Seuntjens, Piet

2013-04-01

The selection and identification of a suitable hydrological model structure is more than fitting parameters of a model structure to reproduce a measured hydrograph. The procedure is highly dependent on various criteria, i.e. the modelling objective, the characteristics and the scale of the system under investigation as well as the available data. Rigorous analysis of the candidate model structures is needed to support and objectify the selection of the most appropriate structure for a specific case (or eventually justify the use of a proposed ensemble of structures). This holds both in the situation of choosing between a limited set of different structures as well as in the framework of flexible model structures with interchangeable components. Many different methods to evaluate and analyse model structures exist. This leads to a sprawl of available methods, all characterized by different assumptions, changing conditions of application and various code implementations. Methods typically focus on optimization, sensitivity analysis or uncertainty analysis, with backgrounds from optimization, machine-learning or statistics amongst others. These methods also need an evaluation metric (objective function) to compare the model outcome with some observed data. However, for current methods described in literature, implementations are not always transparent and reproducible (if available at all). No standard procedures exist to share code and the popularity (and amount of applications) of the methods is sometimes more dependent on the availability than the merits of the method. Moreover, new implementations of existing methods are difficult to verify and the different theoretical backgrounds make it difficult for environmental scientists to decide about the usefulness of a specific method. A common and open framework with a large set of methods can support users in deciding about the most appropriate method. Hence, it enables to simultaneously apply and compare different methods on a fair basis. We developed and present pySTAN (python framework for STructure Analysis), a python package containing a set of functions for model structure evaluation to provide the analysis of (hydrological) model structures. A selected set of algorithms for optimization, uncertainty and sensitivity analysis is currently available, together with a set of evaluation (objective) functions and input distributions to sample from. The methods are implemented model-independent and the python language provides the wrapper functions to apply administer external model codes. Different objective functions can be considered simultaneously with both statistical metrics and more hydrology specific metrics. By using so-called reStructuredText (sphinx documentation generator) and Python documentation strings (docstrings), the generation of manual pages is semi-automated and a specific environment is available to enhance both the readability and transparency of the code. It thereby enables a larger group of users to apply and compare these methods and to extend the functionalities.

Alternative spatial configurations to reflect landscape structure in a hydrological model: SUMMA applications to the Reynolds Creek Watershed and the Columbia River Basin

NASA Astrophysics Data System (ADS)

Nijssen, Bart; Clark, Martyn; Mizukami, Naoki; Chegwidden, Oriana

2016-04-01

Most existing hydrological models use a fixed representation of landscape structure. For example, high-resolution, spatially-distributed models may use grid cells that exchange moisture through the saturated subsurface or may divide the landscape into hydrologic response units that only exchange moisture through surface channels. Alternatively, many regional models represent the landscape through coarse elements that do not model any moisture exchange between these model elements. These spatial organizations are often represented at a low-level in the model code and its data structures, which makes it difficult to evaluate different landscape representations using the same hydrological model. Instead, such experimentation requires the use of multiple, different hydrological models, which in turn complicates the analysis, because differences in model outcomes are no longer constrained by differing spatial representations. This inflexibility in the representation of landscape structure also limits a model's capability for scaling local processes to regional outcomes. In this study, we used the Structure for Unifying Multiple Modeling Alternatives (SUMMA) to evaluate different model spatial configurations to represent landscape structure and to evaluate scaling behavior. SUMMA can represent the moisture exchange between arbitrarily shaped landscape elements in a number of different ways, while using the same model parameterizations for vertical fluxes. This allows us to isolate the effects of changes in landscape representations on modeled hydrological fluxes and states. We examine the effects of spatial configuration in Reynolds Creek, Idaho, USA, which is a research watershed with gaged areas from 1-20 km2. We then use the same modeling system to evaluate scaling behavior in simulated hydrological fluxes in the Columbia River Basin, Pacific Northwest, USA. This basin drains more than 500,000 km2 and includes the Reynolds Creek Watershed.

Partial unfolding and refolding for structure refinement: A unified approach of geometric simulations and molecular dynamics.

PubMed

Kumar, Avishek; Campitelli, Paul; Thorpe, M F; Ozkan, S Banu

2015-12-01

The most successful protein structure prediction methods to date have been template-based modeling (TBM) or homology modeling, which predicts protein structure based on experimental structures. These high accuracy predictions sometimes retain structural errors due to incorrect templates or a lack of accurate templates in the case of low sequence similarity, making these structures inadequate in drug-design studies or molecular dynamics simulations. We have developed a new physics based approach to the protein refinement problem by mimicking the mechanism of chaperons that rehabilitate misfolded proteins. The template structure is unfolded by selectively (targeted) pulling on different portions of the protein using the geometric based technique FRODA, and then refolded using hierarchically restrained replica exchange molecular dynamics simulations (hr-REMD). FRODA unfolding is used to create a diverse set of topologies for surveying near native-like structures from a template and to provide a set of persistent contacts to be employed during re-folding. We have tested our approach on 13 previous CASP targets and observed that this method of folding an ensemble of partially unfolded structures, through the hierarchical addition of contact restraints (that is, first local and then nonlocal interactions), leads to a refolding of the structure along with refinement in most cases (12/13). Although this approach yields refined models through advancement in sampling, the task of blind selection of the best refined models still needs to be solved. Overall, the method can be useful for improved sampling for low resolution models where certain of the portions of the structure are incorrectly modeled. © 2015 Wiley Periodicals, Inc.

Structural Analysis Of CD59 Of Chinese Tree Shrew: A New Reference Molecule For Human Immune System Specific CD59 Drug Discovery.

PubMed

Panda, Subhamay; Kumari, Leena; Panda, Santamay

2017-11-17

Chinese tree shrews (Tupaia belangeri chinensis) bear several characteristics that are considered to be very crucial for utilizing in animal experimental models in biomedical research. Subsequent to the identification of key aspects and signaling pathways in nervous and immune systems, it is revealed that tree shrews acquires shared common as well as unique characteristics, and hence offers a genetic basis for employing this animal as a prospective model for biomedical research. CD59 glycoprotein, commonly referred to as MAC-inhibitory protein (MAC-IP), membrane inhibitor of reactive lysis (MIRL), or protectin, is encoded by the CD59 gene in human beings. It is the member of the LY6/uPAR/alpha-neurotoxin protein family. With this initial point the objective of this study was to determine a comparative composite based structure of CD59 of Chinese tree shrew. The additional objective of this study was to examine the distribution of negatively and positively charged amino acid over molecular modeled structure, distribution of secondary structural elements, hydrophobicity molecular surface analysis and electrostatic potential analysis with the assistance of several bioinformatical analytical tools. CD59 Amino acid sequence of Chinese tree shrew collected from the online database system of National Centre for Biotechnology Information. SignalP 4.0 online server was employed for detection of signal peptide instance within the protein sequence of CD59. Molecular model structure of CD59 protein was generated by the Iterative Threading ASSEmbly Refinement (I-TASSER) suite. The confirmation for three-dimensional structural model was evaluated by structure validation tools. Location of negatively and positively charged amino acid over molecular modeled structure, distribution of secondary structural elements, and hydrophobicity molecular surface analysis was performed with the help of Chimera tool. Electrostatic potential analysis was carried out with the adaptive Poisson-Boltzmann solver package. Subsequently validated model was used for the functionally critical amino acids and active site prediction. The functionally critical amino acids and ligand- binding site (LBS) of the proteins (modeled) was determined using the COACH program. Analysis of Ramachandran plot for Chinese tree shrew depicted that overall, 100% of the residues in homology model were observed in allowed and favored regions, sequentially leading to the validation of the standard of generated protein structural model. In case of CD59 of Chinese tree shrew, the total score of G-factor was found to be -0.66 that was generally larger than the acceptable value. This approach suggests the significance and acceptability of the modeled structure of CD59 of Chinese tree shrew. The molecular model data in cooperation to other relevant post model analysis data put forward molecular insight to protecting activity of CD59 protein molecule of Chinese tree shrew. In the present study, we have proposed the first molecular model structure of uncharted CD59 of Chinese tree shrew by significantly utilizing the comparative composite modeling approach. Therefore, the development of a structural model of the CD59 protein was carried out and analyzed further for deducing molecular enrichment technique. The collaborative effort of molecular model and other relevant data of post model analysis carry forward molecular understanding to protecting activity of CD59 functions towards better insight of features of this natural lead compound. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Modeling and control for vibration suppression of a flexible smart structure

NASA Technical Reports Server (NTRS)

Dosch, J.; Leo, D.; Inman, D.

1993-01-01

Theoretical and experimental results of the modeling and control of a flexible ribbed antenna are presented. The antenna consists of eight flexible ribs which constitutes a smart antenna in the sense that the actuator and sensors are an integral part of the structure. The antenna exhibits closely space and repeated modes, thus multi-input multi-output (MIMO) control is necessary for controllability and observability of the structure. The structure also exhibits mode localization phenomenon and contains post buckled members making an accurate finite element model of the structure difficult to obtain. An identified MIMO minimum order model of the antenna is synthesized from identified single-input single-output (SISO) transfer functions curve fit in the frequency domain. The identified model is used to design a positive position feedback (PPF) controller that increases damping in all of the modes in the targeted frequency range. Due to the accuracy of the open loop model of the antenna, the closed loop response predicted by the identified model correlates well wtih experimental results.

Identification of time-varying structural dynamic systems - An artificial intelligence approach

NASA Technical Reports Server (NTRS)

Glass, B. J.; Hanagud, S.

1992-01-01

An application of the artificial intelligence-derived methodologies of heuristic search and object-oriented programming to the problem of identifying the form of the model and the associated parameters of a time-varying structural dynamic system is presented in this paper. Possible model variations due to changes in boundary conditions or configurations of a structure are organized into a taxonomy of models, and a variant of best-first search is used to identify the model whose simulated response best matches that of the current physical structure. Simulated model responses are verified experimentally. An output-error approach is used in a discontinuous model space, and an equation-error approach is used in the parameter space. The advantages of the AI methods used, compared with conventional programming techniques for implementing knowledge structuring and inheritance, are discussed. Convergence conditions and example problems have been discussed. In the example problem, both the time-varying model and its new parameters have been identified when changes occur.

Uncertainty aggregation and reduction in structure-material performance prediction

NASA Astrophysics Data System (ADS)

Hu, Zhen; Mahadevan, Sankaran; Ao, Dan

2018-02-01

An uncertainty aggregation and reduction framework is presented for structure-material performance prediction. Different types of uncertainty sources, structural analysis model, and material performance prediction model are connected through a Bayesian network for systematic uncertainty aggregation analysis. To reduce the uncertainty in the computational structure-material performance prediction model, Bayesian updating using experimental observation data is investigated based on the Bayesian network. It is observed that the Bayesian updating results will have large error if the model cannot accurately represent the actual physics, and that this error will be propagated to the predicted performance distribution. To address this issue, this paper proposes a novel uncertainty reduction method by integrating Bayesian calibration with model validation adaptively. The observation domain of the quantity of interest is first discretized into multiple segments. An adaptive algorithm is then developed to perform model validation and Bayesian updating over these observation segments sequentially. Only information from observation segments where the model prediction is highly reliable is used for Bayesian updating; this is found to increase the effectiveness and efficiency of uncertainty reduction. A composite rotorcraft hub component fatigue life prediction model, which combines a finite element structural analysis model and a material damage model, is used to demonstrate the proposed method.

Search-based model identification of smart-structure damage

NASA Technical Reports Server (NTRS)

Glass, B. J.; Macalou, A.

1991-01-01

This paper describes the use of a combined model and parameter identification approach, based on modal analysis and artificial intelligence (AI) techniques, for identifying damage or flaws in a rotating truss structure incorporating embedded piezoceramic sensors. This smart structure example is representative of a class of structures commonly found in aerospace systems and next generation space structures. Artificial intelligence techniques of classification, heuristic search, and an object-oriented knowledge base are used in an AI-based model identification approach. A finite model space is classified into a search tree, over which a variant of best-first search is used to identify the model whose stored response most closely matches that of the input. Newly-encountered models can be incorporated into the model space. This adaptativeness demonstrates the potential for learning control. Following this output-error model identification, numerical parameter identification is used to further refine the identified model. Given the rotating truss example in this paper, noisy data corresponding to various damage configurations are input to both this approach and a conventional parameter identification method. The combination of the AI-based model identification with parameter identification is shown to lead to smaller parameter corrections than required by the use of parameter identification alone.

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.

PSpice Model of Lightning Strike to a Steel Reinforced Structure

NASA Astrophysics Data System (ADS)

Koone, Neil; Condren, Brian

2003-12-01

Surges and arcs from lightning can pose hazards to personnel and sensitive equipment, and processes. Steel reinforcement in structures can act as a Faraday cage mitigating lightning effects. Knowing a structure's response to a lightning strike allows hazards associated with lightning to be analyzed. A model of lightning's response in a steel reinforced structure has been developed using PSpice (a commercial circuit simulation). Segments of rebar are modeled as inductors and resistors in series. A program has been written to take architectural information of a steel reinforced structure and "build" a circuit network that is analogous to the network of reinforcement in a facility. A severe current waveform (simulating a 99th percentile lightning strike), modeled as a current source, is introduced in the circuit network, and potential differences within the structure are determined using PSpice. A visual three-dimensional model of the facility displays the voltage distribution across the structure using color to indicate the potential difference relative to the floor. Clear air arcing distances can be calculated from the voltage distribution using a conservative value for the dielectric breakdown strength of air. Potential validation tests for the model will be presented.

Visualization of Hyperconjugation and Subsequent Structural Distortions through 3D Printing of Crystal Structures.

PubMed

Mithila, Farha J; Oyola-Reynoso, Stephanie; Thuo, Martin M; Atkinson, Manza Bj

2016-01-01

Structural distortions due to hyperconjugation in organic molecules, like norbornenes, are well captured through X-ray crystallographic data, but are sometimes difficult to visualize especially for those applying chemical knowledge and are not chemists. Crystal structure from the Cambridge database were downloaded and converted to .stl format. The structures were then printed at the desired scale using a 3D printer. Replicas of the crystal structures were accurately reproduced in scale and any resulting distortions were clearly visible from the macroscale models. Through space interactions or effect of through space hyperconjugation was illustrated through loss of symmetry or distortions thereof. The norbornene structures exhibits distortion that cannot be observed through conventional ball and stick modelling kits. We show that 3D printed models derived from crystallographic data capture even subtle distortions in molecules. We translate such crystallographic data into scaled-up models through 3D printing.

Modelling of resonant MEMS magnetic field sensor with electromagnetic induction sensing

NASA Astrophysics Data System (ADS)

Liu, Song; Xu, Huaying; Xu, Dehui; Xiong, Bin

2017-06-01

This paper presents an analytical model of resonant MEMS magnetic field sensor with electromagnetic induction sensing. The resonant structure vibrates in square extensional (SE) mode. By analyzing the vibration amplitude and quality factor of the resonant structure, the magnetic field sensitivity as a function of device structure parameters and encapsulation pressure is established. The developed analytical model has been verified by comparing calculated results with experiment results and the deviation between them is only 10.25%, which shows the feasibility of the proposed device model. The model can provide theoretical guidance for further design optimization of the sensor. Moreover, a quantitative study of the magnetic field sensitivity is conducted with respect to the structure parameters and encapsulation pressure based on the proposed model.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

USING STRUCTURAL EQUATION MODELING TO INVESTIGATE RELATIONSHIPS AMONG ECOLOGICAL VARIABLES

EPA Science Inventory

This paper gives an introductory account of Structural Equation Modeling (SEM) and demonstrates its application using LISREL< with a model utilizing environmental data. Using nine EMAP data variables, we analyzed their correlation matrix with an SEM model. The model characterized...

An automated method for modeling proteins on known templates using distance geometry.

PubMed

Srinivasan, S; March, C J; Sudarsanam, S

1993-02-01

We present an automated method incorporated into a software package, FOLDER, to fold a protein sequence on a given three-dimensional (3D) template. Starting with the sequence alignment of a family of homologous proteins, tertiary structures are modeled using the known 3D structure of one member of the family as a template. Homologous interatomic distances from the template are used as constraints. For nonhomologous regions in the model protein, the lower and the upper bounds for the interatomic distances are imposed by steric constraints and the globular dimensions of the template, respectively. Distance geometry is used to embed an ensemble of structures consistent with these distance bounds. Structures are selected from this ensemble based on minimal distance error criteria, after a penalty function optimization step. These structures are then refined using energy optimization methods. The method is tested by simulating the alpha-chain of horse hemoglobin using the alpha-chain of human hemoglobin as the template and by comparing the generated models with the crystal structure of the alpha-chain of horse hemoglobin. We also test the packing efficiency of this method by reconstructing the atomic positions of the interior side chains beyond C beta atoms of a protein domain from a known 3D structure. In both test cases, models retain the template constraints and any additionally imposed constraints while the packing of the interior residues is optimized with no short contacts or bond deformations. To demonstrate the use of this method in simulating structures of proteins with nonhomologous disulfides, we construct a model of murine interleukin (IL)-4 using the NMR structure of human IL-4 as the template. The resulting geometry of the nonhomologous disulfide in the model structure for murine IL-4 is consistent with standard disulfide geometry.

Computer-based creativity enhanced conceptual design model for non-routine design of mechanical systems

NASA Astrophysics Data System (ADS)

Li, Yutong; Wang, Yuxin; Duffy, Alex H. B.

2014-11-01

Computer-based conceptual design for routine design has made great strides, yet non-routine design has not been given due attention, and it is still poorly automated. Considering that the function-behavior-structure(FBS) model is widely used for modeling the conceptual design process, a computer-based creativity enhanced conceptual design model(CECD) for non-routine design of mechanical systems is presented. In the model, the leaf functions in the FBS model are decomposed into and represented with fine-grain basic operation actions(BOA), and the corresponding BOA set in the function domain is then constructed. Choosing building blocks from the database, and expressing their multiple functions with BOAs, the BOA set in the structure domain is formed. Through rule-based dynamic partition of the BOA set in the function domain, many variants of regenerated functional schemes are generated. For enhancing the capability to introduce new design variables into the conceptual design process, and dig out more innovative physical structure schemes, the indirect function-structure matching strategy based on reconstructing the combined structure schemes is adopted. By adjusting the tightness of the partition rules and the granularity of the divided BOA subsets, and making full use of the main function and secondary functions of each basic structure in the process of reconstructing of the physical structures, new design variables and variants are introduced into the physical structure scheme reconstructing process, and a great number of simpler physical structure schemes to accomplish the overall function organically are figured out. The creativity enhanced conceptual design model presented has a dominant capability in introducing new deign variables in function domain and digging out simpler physical structures to accomplish the overall function, therefore it can be utilized to solve non-routine conceptual design problem.

Hidden multidimensional social structure modeling applied to biased social perception

NASA Astrophysics Data System (ADS)

Maletić, Slobodan; Zhao, Yi

2018-02-01

Intricacies of the structure of social relations are realized by representing a collection of overlapping opinions as a simplicial complex, thus building latent multidimensional structures, through which agents are, virtually, moving as they exchange opinions. The influence of opinion space structure on the distribution of opinions is demonstrated by modeling consensus phenomena when the opinion exchange between individuals may be affected by the false consensus effect. The results indicate that in the cases with and without bias, the road toward consensus is influenced by the structure of multidimensional space of opinions, and in the biased case, complete consensus is achieved. The applications of proposed modeling framework can easily be generalized, as they transcend opinion formation modeling.

Using Parameter Constraints to Choose State Structures in Cost-Effectiveness Modelling.

PubMed

Thom, Howard; Jackson, Chris; Welton, Nicky; Sharples, Linda

2017-09-01

This article addresses the choice of state structure in a cost-effectiveness multi-state model. Key model outputs, such as treatment recommendations and prioritisation of future research, may be sensitive to state structure choice. For example, it may be uncertain whether to consider similar disease severities or similar clinical events as the same state or as separate states. Standard statistical methods for comparing models require a common reference dataset but merging states in a model aggregates the data, rendering these methods invalid. We propose a method that involves re-expressing a model with merged states as a model on the larger state space in which particular transition probabilities, costs and utilities are constrained to be equal between states. This produces a model that gives identical estimates of cost effectiveness to the model with merged states, while leaving the data unchanged. The comparison of state structures can be achieved by comparing maximised likelihoods or information criteria between constrained and unconstrained models. We can thus test whether the costs and/or health consequences for a patient in two states are the same, and hence if the states can be merged. We note that different structures can be used for rates, costs and utilities, as appropriate. We illustrate our method with applications to two recent models evaluating the cost effectiveness of prescribing anti-depressant medications by depression severity and the cost effectiveness of diagnostic tests for coronary artery disease. State structures in cost-effectiveness models can be compared using standard methods to compare constrained and unconstrained models.

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.

Modelling Ni-mH battery using Cauer and Foster structures

NASA Astrophysics Data System (ADS)

Kuhn, E.; Forgez, C.; Lagonotte, P.; Friedrich, G.

This paper deals with dynamic models of Ni-mH battery and focuses on the development of the equivalent electric models. We propose two equivalent electric models, using Cauer and Foster structures, able to relate both dynamic and energetic behavior of the battery. These structures are well adapted to real time applications (e.g. Battery Management Systems) or system simulations. A special attention will be brought to the influence of the complexity of the equivalent electric scheme on the precision of the model. Experimental validations allow to discuss about performances of proposed models.

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

Three-Dimensional Molecular Modeling of a Diverse Range of SC Clan Serine Proteases

PubMed Central

Laskar, Aparna; Chatterjee, Aniruddha; Chatterjee, Somnath; Rodger, Euan J.

2012-01-01

Serine proteases are involved in a variety of biological processes and are classified into clans sharing structural homology. Although various three-dimensional structures of SC clan proteases have been experimentally determined, they are mostly bacterial and animal proteases, with some from archaea, plants, and fungi, and as yet no structures have been determined for protozoa. To bridge this gap, we have used molecular modeling techniques to investigate the structural properties of different SC clan serine proteases from a diverse range of taxa. Either SWISS-MODEL was used for homology-based structure prediction or the LOOPP server was used for threading-based structure prediction. The predicted models were refined using Insight II and SCRWL and validated against experimental structures. Investigation of secondary structures and electrostatic surface potential was performed using MOLMOL. The structural geometry of the catalytic core shows clear deviations between taxa, but the relative positions of the catalytic triad residues were conserved. Evolutionary divergence was also exhibited by large variation in secondary structure features outside the core, differences in overall amino acid distribution, and unique surface electrostatic potential patterns between species. Encompassing a wide range of taxa, our structural analysis provides an evolutionary perspective on SC clan serine proteases. PMID:23213528

Seven challenges for metapopulation models of epidemics, including households models.

