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Sample records for predicting structural integrity

  1. Status of research aimed at predicting structural integrity

    SciTech Connect

    Reuter, W.G.

    1997-12-31

    Considerable research has been performed throughout the world on measuring the fracture toughness of metals. The existing capability fills the need encountered when selecting materials, thermal-mechanical treatments, welding procedures, etc., but cannot predict the fracture process of structural components containing cracks. The Idaho National Engineering and Environmental Laboratory and the Massachusetts Institute of Technology have been collaborating for a number of years on developing capabilities for using fracture toughness results to predict structural integrity. Because of the high cost of fabricating and testing structural components, these studies have been limited to predicting the fracture process in specimens containing surface cracks. This paper summarizes the present status of the experimental studies of using fracture toughness data to predict crack growth initiation in specimens (structural components) containing surface cracks. These results are limited to homogeneous base materials.

  2. An Integrated Theory for Predicting the Hydrothermomechanical Response of Advanced Composite Structural Components

    NASA Technical Reports Server (NTRS)

    Chamis, C. C.; Lark, R. F.; Sinclair, J. H.

    1977-01-01

    An integrated theory is developed for predicting the hydrothermomechanical (HDTM) response of fiber composite components. The integrated theory is based on a combined theoretical and experimental investigation. In addition to predicting the HDTM response of components, the theory is structured to assess the combined hydrothermal effects on the mechanical properties of unidirectional composites loaded along the material axis and off-axis, and those of angleplied laminates. The theory developed predicts values which are in good agreement with measured data at the micromechanics, macromechanics, laminate analysis and structural analysis levels.

  3. PSiFR: an integrated resource for prediction of protein structure and function.

    PubMed

    Pandit, Shashi B; Brylinski, Michal; Zhou, Hongyi; Gao, Mu; Arakaki, Adrian K; Skolnick, Jeffrey

    2010-03-01

    In the post-genomic era, the annotation of protein function facilitates the understanding of various biological processes. To extend the range of function annotation methods to the twilight zone of sequence identity, we have developed approaches that exploit both protein tertiary structure and/or protein sequence evolutionary relationships. To serve the scientific community, we have integrated the structure prediction tools, TASSER, TASSER-Lite and METATASSER, and the functional inference tools, FINDSITE, a structure-based algorithm for binding site prediction, Gene Ontology molecular function inference and ligand screening, EFICAz(2), a sequence-based approach to enzyme function inference and DBD-hunter, an algorithm for predicting DNA-binding proteins and associated DNA-binding residues, into a unified web resource, Protein Structure and Function prediction Resource (PSiFR). PSiFR is freely available for use on the web at http://psifr.cssb.biology.gatech.edu/

  4. Smoothing Protein Energy Landscapes by Integrating Folding Models with Structure Prediction

    PubMed Central

    Pritchard-Bell, Ari; Shell, M. Scott

    2011-01-01

    Decades of work has investigated the energy landscapes of simple protein models, but what do the landscapes of real, large, atomically detailed proteins look like? We explore an approach to this problem that systematically extracts simple funnel models of actual proteins using ensembles of structure predictions and physics-based atomic force fields and sampling. Central to our effort are calculations of a quantity called the relative entropy, which quantifies the extent to which a given set of structure decoys and a putative native structure can be projected onto a theoretical funnel description. We examine 86 structure prediction targets and one coupled folding-binding system, and find that in a majority of cases the relative entropy robustly signals which structures are nearest to native (i.e., which appear to lie closest to a funnel bottom). Importantly, the landscape model improves substantially upon purely energetic measures in scoring decoys. Our results suggest that physics-based models—including both folding theories and all-atom force fields—may be successfully integrated with structure prediction efforts. Conversely, detailed predictions of structures and the relative entropy approach enable one to extract coarse topographic features of protein landscapes that may enhance the development and application of simpler folding models. PMID:22067165

  5. ProbFold: a probabilistic method for integration of probing data in RNA secondary structure prediction.

    PubMed

    Sahoo, Sudhakar; Świtnicki, Michał P; Pedersen, Jakob Skou

    2016-09-01

    Recently, new RNA secondary structure probing techniques have been developed, including Next Generation Sequencing based methods capable of probing transcriptome-wide. These techniques hold great promise for improving structure prediction accuracy. However, each new data type comes with its own signal properties and biases, which may even be experiment specific. There is therefore a growing need for RNA structure prediction methods that can be automatically trained on new data types and readily extended to integrate and fully exploit multiple types of data. Here, we develop and explore a modular probabilistic approach for integrating probing data in RNA structure prediction. It can be automatically trained given a set of known structures with probing data. The approach is demonstrated on SHAPE datasets, where we evaluate and selectively model specific correlations. The approach often makes superior use of the probing data signal compared to other methods. We illustrate the use of ProbFold on multiple data types using both simulations and a small set of structures with both SHAPE, DMS and CMCT data. Technically, the approach combines stochastic context-free grammars (SCFGs) with probabilistic graphical models. This approach allows rapid adaptation and integration of new probing data types. ProbFold is implemented in C ++. Models are specified using simple textual formats. Data reformatting is done using separate C ++ programs. Source code, statically compiled binaries for x86 Linux machines, C ++ programs, example datasets and a tutorial is available from http://moma.ki.au.dk/prj/probfold/ : jakob.skou@clin.au.dk Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  6. SSME lifetime prediction and verification, integrating environments, structures, materials: The challenge

    NASA Technical Reports Server (NTRS)

    Ryan, R. S.; Salter, L. D.; Young, G. M., III; Munafo, P. M.

    1985-01-01

    The planned missions for the space shuttle dictated a unique and technology-extending rocket engine. The high specific impulse requirements in conjunction with a 55-mission lifetime, plus volume and weight constraints, produced unique structural design, manufacturing, and verification requirements. Operations from Earth to orbit produce severe dynamic environments, which couple with the extreme pressure and thermal environments associated with the high performance, creating large low cycle loads and high alternating stresses above endurance limit which result in high sensitivity to alternating stresses. Combining all of these effects resulted in the requirements for exotic materials, which are more susceptible to manufacturing problems, and the use of an all-welded structure. The challenge of integrating environments, dynamics, structures, and materials into a verified SSME structure is discussed. The verification program and developmental flight results are included. The first six shuttle flights had engine performance as predicted with no failures. The engine system has met the basic design challenges.

  7. Ultrasonic Sensing and Life Prediction for the DARPA Structural Integrity Prognosis System

    NASA Astrophysics Data System (ADS)

    Michaels, Jennifer E.; Michaels, Thomas E.; Cobb, Adam C.; Kacprzynski, Gregory J.

    2007-03-01

    The overall objective of the DARPA Structural Integrity Prognosis System (SIPS) program is to develop technologies to advance material damage state condition assessment with limited or no dedicated maintenance action. As a part of the sensors thrust area, an in situ ultrasonic sensing method was developed and demonstrated to detect cracks initiating from fastener holes and provide an estimate of total crack area. Crack area estimates were combined with load history data, projected future loads, and life prediction models to determine a probability density function for time-to-failure. The ultrasonic method utilizes two shear wave angle beam transducers operating in through transmission mode which are mounted on either side of the hole. The transmitted wave travels through the area of expected cracking, and the presence of cracks around the fastener holes decreases the amount of acoustic energy that is received. Furthermore, as cracks open and close during the fatigue process, the received energy is modulated, i.e., decreased when the cracks are open versus closed, and this non-linear behavior is the basis of algorithms developed to detect and size fastener holes cracks. The ultrasonic method was demonstrated as part of an integrated SIPS demonstration whereby aircraft-grade aluminum subcomponents were fatigued to failure. Results are presented from both the ultrasonic measurements and the integrated life prediction software.

  8. Integration of Expressed Sequence Tag Data Flanking Predicted RNA Secondary Structures Facilitates Novel Non-Coding RNA Discovery

    PubMed Central

    Krzyzanowski, Paul M.; Price, Feodor D.; Muro, Enrique M.; Rudnicki, Michael A.; Andrade-Navarro, Miguel A.

    2011-01-01

    Many computational methods have been used to predict novel non-coding RNAs (ncRNAs), but none, to our knowledge, have explicitly investigated the impact of integrating existing cDNA-based Expressed Sequence Tag (EST) data that flank structural RNA predictions. To determine whether flanking EST data can assist in microRNA (miRNA) prediction, we identified genomic sites encoding putative miRNAs by combining functional RNA predictions with flanking ESTs data in a model consistent with miRNAs undergoing cleavage during maturation. In both human and mouse genomes, we observed that the inclusion of flanking ESTs adjacent to and not overlapping predicted miRNAs significantly improved the performance of various methods of miRNA prediction, including direct high-throughput sequencing of small RNA libraries. We analyzed the expression of hundreds of miRNAs predicted to be expressed during myogenic differentiation using a customized microarray and identified several known and predicted myogenic miRNA hairpins. Our results indicate that integrating ESTs flanking structural RNA predictions improves the quality of cleaved miRNA predictions and suggest that this strategy can be used to predict other non-coding RNAs undergoing cleavage during maturation. PMID:21698286

  9. Structural integrity of frontostriatal connections predicts longitudinal changes in self-esteem.

    PubMed

    Chavez, Robert S; Heatherton, Todd F

    2017-06-01

    Diverse neurological and psychiatric conditions are marked by a diminished sense of positive self-regard, and reductions in self-esteem are associated with risk for these disorders. Recent evidence has shown that the connectivity of frontostriatal circuitry reflects individual differences in self-esteem. However, it remains an open question as to whether the integrity of these connections can predict self-esteem changes over larger timescales. Using diffusion magnetic resonance imaging and probabilistic tractography, we demonstrate that the integrity of white matter pathways linking the medial prefrontal cortex to the ventral striatum predicts changes in self-esteem 8 months after initial scanning in a sample of 30 young adults. Individuals with greater integrity of this pathway during the scanning session at Time 1 showed increased levels of self-esteem at follow-up, whereas individuals with lower integrity showed stifled or decreased levels of self-esteem. These results provide evidence that frontostriatal white matter integrity predicts the trajectory of self-esteem development in early adulthood, which may contribute to blunted levels of positive self-regard seen in multiple psychiatric conditions, including depression and anxiety.

  10. Structural Integrity of Frontostriatal Connections Predicts Longitudinal Changes in Self-esteem

    PubMed Central

    Chavez, Robert S.; Heatherton, Todd F.

    2016-01-01

    Diverse neurological and psychiatric conditions are marked by a diminished sense of positive self-regard, and reductions in self-esteem are associated with risk for these disorders. Recent evidence has shown that the connectivity of frontostriatal circuitry reflects individual differences in self-esteem. However, it remains an open question as to whether the integrity of these connections can predict self-esteem changes over larger timescales. Using diffusion magnetic resonance imaging and probabilistic tractography, we demonstrate that the integrity of white matter pathways linking the medial prefrontal cortex to the ventral striatum predicts changes in self-esteem eight months after initial scanning in sample of thirty young adults. Individuals with greater integrity of this pathway during the scanning session at Time 1 showed increased levels of self-esteem at follow-up, whereas individuals with lower integrity showed stifled or decreased levels of self-esteem. These results provide evidence that frontostriatal white matter integrity predicts the trajectory of self-esteem development in early adulthood, which may contribute to blunted levels of positive self-regard seen in multiple psychiatric conditions including depression and anxiety. PMID:26966986

  11. Integrated prediction of one-dimensional structural features and their relationships with conformational flexibility in helical membrane proteins.

    PubMed

    Ahmad, Shandar; Singh, Yumlembam Hemajit; Paudel, Yogesh; Mori, Takaharu; Sugita, Yuji; Mizuguchi, Kenji

    2010-10-27

    Many structural properties such as solvent accessibility, dihedral angles and helix-helix contacts can be assigned to each residue in a membrane protein. Independent studies exist on the analysis and sequence-based prediction of some of these so-called one-dimensional features. However, there is little explanation of why certain residues are predicted in a wrong structural class or with large errors in the absolute values of these features. On the other hand, membrane proteins undergo conformational changes to allow transport as well as ligand binding. These conformational changes often occur via residues that are inherently flexible and hence, predicting fluctuations in residue positions is of great significance. We performed a statistical analysis of common patterns among selected one-dimensional equilibrium structural features (ESFs) and developed a method for simultaneously predicting all of these features using an integrated system. Our results show that the prediction performance can be improved if multiple structural features are trained in an integrated model, compared to the current practice of developing individual models. In particular, the performance of the solvent accessibility and bend-angle prediction improved in this way. The well-performing bend-angle prediction can be used to predict helical positions with severe kinks at a modest success rate. Further, we showed that single-chain conformational dynamics, measured by B-factors derived from normal mode analysis, could be predicted from observed and predicted ESFs with good accuracy. A web server was developed (http://tardis.nibio.go.jp/netasa/htmone/) for predicting the one-dimensional ESFs from sequence information and analyzing the differences between the predicted and observed values of the ESFs. The prediction performance of the integrated model is significantly better than that of the models performing the task separately for each feature for the solvent accessibility and bend

  12. Integrated prediction of one-dimensional structural features and their relationships with conformational flexibility in helical membrane proteins

    PubMed Central

    2010-01-01

    Background Many structural properties such as solvent accessibility, dihedral angles and helix-helix contacts can be assigned to each residue in a membrane protein. Independent studies exist on the analysis and sequence-based prediction of some of these so-called one-dimensional features. However, there is little explanation of why certain residues are predicted in a wrong structural class or with large errors in the absolute values of these features. On the other hand, membrane proteins undergo conformational changes to allow transport as well as ligand binding. These conformational changes often occur via residues that are inherently flexible and hence, predicting fluctuations in residue positions is of great significance. Results We performed a statistical analysis of common patterns among selected one-dimensional equilibrium structural features (ESFs) and developed a method for simultaneously predicting all of these features using an integrated system. Our results show that the prediction performance can be improved if multiple structural features are trained in an integrated model, compared to the current practice of developing individual models. In particular, the performance of the solvent accessibility and bend-angle prediction improved in this way. The well-performing bend-angle prediction can be used to predict helical positions with severe kinks at a modest success rate. Further, we showed that single-chain conformational dynamics, measured by B-factors derived from normal mode analysis, could be predicted from observed and predicted ESFs with good accuracy. A web server was developed (http://tardis.nibio.go.jp/netasa/htmone/) for predicting the one-dimensional ESFs from sequence information and analyzing the differences between the predicted and observed values of the ESFs. Conclusions The prediction performance of the integrated model is significantly better than that of the models performing the task separately for each feature for the solvent

  13. Air Vehicle Integration and Technology Research (AVIATR). Delivery Order 0023: Predictive Capability for Hypersonic Structural Response and Life Prediction: Phase 2 - Detailed Design of Hypersonic Cruise Vehicle Hot-Structure

    DTIC Science & Technology

    2012-05-01

    AFRL-RQ-WP-TR-2012-0280 AIR VEHICLE INTEGRATION AND TECHNOLOGY RESEARCH (AVIATR) Delivery Order 0023: Predictive Capability for Hypersonic ...Structural Response and Life Prediction: Phase II - Detailed Design of Hypersonic Cruise Vehicle Hot-Structure Brian Zuchowski Lockheed Martin...Capability for Hypersonic Structural Response and Life Prediction: Phase II - Detailed Design of Hypersonic Cruise Vehicle Hot-Structure 5a. CONTRACT

  14. 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.

  15. 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

  16. Integrated prediction of protein folding and unfolding rates from only size and structural class.

    PubMed

    De Sancho, David; Muñoz, Victor

    2011-10-14

    Protein stability, folding and unfolding rates are all determined by the multidimensional folding free energy surface, which in turn is dictated by factors such as size, structure, and amino-acid sequence. Work over the last 15 years has highlighted the role of size and 3D structure in determining folding rates, resulting in many procedures for their prediction. In contrast, unfolding rates are thought to depend on sequence specifics and be much more difficult to predict. Here we introduce a minimalist physics-based model that computes one-dimensional folding free energy surfaces using the number of aminoacids (N) and the structural class (α-helical, all-β, or α-β) as only protein-specific input. In this model N sets the overall cost in conformational entropy and the net stabilization energy, whereas the structural class defines the partitioning of the stabilization energy between local and non-local interactions. To test its predictive power, we calibrated the model empirically and implemented it into an algorithm for the PREdiction of Folding and Unfolding Rates (PREFUR). We found that PREFUR predicts the absolute folding and unfolding rates of an experimental database of 52 proteins with accuracies of ±0.7 and ±1.4 orders of magnitude, respectively (relative to experimental spans of 6 and 8 orders of magnitude). Such prediction uncertainty for proteins vastly varying in size and structure is only two-fold larger than the differences in folding (±0.34) and unfolding rates (±0.7) caused by single-point mutations. Moreover, PREFUR predicts protein stability with an accuracy of ±6.3 kJ mol(-1), relative to the 5 kJ mol(-1) average perturbation induced by single-point mutations. The remarkable performance of our simplistic model demonstrates that size and structural class are the major determinants of the folding landscapes of natural proteins, whereas sequence variability only provides the final 10-20% tuning. PREFUR is thus a powerful bioinformatic tool

  17. Rigorous assessment and integration of the sequence and structure based features to predict hot spots

    PubMed Central

    2011-01-01

    effective in predicting hot spots based on sequence features. Hot spots cannot be fully predicted through simple analysis based on physicochemical characteristics, but there is reason to believe that integration of features and machine learning methods can remarkably improve the predictive performance for hot spots. PMID:21798070

  18. An Integrated Hydrologic Bayesian Multi-Model Combination Framework: Confronting Input, parameter and model structural uncertainty in Hydrologic Prediction

    SciTech Connect

    Ajami, N K; Duan, Q; Sorooshian, S

    2006-05-05

    This paper presents a new technique--Integrated Bayesian Uncertainty Estimator (IBUNE) to account for the major uncertainties of hydrologic rainfall-runoff predictions explicitly. The uncertainties from the input (forcing) data--mainly the precipitation observations and from the model parameters are reduced through a Monte Carlo Markov Chain (MCMC) scheme named Shuffled Complex Evolution Metropolis (SCEM) algorithm which has been extended to include a precipitation error model. Afterwards, the Bayesian Model Averaging (BMA) scheme is employed to further improve the prediction skill and uncertainty estimation using multiple model output. A series of case studies using three rainfall-runoff models to predict the streamflow in the Leaf River basin, Mississippi are used to examine the necessity and usefulness of this technique. The results suggests that ignoring either input forcings error or model structural uncertainty will lead to unrealistic model simulations and their associated uncertainty bounds which does not consistently capture and represent the real-world behavior of the watershed.

  19. An Integrated Bayesian Uncertainty Estimator: fusion of Input, Parameter and Model Structural Uncertainty Estimation in Hydrologic Prediction System

    NASA Astrophysics Data System (ADS)

    Ajami, N. K.; Duan, Q.; Sorooshian, S.

    2005-12-01

    To-date single conceptual hydrologic models often applied to interpret physical processes within a watershed. Nevertheless hydrologic models regardless of their sophistication and complexity are simplified representation of the complex, spatially distributed and highly nonlinear real world system. Consequently their hydrologic predictions contain considerable uncertainty from different sources including: hydrometeorological forcing inputs, boundary/initial conditions, model structure, model parameters which need to be accounted for. Thus far the effort has gone to address these sources of uncertainty explicitly, making an implicit assumption that uncertainties from different sources are additive. Nevertheless because of the nonlinear nature of the hydrologic systems, it is not feasible to account for these uncertainties independently. Here we present the Integrated Bayesian Uncertainty Estimator (IBUNE) which accounts for total uncertainties from all major sources: inputs forcing, model structure, model parameters. This algorithm explores multi-model framework to tackle model structural uncertainty while using the Bayesian rules to estimate parameter and input uncertainty within individual models. Three hydrologic models including SACramento Soil Moisture Accounting (SAC-SMA) model, Hydrologic model (HYMOD) and Simple Water Balance (SWB) model were considered within IBUNE framework for this study. The results which are presented for the Leaf River Basin, MS, indicates that IBUNE gives a better quantification of uncertainty through hydrological modeling processes, therefore provide more reliable and less bias prediction with realistic uncertainty boundaries.

  20. Predictions of structural integrity of steam generator tubes under normal operating, accident, and severe accident conditions

    SciTech Connect

    Majumdar, S.

    1996-09-01

    Available models for predicting failure of flawed and unflawed steam generator tubes under normal operating, accident, and severe accident conditions are reviewed. Tests conducted in the past, though limited, tended to show that the earlier flow-stress model for part-through-wall axial cracks overestimated the damaging influence of deep cracks. This observation is confirmed by further tests at high temperatures as well as by finite element analysis. A modified correlation for deep cracks can correct this shortcoming of the model. Recent tests have shown that lateral restraint can significantly increase the failure pressure of tubes with unsymmetrical circumferential cracks. This observation is confirmed by finite element analysis. The rate-independent flow stress models that are successful at low temperatures cannot predict the rate sensitive failure behavior of steam generator tubes at high temperatures. Therefore, a creep rupture model for predicting failure is developed and validated by tests under varying temperature and pressure loading expected during severe accidents.

  1. Predictions of structural integrity of steam generator tubes under normal operating, accident, an severe accident conditions

    SciTech Connect

    Majumdar, S.

    1997-02-01

    Available models for predicting failure of flawed and unflawed steam generator tubes under normal operating, accident, and severe accident conditions are reviewed. Tests conducted in the past, though limited, tended to show that the earlier flow-stress model for part-through-wall axial cracks overestimated the damaging influence of deep cracks. This observation was confirmed by further tests at high temperatures, as well as by finite-element analysis. A modified correlation for deep cracks can correct this shortcoming of the model. Recent tests have shown that lateral restraint can significantly increase the failure pressure of tubes with unsymmetrical circumferential cracks. This observation was confirmed by finite-element analysis. The rate-independent flow stress models that are successful at low temperatures cannot predict the rate-sensitive failure behavior of steam generator tubes at high temperatures. Therefore, a creep rupture model for predicting failure was developed and validated by tests under various temperature and pressure loadings that can occur during postulated severe accidents.