PubMed

Ball, Frank; Britton, Tom; House, Thomas; Isham, Valerie; Mollison, Denis; Pellis, Lorenzo; Scalia Tomba, Gianpaolo

2015-03-01

This paper considers metapopulation models in the general sense, i.e. where the population is partitioned into sub-populations (groups, patches,...), irrespective of the biological interpretation they have, e.g. spatially segregated large sub-populations, small households or hosts themselves modelled as populations of pathogens. This framework has traditionally provided an attractive approach to incorporating more realistic contact structure into epidemic models, since it often preserves analytic tractability (in stochastic as well as deterministic models) but also captures the most salient structural inhomogeneity in contact patterns in many applied contexts. Despite the progress that has been made in both the theory and application of such metapopulation models, we present here several major challenges that remain for future work, focusing on models that, in contrast to agent-based ones, are amenable to mathematical analysis. The challenges range from clarifying the usefulness of systems of weakly-coupled large sub-populations in modelling the spread of specific diseases to developing a theory for endemic models with household structure. They include also developing inferential methods for data on the emerging phase of epidemics, extending metapopulation models to more complex forms of human social structure, developing metapopulation models to reflect spatial population structure, developing computationally efficient methods for calculating key epidemiological model quantities, and integrating within- and between-host dynamics in models. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Representing Heterogeneity in Structural Relationships Among Multiple Choice Variables Using a Latent Segmentation Approach

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

Garikapati, Venu; Astroza, Sebastian; Pendyala, Ram M.

Travel model systems often adopt a single decision structure that links several activity-travel choices together. The single decision structure is then used to predict activity-travel choices, with those downstream in the decision-making chain influenced by those upstream in the sequence. The adoption of a singular sequential causal structure to depict relationships among activity-travel choices in travel demand model systems ignores the possibility that some choices are made jointly as a bundle as well as the possible presence of structural heterogeneity in the population with respect to decision-making processes. As different segments in the population may adopt and follow different causalmore » decision-making mechanisms when making selected choices jointly, it would be of value to develop simultaneous equations model systems relating multiple endogenous choice variables that are able to identify population subgroups following alternative causal decision structures. Because the segments are not known a priori, they are considered latent and determined endogenously within a joint modeling framework proposed in this paper. The methodology is applied to a national mobility survey data set to identify population segments that follow different causal structures relating residential location choice, vehicle ownership, and car-share and mobility service usage. It is found that the model revealing three distinct latent segments best describes the data, confirming the efficacy of the modeling approach and the existence of structural heterogeneity in decision-making in the population. Future versions of activity-travel model systems should strive to incorporate such structural heterogeneity to better reflect varying decision processes across population subgroups.« less

An overview of multiphase cartilage mechanical modelling and its role in understanding function and pathology.

PubMed

Klika, Václav; Gaffney, Eamonn A; Chen, Ying-Chun; Brown, Cameron P

2016-09-01

There is a long history of mathematical and computational modelling with the objective of understanding the mechanisms governing cartilage׳s remarkable mechanical performance. Nonetheless, despite sophisticated modelling development, simulations of cartilage have consistently lagged behind structural knowledge and thus the relationship between structure and function in cartilage is not fully understood. However, in the most recent generation of studies, there is an emerging confluence between our structural knowledge and the structure represented in cartilage modelling. This raises the prospect of further refinement in our understanding of cartilage function and also the initiation of an engineering-level understanding for how structural degradation and ageing relates to cartilage dysfunction and pathology, as well as informing the potential design of prospective interventions. Aimed at researchers entering the field of cartilage modelling, we thus review the basic principles of cartilage models, discussing the underlying physics and assumptions in relatively simple settings, whilst presenting the derivation of relatively parsimonious multiphase cartilage models consistent with our discussions. We proceed to consider modern developments that start aligning the structure captured in the models with observed complexities. This emphasises the challenges associated with constitutive relations, boundary conditions, parameter estimation and validation in cartilage modelling programmes. Consequently, we further detail how both experimental interrogations and modelling developments can be utilised to investigate and reduce such difficulties before summarising how cartilage modelling initiatives may improve our understanding of cartilage ageing, pathology and intervention. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

A discourse on sensitivity analysis for discretely-modeled structures

NASA Technical Reports Server (NTRS)

Adelman, Howard M.; Haftka, Raphael T.

1991-01-01

A descriptive review is presented of the most recent methods for performing sensitivity analysis of the structural behavior of discretely-modeled systems. The methods are generally but not exclusively aimed at finite element modeled structures. Topics included are: selections of finite difference step sizes; special consideration for finite difference sensitivity of iteratively-solved response problems; first and second derivatives of static structural response; sensitivity of stresses; nonlinear static response sensitivity; eigenvalue and eigenvector sensitivities for both distinct and repeated eigenvalues; and sensitivity of transient response for both linear and nonlinear structural response.

Customizing G Protein-coupled receptor models for structure-based virtual screening.

PubMed

de Graaf, Chris; Rognan, Didier

2009-01-01

This review will focus on the construction, refinement, and validation of G Protein-coupled receptor models for the purpose of structure-based virtual screening. Practical tips and tricks derived from concrete modeling and virtual screening exercises to overcome the problems and pitfalls associated with the different steps of the receptor modeling workflow will be presented. These examples will not only include rhodopsin-like (class A), but also secretine-like (class B), and glutamate-like (class C) receptors. In addition, the review will present a careful comparative analysis of current crystal structures and their implication on homology modeling. The following themes will be discussed: i) the use of experimental anchors in guiding the modeling procedure; ii) amino acid sequence alignments; iii) ligand binding mode accommodation and binding cavity expansion; iv) proline-induced kinks in transmembrane helices; v) binding mode prediction and virtual screening by receptor-ligand interaction fingerprint scoring; vi) extracellular loop modeling; vii) virtual filtering schemes. Finally, an overview of several successful structure-based screening shows that receptor models, despite structural inaccuracies, can be efficiently used to find novel ligands.

Modeling protein structure at near atomic resolutions with Gorgon.

PubMed

Baker, Matthew L; Abeysinghe, Sasakthi S; Schuh, Stephen; Coleman, Ross A; Abrams, Austin; Marsh, Michael P; Hryc, Corey F; Ruths, Troy; Chiu, Wah; Ju, Tao

2011-05-01

Electron cryo-microscopy (cryo-EM) has played an increasingly important role in elucidating the structure and function of macromolecular assemblies in near native solution conditions. Typically, however, only non-atomic resolution reconstructions have been obtained for these large complexes, necessitating computational tools for integrating and extracting structural details. With recent advances in cryo-EM, maps at near-atomic resolutions have been achieved for several macromolecular assemblies from which models have been manually constructed. In this work, we describe a new interactive modeling toolkit called Gorgon targeted at intermediate to near-atomic resolution density maps (10-3.5 Å), particularly from cryo-EM. Gorgon's de novo modeling procedure couples sequence-based secondary structure prediction with feature detection and geometric modeling techniques to generate initial protein backbone models. Beyond model building, Gorgon is an extensible interactive visualization platform with a variety of computational tools for annotating a wide variety of 3D volumes. Examples from cryo-EM maps of Rotavirus and Rice Dwarf Virus are used to demonstrate its applicability to modeling protein structure. Copyright © 2011 Elsevier Inc. All rights reserved.

Seismic performance evaluation of RC frame-shear wall structures using nonlinear analysis methods

NASA Astrophysics Data System (ADS)

Shi, Jialiang; Wang, Qiuwei

To further understand the seismic performance of reinforced concrete (RC) frame-shear wall structures, a 1/8 model structure is scaled from a main factory structure with seven stories and seven bays. The model with four-stories and two-bays was pseudo-dynamically tested under six earthquake actions whose peak ground accelerations (PGA) vary from 50gal to 400gal. The damage process and failure patterns were investigated. Furthermore, nonlinear dynamic analysis (NDA) and capacity spectrum method (CSM) were adopted to evaluate the seismic behavior of the model structure. The top displacement curve, story drift curve and distribution of hinges were obtained and discussed. It is shown that the model structure had the characteristics of beam-hinge failure mechanism. The two methods can be used to evaluate the seismic behavior of RC frame-shear wall structures well. What’s more, the NDA can be somewhat replaced by CSM for the seismic performance evaluation of RC structures.

Finite element structural model of a large, thin, completely free, flat plate. [for large space structures

NASA Technical Reports Server (NTRS)

Joshi, S. M.; Groom, N. J.

1980-01-01

A finite element structural model of a 30.48 m x 30.48 m x 2.54 mm completely free aluminum plate is described and modal frequencies and mode shape data for the first 44 modes are presented. An explanation of the procedure for using the data is also presented. The model should prove useful for the investigation of controller design approaches for large flexible space structures.

A new model for approximating RNA folding trajectories and population kinetics

NASA Astrophysics Data System (ADS)

Kirkpatrick, Bonnie; Hajiaghayi, Monir; Condon, Anne

2013-01-01

RNA participates both in functional aspects of the cell and in gene regulation. The interactions of these molecules are mediated by their secondary structure which can be viewed as a planar circle graph with arcs for all the chemical bonds between pairs of bases in the RNA sequence. The problem of predicting RNA secondary structure, specifically the chemically most probable structure, has many useful and efficient algorithms. This leaves RNA folding, the problem of predicting the dynamic behavior of RNA structure over time, as the main open problem. RNA folding is important for functional understanding because some RNA molecules change secondary structure in response to interactions with the environment. The full RNA folding model on at most O(3n) secondary structures is the gold standard. We present a new subset approximation model for the full model, give methods to analyze its accuracy and discuss the relative merits of our model as compared with a pre-existing subset approximation. The main advantage of our model is that it generates Monte Carlo folding pathways with the same probabilities with which they are generated under the full model. The pre-existing subset approximation does not have this property.

Finite Element Model Development and Validation for Aircraft Fuselage Structures

NASA Technical Reports Server (NTRS)

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

2000-01-01

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

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

PubMed

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

2011-06-01

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

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

PubMed Central

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

2011-01-01

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

The inverse niche model for food webs with parasites

USGS Publications Warehouse

Warren, Christopher P.; Pascual, Mercedes; Lafferty, Kevin D.; Kuris, Armand M.

2010-01-01

Although parasites represent an important component of ecosystems, few field and theoretical studies have addressed the structure of parasites in food webs. We evaluate the structure of parasitic links in an extensive salt marsh food web, with a new model distinguishing parasitic links from non-parasitic links among free-living species. The proposed model is an extension of the niche model for food web structure, motivated by the potential role of size (and related metabolic rates) in structuring food webs. The proposed extension captures several properties observed in the data, including patterns of clustering and nestedness, better than does a random model. By relaxing specific assumptions, we demonstrate that two essential elements of the proposed model are the similarity of a parasite's hosts and the increasing degree of parasite specialization, along a one-dimensional niche axis. Thus, inverting one of the basic rules of the original model, the one determining consumers' generality appears critical. Our results support the role of size as one of the organizing principles underlying niche space and food web topology. They also strengthen the evidence for the non-random structure of parasitic links in food webs and open the door to addressing questions concerning the consequences and origins of this structure.

A Hierarchical Multi-Model Approach for Uncertainty Segregation, Prioritization and Comparative Evaluation of Competing Modeling Propositions

NASA Astrophysics Data System (ADS)

Tsai, F. T.; Elshall, A. S.; Hanor, J. S.

2012-12-01

Subsurface modeling is challenging because of many possible competing propositions for each uncertain model component. How can we judge that we are selecting the correct proposition for an uncertain model component out of numerous competing propositions? How can we bridge the gap between synthetic mental principles such as mathematical expressions on one hand, and empirical observation such as observation data on the other hand when uncertainty exists on both sides? In this study, we introduce hierarchical Bayesian model averaging (HBMA) as a multi-model (multi-proposition) framework to represent our current state of knowledge and decision for hydrogeological structure modeling. The HBMA framework allows for segregating and prioritizing different sources of uncertainty, and for comparative evaluation of competing propositions for each source of uncertainty. We applied the HBMA to a study of hydrostratigraphy and uncertainty propagation of the Southern Hills aquifer system in the Baton Rouge area, Louisiana. We used geophysical data for hydrogeological structure construction through indictor hydrostratigraphy method and used lithologic data from drillers' logs for model structure calibration. However, due to uncertainty in model data, structure and parameters, multiple possible hydrostratigraphic models were produced and calibrated. The study considered four sources of uncertainties. To evaluate mathematical structure uncertainty, the study considered three different variogram models and two geological stationarity assumptions. With respect to geological structure uncertainty, the study considered two geological structures with respect to the Denham Springs-Scotlandville fault. With respect to data uncertainty, the study considered two calibration data sets. These four sources of uncertainty with their corresponding competing modeling propositions resulted in 24 calibrated models. The results showed that by segregating different sources of uncertainty, HBMA analysis provided insights on uncertainty priorities and propagation. In addition, it assisted in evaluating the relative importance of competing modeling propositions for each uncertain model component. By being able to dissect the uncertain model components and provide weighted representation of the competing propositions for each uncertain model component based on the background knowledge, the HBMA functions as an epistemic framework for advancing knowledge about the system under study.

Maximum Likelihood Analysis of Nonlinear Structural Equation Models with Dichotomous Variables

ERIC Educational Resources Information Center

Song, Xin-Yuan; Lee, Sik-Yum

2005-01-01

In this article, a maximum likelihood approach is developed to analyze structural equation models with dichotomous variables that are common in behavioral, psychological and social research. To assess nonlinear causal effects among the latent variables, the structural equation in the model is defined by a nonlinear function. The basic idea of the…

Can Heterosexism Harm Organizations? Predicting the Perceived Organizational Citizenship Behaviors of Gay and Lesbian Employees

ERIC Educational Resources Information Center

Brenner, Bradley R.; Lyons, Heather Z.; Fassinger, Ruth E.

2010-01-01

An initial test and validation of a model predicting perceived organizational citizenship behaviors (OCBs) of lesbian and gay employees were conducted using structural equation modeling. The proposed structural model demonstrated acceptable goodness of ft and structural invariance across 2 samples (ns = 311 and 295), which suggested that…

The Urban Forest Effects (UFORE) model: quantifying urban forest structure and functions

Treesearch

David J. Nowak; Daniel E. Crane

2000-01-01

The Urban Forest Effects (UFORE) computer model was developed to help managers and researchers quantify urban forest structure and functions. The model quantifies species composition and diversity, diameter distribution, tree density and health, leaf area, leaf biomass, and other structural characteristics; hourly volatile organic compound emissions (emissions that...

A Structural Equation Modeling Analysis of Influences on Juvenile Delinquency

ERIC Educational Resources Information Center

Barrett, David E.; Katsiyannis, Antonis; Zhang, Dalun; Zhang, Dake

2014-01-01

This study examined influences on delinquency and recidivism using structural equation modeling. The sample comprised 199,204 individuals: 99,602 youth whose cases had been processed by the South Carolina Department of Juvenile Justice and a matched control group of 99,602 youth without juvenile records. Structural equation modeling for the…

Are Structural Estimates of Auction Models Reasonable? Evidence from Experimental Data

ERIC Educational Resources Information Center

Bajari, Patrick; Hortacsu, Ali

2005-01-01

Recently, economists have developed methods for structural estimation of auction models. Many researchers object to these methods because they find the strict rationality assumptions to be implausible. Using bid data from first-price auction experiments, we estimate four alternative structural models: (1) risk-neutral Bayes-Nash, (2) risk-averse…

Testing the Structure of Hydrological Models using Genetic Programming

NASA Astrophysics Data System (ADS)

Selle, B.; Muttil, N.

2009-04-01

Genetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that genetic programming can be used to test the structure hydrological models and to identify dominant processes in hydrological systems. To test this, genetic programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, water table depths and water ponding times during surface irrigation. Using genetic programming, a simple model of deep percolation was consistently evolved in multiple model runs. This simple and interpretable model confirmed the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that genetic programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.

Research and development of a digital design system for hull structures

NASA Astrophysics Data System (ADS)

Zhan, Yi-Ting; Ji, Zhuo-Shang; Liu, Yin-Dong

2007-06-01

Methods used for digital ship design were studied and formed the basis of a proposed frame model suitable for ship construction modeling. Based on 3-D modeling software, a digital design system for hull structures was developed. Basic software systems for modeling, modifying, and assembly simulation were developed. The system has good compatibility, and models created by it can be saved in different 3-D file formats, and 2D engineering drawings can be output directly. The model can be modified dynamically, overcoming the necessity of repeated modifications during hull structural design. Through operations such as model construction, intervention inspection, and collision detection, problems can be identified and modified during the hull structural design stage. Technologies for centralized control of the system, database management, and 3-D digital design are integrated into this digital model in the preliminary design stage of shipbuilding.

Curved Thermopiezoelectric Shell Structures Modeled by Finite Element Analysis

NASA Technical Reports Server (NTRS)

Lee, Ho-Jun

2000-01-01

"Smart" structures composed of piezoelectric materials may significantly improve the performance of aeropropulsion systems through a variety of vibration, noise, and shape-control applications. The development of analytical models for piezoelectric smart structures is an ongoing, in-house activity at the NASA Glenn Research Center at Lewis Field focused toward the experimental characterization of these materials. Research efforts have been directed toward developing analytical models that account for the coupled mechanical, electrical, and thermal response of piezoelectric composite materials. Current work revolves around implementing thermal effects into a curvilinear-shell finite element code. This enhances capabilities to analyze curved structures and to account for coupling effects arising from thermal effects and the curved geometry. The current analytical model implements a unique mixed multi-field laminate theory to improve computational efficiency without sacrificing accuracy. The mechanics can model both the sensory and active behavior of piezoelectric composite shell structures. Finite element equations are being implemented for an eight-node curvilinear shell element, and numerical studies are being conducted to demonstrate capabilities to model the response of curved piezoelectric composite structures (see the figure).

Structural models for the design of novel antiviral agents against Greek Goat Encephalitis

PubMed Central

Papageorgiou, Louis; Loukatou, Styliani; Koumandou, Vassiliki Lila; Makałowski, Wojciech; Megalooikonomou, Vasileios

2014-01-01

The Greek Goat Encephalitis virus (GGE) belongs to the Flaviviridae family of the genus Flavivirus. The GGE virus constitutes an important pathogen of livestock that infects the goat’s central nervous system. The viral enzymes of GGE, helicase and RNA-dependent RNA polymerase (RdRP), are ideal targets for inhibitor design, since those enzymes are crucial for the virus’ survival, proliferation and transmission. In an effort to understand the molecular structure underlying the functions of those viral enzymes, the three dimensional structures of GGE NS3 helicase and NS5 RdRP have been modelled. The models were constructed in silico using conventional homology modelling techniques and the known 3D crystal structures of solved proteins from closely related species as templates. The established structural models of the GGE NS3 helicase and NS5 RdRP have been evaluated for their viability using a repertoire of in silico tools. The goal of this study is to present the 3D conformations of the GGE viral enzymes as reliable structural models that could provide the platform for the design of novel anti-GGE agents. PMID:25392762

Track structure model of cell damage in space flight

NASA Technical Reports Server (NTRS)

Katz, Robert; Cucinotta, Francis A.; Wilson, John W.; Shinn, Judy L.; Ngo, Duc M.

1992-01-01

The phenomenological track-structure model of cell damage is discussed. A description of the application of the track-structure model with the NASA Langley transport code for laboratory and space radiation is given. Comparisons to experimental results for cell survival during exposure to monoenergetic, heavy-ion beams are made. The model is also applied to predict cell damage rates and relative biological effectiveness for deep-space exposures.

Application of a baseflow filter for evaluating model structure suitability of the IHACRES CMD

NASA Astrophysics Data System (ADS)

Kim, H. S.

2015-02-01

The main objective of this study was to assess the predictive uncertainty from the rainfall-runoff model structure coupling a conceptual module (non-linear module) with a metric transfer function module (linear module). The methodology was primarily based on the comparison between the outputs of the rainfall-runoff model and those from an alternative model approach. An alternative model approach was used to minimise uncertainties arising from data and the model structure. A baseflow filter was adopted to better understand deficiencies in the forms of the rainfall-runoff model by avoiding the uncertainties related to data and the model structure. The predictive uncertainty from the model structure was investigated for representative groups of catchments having similar hydrological response characteristics in the upper Murrumbidgee Catchment. In the assessment of model structure suitability, the consistency (or variability) of catchment response over time and space in model performance and parameter values has been investigated to detect problems related to the temporal and spatial variability of the model accuracy. The predictive error caused by model uncertainty was evaluated through analysis of the variability of the model performance and parameters. A graphical comparison of model residuals, effective rainfall estimates and hydrographs was used to determine a model's ability related to systematic model deviation between simulated and observed behaviours and general behavioural differences in the timing and magnitude of peak flows. The model's predictability was very sensitive to catchment response characteristics. The linear module performs reasonably well in the wetter catchments but has considerable difficulties when applied to the drier catchments where a hydrologic response is dominated by quick flow. The non-linear module has a potential limitation in its capacity to capture non-linear processes for converting observed rainfall into effective rainfall in both the wetter and drier catchments. The comparative study based on a better quantification of the accuracy and precision of hydrological modelling predictions yields a better understanding for the potential improvement of model deficiencies.

Cognitive Diagnostic Analysis Using Hierarchically Structured Skills

ERIC Educational Resources Information Center

Su, Yu-Lan

2013-01-01

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

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.

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.

Model of lightning strike to a steel reinforce structure using PSpice

NASA Astrophysics Data System (ADS)

Koone, Neil; Condren, Brian

2003-03-01

Surges and arcs from lightning can pose hazards to personnel and sensitive equipment and processes. Steel reinforcement in structures can act as a Faraday cage mitigating lightning effects. Knowing a structure's response to a lightning strike allows hazards associated with lightning to be analyzed. A model of lightning's response in a steel reinforced structure has been developed using PSpice (a commercial circuit simulation). Segments of rebar are modeled as inductors and resistors in series. A program has been written to take architectural information of a steel reinforced structure and "build" a circuit network that is analogous to the network of reinforcement in a facility. A severe current waveform (simulating a 99th percentile lightning strike), modeled as a current source, is introduced in the circuit network, and potential differences within the structure are determined using PSpice. A visual three-dimensional model of the facility displays the voltage distribution across the structure using color to indicate the potential difference relative to the floor. Clear air arcing distances can be calculated from the voltage distribution using a conservative value for the dielectric breakdown strength of air.

Nonlinear Analysis and Scaling Laws for Noncircular Composite Structures Subjected to Combined Loads

NASA Technical Reports Server (NTRS)

Hilburger, Mark W.; Rose, Cheryl A.; Starnes, James H., Jr.

2001-01-01

Results from an analytical study of the response of a built-up, multi-cell noncircular composite structure subjected to combined internal pressure and mechanical loads are presented. Nondimensional parameters and scaling laws based on a first-order shear-deformation plate theory are derived for this noncircular composite structure. The scaling laws are used to design sub-scale structural models for predicting the structural response of a full-scale structure representative of a portion of a blended-wing-body transport aircraft. Because of the complexity of the full-scale structure, some of the similitude conditions are relaxed for the sub-scale structural models. Results from a systematic parametric study are used to determine the effects of relaxing selected similitude conditions on the sensitivity of the effectiveness of using the sub-scale structural model response characteristics for predicting the full-scale structure response characteristics.

Covering complete proteomes with X-ray structures: A current snapshot

DOE PAGES

Mizianty, Marcin J.; Fan, Xiao; Yan, Jing; ...

2014-10-23

Structural genomics programs have developed and applied structure-determination pipelines to a wide range of protein targets, facilitating the visualization of macromolecular interactions and the understanding of their molecular and biochemical functions. The fundamental question of whether three-dimensional structures of all proteins and all functional annotations can be determined using X-ray crystallography is investigated. A first-of-its-kind large-scale analysis of crystallization propensity for all proteins encoded in 1953 fully sequenced genomes was performed. It is shown that current X-ray crystallographic knowhow combined with homology modeling can provide structures for 25% of modeling families (protein clusters for which structural models can be obtainedmore » through homology modeling), with at least one structural model produced for each Gene Ontology functional annotation. The coverage varies between superkingdoms, with 19% for eukaryotes, 35% for bacteria and 49% for archaea, and with those of viruses following the coverage values of their hosts. It is shown that the crystallization propensities of proteomes from the taxonomic superkingdoms are distinct. The use of knowledge-based target selection is shown to substantially increase the ability to produce X-ray structures. It is demonstrated that the human proteome has one of the highest attainable coverage values among eukaryotes, and GPCR membrane proteins suitable for X-ray structure determination were determined.« less

Adjustable internal structure for reconstructing gradient index profile of crystalline lens.

PubMed

Bahrami, Mehdi; Goncharov, Alexander V; Pierscionek, Barbara K

2014-03-01

Employing advanced technologies in studying the crystalline lens of the eye has improved our understanding of the refractive index gradient of the lens. Reconstructing and studying such a complex structure requires models with adaptable internal geometry that can be altered to simulate geometrical and optical changes of the lens with aging. In this Letter, we introduce an optically well-defined, geometrical structure for modeling the gradient refractive index profile of the crystalline lens with the advantage of an adjustable internal structure that is not available with existing models. The refractive index profile assigned to this rotationally symmetric geometry is calculated numerically, yet it is shown that this does not limit the model. The study provides a basis for developing lens models with sophisticated external and internal structures without the need for analytical solutions to calculate refractive index profiles.

Structure and dynamics of complex liquid water: Molecular dynamics simulation

NASA Astrophysics Data System (ADS)

S, Indrajith V.; Natesan, Baskaran

2015-06-01

We have carried out detailed structure and dynamical studies of complex liquid water using molecular dynamics simulations. Three different model potentials, namely, TIP3P, TIP4P and SPC-E have been used in the simulations, in order to arrive at the best possible potential function that could reproduce the structure of experimental bulk water. All the simulations were performed in the NVE micro canonical ensemble using LAMMPS. The radial distribution functions, gOO, gOH and gHH and the self diffusion coefficient, Ds, were calculated for all three models. We conclude from our results that the structure and dynamical parameters obtained for SPC-E model matched well with the experimental values, suggesting that among the models studied here, the SPC-E model gives the best structure and dynamics of bulk water.

Supramolecular structure of methyl cellulose and lambda- and kappa-carrageenan in water: SAXS study using the string-of-beads model.

PubMed

Dogsa, Iztok; Cerar, Jure; Jamnik, Andrej; Tomšič, Matija

2017-09-15

A detailed data analysis utilizing the string-of-beads model was performed on experimental small-angle X-ray scattering (SAXS) curves in a targeted structural study of three, very important, industrial polysaccharides. The results demonstrate the quality of performance for this model on three polymers with quite different thermal structural behavior. Furthermore, they show the advantages of the model used by way of excellent fits in the ranges where the classic approach to the small-angle scattering data interpretation fails and an additional 3D visualization of the model's molecular conformations and anticipated polysaccharide supramolecular structure. The importance of this study is twofold: firstly, the methodology used and, secondly, the structural details of important biopolymers that are widely applicable in practice. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Park, Eun Jung

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

Definition of ground test for verification of large space structure control

NASA Technical Reports Server (NTRS)

Seltzer, S. M.; Doane, G. B., III

1985-01-01

Directions regarding the analytical models were received. A counter balance arm with weights was added at the top of the ASTROMAST to offset the arm with the gimbals. In addition to this model, three more models were requested from MSFC: structure as in the revised model with the addition of lumped masses at bays 46 and 91 of the ASTROMAST; cantilevered cruciform structure with lumped masses at bays 46 and 91, and an all up cruciform structure with lumped masses at bays 46 and 91. Figures for each model and their corresponding natural frequencies and general mode shapes associated with these frequencies are included. The drawbar in use in the cruciform models must be incorporated into the antenna and ASTROMAST models. The total tensile load carrying capability of the ASTROMAST is approximately 840 pounds.

3D WHOLE-PROMINENCE FINE STRUCTURE MODELING

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

Gunár, Stanislav; Mackay, Duncan H.

2015-04-20

We present the first 3D whole-prominence fine structure model. The model combines a 3D magnetic field configuration of an entire prominence obtained from nonlinear force-free field simulations, with a detailed description of the prominence plasma. The plasma is located in magnetic dips in hydrostatic equilibrium and is distributed along multiple fine structures within the 3D magnetic model. Through the use of a novel radiative transfer visualization technique for the Hα line such plasma-loaded magnetic field model produces synthetic images of the modeled prominence comparable with high-resolution observations. This allows us for the first time to use a single technique tomore » consistently study, in both emission on the limb and absorption against the solar disk, the fine structures of prominences/filaments produced by a magnetic field model.« less

Processing Speed in Children: Examination of the Structure in Middle Childhood and Its Impact on Reading

ERIC Educational Resources Information Center

Gerst, Elyssa H.

2017-01-01

The primary aim of this study was to examine the structure of processing speed (PS) in middle childhood by comparing five theoretically driven models of PS. The models consisted of two conceptual models (a unitary model, a complexity model) and three methodological models (a stimulus material model, an output modality model, and a timing modality…

A Template-Based Protein Structure Reconstruction Method Using Deep Autoencoder Learning.

PubMed

Li, Haiou; Lyu, Qiang; Cheng, Jianlin

2016-12-01

Protein structure prediction is an important problem in computational biology, and is widely applied to various biomedical problems such as protein function study, protein design, and drug design. In this work, we developed a novel deep learning approach based on a deeply stacked denoising autoencoder for protein structure reconstruction. We applied our approach to a template-based protein structure prediction using only the 3D structural coordinates of homologous template proteins as input. The templates were identified for a target protein by a PSI-BLAST search. 3DRobot (a program that automatically generates diverse and well-packed protein structure decoys) was used to generate initial decoy models for the target from the templates. A stacked denoising autoencoder was trained on the decoys to obtain a deep learning model for the target protein. The trained deep model was then used to reconstruct the final structural model for the target sequence. With target proteins that have highly similar template proteins as benchmarks, the GDT-TS score of the predicted structures is greater than 0.7, suggesting that the deep autoencoder is a promising method for protein structure reconstruction.

Analytical investigation of a three-dimensional FRP-retrofitted reinforced concrete structure's behaviour under earthquake load effect in ANSYS program

NASA Astrophysics Data System (ADS)

Altun, F.; Birdal, F.

2012-12-01

In this study, a 1:3 scaled, three-storey, FRP (Fiber Reinforced Polymer) retrofitted reinforced concrete model structure whose behaviour and crack development were identified experimentally in the laboratory was investigated analytically. Determination of structural behaviour under earthquake load is only possible in a laboratory environment with a specific scale, as carrying out structural experiments is difficult due to the evaluation of increased parameter numbers and because it requires an expensive laboratory setup. In an analytical study, structure was modelled using ANSYS Finite Element Package Program (2007), and its behaviour and crack development were revealed. When experimental difficulties are taken into consideration, analytical investigation of structure behaviour is more economic and much faster. At the end of the study, experimental results of structural behaviour and crack development were compared with analytical data. It was concluded that in a model structure retrofitted with FRP, the behaviour and cracking model can be determined without testing by determining the reasons for the points where analytical results are not converged with experimental data. Better understanding of structural behaviour is analytically enabled with the study.

RCK: accurate and efficient inference of sequence- and structure-based protein-RNA binding models from RNAcompete data.

PubMed

Orenstein, Yaron; Wang, Yuhao; Berger, Bonnie

2016-06-15

Protein-RNA interactions, which play vital roles in many processes, are mediated through both RNA sequence and structure. CLIP-based methods, which measure protein-RNA binding in vivo, suffer from experimental noise and systematic biases, whereas in vitro experiments capture a clearer signal of protein RNA-binding. Among them, RNAcompete provides binding affinities of a specific protein to more than 240 000 unstructured RNA probes in one experiment. The computational challenge is to infer RNA structure- and sequence-based binding models from these data. The state-of-the-art in sequence models, Deepbind, does not model structural preferences. RNAcontext models both sequence and structure preferences, but is outperformed by GraphProt. Unfortunately, GraphProt cannot detect structural preferences from RNAcompete data due to the unstructured nature of the data, as noted by its developers, nor can it be tractably run on the full RNACompete dataset. We develop RCK, an efficient, scalable algorithm that infers both sequence and structure preferences based on a new k-mer based model. Remarkably, even though RNAcompete data is designed to be unstructured, RCK can still learn structural preferences from it. RCK significantly outperforms both RNAcontext and Deepbind in in vitro binding prediction for 244 RNAcompete experiments. Moreover, RCK is also faster and uses less memory, which enables scalability. While currently on par with existing methods in in vivo binding prediction on a small scale test, we demonstrate that RCK will increasingly benefit from experimentally measured RNA structure profiles as compared to computationally predicted ones. By running RCK on the entire RNAcompete dataset, we generate and provide as a resource a set of protein-RNA structure-based models on an unprecedented scale. Software and models are freely available at http://rck.csail.mit.edu/ bab@mit.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

The demographic consequences of growing older and bigger in oyster populations.

PubMed

Moore, Jacob L; Lipcius, Romuald N; Puckett, Brandon; Schreiber, Sebastian J

2016-10-01

Structured population models, particularly size- or age-structured, have a long history of informing conservation and natural resource management. While size is often easier to measure than age and is the focus of many management strategies, age-structure can have important effects on population dynamics that are not captured in size-only models. However, relatively few studies have included the simultaneous effects of both age- and size-structure. To better understand how population structure, particularly that of age and size, impacts restoration and management decisions, we developed and compared a size-structured integral projection model (IPM) and an age- and size-structured IPM, using a population of Crassostrea gigas oysters in the northeastern Pacific Ocean. We analyzed sensitivity of model results across values of local retention that give populations decreasing in size to populations increasing in size. We found that age- and size-structured models yielded the best fit to the demographic data and provided more reliable results about long-term demography. Elasticity analysis showed that population growth rate was most sensitive to changes in the survival of both large (>175 mm shell length) and small (<75 mm shell length) oysters, indicating that a maximum size limit, in addition to a minimum size limit, could be an effective strategy for maintaining a sustainable population. In contrast, the purely size-structured model did not detect the importance of large individuals. Finally, patterns in stable age and stable size distributions differed between populations decreasing in size due to limited local retention and populations increasing in size due to high local retention. These patterns can be used to determine population status and restoration success. The methodology described here provides general insight into the necessity of including both age- and size-structure into modeling frameworks when using population models to inform restoration and management decisions. © 2016 by the Ecological Society of America.

Assessing the skill of hydrology models at simulating the water cycle in the HJ Andrews LTER: Assumptions, strengths and weaknesses

EPA Science Inventory

Simulated impacts of climate on hydrology can vary greatly as a function of the scale of the input data, model assumptions, and model structure. Four models are commonly used to simulate streamflow in model assumptions, and model structure. Four models are commonly used to simu...

Structural Equation Modeling of Multivariate Time Series

ERIC Educational Resources Information Center

du Toit, Stephen H. C.; Browne, Michael W.

2007-01-01

The covariance structure of a vector autoregressive process with moving average residuals (VARMA) is derived. It differs from other available expressions for the covariance function of a stationary VARMA process and is compatible with current structural equation methodology. Structural equation modeling programs, such as LISREL, may therefore be…

Ensemble modelling and structured decision-making to support Emergency Disease Management.

PubMed

Webb, Colleen T; Ferrari, Matthew; Lindström, Tom; Carpenter, Tim; Dürr, Salome; Garner, Graeme; Jewell, Chris; Stevenson, Mark; Ward, Michael P; Werkman, Marleen; Backer, Jantien; Tildesley, Michael

2017-03-01

Epidemiological models in animal health are commonly used as decision-support tools to understand the impact of various control actions on infection spread in susceptible populations. Different models contain different assumptions and parameterizations, and policy decisions might be improved by considering outputs from multiple models. However, a transparent decision-support framework to integrate outputs from multiple models is nascent in epidemiology. Ensemble modelling and structured decision-making integrate the outputs of multiple models, compare policy actions and support policy decision-making. We briefly review the epidemiological application of ensemble modelling and structured decision-making and illustrate the potential of these methods using foot and mouth disease (FMD) models. In case study one, we apply structured decision-making to compare five possible control actions across three FMD models and show which control actions and outbreak costs are robustly supported and which are impacted by model uncertainty. In case study two, we develop a methodology for weighting the outputs of different models and show how different weighting schemes may impact the choice of control action. Using these case studies, we broadly illustrate the potential of ensemble modelling and structured decision-making in epidemiology to provide better information for decision-making and outline necessary development of these methods for their further application. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Kaloyanova, Valentina B.

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

Flight dynamics simulation modeling and control of a large flexible tiltrotor aircraft

NASA Astrophysics Data System (ADS)

Juhasz, Ondrej

A high order rotorcraft mathematical model is developed and validated against the XV-15 and a Large Civil Tiltrotor (LCTR) concept. The mathematical model is generic and allows for any rotorcraft configuration, from single main rotor helicopters to coaxial and tiltrotor aircraft. Rigid-body and inflow states, as well as flexible wing and blade states are used in the analysis. The separate modeling of each rotorcraft component allows for structural flexibility to be included, which is important when modeling large aircraft where structural modes affect the flight dynamics frequency ranges of interest, generally 1 to 20 rad/sec. Details of the formulation of the mathematical model are given, including derivations of structural, aerodynamic, and inertial loads. The linking of the components of the aircraft is developed using an approach similar to multibody analyses by exploiting a tree topology, but without equations of constraints. Assessments of the effects of wing flexibility are given. Flexibility effects are evaluated by looking at the nature of the couplings between rigid-body modes and wing structural modes and vice versa. The effects of various different forms of structural feedback on aircraft dynamics are analyzed. A proportional-integral feedback on the structural acceleration is deemed to be most effective at both improving the damping and reducing the overall excitation of a structural mode. A model following control architecture is then implemented on full order flexible LCTR models. For this aircraft, the four lowest frequency structural modes are below 20 rad/sec, and are thus needed for control law development and analysis. The impact of structural feedback on both Attitude-Command, Attitude-Hold (ACAH) and Translational Rate Command (TRC) response types are investigated. A rigid aircraft model has optimistic performance characteristics, and a control system designed for a rigid aircraft could potentially destabilize a flexible one. The various control systems are flown in a fixed-base simulator. Pilot inputs and aircraft performance are recorded and analyzed.

Bi-objective integer programming for RNA secondary structure prediction with pseudoknots.

PubMed

Legendre, Audrey; Angel, Eric; Tahi, Fariza

2018-01-15

RNA structure prediction is an important field in bioinformatics, and numerous methods and tools have been proposed. Pseudoknots are specific motifs of RNA secondary structures that are difficult to predict. Almost all existing methods are based on a single model and return one solution, often missing the real structure. An alternative approach would be to combine different models and return a (small) set of solutions, maximizing its quality and diversity in order to increase the probability that it contains the real structure. We propose here an original method for predicting RNA secondary structures with pseudoknots, based on integer programming. We developed a generic bi-objective integer programming algorithm allowing to return optimal and sub-optimal solutions optimizing simultaneously two models. This algorithm was then applied to the combination of two known models of RNA secondary structure prediction, namely MEA and MFE. The resulting tool, called BiokoP, is compared with the other methods in the literature. The results show that the best solution (structure with the highest F 1 -score) is, in most cases, given by BiokoP. Moreover, the results of BiokoP are homogeneous, regardless of the pseudoknot type or the presence or not of pseudoknots. Indeed, the F 1 -scores are always higher than 70% for any number of solutions returned. The results obtained by BiokoP show that combining the MEA and the MFE models, as well as returning several optimal and several sub-optimal solutions, allow to improve the prediction of secondary structures. One perspective of our work is to combine better mono-criterion models, in particular to combine a model based on the comparative approach with the MEA and the MFE models. This leads to develop in the future a new multi-objective algorithm to combine more than two models. BiokoP is available on the EvryRNA platform: https://EvryRNA.ibisc.univ-evry.fr .

Exploring the measurement structure of the Gambling Related Cognitions Scale (GRCS) in treatment-seekers: A Bayesian structural equation modelling approach.

PubMed

Smith, David; Woodman, Richard; Drummond, Aaron; Battersby, Malcolm

2016-03-30

Knowledge of a problem gambler's underlying gambling related cognitions plays an important role in treatment planning. The Gambling Related Cognitions Scale (GRCS) is therefore frequently used in clinical settings for screening and evaluation of treatment outcomes. However, GRCS validation studies have generated conflicting results regarding its latent structure using traditional confirmatory factor analyses (CFA). This may partly be due to the rigid constraints imposed on cross-factor loadings with traditional CFA. The aim of this investigation was to determine whether a Bayesian structural equation modelling (BSEM) approach to examination of the GRCS factor structure would better replicate substantive theory and also inform model re-specifications. Participants were 454 treatment-seekers at first presentation to a gambling treatment centre between January 2012 and December 2014. Model fit indices were well below acceptable standards for CFA. In contrast, the BSEM model which included small informative priors for the residual covariance matrix in addition to cross-loadings produced excellent model fit for the original hypothesised factor structure. The results also informed re-specification of the CFA model which provided more reasonable model fit. These conclusions have implications that should be useful to both clinicians and researchers evaluating measurement models relating to gambling related cognitions in treatment-seekers. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Likelihood analysis of spatial capture-recapture models for stratified or class structured populations

USGS Publications Warehouse

Royle, J. Andrew; Sutherland, Christopher S.; Fuller, Angela K.; Sun, Catherine C.

2015-01-01

We develop a likelihood analysis framework for fitting spatial capture-recapture (SCR) models to data collected on class structured or stratified populations. Our interest is motivated by the necessity of accommodating the problem of missing observations of individual class membership. This is particularly problematic in SCR data arising from DNA analysis of scat, hair or other material, which frequently yields individual identity but fails to identify the sex. Moreover, this can represent a large fraction of the data and, given the typically small sample sizes of many capture-recapture studies based on DNA information, utilization of the data with missing sex information is necessary. We develop the class structured likelihood for the case of missing covariate values, and then we address the scaling of the likelihood so that models with and without class structured parameters can be formally compared regardless of missing values. We apply our class structured model to black bear data collected in New York in which sex could be determined for only 62 of 169 uniquely identified individuals. The models containing sex-specificity of both the intercept of the SCR encounter probability model and the distance coefficient, and including a behavioral response are strongly favored by log-likelihood. Estimated population sex ratio is strongly influenced by sex structure in model parameters illustrating the importance of rigorous modeling of sex differences in capture-recapture models.

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.

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

PubMed

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

2018-01-01

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

Irreducible Uncertainty in Terrestrial Carbon Projections

NASA Astrophysics Data System (ADS)

Lovenduski, N. S.; Bonan, G. B.

2016-12-01

We quantify and isolate the sources of uncertainty in projections of carbon accumulation by the ocean and terrestrial biosphere over 2006-2100 using output from Earth System Models participating in the 5th Coupled Model Intercomparison Project. We consider three independent sources of uncertainty in our analysis of variance: (1) internal variability, driven by random, internal variations in the climate system, (2) emission scenario, driven by uncertainty in future radiative forcing, and (3) model structure, wherein different models produce different projections given the same emission scenario. Whereas uncertainty in projections of ocean carbon accumulation by 2100 is 100 Pg C and driven primarily by emission scenario, uncertainty in projections of terrestrial carbon accumulation by 2100 is 50% larger than that of the ocean, and driven primarily by model structure. This structural uncertainty is correlated with emission scenario: the variance associated with model structure is an order of magnitude larger under a business-as-usual scenario (RCP8.5) than a mitigation scenario (RCP2.6). In an effort to reduce this structural uncertainty, we apply various model weighting schemes to our analysis of variance in terrestrial carbon accumulation projections. The largest reductions in uncertainty are achieved when giving all the weight to a single model; here the uncertainty is of a similar magnitude to the ocean projections. Such an analysis suggests that this structural uncertainty is irreducible given current terrestrial model development efforts.

Modeling and control of flexible space structures

NASA Technical Reports Server (NTRS)

Wie, B.; Bryson, A. E., Jr.

1981-01-01

The effects of actuator and sensor locations on transfer function zeros are investigated, using uniform bars and beams as generic models of flexible space structures. It is shown how finite element codes may be used directly to calculate transfer function zeros. The impulse response predicted by finite-dimensional models is compared with the exact impulse response predicted by the infinite dimensional models. It is shown that some flexible structures behave as if there were a direct transmission between actuator and sensor (equal numbers of zeros and poles in the transfer function). Finally, natural damping models for a vibrating beam are investigated since natural damping has a strong influence on the appropriate active control logic for a flexible structure.

Vfold: a web server for RNA structure and folding thermodynamics prediction.

PubMed

Xu, Xiaojun; Zhao, Peinan; Chen, Shi-Jie

2014-01-01

The ever increasing discovery of non-coding RNAs leads to unprecedented demand for the accurate modeling of RNA folding, including the predictions of two-dimensional (base pair) and three-dimensional all-atom structures and folding stabilities. Accurate modeling of RNA structure and stability has far-reaching impact on our understanding of RNA functions in human health and our ability to design RNA-based therapeutic strategies. The Vfold server offers a web interface to predict (a) RNA two-dimensional structure from the nucleotide sequence, (b) three-dimensional structure from the two-dimensional structure and the sequence, and (c) folding thermodynamics (heat capacity melting curve) from the sequence. To predict the two-dimensional structure (base pairs), the server generates an ensemble of structures, including loop structures with the different intra-loop mismatches, and evaluates the free energies using the experimental parameters for the base stacks and the loop entropy parameters given by a coarse-grained RNA folding model (the Vfold model) for the loops. To predict the three-dimensional structure, the server assembles the motif scaffolds using structure templates extracted from the known PDB structures and refines the structure using all-atom energy minimization. The Vfold-based web server provides a user friendly tool for the prediction of RNA structure and stability. The web server and the source codes are freely accessible for public use at "http://rna.physics.missouri.edu".