  2. Structural Integrity of the Contralesional Hemisphere Predicts Cognitive Impairment in Ischemic Stroke at Three Months

    PubMed Central

    Dacosta-Aguayo, Rosalia; Graña, Manuel; Fernández-Andújar, Marina; López-Cancio, Elena; Cáceres, Cynthia; Bargalló, Núria; Barrios, Maite; Clemente, Immaculada; Monserrat, Pere Toran; Sas, Maite Alzamora; Dávalos, Antoni

    2014-01-01

    After stroke, white matter integrity can be affected both locally and distally to the primary lesion location. It has been shown that tract disruption in mirror’s regions of the contralateral hemisphere is associated with degree of functional impairment. Fourteen patients suffering right hemispheric focal stroke (S) and eighteen healthy controls (HC) underwent Diffusion Weighted Imaging (DWI) and neuropsychological assessment. The stroke patient group was divided into poor (SP; n = 8) and good (SG; n = 6) cognitive recovery groups according to their cognitive improvement from the acute phase (72 hours after stroke) to the subacute phase (3 months post-stroke). Whole-brain DWI data analysis was performed by computing Diffusion Tensor Imaging (DTI) followed by Tract Based Spatial Statistics (TBSS). Assessment of effects was obtained computing the correlation of the projections on TBSS skeleton of Fractional Anisotropy (FA) and Radial Diffusivity (RD) with cognitive test results. Significant decrease of FA was found only in right brain anatomical areas for the S group when compared to the HC group. Analyzed separately, stroke patients with poor cognitive recovery showed additional significant FA decrease in several left hemisphere regions; whereas SG patients showed significant decrease only in the left genu of corpus callosum when compared to the HC. For the SG group, whole brain analysis revealed significant correlation between the performance in the Semantic Fluency test and the FA in the right hemisphere as well as between the performance in the Grooved Pegboard Test (GPT) and theTrail Making Test-part A and the FA in the left hemisphere. For the SP group, correlation analysis revealed significant correlation between the performance in the GPT and the FA in the right hemisphere. PMID:24475078

  3. Structural integrity of the contralesional hemisphere predicts cognitive impairment in ischemic stroke at three months.

    PubMed

    Dacosta-Aguayo, Rosalia; Graña, Manuel; Fernández-Andújar, Marina; López-Cancio, Elena; Cáceres, Cynthia; Bargalló, Núria; Barrios, Maite; Clemente, Immaculada; Monserrat, Pere Toran; Sas, Maite Alzamora; Dávalos, Antoni; Auer, Tibor; Mataró, Maria

    2014-01-01

    After stroke, white matter integrity can be affected both locally and distally to the primary lesion location. It has been shown that tract disruption in mirror's regions of the contralateral hemisphere is associated with degree of functional impairment. Fourteen patients suffering right hemispheric focal stroke (S) and eighteen healthy controls (HC) underwent Diffusion Weighted Imaging (DWI) and neuropsychological assessment. The stroke patient group was divided into poor (SP; n = 8) and good (SG; n = 6) cognitive recovery groups according to their cognitive improvement from the acute phase (72 hours after stroke) to the subacute phase (3 months post-stroke). Whole-brain DWI data analysis was performed by computing Diffusion Tensor Imaging (DTI) followed by Tract Based Spatial Statistics (TBSS). Assessment of effects was obtained computing the correlation of the projections on TBSS skeleton of Fractional Anisotropy (FA) and Radial Diffusivity (RD) with cognitive test results. Significant decrease of FA was found only in right brain anatomical areas for the S group when compared to the HC group. Analyzed separately, stroke patients with poor cognitive recovery showed additional significant FA decrease in several left hemisphere regions; whereas SG patients showed significant decrease only in the left genu of corpus callosum when compared to the HC. For the SG group, whole brain analysis revealed significant correlation between the performance in the Semantic Fluency test and the FA in the right hemisphere as well as between the performance in the Grooved Pegboard Test (GPT) and the Trail Making Test-part A and the FA in the left hemisphere. For the SP group, correlation analysis revealed significant correlation between the performance in the GPT and the FA in the right hemisphere.

  4. Improved prediction of RNA secondary structure by integrating the free energy model with restraints derived from experimental probing data.

    PubMed

    Wu, Yang; Shi, Binbin; Ding, Xinqiang; Liu, Tong; Hu, Xihao; Yip, Kevin Y; Yang, Zheng Rong; Mathews, David H; Lu, Zhi John

    2015-09-03

    Recently, several experimental techniques have emerged for probing RNA structures based on high-throughput sequencing. However, most secondary structure prediction tools that incorporate probing data are designed and optimized for particular types of experiments. For example, RNAstructure-Fold is optimized for SHAPE data, while SeqFold is optimized for PARS data. Here, we report a new RNA secondary structure prediction method, restrained MaxExpect (RME), which can incorporate multiple types of experimental probing data and is based on a free energy model and an MEA (maximizing expected accuracy) algorithm. We first demonstrated that RME substantially improved secondary structure prediction with perfect restraints (base pair information of known structures). Next, we collected structure-probing data from diverse experiments (e.g. SHAPE, PARS and DMS-seq) and transformed them into a unified set of pairing probabilities with a posterior probabilistic model. By using the probability scores as restraints in RME, we compared its secondary structure prediction performance with two other well-known tools, RNAstructure-Fold (based on a free energy minimization algorithm) and SeqFold (based on a sampling algorithm). For SHAPE data, RME and RNAstructure-Fold performed better than SeqFold, because they markedly altered the energy model with the experimental restraints. For high-throughput data (e.g. PARS and DMS-seq) with lower probing efficiency, the secondary structure prediction performances of the tested tools were comparable, with performance improvements for only a portion of the tested RNAs. However, when the effects of tertiary structure and protein interactions were removed, RME showed the highest prediction accuracy in the DMS-accessible regions by incorporating in vivo DMS-seq data. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  5. Improved prediction of RNA secondary structure by integrating the free energy model with restraints derived from experimental probing data

    PubMed Central

    Wu, Yang; Shi, Binbin; Ding, Xinqiang; Liu, Tong; Hu, Xihao; Yip, Kevin Y.; Yang, Zheng Rong; Mathews, David H.; Lu, Zhi John

    2015-01-01

    Recently, several experimental techniques have emerged for probing RNA structures based on high-throughput sequencing. However, most secondary structure prediction tools that incorporate probing data are designed and optimized for particular types of experiments. For example, RNAstructure-Fold is optimized for SHAPE data, while SeqFold is optimized for PARS data. Here, we report a new RNA secondary structure prediction method, restrained MaxExpect (RME), which can incorporate multiple types of experimental probing data and is based on a free energy model and an MEA (maximizing expected accuracy) algorithm. We first demonstrated that RME substantially improved secondary structure prediction with perfect restraints (base pair information of known structures). Next, we collected structure-probing data from diverse experiments (e.g. SHAPE, PARS and DMS-seq) and transformed them into a unified set of pairing probabilities with a posterior probabilistic model. By using the probability scores as restraints in RME, we compared its secondary structure prediction performance with two other well-known tools, RNAstructure-Fold (based on a free energy minimization algorithm) and SeqFold (based on a sampling algorithm). For SHAPE data, RME and RNAstructure-Fold performed better than SeqFold, because they markedly altered the energy model with the experimental restraints. For high-throughput data (e.g. PARS and DMS-seq) with lower probing efficiency, the secondary structure prediction performances of the tested tools were comparable, with performance improvements for only a portion of the tested RNAs. However, when the effects of tertiary structure and protein interactions were removed, RME showed the highest prediction accuracy in the DMS-accessible regions by incorporating in vivo DMS-seq data. PMID:26170232

  6. Crystal structure and prediction.

    PubMed

    Thakur, Tejender S; Dubey, Ritesh; Desiraju, Gautam R

    2015-04-01

    The notion of structure is central to the subject of chemistry. This review traces the development of the idea of crystal structure since the time when a crystal structure could be determined from a three-dimensional diffraction pattern and assesses the feasibility of computationally predicting an unknown crystal structure of a given molecule. Crystal structure prediction is of considerable fundamental and applied importance, and its successful execution is by no means a solved problem. The ease of crystal structure determination today has resulted in the availability of large numbers of crystal structures of higher-energy polymorphs and pseudopolymorphs. These structural libraries lead to the concept of a crystal structure landscape. A crystal structure of a compound may accordingly be taken as a data point in such a landscape.

  7. Crystal Structure and Prediction

    NASA Astrophysics Data System (ADS)

    Thakur, Tejender S.; Dubey, Ritesh; Desiraju, Gautam R.

    2015-04-01

    The notion of structure is central to the subject of chemistry. This review traces the development of the idea of crystal structure since the time when a crystal structure could be determined from a three-dimensional diffraction pattern and assesses the feasibility of computationally predicting an unknown crystal structure of a given molecule. Crystal structure prediction is of considerable fundamental and applied importance, and its successful execution is by no means a solved problem. The ease of crystal structure determination today has resulted in the availability of large numbers of crystal structures of higher-energy polymorphs and pseudopolymorphs. These structural libraries lead to the concept of a crystal structure landscape. A crystal structure of a compound may accordingly be taken as a data point in such a landscape.

  8. AIR VEHICLE INTEGRATION AND TECHNOLOGY RESEARCH (AVIATR) Task Order 0015: Predictive Capability for Hypersonic Structural Response and Life Prediction: Phase 1-Identification of Knowledge Gaps, Volume 1: Nonproprietary Version

    DTIC Science & Technology

    2010-09-01

    AFRL-RB-WP-TR-2010-3068,V1 AIR VEHICLE INTEGRATION AND TECHNOLOGY RESEARCH (AVIATR) Task Order 0015: Predictive Capability for Hypersonic ...Order 0015: Predictive Capability for Hypersonic Structural Response and Life Prediction: Phase 1-Identification of Knowledge Gaps, Volume 1...AND ADDRESS(ES) 8. PERFORMING ORGANIZATION The Boeing Company M/C 110-SK56 2600 Westminster Avenue Seal Beach , CA 90740 REPORT NUMBER 9

  9. Structural integrity of the substantia nigra and subthalamic nucleus predicts flexibility of instrumental learning in older-age individuals

    PubMed Central

    Chowdhury, Rumana; Guitart-Masip, Marc; Lambert, Christian; Dolan, Raymond J.; Düzel, Emrah

    2013-01-01

    Flexible instrumental learning is required to harness the appropriate behaviors to obtain rewards and to avoid punishments. The precise contribution of dopaminergic midbrain regions (substantia nigra/ventral tegmental area [SN/VTA]) to this form of behavioral adaptation remains unclear. Normal aging is associated with a variable loss of dopamine neurons in the SN/VTA. We therefore tested the relationship between flexible instrumental learning and midbrain structural integrity. We compared task performance on a probabilistic monetary go/no-go task, involving trial and error learning of: “go to win,” “no-go to win,” “go to avoid losing,” and “no-go to avoid losing” in 42 healthy older adults to previous behavioral data from 47 younger adults. Quantitative structural magnetization transfer images were obtained to index regional structural integrity. On average, both some younger and some older participants demonstrated a behavioral asymmetry whereby they were better at learning to act for reward (“go to win” > “no-go to win”), but better at learning not to act to avoid punishment (“no-go to avoid losing” > “go to avoid losing”). Older, but not younger, participants with greater structural integrity of the SN/VTA and the adjacent subthalamic nucleus could overcome this asymmetry. We show that interindividual variability among healthy older adults of the structural integrity within the SN/VTA and subthalamic nucleus relates to effective acquisition of competing instrumental responses. PMID:23623600

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

    PubMed Central

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

    2012-01-01

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

  11. Integrated structure- and ligand-based in silico approach to predict inhibition of cytochrome P450 2D6.

    PubMed

    Martiny, Virginie Y; Carbonell, Pablo; Chevillard, Florent; Moroy, Gautier; Nicot, Arnaud B; Vayer, Philippe; Villoutreix, Bruno O; Miteva, Maria A

    2015-12-15

    Cytochrome P450 (CYP) is a superfamily of enzymes responsible for the metabolism of drugs, xenobiotics and endogenous compounds. CYP2D6 metabolizes about 30% of drugs and predicting potential CYP2D6 inhibition is important in early-stage drug discovery. We developed an original in silico approach for the prediction of CYP2D6 inhibition combining the knowledge of the protein structure and its dynamic behavior in response to the binding of various ligands and machine learning modeling. This approach includes structural information for CYP2D6 based on the available crystal structures and molecular dynamic simulations (MD) that we performed to take into account conformational changes of the binding site. We performed modeling using three learning algorithms--support vector machine, RandomForest and NaiveBayesian--and we constructed combined models based on topological information of known CYP2D6 inhibitors and predicted binding energies computed by docking on both X-ray and MD protein conformations. In addition, we identified three MD-derived structures that are capable all together to better discriminate inhibitors and non-inhibitors compared with individual CYP2D6 conformations, thus ensuring complementary ligand profiles. Inhibition models based on classical molecular descriptors and predicted binding energies were able to predict CYP2D6 inhibition with an accuracy of 78% on the training set and 75% on the external validation set. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  12. An integrated degradation and structural model for predicting the service life of buried reinforced concrete structures for low- and intermediate-level radioactive waste disposal

    SciTech Connect

    Brandstetter, E.R.; Lolcama, J.L.; Reed, S.R.

    1994-03-01

    The primary focus of this study was to determine the possible rates of roof and wall failure and the times to structural collapse of the roof and walls of three vault designs at the Department of Energy`s Savannah River Site near Aiken, South Carolina. Failure was defined as a loss of ability to divert soil water around the vault. Collapse was defined as the total loss of structure integrity of the vault. Failure and eventual collapse of the three vault types results from concrete deterioration under stress, in the presence of corrosive soil water. Degradation rates for reinforced concrete were utilized, and the resultant changes in properties (such as strength, thickness, cracking and hydraulic conductivity) were evaluated. Baseline times to failure and collapse of the walls and roof components were modeled, and sensitivity analyses were conducted to provide boundaries on these estimated times. Thus, the goal of the project was to provide a bounding analysis of the time to roof and wall failure and potential collapse, rather than an actual prediction of the time to failure, and collapse.

  13. Integrated support structure

    NASA Technical Reports Server (NTRS)

    Bruneau, Stephen D.; Campbell, John T.; Struven, Christopher A.

    1990-01-01

    This Major Qualifying Project is part of the Advanced Space Design Program at WPI. The goal is to design a support structure for a NASA GetAway Special experimental canister. The payload integration, weight, volume, and structural integrity of the canister as specified by NASA guidelines were studied. The end result is a complete set of design drawings with interface drawings and data to specify the design and leave a base on which the next group can concentrate.

  14. An integrated approach for non-periodic dynamic response prediction of complex structures: Numerical and experimental analysis

    NASA Astrophysics Data System (ADS)

    Rahneshin, Vahid; Chierichetti, Maria

    2016-09-01

    In this paper, a combined numerical and experimental method, called Extended Load Confluence Algorithm, is presented to accurately predict the dynamic response of non-periodic structures when little or no information about the applied loads is available. This approach, which falls into the category of Shape Sensing methods, inputs limited experimental information acquired from sensors to a mapping algorithm that predicts the response at unmeasured locations. The proposed algorithm consists of three major cores: an experimental core for data acquisition, a numerical core based on Finite Element Method for modeling the structure, and a mapping algorithm that improves the numerical model based on a modal approach in the frequency domain. The robustness and precision of the proposed algorithm are verified through numerical and experimental examples. The results of this paper demonstrate that without a precise knowledge of the loads acting on the structure, the dynamic behavior of the system can be predicted in an effective and precise manner after just a few iterations.

  15. Integrating Drug's Mode of Action into Quantitative Structure-Activity Relationships for Improved Prediction of Drug-Induced Liver Injury.

    PubMed

    Wu, Leihong; Liu, Zhichao; Auerbach, Scott; Huang, Ruili; Chen, Minjun; McEuen, Kristin; Xu, Joshua; Fang, Hong; Tong, Weida

    2017-04-24

    Drug-induced liver injury (DILI) is complex in mechanism. Different drugs could undergo different mechanisms but result in the same DILI type, while the same drug could lead to different DILI types via different mechanisms. Therefore, predicting a drug's potential for DILI should take its underlying mechanisms into consideration. To achieve that, we constructed a novel approach by incorporating the drug's Mode of Action (MOA) into Quantitative Structure-Activity Relationship (QSAR) modeling. This MOA-DILI approach was examined using a data set of 333 drugs. The drugs were first grouped according to their MOA profiles (positive or negative in each MOA) based on the Tox21 qHTS assays. QSAR models for individual MOA assays were developed and subsequently combined to obtain the MOA-DILI model. A hold-out testing strategy (222 drugs for training and 111 drugs as a test set) was employed, which yielded a predictive accuracy of 0.711. The MOA-DILI model was directly compared with the standard QSAR approach using the same hold-out strategy, and the QSAR model yielded an accuracy of 0.662. To minimize the random chance in splitting training/test sets, the hold-out testing process was repeated 1000 times, and the observed difference in prediction accuracy between MOA-DILI and QSARs was statistically significant (P value <0.0001). Out of 17 MOAs used, four assays (i.e., antioxidant response elements, PPAR-gamma, estrogen receptor, and thyroid receptor assays) contributed most to the improved prediction of the MOA-DILI model over QSARs. In conclusion, the MOA-DILI approach has the potential to significantly improve predictive outcomes and to reveal complex relationships between MOAs and DILI, all of which would be helpful in developing DILI predictive models in drug screening and for risk assessment of industrial chemicals.

  16. Protein structure prediction using hybrid AI methods

    SciTech Connect

    Guan, X.; Mural, R.J.; Uberbacher, E.C.

    1993-11-01

    This paper describes a new approach for predicting protein structures based on Artificial Intelligence methods and genetic algorithms. We combine nearest neighbor searching algorithms, neural networks, heuristic rules and genetic algorithms to form an integrated system to predict protein structures from their primary amino acid sequences. First we describe our methods and how they are integrated, and then apply our methods to several protein sequences. The results are very close to the real structures obtained by crystallography. Parallel genetic algorithms are also implemented.

  17. Water in protein structure prediction

    PubMed Central

    Papoian, Garegin A.; Ulander, Johan; Eastwood, Michael P.; Luthey-Schulten, Zaida; Wolynes, Peter G.

    2004-01-01

    Proteins have evolved to use water to help guide folding. A physically motivated, nonpairwise-additive model of water-mediated interactions added to a protein structure prediction Hamiltonian yields marked improvement in the quality of structure prediction for larger proteins. Free energy profile analysis suggests that long-range water-mediated potentials guide folding and smooth the underlying folding funnel. Analyzing simulation trajectories gives direct evidence that water-mediated interactions facilitate native-like packing of supersecondary structural elements. Long-range pairing of hydrophilic groups is an integral part of protein architecture. Specific water-mediated interactions are a universal feature of biomolecular recognition landscapes in both folding and binding. PMID:14988499

  18. Integrated structural health monitoring.

    SciTech Connect

    Farrar, C. R.

    2001-01-01

    Structural health monitoring is the implementation of a damage detection strategy for aerospace, civil and mechanical engineering infrastructure. Typical damage experienced by this infrastructure might be the development of fatigue cracks, degradation of structural connections, or bearing wear in rotating machinery. The goal of the research effort reported herein is to develop a robust and cost-effective structural health monitoring solution by integrating and extending technologies from various engineering and information technology disciplines. It is the authors opinion that all structural health monitoring systems must be application specific. Therefore, a specific application, monitoring welded moment resisting steel frame connections in structures subjected to seismic excitation, is described along with the motivation for choosing this application. The structural health monitoring solution for this application will integrate structural dynamics, wireless data acquisition, local actuation, micro-electromechanical systems (MEMS) technology, and statistical pattern recognition algorithms. The proposed system is based on an assessment of the deficiencies associated with many current structural health monitoring technologies including past efforts by the authors. This paper provides an example of the integrated approach to structural health monitoring being undertaken at Los Alamos National Laboratory and summarizes progress to date on various aspects of the technology development.

  19. Integrated structural health monitoring

    NASA Astrophysics Data System (ADS)

    Farrar, Charles R.; Sohn, Hoon; Fugate, Michael L.; Czarnecki, Jerry J.

    2001-07-01

    Structural health monitoring is the implementation of a damage detection strategy for aerospace, civil and mechanical engineering infrastructure. Typical damage experienced by this infrastructure might be the development of fatigue cracks, degradation of structural connections, or bearing wear in rotating machinery. The goal of the research effort reported herein is to develop a robust and cost-effective structural health monitoring solution by integrating and extending technologies from various engineering and information technology disciplines. It is the author's opinion that all structural health monitoring systems must be application specific. Therefore, a specific application, monitoring welded moment resisting steel frame connections in structures subjected to seismic excitation, is described along with the motivation for choosing this application. The structural health monitoring solution for this application will integrate structural dynamics, wireless data acquisition, local actuation, micro-electromechanical systems (MEMS) technology, and statistical pattern recognition algorithms. The proposed system is based on an assessment of the deficiencies associated with many current structural health monitoring technologies including past efforts by the authors. This paper provides an example of the integrated approach to structural health monitoring being undertaken at Los Alamos National Laboratory and summarizes progress to date on various aspects of the technology development.

  20. Structural model integrity

    NASA Technical Reports Server (NTRS)

    Wallerstein, D. V.; Lahey, R. S.; Haggenmacher, G. W.

    1977-01-01

    Many of the practical aspects and problems of ensuring the integrity of a structural model are discussed, as well as the steps which have been taken in the NASTRAN system to assure that these checks can be routinely performed. Model integrity as used applies not only to the structural model but also to the loads applied to the model. Emphasis is also placed on the fact that when dealing with substructure analysis, all of the checking procedures discussed should be applied at the lowest level of substructure prior to any coupling.

  1. Structural model integrity

    NASA Technical Reports Server (NTRS)

    Wallerstein, D. V.; Lahey, R. S.; Haggenmacher, G. W.

    1977-01-01

    Many of the practical aspects and problems of ensuring the integrity of a structural model are discussed, as well as the steps which have been taken in the NASTRAN system to assure that these checks can be routinely performed. Model integrity as used applies not only to the structural model but also to the loads applied to the model. Emphasis is also placed on the fact that when dealing with substructure analysis, all of the checking procedures discussed should be applied at the lowest level of substructure prior to any coupling.

  2. Integrative Approaches for Predicting in vivo Effects of Chemicals from their Structural Descriptors and the Results of Short-term Biological Assays

    PubMed Central

    Low, Yen S.; Sedykh, Alexander; Rusyn, Ivan; Tropsha, Alexander

    2017-01-01

    Cheminformatics approaches such as Quantitative Structure Activity Relationship (QSAR) modeling have been used traditionally for predicting chemical toxicity. In recent years, high throughput biological assays have been increasingly employed to elucidate mechanisms of chemical toxicity and predict toxic effects of chemicals in vivo. The data generated in such assays can be considered as biological descriptors of chemicals that can be combined with molecular descriptors and employed in QSAR modeling to improve the accuracy of toxicity prediction. In this review, we discuss several approaches for integrating chemical and biological data for predicting biological effects of chemicals in vivo and compare their performance across several data sets. We conclude that while no method consistently shows superior performance, the integrative approaches rank consistently among the best yet offer enriched interpretation of models over those built with either chemical or biological data alone. We discuss the outlook for such interdisciplinary methods and offer recommendations to further improve the accuracy and interpretability of computational models that predict chemical toxicity. PMID:24805064

  3. Functional region prediction with a set of appropriate homologous sequences-an index for sequence selection by integrating structure and sequence information with spatial statistics

    PubMed Central

    2012-01-01

    Background The detection of conserved residue clusters on a protein structure is one of the effective strategies for the prediction of functional protein regions. Various methods, such as Evolutionary Trace, have been developed based on this strategy. In such approaches, the conserved residues are identified through comparisons of homologous amino acid sequences. Therefore, the selection of homologous sequences is a critical step. It is empirically known that a certain degree of sequence divergence in the set of homologous sequences is required for the identification of conserved residues. However, the development of a method to select homologous sequences appropriate for the identification of conserved residues has not been sufficiently addressed. An objective and general method to select appropriate homologous sequences is desired for the efficient prediction of functional regions. Results We have developed a novel index to select the sequences appropriate for the identification of conserved residues, and implemented the index within our method to predict the functional regions of a protein. The implementation of the index improved the performance of the functional region prediction. The index represents the degree of conserved residue clustering on the tertiary structure of the protein. For this purpose, the structure and sequence information were integrated within the index by the application of spatial statistics. Spatial statistics is a field of statistics in which not only the attributes but also the geometrical coordinates of the data are considered simultaneously. Higher degrees of clustering generate larger index scores. We adopted the set of homologous sequences with the highest index score, under the assumption that the best prediction accuracy is obtained when the degree of clustering is the maximum. The set of sequences selected by the index led to higher functional region prediction performance than the sets of sequences selected by other sequence

  4. Functional region prediction with a set of appropriate homologous sequences--an index for sequence selection by integrating structure and sequence information with spatial statistics.

    PubMed

    Nemoto, Wataru; Toh, Hiroyuki

    2012-05-29

    The detection of conserved residue clusters on a protein structure is one of the effective strategies for the prediction of functional protein regions. Various methods, such as Evolutionary Trace, have been developed based on this strategy. In such approaches, the conserved residues are identified through comparisons of homologous amino acid sequences. Therefore, the selection of homologous sequences is a critical step. It is empirically known that a certain degree of sequence divergence in the set of homologous sequences is required for the identification of conserved residues. However, the development of a method to select homologous sequences appropriate for the identification of conserved residues has not been sufficiently addressed. An objective and general method to select appropriate homologous sequences is desired for the efficient prediction of functional regions. We have developed a novel index to select the sequences appropriate for the identification of conserved residues, and implemented the index within our method to predict the functional regions of a protein. The implementation of the index improved the performance of the functional region prediction. The index represents the degree of conserved residue clustering on the tertiary structure of the protein. For this purpose, the structure and sequence information were integrated within the index by the application of spatial statistics. Spatial statistics is a field of statistics in which not only the attributes but also the geometrical coordinates of the data are considered simultaneously. Higher degrees of clustering generate larger index scores. We adopted the set of homologous sequences with the highest index score, under the assumption that the best prediction accuracy is obtained when the degree of clustering is the maximum. The set of sequences selected by the index led to higher functional region prediction performance than the sets of sequences selected by other sequence-based methods

  5. TRITIUM RESERVOIR STRUCTURAL PERFORMANCE PREDICTION

    SciTech Connect

    Lam, P.S.; Morgan, M.J

    2005-11-10

    The burst test is used to assess the material performance of tritium reservoirs in the surveillance program in which reservoirs have been in service for extended periods of time. A materials system model and finite element procedure were developed under a Savannah River Site Plant-Directed Research and Development (PDRD) program to predict the structural response under a full range of loading and aged material conditions of the reservoir. The results show that the predicted burst pressure and volume ductility are in good agreement with the actual burst test results for the unexposed units. The material tensile properties used in the calculations were obtained from a curved tensile specimen harvested from a companion reservoir by Electric Discharge Machining (EDM). In the absence of exposed and aged material tensile data, literature data were used for demonstrating the methodology in terms of the helium-3 concentration in the metal and the depth of penetration in the reservoir sidewall. It can be shown that the volume ductility decreases significantly with the presence of tritium and its decay product, helium-3, in the metal, as was observed in the laboratory-controlled burst tests. The model and analytical procedure provides a predictive tool for reservoir structural integrity under aging conditions. It is recommended that benchmark tests and analysis for aged materials be performed. The methodology can be augmented to predict performance for reservoir with flaws.

  6. Integrating In Silico Prediction Methods, Molecular Docking, and Molecular Dynamics Simulation to Predict the Impact of ALK Missense Mutations in Structural Perspective

    PubMed Central

    Priya Doss, C. George; Chen, Luonan

    2014-01-01

    Over the past decade, advancements in next generation sequencing technology have placed personalized genomic medicine upon horizon. Understanding the likelihood of disease causing mutations in complex diseases as pathogenic or neutral remains as a major task and even impossible in the structural context because of its time consuming and expensive experiments. Among the various diseases causing mutations, single nucleotide polymorphisms (SNPs) play a vital role in defining individual's susceptibility to disease and drug response. Understanding the genotype-phenotype relationship through SNPs is the first and most important step in drug research and development. Detailed understanding of the effect of SNPs on patient drug response is a key factor in the establishment of personalized medicine. In this paper, we represent a computational pipeline in anaplastic lymphoma kinase (ALK) for SNP-centred study by the application of in silico prediction methods, molecular docking, and molecular dynamics simulation approaches. Combination of computational methods provides a way in understanding the impact of deleterious mutations in altering the protein drug targets and eventually leading to variable patient's drug response. We hope this rapid and cost effective pipeline will also serve as a bridge to connect the clinicians and in silico resources in tailoring treatments to the patients' specific genotype. PMID:25054154

  7. Integrating in silico prediction methods, molecular docking, and molecular dynamics simulation to predict the impact of ALK missense mutations in structural perspective.

    PubMed

    Doss, C George Priya; Chakraborty, Chiranjib; Chen, Luonan; Zhu, Hailong

    2014-01-01

    Over the past decade, advancements in next generation sequencing technology have placed personalized genomic medicine upon horizon. Understanding the likelihood of disease causing mutations in complex diseases as pathogenic or neutral remains as a major task and even impossible in the structural context because of its time consuming and expensive experiments. Among the various diseases causing mutations, single nucleotide polymorphisms (SNPs) play a vital role in defining individual's susceptibility to disease and drug response. Understanding the genotype-phenotype relationship through SNPs is the first and most important step in drug research and development. Detailed understanding of the effect of SNPs on patient drug response is a key factor in the establishment of personalized medicine. In this paper, we represent a computational pipeline in anaplastic lymphoma kinase (ALK) for SNP-centred study by the application of in silico prediction methods, molecular docking, and molecular dynamics simulation approaches. Combination of computational methods provides a way in understanding the impact of deleterious mutations in altering the protein drug targets and eventually leading to variable patient's drug response. We hope this rapid and cost effective pipeline will also serve as a bridge to connect the clinicians and in silico resources in tailoring treatments to the patients' specific genotype.

  8. Integral Textile Ceramic Structures

    NASA Astrophysics Data System (ADS)

    Marshall, David B.; Cox, Brian N.

    2008-08-01

    A new paradigm for ceramic composite structural components enables functionality in heat exchange, transpiration, detailed shape, and thermal strain management that significantly exceeds the prior art. The paradigm is based on the use of three-dimensional fiber reinforcement that is tailored to the specific shape, stress, and thermal requirements of a structural application and therefore generally requires innovative textile methods for each realization. Key features include the attainment of thin skins (less than 1 mm) that are nevertheless structurally robust, transpiration holes formed without cutting fibers, double curvature, compliant integral attachment to other structures that avoids thermal stress buildup, and microcomposite ceramic matrices that minimize spalling and allow the formation of smooth surfaces. All these features can be combined into structures of very varied gross shape and function, using a wide range of materials such as all-oxide systems and SiC and carbon fibers in SiC matrices. Illustrations are drawn from rocket nozzles, thermal protection systems, and gas turbine engines. The new design challenges that arise for such material/structure systems are being met by specialized computational modeling that departs significantly in the representation of materials behavior from that used in conventional finite element methods.

  9. Protein structural motifs in prediction and design.

    PubMed

    Mackenzie, Craig O; Grigoryan, Gevorg

    2017-06-01

    The Protein Data Bank (PDB) has been an integral resource for shaping our fundamental understanding of protein structure and for the advancement of such applications as protein design and structure prediction. Over the years, information from the PDB has been used to generate models ranging from specific structural mechanisms to general statistical potentials. With accumulating structural data, it has become possible to mine for more complete and complex structural observations, deducing more accurate generalizations. Motif libraries, which capture recurring structural features along with their sequence preferences, have exposed modularity in the structural universe and found successful application in various problems of structural biology. Here we summarize recent achievements in this arena, focusing on subdomain level structural patterns and their applications to protein design and structure prediction, and suggest promising future directions as the structural database continues to grow. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Integration of M.I.T. Studies on Prediction and Control of Distortion in Welded Aluminum Structures

    DTIC Science & Technology

    1976-09-20

    structures by inteqrating results obtained recently at M.I.T. The teport covers all the informacion in seven main sections, as summarized below. At the...1 to 4 feet wide , and 6 feet long. 10 (2) To analyze these transient temperature and strain changes by utilizing one-dimensional and two-dimensional...including the National Science Foundation, Welding Research Council, Office of Naval Research and a group of companies.* The following is a list of

  11. Air Vehicle Integration and Technology Research (AVIATR). Task Order 0023: Predictive Capability for Hypersonic Structural Response and Life Prediction: Phase 2 - Detailed Design of Hypersonic Cruise Vehicle Hot-Structure

    DTIC Science & Technology

    2012-02-01

    Structural Response and Life Prediction: Phase II – Detailed Design of Hypersonic Cruise Vehicle Hot-Structure Rob Quiroz , Jon Embler, Rich Jacobs...5a. CONTRACT NUMBER FA8650-08-D-3857-0023 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 62201F 6. AUTHOR(S) Rob Quiroz , Jon Embler, Rich...officer for the program has been Ms. Genet Stewart. The Boeing team was composed of a core group consisting of Rob Quiroz , Rick Jacobs, George

  12. Integrating satellite remote sensing data and field data to predict rangeland structural indicators at the continental scale

    NASA Astrophysics Data System (ADS)

    Zhang, J.; Okin, G.

    2016-12-01

    Rangelands provide a variety of important ecosystem goods and services across drylands globally. They are also the most important emitters of dust across the globe. Field data collection based on points does not represent spatially continuous information about surface variables and, given the vast size of the world's rangelands, cannot cover even a small fraction of their area. Remote sensing is potentially a labor- and time-saving method to observe important rangeland vegetation variables at both temporal and spatial scales. Information on vegetation cover, bare gap size, and plant height provide key rangeland vegetation variables in arid and semiarid rangelands, in part because they strongly impact dust emission and determine wildlife habitat characteristics. This study reports on relationships between remote sensing in the reflected solar spectrum and field measures related to these three variables, and shows how these relationships can be extended to produce spatially and temporally continuous datasets coupled with quantitative estimates of error. Field data for this study included over 3,800 Assessment, Inventory, and Monitoring (AIM) measurements on Bureau of Land Management (BLM) lands throughout the western US. Remote sensing data were derived from MODIS nadir BRDF-adjusted reflectance (NBAR) and Landsat 8 OLI surface reflectance. Normalized bare gap size, total foliar cover, herbaceous cover and herbaceous height exhibit the greatest predictability from remote sensing variables with physically-reasonable relationships between remote sensing variables and field measures. Data fields produced using these relationships across the western US exhibit good agreement with independent high-resolution imagery.

  13. AIR VEHICLES INTEGRATION AND TECHNOLOGY RESEARCH (AVIATR) Task Order 0015: Predictive Capability for Hypersonic Structural Response and Life Prediction Phase 1 - Identification of Knowledge Gaps

    DTIC Science & Technology

    2010-08-01

    rudder, all-moving horizontal tails, and body flap were “beefed up ” based on preliminary flutter assessment. The all-moving tail/ wing carry-through...external surface temperatures on the fuselage and wings of up to 640°F, and the acreage surface and structural temperatures in the engine nacelle area...edge to rotate up into the air-stream inducing a heating amplification on the panel edge as well as on the adjacent panels. In the X-33 program the

  14. (PS)2: protein structure prediction server

    PubMed Central

    Chen, Chih-Chieh; Hwang, Jenn-Kang; Yang, Jinn-Moon

    2006-01-01

    Protein structure prediction provides valuable insights into function, and comparative modeling is one of the most reliable methods to predict 3D structures directly from amino acid sequences. However, critical problems arise during the selection of the correct templates and the alignment of query sequences therewith. We have developed an automatic protein structure prediction server, (PS)2, which uses an effective consensus strategy both in template selection, which combines PSI-BLAST and IMPALA, and target–template alignment integrating PSI-BLAST, IMPALA and T-Coffee. (PS)2 was evaluated for 47 comparative modeling targets in CASP6 (Critical Assessment of Techniques for Protein Structure Prediction). For the benchmark dataset, the predictive performance of (PS)2, based on the mean GTD_TS score, was superior to 10 other automatic servers. Our method is based solely on the consensus sequence and thus is considerably faster than other methods that rely on the additional structural consensus of templates. Our results show that (PS)2, coupled with suitable consensus strategies and a new similarity score, can significantly improve structure prediction. Our approach should be useful in structure prediction and modeling. The (PS)2 is available through the website at . PMID:16844981

  15. Integrated control-structure design

    NASA Technical Reports Server (NTRS)

    Hunziker, K. Scott; Kraft, Raymond H.; Bossi, Joseph A.

    1991-01-01

    A new approach for the design and control of flexible space structures is described. The approach integrates the structure and controller design processes thereby providing extra opportunities for avoiding some of the disastrous effects of control-structures interaction and for discovering new, unexpected avenues of future structural design. A control formulation based on Boyd's implementation of Youla parameterization is employed. Control design parameters are coupled with structural design variables to produce a set of integrated-design variables which are selected through optimization-based methodology. A performance index reflecting spacecraft mission goals and constraints is formulated and optimized with respect to the integrated design variables. Initial studies have been concerned with achieving mission requirements with a lighter, more flexible space structure. Details of the formulation of the integrated-design approach are presented and results are given from a study involving the integrated redesign of a flexible geostationary platform.

  16. Predicting Faculty Integration of Faith and Learning

    ERIC Educational Resources Information Center

    Kaul, Corina R.; Hardin, Kimberly A.; Beaujean, A. Alexander

    2017-01-01

    Concern regarding the secularization of Christian higher education has prompted researchers to investigate the extent that faith and learning is integrated at a faculty level and what factors might predict faculty integration (Lyon, Beaty, Parker, & Mencken, 2005). This research attempted to replicate Lyon et al.'s (2005) logistic regression…

  17. Protein Function Prediction: Towards Integration of Similarity Metrics

    PubMed Central

    Erdin, Serkan; Lisewski, Andreas Martin; Lichtarge, Olivier

    2011-01-01

    Summary Genomics centers discover increasingly many protein sequences and structures, but not necessarily their full biological functions. Thus, currently, fewer than one percent of proteins have experimentally verified biochemical activities. To fill this gap, function prediction algorithms apply metrics of similarity between proteins on the premise that those sufficiently alike in sequence, or structure, will perform identical functions. Although high sensitivity is elusive, network analyses that integrate these metrics together hold the promise of rapid gains in function prediction specificity. PMID:21353529

  18. Kalman-predictive-proportional-integral-derivative (KPPID)

    SciTech Connect

    Fluerasu, A.; Sutton, M.

    2004-12-17

    With third generation synchrotron X-ray sources, it is possible to acquire detailed structural information about the system under study with time resolution orders of magnitude faster than was possible a few years ago. These advances have generated many new challenges for changing and controlling the state of the system on very short time scales, in a uniform and controlled manner. For our particular X-ray experiments on crystallization or order-disorder phase transitions in metallic alloys, we need to change the sample temperature by hundreds of degrees as fast as possible while avoiding over or under shooting. To achieve this, we designed and implemented a computer-controlled temperature tracking system which combines standard Proportional-Integral-Derivative (PID) feedback, thermal modeling and finite difference thermal calculations (feedforward), and Kalman filtering of the temperature readings in order to reduce the noise. The resulting Kalman-Predictive-Proportional-Integral-Derivative (KPPID) algorithm allows us to obtain accurate control, to minimize the response time and to avoid over/under shooting, even in systems with inherently noisy temperature readings and time delays. The KPPID temperature controller was successfully implemented at the Advanced Photon Source at Argonne National Laboratories and was used to perform coherent and time-resolved X-ray diffraction experiments.

  19. Both predictability and familiarity facilitate contour integration.

    PubMed

    Sassi, Michaël; Demeyer, Maarten; Machilsen, Bart; Putzeys, Tom; Wagemans, Johan

    2014-05-30

    Research has shown that contour detection is impaired in the visual periphery for snake-shaped Gabor contours but not for circular and elliptical contours. This discrepancy in findings could be due to differences in intrinsic shape properties, including shape closure and curvature variation, as well as to differences in stimulus predictability and familiarity. In a detection task using only circular contours, the target shape is both more familiar and more predictable to the observer compared with a detection task in which a different snake-shaped contour is presented on each trial. In this study, we investigated the effects of stimulus familiarity and predictability on contour integration by manipulating and disentangling the familiarity and predictability of snakelike stimuli. We manipulated stimulus familiarity by extensively training observers with one particular snake shape. Predictability was varied by alternating trial blocks with only a single target shape and trial blocks with multiple target shapes. Our results show that both predictability and familiarity facilitated contour integration, which constitutes novel behavioral evidence for the adaptivity of the contour integration mechanism in humans. If familiarity or predictability facilitated contour integration in the periphery specifically, this could explain the discrepant findings obtained with snake contours as compared with circles or ellipses. However, we found that their facilitatory effects did not differ between central and peripheral vision and thus cannot explain that particular discrepancy in the literature.

  20. Structural integrity of the corpus callosum predicts long-term transfer of fluid intelligence-related training gains in normal aging.

    PubMed

    Wolf, Dominik; Fischer, Florian Udo; Fesenbeckh, Johanna; Yakushev, Igor; Lelieveld, Irene Maria; Scheurich, Armin; Schermuly, Ingrid; Zschutschke, Lisa; Fellgiebel, Andreas

    2014-01-01

    Although cognitive training usually improves cognitive test performance, the capability to transfer these training gains into respective or functionally related cognitive domains varies significantly. Since most studies demonstrate rather limited transfer effects in older adults, aging might be an important factor in transfer capability differences. This study investigated the transfer capability of logical reasoning training gains to a measure of Fluid Intelligence (Gf) in relation to age, general intelligence, and brain structural integrity as measured by diffusion tensor imaging. In a group of 41 highly educated healthy elderly, 71% demonstrated successful transfer immediately after a 4-week training session (i.e. short-term transfer). In a subgroup of 22% of subjects transfer maintained over a 3-month follow-up period (i.e. long-term transfer). While short-term transfer was not related to structural integrity, long-term transfer was associated with increased structural integrity in corpus and genu of the corpus callosum. Since callosal structural integrity was also related to age (in the present and foregoing studies), previously observed associations between age and transfer might be moderated by the structural integrity. Surprisingly, age was not directly associated with transfer in this study which could be explained by the multi-dependency of the structural integrity (modulating factors beside age, e.g. genetics). In this highly educated sample, general intelligence was not related to transfer suggesting that high intelligence is not sufficient for transfer in normal aging. Further studies are needed to reveal the interaction of transfer, age, and structural integrity and delineate mechanisms of age-dependent transfer capabilities. Copyright © 2012 Wiley Periodicals, Inc.

  1. Reliability and structural integrity

    NASA Technical Reports Server (NTRS)

    Davidson, J. R.

    1976-01-01

    An analytic model is developed to calculate the reliability of a structure after it is inspected for cracks. The model accounts for the growth of undiscovered cracks between inspections and their effect upon the reliability after subsequent inspections. The model is based upon a differential form of Bayes' Theorem for reliability, and upon fracture mechanics for crack growth.