Computational study of RNA folding kinetics and thermodynamics

NASA Astrophysics Data System (ADS)

Morgan, Steven Robert

RNA in its many forms is involved in the processes of protein manufacture, gene splicing, catalysis and gene regulation. It is also the store of genetic information in some viruses. The function of the RNA is determined by its structure, and it is the purpose of this thesis to investigate kinetic and thermodynamic properties of RNA secondary structures in order to obtain a better understanding of their formation and function. Our main tenet is that kinetic formation of RNA structure is necessary to explain features found in natural RNA structures, as well as aspects of the biological function of RNA. Firstly we show that examination of the energies of fragments of RNA secondary structure provides evidence for kinetic formation of structure. Local regions of RNA of length less than about 100 nucleotides adopt a conformation with energy near or equal to the minimum possible for those regions, whilst the energies of larger domains are much further from the their respective minima. This is consistent with the patterns that would be expected if RNA structure is folded Idneticatic during transcription. A Monte-Carlo algorithm is then used to model the kinetic folding of RNA during transcriptional growth. The algorithm is capable of finding the correct structure of a natural RNA for which the minimum free energy approach is unsuccessful. In the viral phage MS2 Idneticatic formed RNA structure plays an important role in the regulation of gene expression. The folding algorithm can accurately model this by IdneticaUy controlling access to the gene initiation region. The algorithm is also successfully used to model the control of replication in the ColEl plasmid. Taking a different approach, we then use a simplified model of RNA secondary structure to investigate the size of energy barriers between degenerate minimum energy structures. This model has much in common with physical systems such as spin glasses, and in fact shows similar behaviour to these systems in that energy barriers between structures grow quickly with the length of the RNA sequence. These barriers will serve to trap RNA in non-optimal structures. Together these studies demonstrate the necessity of studying RNA secondary structure from a kinetic point of view, and provide clear directions in which further work may be taken. Kinetic models of RNA secondary structure should continue to prove useful in modelling the structure and function of RNA.

A structure for maturing intelligent tutoring system student models

NASA Technical Reports Server (NTRS)

Holmes, Willard M.

1990-01-01

A special structure is examined for evolving a detached model of the user of an intelligent tutoring system. Tutoring is used in the context of education and training devices. A detached approach to populating the student model data structure is examined in the context of the need for time dependent reasoning about what the student knows about a particular concept in the domain of interest. This approach, to generating a data structure for the student model, allows an inference engine separate from the tutoring strategy determination to be used. This methodology has advantages in environments requiring real-time operation.

Suppressor Variables and Multilevel Mixture Modelling

ERIC Educational Resources Information Center

Darmawan, I Gusti Ngurah; Keeves, John P.

2006-01-01

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

Nonlinear finite element model updating for damage identification of civil structures using batch Bayesian estimation

NASA Astrophysics Data System (ADS)

Ebrahimian, Hamed; Astroza, Rodrigo; Conte, Joel P.; de Callafon, Raymond A.

2017-02-01

This paper presents a framework for structural health monitoring (SHM) and damage identification of civil structures. This framework integrates advanced mechanics-based nonlinear finite element (FE) modeling and analysis techniques with a batch Bayesian estimation approach to estimate time-invariant model parameters used in the FE model of the structure of interest. The framework uses input excitation and dynamic response of the structure and updates a nonlinear FE model of the structure to minimize the discrepancies between predicted and measured response time histories. The updated FE model can then be interrogated to detect, localize, classify, and quantify the state of damage and predict the remaining useful life of the structure. As opposed to recursive estimation methods, in the batch Bayesian estimation approach, the entire time history of the input excitation and output response of the structure are used as a batch of data to estimate the FE model parameters through a number of iterations. In the case of non-informative prior, the batch Bayesian method leads to an extended maximum likelihood (ML) estimation method to estimate jointly time-invariant model parameters and the measurement noise amplitude. The extended ML estimation problem is solved efficiently using a gradient-based interior-point optimization algorithm. Gradient-based optimization algorithms require the FE response sensitivities with respect to the model parameters to be identified. The FE response sensitivities are computed accurately and efficiently using the direct differentiation method (DDM). The estimation uncertainties are evaluated based on the Cramer-Rao lower bound (CRLB) theorem by computing the exact Fisher Information matrix using the FE response sensitivities with respect to the model parameters. The accuracy of the proposed uncertainty quantification approach is verified using a sampling approach based on the unscented transformation. Two validation studies, based on realistic structural FE models of a bridge pier and a moment resisting steel frame, are performed to validate the performance and accuracy of the presented nonlinear FE model updating approach and demonstrate its application to SHM. These validation studies show the excellent performance of the proposed framework for SHM and damage identification even in the presence of high measurement noise and/or way-out initial estimates of the model parameters. Furthermore, the detrimental effects of the input measurement noise on the performance of the proposed framework are illustrated and quantified through one of the validation studies.

A three-dimensional polyhedral unit model for grain boundary structure in fcc metals

NASA Astrophysics Data System (ADS)

Banadaki, Arash Dehghan; Patala, Srikanth

2017-03-01

One of the biggest challenges in developing truly bottom-up models for the performance of polycrystalline materials is the lack of robust quantitative structure-property relationships for interfaces. As a first step in analyzing such relationships, we present a polyhedral unit model to classify the geometrical nature of atomic packing along grain boundaries. While the atomic structure in disordered systems has been a topic of interest for many decades, geometrical analyses of grain boundaries has proven to be particularly challenging because of the wide range of structures that are possible depending on the underlying macroscopic crystallographic character. In this article, we propose an algorithm that can partition the atomic structure into a connected array of three-dimensional polyhedra, and thus, present a three-dimensional polyhedral unit model for grain boundaries. A point-pattern matching algorithm is also provided for quantifying the distortions of the observed grain boundary polyhedral units. The polyhedral unit model is robust enough to capture the structure of high-Σ, mixed character interfaces and, hence, provides a geometric tool for comparing grain boundary structures across the five-parameter crystallographic phase-space. Since the obtained polyhedral units circumscribe the voids present in the structure, such a description provides valuable information concerning segregation sites within the grain boundary. We anticipate that this technique will serve as a powerful tool in the analysis of grain boundary structure. The polyhedral unit model is also applicable to a wide array of material systems as the proposed algorithm is not limited by the underlying lattice structure.

DEM modeling of flexible structures against granular material avalanches

NASA Astrophysics Data System (ADS)

Lambert, Stéphane; Albaba, Adel; Nicot, François; Chareyre, Bruno

2016-04-01

This article presents the numerical modeling of flexible structures intended to contain avalanches of granular and coarse material (e.g. rock slide, a debris slide). The numerical model is based on a discrete element method (YADE-Dem). The DEM modeling of both the flowing granular material and the flexible structure are detailed before presenting some results. The flowing material consists of a dry polydisperse granular material accounting for the non-sphericity of real materials. The flexible structure consists in a metallic net hanged on main cables, connected to the ground via anchors, on both sides of the channel, including dissipators. All these components were modeled as flexible beams or wires, with mechanical parameters defined from literature data. The simulation results are presented with the aim of investigating the variability of the structure response depending on different parameters related to the structure (inclination of the fence, with/without brakes, mesh size opening), but also to the channel (inclination). Results are then compared with existing recommendations in similar fields.

Bi-directional evolutionary structural optimization for strut-and-tie modelling of three-dimensional structural concrete

NASA Astrophysics Data System (ADS)

Shobeiri, Vahid; Ahmadi-Nedushan, Behrouz

2017-12-01

This article presents a method for the automatic generation of optimal strut-and-tie models in reinforced concrete structures using a bi-directional evolutionary structural optimization method. The methodology presented is developed for compliance minimization relying on the Abaqus finite element software package. The proposed approach deals with the generation of truss-like designs in a three-dimensional environment, addressing the design of corbels and joints as well as bridge piers and pile caps. Several three-dimensional examples are provided to show the capabilities of the proposed framework in finding optimal strut-and-tie models in reinforced concrete structures and verifying its efficiency to cope with torsional actions. Several issues relating to the use of the topology optimization for strut-and-tie modelling of structural concrete, such as chequerboard patterns, mesh-dependency and multiple load cases, are studied. In the last example, a design procedure for detailing and dimensioning of the strut-and-tie models is given according to the American Concrete Institute (ACI) 318-08 provisions.

A Self-Assisting Protein Folding Model for Teaching Structural Molecular Biology.

PubMed

Davenport, Jodi; Pique, Michael; Getzoff, Elizabeth; Huntoon, Jon; Gardner, Adam; Olson, Arthur

2017-04-04

Structural molecular biology is now becoming part of high school science curriculum thus posing a challenge for teachers who need to convey three-dimensional (3D) structures with conventional text and pictures. In many cases even interactive computer graphics does not go far enough to address these challenges. We have developed a flexible model of the polypeptide backbone using 3D printing technology. With this model we have produced a polypeptide assembly kit to create an idealized model of the Triosephosphate isomerase mutase enzyme (TIM), which forms a structure known as TIM barrel. This kit has been used in a laboratory practical where students perform a step-by-step investigation into the nature of protein folding, starting with the handedness of amino acids to the formation of secondary and tertiary structure. Based on the classroom evidence we collected, we conclude that these models are valuable and inexpensive resource for teaching structural molecular biology. Copyright © 2017 Elsevier Ltd. All rights reserved.

Combined DFT and BS study on the exchange coupling of dinuclear sandwich-type POM: comparison of different functionals and reliability of structure modeling.

PubMed

Yin, Bing; Xue, GangLin; Li, JianLi; Bai, Lu; Huang, YuanHe; Wen, ZhenYi; Jiang, ZhenYi

2012-05-01

The exchange coupling of a group of three dinuclear sandwich-type polyoxomolybdates [MM'(AsMo7O27)2](12-) with MM' = CrCr, FeFe, FeCr are theoretically predicted from combined DFT and broken-symmetry (BS) approach. Eight different XC functionals are utilized to calculate the exchange-coupling constant J from both the full crystalline structures and model structures of smaller size. The comparison between theoretical values and accurate experimental results supports the applicability of DFT-BS method in this new type of sandwich-type dinuclear polyoxomolybdates. However, a careful choice of functionals is necessary to achieve the desired accuracy. The encouraging results obtained from calculations on model structures highlight the great potential of application of structure modeling in theoretical study of POM. Structural modeling may not only reduce the computational cost of large POM species but also be able to take into account the external field effect arising from solvent molecules in solution or counterions in crystal.

Quantitative structure-retention relationships for gas chromatographic retention indices of alkylbenzenes with molecular graph descriptors.

PubMed

Ivanciuc, O; Ivanciuc, T; Klein, D J; Seitz, W A; Balaban, A T

2001-02-01

Quantitative structure-retention relationships (QSRR) represent statistical models that quantify the connection between the molecular structure and the chromatographic retention indices of organic compounds, allowing the prediction of retention indices of novel, not yet synthesized compounds, solely from their structural descriptors. Using multiple linear regression, QSRR models for the gas chromatographic Kováts retention indices of 129 alkylbenzenes are generated using molecular graph descriptors. The correlational ability of structural descriptors computed from 10 molecular matrices is investigated, showing that the novel reciprocal matrices give numerical indices with improved correlational ability. A QSRR equation with 5 graph descriptors gives the best calibration and prediction results, demonstrating the usefulness of the molecular graph descriptors in modeling chromatographic retention parameters. The sequential orthogonalization of descriptors suggests simpler QSRR models by eliminating redundant structural information.

Hill-Climbing search and diversification within an evolutionary approach to protein structure prediction.

PubMed

Chira, Camelia; Horvath, Dragos; Dumitrescu, D

2011-07-30

Proteins are complex structures made of amino acids having a fundamental role in the correct functioning of living cells. The structure of a protein is the result of the protein folding process. However, the general principles that govern the folding of natural proteins into a native structure are unknown. The problem of predicting a protein structure with minimum-energy starting from the unfolded amino acid sequence is a highly complex and important task in molecular and computational biology. Protein structure prediction has important applications in fields such as drug design and disease prediction. The protein structure prediction problem is NP-hard even in simplified lattice protein models. An evolutionary model based on hill-climbing genetic operators is proposed for protein structure prediction in the hydrophobic - polar (HP) model. Problem-specific search operators are implemented and applied using a steepest-ascent hill-climbing approach. Furthermore, the proposed model enforces an explicit diversification stage during the evolution in order to avoid local optimum. The main features of the resulting evolutionary algorithm - hill-climbing mechanism and diversification strategy - are evaluated in a set of numerical experiments for the protein structure prediction problem to assess their impact to the efficiency of the search process. Furthermore, the emerging consolidated model is compared to relevant algorithms from the literature for a set of difficult bidimensional instances from lattice protein models. The results obtained by the proposed algorithm are promising and competitive with those of related methods.

Determining Protein Complex Structures Based on a Bayesian Model of in Vivo Förster Resonance Energy Transfer (FRET) Data*

PubMed Central

Bonomi, Massimiliano; Pellarin, Riccardo; Kim, Seung Joong; Russel, Daniel; Sundin, Bryan A.; Riffle, Michael; Jaschob, Daniel; Ramsden, Richard; Davis, Trisha N.; Muller, Eric G. D.; Sali, Andrej

2014-01-01

The use of in vivo Förster resonance energy transfer (FRET) data to determine the molecular architecture of a protein complex in living cells is challenging due to data sparseness, sample heterogeneity, signal contributions from multiple donors and acceptors, unequal fluorophore brightness, photobleaching, flexibility of the linker connecting the fluorophore to the tagged protein, and spectral cross-talk. We addressed these challenges by using a Bayesian approach that produces the posterior probability of a model, given the input data. The posterior probability is defined as a function of the dependence of our FRET metric FRETR on a structure (forward model), a model of noise in the data, as well as prior information about the structure, relative populations of distinct states in the sample, forward model parameters, and data noise. The forward model was validated against kinetic Monte Carlo simulations and in vivo experimental data collected on nine systems of known structure. In addition, our Bayesian approach was validated by a benchmark of 16 protein complexes of known structure. Given the structures of each subunit of the complexes, models were computed from synthetic FRETR data with a distance root-mean-squared deviation error of 14 to 17 Å. The approach is implemented in the open-source Integrative Modeling Platform, allowing us to determine macromolecular structures through a combination of in vivo FRETR data and data from other sources, such as electron microscopy and chemical cross-linking. PMID:25139910

Impact of structural and psychological empowerment on job strain in nursing work settings: expanding Kanter's model.

PubMed

Laschinger, H K; Finegan, J; Shamian, J; Wilk, P

2001-05-01

In this study, we tested an expanded model of Kanter's structural empowerment, which specified the relationships among structural and psychological empowerment, job strain, and work satisfaction. Strategies proposed in Kanter's empowerment theory have the potential to reduce job strain and improve employee work satisfaction and performance in current restructured healthcare settings. The addition to the model of psychological empowerment as an outcome of structural empowerment provides an understanding of the intervening mechanisms between structural work conditions and important organizational outcomes. A predictive, nonexperimental design was used to test the model in a random sample of 404 Canadian staff nurses. The Conditions of Work Effectiveness Questionnaire, the Psychological Empowerment Questionnaire, the Job Content Questionnaire, and the Global Satisfaction Scale were used to measure the major study variables. Structural equation modelling analyses revealed a good fit of the hypothesized model to the data based on various fit indices (chi 2 = 1140, df = 545, chi 2/df ratio = 2.09, CFI = 0.986, RMSEA = 0.050). The amount of variance accounted for in the model was 58%. Staff nurses felt that structural empowerment in their workplace resulted in higher levels of psychological empowerment. These heightened feelings of psychological empowerment in turn strongly influenced job strain and work satisfaction. However, job strain did not have a direct effect on work satisfaction. These results provide initial support for an expanded model of organizational empowerment and offer a broader understanding of the empowerment process.

Using Structural Equation Modeling To Fit Models Incorporating Principal Components.

ERIC Educational Resources Information Center

Dolan, Conor; Bechger, Timo; Molenaar, Peter

1999-01-01

Considers models incorporating principal components from the perspectives of structural-equation modeling. These models include the following: (1) the principal-component analysis of patterned matrices; (2) multiple analysis of variance based on principal components; and (3) multigroup principal-components analysis. Discusses fitting these models…

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.

Factor Structure of the Quality of Life Scale for Mental Disorders in Patients With Schizophrenia.

PubMed

Chiu, En-Chi; Lee, Shu-Chun

2018-06-01

The Quality of Life for Mental Disorders (QOLMD) scale was designed to measure health-related quality of life (HRQOL) in patients with mental illness, especially schizophrenia. The QOLMD contains 45 items, which are divided into eight domains. However, the factor structure of the QOLMD has not been evaluated, which restricts the interpretations of the results of this scale. The purpose of this study was to evaluate the factor structures (i.e., unidimensionality, eight-factor structure, and second-order model) of the QOLMD in patients with schizophrenia. Two hundred thirty-eight outpatients with schizophrenia participated. We first conducted confirmatory factor analysis to evaluate the unidimensionality of each domain. After the unidimensionality of the eight individual domains was supported, we examined the eight-factor structure and second-order model. The results of unidimensionality showed sufficient model fit in all of the domains with the exception of the autonomy domain. A good model fit was confirmed for the autonomy domain after deleting two of the original items. The eight-factor structure for the 43-item QOLMD showed an acceptable model fit, although the second-order model showed poor model fit. Our results supported the unidimensionality and eight-factor structure of the 43-item QOLMD. The sum score for each of the domains may be used to reflect its domain-specific function. We recommend using the 43-item QOLMD to capture the multiple domains of HRQOL. However, the second-order model showed an unsatisfactory model fit. Furthermore, caution is advised when interpreting overall HRQOL using the total score for the eight domains.

On the temporal evolution of long-wavelength mantle structure of the Earth since the early Paleozoic

NASA Astrophysics Data System (ADS)

Zhong, Shijie; Rudolph, Maxwell L.

2015-05-01

The seismic structure of the Earth's lower mantle is characterized by a dominantly degree-2 pattern with the African and Pacific large low shear velocity provinces (i.e., LLSVP) that are separated by circum-Pacific seismically fast anomalies. It is important to understand the origin of such a degree-2 mantle structure and its temporal evolution. In this study, we investigated the effects of plate motion history and mantle viscosity on the temporal evolution of the lower mantle structure since the early Paleozoic by formulating 3-D spherical shell models of thermochemical convection. For convection models with realistic mantle viscosity and no initial structure, it takes about ˜50 Myr to develop dominantly degree-2 lower mantle structure using the published plate motion models for the last either 120 Ma or 250 Ma. However, it takes longer time to develop the mantle structure for more viscous mantle. While the circum-Pangea subduction in plate motion history models promotes the formation of degree-2 mantle structure, the published pre-Pangea plate motions before 330 Ma produce relatively cold lower mantle in the African hemisphere and significant degree-1 structure in the early Pangea (˜300 Ma) or later times, even if the lower mantle has an initially degree-2 structure and a viscosity as high as 1023 Pas. This suggests that the African LLSVP may not be stationary since the early Paleozoic. With the published plate motion models and lower mantle viscosity of 1022 Pas, our mantle convection models suggest that the present-day degree-2 mantle structure may have largely been formed by ˜200 Ma.

Integration of system identification and finite element modelling of nonlinear vibrating structures

NASA Astrophysics Data System (ADS)

Cooper, Samson B.; DiMaio, Dario; Ewins, David J.

2018-03-01

The Finite Element Method (FEM), Experimental modal analysis (EMA) and other linear analysis techniques have been established as reliable tools for the dynamic analysis of engineering structures. They are often used to provide solutions to small and large structures and other variety of cases in structural dynamics, even those exhibiting a certain degree of nonlinearity. Unfortunately, when the nonlinear effects are substantial or the accuracy of the predicted response is of vital importance, a linear finite element model will generally prove to be unsatisfactory. As a result, the validated linear FE model requires further enhancement so that it can represent and predict the nonlinear behaviour exhibited by the structure. In this paper, a pragmatic approach to integrating test-based system identification and FE modelling of a nonlinear structure is presented. This integration is based on three different phases: the first phase involves the derivation of an Underlying Linear Model (ULM) of the structure, the second phase includes experiment-based nonlinear identification using measured time series and the third phase covers augmenting the linear FE model and experimental validation of the nonlinear FE model. The proposed case study is demonstrated on a twin cantilever beam assembly coupled with a flexible arch shaped beam. In this case, polynomial-type nonlinearities are identified and validated with force-controlled stepped-sine test data at several excitation levels.

Experimental validation of a numerical 3-D finite model applied to wind turbines design under vibration constraints: TREVISE platform

NASA Astrophysics Data System (ADS)

Sellami, Takwa; Jelassi, Sana; Darcherif, Abdel Moumen; Berriri, Hanen; Mimouni, Med Faouzi

2018-04-01

With the advancement of wind turbines towards complex structures, the requirement of trusty structural models has become more apparent. Hence, the vibration characteristics of the wind turbine components, like the blades and the tower, have to be extracted under vibration constraints. Although extracting the modal properties of blades is a simple task, calculating precise modal data for the whole wind turbine coupled to its tower/foundation is still a perplexing task. In this framework, this paper focuses on the investigation of the structural modeling approach of modern commercial micro-turbines. Thus, the structural model a complex designed wind turbine, which is Rutland 504, is established based on both experimental and numerical methods. A three-dimensional (3-D) numerical model of the structure was set up based on the finite volume method (FVM) using the academic finite element analysis software ANSYS. To validate the created model, experimental vibration tests were carried out using the vibration test system of TREVISE platform at ECAM-EPMI. The tests were based on the experimental modal analysis (EMA) technique, which is one of the most efficient techniques for identifying structures parameters. Indeed, the poles and residues of the frequency response functions (FRF), between input and output spectra, were calculated to extract the mode shapes and the natural frequencies of the structure. Based on the obtained modal parameters, the numerical designed model was up-dated.

LYRA, a webserver for lymphocyte receptor structural modeling.

PubMed

Klausen, Michael Schantz; Anderson, Mads Valdemar; Jespersen, Martin Closter; Nielsen, Morten; Marcatili, Paolo

2015-07-01

The accurate structural modeling of B- and T-cell receptors is fundamental to gain a detailed insight in the mechanisms underlying immunity and in developing new drugs and therapies. The LYRA (LYmphocyte Receptor Automated modeling) web server (http://www.cbs.dtu.dk/services/LYRA/) implements a complete and automated method for building of B- and T-cell receptor structural models starting from their amino acid sequence alone. The webserver is freely available and easy to use for non-specialists. Upon submission, LYRA automatically generates alignments using ad hoc profiles, predicts the structural class of each hypervariable loop, selects the best templates in an automatic fashion, and provides within minutes a complete 3D model that can be downloaded or inspected online. Experienced users can manually select or exclude template structures according to case specific information. LYRA is based on the canonical structure method, that in the last 30 years has been successfully used to generate antibody models of high accuracy, and in our benchmarks this approach proves to achieve similarly good results on TCR modeling, with a benchmarked average RMSD accuracy of 1.29 and 1.48 Å for B- and T-cell receptors, respectively. To the best of our knowledge, LYRA is the first automated server for the prediction of TCR structure. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

On the morphology of the scattering medium as seen by MST/ST radars

NASA Technical Reports Server (NTRS)

Gage, K. S.