  2. Integrating alternative splicing detection into gene prediction

    PubMed Central

    Foissac, Sylvain; Schiex, Thomas

    2005-01-01

    Background Alternative splicing (AS) is now considered as a major actor in transcriptome/proteome diversity and it cannot be neglected in the annotation process of a new genome. Despite considerable progresses in term of accuracy in computational gene prediction, the ability to reliably predict AS variants when there is local experimental evidence of it remains an open challenge for gene finders. Results We have used a new integrative approach that allows to incorporate AS detection into ab initio gene prediction. This method relies on the analysis of genomically aligned transcript sequences (ESTs and/or cDNAs), and has been implemented in the dynamic programming algorithm of the graph-based gene finder EuGÈNE. Given a genomic sequence and a set of aligned transcripts, this new version identifies the set of transcripts carrying evidence of alternative splicing events, and provides, in addition to the classical optimal gene prediction, alternative optimal predictions (among those which are consistent with the AS events detected). This allows for multiple annotations of a single gene in a way such that each predicted variant is supported by a transcript evidence (but not necessarily with a full-length coverage). Conclusions This automatic combination of experimental data analysis and ab initio gene finding offers an ideal integration of alternatively spliced gene prediction inside a single annotation pipeline. PMID:15705189

  3. Structural integrity in aircraft.

    NASA Technical Reports Server (NTRS)

    Hardrath, H. F.

    1973-01-01

    The paper reviews briefly the current design philosophies for achieving long, efficient, and reliable service in aircraft structures. The strengths and weaknesses of these design philosophies and their demonstrated records of success are discussed. The state of the art has not been developed to the point where designing can be done without major test inspection and maintenance programs. A broad program of research is proposed through which a viable computerized design scheme will be provided during the next decade. The program will organize and correlate existing knowledge on fatigue and fracture behavior, identify gaps in this knowledge, and guide specific research to upgrade design capabilities.

  4. SHAPE-Directed RNA Secondary Structure Prediction

    PubMed Central

    Low, Justin T.; Weeks, Kevin M.

    2010-01-01

    The diverse functional roles of RNA are determined by its underlying structure. Accurate and comprehensive knowledge of RNA structure would inform a broader understanding of RNA biology and facilitate exploiting RNA as a biotechnological tool and therapeutic target. Determining the pattern of base pairing, or secondary structure, of RNA is a first step in these endeavors. Advances in experimental, computational, and comparative analysis approaches for analyzing secondary structure have yielded accurate structures for many small RNAs, but only a few large (>500 nts) RNAs. In addition, most current methods for determining a secondary structure require considerable effort, analytical expertise, and technical ingenuity. In this review, we outline an efficient strategy for developing accurate secondary structure models for RNAs of arbitrary length. This approach melds structural information obtained using SHAPE chemistry with structure prediction using nearest-neighbor rules and the dynamic programming algorithm implemented in the RNAstructure program. Prediction accuracies reach ≥95% for RNAs on the kilobase scale. This approach facilitates both development of new models and refinement of existing RNA structure models, which we illustrate using the Gag-Pol frameshift element in an HIV-1 M-group genome. Most promisingly, integrated experimental and computational refinement brings closer the ultimate goal of efficiently and accurately establishing the secondary structure for any RNA sequence. PMID:20554050

  5. Structurally integrated steel solar collector

    DOEpatents

    Moore, S.W.

    1975-06-03

    Herein is disclosed a flate plate solar heat collector unit. The solar collector is integrated as a structural unit so that the collector also functions as the building roof. The functions of efficient heat collection, liquid coolant flow passages, roof structural support, and building insulation are combined into one unit.

  6. Structurally integrated steel solar collector

    DOEpatents

    Moore, Stanley W.

    1977-03-08

    Herein is disclosed a flat plate solar heat collector unit. The solar collector is integrated as a structural unit so that the collector also functions as the building roof. The functions of efficient heat collection, liquid coolant flow passages, roof structural support and building insulation are combined into one unit.

  7. Integrative structure modeling with IMP.

    PubMed

    Webb, Benjamin; Viswanath, Shruthi; Bonomi, Massimiliano; Pellarin, Riccardo; Greenberg, Charles H; Saltzberg, Daniel; Sali, Andrej

    2017-09-28

    Building models of a biological system that are consistent with the myriad data available is one of the key challenges in biology. Modeling the structure and dynamics of macromolecular assemblies, for example, can give insights into how biological systems work, evolved, might be controlled, and even designed. Integrative structure modeling casts the building of structural models as a computational optimization problem, for which information about the assembly is encoded into a scoring function that evaluates candidate models. Here, we describe our open source software suite for integrative structure modeling, Integrative Modeling Platform (IMP) (https://integrativemodeling.org), and demonstrate its use. This article is protected by copyright. All rights reserved. © 2017 The Protein Society.

  8. Integrating Diverse Datasets Improves Developmental Enhancer Prediction

    PubMed Central

    Erwin, Genevieve D.; Oksenberg, Nir; Truty, Rebecca M.; Kostka, Dennis; Murphy, Karl K.; Ahituv, Nadav; Pollard, Katherine S.; Capra, John A.

    2014-01-01

    Gene-regulatory enhancers have been identified using various approaches, including evolutionary conservation, regulatory protein binding, chromatin modifications, and DNA sequence motifs. To integrate these different approaches, we developed EnhancerFinder, a two-step method for distinguishing developmental enhancers from the genomic background and then predicting their tissue specificity. EnhancerFinder uses a multiple kernel learning approach to integrate DNA sequence motifs, evolutionary patterns, and diverse functional genomics datasets from a variety of cell types. In contrast with prediction approaches that define enhancers based on histone marks or p300 sites from a single cell line, we trained EnhancerFinder on hundreds of experimentally verified human developmental enhancers from the VISTA Enhancer Browser. We comprehensively evaluated EnhancerFinder using cross validation and found that our integrative method improves the identification of enhancers over approaches that consider a single type of data, such as sequence motifs, evolutionary conservation, or the binding of enhancer-associated proteins. We find that VISTA enhancers active in embryonic heart are easier to identify than enhancers active in several other embryonic tissues, likely due to their uniquely high GC content. We applied EnhancerFinder to the entire human genome and predicted 84,301 developmental enhancers and their tissue specificity. These predictions provide specific functional annotations for large amounts of human non-coding DNA, and are significantly enriched near genes with annotated roles in their predicted tissues and lead SNPs from genome-wide association studies. We demonstrate the utility of EnhancerFinder predictions through in vivo validation of novel embryonic gene regulatory enhancers from three developmental transcription factor loci. Our genome-wide developmental enhancer predictions are freely available as a UCSC Genome Browser track, which we hope will enable

  9. Integrating diverse datasets improves developmental enhancer prediction.

    PubMed

    Erwin, Genevieve D; Oksenberg, Nir; Truty, Rebecca M; Kostka, Dennis; Murphy, Karl K; Ahituv, Nadav; Pollard, Katherine S; Capra, John A

    2014-06-01

    Gene-regulatory enhancers have been identified using various approaches, including evolutionary conservation, regulatory protein binding, chromatin modifications, and DNA sequence motifs. To integrate these different approaches, we developed EnhancerFinder, a two-step method for distinguishing developmental enhancers from the genomic background and then predicting their tissue specificity. EnhancerFinder uses a multiple kernel learning approach to integrate DNA sequence motifs, evolutionary patterns, and diverse functional genomics datasets from a variety of cell types. In contrast with prediction approaches that define enhancers based on histone marks or p300 sites from a single cell line, we trained EnhancerFinder on hundreds of experimentally verified human developmental enhancers from the VISTA Enhancer Browser. We comprehensively evaluated EnhancerFinder using cross validation and found that our integrative method improves the identification of enhancers over approaches that consider a single type of data, such as sequence motifs, evolutionary conservation, or the binding of enhancer-associated proteins. We find that VISTA enhancers active in embryonic heart are easier to identify than enhancers active in several other embryonic tissues, likely due to their uniquely high GC content. We applied EnhancerFinder to the entire human genome and predicted 84,301 developmental enhancers and their tissue specificity. These predictions provide specific functional annotations for large amounts of human non-coding DNA, and are significantly enriched near genes with annotated roles in their predicted tissues and lead SNPs from genome-wide association studies. We demonstrate the utility of EnhancerFinder predictions through in vivo validation of novel embryonic gene regulatory enhancers from three developmental transcription factor loci. Our genome-wide developmental enhancer predictions are freely available as a UCSC Genome Browser track, which we hope will enable

  10. Servers for protein structure prediction.

    PubMed

    Fischer, Daniel

    2006-04-01

    The 1990s cultivated a generation of protein structure human predictors. As a result of structural genomics and genome sequencing projects, and significant improvements in the performance of protein structure prediction methods, a generation of automated servers has evolved in the past few years. Servers for close and distant homology modeling are now routinely used by many biologists, and have already been applied to the experimental structure determination process itself, and to the interpretation and annotation of genome sequences. Because dozens of servers are currently available, it is hard for a biologist to know which server(s) to use; however, the state of the art of these methods is now assessed through the LiveBench and CAFASP experiments. Meta-servers--servers that use the results of other autonomous servers to produce a consensus prediction--have proven to be the best performers, and are already challenging all but a handful of expert human predictors. The difference in performance of the top ten autonomous (non-meta) servers is small and hard to assess using relatively small test sets. Recent experiments suggest that servers will soon free humans from most of the burden of protein structure prediction.

  11. Protein complex compositions predicted by structural similarity

    PubMed Central

    Davis, Fred P.; Braberg, Hannes; Shen, Min-Yi; Pieper, Ursula; Sali, Andrej; Madhusudhan, M.S.

    2006-01-01

    Proteins function through interactions with other molecules. Thus, the network of physical interactions among proteins is of great interest to both experimental and computational biologists. Here we present structure-based predictions of 3387 binary and 1234 higher order protein complexes in Saccharomyces cerevisiae involving 924 and 195 proteins, respectively. To generate candidate complexes, comparative models of individual proteins were built and combined together using complexes of known structure as templates. These candidate complexes were then assessed using a statistical potential, derived from binary domain interfaces in PIBASE (). The statistical potential discriminated a benchmark set of 100 interface structures from a set of sequence-randomized negative examples with a false positive rate of 3% and a true positive rate of 97%. Moreover, the predicted complexes were also filtered using functional annotation and sub-cellular localization data. The ability of the method to select the correct binding mode among alternates is demonstrated for three camelid VHH domain—porcine α–amylase interactions. We also highlight the prediction of co-complexed domain superfamilies that are not present in template complexes. Through integration with MODBASE, the application of the method to proteomes that are less well characterized than that of S.cerevisiae will contribute to expansion of the structural and functional coverage of protein interaction space. The predicted complexes are deposited in MODBASE (). PMID:16738133

  12. Charge structure in volcanic plumes: a comparison of plume properties predicted by an integral plume model to observations of volcanic lightning during the 2010 eruption of Eyjafjallajökull, Iceland.

    PubMed

    Woodhouse, Mark J; Behnke, Sonja A

    Observations of volcanic lightning made using a lightning mapping array during the 2010 eruption of Eyjafjallajökull allow the trajectory and growth of the volcanic plume to be determined. The lightning observations are compared with predictions of an integral model of volcanic plumes that includes descriptions of the interaction with wind and the effects of moisture. We show that the trajectory predicted by the integral model closely matches the observational data and the model well describes the growth of the plume downwind of the vent. Analysis of the lightning signals reveals information on the dominant charge structure within the volcanic plume. During the Eyjafjallajökull eruption both monopole and dipole charge structures were observed in the plume. By using the integral plume model, we propose the varying charge structure is connected to the availability of condensed water and low temperatures at high altitudes in the plume, suggesting ice formation may have contributed to the generation of a dipole charge structure via thunderstorm-style ice-based charging mechanisms, though overall this charging mechanism is believed to have had only a weak influence on the production of lightning.

  13. Nanocomposites for Enhanced Structural Integrity

    DTIC Science & Technology

    2007-09-11

    developing methods to optimally functionalize these nanoreinforcements. A coupling agent methacryloxy propyl trimethoxy silane (MPS) was found to be...102 Nanocomposites for Enhanced Structural Integrity AFOSR bn0)2-1-0414 H. Thomas Hahn Mechanical & Aerospace Engineering Department University of...nanocomposite. A coupling agent methacryloxy propyl trimethoxy silane (MPS) was found to be effective for the SiC nanocomposite. As for the graphite

  14. Predictive structural dynamic network analysis.

    PubMed

    Chen, Rong; Herskovits, Edward H

    2015-04-30

    Classifying individuals based on magnetic resonance data is an important task in neuroscience. Existing brain network-based methods to classify subjects analyze data from a cross-sectional study and these methods cannot classify subjects based on longitudinal data. We propose a network-based predictive modeling method to classify subjects based on longitudinal magnetic resonance data. Our method generates a dynamic Bayesian network model for each group which represents complex spatiotemporal interactions among brain regions, and then calculates a score representing that subject's deviation from expected network patterns. This network-derived score, along with other candidate predictors, are used to construct predictive models. We validated the proposed method based on simulated data and the Alzheimer's Disease Neuroimaging Initiative study. For the Alzheimer's Disease Neuroimaging Initiative study, we built a predictive model based on the baseline biomarker characterizing the baseline state and the network-based score which was constructed based on the state transition probability matrix. We found that this combined model achieved 0.86 accuracy, 0.85 sensitivity, and 0.87 specificity. For the Alzheimer's Disease Neuroimaging Initiative study, the model based on the baseline biomarkers achieved 0.77 accuracy. The accuracy of our model is significantly better than the model based on the baseline biomarkers (p-value=0.002). We have presented a method to classify subjects based on structural dynamic network model based scores. This method is of great importance to distinguish subjects based on structural network dynamics and the understanding of the network architecture of brain processes and disorders. Copyright © 2015 Elsevier B.V. All rights reserved.

  15. Computer analysis and structure prediction of nucleic acids and proteins.

    PubMed Central

    Kanehisa, M; Klein, P; Greif, P; DeLisi, C

    1984-01-01

    We have developed an integrated computer system for analysis of nucleic acid and protein sequences, which consists of sequence and structure databases, a relational database, and software for structural analysis. The system is potentially applicable to a number of problems in structural biology including predictive classification of the function and location of oncogene products. PMID:6546426

  16. Structure Prediction and Analysis of Neuraminidase Sequence Variants

    ERIC Educational Resources Information Center

    Thayer, Kelly M.

    2016-01-01

    Analyzing protein structure has become an integral aspect of understanding systems of biochemical import. The laboratory experiment endeavors to introduce protein folding to ascertain structures of proteins for which the structure is unavailable, as well as to critically evaluate the quality of the prediction obtained. The model system used is the…

  17. Structure Prediction and Analysis of Neuraminidase Sequence Variants

    ERIC Educational Resources Information Center

    Thayer, Kelly M.

    2016-01-01

    Analyzing protein structure has become an integral aspect of understanding systems of biochemical import. The laboratory experiment endeavors to introduce protein folding to ascertain structures of proteins for which the structure is unavailable, as well as to critically evaluate the quality of the prediction obtained. The model system used is the…

  18. Protein structural domains: definition and prediction.

    PubMed

    Ezkurdia, Iakes; Tress, Michael L

    2011-11-01

    Recognition and prediction of structural domains in proteins is an important part of structure and function prediction. This unit lists the range of tools available for domain prediction, and describes sequence and structural analysis tools that complement domain prediction methods. Also detailed are the basic domain prediction steps, along with suggested strategies for different protein sequences and potential pitfalls in domain boundary prediction. The difficult problem of domain orientation prediction is also discussed. All the resources necessary for domain boundary prediction are accessible via publicly available Web servers and databases and do not require computational expertise.

  19. CRHunter: integrating multifaceted information to predict catalytic residues in enzymes

    PubMed Central

    Sun, Jun; Wang, Jia; Xiong, Dan; Hu, Jian; Liu, Rong

    2016-01-01

    A variety of algorithms have been developed for catalytic residue prediction based on either feature- or template-based methodology. However, no studies have systematically compared these two strategies and further considered whether their combination could improve the prediction performance. Herein, we developed an integrative algorithm named CRHunter by simultaneously using the complementarity between feature- and template-based methodologies and that between structural and sequence information. Several novel structural features were generated by the Delaunay triangulation and Laplacian transformation of enzyme structures. Combining these features with traditional descriptors, we invented two support vector machine feature predictors based on both structural and sequence information. Furthermore, we established two template predictors using structure and profile alignments. Evaluated on datasets with different levels of homology, our feature predictors achieve relatively stable performance, whereas our template predictors yield poor results when the homological relationships become weak. Nevertheless, the hybrid algorithm CRHunter consistently achieves optimal performance among all our predictors. We also illustrate that our methodology can be applied to the predicted structures of enzymes. Compared with state-of-the-art methods, CRHunter yields comparable or better performance on various datasets. Finally, the application of this algorithm to structural genomics targets sheds light on solved protein structures with unknown functions. PMID:27665935

  20. Global integrated drought monitoring and prediction system.

    PubMed

    Hao, Zengchao; AghaKouchak, Amir; Nakhjiri, Navid; Farahmand, Alireza

    2014-01-01

    Drought is by far the most costly natural disaster that can lead to widespread impacts, including water and food crises. Here we present data sets available from the Global Integrated Drought Monitoring and Prediction System (GIDMaPS), which provides drought information based on multiple drought indicators. The system provides meteorological and agricultural drought information based on multiple satellite-, and model-based precipitation and soil moisture data sets. GIDMaPS includes a near real-time monitoring component and a seasonal probabilistic prediction module. The data sets include historical drought severity data from the monitoring component, and probabilistic seasonal forecasts from the prediction module. The probabilistic forecasts provide essential information for early warning, taking preventive measures, and planning mitigation strategies. GIDMaPS data sets are a significant extension to current capabilities and data sets for global drought assessment and early warning. The presented data sets would be instrumental in reducing drought impacts especially in developing countries. Our results indicate that GIDMaPS data sets reliably captured several major droughts from across the globe.

  1. Global integrated drought monitoring and prediction system

    PubMed Central

    Hao, Zengchao; AghaKouchak, Amir; Nakhjiri, Navid; Farahmand, Alireza

    2014-01-01

    Drought is by far the most costly natural disaster that can lead to widespread impacts, including water and food crises. Here we present data sets available from the Global Integrated Drought Monitoring and Prediction System (GIDMaPS), which provides drought information based on multiple drought indicators. The system provides meteorological and agricultural drought information based on multiple satellite-, and model-based precipitation and soil moisture data sets. GIDMaPS includes a near real-time monitoring component and a seasonal probabilistic prediction module. The data sets include historical drought severity data from the monitoring component, and probabilistic seasonal forecasts from the prediction module. The probabilistic forecasts provide essential information for early warning, taking preventive measures, and planning mitigation strategies. GIDMaPS data sets are a significant extension to current capabilities and data sets for global drought assessment and early warning. The presented data sets would be instrumental in reducing drought impacts especially in developing countries. Our results indicate that GIDMaPS data sets reliably captured several major droughts from across the globe. PMID:25977759

  2. Toward structure prediction of cyclic peptides.

    PubMed

    Yu, Hongtao; Lin, Yu-Shan

    2015-02-14

    Cyclic peptides are a promising class of molecules that can be used to target specific protein-protein interactions. A computational method to accurately predict their structures would substantially advance the development of cyclic peptides as modulators of protein-protein interactions. Here, we develop a computational method that integrates bias-exchange metadynamics simulations, a Boltzmann reweighting scheme, dihedral principal component analysis and a modified density peak-based cluster analysis to provide a converged structural description for cyclic peptides. Using this method, we evaluate the performance of a number of popular protein force fields on a model cyclic peptide. All the tested force fields seem to over-stabilize the α-helix and PPII/β regions in the Ramachandran plot, commonly populated by linear peptides and proteins. Our findings suggest that re-parameterization of a force field that well describes the full Ramachandran plot is necessary to accurately model cyclic peptides.

  3. Assuring structural integrity in Army systems

    NASA Technical Reports Server (NTRS)

    1985-01-01

    The object of this study was to recommend possible improvements in the manner in which structural integrity of Army systems is assured. The elements of a structural integrity program are described, and relevant practices used in various industries and government organizations are reviewed. Some case histories of Army weapon systems are examined. The mandatory imposition of a structural integrity program patterned after the Air Force Aircraft Structural Integrity Program is recommended and the benefits of such an action are identified.

  4. Integrated Propulsion/Vehicle System Structurally Optimized

    NASA Technical Reports Server (NTRS)

    Hunter, James E.; McCurdy, David R.

    2003-01-01

    Ongoing research and testing are essential in the development of air-breathing hypersonic propulsion technology, and this year some positive advancement was made at the NASA Glenn Research Center. Recent work performed for GTX, a rocket-based combined-cycle, single-stage-to-orbit concept, included structural assessments of both the engine and flight vehicle. In the development of air-breathing engine technology, it is impractical to design and optimize components apart from the fully integrated system because tradeoffs must be made between performance and structural capability. Efforts were made to control the flight trajectory, for example, to minimize the aerodynamic heating effects. Structural optimization was applied to evaluate concept feasibility and was instrumental in the determination of the gross liftoff weight of the integrated system. Achieving low Earth orbit with even a small payload requires an aggressive approach to weight minimization through the use of lightweight, oxidation-resistant composite materials. Assessing the integrated system involved investigating the flight trajectory to determine where the critical load events occur in flight and then generating the corresponding environment at each of these events. Structural evaluation requires the mapping of the critical flight loads to finite element models, including the combined effects of aerodynamic, inertial, combustion, and other loads. NASA s APAS code was used to generate aerodynamic pressure and temperature profiles at each critical event. The radiation equilibrium surface temperatures from APAS were used to predict temperatures through the thickness. Heat transfer solutions using NASA's MINIVER code and the SINDA code (Cullimore & Ring Technologies, Littleton, CO) were calculated at selective points external to the integrated vehicle system and then extrapolated over the entire exposed surface. FORTRAN codes were written to expedite the finite element mapping of the aerodynamic heating

  5. Critical Zone Observatories (CZOs): Integrating measurements and models of Earth surface processes to improve prediction of landscape structure, function and evolution

    NASA Astrophysics Data System (ADS)

    Chorover, J.; Anderson, S. P.; Bales, R. C.; Duffy, C.; Scatena, F. N.; Sparks, D. L.; White, T.

    2012-12-01

    The "Critical Zone" - that portion of Earth's land surface that extends from the outer periphery of the vegetation canopy to the lower limit of circulating groundwater - has evolved in response to climatic and tectonic forcing throughout Earth's history, but human activities have recently emerged as a major agent of change as well. With funding from NSF, a network of currently six CZOs is being developed in the U.S. to provide infrastructure, data and models that facilitate understanding the evolution, structure, and function of this zone at watershed to grain scales. Each CZO is motivated by a unique set of hypotheses proposed by a specific investigator team, but coordination of cross-site activities is also leading to integration of a common set of multi-disciplinary tools and approaches for cross-site syntheses. The resulting harmonized four-dimensional datasets are intended to facilitate community-wide exploration of process couplings among hydrology, ecology, soil science, geochemistry and geomorphology across the larger (network-scale) parameter space. Such an approach enables testing of the generalizability of findings at a given site, and also of emergent hypotheses conceived independently of an original CZO investigator team. This two-pronged method for developing a network of individual CZOs across a range of watershed systems is now yielding novel observations and models that resolve mechanisms for Critical Zone change occurring on geological to hydrologic time-scales. For example, recent advances include improved understanding of (i) how mass and energy flux as modulated by ecosystem exchange transforms bedrock to structured, soil-mantled and/or erosive landscapes; (ii) how long-term evolution of landscape structure affects event-based hydrologic and biogeochemical response at pore to catchment scales; (iii) how complementary isotopic measurements can be used to resolve pathways and time scales of water and solute transport from canopy to stream, and

  6. Practical lessons from protein structure prediction

    PubMed Central

    Ginalski, Krzysztof; Grishin, Nick V.; Godzik, Adam; Rychlewski, Leszek

    2005-01-01

    Despite recent efforts to develop automated protein structure determination protocols, structural genomics projects are slow in generating fold assignments for complete proteomes, and spatial structures remain unknown for many protein families. Alternative cheap and fast methods to assign folds using prediction algorithms continue to provide valuable structural information for many proteins. The development of high-quality prediction methods has been boosted in the last years by objective community-wide assessment experiments. This paper gives an overview of the currently available practical approaches to protein structure prediction capable of generating accurate fold assignment. Recent advances in assessment of the prediction quality are also discussed. PMID:15805122

  7. Integrated Computational Solution for Predicting Skin Sensitization Potential of Molecules

    PubMed Central

    Desai, Aarti; Singh, Vivek K.; Jere, Abhay

    2016-01-01

    Introduction Skin sensitization forms a major toxicological endpoint for dermatology and cosmetic products. Recent ban on animal testing for cosmetics demands for alternative methods. We developed an integrated computational solution (SkinSense) that offers a robust solution and addresses the limitations of existing computational tools i.e. high false positive rate and/or limited coverage. Results The key components of our solution include: QSAR models selected from a combinatorial set, similarity information and literature-derived sub-structure patterns of known skin protein reactive groups. Its prediction performance on a challenge set of molecules showed accuracy = 75.32%, CCR = 74.36%, sensitivity = 70.00% and specificity = 78.72%, which is better than several existing tools including VEGA (accuracy = 45.00% and CCR = 54.17% with ‘High’ reliability scoring), DEREK (accuracy = 72.73% and CCR = 71.44%) and TOPKAT (accuracy = 60.00% and CCR = 61.67%). Although, TIMES-SS showed higher predictive power (accuracy = 90.00% and CCR = 92.86%), the coverage was very low (only 10 out of 77 molecules were predicted reliably). Conclusions Owing to improved prediction performance and coverage, our solution can serve as a useful expert system towards Integrated Approaches to Testing and Assessment for skin sensitization. It would be invaluable to cosmetic/ dermatology industry for pre-screening their molecules, and reducing time, cost and animal testing. PMID:27271321

  8. The PSIPRED protein structure prediction server.

    PubMed

    McGuffin, L J; Bryson, K; Jones, D T

    2000-04-01

    The PSIPRED protein structure prediction server allows users to submit a protein sequence, perform a prediction of their choice and receive the results of the prediction both textually via e-mail and graphically via the web. The user may select one of three prediction methods to apply to their sequence: PSIPRED, a highly accurate secondary structure prediction method; MEMSAT 2, a new version of a widely used transmembrane topology prediction method; or GenTHREADER, a sequence profile based fold recognition method. Freely available to non-commercial users at http://globin.bio.warwick.ac.uk/psipred/

  9. PSPP: A Protein Structure Prediction Pipeline for Computing Clusters

    PubMed Central

    Lee, Michael S.; Bondugula, Rajkumar; Desai, Valmik; Zavaljevski, Nela; Yeh, In-Chul; Wallqvist, Anders; Reifman, Jaques

    2009-01-01

    Background Protein structures are critical for understanding the mechanisms of biological systems and, subsequently, for drug and vaccine design. Unfortunately, protein sequence data exceed structural data by a factor of more than 200 to 1. This gap can be partially filled by using computational protein structure prediction. While structure prediction Web servers are a notable option, they often restrict the number of sequence queries and/or provide a limited set of prediction methodologies. Therefore, we present a standalone protein structure prediction software package suitable for high-throughput structural genomic applications that performs all three classes of prediction methodologies: comparative modeling, fold recognition, and ab initio. This software can be deployed on a user's own high-performance computing cluster. Methodology/Principal Findings The pipeline consists of a Perl core that integrates more than 20 individual software packages and databases, most of which are freely available from other research laboratories. The query protein sequences are first divided into domains either by domain boundary recognition or Bayesian statistics. The structures of the individual domains are then predicted using template-based modeling or ab initio modeling. The predicted models are scored with a statistical potential and an all-atom force field. The top-scoring ab initio models are annotated by structural comparison against the Structural Classification of Proteins (SCOP) fold database. Furthermore, secondary structure, solvent accessibility, transmembrane helices, and structural disorder are predicted. The results are generated in text, tab-delimited, and hypertext markup language (HTML) formats. So far, the pipeline has been used to study viral and bacterial proteomes. Conclusions The standalone pipeline that we introduce here, unlike protein structure prediction Web servers, allows users to devote their own computing assets to process a potentially unlimited

  10. INTEGRATING COMPUTATIONAL PROTEIN FUNCTION PREDICTION INTO DRUG DISCOVERY INITIATIVES

    PubMed Central

    Grant, Marianne A.

    2014-01-01

    Pharmaceutical researchers must evaluate vast numbers of protein sequences and formulate innovative strategies for identifying valid targets and discovering leads against them as a way of accelerating drug discovery. The ever increasing number and diversity of novel protein sequences identified by genomic sequencing projects and the success of worldwide structural genomics initiatives have spurred great interest and impetus in the development of methods for accurate, computationally empowered protein function prediction and active site identification. Previously, in the absence of direct experimental evidence, homology-based protein function annotation remained the gold-standard for in silico analysis and prediction of protein function. However, with the continued exponential expansion of sequence databases, this approach is not always applicable, as fewer query protein sequences demonstrate significant homology to protein gene products of known function. As a result, several non-homology based methods for protein function prediction that are based on sequence features, structure, evolution, biochemical and genetic knowledge have emerged. Herein, we review current bioinformatic programs and approaches for protein function prediction/annotation and discuss their integration into drug discovery initiatives. The development of such methods to annotate protein functional sites and their application to large protein functional families is crucial to successfully utilizing the vast amounts of genomic sequence information available to drug discovery and development processes. PMID:25530654

  11. MSACompro: improving multiple protein sequence alignment by predicted structural features.

    PubMed

    Deng, Xin; Cheng, Jianlin

    2014-01-01

    Multiple Sequence Alignment (MSA) is an essential tool in protein structure modeling, gene and protein function prediction, DNA motif recognition, phylogenetic analysis, and many other bioinformatics tasks. Therefore, improving the accuracy of multiple sequence alignment is an important long-term objective in bioinformatics. We designed and developed a new method MSACompro to incorporate predicted secondary structure, relative solvent accessibility, and residue-residue contact information into the currently most accurate posterior probability-based MSA methods to improve the accuracy of multiple sequence alignments. Different from the multiple sequence alignment methods that use the tertiary structure information of some sequences, our method uses the structural information purely predicted from sequences. In this chapter, we first introduce some background and related techniques in the field of multiple sequence alignment. Then, we describe the detailed algorithm of MSACompro. Finally, we show that integrating predicted protein structural information improved the multiple sequence alignment accuracy.

  12. Damage Tolerance of Integral Structure in Rotorcraft

    NASA Technical Reports Server (NTRS)

    Forth, Scott C.; Urban, Michael R.

    2003-01-01

    The rotorcraft industry has rapidly implemented integral structures into aircraft to benefit from the weight and cost advantages over traditionally riveted structure. The cost to manufacture an integral structure, where the entire component is machined from a single plate of material, is about one-fifth that of a riveted structure. Furthermore, the integral structure can weigh only one-half that of a riveted structure through optimal design of stiffening structure and part reduction. Finally, inspection and repair of damage in the field can be less costly than riveted structure. There are no rivet heads to inspect under, reducing inspection time, and damage can be removed or patched readily without altering the primary structure, reducing replacement or repair costs. In this paper, the authors will investigate the damage tolerance implications of fielding an integral structure manufactured from thick plate aluminum.

  13. OPTIMIZATION BIAS IN ENERGY-BASED STRUCTURE PREDICTION.

    PubMed

    Petrella, Robert J

    2013-12-01

    Physics-based computational approaches to predicting the structure of macromolecules such as proteins are gaining increased use, but there are remaining challenges. In the current work, it is demonstrated that in energy-based prediction methods, the degree of optimization of the sampled structures can influence the prediction results. In particular, discrepancies in the degree of local sampling can bias the predictions in favor of the oversampled structures by shifting the local probability distributions of the minimum sampled energies. In simple systems, it is shown that the magnitude of the errors can be calculated from the energy surface, and for certain model systems, derived analytically. Further, it is shown that for energy wells whose forms differ only by a randomly assigned energy shift, the optimal accuracy of prediction is achieved when the sampling around each structure is equal. Energy correction terms can be used in cases of unequal sampling to reproduce the total probabilities that would occur under equal sampling, but optimal corrections only partially restore the prediction accuracy lost to unequal sampling. For multiwell systems, the determination of the correction terms is a multibody problem; it is shown that the involved cross-correlation multiple integrals can be reduced to simpler integrals. The possible implications of the current analysis for macromolecular structure prediction are discussed.

  14. OPTIMIZATION BIAS IN ENERGY-BASED STRUCTURE PREDICTION

    PubMed Central

    Petrella, Robert J.

    2014-01-01

    Physics-based computational approaches to predicting the structure of macromolecules such as proteins are gaining increased use, but there are remaining challenges. In the current work, it is demonstrated that in energy-based prediction methods, the degree of optimization of the sampled structures can influence the prediction results. In particular, discrepancies in the degree of local sampling can bias the predictions in favor of the oversampled structures by shifting the local probability distributions of the minimum sampled energies. In simple systems, it is shown that the magnitude of the errors can be calculated from the energy surface, and for certain model systems, derived analytically. Further, it is shown that for energy wells whose forms differ only by a randomly assigned energy shift, the optimal accuracy of prediction is achieved when the sampling around each structure is equal. Energy correction terms can be used in cases of unequal sampling to reproduce the total probabilities that would occur under equal sampling, but optimal corrections only partially restore the prediction accuracy lost to unequal sampling. For multiwell systems, the determination of the correction terms is a multibody problem; it is shown that the involved cross-correlation multiple integrals can be reduced to simpler integrals. The possible implications of the current analysis for macromolecular structure prediction are discussed. PMID:25552783

  15. The MULTICOM toolbox for protein structure prediction.

    PubMed

    Cheng, Jianlin; Li, Jilong; Wang, Zheng; Eickholt, Jesse; Deng, Xin

    2012-04-30

    As genome sequencing is becoming routine in biomedical research, the total number of protein sequences is increasing exponentially, recently reaching over 108 million. However, only a tiny portion of these proteins (i.e. ~75,000 or < 0.07%) have solved tertiary structures determined by experimental techniques. The gap between protein sequence and structure continues to enlarge rapidly as the throughput of genome sequencing techniques is much higher than that of protein structure determination techniques. Computational software tools for predicting protein structure and structural features from protein sequences are crucial to make use of this vast repository of protein resources. To meet the need, we have developed a comprehensive MULTICOM toolbox consisting of a set of protein structure and structural feature prediction tools. These tools include secondary structure prediction, solvent accessibility prediction, disorder region prediction, domain boundary prediction, contact map prediction, disulfide bond prediction, beta-sheet topology prediction, fold recognition, multiple template combination and alignment, template-based tertiary structure modeling, protein model quality assessment, and mutation stability prediction. These tools have been rigorously tested by many users in the last several years and/or during the last three rounds of the Critical Assessment of Techniques for Protein Structure Prediction (CASP7-9) from 2006 to 2010, achieving state-of-the-art or near performance. In order to facilitate bioinformatics research and technological development in the field, we have made the MULTICOM toolbox freely available as web services and/or software packages for academic use and scientific research. It is available at http://sysbio.rnet.missouri.edu/multicom_toolbox/.

  16. The MULTICOM toolbox for protein structure prediction

    PubMed Central

    2012-01-01

    Background As genome sequencing is becoming routine in biomedical research, the total number of protein sequences is increasing exponentially, recently reaching over 108 million. However, only a tiny portion of these proteins (i.e. ~75,000 or < 0.07%) have solved tertiary structures determined by experimental techniques. The gap between protein sequence and structure continues to enlarge rapidly as the throughput of genome sequencing techniques is much higher than that of protein structure determination techniques. Computational software tools for predicting protein structure and structural features from protein sequences are crucial to make use of this vast repository of protein resources. Results To meet the need, we have developed a comprehensive MULTICOM toolbox consisting of a set of protein structure and structural feature prediction tools. These tools include secondary structure prediction, solvent accessibility prediction, disorder region prediction, domain boundary prediction, contact map prediction, disulfide bond prediction, beta-sheet topology prediction, fold recognition, multiple template combination and alignment, template-based tertiary structure modeling, protein model quality assessment, and mutation stability prediction. Conclusions These tools have been rigorously tested by many users in the last several years and/or during the last three rounds of the Critical Assessment of Techniques for Protein Structure Prediction (CASP7-9) from 2006 to 2010, achieving state-of-the-art or near performance. In order to facilitate bioinformatics research and technological development in the field, we have made the MULTICOM toolbox freely available as web services and/or software packages for academic use and scientific research. It is available at http://sysbio.rnet.missouri.edu/multicom_toolbox/. PMID:22545707

  17. Integrated strategy for mutagenicity prediction applied to food contact chemicals.

    PubMed

    Manganelli, Serena; Schilter, Benoît; Benfenati, Emilio; Manganaro, Alberto; Lo Piparo, Elena

    2017-09-18

    Food contamination due to unintentional leakage of chemicals from food contact materials (FCM) is a source of increasing concern. Since for many of these substances, only limited or no toxicological data are available, the development of alternative methodologies to establish rapidly and cost-efficiently level of safety concern is critical to ensure adequate consumer protection. Computational toxicology methods are considered the most promising solutions to cope with this data gap. In particular, mutagenicity assessment has a particular relevance and is a mandatory requirement for all substances released from plastic FCM, regardless how low migration and exposure are. In the present work, a strategy integrating a number of (Quantitative) Structure Activity Relationship ((Q)SAR) models for Ames mutagenicity predictions is proposed. A list of chemicals representing likely migrating moieties from FCM was selected to test the value of the newly defined strategy and the possibility to combine predictions given by the different algorithms was evaluated. In particular, a scheme to integrate mutagenicity estimations into a single final assessment was developed resulting in an increased domain of applicability. In most cases, a deeper analysis of experimental data, where available, allowed fixing misclassification errors, highlighting the importance of data curation in the development, validation and application of in silico methods. The high accuracy of the strategy provided the rationales for its application for toxicologically uncharacterized chemicals. Finally, the overall strategy of integration will be automated through its implementation into a freely available software application.

  18. Collective prediction based on community structure

    NASA Astrophysics Data System (ADS)

    Jiang, Yasong; Li, Taisong; Zhang, Yan; Yan, Yonghong

    2017-01-01

    Collective prediction algorithms have been used to improve performances when network structures are involved in prediction tasks. The training dataset of such tasks often contain information of content, links and labels, while the testing dataset have only content and link information. Conventional collective prediction algorithms conduct predictions based on the content of a node and the information of its direct neighbors with a base classifier. However, the information of some direct neighbor nodes may be not consistent with the target one. In addition, the information of indirect neighbors can be helpful when that of direct neighbors is scant. In this paper, instead of using information of direct neighbors, we propose to apply community structures in networks to prediction tasks. A community detection method is aggregated into the collective prediction process to improve prediction performance. Experimental results show that the proposed algorithm outperforms a number of standard prediction algorithms specially under conditions that labeled training dataset are limited.

  19. The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction.

    PubMed

    Roche, Daniel B; Buenavista, Maria T; Tetchner, Stuart J; McGuffin, Liam J

    2011-07-01

    The IntFOLD server is a novel independent server that integrates several cutting edge methods for the prediction of structure and function from sequence. Our guiding principles behind the server development were as follows: (i) to provide a simple unified resource that makes our prediction software accessible to all and (ii) to produce integrated output for predictions that can be easily interpreted. The output for predictions is presented as a simple table that summarizes all results graphically via plots and annotated 3D models. The raw machine readable data files for each set of predictions are also provided for developers, which comply with the Critical Assessment of Methods for Protein Structure Prediction (CASP) data standards. The server comprises an integrated suite of five novel methods: nFOLD4, for tertiary structure prediction; ModFOLD 3.0, for model quality assessment; DISOclust 2.0, for disorder prediction; DomFOLD 2.0 for domain prediction; and FunFOLD 1.0, for ligand binding site prediction. Predictions from the IntFOLD server were found to be competitive in several categories in the recent CASP9 experiment. The IntFOLD server is available at the following web site: http://www.reading.ac.uk/bioinf/IntFOLD/.

  20. Protein Structure Prediction with Visuospatial Analogy

    NASA Astrophysics Data System (ADS)

    Davies, Jim; Glasgow, Janice; Kuo, Tony

    We show that visuospatial representations and reasoning techniques can be used as a similarity metric for analogical protein structure prediction. Our system retrieves pairs of α-helices based on contact map similarity, then transfers and adapts the structure information to an unknown helix pair, showing that similar protein contact maps predict similar 3D protein structure. The success of this method provides support for the notion that changing representations can enable similarity metrics in analogy.

  1. Impact of active controls technology on structural integrity

    NASA Technical Reports Server (NTRS)

    Noll, Thomas; Austin, Edward; Donley, Shawn; Graham, George; Harris, Terry

    1991-01-01

    This paper summarizes the findings of The Technical Cooperation Program to assess the impact of active controls technology on the structural integrity of aeronautical vehicles and to evaluate the present state-of-the-art for predicting the loads caused by a flight-control system modification and the resulting change in the fatigue life of the flight vehicle. The potential for active controls to adversely affect structural integrity is described, and load predictions obtained using two state-of-the-art analytical methods are given.

  2. Computational Prediction of RNA Tertiary Structure

    NASA Astrophysics Data System (ADS)

    Zhao, Yunjie; Gong, Zhou; Chen, Changjun; Xiao, Yi

    2012-02-01

    RNAs have been found to be involved in the biological processes. The large RNA usually consists of two basic elements: RNA hairpins and duplex. Due to the experimental determination difficulties, the few RNA tertiary structures limit our understanding of the specific regulation mechanisms and functions. Therefore, RNA tertiary structure prediction is very important for understanding RNA biological functions. Since RNA often folds hierarchically, one of the possible RNA structure prediction approaches is through the hierarchical steps. Here, we focus on the prediction method of RNA tertiary hairpin and duplex structures in which assembles the small tertiary structure fragments from well-defined RNA structural motifs. In a benchmark test with known experiment structures, more than half of the cases agree with the experimental structure better than 3 å RMSD over all the heavy atoms. The prediction results also reproduce the native like complementary base pairs of the secondary structures. Most importantly, the method performs the atomic accuracy of tertiary structures by about several minutes. We expect that the method will be a useful resource for RNA tertiary structure prediction and helpful to the biological research community.

  3. A physical approach to protein structure prediction.

    PubMed Central

    Crivelli, Silvia; Eskow, Elizabeth; Bader, Brett; Lamberti, Vincent; Byrd, Richard; Schnabel, Robert; Head-Gordon, Teresa

    2002-01-01

    We describe our global optimization method called Stochastic Perturbation with Soft Constraints (SPSC), which uses information from known proteins to predict secondary structure, but not in the tertiary structure predictions or in generating the terms of the physics-based energy function. Our approach is also characterized by the use of an all atom energy function that includes a novel hydrophobic solvation function derived from experiments that shows promising ability for energy discrimination against misfolded structures. We present the results obtained using our SPSC method and energy function for blind prediction in the 4th Critical Assessment of Techniques for Protein Structure Prediction competition, and show that our approach is more effective on targets for which less information from known proteins is available. In fact our SPSC method produced the best prediction for one of the most difficult targets of the competition, a new fold protein of 240 amino acids. PMID:11751294

  4. Energy-directed RNA structure prediction.

    PubMed

    Hofacker, Ivo L

    2014-01-01

    In this chapter we present the classic dynamic programming algorithms for RNA structure prediction by energy minimization, as well as variations of this approach that allow to compute suboptimal foldings, or even the partition function over all possible secondary structures. The latter are essential in order to deal with the inaccuracy of minimum free energy (MFE) structure prediction, and can be used, for example, to derive reliability measures that assign a confidence value to all or part of a predicted structure. In addition, we discuss recently proposed alternatives to the MFE criterion such as the use of maximum expected accuracy (MEA) or centroid structures. The dynamic programming algorithms implicitly assume that the RNA molecule is in thermodynamic equilibrium. However, especially for long RNAs, this need not be the case. In the last section we therefore discuss approaches for predicting RNA folding kinetics and co-transcriptional folding.