1983-01-01

Much is learned about the morphology of the small scale structures of the atmosphere from analysis of echoes observed by MST radars. The use of physical models enables a synthesis of diverse observations. Each model contains an implicit assumption about the nature of the irregularity structure of the medium. A comparison is made between the irregularity structure implicit in several models and what is known about the structure of the medium.

Cavitation and Wake Structure of Unsteady Tip Vortex Flows

DTIC Science & Technology

1992-12-10

wake structure generated by three-dimensional lifting surfaces. No longer can the wake be modeled as a simple horseshoe vortex structure with the tip...first initiates. -13- Z Strtn vortex "~Bound vortex "’ ; b Wake 2 Figure 1.5 Far-Field Horseshoe Model of a Finite Wing This figure shows a finite wing...Figure 1.11 Simplified Illustration of Wake Structure Behind an Oscillating Wing This schematic shows a simplified model of the trailing vortex

X-ray structure determination at low resolution

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

Brunger, Axel T., E-mail: brunger@stanford.edu; Department of Molecular and Cellular Physiology, Stanford University; Department of Neurology and Neurological Sciences, Stanford University

2009-02-01

Refinement is meaningful even at 4 Å or lower, but with present methodologies it should start from high-resolution crystal structures whenever possible. As an example of structure determination in the 3.5–4.5 Å resolution range, crystal structures of the ATPase p97/VCP, consisting of an N-terminal domain followed by a tandem pair of ATPase domains (D1 and D2), are discussed. The structures were originally solved by molecular replacement with the high-resolution structure of the N-D1 fragment of p97/VCP, whereas the D2 domain was manually built using its homology to the D1 domain as a guide. The structure of the D2 domain alonemore » was subsequently solved at 3 Å resolution. The refined model of D2 and the high-resolution structure of the N-D1 fragment were then used as starting models for re-refinement against the low-resolution diffraction data for full-length p97. The re-refined full-length models showed significant improvement in both secondary structure and R values. The free R values dropped by as much as 5% compared with the original structure refinements, indicating that refinement is meaningful at low resolution and that there is information in the diffraction data even at ∼4 Å resolution that objectively assesses the quality of the model. It is concluded that de novo model building is problematic at low resolution and refinement should start from high-resolution crystal structures whenever possible.« less

Modes of interconnected lattice trusses using continuum models, part 1

NASA Technical Reports Server (NTRS)

Balakrishnan, A. V.

1991-01-01

This represents a continuing systematic attempt to explore the use of continuum models--in contrast to the Finite Element Models currently universally in use--to develop feedback control laws for stability enhancement of structures, particularly large structures, for deployment in space. We shall show that for the control objective, continuum models do offer unique advantages. It must be admitted of course that developing continuum models for arbitrary structures is no easy task. In this paper we take advantage of the special nature of current Large Space Structures--typified by the NASA-LaRC Evolutionary Model which will be our main concern--which consists of interconnected orthogonal lattice trusses each with identical bays. Using an equivalent one-dimensional Timoshenko beam model, we develop an almost complete continuum model for the evolutionary structure. We do this in stages, beginning only with the main bus as flexible and then going on to make all the appendages also flexible-except for the antenna structure. Based on these models we proceed to develop formulas for mode frequencies and shapes. These are shown to be the roots of the determinant of a matrix of small dimension compared with mode calculations using Finite Element Models, even though the matrix involves transcendental functions. The formulas allow us to study asymptotic properties of the modes and how they evolve as we increase the number of bodies which are treated as flexible. The asymptotics, in fact, become simpler.

Construction of a three-dimensional interactive model of the skull base and cranial nerves.

PubMed

Kakizawa, Yukinari; Hongo, Kazuhiro; Rhoton, Albert L

2007-05-01

The goal was to develop an interactive three-dimensional (3-D) computerized anatomic model of the skull base for teaching microneurosurgical anatomy and for operative planning. The 3-D model was constructed using commercially available software (Maya 6.0 Unlimited; Alias Systems Corp., Delaware, MD), a personal computer, four cranial specimens, and six dry bones. Photographs from at least two angles of the superior and lateral views were imported to the 3-D software. Many photographs were needed to produce the model in anatomically complex areas. Careful dissection was needed to expose important structures in the two views. Landmarks, including foramen, bone, and dura mater, were used as reference points. The 3-D model of the skull base and related structures was constructed using more than 300,000 remodeled polygons. The model can be viewed from any angle. It can be rotated 360 degrees in any plane using any structure as the focal point of rotation. The model can be reduced or enlarged using the zoom function. Variable transparencies could be assigned to any structures so that the structures at any level can be seen. Anatomic labels can be attached to the structures in the 3-D model for educational purposes. This computer-generated 3-D model can be observed and studied repeatedly without the time limitations and stresses imposed by surgery. This model may offer the potential to create interactive surgical exercises useful in evaluating multiple surgical routes to specific target areas in the skull base.

Information-System Structure by Communication-Technology Concepts: A Cybernetic Model Approach.

ERIC Educational Resources Information Center

Reisig, Gerhard H. R.

1978-01-01

Presents the "Evidence-of-Existence" information system in which the structure is developed, with application of cybernetic concepts, as an isomorphic model in analogy to the system structure of communication technology. Three criteria of structuring are postulated: (1) source-channel-sink, with input-output characteristics, (2) filter-type…

Salmonella Typhimurium and Staphylococcus aureus dynamics in/on variable (micro)structures of fish-based model systems at suboptimal temperatures.

PubMed

Baka, Maria; Verheyen, Davy; Cornette, Nicolas; Vercruyssen, Stijn; Van Impe, Jan F

2017-01-02

The limited knowledge concerning the influence of food (micro)structure on microbial dynamics decreases the accuracy of the developed predictive models, as most studies have mainly been based on experimental data obtained in liquid microbiological media or in/on real foods. The use of model systems has a great potential when studying this complex factor. Apart from the variability in (micro)structural properties, model systems vary in compositional aspects, as a consequence of their (micro)structural variation. In this study, different experimental food model systems, with compositional and physicochemical properties similar to fish patés, are developed to study the influence of food (micro)structure on microbial dynamics. The microbiological safety of fish products is of major importance given the numerous cases of salmonellosis and infections attributed to staphylococcus toxins. The model systems understudy represent food (micro)structures of liquids, aqueous gels, emulsions and gelled emulsions. The growth/inactivation dynamics and a modelling approach of combined growth and inactivation of Salmonella Typhimurium and Staphylococcus aureus, related to fish products, are investigated in/on these model systems at temperatures relevant to fish products' common storage (4°C) and to abuse storage temperatures (8 and 12°C). ComBase (http://www.combase.cc/) predictions compared with the maximum specific growth rate (μ max ) values estimated by the Baranyi and Roberts model in the current study indicated that the (micro)structure influences the microbial dynamics. Overall, ComBase overestimated microbial growth at the same pH, a w and storage temperature. Finally, the storage temperature had also an influence on how much each model system affected the microbial dynamics. Copyright © 2016. Published by Elsevier B.V.

Generation, Analysis and Characterization of Anisotropic Engineered Meta Materials

NASA Astrophysics Data System (ADS)

Trifale, Ninad T.

A methodology for a systematic generation of highly anisotropic micro-lattice structures was investigated. Multiple algorithms for generation and validation of engineered structures are developed and evaluated. Set of all possible permutations of structures for an 8-node cubic unit cell were considered and the degree of anisotropy of meta-properties in heat transport and mechanical elasticity were evaluated. Feasibility checks were performed to ensure that the generated unit cell network was repeatable and a continuous lattice structure. Four different strategies for generating permutations of the structures are discussed. Analytical models were developed to predict effective thermal, mechanical and permeability characteristics of these cellular structures.Experimentation and numerical modeling techniques were used to validate the models that are developed. A self-consistent mechanical elasticity model was developed which connects the meso-scale properties to stiffness of individual struts. A three dimensional thermal resistance network analogy was used to evaluate the effective thermal conductivity of the structures. The struts were modeled as a network of one dimensional thermal resistive elements and effective conductivity evaluated. Models were validated against numerical simulations and experimental measurements on 3D printed samples. Model was developed to predict effective permeability of these engineered structures based on Darcy's law. Drag coefficients were evaluated for individual connections in transverse and longitudinal directions and an interaction term was calibrated from the experimental data in literature in order to predict permeability. Generic optimization framework coupled to finite element solver is developed for analyzing any application involving use of porous structures. An objective functions were generated structure to address frequently observed trade-off between the stiffness, thermal conductivity, permeability and porosity. Three application were analyzed for potential use of engineered materials. Heat spreader application involving thermal and mechanical constraints, artificial bone grafts application involving mechanical and permeability constraints and structural materials applications involving mechanical, thermal and porosity constraints is analyzed. Recommendations for optimum topologies for specific operating conditions are provided.

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

Computer Models of Proteins

NASA Technical Reports Server (NTRS)

2000-01-01

Dr. Marc Pusey (seated) and Dr. Craig Kundrot use computers to analyze x-ray maps and generate three-dimensional models of protein structures. With this information, scientists at Marshall Space Flight Center can learn how proteins are made and how they work. The computer screen depicts a proten structure as a ball-and-stick model. Other models depict the actual volume occupied by the atoms, or the ribbon-like structures that are crucial to a protein's function.

Shock Structure Analysis and Aerodynamics in a Weakly Ionized Gas Flow

NASA Technical Reports Server (NTRS)

Saeks, R.; Popovic, S.; Chow, A. S.

2006-01-01

The structure of a shock wave propagating through a weakly ionized gas is analyzed using an electrofluid dynamics model composed of classical conservation laws and Gauss Law. A viscosity model is included to correctly model the spatial scale of the shock structure, and quasi-neutrality is not assumed. A detailed analysis of the structure of a shock wave propagating in a weakly ionized gas is presented, together with a discussion of the physics underlying the key features of the shock structure. A model for the flow behind a shock wave propagating through a weakly ionized gas is developed and used to analyze the effect of the ionization on the aerodynamics and performance of a two-dimensional hypersonic lifting body.

Maximum Likelihood Analysis of a Two-Level Nonlinear Structural Equation Model with Fixed Covariates

ERIC Educational Resources Information Center

Lee, Sik-Yum; Song, Xin-Yuan

2005-01-01

In this article, a maximum likelihood (ML) approach for analyzing a rather general two-level structural equation model is developed for hierarchically structured data that are very common in educational and/or behavioral research. The proposed two-level model can accommodate nonlinear causal relations among latent variables as well as effects…

Factors that Affect Mathematics-Science (MS) Scores in the Secondary Education Institutional Exam: An Application of Structural Equation Modeling

ERIC Educational Resources Information Center

Yavuz, Mustafa

2009-01-01

Discovering what determines students' success in the Secondary Education Institutional Exam is very important to parents and it is also critical for students, teachers, directors, and researchers. Research was carried out by studying the related literature and structural equation modeling techniques. A structural model was created that consisted…

An Improved Estimation Using Polya-Gamma Augmentation for Bayesian Structural Equation Models with Dichotomous Variables

ERIC Educational Resources Information Center

Kim, Seohyun; Lu, Zhenqiu; Cohen, Allan S.

2018-01-01

Bayesian algorithms have been used successfully in the social and behavioral sciences to analyze dichotomous data particularly with complex structural equation models. In this study, we investigate the use of the Polya-Gamma data augmentation method with Gibbs sampling to improve estimation of structural equation models with dichotomous variables.…

Impact of Diagnosticity on the Adequacy of Models for Cognitive Diagnosis under a Linear Attribute Structure: A Simulation Study

ERIC Educational Resources Information Center

de La Torre, Jimmy; Karelitz, Tzur M.

2009-01-01

Compared to unidimensional item response models (IRMs), cognitive diagnostic models (CDMs) based on latent classes represent examinees' knowledge and item requirements using discrete structures. This study systematically examines the viability of retrofitting CDMs to IRM-based data with a linear attribute structure. The study utilizes a procedure…

Item response theory and structural equation modelling for ordinal data: Describing the relationship between KIDSCREEN and Life-H.

PubMed

Titman, Andrew C; Lancaster, Gillian A; Colver, Allan F

2016-10-01

Both item response theory and structural equation models are useful in the analysis of ordered categorical responses from health assessment questionnaires. We highlight the advantages and disadvantages of the item response theory and structural equation modelling approaches to modelling ordinal data, from within a community health setting. Using data from the SPARCLE project focussing on children with cerebral palsy, this paper investigates the relationship between two ordinal rating scales, the KIDSCREEN, which measures quality-of-life, and Life-H, which measures participation. Practical issues relating to fitting models, such as non-positive definite observed or fitted correlation matrices, and approaches to assessing model fit are discussed. item response theory models allow properties such as the conditional independence of particular domains of a measurement instrument to be assessed. When, as with the SPARCLE data, the latent traits are multidimensional, structural equation models generally provide a much more convenient modelling framework. © The Author(s) 2013.

Evaluation of 3D-Jury on CASP7 models.

PubMed

Kaján, László; Rychlewski, Leszek

2007-08-21

3D-Jury, the structure prediction consensus method publicly available in the Meta Server http://meta.bioinfo.pl/, was evaluated using models gathered in the 7th round of the Critical Assessment of Techniques for Protein Structure Prediction (CASP7). 3D-Jury is an automated expert process that generates protein structure meta-predictions from sets of models obtained from partner servers. The performance of 3D-Jury was analysed for three aspects. First, we examined the correlation between the 3D-Jury score and a model quality measure: the number of correctly predicted residues. The 3D-Jury score was shown to correlate significantly with the number of correctly predicted residues, the correlation is good enough to be used for prediction. 3D-Jury was also found to improve upon the competing servers' choice of the best structure model in most cases. The value of the 3D-Jury score as a generic reliability measure was also examined. We found that the 3D-Jury score separates bad models from good models better than the reliability score of the original server in 27 cases and falls short of it in only 5 cases out of a total of 38. We report the release of a new Meta Server feature: instant 3D-Jury scoring of uploaded user models. The 3D-Jury score continues to be a good indicator of structural model quality. It also provides a generic reliability score, especially important for models that were not assigned such by the original server. Individual structure modellers can also benefit from the 3D-Jury scoring system by testing their models in the new instant scoring feature http://meta.bioinfo.pl/compare_your_model_example.pl available in the Meta Server.

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.

Targeted Maximum Likelihood Estimation for Dynamic and Static Longitudinal Marginal Structural Working Models

PubMed Central

Schwab, Joshua; Gruber, Susan; Blaser, Nello; Schomaker, Michael; van der Laan, Mark

2015-01-01

This paper describes a targeted maximum likelihood estimator (TMLE) for the parameters of longitudinal static and dynamic marginal structural models. We consider a longitudinal data structure consisting of baseline covariates, time-dependent intervention nodes, intermediate time-dependent covariates, and a possibly time-dependent outcome. The intervention nodes at each time point can include a binary treatment as well as a right-censoring indicator. Given a class of dynamic or static interventions, a marginal structural model is used to model the mean of the intervention-specific counterfactual outcome as a function of the intervention, time point, and possibly a subset of baseline covariates. Because the true shape of this function is rarely known, the marginal structural model is used as a working model. The causal quantity of interest is defined as the projection of the true function onto this working model. Iterated conditional expectation double robust estimators for marginal structural model parameters were previously proposed by Robins (2000, 2002) and Bang and Robins (2005). Here we build on this work and present a pooled TMLE for the parameters of marginal structural working models. We compare this pooled estimator to a stratified TMLE (Schnitzer et al. 2014) that is based on estimating the intervention-specific mean separately for each intervention of interest. The performance of the pooled TMLE is compared to the performance of the stratified TMLE and the performance of inverse probability weighted (IPW) estimators using simulations. Concepts are illustrated using an example in which the aim is to estimate the causal effect of delayed switch following immunological failure of first line antiretroviral therapy among HIV-infected patients. Data from the International Epidemiological Databases to Evaluate AIDS, Southern Africa are analyzed to investigate this question using both TML and IPW estimators. Our results demonstrate practical advantages of the pooled TMLE over an IPW estimator for working marginal structural models for survival, as well as cases in which the pooled TMLE is superior to its stratified counterpart. PMID:25909047

Topology of Document Retrieval Systems.

ERIC Educational Resources Information Center

Everett, Daniel M.; Cater, Steven C.

1992-01-01

Explains the use of a topological structure to examine the closeness between documents in retrieval systems and analyzes the topological structure of a vector-space model, a fuzzy-set model, an extended Boolean model, a probabilistic model, and a TIRS (Topological Information Retrieval System) model. Proofs for the results are appended. (17…

Generative Models of Disfluency

ERIC Educational Resources Information Center

Miller, Timothy A.

2010-01-01

This thesis describes a generative model for representing disfluent phenomena in human speech. This model makes use of observed syntactic structure present in disfluent speech, and uses a right-corner transform on syntax trees to model this structure in a very natural way. Specifically, the phenomenon of speech repair is modeled by explicitly…

Partial Least Squares Structural Equation Modeling with R

ERIC Educational Resources Information Center

Ravand, Hamdollah; Baghaei, Purya

2016-01-01

Structural equation modeling (SEM) has become widespread in educational and psychological research. Its flexibility in addressing complex theoretical models and the proper treatment of measurement error has made it the model of choice for many researchers in the social sciences. Nevertheless, the model imposes some daunting assumptions and…

Review: To be or not to be an identifiable model. Is this a relevant question in animal science modelling?

PubMed

Muñoz-Tamayo, R; Puillet, L; Daniel, J B; Sauvant, D; Martin, O; Taghipoor, M; Blavy, P

2018-04-01

What is a good (useful) mathematical model in animal science? For models constructed for prediction purposes, the question of model adequacy (usefulness) has been traditionally tackled by statistical analysis applied to observed experimental data relative to model-predicted variables. However, little attention has been paid to analytic tools that exploit the mathematical properties of the model equations. For example, in the context of model calibration, before attempting a numerical estimation of the model parameters, we might want to know if we have any chance of success in estimating a unique best value of the model parameters from available measurements. This question of uniqueness is referred to as structural identifiability; a mathematical property that is defined on the sole basis of the model structure within a hypothetical ideal experiment determined by a setting of model inputs (stimuli) and observable variables (measurements). Structural identifiability analysis applied to dynamic models described by ordinary differential equations (ODEs) is a common practice in control engineering and system identification. This analysis demands mathematical technicalities that are beyond the academic background of animal science, which might explain the lack of pervasiveness of identifiability analysis in animal science modelling. To fill this gap, in this paper we address the analysis of structural identifiability from a practitioner perspective by capitalizing on the use of dedicated software tools. Our objectives are (i) to provide a comprehensive explanation of the structural identifiability notion for the community of animal science modelling, (ii) to assess the relevance of identifiability analysis in animal science modelling and (iii) to motivate the community to use identifiability analysis in the modelling practice (when the identifiability question is relevant). We focus our study on ODE models. By using illustrative examples that include published mathematical models describing lactation in cattle, we show how structural identifiability analysis can contribute to advancing mathematical modelling in animal science towards the production of useful models and, moreover, highly informative experiments via optimal experiment design. Rather than attempting to impose a systematic identifiability analysis to the modelling community during model developments, we wish to open a window towards the discovery of a powerful tool for model construction and experiment design.

Achilles tendons from decorin- and biglycan-null mouse models have inferior mechanical and structural properties predicted by an image-based empirical damage model

PubMed Central

Gordon, J.A.; Freedman, B.R.; Zuskov, A.; Iozzo, R.V.; Birk, D.E.; Soslowsky, L.J.

2015-01-01

Achilles tendons are a common source of pain and injury, and their pathology may originate from aberrant structure function relationships. Small leucine rich proteoglycans (SLRPs) influence mechanical and structural properties in a tendon-specific manner. However, their roles in the Achilles tendon have not been defined. The objective of this study was to evaluate the mechanical and structural differences observed in mouse Achilles tendons lacking class I SLRPs; either decorin or biglycan. In addition, empirical modeling techniques based on mechanical and image-based measures were employed. Achilles tendons from decorin-null (Dcn−/−) and biglycan-null (Bgn−/−) C57BL/6 female mice (N=102) were used. Each tendon underwent a dynamic mechanical testing protocol including simultaneous polarized light image capture to evaluate both structural and mechanical properties of each Achilles tendon. An empirical damage model was adapted for application to genetic variation and for use with image based structural properties to predict tendon dynamic mechanical properties. We found that Achilles tendons lacking decorin and biglycan had inferior mechanical and structural properties that were age dependent; and that simple empirical models, based on previously described damage models, were predictive of Achilles tendon dynamic modulus in both decorin- and biglycan-null mice. PMID:25888014

Proposed structure of putative glucose channel in GLUT1 facilitative glucose transporter.

PubMed Central

Zeng, H; Parthasarathy, R; Rampal, A L; Jung, C Y

1996-01-01

A family of structurally related intrinsic membrane proteins (facilitative glucose transporters) catalyzes the movement of glucose across the plasma membrane of animal cells. Evidence indicates that these proteins show a common structural motif where approximately 50% of the mass is embedded in lipid bilayer (transmembrane domain) in 12 alpha-helices (transmembrane helices; TMHs) and accommodates a water-filled channel for substrate passage (glucose channel) whose tertiary structure is currently unknown. Using recent advances in protein structure prediction algorithms we proposed here two three-dimensional structural models for the transmembrane glucose channel of GLUT1 glucose transporter. Our models emphasize the physical dimension and water accessibility of the channel, loop lengths between TMHs, the macrodipole orientation in four-helix bundle motif, and helix packing energy. Our models predict that five TMHs, either TMHs 3, 4, 7, 8, 11 (Model 1) or TMHs 2, 5, 11, 8, 7 (Model 2), line the channel, and the remaining TMHs surround these channel-lining TMHs. We discuss how our models are compatible with the experimental data obtained with this protein, and how they can be used in designing new biochemical and molecular biological experiments in elucidation of the structural basis of this important protein function. Images FIGURE 1 FIGURE 2 FIGURE 4 FIGURE 5 PMID:8770183

Achilles tendons from decorin- and biglycan-null mouse models have inferior mechanical and structural properties predicted by an image-based empirical damage model.