  5. Predicting pseudoknotted structures across two RNA sequences

    PubMed Central

    Sperschneider, Jana; Datta, Amitava; Wise, Michael J.

    2012-01-01

    Motivation: Laboratory RNA structure determination is demanding and costly and thus, computational structure prediction is an important task. Single sequence methods for RNA secondary structure prediction are limited by the accuracy of the underlying folding model, if a structure is supported by a family of evolutionarily related sequences, one can be more confident that the prediction is accurate. RNA pseudoknots are functional elements, which have highly conserved structures. However, few comparative structure prediction methods can handle pseudoknots due to the computational complexity. Results: A comparative pseudoknot prediction method called DotKnot-PW is introduced based on structural comparison of secondary structure elements and H-type pseudoknot candidates. DotKnot-PW outperforms other methods from the literature on a hand-curated test set of RNA structures with experimental support. Availability: DotKnot-PW and the RNA structure test set are available at the web site http://dotknot.csse.uwa.edu.au/pw. Contact: janaspe@csse.uwa.edu.au Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23044552

  6. Structural Integrity in Measures of Self Concept.

    ERIC Educational Resources Information Center

    Stenner, A. Jackson; Katzenmeyer, W.G.

    Structural integrity of a measure is defined in terms of its replicability, constancy, invariance, and stability. Work completed in the development and validation of the Self Observation Scales (SOS) Primary Level (Stenner and Katzenmeyer, 1973) serves to illustrate one method of establishing structural integrity. The name of each scale of the SOS…

  7. SCRATCH: a protein structure and structural feature prediction server

    PubMed Central

    Cheng, J.; Randall, A. Z.; Sweredoski, M. J.; Baldi, P.

    2005-01-01

    SCRATCH is a server for predicting protein tertiary structure and structural features. The SCRATCH software suite includes predictors for secondary structure, relative solvent accessibility, disordered regions, domains, disulfide bridges, single mutation stability, residue contacts versus average, individual residue contacts and tertiary structure. The user simply provides an amino acid sequence and selects the desired predictions, then submits to the server. Results are emailed to the user. The server is available at . PMID:15980571

  8. Transmembrane beta-barrel protein structure prediction

    NASA Astrophysics Data System (ADS)

    Randall, Arlo; Baldi, Pierre

    Transmembrane β-barrel (TMB) proteins are embedded in the outer membranes of mitochondria, Gram-negative bacteria, and chloroplasts. These proteins perform critical functions, including active ion-transport and passive nutrient intake. Therefore, there is a need for accurate prediction of secondary and tertiary structures of TMB proteins. A variety of methods have been developed for predicting the secondary structure and these predictions are very useful for constructing a coarse topology of TMB structure; however, they do not provide enough information to construct a low-resolution tertiary structure for a TMB protein. In addition, while the overall structural architecture is well conserved among TMB proteins, the amino acid sequences are highly divergent. Thus, traditional homology modeling methods cannot be applied to many putative TMB proteins. Here, we describe the TMBpro: a pipeline of methods for predicting TMB secondary structure, β-residue contacts, and finally tertiary structure. The tertiary prediction method relies on the specific construction rules that TMB proteins adhere to and on the predicted β-residue contacts to dramatically reduce the search space for the model building procedure.

  9. Predicting and prioritizing maintenance for concrete structures

    SciTech Connect

    Hertlein, B.H. )

    1991-06-01

    Using nondestructive testing of concrete structures to predict maintenance needs can help schedule maintenance work in advance and prevent unexpected shutdowns. Nondestructive testing methods are described and development of a testing program is discussed.

  10. Predicting crystal structures of organic compounds.

    PubMed

    Price, Sarah L

    2014-04-07

    Currently, organic crystal structure prediction (CSP) methods are based on searching for the most thermodynamically stable crystal structure, making various approximations in evaluating the crystal energy. The most stable (global minimum) structure provides a prediction of an experimental crystal structure. However, depending on the specific molecule, there may be other structures which are very close in energy. In this case, the other structures on the crystal energy landscape may be polymorphs, components of static or dynamic disorder in observed structures, or there may be no route to nucleating and growing these structures. A major reason for performing CSP studies is as a complement to solid form screening to see which alternative packings to the known polymorphs are thermodynamically feasible.

  11. Predicting RNA structure: advances and limitations.

    PubMed

    Hofacker, Ivo L; Lorenz, Ronny

    2014-01-01

    RNA secondary structures can be predicted using efficient algorithms. A widely used software package implementing a large number of computational methods is the ViennaRNA Package. This chapter describes how to use programs from the ViennaRNA Package to perform common tasks such as prediction of minimum free-energy structures, suboptimal structures, or base pairing probabilities, and generating secondary structure plots with reliability annotation. Moreover, we present recent methods to assess the folding kinetics of an RNA via 2D projections of the energy landscape, identification of local minima and energy barriers, or simulation of RNA folding as a Markov process.

  12. Enhanced multi-view prediction structure

    NASA Astrophysics Data System (ADS)

    Liu, Da; Li, Yi; Xiong, Yazhou; Wang, Li; Li, Chunyan; Yin, Fang

    2016-11-01

    In this paper, firstly an extended DFMC Structure is proposed, then HQF jump period in extended DFMC is presented. Considering temporal-view and interview prediction structure, HQF location is determined. From the HQF, an enhance LQF is proposed. Then considering the HQF and enhance LQF, improved interview prediction is proposed. Finally bit allocation in the proposed multi-view is proposed. Experimental results show that the proposed method can achieve better performance than the previous schemes.

  13. Predicting Protein Structure Using Parallel Genetic Algorithms.

    DTIC Science & Technology

    1994-12-01

    34 IEEE Transactions on Systems, Man and Cybernetics, 10(9) (September 1980). 16. De Jong, Kenneth A. "On Using Genetic Algoriths to Search Program...By " Predicting rotein Structure D istribticfiar.. ................ Using Parallel Genetic Algorithms ,Avaiu " ’ •"... Dist THESIS I IGeorge H...iiLite-d Approved for public release; distribution unlimited AFIT/ GCS /ENG/94D-03 Predicting Protein Structure Using Parallel Genetic Algorithms

  14. Integrated method for combustion stability prediction

    NASA Astrophysics Data System (ADS)

    Yu, Y. C.; O'Hara, L.; Smith, R. J.; Anderson, W. E.; Merkle, C. L.

    2011-10-01

    Major obstacles in overcoming combustion instability include the absence of a mechanistic and a priori prediction capability, and the difficulty in studying instability in the laboratory due to the perceived need for testing at the full-scale pressure and geometry to ensure that important processes are maintained. A hierarchal approach toward combustion instability is described that comprises experiment, analysis, and highfidelity computation to develop combustion response submodels that can be used in engineering-level design analysis. The paper provides an illustrative example of how these elements are used to develop a prediction for growth rates in model rocket combustors that generate spontaneous longitudinal combustion instabilities.

  15. GAPIT: genome association and prediction integrated tool

    USDA-ARS?s Scientific Manuscript database

    Advances in high throughput sequencing have improved the detection of genes underlying important traits as well as the prediction accuracy of disease risk and breeding value of crop or livestock. Software programs developed to perform statistical genetic analysis that support these activities should...

  16. MUFOLD: A new solution for protein 3D structure prediction.

    PubMed

    Zhang, Jingfen; Wang, Qingguo; Barz, Bogdan; He, Zhiquan; Kosztin, Ioan; Shang, Yi; Xu, Dong

    2010-04-01

    There have been steady improvements in protein structure prediction during the past 2 decades. However, current methods are still far from consistently predicting structural models accurately with computing power accessible to common users. Toward achieving more accurate and efficient structure prediction, we developed a number of novel methods and integrated them into a software package, MUFOLD. First, a systematic protocol was developed to identify useful templates and fragments from Protein Data Bank for a given target protein. Then, an efficient process was applied for iterative coarse-grain model generation and evaluation at the Calpha or backbone level. In this process, we construct models using interresidue spatial restraints derived from alignments by multidimensional scaling, evaluate and select models through clustering and static scoring functions, and iteratively improve the selected models by integrating spatial restraints and previous models. Finally, the full-atom models were evaluated using molecular dynamics simulations based on structural changes under simulated heating. We have continuously improved the performance of MUFOLD by using a benchmark of 200 proteins from the Astral database, where no template with >25% sequence identity to any target protein is included. The average root-mean-square deviation of the best models from the native structures is 4.28 A, which shows significant and systematic improvement over our previous methods. The computing time of MUFOLD is much shorter than many other tools, such as Rosetta. MUFOLD demonstrated some success in the 2008 community-wide experiment for protein structure prediction CASP8.

  17. Characteristics and Prediction of RNA Structure

    PubMed Central

    Zhu, Daming; Zhang, Caiming; Han, Huijian; Crandall, Keith A.

    2014-01-01

    RNA secondary structures with pseudoknots are often predicted by minimizing free energy, which is NP-hard. Most RNAs fold during transcription from DNA into RNA through a hierarchical pathway wherein secondary structures form prior to tertiary structures. Real RNA secondary structures often have local instead of global optimization because of kinetic reasons. The performance of RNA structure prediction may be improved by considering dynamic and hierarchical folding mechanisms. This study is a novel report on RNA folding that accords with the golden mean characteristic based on the statistical analysis of the real RNA secondary structures of all 480 sequences from RNA STRAND, which are validated by NMR or X-ray. The length ratios of domains in these sequences are approximately 0.382L, 0.5L, 0.618L, and L, where L is the sequence length. These points are just the important golden sections of sequence. With this characteristic, an algorithm is designed to predict RNA hierarchical structures and simulate RNA folding by dynamically folding RNA structures according to the above golden section points. The sensitivity and number of predicted pseudoknots of our algorithm are better than those of the Mfold, HotKnots, McQfold, ProbKnot, and Lhw-Zhu algorithms. Experimental results reflect the folding rules of RNA from a new angle that is close to natural folding. PMID:25110687

  18. Predicting complex mineral structures using genetic algorithms.

    PubMed

    Mohn, Chris E; Kob, Walter

    2015-10-28

    We show that symmetry-adapted genetic algorithms are capable of finding the ground state of a range of complex crystalline phases including layered- and incommensurate super-structures. This opens the way for the atomistic prediction of complex crystal structures of functional materials and mineral phases.

  19. Improving RNA secondary structure prediction with structure mapping data.

    PubMed

    Sloma, Michael F; Mathews, David H

    2015-01-01

    Methods to probe RNA secondary structure, such as small molecule modifying agents, secondary structure-specific nucleases, inline probing, and SHAPE chemistry, are widely used to study the structure of functional RNA. Computational secondary structure prediction programs can incorporate probing data to predict structure with high accuracy. In this chapter, an overview of current methods for probing RNA secondary structure is provided, including modern high-throughput methods. Methods for guiding secondary structure prediction algorithms using these data are explained, and best practices for using these data are provided. This chapter concludes by listing a number of open questions about how to best use probing data, and what these data can provide. © 2015 Elsevier Inc. All rights reserved.

  20. Plated lamination structures for integrated magnetic devices

    SciTech Connect

    Webb, Bucknell C.

    2014-06-17

    Semiconductor integrated magnetic devices such as inductors, transformers, etc., having laminated magnetic-insulator stack structures are provided, wherein the laminated magnetic-insulator stack structures are formed using electroplating techniques. For example, an integrated laminated magnetic device includes a multilayer stack structure having alternating magnetic and insulating layers formed on a substrate, wherein each magnetic layer in the multilayer stack structure is separated from another magnetic layer in the multilayer stack structure by an insulating layer, and a local shorting structure to electrically connect each magnetic layer in the multilayer stack structure to an underlying magnetic layer in the multilayer stack structure to facilitate electroplating of the magnetic layers using an underlying conductive layer (magnetic or seed layer) in the stack as an electrical cathode/anode for each electroplated magnetic layer in the stack structure.

  1. Predicting structure in nonsymmetric sparse matrix factorizations

    SciTech Connect

    Gilbert, J.R.; Ng, E.G.

    1992-10-01

    Many computations on sparse matrices have a phase that predicts the nonzero structure of the output, followed by a phase that actually performs the numerical computation. We study structure prediction for computations that involve nonsymmetric row and column permutations and nonsymmetric or non-square matrices. Our tools are bipartite graphs, matchings, and alternating paths. Our main new result concerns LU factorization with partial pivoting. We show that if a square matrix A has the strong Hall property (i.e., is fully indecomposable) then an upper bound due to George and Ng on the nonzero structure of L + U is as tight as possible. To show this, we prove a crucial result about alternating paths in strong Hall graphs. The alternating-paths theorem seems to be of independent interest: it can also be used to prove related results about structure prediction for QR factorization that are due to Coleman, Edenbrandt, Gilbert, Hare, Johnson, Olesky, Pothen, and van den Driessche.

  2. Predicting structure in nonsymmetric sparse matrix factorizations

    SciTech Connect

    Gilbert, J.R.; Ng, E.

    1991-12-31

    Many computations on sparse matrices have a phase that predicts the nonzero structure of the output, followed by a phase that actually performs the numerical computation. We study structure prediction for computations that involve nonsymmetric row and column permutations and nonsymmetric or non-square matrices. Our tools are bipartite graphs, matchings, and alternating paths. Our main new result concerns LU factorization with partial pivoting. We show that if a square matrix A has the strong Hall property (i.e., is fully indecomposable) then an upper bound due to George and Ng on the nonzero structure of L + U is as tight as possible. To show this, we prove a crucial result about alternating paths in strong Hall graphs. The alternating-paths theorem seems to be of independent interest: it can also be used to prove related results about structure prediction for QR factorization that are due to Coleman, Edenbrandt, Gilbert, Hare, Johnson, Olesky, Pothen, and van den Driessche.

  3. Predicting structure in nonsymmetric sparse matrix factorizations

    SciTech Connect

    Gilbert, J.R. ); Ng, E. )

    1991-01-01

    Many computations on sparse matrices have a phase that predicts the nonzero structure of the output, followed by a phase that actually performs the numerical computation. We study structure prediction for computations that involve nonsymmetric row and column permutations and nonsymmetric or non-square matrices. Our tools are bipartite graphs, matchings, and alternating paths. Our main new result concerns LU factorization with partial pivoting. We show that if a square matrix A has the strong Hall property (i.e., is fully indecomposable) then an upper bound due to George and Ng on the nonzero structure of L + U is as tight as possible. To show this, we prove a crucial result about alternating paths in strong Hall graphs. The alternating-paths theorem seems to be of independent interest: it can also be used to prove related results about structure prediction for QR factorization that are due to Coleman, Edenbrandt, Gilbert, Hare, Johnson, Olesky, Pothen, and van den Driessche.

  4. Predicting structure in nonsymmetric sparse matrix factorizations

    SciTech Connect

    Gilbert, J.R. ); Ng, E.G. )

    1992-10-01

    Many computations on sparse matrices have a phase that predicts the nonzero structure of the output, followed by a phase that actually performs the numerical computation. We study structure prediction for computations that involve nonsymmetric row and column permutations and nonsymmetric or non-square matrices. Our tools are bipartite graphs, matchings, and alternating paths. Our main new result concerns LU factorization with partial pivoting. We show that if a square matrix A has the strong Hall property (i.e., is fully indecomposable) then an upper bound due to George and Ng on the nonzero structure of L + U is as tight as possible. To show this, we prove a crucial result about alternating paths in strong Hall graphs. The alternating-paths theorem seems to be of independent interest: it can also be used to prove related results about structure prediction for QR factorization that are due to Coleman, Edenbrandt, Gilbert, Hare, Johnson, Olesky, Pothen, and van den Driessche.

  5. Data-directed RNA secondary structure prediction using probabilistic modeling.

    PubMed

    Deng, Fei; Ledda, Mirko; Vaziri, Sana; Aviran, Sharon

    2016-08-01

    Structure dictates the function of many RNAs, but secondary RNA structure analysis is either labor intensive and costly or relies on computational predictions that are often inaccurate. These limitations are alleviated by integration of structure probing data into prediction algorithms. However, existing algorithms are optimized for a specific type of probing data. Recently, new chemistries combined with advances in sequencing have facilitated structure probing at unprecedented scale and sensitivity. These novel technologies and anticipated wealth of data highlight a need for algorithms that readily accommodate more complex and diverse input sources. We implemented and investigated a recently outlined probabilistic framework for RNA secondary structure prediction and extended it to accommodate further refinement of structural information. This framework utilizes direct likelihood-based calculations of pseudo-energy terms per considered structural context and can readily accommodate diverse data types and complex data dependencies. We use real data in conjunction with simulations to evaluate performances of several implementations and to show that proper integration of structural contexts can lead to improvements. Our tests also reveal discrepancies between real data and simulations, which we show can be alleviated by refined modeling. We then propose statistical preprocessing approaches to standardize data interpretation and integration into such a generic framework. We further systematically quantify the information content of data subsets, demonstrating that high reactivities are major drivers of SHAPE-directed predictions and that better understanding of less informative reactivities is key to further improvements. Finally, we provide evidence for the adaptive capability of our framework using mock probe simulations. © 2016 Deng et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

  6. Structure Learning in Bayesian Sensorimotor Integration

    PubMed Central

    Genewein, Tim; Hez, Eduard; Razzaghpanah, Zeynab; Braun, Daniel A.

    2015-01-01

    Previous studies have shown that sensorimotor processing can often be described by Bayesian learning, in particular the integration of prior and feedback information depending on its degree of reliability. Here we test the hypothesis that the integration process itself can be tuned to the statistical structure of the environment. We exposed human participants to a reaching task in a three-dimensional virtual reality environment where we could displace the visual feedback of their hand position in a two dimensional plane. When introducing statistical structure between the two dimensions of the displacement, we found that over the course of several days participants adapted their feedback integration process in order to exploit this structure for performance improvement. In control experiments we found that this adaptation process critically depended on performance feedback and could not be induced by verbal instructions. Our results suggest that structural learning is an important meta-learning component of Bayesian sensorimotor integration. PMID:26305797

  7. Improved Predictions of Secondary Structures for RNA

    NASA Astrophysics Data System (ADS)

    Jaeger, John A.; Turner, Douglas H.; Zuker, Michael

    1989-10-01

    The accuracy of computer predictions of RNA secondary structure from sequence data and free energy parameters has been increased to roughly 70%. Performance is judged by comparison with structures known from phylogenetic analysis. The algorithm also generates suboptimal structures. On average, the best structure within 10% of the lowest free energy contains roughly 90% of phylogenetically known helixes. The algorithm does not include tertiary interactions or pseudoknots and employs a crude model for single-stranded regions. The only favorable interactions are base pairing and stacking of terminal unpaired nucleotides at the ends of helixes. The excellent performance is consistent with these interactions being the primary interactions determining RNA secondary structure.

  8. Particle-swarm structure prediction on clusters

    NASA Astrophysics Data System (ADS)

    Lv, Jian; Wang, Yanchao; Zhu, Li; Ma, Yanming

    2012-08-01

    We have developed an efficient method for cluster structure prediction based on the generalization of particle swarm optimization (PSO). A local version of PSO algorithm was implemented to utilize a fine exploration of potential energy surface for a given non-periodic system. We have specifically devised a technique of so-called bond characterization matrix (BCM) to allow the proper measure on the structural similarity. The BCM technique was then employed to eliminate similar structures and define the desirable local search spaces. We find that the introduction of point group symmetries into generation of cluster structures enables structural diversity and apparently avoids the generation of liquid-like (or disordered) clusters for large systems, thus considerably improving the structural search efficiency. We have incorporated Metropolis criterion into our method to further enhance the structural evolution towards low-energy regimes of potential energy surfaces. Our method has been extensively benchmarked on Lennard-Jones clusters with different sizes up to 150 atoms and applied into prediction of new structures of medium-sized Lin (n = 20, 40, 58) clusters. High search efficiency was achieved, demonstrating the reliability of the current methodology and its promise as a major method on cluster structure prediction.

  9. Structural Integrity of Intelligent Materials and Structures

    DTIC Science & Technology

    1994-02-17

    Memory Actuators ," J. Sound and Vibr., Vol. 140, pp. 437-456, 1990.I 7. Jackson, C.M. et al., ൿ- Nitinol - The Alloy with a Memory:3 Its Physical...55W0 Standard Foam 298 (Rev 2869) P..*Cb.d by ANSI S.13 239- 290,102 -- 2Q-•.m* 4 0388; IMSNVV, INC. Approved f or publ iC rel685O 3 P.O. Box 865...Douglas Aircraft, Grumman, and other companies have resulted in the development of shape memory actuators for the3 control of space structures, the

  10. Predicting Odor Perceptual Similarity from Odor Structure

    PubMed Central

    Weiss, Tali; Frumin, Idan; Khan, Rehan M.; Sobel, Noam

    2013-01-01

    To understand the brain mechanisms of olfaction we must understand the rules that govern the link between odorant structure and odorant perception. Natural odors are in fact mixtures made of many molecules, and there is currently no method to look at the molecular structure of such odorant-mixtures and predict their smell. In three separate experiments, we asked 139 subjects to rate the pairwise perceptual similarity of 64 odorant-mixtures ranging in size from 4 to 43 mono-molecular components. We then tested alternative models to link odorant-mixture structure to odorant-mixture perceptual similarity. Whereas a model that considered each mono-molecular component of a mixture separately provided a poor prediction of mixture similarity, a model that represented the mixture as a single structural vector provided consistent correlations between predicted and actual perceptual similarity (r≥0.49, p<0.001). An optimized version of this model yielded a correlation of r = 0.85 (p<0.001) between predicted and actual mixture similarity. In other words, we developed an algorithm that can look at the molecular structure of two novel odorant-mixtures, and predict their ensuing perceptual similarity. That this goal was attained using a model that considers the mixtures as a single vector is consistent with a synthetic rather than analytical brain processing mechanism in olfaction. PMID:24068899

  11. Test Structures For Bumpy Integrated Circuits

    NASA Technical Reports Server (NTRS)

    Buehler, Martin G.; Sayah, Hoshyar R.

    1989-01-01

    Cross-bridge resistors added to comb and serpentine patterns. Improved combination of test structures built into integrated circuit used to evaluate design rules, fabrication processes, and quality of interconnections. Consist of meshing serpentines and combs, and cross bridge. Structures used to make electrical measurements revealing defects in design or fabrication. Combination of test structures includes three comb arrays, two serpentine arrays, and cross bridge. Made of aluminum or polycrystalline silicon, depending on material in integrated-circuit layers evaluated. Aluminum combs and serpentine arrays deposited over steps made by polycrystalline silicon and diffusion layers, while polycrystalline silicon versions of these structures used to cross over steps made by thick oxide layer.

  12. Predicting ramps by integrating different sorts of information

    NASA Astrophysics Data System (ADS)

    Hirata, Yoshito; Aihara, Kazuyuki

    2016-05-01

    Although predicting sudden rapid changes of renewable energy outputs is useful for maintaining the stability of power grids with many renewable energy resources, the prediction is difficult so far. Here we list causes for the uncertainty for our prediction, quantify them, and forecast whether such sudden rapid changes are likely to happen or not by integrating their quantifications with a method of machine learning. We test the proposed forecast using a toy model and real datasets of solar irradiance and wind speed.

  13. Integrated flow field (IFF) structure

    NASA Technical Reports Server (NTRS)

    Pien, Shyhing M. (Inventor); Warshay, Marvin (Inventor)

    2012-01-01

    The present disclosure relates in part to a flow field structure comprising a hydrophilic part and a hydrophobic part communicably attached to each other via a connecting interface. The present disclosure further relates to electrochemical cells comprising the aforementioned flow fields.

  14. The predictive integration method for dynamics of infrequent events

    NASA Astrophysics Data System (ADS)

    Cubuk, Ekin; Waterland, Amos; Kaxiras, Efthimios

    2012-02-01

    With the increasing prominence and availability of multi-processor computers, recasting problems in a form amenable to parallel solution is becoming a critical step in effective scientific computation. We present a method for parallelizing molecular dynamics simulations in time scale, by using predictive integration. Our method is closely related to Voter's parallel replica method, but goes beyond that approach in that it involves speculatively initializing processors in more than one basin. Our predictive integration method requires predicting possible future configurations while it does not suffer from restrictions due to correlation time after transitions between basins.

  15. Predicting polymeric crystal structures by evolutionary algorithms.

    PubMed

    Zhu, Qiang; Sharma, Vinit; Oganov, Artem R; Ramprasad, Ramamurthy

    2014-10-21

    The recently developed evolutionary algorithm USPEX proved to be a tool that enables accurate and reliable prediction of structures. Here we extend this method to predict the crystal structure of polymers by constrained evolutionary search, where each monomeric unit is treated as a building block with fixed connectivity. This greatly reduces the search space and allows the initial structure generation with different sequences and packings of these blocks. The new constrained evolutionary algorithm is successfully tested and validated on a diverse range of experimentally known polymers, namely, polyethylene, polyacetylene, poly(glycolic acid), poly(vinyl chloride), poly(oxymethylene), poly(phenylene oxide), and poly (p-phenylene sulfide). By fixing the orientation of polymeric chains, this method can be further extended to predict the structures of complex linear polymers, such as all polymorphs of poly(vinylidene fluoride), nylon-6 and cellulose. The excellent agreement between predicted crystal structures and experimentally known structures assures a major role of this approach in the efficient design of the future polymeric materials.

  16. Fracture Testing of Integral Stiffened Structure

    NASA Technical Reports Server (NTRS)

    Newman, John A.; Smith, Stephen W.; Piascik, Robert S.; Dawicke, David S.; Johnston, William M.; Willard, Scott A.

    2008-01-01

    Laboratory testing was conducted to evaluate safety concerns for integrally-stiffened tanks that were found to have developed cracks during pressurization testing. Cracks occurred at fastener holes where additional stiffeners were attached to the integrally-stiffened tank structure. Tests were conducted to obtain material properties and to reproduce the crack morphologies that were observed in service to help determine if the tanks are safe for operation. Reproducing the cracking modes observed during pressurization testing required a complex loading state involving both a tensile load in the integrally-stiffened structure and a pin-load at a fastener hole.

  17. Integrable structures in quantum field theory

    NASA Astrophysics Data System (ADS)

    Negro, Stefano

    2016-08-01

    This review was born as notes for a lecture given at the Young Researchers Integrability School (YRIS) school on integrability in Durham, in the summer of 2015. It deals with a beautiful method, developed in the mid-nineties by Bazhanov, Lukyanov and Zamolodchikov and, as such, called BLZ. This method can be interpreted as a field theory version of the quantum inverse scattering, also known as the algebraic Bethe ansatz. Starting with the case of conformal field theories (CFTs) we show how to build the field theory analogues of commuting transfer T matrices and Baxter Q-operators of integrable lattice models. These objects contain the complete information of the integrable structure of the theory, viz. the integrals of motion, and can be used, as we will show, to derive the thermodynamic Bethe ansatz and nonlinear integral equations. This same method can be easily extended to the description of integrable structures of certain particular massive deformations of CFTs; these, in turn, can be described as quantum group reductions of the quantum sine-Gordon model and it is an easy step to include this last theory in the framework of BLZ approach. Finally we show an interesting and surprising connection of the BLZ structures with classical objects emerging from the study of classical integrable models via the inverse scattering transform method. This connection goes under the name of ODE/IM correspondence and we will present it for the specific case of quantum sine-Gordon model only.

  18. Protein Structure Prediction with Evolutionary Algorithms

    SciTech Connect

    Hart, W.E.; Krasnogor, N.; Pelta, D.A.; Smith, J.

    1999-02-08

    Evolutionary algorithms have been successfully applied to a variety of molecular structure prediction problems. In this paper we reconsider the design of genetic algorithms that have been applied to a simple protein structure prediction problem. Our analysis considers the impact of several algorithmic factors for this problem: the confirmational representation, the energy formulation and the way in which infeasible conformations are penalized, Further we empirically evaluated the impact of these factors on a small set of polymer sequences. Our analysis leads to specific recommendations for both GAs as well as other heuristic methods for solving PSP on the HP model.

  19. Protein Structure Prediction by Protein Threading

    NASA Astrophysics Data System (ADS)

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

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

  20. Reduced ceria nanofilms from structure prediction.

    PubMed

    Kozlov, Sergey M; Demiroglu, Ilker; Neyman, Konstantin M; Bromley, Stefan T

    2015-03-14

    Experimentally, Ce2O3 films are used to study cerium oxide in its fully or partially reduced state, as present in many applications. We have explored the space of low energy Ce2O3 nanofilms using structure prediction and density functional calculations, yielding more than 30 distinct nanofilm structures. First, our results help to rationalize the roles of thermodynamics and kinetics in the preparation of reduced ceria nanofilms with different bulk crystalline structures (e.g. A-type or bixbyite) depending on the support used. Second, we predict a novel, as yet experimentally unresolved, nanofilm which has a structure that does not correspond to any previously reported bulk A2B3 phase and which has an energetic stability between that of A-type and bixbyite. To assist identification and fabrication of this new Ce2O3 nanofilm we calculate some observable properties and propose supports for its epitaxial growth.

  1. Integrated segmentation of cellular structures

    NASA Astrophysics Data System (ADS)

    Ajemba, Peter; Al-Kofahi, Yousef; Scott, Richard; Donovan, Michael; Fernandez, Gerardo

    2011-03-01

    Automatic segmentation of cellular structures is an essential step in image cytology and histology. Despite substantial progress, better automation and improvements in accuracy and adaptability to novel applications are needed. In applications utilizing multi-channel immuno-fluorescence images, challenges include misclassification of epithelial and stromal nuclei, irregular nuclei and cytoplasm boundaries, and over and under-segmentation of clustered nuclei. Variations in image acquisition conditions and artifacts from nuclei and cytoplasm images often confound existing algorithms in practice. In this paper, we present a robust and accurate algorithm for jointly segmenting cell nuclei and cytoplasm using a combination of ideas to reduce the aforementioned problems. First, an adaptive process that includes top-hat filtering, Eigenvalues-of-Hessian blob detection and distance transforms is used to estimate the inverse illumination field and correct for intensity non-uniformity in the nuclei channel. Next, a minimum-error-thresholding based binarization process and seed-detection combining Laplacian-of-Gaussian filtering constrained by a distance-map-based scale selection is used to identify candidate seeds for nuclei segmentation. The initial segmentation using a local maximum clustering algorithm is refined using a minimum-error-thresholding technique. Final refinements include an artifact removal process specifically targeted at lumens and other problematic structures and a systemic decision process to reclassify nuclei objects near the cytoplasm boundary as epithelial or stromal. Segmentation results were evaluated using 48 realistic phantom images with known ground-truth. The overall segmentation accuracy exceeds 94%. The algorithm was further tested on 981 images of actual prostate cancer tissue. The artifact removal process worked in 90% of cases. The algorithm has now been deployed in a high-volume histology analysis application.

  2. Structurally Integrated Antenna Concepts for HALE UAVs

    NASA Technical Reports Server (NTRS)

    Cravey, Robin L.; Vedeler, Erik; Goins, Larry; Young, W. Robert; Lawrence, Roland W.

    2006-01-01

    This technical memorandum describes work done in support of the Multifunctional Structures and Materials Team under the Vehicle Systems Program's ITAS (Integrated Tailored Aero Structures) Project during FY 2005. The Electromagnetics and Sensors Branch (ESB) developed three ultra lightweight antenna concepts compatible with HALE UAVs (High Altitude Long Endurance Unmanned Aerial Vehicles). ESB also developed antenna elements that minimize the interaction between elements and the vehicle to minimize the impact of wing flexure on the EM (electromagnetic) performance of the integrated array. In addition, computer models were developed to perform phase correction for antenna arrays whose elements are moving relative to each other due to wing deformations expected in HALE vehicle concepts. Development of lightweight, conformal or structurally integrated antenna elements and compensating for the impact of a lightweight, flexible structure on a large antenna array are important steps in the realization of HALE UAVs for microwave applications such as passive remote sensing and communications.

  3. UK Environmental Prediction - integration and evaluation at the convective scale

    NASA Astrophysics Data System (ADS)

    Fallmann, Joachim; Lewis, Huw; Castillo, Juan Manuel; Pearson, David; Harris, Chris; Saulter, Andy; Bricheno, Lucy; Blyth, Eleanor

    2016-04-01

    It has long been understood that accurate prediction and warning of the impacts of severe weather requires an integrated approach to forecasting. For example, high impact weather is typically manifested through various interactions and feedbacks between different components of the Earth System. Damaging high winds can lead to significant damage from the large waves and storm surge along coastlines. The impact of intense rainfall can be translated through saturated soils and land surface processes, high river flows and flooding inland. The substantial impacts on individuals, businesses and infrastructure of such events indicate a pressing need to understand better the value that might be delivered through more integrated environmental prediction. To address this need, the Met Office, NERC Centre for Ecology & Hydrology and NERC National Oceanography Centre have begun to develop the foundations of a coupled high resolution probabilistic forecast system for the UK at km-scale. This links together existing model components of the atmosphere, coastal ocean, land surface and hydrology. Our initial focus has been on a 2-year Prototype project to demonstrate the UK coupled prediction concept in research mode. This presentation will provide an update on UK environmental prediction activities. We will present the results from the initial implementation of an atmosphere-land-ocean coupled system and discuss progress and initial results from further development to integrate wave interactions. We will discuss future directions and opportunities for collaboration in environmental prediction, and the challenges to realise the potential of integrated regional coupled forecasting for improving predictions and applications.

  4. Ko Displacement Theory for Structural Shape Predictions

    NASA Technical Reports Server (NTRS)

    Ko, William L.

    2010-01-01

    The development of the Ko displacement theory for predictions of structure deformed shapes was motivated in 2003 by the Helios flying wing, which had a 247-ft (75-m) wing span with wingtip deflections reaching 40 ft (12 m). The Helios flying wing failed in midair in June 2003, creating the need to develop new technology to predict in-flight deformed shapes of unmanned aircraft wings for visual display before the ground-based pilots. Any types of strain sensors installed on a structure can only sense the surface strains, but are incapable to sense the overall deformed shapes of structures. After the invention of the Ko displacement theory, predictions of structure deformed shapes could be achieved by feeding the measured surface strains into the Ko displacement transfer functions for the calculations of out-of-plane deflections and cross sectional rotations at multiple locations for mapping out overall deformed shapes of the structures. The new Ko displacement theory combined with a strain-sensing system thus created a revolutionary new structure- shape-sensing technology.

  5. Structures of the CRISPR genome integration complex.

    PubMed

    Wright, Addison V; Liu, Jun-Jie; Knott, Gavin J; Doxzen, Kevin W; Nogales, Eva; Doudna, Jennifer A

    2017-09-15

    CRISPR-Cas systems depend on the Cas1-Cas2 integrase to capture and integrate short foreign DNA fragments into the CRISPR locus, enabling adaptation to new viruses. We present crystal structures of Cas1-Cas2 bound to both donor and target DNA in intermediate and product integration complexes, as well as a cryo-electron microscopy structure of the full CRISPR locus integration complex, including the accessory protein IHF (integration host factor). The structures show unexpectedly that indirect sequence recognition dictates integration site selection by favoring deformation of the repeat and the flanking sequences. IHF binding bends the DNA sharply, bringing an upstream recognition motif into contact with Cas1 to increase both the specificity and efficiency of integration. These results explain how the Cas1-Cas2 CRISPR integrase recognizes a sequence-dependent DNA structure to ensure site-selective CRISPR array expansion during the initial step of bacterial adaptive immunity. Copyright © 2017, American Association for the Advancement of Science.

  6. Mixed time integration methods for transient thermal analysis of structures

    NASA Technical Reports Server (NTRS)

    Liu, W. K.

    1982-01-01

    The computational methods used to predict and optimize the thermal structural behavior of aerospace vehicle structures are reviewed. In general, two classes of algorithms, implicit and explicit, are used in transient thermal analysis of structures. Each of these two methods has its own merits. Due to the different time scales of the mechanical and thermal responses, the selection of a time integration method can be a different yet critical factor in the efficient solution of such problems. Therefore mixed time integration methods for transient thermal analysis of structures are being developed. The computer implementation aspects and numerical evaluation of these mixed time implicit-explicit algorithms in thermal analysis of structures are presented. A computationally useful method of estimating the critical time step for linear quadrilateral element is also given. Numerical tests confirm the stability criterion and accuracy characteristics of the methods. The superiority of these mixed time methods to the fully implicit method or the fully explicit method is also demonstrated.

  7. Evaluation of structural integrity using integrated testing and analysis

    NASA Technical Reports Server (NTRS)

    Coppolino, Robert N.

    1988-01-01

    An integrated approach to dynamic testing and mathematical model analysis is described. The overall approach addresses four key tasks, namely, pretest planning and analysis, test data acquisition, data reduction and analysis, and test/analysis correlation and mathematical model updates. Several key software programs are employed to accomplish this task. They are a leading finite element code, a sophisticated data analysis processor and a graphical pre- and post-processor along with an advanced interface utility. Several practical structures are used to illustrate tools and concepts employed in the integrated test analysis process.

  8. Structure-Based Predictions of Activity Cliffs

    PubMed Central

    Husby, Jarmila; Bottegoni, Giovanni; Kufareva, Irina; Abagyan, Ruben; Cavalli, Andrea

    2015-01-01

    In drug discovery, it is generally accepted that neighboring molecules in a given descriptors' space display similar activities. However, even in regions that provide strong predictability, structurally similar molecules can occasionally display large differences in potency. In QSAR jargon, these discontinuities in the activity landscape are known as ‘activity cliffs’. In this study, we assessed the reliability of ligand docking and virtual ligand screening schemes in predicting activity cliffs. We performed our calculations on a diverse, independently collected database of cliff-forming co-crystals. Starting from ideal situations, which allowed us to establish our baseline, we progressively moved toward simulating more realistic scenarios. Ensemble- and template-docking achieved a significant level of accuracy, suggesting that, despite the well-known limitations of empirical scoring schemes, activity cliffs can be accurately predicted by advanced structure-based methods. PMID:25918827

  9. Cascaded multiple classifiers for secondary structure prediction.

    PubMed Central

    Ouali, M.; King, R. D.

    2000-01-01

    We describe a new classifier for protein secondary structure prediction that is formed by cascading together different types of classifiers using neural networks and linear discrimination. The new classifier achieves an accuracy of 76.7% (assessed by a rigorous full Jack-knife procedure) on a new nonredundant dataset of 496 nonhomologous sequences (obtained from G.J. Barton and J.A. Cuff). This database was especially designed to train and test protein secondary structure prediction methods, and it uses a more stringent definition of homologous sequence than in previous studies. We show that it is possible to design classifiers that can highly discriminate the three classes (H, E, C) with an accuracy of up to 78% for beta-strands, using only a local window and resampling techniques. This indicates that the importance of long-range interactions for the prediction of beta-strands has been probably previously overestimated. PMID:10892809

  10. Predicting continuous local structure and the effect of its substitution for secondary structure in fragment-free protein structure prediction.

    PubMed

    Faraggi, Eshel; Yang, Yuedong; Zhang, Shesheng; Zhou, Yaoqi

    2009-11-11

    Local structures predicted from protein sequences are used extensively in every aspect of modeling and prediction of protein structure and function. For more than 50 years, they have been predicted at a low-resolution coarse-grained level (e.g., three-state secondary structure). Here, we combine a two-state classifier with real-value predictor to predict local structure in continuous representation by backbone torsion angles. The accuracy of the angles predicted by this approach is close to that derived from NMR chemical shifts. Their substitution for predicted secondary structure as restraints for ab initio structure prediction doubles the success rate. This result demonstrates the potential of predicted local structure for fragment-free tertiary-structure prediction. It further implies potentially significant benefits from using predicted real-valued torsion angles as a replacement for or supplement to the secondary-structure prediction tools used almost exclusively in many computational methods ranging from sequence alignment to function prediction.

  11. RNA Structure: Advances and Assessment of 3D Structure Prediction.

    PubMed

    Miao, Zhichao; Westhof, Eric

    2017-03-30

    Biological functions of RNA molecules are dependent upon sustained specific three-dimensional (3D) structures of RNA, with or without the help of proteins. Understanding of RNA structure is frequently based on 2D structures, which describe only the Watson-Crick (WC) base pairs. Here, we hierarchically review the structural elements of RNA and how they contribute to RNA 3D structure. We focus our analysis on the non-WC base pairs and on RNA modules. Several computer programs have now been designed to predict RNA modules. We describe the RNA-Puzzles initiative, which is a community-wide, blind assessment of RNA 3D structure prediction programs to determine the capabilities and bottlenecks of current predictions. The assessment metrics used in RNA-Puzzles are briefly described. The detection of RNA 3D modules from sequence data and their automatic implementation belong to the current challenges in RNA 3D structure prediction. Expected final online publication date for the Annual Review of Biophysics Volume 46 is May 20, 2017. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

  12. RNA secondary structure prediction using soft computing.

    PubMed

    Ray, Shubhra Sankar; Pal, Sankar K

    2013-01-01

    Prediction of RNA structure is invaluable in creating new drugs and understanding genetic diseases. Several deterministic algorithms and soft computing-based techniques have been developed for more than a decade to determine the structure from a known RNA sequence. Soft computing gained importance with the need to get approximate solutions for RNA sequences by considering the issues related with kinetic effects, cotranscriptional folding, and estimation of certain energy parameters. A brief description of some of the soft computing-based techniques, developed for RNA secondary structure prediction, is presented along with their relevance. The basic concepts of RNA and its different structural elements like helix, bulge, hairpin loop, internal loop, and multiloop are described. These are followed by different methodologies, employing genetic algorithms, artificial neural networks, and fuzzy logic. The role of various metaheuristics, like simulated annealing, particle swarm optimization, ant colony optimization, and tabu search is also discussed. A relative comparison among different techniques, in predicting 12 known RNA secondary structures, is presented, as an example. Future challenging issues are then mentioned.

  13. UK Environmental Prediction - integration and evaluation at the convective scale

    NASA Astrophysics Data System (ADS)

    Fallmann, Joachim; Lewis, Huw; Castillo, Juan Manuel; Pearson, David; Harris, Chris; Saulter, Andy; Bricheno, Lucy; Blyth, Eleanor

    2016-04-01

    Traditionally, the simulation of regional ocean, wave and atmosphere components of the Earth System have been considered separately, with some information on other components provided by means of boundary or forcing conditions. More recently, the potential value of a more integrated approach, as required for global climate and Earth System prediction, for regional short-term applications has begun to gain increasing research effort. In the UK, this activity is motivated by an understanding that accurate prediction and warning of the impacts of severe weather requires an integrated approach to forecasting. The substantial impacts on individuals, businesses and infrastructure of such events indicate a pressing need to understand better the value that might be delivered through more integrated environmental prediction. To address this need, the Met Office, NERC Centre for Ecology & Hydrology and NERC National Oceanography Centre have begun to develop the foundations of a coupled high resolution probabilistic forecast system for the UK at km-scale. This links together existing model components of the atmosphere, coastal ocean, land surface and hydrology. Our initial focus has been on a 2-year Prototype project to demonstrate the UK coupled prediction concept in research mode. This presentation will provide an update on UK environmental prediction activities. We will present the results from the initial implementation of an atmosphere-land-ocean coupled system, including a new eddy-permitting resolution ocean component, and discuss progress and initial results from further development to integrate wave interactions in this relatively high resolution system. We will discuss future directions and opportunities for collaboration in environmental prediction, and the challenges to realise the potential of integrated regional coupled forecasting for improving predictions and applications.

  14. Gene structure prediction by linguistic methods

    SciTech Connect

    Dong, S.; Searls, D.B.