PubMed

Gordon, J A; Freedman, B R; Zuskov, A; Iozzo, R V; Birk, D E; Soslowsky, L J

2015-07-16

Achilles tendons are a common source of pain and injury, and their pathology may originate from aberrant structure function relationships. Small leucine rich proteoglycans (SLRPs) influence mechanical and structural properties in a tendon-specific manner. However, their roles in the Achilles tendon have not been defined. The objective of this study was to evaluate the mechanical and structural differences observed in mouse Achilles tendons lacking class I SLRPs; either decorin or biglycan. In addition, empirical modeling techniques based on mechanical and image-based measures were employed. Achilles tendons from decorin-null (Dcn(-/-)) and biglycan-null (Bgn(-/-)) C57BL/6 female mice (N=102) were used. Each tendon underwent a dynamic mechanical testing protocol including simultaneous polarized light image capture to evaluate both structural and mechanical properties of each Achilles tendon. An empirical damage model was adapted for application to genetic variation and for use with image based structural properties to predict tendon dynamic mechanical properties. We found that Achilles tendons lacking decorin and biglycan had inferior mechanical and structural properties that were age dependent; and that simple empirical models, based on previously described damage models, were predictive of Achilles tendon dynamic modulus in both decorin- and biglycan-null mice. Copyright © 2015 Elsevier Ltd. All rights reserved.

Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation

PubMed Central

2017-01-01

The concept of dynamical compensation has been recently introduced to describe the ability of a biological system to keep its output dynamics unchanged in the face of varying parameters. However, the original definition of dynamical compensation amounts to lack of structural identifiability. This is relevant if model parameters need to be estimated, as is often the case in biological modelling. Care should we taken when using an unidentifiable model to extract biological insight: the estimated values of structurally unidentifiable parameters are meaningless, and model predictions about unmeasured state variables can be wrong. Taking this into account, we explore alternative definitions of dynamical compensation that do not necessarily imply structural unidentifiability. Accordingly, we show different ways in which a model can be made identifiable while exhibiting dynamical compensation. Our analyses enable the use of the new concept of dynamical compensation in the context of parameter identification, and reconcile it with the desirable property of structural identifiability. PMID:29186132

Weak lensing probe of cubic Galileon model

NASA Astrophysics Data System (ADS)

Dinda, Bikash R.

2018-06-01

The cubic Galileon model containing the lowest non-trivial order action of the full Galileon action can produce the stable late-time cosmic acceleration. This model can have a significant role in the growth of structures. The signatures of the cubic Galileon model in the structure formation can be probed by the weak lensing statistics. Weak lensing convergence statistics is one of the strongest probes to the structure formation and hence it can probe the dark energy or modified theories of gravity models. In this work, we investigate the detectability of the cubic Galileon model from the ΛCDM model or from the canonical quintessence model through the convergence power spectrum and bi-spectrum.

Crack Detection in Fibre Reinforced Plastic Structures Using Embedded Fibre Bragg Grating Sensors: Theory, Model Development and Experimental Validation

PubMed Central

Pereira, G. F.; Mikkelsen, L. P.; McGugan, M.

2015-01-01

In a fibre-reinforced polymer (FRP) structure designed using the emerging damage tolerance and structural health monitoring philosophy, sensors and models that describe crack propagation will enable a structure to operate despite the presence of damage by fully exploiting the material’s mechanical properties. When applying this concept to different structures, sensor systems and damage types, a combination of damage mechanics, monitoring technology, and modelling is required. The primary objective of this article is to demonstrate such a combination. This article is divided in three main topics: the damage mechanism (delamination of FRP), the structural health monitoring technology (fibre Bragg gratings to detect delamination), and the finite element method model of the structure that incorporates these concepts into a final and integrated damage-monitoring concept. A novel method for assessing a crack growth/damage event in fibre-reinforced polymer or structural adhesive-bonded structures using embedded fibre Bragg grating (FBG) sensors is presented by combining conventional measured parameters, such as wavelength shift, with parameters associated with measurement errors, typically ignored by the end-user. Conjointly, a novel model for sensor output prediction (virtual sensor) was developed using this FBG sensor crack monitoring concept and implemented in a finite element method code. The monitoring method was demonstrated and validated using glass fibre double cantilever beam specimens instrumented with an array of FBG sensors embedded in the material and tested using an experimental fracture procedure. The digital image correlation technique was used to validate the model prediction by correlating the specific sensor response caused by the crack with the developed model. PMID:26513653

Modeling and prediction of peptide drift times in ion mobility spectrometry using sequence-based and structure-based approaches.

PubMed

Zhang, Yiming; Jin, Quan; Wang, Shuting; Ren, Ren

2011-05-01

The mobile behavior of 1481 peptides in ion mobility spectrometry (IMS), which are generated by protease digestion of the Drosophila melanogaster proteome, is modeled and predicted based on two different types of characterization methods, i.e. sequence-based approach and structure-based approach. In this procedure, the sequence-based approach considers both the amino acid composition of a peptide and the local environment profile of each amino acid in the peptide; the structure-based approach is performed with the CODESSA protocol, which regards a peptide as a common organic compound and generates more than 200 statistically significant variables to characterize the whole structure profile of a peptide molecule. Subsequently, the nonlinear support vector machine (SVM) and Gaussian process (GP) as well as linear partial least squares (PLS) regression is employed to correlate the structural parameters of the characterizations with the IMS drift times of these peptides. The obtained quantitative structure-spectrum relationship (QSSR) models are evaluated rigorously and investigated systematically via both one-deep and two-deep cross-validations as well as the rigorous Monte Carlo cross-validation (MCCV). We also give a comprehensive comparison on the resulting statistics arising from the different combinations of variable types with modeling methods and find that the sequence-based approach can give the QSSR models with better fitting ability and predictive power but worse interpretability than the structure-based approach. In addition, though the QSSR modeling using sequence-based approach is not needed for the preparation of the minimization structures of peptides before the modeling, it would be considerably efficient as compared to that using structure-based approach. Copyright © 2011 Elsevier Ltd. All rights reserved.

Ground vibration test results for Drones for Aerodynamic and Structural Testing (DAST)/Aeroelastic Research Wing (ARW-1R) aircraft

NASA Technical Reports Server (NTRS)

Cox, T. H.; Gilyard, G. B.

1986-01-01

The drones for aerodynamic and structural testing (DAST) project was designed to control flutter actively at high subsonic speeds. Accurate knowledge of the structural model was critical for the successful design of the control system. A ground vibration test was conducted on the DAST vehicle to determine the structural model characteristics. This report presents and discusses the vibration and test equipment, the test setup and procedures, and the antisymmetric and symmetric mode shape results. The modal characteristics were subsequently used to update the structural model employed in the control law design process.

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.

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.

A template-finding algorithm and a comprehensive benchmark for homology modeling of proteins

PubMed Central

Vallat, Brinda Kizhakke; Pillardy, Jaroslaw; Elber, Ron

2010-01-01

The first step in homology modeling is to identify a template protein for the target sequence. The template structure is used in later phases of the calculation to construct an atomically detailed model for the target. We have built from the Protein Data Bank a large-scale learning set that includes tens of millions of pair matches that can be either a true template or a false one. Discriminatory learning (learning from positive and negative examples) is employed to train a decision tree. Each branch of the tree is a mathematical programming model. The decision tree is tested on an independent set from PDB entries and on the sequences of CASP7. It provides significant enrichment of true templates (between 50-100 percent) when compared to PSI-BLAST. The model is further verified by building atomically detailed structures for each of the tentative true templates with modeller. The probability that a true match does not yield an acceptable structural model (within 6Å RMSD from the native structure), decays linearly as a function of the TM structural-alignment score. PMID:18300226

Robustness of atomistic Gō models in predicting native-like folding intermediates

NASA Astrophysics Data System (ADS)

Estácio, S. G.; Fernandes, C. S.; Krobath, H.; Faísca, P. F. N.; Shakhnovich, E. I.

2012-08-01

Gō models are exceedingly popular tools in computer simulations of protein folding. These models are native-centric, i.e., they are directly constructed from the protein's native structure. Therefore, it is important to understand up to which extent the atomistic details of the native structure dictate the folding behavior exhibited by Gō models. Here we address this challenge by performing exhaustive discrete molecular dynamics simulations of a Gō potential combined with a full atomistic protein representation. In particular, we investigate the robustness of this particular type of Gō models in predicting the existence of intermediate states in protein folding. We focus on the N47G mutational form of the Spc-SH3 folding domain (x-ray structure) and compare its folding pathway with that of alternative native structures produced in silico. Our methodological strategy comprises equilibrium folding simulations, structural clustering, and principal component analysis.

Theoretical and software considerations for nonlinear dynamic analysis

NASA Technical Reports Server (NTRS)

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

1983-01-01

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

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.

Hidden Markov model-derived structural alphabet for proteins: the learning of protein local shapes captures sequence specificity.

PubMed

Camproux, A C; Tufféry, P

2005-08-05

Understanding and predicting protein structures depend on the complexity and the accuracy of the models used to represent them. We have recently set up a Hidden Markov Model to optimally compress protein three-dimensional conformations into a one-dimensional series of letters of a structural alphabet. Such a model learns simultaneously the shape of representative structural letters describing the local conformation and the logic of their connections, i.e. the transition matrix between the letters. Here, we move one step further and report some evidence that such a model of protein local architecture also captures some accurate amino acid features. All the letters have specific and distinct amino acid distributions. Moreover, we show that words of amino acids can have significant propensities for some letters. Perspectives point towards the prediction of the series of letters describing the structure of a protein from its amino acid sequence.

Models of metal binding structures in fulvic acid from the Suwannee River, Georgia

USGS Publications Warehouse

Leenheer, J.A.; Brown, G.K.; MacCarthy, P.; Cabaniss, S.E.

1998-01-01

Fulvic acid, isolated from the Suwannee River, Georgia, was assessed for its ability to bind Ca2+, Cd2+, Cu2+, Ni2+, and Zn2+ ions at pH 6 before and after extensive fractionation that was designed to reveal the nature of metal binding functional groups. The binding constant for Ca2+ ion had the greatest increase of all the ions in a metal binding fraction that was selected for intensive characterization for the purpose of building quantitative average model structures. The 'metal binding' fraction was characterized by quantitative 13C NMR, 1H NMR, and FT-1R spectrometry and elemental, titrimetric, and molecular weight determinations. The characterization data revealed that carboxyl groups were clustered in short- chain aliphatic dibasic acid structures. The Ca2+ binding data suggested that ether-substituted oxysuccinic acid structures are good models for the metal binding sites at pH 6. Structural models were derived based upon oxidation and photolytic rearrangements of cutin, lignin, and tannin precursors. These structural models rich in substituted dibasic acid structures revealed polydentate binding sites with the potential for both inner-sphere and outer-sphere type binding. The majority of the fulvic acid molecule was involved with metal binding rather than a small substructural unit.Fulvic acid, isolated from the Suwannee River, Georgia, was assessed for its ability to bind Ca2+, Cd2+, Cu2+, Ni2+, and Zn2+ ions at pH 6 before and after extensive fractionation that was designed to reveal the nature of metal binding functional groups. The binding constant for Ca2+ ion had the greatest increase of all the ions in a metal binding fraction that was selected for intensive characterization for the purpose of building quantitative average model structures. The `metal binding' fraction was characterized by quantitative 13C NMR, 1H NMR, and FT-IR spectrometry and elemental, titrimetric, and molecular weight determinations. The characterization data revealed that carboxyl groups were clustered in short-chain aliphatic dibasic acid structures. The Ca2+ binding data suggested that ether-substituted oxysuccinic acid structures are good models for the metal binding sites at pH 6. Structural models were derived based upon oxidation and photolytic rearrangements of cutin, lignin, and tannin precursors. These structural models rich in substituted dibasic acid structures revealed polydentate binding sites with the potential for both inner-sphere and outer-sphere type binding. The majority of the fulvic acid molecule was involved with metal binding rather than a small substructural unit.

In Silico Analysis for the Study of Botulinum Toxin Structure

NASA Astrophysics Data System (ADS)

Suzuki, Tomonori; Miyazaki, Satoru

2010-01-01

Protein-protein interactions play many important roles in biological function. Knowledge of protein-protein complex structure is required for understanding the function. The determination of protein-protein complex structure by experimental studies remains difficult, therefore computational prediction of protein structures by structure modeling and docking studies is valuable method. In addition, MD simulation is also one of the most popular methods for protein structure modeling and characteristics. Here, we attempt to predict protein-protein complex structure and property using some of bioinformatic methods, and we focus botulinum toxin complex as target structure.

Extending existing structural identifiability analysis methods to mixed-effects models.

PubMed

Janzén, David L I; Jirstrand, Mats; Chappell, Michael J; Evans, Neil D

2018-01-01

The concept of structural identifiability for state-space models is expanded to cover mixed-effects state-space models. Two methods applicable for the analytical study of the structural identifiability of mixed-effects models are presented. The two methods are based on previously established techniques for non-mixed-effects models; namely the Taylor series expansion and the input-output form approach. By generating an exhaustive summary, and by assuming an infinite number of subjects, functions of random variables can be derived which in turn determine the distribution of the system's observation function(s). By considering the uniqueness of the analytical statistical moments of the derived functions of the random variables, the structural identifiability of the corresponding mixed-effects model can be determined. The two methods are applied to a set of examples of mixed-effects models to illustrate how they work in practice. Copyright © 2017 Elsevier Inc. All rights reserved.

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

Los Alamos National Laboratory, Mailstop M888, Los Alamos, NM 87545, USA; Lawrence Berkeley National Laboratory, One Cyclotron Road, Building 64R0121, Berkeley, CA 94720, USA; Department of Haematology, University of Cambridge, Cambridge CB2 0XY, England

The PHENIX AutoBuild Wizard is a highly automated tool for iterative model-building, structure refinement and density modification using RESOLVE or TEXTAL model-building, RESOLVE statistical density modification, and phenix.refine structure refinement. Recent advances in the AutoBuild Wizard and phenix.refine include automated detection and application of NCS from models as they are built, extensive model completion algorithms, and automated solvent molecule picking. Model completion algorithms in the AutoBuild Wizard include loop-building, crossovers between chains in different models of a structure, and side-chain optimization. The AutoBuild Wizard has been applied to a set of 48 structures at resolutions ranging from 1.1 {angstrom} tomore » 3.2 {angstrom}, resulting in a mean R-factor of 0.24 and a mean free R factor of 0.29. The R-factor of the final model is dependent on the quality of the starting electron density, and relatively independent of resolution.« less

Estimating, Testing, and Comparing Specific Effects in Structural Equation Models: The Phantom Model Approach

ERIC Educational Resources Information Center

Macho, Siegfried; Ledermann, Thomas

2011-01-01

The phantom model approach for estimating, testing, and comparing specific effects within structural equation models (SEMs) is presented. The rationale underlying this novel method consists in representing the specific effect to be assessed as a total effect within a separate latent variable model, the phantom model that is added to the main…

Level-Specific Evaluation of Model Fit in Multilevel Structural Equation Modeling

ERIC Educational Resources Information Center

Ryu, Ehri; West, Stephen G.

2009-01-01

In multilevel structural equation modeling, the "standard" approach to evaluating the goodness of model fit has a potential limitation in detecting the lack of fit at the higher level. Level-specific model fit evaluation can address this limitation and is more informative in locating the source of lack of model fit. We proposed level-specific test…

Outdoor Program Models: Placing Cooperative Adventure and Adventure Education Models on the Continuum.

ERIC Educational Resources Information Center

Guthrie, Steven P.

In two articles on outdoor programming models, Watters distinguished four models on a continuum ranging from the common adventure model, with minimal organizational structure and leadership control, to the guide service model, in which leaders are autocratic and trips are highly structured. Club programs and instructional programs were in between,…

Probing the structure of Leishmania major DHFR TS and structure based virtual screening of peptide library for the identification of anti-leishmanial leads.

PubMed

Rajasekaran, Rajalakshmi; Chen, Yi-Ping Phoebe

2012-09-01

Leishmaniasis, a multi-faceted ethereal disease is considered to be one of the World's major communicable diseases that demands exhaustive research and control measures. The substantial data on these protozoan parasites has not been utilized completely to develop potential therapeutic strategies against Leishmaniasis. Dihydrofolate reductase thymidylate synthase (DHFR-TS) plays a major role in the infective state of the parasite and hence the DHFR-TS based drugs remains of much interest to researchers working on Leishmaniasis. Although, crystal structures of DHFR-TS from different species including Plasmodium falciparum and Trypanosoma cruzi are available, the experimentally determined structure of the Leishmania major DHFR-TS has not yet been reported in the Protein Data Bank. A high quality three dimensional structure of L.major DHFR-TS has been modeled through the homology modeling approach. Carefully refined and the energy minimized structure of the modeled protein was validated using a number of structure validation programs to confirm its structure quality. The modeled protein structure was used in the process of structure based virtual screening to figure out a potential lead structure against DHFR TS. The lead molecule identified has a binding affinity of 0.51 nM and clearly follows drug like properties.

Observing and modelling phytoplankton community structure in the North Sea

NASA Astrophysics Data System (ADS)

Ford, David A.; van der Molen, Johan; Hyder, Kieran; Bacon, John; Barciela, Rosa; Creach, Veronique; McEwan, Robert; Ruardij, Piet; Forster, Rodney

2017-03-01

Phytoplankton form the base of the marine food chain, and knowledge of phytoplankton community structure is fundamental when assessing marine biodiversity. Policy makers and other users require information on marine biodiversity and other aspects of the marine environment for the North Sea, a highly productive European shelf sea. This information must come from a combination of observations and models, but currently the coastal ocean is greatly under-sampled for phytoplankton data, and outputs of phytoplankton community structure from models are therefore not yet frequently validated. This study presents a novel set of in situ observations of phytoplankton community structure for the North Sea using accessory pigment analysis. The observations allow a good understanding of the patterns of surface phytoplankton biomass and community structure in the North Sea for the observed months of August 2010 and 2011. Two physical-biogeochemical ocean models, the biogeochemical components of which are different variants of the widely used European Regional Seas Ecosystem Model (ERSEM), were then validated against these and other observations. Both models were a good match for sea surface temperature observations, and a reasonable match for remotely sensed ocean colour observations. However, the two models displayed very different phytoplankton community structures, with one better matching the in situ observations than the other. Nonetheless, both models shared some similarities with the observations in terms of spatial features and inter-annual variability. An initial comparison of the formulations and parameterizations of the two models suggests that diversity between the parameter settings of model phytoplankton functional types, along with formulations which promote a greater sensitivity to changes in light and nutrients, is key to capturing the observed phytoplankton community structure. These findings will help inform future model development, which should be coupled with detailed validation studies, in order to help facilitate the wider application of marine biogeochemical modelling to user and policy needs.

The influence of vegetation height heterogeneity on forest and woodland bird species richness across the United States.

PubMed

Huang, Qiongyu; Swatantran, Anu; Dubayah, Ralph; Goetz, Scott J

2014-01-01

Avian diversity is under increasing pressures. It is thus critical to understand the ecological variables that contribute to large scale spatial distribution of avian species diversity. Traditionally, studies have relied primarily on two-dimensional habitat structure to model broad scale species richness. Vegetation vertical structure is increasingly used at local scales. However, the spatial arrangement of vegetation height has never been taken into consideration. Our goal was to examine the efficacies of three-dimensional forest structure, particularly the spatial heterogeneity of vegetation height in improving avian richness models across forested ecoregions in the U.S. We developed novel habitat metrics to characterize the spatial arrangement of vegetation height using the National Biomass and Carbon Dataset for the year 2000 (NBCD). The height-structured metrics were compared with other habitat metrics for statistical association with richness of three forest breeding bird guilds across Breeding Bird Survey (BBS) routes: a broadly grouped woodland guild, and two forest breeding guilds with preferences for forest edge and for interior forest. Parametric and non-parametric models were built to examine the improvement of predictability. Height-structured metrics had the strongest associations with species richness, yielding improved predictive ability for the woodland guild richness models (r(2) = ∼ 0.53 for the parametric models, 0.63 the non-parametric models) and the forest edge guild models (r(2) = ∼ 0.34 for the parametric models, 0.47 the non-parametric models). All but one of the linear models incorporating height-structured metrics showed significantly higher adjusted-r2 values than their counterparts without additional metrics. The interior forest guild richness showed a consistent low association with height-structured metrics. Our results suggest that height heterogeneity, beyond canopy height alone, supplements habitat characterization and richness models of forest bird species. The metrics and models derived in this study demonstrate practical examples of utilizing three-dimensional vegetation data for improved characterization of spatial patterns in species richness.

Nonlinear interaction between underwater explosion bubble and structure based on fully coupled model

NASA Astrophysics Data System (ADS)

Zhang, A. M.; Wu, W. B.; Liu, Y. L.; Wang, Q. X.

2017-08-01

The interaction between an underwater explosion bubble and an elastic-plastic structure is a complex transient process, accompanying violent bubble collapsing, jet impact, penetration through the bubble, and large structural deformation. In the present study, the bubble dynamics are modeled using the boundary element method and the nonlinear transient structural response is modeled using the explicit finite element method. A new fully coupled 3D model is established through coupling the equations for the state variables of the fluid and structure and solving them as a set of coupled linear algebra equations. Based on the acceleration potential theory, the mutual dependence between the hydrodynamic load and the structural motion is decoupled. The pressure distribution in the flow field is calculated with the Bernoulli equation, where the partial derivative of the velocity potential in time is calculated using the boundary integral method to avoid numerical instabilities. To validate the present fully coupled model, the experiments of small-scale underwater explosion near a stiffened plate are carried out. High-speed imaging is used to capture the bubble behaviors and strain gauges are used to measure the strain response. The numerical results correspond well with the experimental data, in terms of bubble shapes and structural strain response. By both the loosely coupled model and the fully coupled model, the interaction between a bubble and a hollow spherical shell is studied. The bubble patterns vary with different parameters. When the fully coupled model and the loosely coupled model are advanced with the same time step, the error caused by the loosely coupled model becomes larger with the coupling effect becoming stronger. The fully coupled model is more stable than the loosely coupled model. Besides, the influences of the internal fluid on the dynamic response of the spherical shell are studied. At last, the case that the bubble interacts with an air-backed stiffened plate is simulated. The associated interesting physical phenomenon is obtained and expounded.

The Influence of Vegetation Height Heterogeneity on Forest and Woodland Bird Species Richness across the United States

PubMed Central

Huang, Qiongyu; Swatantran, Anu; Dubayah, Ralph; Goetz, Scott J.

2014-01-01

Avian diversity is under increasing pressures. It is thus critical to understand the ecological variables that contribute to large scale spatial distribution of avian species diversity. Traditionally, studies have relied primarily on two-dimensional habitat structure to model broad scale species richness. Vegetation vertical structure is increasingly used at local scales. However, the spatial arrangement of vegetation height has never been taken into consideration. Our goal was to examine the efficacies of three-dimensional forest structure, particularly the spatial heterogeneity of vegetation height in improving avian richness models across forested ecoregions in the U.S. We developed novel habitat metrics to characterize the spatial arrangement of vegetation height using the National Biomass and Carbon Dataset for the year 2000 (NBCD). The height-structured metrics were compared with other habitat metrics for statistical association with richness of three forest breeding bird guilds across Breeding Bird Survey (BBS) routes: a broadly grouped woodland guild, and two forest breeding guilds with preferences for forest edge and for interior forest. Parametric and non-parametric models were built to examine the improvement of predictability. Height-structured metrics had the strongest associations with species richness, yielding improved predictive ability for the woodland guild richness models (r2 = ∼0.53 for the parametric models, 0.63 the non-parametric models) and the forest edge guild models (r2 = ∼0.34 for the parametric models, 0.47 the non-parametric models). All but one of the linear models incorporating height-structured metrics showed significantly higher adjusted-r2 values than their counterparts without additional metrics. The interior forest guild richness showed a consistent low association with height-structured metrics. Our results suggest that height heterogeneity, beyond canopy height alone, supplements habitat characterization and richness models of forest bird species. The metrics and models derived in this study demonstrate practical examples of utilizing three-dimensional vegetation data for improved characterization of spatial patterns in species richness. PMID:25101782

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 foamed structures in numerical testing

NASA Astrophysics Data System (ADS)

John, Antoni; John, Małgorzata

2018-01-01

In the paper numerical simulation of the foamed metal structures using numerical homogenization algorithm is prescribed. From the beginning, numerical model of heterogeneous porous simplified structures of typical foamed metal, based on the FEM was built and material parameters (coefficients of elasticity matrix of the considered structure) were determined with use of numerical homogenization algorithm. During the work the different RVE models of structure were created and their properties were compared at different relative density, different numbers and the size and structure of the arrangement of voids. Finally, obtained results were used in modeling of typical elements made from foam metals structures - sandwich structure and profile filled with metal foam. Simulation were performed for different dimensions of cladding and core. Additionally, the test of influence material orientation (arrangement of voids in RVE element) on the maximum stresses and displacement during bending test was performed.

Analysis of whisker-toughened CMC structural components using an interactive reliability model

NASA Technical Reports Server (NTRS)

Duffy, Stephen F.; Palko, Joseph L.

1992-01-01

Realizing wider utilization of ceramic matrix composites (CMC) requires the development of advanced structural analysis technologies. This article focuses on the use of interactive reliability models to predict component probability of failure. The deterministic William-Warnke failure criterion serves as theoretical basis for the reliability model presented here. The model has been implemented into a test-bed software program. This computer program has been coupled to a general-purpose finite element program. A simple structural problem is presented to illustrate the reliability model and the computer algorithm.

Developing Regionalized Models of Lithospheric Thickness and Velocity Structure Across Eurasia and the Middle East from Jointly Inverting P-Wave and S-Wave Receiver Functions with Rayleigh Wave Group and Phase Velocities

DTIC Science & Technology

2010-09-01

lithospheric velocity structure for a wide variety of tectonic regions throughout Eurasia and the Middle East. We expect the regionalized models will improve...constructed by combining the 1D joint inversion models within each tectonic region and validated through regional waveform modeling. The velocity models thus...important differences in lithospheric structure between the cratonic regions of Eastern Europe and the tectonic regions of Western Europe and the

Structural models for nickel electrode active mass

NASA Technical Reports Server (NTRS)

Cornilsen, Bahne C.; Karjala, P. J.; Loyselle, P. L.

1987-01-01

Raman spectroscopic data allow one to distinguish nickel electrode active mass, alpha and beta phase materials. Discharges active mass is not isostructural with beta-Ni(OH)2. This is contrary to the generally accepted model for the discharged beta phase of active mass. It is concluded that charged active mass displays a disordered and nonstoichiometric, nonclose packed structure of the R3 bar m, NiOOH structure type. Raman spectral data and x ray diffraction data are analyzed and shown to be consistent with this structural model.

A gravity model for the Sudbury Structure along the Lithoprobe seismic line

NASA Astrophysics Data System (ADS)

McGrath, P. H.; Broome, H. J.

1994-05-01

Previous gravity models of the Sudbury Structure (1850 Ma) were constrained by surface geology, and by density measurements of surface and borehole rock samples. Recent high-resolution seismic reflection data provide additional constraints for modeling new gravity observations made along the Sudbury Lithoprobe transect. Results indicate, (1) density distributions constrained by the seismic data yield calculated gravity values matching the Bouguer gravity data, (2) the main sources of gravitational disturbance are external to the Sudbury Structure, (3) the positive gravity anomaly trend south of the Sudbury Structure is associated with mafic rocks of Proterozoic age, and (4) the large, ramplike, gravity anomaly paralleling the northwest margin of the Sudbury Structure is an expression of a northward dipping boundary within the Archean basement. The presence of a hidden mafic layer beneath the Sudbury Structure is not required to model the Bouguer gravity data. An enigma is an 8 mGal, positive, gravity anomaly over the south central Sudbury Structure.

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

NASA Technical Reports Server (NTRS)

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

2013-01-01

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

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

PubMed Central

Kmiecik, Sebastian; Jamroz, Michal; Kolinski, Michal

2014-01-01

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

Model Comparison of Nonlinear Structural Equation Models with Fixed Covariates.

ERIC Educational Resources Information Center

Lee, Sik-Yum; Song, Xin-Yuan

2003-01-01

Proposed a new nonlinear structural equation model with fixed covariates to deal with some complicated substantive theory and developed a Bayesian path sampling procedure for model comparison. Illustrated the approach with an illustrative example using data from an international study. (SLD)

Outer planet probe engineering model structural tests

NASA Technical Reports Server (NTRS)

Smittkamp, J. A.; Gustin, W. H.; Griffin, M. W.

1977-01-01

A series of proof of concept structural tests was performed on an engineering model of the Outer Planets Atmospheric Entry Probe. The tests consisted of pyrotechnic shock, dynamic and static loadings. The tests partially verified the structural concept.

On correction of model of stabilization of distribution of concentration of radiation defects in a multilayer structure with account experiment data

NASA Astrophysics Data System (ADS)

Pankratov, E. L.

2018-05-01

We introduce a model of redistribution of point radiation defects, their interaction between themselves and redistribution of their simplest complexes (divacancies and diinterstitials) in a multilayer structure. The model gives a possibility to describe qualitatively nonmonotonicity of distributions of concentrations of radiation defects on interfaces between layers of the multilayer structure. The nonmonotonicity was recently found experimentally. To take into account the nonmonotonicity we modify recently used in literature model for analysis of distribution of concentration of radiation defects. To analyze the model we used an approach of solution of boundary problems, which could be used without crosslinking of solutions on interfaces between layers of the considered multilayer structures.

Structural Equation Model Trees

PubMed Central

Brandmaier, Andreas M.; von Oertzen, Timo; McArdle, John J.; Lindenberger, Ulman

2015-01-01

In the behavioral and social sciences, structural equation models (SEMs) have become widely accepted as a modeling tool for the relation between latent and observed variables. SEMs can be seen as a unification of several multivariate analysis techniques. SEM Trees combine the strengths of SEMs and the decision tree paradigm by building tree structures that separate a data set recursively into subsets with significantly different parameter estimates in a SEM. SEM Trees provide means for finding covariates and covariate interactions that predict differences in structural parameters in observed as well as in latent space and facilitate theory-guided exploration of empirical data. We describe the methodology, discuss theoretical and practical implications, and demonstrate applications to a factor model and a linear growth curve model. PMID:22984789

Variable structure control of nonlinear systems through simplified uncertain models

NASA Technical Reports Server (NTRS)

Sira-Ramirez, Hebertt

1986-01-01

A variable structure control approach is presented for the robust stabilization of feedback equivalent nonlinear systems whose proposed model lies in the same structural orbit of a linear system in Brunovsky's canonical form. An attempt to linearize exactly the nonlinear plant on the basis of the feedback control law derived for the available model results in a nonlinearly perturbed canonical system for the expanded class of possible equivalent control functions. Conservatism tends to grow as modeling errors become larger. In order to preserve the internal controllability structure of the plant, it is proposed that model simplification be carried out on the open-loop-transformed system. As an example, a controller is developed for a single link manipulator with an elastic joint.

Finite Rotation Analysis of Highly Thin and Flexible Structures

NASA Technical Reports Server (NTRS)

Clarke, Greg V.; Lee, Keejoo; Lee, Sung W.; Broduer, Stephen J. (Technical Monitor)

2001-01-01

Deployable space structures such as sunshields and solar sails are extremely thin and highly flexible with limited bending rigidity. For analytical investigation of their responses during deployment and operation in space, these structures can be modeled as thin shells. The present work examines the applicability of the solid shell element formulation to modeling of deployable space structures. The solid shell element formulation that models a shell as a three-dimensional solid is convenient in that no rotational parameters are needed for the description of kinematics of deformation. However, shell elements may suffer from element locking as the thickness becomes smaller unless special care is taken. It is shown that, when combined with the assumed strain formulation, the solid shell element formulation results in finite element models that are free of locking even for extremely thin structures. Accordingly, they can be used for analysis of highly flexible space structures undergoing geometrically nonlinear finite rotations.

Structural modeling for multicell composite rotor blades

NASA Technical Reports Server (NTRS)

Rehfield, Lawrence W.; Atilgan, Ali R.

1987-01-01

Composite material systems are currently good candidates for aerospace structures, primarily for the design flexibility they offer, i.e., it is possible to tailor the material and manufacturing approach to the application. A working definition of elastic or structural tailoring is the use of structural concept, fiber orientation, ply stacking sequence, and a blend of materials to achieve specific performance goals. In the design process, choices of materials and dimensions are made which produce specific response characteristics, and which permit the selected goals to be achieved. Common choices for tailoring goals are preventing instabilities or vibration resonances or enhancing damage tolerance. An essential, enabling factor in the design of tailored composite structures is structural modeling that accurately, but simply, characterizes response. The objective of this paper is to present a new multicell beam model for composite rotor blades and to validate predictions based on the new model by comparison with a finite element simulation in three benchmark static load cases.

An Integrated Approach Linking Process to Structural Modeling With Microstructural Characterization for Injections-Molded Long-Fiber Thermoplastics

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

Nguyen, Ba Nghiep; Bapanapalli, Satish K.; Smith, Mark T.

2008-09-01

The objective of our work is to enable the optimum design of lightweight automotive structural components using injection-molded long fiber thermoplastics (LFTs). To this end, an integrated approach that links process modeling to structural analysis with experimental microstructural characterization and validation is developed. First, process models for LFTs are developed and implemented into processing codes (e.g. ORIENT, Moldflow) to predict the microstructure of the as-formed composite (i.e. fiber length and orientation distributions). In parallel, characterization and testing methods are developed to obtain necessary microstructural data to validate process modeling predictions. Second, the predicted LFT composite microstructure is imported into amore » structural finite element analysis by ABAQUS to determine the response of the as-formed composite to given boundary conditions. At this stage, constitutive models accounting for the composite microstructure are developed to predict various types of behaviors (i.e. thermoelastic, viscoelastic, elastic-plastic, damage, fatigue, and impact) of LFTs. Experimental methods are also developed to determine material parameters and to validate constitutive models. Such a process-linked-structural modeling approach allows an LFT composite structure to be designed with confidence through numerical simulations. Some recent results of our collaborative research will be illustrated to show the usefulness and applications of this integrated approach.« less

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

PubMed

Metler, Samantha J; Busseri, Michael A

2017-04-01

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

Modeling Of Object- And Scene-Prototypes With Hierarchically Structured Classes

NASA Astrophysics Data System (ADS)

Ren, Z.; Jensch, P.; Ameling, W.

1989-03-01

The success of knowledge-based image analysis methodology and implementation tools depends largely on an appropriately and efficiently built model wherein the domain-specific context information about and the inherent structure of the observed image scene have been encoded. For identifying an object in an application environment a computer vision system needs to know firstly the description of the object to be found in an image or in an image sequence, secondly the corresponding relationships between object descriptions within the image sequence. This paper presents models of image objects scenes by means of hierarchically structured classes. Using the topovisual formalism of graph and higraph, we are currently studying principally the relational aspect and data abstraction of the modeling in order to visualize the structural nature resident in image objects and scenes, and to formalize. their descriptions. The goal is to expose the structure of image scene and the correspondence of image objects in the low level image interpretation. process. The object-based system design approach has been applied to build the model base. We utilize the object-oriented programming language C + + for designing, testing and implementing the abstracted entity classes and the operation structures which have been modeled topovisually. The reference images used for modeling prototypes of objects and scenes are from industrial environments as'well as medical applications.

Ion-acoustic and electron-acoustic type nonlinear waves in dusty plasmas

NASA Astrophysics Data System (ADS)

Volosevich, A.-V.; Meister, C.-V.

2003-04-01

In the present work, two three-dimensional nonlinear theoretical models of electrostatic solitary waves are investigated within the frame of magnetohydrodynamics. Both times, a multi-component plasma is considered, which consists of hot electrons with a rather flexible distribution function, hot ions with Boltzmann-type distribution, and (negatively as well as positively charged) dust. Additionally, cold ion beams are taken into account in the model to study ion-acoustic structures (IAS), and cold electron beams are included into the model to investigate electron-acoustic structures (EAS). The numerical results of the considered theoretical models allow to make the following conclusions: 1) Electrostatic structures with negative potential (of rarefaction type) are formed both in the IAS model and in the EAS model, but structures with negative potential (of compressional type) are formed in the IAS model only. 2) The intervals of various plasma parameters (velocities of ion and electron beams, temperatures, densities of the plasma components, ions' masses), for which the existence of IAS and EAS solitary waves and structures is possible, are calculated. 3) Further, the parameters of the electrostatic structures (wave amplitudes, scales along and perpendicular to the magnetic field, velocities) are estimated. 4) The application of the present numerical simulation for multi-component plasmas to various astrophysical systems under different physical conditions is discussed.

Fast flexible modeling of RNA structure using internal coordinates.

PubMed

Flores, Samuel Coulbourn; Sherman, Michael A; Bruns, Christopher M; Eastman, Peter; Altman, Russ Biagio

2011-01-01

Modeling the structure and dynamics of large macromolecules remains a critical challenge. Molecular dynamics (MD) simulations are expensive because they model every atom independently, and are difficult to combine with experimentally derived knowledge. Assembly of molecules using fragments from libraries relies on the database of known structures and thus may not work for novel motifs. Coarse-grained modeling methods have yielded good results on large molecules but can suffer from difficulties in creating more detailed full atomic realizations. There is therefore a need for molecular modeling algorithms that remain chemically accurate and economical for large molecules, do not rely on fragment libraries, and can incorporate experimental information. RNABuilder works in the internal coordinate space of dihedral angles and thus has time requirements proportional to the number of moving parts rather than the number of atoms. It provides accurate physics-based response to applied forces, but also allows user-specified forces for incorporating experimental information. A particular strength of RNABuilder is that all Leontis-Westhof basepairs can be specified as primitives by the user to be satisfied during model construction. We apply RNABuilder to predict the structure of an RNA molecule with 160 bases from its secondary structure, as well as experimental information. Our model matches the known structure to 10.2 Angstroms RMSD and has low computational expense.

Organizational Structure and Design in Higher Education: A Literature Review of Organizational Structures in Higher Education with a Focus on the Co-Existence of Academic and Non-Academic Structures.

ERIC Educational Resources Information Center

White, Auston E.

Two structures of authority coexist in colleges and universities: one that manages the supporting functional services and one that deals with the production areas of scholarship, teaching, and learning. This literature review defines organizational structure, discusses traditional organization models such as bureaucratic models, and outlines the…

Experiments in Sound and Structural Vibrations Using an Air-Analog Model Ducted Propulsion System

DTIC Science & Technology

2007-08-01

Department of Aerospace S~and Mechanical Engineering I 20070904056 I EXPERIMENTS IN SOUND AND STRUCTURAL VIBRATIONS USING AN AIR -ANALOG MODEL DUCTED...SOUND AND STRUCTURAL * VIBRATIONS USING AN AIR -ANALOG MODEL DUCTED PROPULSION SYSTEM FINAL TECHNICAL REPORT Prepared by: Scott C. Morris Assistant...Vibration Using Air - 5b. GRANT NUMBER Analog Model Ducted Propulsion Systems N00014-1-0522 5C. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER

Near Identifiability of Dynamical Systems

NASA Technical Reports Server (NTRS)

Hadaegh, F. Y.; Bekey, G. A.

1987-01-01

Concepts regarding approximate mathematical models treated rigorously. Paper presents new results in analysis of structural identifiability, equivalence, and near equivalence between mathematical models and physical processes they represent. Helps establish rigorous mathematical basis for concepts related to structural identifiability and equivalence revealing fundamental requirements, tacit assumptions, and sources of error. "Structural identifiability," as used by workers in this field, loosely translates as meaning ability to specify unique mathematical model and set of model parameters that accurately predict behavior of corresponding physical system.

Incorporation of composite defects from ultrasonic NDE into CAD and FE models

NASA Astrophysics Data System (ADS)

Bingol, Onur Rauf; Schiefelbein, Bryan; Grandin, Robert J.; Holland, Stephen D.; Krishnamurthy, Adarsh

2017-02-01

Fiber-reinforced composites are widely used in aerospace industry due to their combined properties of high strength and low weight. However, owing to their complex structure, it is difficult to assess the impact of manufacturing defects and service damage on their residual life. While, ultrasonic testing (UT) is the preferred NDE method to identify the presence of defects in composites, there are no reasonable ways to model the damage and evaluate the structural integrity of composites. We have developed an automated framework to incorporate flaws and known composite damage automatically into a finite element analysis (FEA) model of composites, ultimately aiding in accessing the residual life of composites and make informed decisions regarding repairs. The framework can be used to generate a layer-by-layer 3D structural CAD model of the composite laminates replicating their manufacturing process. Outlines of structural defects, such as delaminations, are automatically detected from UT of the laminate and are incorporated into the CAD model between the appropriate layers. In addition, the framework allows for direct structural analysis of the resulting 3D CAD models with defects by automatically applying the appropriate boundary conditions. In this paper, we show a working proof-of-concept for the composite model builder with capabilities of incorporating delaminations between laminate layers and automatically preparing the CAD model for structural analysis using a FEA software.

A general model-based design of experiments approach to achieve practical identifiability of pharmacokinetic and pharmacodynamic models.

PubMed

Galvanin, Federico; Ballan, Carlo C; Barolo, Massimiliano; Bezzo, Fabrizio

2013-08-01

The use of pharmacokinetic (PK) and pharmacodynamic (PD) models is a common and widespread practice in the preliminary stages of drug development. However, PK-PD models may be affected by structural identifiability issues intrinsically related to their mathematical formulation. A preliminary structural identifiability analysis is usually carried out to check if the set of model parameters can be uniquely determined from experimental observations under the ideal assumptions of noise-free data and no model uncertainty. However, even for structurally identifiable models, real-life experimental conditions and model uncertainty may strongly affect the practical possibility to estimate the model parameters in a statistically sound way. A systematic procedure coupling the numerical assessment of structural identifiability with advanced model-based design of experiments formulations is presented in this paper. The objective is to propose a general approach to design experiments in an optimal way, detecting a proper set of experimental settings that ensure the practical identifiability of PK-PD models. Two simulated case studies based on in vitro bacterial growth and killing models are presented to demonstrate the applicability and generality of the methodology to tackle model identifiability issues effectively, through the design of feasible and highly informative experiments.

Building a model of the blue cone pigment based on the wild type rhodopsin structure with QM/MM methods.

PubMed

Frähmcke, Jan S; Wanko, Marius; Elstner, Marcus

2012-03-15

Understanding the mechanism of color tuning of the retinal chromophore by its host protein became one of the key issues in the research on rhodopsins. While early mutation studies addressed its genetic origin, recent studies advanced to investigate its structural origin, based on X-ray crystallographic structures. For the human cone pigments, no crystal structures have been produced, and homology models were employed to elucidate the origin of its blue-shifted absorption. In this theoretical study, we take a different route to establish a structural model for human blue. Starting from the well-resolved structure of bovine rhodopsin, we derive multiple mutant models by stepwise mutation and equilibration using molecular dynamics simulations in a hybrid quantum mechanics/molecular mechanics framework. Our 30fold mutant reproduces the experimental UV-vis absorption shift of 0.45 eV and provides new insights about both structural and genetic factors that affect the excitation energy. Electrostatic effects of individual amino acids and collaborative structural effects are analyzed using semiempirical (OM2/MRCI) and ab initio (SORCI) multireference approaches. © 2012 American Chemical Society

Structural simplicity as a restraint on the structure of amorphous silicon

NASA Astrophysics Data System (ADS)

Cliffe, Matthew J.; Bartók, Albert P.; Kerber, Rachel N.; Grey, Clare P.; Csányi, Gábor; Goodwin, Andrew L.

2017-06-01

Understanding the structural origins of the properties of amorphous materials remains one of the most important challenges in structural science. In this study, we demonstrate that local "structural simplicity", embodied by the degree to which atomic environments within a material are similar to each other, is a powerful concept for rationalizing the structure of amorphous silicon (a -Si) a canonical amorphous material. We show, by restraining a reverse Monte Carlo refinement against pair distribution function (PDF) data to be simpler, that the simplest model consistent with the PDF is a continuous random network (CRN). A further effect of producing a simple model of a -Si is the generation of a (pseudo)gap in the electronic density of states, suggesting that structural homogeneity drives electronic homogeneity. That this method produces models of a -Si that approach the state-of-the-art without the need for chemically specific restraints (beyond the assumption of homogeneity) suggests that simplicity-based refinement approaches may allow experiment-driven structural modeling techniques to be developed for the wide variety of amorphous semiconductors with strong local order.

Gravity profiles across the Uyaijah Ring structure, Kingdom of Saudi Arabia

USGS Publications Warehouse

Gettings, M.E.; Andreasen, G.E.

1987-01-01

The resulting structural model, based on profile fits to gravity responses of three-dimensional models and excess-mass calculations, gives a depth estimate to the base of the complex of 4.75 km. The contacts of the complex are inferred to be steeply dipping inward along the southwest margin of the structure. To the north and east, however, the basal contact of the complex dips more gently inward (about 30 degrees). The ring structure appears to be composed of three laccolith-shaped plutons; two are granitic in composition and make up about 85 percent of the volume of the complex, and one is granodioritic and comprises the remaining 15 percent. The source area for the plutons appears to be in the southwest quadrant of the Uyaijah ring structure. A northwest-trending shear zone cuts the northern half of the structure and contains mafic dikes that have a small but identifiable gravity-anomaly response. The structural model agrees with models derived from geological interpretation except that the estimated depth to which the structure extends is decreased considerably by the gravity results.

Evaluation of 3D-Jury on CASP7 models

PubMed Central

Kaján, László; Rychlewski, Leszek

2007-01-01

Background 3D-Jury, the structure prediction consensus method publicly available in the Meta Server , was evaluated using models gathered in the 7th round of the Critical Assessment of Techniques for Protein Structure Prediction (CASP7). 3D-Jury is an automated expert process that generates protein structure meta-predictions from sets of models obtained from partner servers. Results The performance of 3D-Jury was analysed for three aspects. First, we examined the correlation between the 3D-Jury score and a model quality measure: the number of correctly predicted residues. The 3D-Jury score was shown to correlate significantly with the number of correctly predicted residues, the correlation is good enough to be used for prediction. 3D-Jury was also found to improve upon the competing servers' choice of the best structure model in most cases. The value of the 3D-Jury score as a generic reliability measure was also examined. We found that the 3D-Jury score separates bad models from good models better than the reliability score of the original server in 27 cases and falls short of it in only 5 cases out of a total of 38. We report the release of a new Meta Server feature: instant 3D-Jury scoring of uploaded user models. Conclusion The 3D-Jury score continues to be a good indicator of structural model quality. It also provides a generic reliability score, especially important for models that were not assigned such by the original server. Individual structure modellers can also benefit from the 3D-Jury scoring system by testing their models in the new instant scoring feature available in the Meta Server. PMID:17711571

Evaluation of a model of violence risk assessment among forensic psychiatric patients.

PubMed

Douglas, Kevin S; Ogloff, James R P; Hart, Stephen D

2003-10-01

This study tested the interrater reliability and criterion-related validity of structured violence risk judgments made by using one application of the structured professional judgment model of violence risk assessment, the HCR-20 violence risk assessment scheme, which assesses 20 key risk factors in three domains: historical, clinical, and risk management. The HCR-20 was completed for a sample of 100 forensic psychiatric patients who had been found not guilty by reason of a mental disorder and were subsequently released to the community. Violence in the community was determined from multiple file-based sources. Interrater reliability of structured final risk judgments of low, moderate, or high violence risk made on the basis of the structured professional judgment model was acceptable (weighted kappa=.61). Structured final risk judgments were significantly predictive of postrelease community violence, yielding moderate to large effect sizes. Event history analyses showed that final risk judgments made with the structured professional judgment model added incremental validity to the HCR-20 used in an actuarial (numerical) sense. The findings support the structured professional judgment model of risk assessment as well as the HCR-20 specifically and suggest that clinical judgment, if made within a structured context, can contribute in meaningful ways to the assessment of violence risk.

Is Small Still Beautiful for the Strengths and Difficulties Questionnaire? Novel Findings Using Exploratory Structural Equation Modeling.

PubMed

Garrido, Luis Eduardo; Barrada, Juan Ramón; Aguasvivas, José Armando; Martínez-Molina, Agustín; Arias, Víctor B; Golino, Hudson F; Legaz, Eva; Ferrís, Gloria; Rojo-Moreno, Luis

2018-06-01

During the present decade a large body of research has employed confirmatory factor analysis (CFA) to evaluate the factor structure of the Strengths and Difficulties Questionnaire (SDQ) across multiple languages and cultures. However, because CFA can produce strongly biased estimations when the population cross-loadings differ meaningfully from zero, it may not be the most appropriate framework to model the SDQ responses. With this in mind, the current study sought to assess the factorial structure of the SDQ using the more flexible exploratory structural equation modeling approach. Using a large-scale Spanish sample composed of 67,253 youths aged between 10 and 18 years ( M = 14.16, SD = 1.07), the results showed that CFA provided a severely biased and overly optimistic assessment of the underlying structure of the SDQ. In contrast, exploratory structural equation modeling revealed a generally weak factorial structure, including questionable indicators with large cross-loadings, multiple error correlations, and significant wording variance. A subsequent Monte Carlo study showed that sample sizes greater than 4,000 would be needed to adequately recover the SDQ loading structure. The findings from this study prevent recommending the SDQ as a screening tool and suggest caution when interpreting previous results in the literature based on CFA modeling.

The modified turning bands (MTB) model for space-time rainfall. I. Model definition and properties

NASA Astrophysics Data System (ADS)

Mellor, Dale

1996-02-01

A new stochastic model of space-time rainfall, the Modified Turning Bands (MTB) model, is proposed which reproduces, in particular, the movements and developments of rainbands, cluster potential regions and raincells, as well as their respective interactions. The ensemble correlation structure is unsuitable for practical estimation of the model parameters because the model is not ergodic in this statistic, and hence it cannot easily be measured from a single real storm. Thus, some general theory on the internal covariance structure of a class of stochastic models is presented, of which the MTB model is an example. It is noted that, for the MTB model, the internal covariance structure may be measured from a single storm, and can thus be used for model identification.

Quantifying model-structure- and parameter-driven uncertainties in spring wheat phenology prediction with Bayesian analysis

DOE PAGES

Alderman, Phillip D.; Stanfill, Bryan

2016-10-06

Recent international efforts have brought renewed emphasis on the comparison of different agricultural systems models. Thus far, analysis of model-ensemble simulated results has not clearly differentiated between ensemble prediction uncertainties due to model structural differences per se and those due to parameter value uncertainties. Additionally, despite increasing use of Bayesian parameter estimation approaches with field-scale crop models, inadequate attention has been given to the full posterior distributions for estimated parameters. The objectives of this study were to quantify the impact of parameter value uncertainty on prediction uncertainty for modeling spring wheat phenology using Bayesian analysis and to assess the relativemore » contributions of model-structure-driven and parameter-value-driven uncertainty to overall prediction uncertainty. This study used a random walk Metropolis algorithm to estimate parameters for 30 spring wheat genotypes using nine phenology models based on multi-location trial data for days to heading and days to maturity. Across all cases, parameter-driven uncertainty accounted for between 19 and 52% of predictive uncertainty, while model-structure-driven uncertainty accounted for between 12 and 64%. Here, this study demonstrated the importance of quantifying both model-structure- and parameter-value-driven uncertainty when assessing overall prediction uncertainty in modeling spring wheat phenology. More generally, Bayesian parameter estimation provided a useful framework for quantifying and analyzing sources of prediction uncertainty.« less

The Interplay of School Readiness and Teacher Readiness for Educational Technology Integration: A Structural Equation Model

ERIC Educational Resources Information Center

Petko, Dominik; Prasse, Doreen; Cantieni, Andrea

2018-01-01

Decades of research have shown that technological change in schools depends on multiple interrelated factors. Structural equation models explaining the interplay of factors often suffer from high complexity and low coherence. To reduce complexity, a more robust structural equation model was built with data from a survey of 349 Swiss primary school…

Role Stress Revisited: Job Structuring Antecedents, Work Outcomes, and Moderating Effects of Locus of Control

ERIC Educational Resources Information Center

Conley, Sharon; You, Sukkyung

2014-01-01

A previous study examined role stress in relation to work outcomes; in this study, we added job structuring antecedents to a model of role stress and examined the moderating effects of locus of control. Structural equation modeling was used to assess the plausibility of our conceptual model, which specified hypothesized linkages among teachers'…

Single High Fidelity Geometric Data Sets for LCM - Model Requirements

DTIC Science & Technology

2006-11-01

are extensive single 3D CAD data models incorporating hull structure, propulsion, steering, piping , electrical, HVAC and other systems, which make...single 3D CAD data models incorporating hull structure, propulsion, steering, piping , electrical, HVAC and other systems. During this same period...be sufficiently flexible to accommodate the diverse requirements of various types of structural analyses. Section Properties & Material Data

An Analysis of Turkey's PISA 2015 Results Using Two-Level Hierarchical Linear Modelling

ERIC Educational Resources Information Center

Atas, Dogu; Karadag, Özge

2017-01-01

In the field of education, most of the data collected are multi-level structured. Cities, city based schools, school based classes and finally students in the classrooms constitute a hierarchical structure. Hierarchical linear models give more accurate results compared to standard models when the data set has a structure going far as individuals,…

Enabling School Structure, Collective Responsibility, and a Culture of Academic Optimism: Toward a Robust Model of School Performance in Taiwan

ERIC Educational Resources Information Center

Wu, Jason H.; Hoy, Wayne K.; Tarter, C. John

2013-01-01

Purpose: The purpose of this research is twofold: to test a theory of academic optimism in Taiwan elementary schools and to expand the theory by adding new variables, collective responsibility and enabling school structure, to the model. Design/methodology/approach: Structural equation modeling was used to test, refine, and expand an…

Writing-to-Learn the Nature of Science in the Context of the Lewis Dot Structure Model

ERIC Educational Resources Information Center

Shultz, Ginger V.; Gere, Anne Ruggles

2015-01-01

Traditional methods for teaching the Lewis dot structure model emphasize rule-based learning and often neglect the purpose and function of the model. Thus, many students are unable to extend their understanding of molecular structures in new contexts. The assignment described here addresses this issue by asking students to read and write about the…

Thick strings, the liquid crystal blue phase, and cosmological large-scale structure

NASA Technical Reports Server (NTRS)

Luo, Xiaochun; Schramm, David N.

1992-01-01

A phenomenological model based on the liquid crystal blue phase is proposed as a model for a late-time cosmological phase transition. Topological defects, in particular thick strings and/or domain walls, are presented as seeds for structure formation. It is shown that the observed large-scale structure, including quasi-periodic wall structure, can be well fitted in the model without violating the microwave background isotropy bound or the limits from induced gravitational waves and the millisecond pulsar timing. Furthermore, such late-time transitions can produce objects such as quasars at high redshifts. The model appears to work with either cold or hot dark matter.

Significance of Shear Wall in Multi-Storey Structure With Seismic Analysis

NASA Astrophysics Data System (ADS)

Bongilwar, Rajat; Harne, V. R.; Chopade, Aditya

2018-03-01

In past decades, shear walls are one of the most appropriate and important structural component in multi-storied building. Therefore, it would be very interesting to study the structural response and their systems in multi-storied structure. Shear walls contribute the stiffness and strength during earthquakes which are often neglected during design of structure and construction. This study shows the effect of shear walls which significantly affect the vulnerability of structures. In order to test this hypothesis, G+8 storey building was considered with and without shear walls and analyzed for various parameters like base shear, storey drift ratio, lateral displacement, bending moment and shear force. Significance of shear wall has been studied with the help of two models. First model is without shear wall i.e. bare frame and other another model is with shear wall considering opening also in it. For modeling and analysis of both the models, FEM based software ETABS 2016 were used. The analysis of all models was done using Equivalent static method. The comparison of results has been done based on same parameters like base shear, storey drift ratio, lateral displacement, bending moment and shear force.

Enhanced dielectric standoff and mechanical failure in field-structured composites

NASA Astrophysics Data System (ADS)

Martin, James E.; Tigges, Chris P.; Anderson, Robert A.; Odinek, Judy

1999-09-01

We report dielectric breakdown experiments on electric-field-structured composites of high-dielectric-constant BaTiO3 particles in an epoxy resin. These experiments show a significant increase in the dielectric standoff strength perpendicular to the field structuring direction, relative to control samples consisting of randomly dispersed particles. To understand the relation of this observation to microstructure, we apply a simple resistor-short breakdown model to three-dimensional composite structures generated from a dynamical simulation. In this breakdown model the composite material is assumed to conduct primarily through particle contacts, so the simulated structures are mapped onto a resistor network where the center of mass of each particle is a node that is connected to neighboring nodes by resistors of fixed resistance that irreversibly short to perfect conductors when the current reaches a threshold value. This model gives relative breakdown voltages that are in good agreement with experimental results. Finally, we consider a primitive model of the mechanical strength of a field-structured composite material, which is a current-driven, conductor-insulator fuse model. This model leads to a macroscopic fusing behavior and can be related to mechanical failure of the composite.

Constructing stage-structured matrix population models from life tables: comparison of methods

PubMed Central

Diaz-Lopez, Jasmin

2017-01-01

A matrix population model is a convenient tool for summarizing per capita survival and reproduction rates (collectively vital rates) of a population and can be used for calculating an asymptotic finite population growth rate (λ) and generation time. These two pieces of information can be used for determining the status of a threatened species. The use of stage-structured population models has increased in recent years, and the vital rates in such models are often estimated using a life table analysis. However, potential bias introduced when converting age-structured vital rates estimated from a life table into parameters for a stage-structured population model has not been assessed comprehensively. The objective of this study was to investigate the performance of methods for such conversions using simulated life histories of organisms. The underlying models incorporate various types of life history and true population growth rates of varying levels. The performance was measured by comparing differences in λ and the generation time calculated using the Euler-Lotka equation, age-structured population matrices, and several stage-structured population matrices that were obtained by applying different conversion methods. The results show that the discretization of age introduces only small bias in λ or generation time. Similarly, assuming a fixed age of maturation at the mean age of maturation does not introduce much bias. However, aggregating age-specific survival rates into a stage-specific survival rate and estimating a stage-transition rate can introduce substantial bias depending on the organism’s life history type and the true values of λ. In order to aggregate survival rates, the use of the weighted arithmetic mean was the most robust method for estimating λ. Here, the weights are given by survivorship curve after discounting with λ. To estimate a stage-transition rate, matching the proportion of individuals transitioning, with λ used for discounting the rate, was the best approach. However, stage-structured models performed poorly in estimating generation time, regardless of the methods used for constructing the models. Based on the results, we recommend using an age-structured matrix population model or the Euler-Lotka equation for calculating λ and generation time when life table data are available. Then, these age-structured vital rates can be converted into a stage-structured model for further analyses. PMID:29085763

Constructing stage-structured matrix population models from life tables: comparison of methods.

PubMed

Fujiwara, Masami; Diaz-Lopez, Jasmin

2017-01-01

A matrix population model is a convenient tool for summarizing per capita survival and reproduction rates (collectively vital rates) of a population and can be used for calculating an asymptotic finite population growth rate ( λ ) and generation time. These two pieces of information can be used for determining the status of a threatened species. The use of stage-structured population models has increased in recent years, and the vital rates in such models are often estimated using a life table analysis. However, potential bias introduced when converting age-structured vital rates estimated from a life table into parameters for a stage-structured population model has not been assessed comprehensively. The objective of this study was to investigate the performance of methods for such conversions using simulated life histories of organisms. The underlying models incorporate various types of life history and true population growth rates of varying levels. The performance was measured by comparing differences in λ and the generation time calculated using the Euler-Lotka equation, age-structured population matrices, and several stage-structured population matrices that were obtained by applying different conversion methods. The results show that the discretization of age introduces only small bias in λ or generation time. Similarly, assuming a fixed age of maturation at the mean age of maturation does not introduce much bias. However, aggregating age-specific survival rates into a stage-specific survival rate and estimating a stage-transition rate can introduce substantial bias depending on the organism's life history type and the true values of λ . In order to aggregate survival rates, the use of the weighted arithmetic mean was the most robust method for estimating λ . Here, the weights are given by survivorship curve after discounting with λ . To estimate a stage-transition rate, matching the proportion of individuals transitioning, with λ used for discounting the rate, was the best approach. However, stage-structured models performed poorly in estimating generation time, regardless of the methods used for constructing the models. Based on the results, we recommend using an age-structured matrix population model or the Euler-Lotka equation for calculating λ and generation time when life table data are available. Then, these age-structured vital rates can be converted into a stage-structured model for further analyses.

Improving fault image by determination of optimum seismic survey parameters using ray-based modeling

NASA Astrophysics Data System (ADS)

Saffarzadeh, Sadegh; Javaherian, Abdolrahim; Hasani, Hossein; Talebi, Mohammad Ali

2018-06-01

In complex structures such as faults, salt domes and reefs, specifying the survey parameters is more challenging and critical owing to the complicated wave field behavior involved in such structures. In the petroleum industry, detecting faults has become crucial for reservoir potential where faults can act as traps for hydrocarbon. In this regard, seismic survey modeling is employed to construct a model close to the real structure, and obtain very realistic synthetic seismic data. Seismic modeling software, the velocity model and parameters pre-determined by conventional methods enable a seismic survey designer to run a shot-by-shot virtual survey operation. A reliable velocity model of structures can be constructed by integrating the 2D seismic data, geological reports and the well information. The effects of various survey designs can be investigated by the analysis of illumination maps and flower plots. Also, seismic processing of the synthetic data output can describe the target image using different survey parameters. Therefore, seismic modeling is one of the most economical ways to establish and test the optimum acquisition parameters to obtain the best image when dealing with complex geological structures. The primary objective of this study is to design a proper 3D seismic survey orientation to achieve fault zone structures through ray-tracing seismic modeling. The results prove that a seismic survey designer can enhance the image of fault planes in a seismic section by utilizing the proposed modeling and processing approach.

Conformational Transitions upon Ligand Binding: Holo-Structure Prediction from Apo Conformations

PubMed Central

Seeliger, Daniel; de Groot, Bert L.

2010-01-01

Biological function of proteins is frequently associated with the formation of complexes with small-molecule ligands. Experimental structure determination of such complexes at atomic resolution, however, can be time-consuming and costly. Computational methods for structure prediction of protein/ligand complexes, particularly docking, are as yet restricted by their limited consideration of receptor flexibility, rendering them not applicable for predicting protein/ligand complexes if large conformational changes of the receptor upon ligand binding are involved. Accurate receptor models in the ligand-bound state (holo structures), however, are a prerequisite for successful structure-based drug design. Hence, if only an unbound (apo) structure is available distinct from the ligand-bound conformation, structure-based drug design is severely limited. We present a method to predict the structure of protein/ligand complexes based solely on the apo structure, the ligand and the radius of gyration of the holo structure. The method is applied to ten cases in which proteins undergo structural rearrangements of up to 7.1 Å backbone RMSD upon ligand binding. In all cases, receptor models within 1.6 Å backbone RMSD to the target were predicted and close-to-native ligand binding poses were obtained for 8 of 10 cases in the top-ranked complex models. A protocol is presented that is expected to enable structure modeling of protein/ligand complexes and structure-based drug design for cases where crystal structures of ligand-bound conformations are not available. PMID:20066034

The application of data mining and cloud computing techniques in data-driven models for structural health monitoring

NASA Astrophysics Data System (ADS)

Khazaeli, S.; Ravandi, A. G.; Banerji, S.; Bagchi, A.

2016-04-01

Recently, data-driven models for Structural Health Monitoring (SHM) have been of great interest among many researchers. In data-driven models, the sensed data are processed to determine the structural performance and evaluate the damages of an instrumented structure without necessitating the mathematical modeling of the structure. A framework of data-driven models for online assessment of the condition of a structure has been developed here. The developed framework is intended for automated evaluation of the monitoring data and structural performance by the Internet technology and resources. The main challenges in developing such framework include: (a) utilizing the sensor measurements to estimate and localize the induced damage in a structure by means of signal processing and data mining techniques, and (b) optimizing the computing and storage resources with the aid of cloud services. The main focus in this paper is to demonstrate the efficiency of the proposed framework for real-time damage detection of a multi-story shear-building structure in two damage scenarios (change in mass and stiffness) in various locations. Several features are extracted from the sensed data by signal processing techniques and statistical methods. Machine learning algorithms are deployed to select damage-sensitive features as well as classifying the data to trace the anomaly in the response of the structure. Here, the cloud computing resources from Amazon Web Services (AWS) have been used to implement the proposed framework.

Model Selection with the Linear Mixed Model for Longitudinal Data

ERIC Educational Resources Information Center

Ryoo, Ji Hoon

2011-01-01

Model building or model selection with linear mixed models (LMMs) is complicated by the presence of both fixed effects and random effects. The fixed effects structure and random effects structure are codependent, so selection of one influences the other. Most presentations of LMM in psychology and education are based on a multilevel or…

The Integration of Continuous and Discrete Latent Variable Models: Potential Problems and Promising Opportunities

ERIC Educational Resources Information Center

Bauer, Daniel J.; Curran, Patrick J.

2004-01-01

Structural equation mixture modeling (SEMM) integrates continuous and discrete latent variable models. Drawing on prior research on the relationships between continuous and discrete latent variable models, the authors identify 3 conditions that may lead to the estimation of spurious latent classes in SEMM: misspecification of the structural model,…

Peptide inhibitors of botulinum neurotoxin serotype A: design, inhibition, cocrystal structures, structure-activity relationship and pharmacophore modeling

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

Kumar G.; Swaminathan S.; Kumaran, D.

Clostridium botulinum neurotoxins are classified as Category A bioterrorism agents by the Centers for Disease Control and Prevention (CDC). The seven serotypes (A-G) of the botulinum neurotoxin, the causative agent of the disease botulism, block neurotransmitter release by specifically cleaving one of the three SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) proteins and induce flaccid paralysis. Using a structure-based drug-design approach, a number of peptide inhibitors were designed and their inhibitory activity against botulinum serotype A (BoNT/A) protease was determined. The most potent peptide, RRGF, inhibited BoNT/A protease with an IC{sub 50} of 0.9 {micro}M and a K{sub i} ofmore » 358 nM. High-resolution crystal structures of various peptide inhibitors in complex with the BoNT/A protease domain were also determined. Based on the inhibitory activities and the atomic interactions deduced from the cocrystal structures, the structure-activity relationship was analyzed and a pharmacophore model was developed. Unlike the currently available models, this pharmacophore model is based on a number of enzyme-inhibitor peptide cocrystal structures and improved the existing models significantly, incorporating new features.« less

Identification of Historical Veziragasi Aqueduct Using the Operational Modal Analysis

PubMed Central

Ercan, E.; Nuhoglu, A.

2014-01-01

This paper describes the results of a model updating study conducted on a historical aqueduct, called Veziragasi, in Turkey. The output-only modal identification results obtained from ambient vibration measurements of the structure were used to update a finite element model of the structure. For the purposes of developing a solid model of the structure, the dimensions of the structure, defects, and material degradations in the structure were determined in detail by making a measurement survey. For evaluation of the material properties of the structure, nondestructive and destructive testing methods were applied. The modal analysis of the structure was calculated by FEM. Then, a nondestructive dynamic test as well as operational modal analysis was carried out and dynamic properties were extracted. The natural frequencies and corresponding mode shapes were determined from both theoretical and experimental modal analyses and compared with each other. A good harmony was attained between mode shapes, but there were some differences between natural frequencies. The sources of the differences were introduced and the FEM model was updated by changing material parameters and boundary conditions. Finally, the real analytical model of the aqueduct was put forward and the results were discussed. PMID:24511287

Numerical modeling of the exterior-to-interior transmission of impulsive sound through three-dimensional, thin-walled elastic structures

NASA Astrophysics Data System (ADS)

Remillieux, Marcel C.; Pasareanu, Stephanie M.; Svensson, U. Peter

2013-12-01

Exterior propagation of impulsive sound and its transmission through three-dimensional, thin-walled elastic structures, into enclosed cavities, are investigated numerically in the framework of linear dynamics. A model was developed in the time domain by combining two numerical tools: (i) exterior sound propagation and induced structural loading are computed using the image-source method for the reflected field (specular reflections) combined with an extension of the Biot-Tolstoy-Medwin method for the diffracted field, (ii) the fully coupled vibro-acoustic response of the interior fluid-structure system is computed using a truncated modal-decomposition approach. In the model for exterior sound propagation, it is assumed that all surfaces are acoustically rigid. Since coupling between the structure and the exterior fluid is not enforced, the model is applicable to the case of a light exterior fluid and arbitrary interior fluid(s). The structural modes are computed with the finite-element method using shell elements. Acoustic modes are computed analytically assuming acoustically rigid boundaries and rectangular geometries of the enclosed cavities. This model is verified against finite-element solutions for the cases of rectangular structures containing one and two cavities, respectively.