    1994-10-01

    The higher-order structure of genes and other features of biological sequences can be described by means of formal grammars. These grammars can then be used by general-purpose parsers to detect and to assemble such structures by means of syntactic pattern recognition. We describe a grammar and parser for eukaryotic protein-encoding genes, which by some measures is as effective as current connectionist and combinatorial algorithms in predicting gene structures for sequence database entries. Parameters of the grammar rules are optimized for several different species, and mixing experiments are performed to determine the degree of species specificity and the relative importance of compositional, signal-based, and syntactic components in gene prediction. 24 refs., 5 figs., 3 tabs.

  15. An Integrated Approach to Anti-Cancer Drug Sensitivity Prediction.

    PubMed

    Berlow, Noah; Haider, Saad; Wan, Qian; Geltzeiler, Mathew; Davis, Lara E; Keller, Charles; Pal, Ranadip

    2014-01-01

    A framework for design of personalized cancer therapy requires the ability to predict the sensitivity of a tumor to anticancer drugs. The predictive modeling of tumor sensitivity to anti-cancer drugs has primarily focused on generating functions that map gene expressions and genetic mutation profiles to drug sensitivity. In this paper, we present a new approach for drug sensitivity prediction and combination therapy design based on integrated functional and genomic characterizations. The modeling approach when applied to data from the Cancer Cell Line Encyclopedia shows a significant gain in prediction accuracy as compared to elastic net and random forest techniques based on genomic characterizations. Utilizing a Mouse Embryonal Rhabdomyosarcoma cell culture and a drug screen of 60 targeted drugs, we show that predictive modeling based on functional data alone can also produce high accuracy predictions. The framework also allows us to generate personalized tumor proliferation circuits to gain further insights on the individualized biological pathway.

  16. Predicting structured metadata from unstructured metadata

    PubMed Central

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

    2016-01-01

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

  17. Predicting structured metadata from unstructured metadata.

    PubMed

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

    2016-01-01

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

  18. Rich parameterization improves RNA structure prediction.

    PubMed

    Zakov, Shay; Goldberg, Yoav; Elhadad, Michael; Ziv-Ukelson, Michal

    2011-11-01

    Current approaches to RNA structure prediction range from physics-based methods, which rely on thousands of experimentally measured thermodynamic parameters, to machine-learning (ML) techniques. While the methods for parameter estimation are successfully shifting toward ML-based approaches, the model parameterizations so far remained fairly constant. We study the potential contribution of increasing the amount of information utilized by RNA folding prediction models to the improvement of their prediction quality. This is achieved by proposing novel models, which refine previous ones by examining more types of structural elements, and larger sequential contexts for these elements. Our proposed fine-grained models are made practical thanks to the availability of large training sets, advances in machine-learning, and recent accelerations to RNA folding algorithms. We show that the application of more detailed models indeed improves prediction quality, while the corresponding running time of the folding algorithm remains fast. An additional important outcome of this experiment is a new RNA folding prediction model (coupled with a freely available implementation), which results in a significantly higher prediction quality than that of previous models. This final model has about 70,000 free parameters, several orders of magnitude more than previous models. Being trained and tested over the same comprehensive data sets, our model achieves a score of 84% according to the F₁-measure over correctly-predicted base-pairs (i.e., 16% error rate), compared to the previously best reported score of 70% (i.e., 30% error rate). That is, the new model yields an error reduction of about 50%. Trained models and source code are available at www.cs.bgu.ac.il/?negevcb/contextfold.

  19. Bankruptcy Prediction with Interfirm Network Structure

    NASA Astrophysics Data System (ADS)

    Kamei, Hideto; Takayasu, Hideki; Kabashima, Yoshiyuki; Takayasu, Misako

    This study examines bankruptcy in terms of financial variables as well as interfirm network structure variables. We first binarize the variables by introducing a threshold and then select the appropriate set of variables that minimize the p-value in Fisher's exact test. Here, the financial variables related to borrowing and savings are strongly correlated with bankruptcy, but the variables of trade network and capital network, including chain bankruptcy effect, have weaker yet significant correlations. Finally, we perform a bankruptcy prediction with the selected variables and a second-order Ising model and confirm that the Ising model has relatively higher predictive power than the logit model.

  20. Structural Integrity Assessment Using Process Compensated Resonant Testing (pcrt)

    NASA Astrophysics Data System (ADS)

    Singh, Surendra; Jauriqui, Leanne; Biedermann, Eric; Yen, Eric; Cabrera, Daniel; Whalen, Larry; Piotrowski, David; Heck, David

    2011-06-01

    Honeywell, in collaboration with Vibrant, Delta TechOps, and Boeing, has used Process Compensated Resonant Testing (PCRT) for studying structural integrity and functional performance in various components in Auxiliary Power Units (APUs), Propulsion Engines, Defense and Space applications, and Maintenance Repair & Overhaul (MR&O). The motivation behind this work has been the desire to use PCRT for studying Manufacturing Process Control (MPC) and Structural Sustainability Evaluation (SSE), in addition to traditional quality inspection. In this paper, we will report some of these findings and discuss long term PCRT applications, such as structural sustainability evaluation, damage evolution assessment, and life prediction strategy in parts.

  1. An Integrated Software Package to Enable Predictive Simulation Capabilities

    SciTech Connect

    Chen, Yousu; Fitzhenry, Erin B.; Jin, Shuangshuang; Palmer, Bruce J.; Sharma, Poorva; Huang, Zhenyu

    2016-08-11

    The power grid is increasing in complexity due to the deployment of smart grid technologies. Such technologies vastly increase the size and complexity of power grid systems for simulation and modeling. This increasing complexity necessitates not only the use of high-performance-computing (HPC) techniques, but a smooth, well-integrated interplay between HPC applications. This paper presents a new integrated software package that integrates HPC applications and a web-based visualization tool based on a middleware framework. This framework can support the data communication between different applications. Case studies with a large power system demonstrate the predictive capability brought by the integrated software package, as well as the better situational awareness provided by the web-based visualization tool in a live mode. Test results validate the effectiveness and usability of the integrated software package.

  2. Frontoparietal white matter integrity predicts haptic performance in chronic stroke.

    PubMed

    Borstad, Alexandra L; Choi, Seongjin; Schmalbrock, Petra; Nichols-Larsen, Deborah S

    2016-01-01

    Frontoparietal white matter supports information transfer between brain areas involved in complex haptic tasks such as somatosensory discrimination. The purpose of this study was to gain an understanding of the relationship between microstructural integrity of frontoparietal network white matter and haptic performance in persons with chronic stroke and to compare frontoparietal network integrity in participants with stroke and age matched control participants. Nineteen individuals with stroke and 16 controls participated. Haptic performance was quantified using the Hand Active Sensation Test (HASTe), an 18-item match-to-sample test of weight and texture discrimination. Three tesla MRI was used to obtain diffusion-weighted and high-resolution anatomical images of the whole brain. Probabilistic tractography was used to define 10 frontoparietal tracts total; Four intrahemispheric tracts measured bilaterally 1) thalamus to primary somatosensory cortex (T-S1), 2) thalamus to primary motor cortex (T-M1), 3) primary to secondary somatosensory cortex (S1 to SII) and 4) primary somatosensory cortex to middle frontal gyrus (S1 to MFG) and, 2 interhemispheric tracts; S1-S1 and precuneus interhemispheric. A control tract outside the network, the cuneus interhemispheric tract, was also examined. The diffusion metrics fractional anisotropy (FA), mean diffusivity (MD), axial (AD) and radial diffusivity (RD) were quantified for each tract. Diminished FA and elevated MD values are associated with poorer white matter integrity in chronic stroke. Nine of 10 tracts quantified in the frontoparietal network had diminished structural integrity poststroke compared to the controls. The precuneus interhemispheric tract was not significantly different between groups. Principle component analysis across all frontoparietal white matter tract MD values indicated a single factor explained 47% and 57% of the variance in tract mean diffusivity in stroke and control groups respectively. Age

  3. Frontoparietal white matter integrity predicts haptic performance in chronic stroke

    PubMed Central

    Borstad, Alexandra L.; Choi, Seongjin; Schmalbrock, Petra; Nichols-Larsen, Deborah S.

    2015-01-01

    Frontoparietal white matter supports information transfer between brain areas involved in complex haptic tasks such as somatosensory discrimination. The purpose of this study was to gain an understanding of the relationship between microstructural integrity of frontoparietal network white matter and haptic performance in persons with chronic stroke and to compare frontoparietal network integrity in participants with stroke and age matched control participants. Nineteen individuals with stroke and 16 controls participated. Haptic performance was quantified using the Hand Active Sensation Test (HASTe), an 18-item match-to-sample test of weight and texture discrimination. Three tesla MRI was used to obtain diffusion-weighted and high-resolution anatomical images of the whole brain. Probabilistic tractography was used to define 10 frontoparietal tracts total; Four intrahemispheric tracts measured bilaterally 1) thalamus to primary somatosensory cortex (T–S1), 2) thalamus to primary motor cortex (T–M1), 3) primary to secondary somatosensory cortex (S1 to SII) and 4) primary somatosensory cortex to middle frontal gyrus (S1 to MFG) and, 2 interhemispheric tracts; S1–S1 and precuneus interhemispheric. A control tract outside the network, the cuneus interhemispheric tract, was also examined. The diffusion metrics fractional anisotropy (FA), mean diffusivity (MD), axial (AD) and radial diffusivity (RD) were quantified for each tract. Diminished FA and elevated MD values are associated with poorer white matter integrity in chronic stroke. Nine of 10 tracts quantified in the frontoparietal network had diminished structural integrity poststroke compared to the controls. The precuneus interhemispheric tract was not significantly different between groups. Principle component analysis across all frontoparietal white matter tract MD values indicated a single factor explained 47% and 57% of the variance in tract mean diffusivity in stroke and control groups respectively. Age

  4. Prediction and integration of regulatory and protein-protein interactions

    SciTech Connect

    Wichadakul, Duangdao; McDermott, Jason E.; Samudrala, Ram

    2009-04-20

    Knowledge of transcriptional regulatory interactions (TRIs) is essential for exploring functional genomics and systems biology in any organism. While several results from genome-wide analysis of transcriptional regulatory networks are available, they are limited to model organisms such as yeast [1] and worm [2]. Beyond these networks, experiments on TRIs study only individual genes and proteins of specific interest. In this chapter, we present a method for the integration of various data sets to predict TRIs for 54 organisms in the Bioverse [3]. We describe how to compile and handle various formats and identifiers of data sets from different sources, and how to predict the TRIs using a homology-based approach, utilizing the compiled data sets. Integrated data sets include experimentally verified TRIs, binding sites of transcription factors, promoter sequences, protein sub-cellular localization, and protein families. Predicted TRIs expand the networks of gene regulation for a large number of organisms. The integration of experimentally verified and predicted TRIs with other known protein-protein interactions (PPIs) gives insight into specific pathways, network motifs, and the topological dynamics of an integrated network with gene expression under different conditions, essential for exploring functional genomics and systems biology.

  5. Development of an Integrated Moisture Index for predicting species composition

    Treesearch

    Louis R. Iverson; Charles T. Scott; Martin E. Dale; Anantha Prasad

    1996-01-01

    A geographic information system (GIS) approach was used to develop an Integrated Moisture Index (IMI), which was used to predict species composition for Ohio forests. Several landscape features (a slope-aspect shading index, cumulative flow of water downslope, curvature of the landscape, and the water-holding capacity of the soil) were derived from elevation and soils...

  6. Epitopemap: a web application for integrated whole proteome epitope prediction.

    PubMed

    Farrell, Damien; Gordon, Stephen V

    2015-07-14

    Predictions of MHC binding affinity are commonly used in immunoinformatics for T cell epitope prediction. There are multiple available methods, some of which provide web access. However there is currently no convenient way to access the results from multiple methods at the same time or to execute predictions for an entire proteome at once. We designed a web application that allows integration of multiple epitope prediction methods for any number of proteins in a genome. The tool is a front-end for various freely available methods. Features include visualisation of results from multiple predictors within proteins in one plot, genome-wide analysis and estimates of epitope conservation. We present a self contained web application, Epitopemap, for calculating and viewing epitope predictions with multiple methods. The tool is easy to use and will assist in computational screening of viral or bacterial genomes.

  7. Integrating phenotype and gene expression data for predicting gene function.

    PubMed

    Malone, Brandon M; Perkins, Andy D; Bridges, Susan M

    2009-10-08

    This paper presents a framework for integrating disparate data sets to predict gene function. The algorithm constructs a graph, called an integrated similarity graph, by computing similarities based upon both gene expression and textual phenotype data. This integrated graph is then used to make predictions about whether individual genes should be assigned a particular annotation from the Gene Ontology. A combined graph was generated from publicly-available gene expression data and phenotypic information from Saccharomyces cerevisiae. This graph was used to assign annotations to genes, as were graphs constructed from gene expression data and textual phenotype information alone. While the F-measure appeared similar for all three methods, annotations based upon the integrated similarity graph exhibited a better overall precision than gene expression or phenotype information alone can generate. The integrated approach was also able to assign almost as many annotations as the gene expression method alone, and generated significantly more total and correct assignments than the phenotype information could provide. These results suggest that augmenting standard gene expression data sets with publicly-available textual phenotype data can help generate more precise functional annotation predictions while mitigating the weaknesses of a standard textual phenotype approach.

  8. Topological structure prediction in binary nanoparticle superlattices

    DOE PAGES

    Travesset, A.

    2017-04-27

    Systems of spherical nanoparticles with capping ligands have been shown to self-assemble into beautiful superlattices of fascinating structure and complexity. Here, I show that the spherical geometry of the nanoparticle imposes constraints on the nature of the topological defects associated with the capping ligand and that such topological defects control the structure and stability of the superlattices that can be assembled. Furthermore, all of these considerations form the basis for the orbifold topological model (OTM) described in this paper. Finally, the model quantitatively predicts the structure of super-lattices where capping ligands are hydrocarbon chains in excellent agreement with experimental results,more » explains the appearance of low packing fraction lattices as equilibrium, why certain similar structures are more stable (bccAB6vs. CaB6, AuCu vs. CsCl, etc.) and many other experimental observations.« less

  9. Integrate modelling of smart structures for astronomy: design future technologies

    NASA Astrophysics Data System (ADS)

    Riva, M.; Moschetti, M.

    2016-07-01

    The astronomical instrumentation needs high level of image quality and stability. The quality of images processed by an optical instrument can be referred to the size of the spot and/or the point spread function (p.s.f.), while the stability is related to the displacement of the spot centroid during the observations. The importance of new design procedures for astronomical instruments through the direct design of the materials taking into account their functionalities integrating different approaches (FEM + raytracing) is then enhanced by the new upcoming requirement. Different functional materials can be joined together exploiting each peculiar property in order to realize an integrated structure better known as Smart Structure. They are capable of sensing and reacting to their environment in a predictable and desired manner, through the integration of various elements, such as sensors, actuators, power sources, signal processors, and communications network. The Paper describes possible application related to two main functional materials: piezoelectric materials and Shape Memory Alloys.

  10. Reduced ceria nanofilms from structure prediction

    NASA Astrophysics Data System (ADS)

    Kozlov, Sergey M.; Demiroglu, Ilker; Neyman, Konstantin M.; Bromley, Stefan T.

    2015-02-01

    Experimentally, Ce2O3 films are used to study cerium oxide in its fully or partially reduced state, as present in many applications. We have explored the space of low energy Ce2O3 nanofilms using structure prediction and density functional calculations, yielding more than 30 distinct nanofilm structures. First, our results help to rationalize the roles of thermodynamics and kinetics in the preparation of reduced ceria nanofilms with different bulk crystalline structures (e.g. A-type or bixbyite) depending on the support used. Second, we predict a novel, as yet experimentally unresolved, nanofilm which has a structure that does not correspond to any previously reported bulk A2B3 phase and which has an energetic stability between that of A-type and bixbyite. To assist identification and fabrication of this new Ce2O3 nanofilm we calculate some observable properties and propose supports for its epitaxial growth.Experimentally, Ce2O3 films are used to study cerium oxide in its fully or partially reduced state, as present in many applications. We have explored the space of low energy Ce2O3 nanofilms using structure prediction and density functional calculations, yielding more than 30 distinct nanofilm structures. First, our results help to rationalize the roles of thermodynamics and kinetics in the preparation of reduced ceria nanofilms with different bulk crystalline structures (e.g. A-type or bixbyite) depending on the support used. Second, we predict a novel, as yet experimentally unresolved, nanofilm which has a structure that does not correspond to any previously reported bulk A2B3 phase and which has an energetic stability between that of A-type and bixbyite. To assist identification and fabrication of this new Ce2O3 nanofilm we calculate some observable properties and propose supports for its epitaxial growth. Electronic supplementary information (ESI) available: Graph of IP versus DFT relative energies for nanofilms, GGA + U calculated lattice parameters and

  11. Prediction of RNA secondary structures with pseudoknots

    NASA Astrophysics Data System (ADS)

    Bon, M.; Orland, H.

    2010-08-01

    We present a new algorithm to predict RNA secondary structures with pseudoknots. The method is based on a classification of RNA structures according to their topological genus. The algorithm utilizes a simplified parametrization of the free energies for pair stacking, loop penalties, etc. and in addition a free energy penalty proportional to the topological genus of the pairing graph. Our method can take into account all pseudoknot topologies and achieves high success rates compared to state-of-the-art methods. This shows that the genus is a promising concept to classify pseudoknots.

  12. Protein Structure Prediction Using String Kernels

    DTIC Science & Technology

    2006-03-03

    evaluated using the sets of sequences obtained from the SCOP database [39]. The SCOP database is a manually curated protein structure database assigning...proteins into hierarchically defined classes. The fold prediction problem in the context of SCOP can be defined as assigning a protein sequence to its...above techniques, remote homology detection is simulated by formulating it as a superfamily classification problem within the context of the SCOP database

  13. A Software Pipeline for Protein Structure Prediction

    DTIC Science & Technology

    2006-11-01

    distant relationships between the domain sequence and a library of thousands of protein fold templates derived from the SCOP 1.69 database (Andreeva...from the SCOP 1.69 database (Andreeva, Howorth et al. 2004) and a list of PDB sequences that have low sequence similarity to every other sequence...protein as defined by SCOP . 4. DISCUSSION Our assessment of the capabilities of the protein structure-prediction suite is consistent with other

  14. NEWS: Improving Water and Energy Prediction through Integration

    NASA Astrophysics Data System (ADS)

    Belvedere, D. R.; Entin, J.; Houser, P.; Schiffer, R. A.

    2010-12-01

    The water and energy cycle is driven by a multiplicity of complex processes and interactions at all time and space scales, many of which are inadequately understood and poorly represented in model predictions. In addition, many of the components of the global water cycle prediction system are available, but not integrated; yet improved water and energy cycle process understanding and model prediction require inter-disciplinary integration of many traditional disciplines, including atmospheric, terrestrial and ocean scientists, observationalists, modelers and stakeholders, and weather, climate and geologic researchers. In 2003 NASA established the NASA Energy and Water cycle Study (NEWS), whose long-term grand challenge is to document and enable improved, observationally based, predictions of water and energy cycle consequences of Earth system variability and change. However, recognizing that, the broad objectives of energy and water cycling related climate research extend well beyond the purview of any single agency or program, and call for the support of many activities that are matched to each agency's respective roles and missions. This poster will highlight inter-disciplinary science results made possible through NEWS critical linkages (integration) by the four NEWS working groups listed below, NASA research programs and satellite missions, other agencies, and international efforts. Drought & Flood Extremes: including water and energy aspects of abrupt climate change Evaporation & Latent Heating: including both land and ocean Water and Energy Cycle Climatology: exploiting and influencing evolving observing systems Modeling & Water Cycle Prediction: fostering interaction with the global modeling community

  15. Integrated Management of Structural Pests in Schools.

    ERIC Educational Resources Information Center

    Illinois State Dept. of Public Health, Springfield.

    The state of Illinois is encouraging schools to better inspect and evaluate the causes of their pest infestation problems through use of the Integrated Pest Management (IPM) guidelines developed by the Illinois Department of Public Health. This guide reviews the philosophy and organization of an IPM program for structural pests in schools,…

  16. Testing Predictive Models of Technology Integration in Mexico and the United States

    ERIC Educational Resources Information Center

    Velazquez, Cesareo Morales

    2008-01-01

    Data from Mexico City, Mexico (N = 978) and from Texas, USA (N = 932) were used to test the predictive validity of the teacher professional development component of the Will, Skill, Tool Model of Technology Integration in a cross-cultural context. Structural equation modeling (SEM) was used to test the model. Analyses of these data yielded…

  17. Testing Predictive Models of Technology Integration in Mexico and the United States

    ERIC Educational Resources Information Center

    Velazquez, Cesareo Morales

    2008-01-01

    Data from Mexico City, Mexico (N = 978) and from Texas, USA (N = 932) were used to test the predictive validity of the teacher professional development component of the Will, Skill, Tool Model of Technology Integration in a cross-cultural context. Structural equation modeling (SEM) was used to test the model. Analyses of these data yielded…

  18. Enhancing interacting residue prediction with integrated contact matrix prediction in protein-protein interaction.

    PubMed

    Du, Tianchuan; Liao, Li; Wu, Cathy H

    2016-12-01

    Identifying the residues in a protein that are involved in protein-protein interaction and identifying the contact matrix for a pair of interacting proteins are two computational tasks at different levels of an in-depth analysis of protein-protein interaction. Various methods for solving these two problems have been reported in the literature. However, the interacting residue prediction and contact matrix prediction were handled by and large independently in those existing methods, though intuitively good prediction of interacting residues will help with predicting the contact matrix. In this work, we developed a novel protein interacting residue prediction system, contact matrix-interaction profile hidden Markov model (CM-ipHMM), with the integration of contact matrix prediction and the ipHMM interaction residue prediction. We propose to leverage what is learned from the contact matrix prediction and utilize the predicted contact matrix as "feedback" to enhance the interaction residue prediction. The CM-ipHMM model showed significant improvement over the previous method that uses the ipHMM for predicting interaction residues only. It indicates that the downstream contact matrix prediction could help the interaction site prediction.

  19. MMM: A toolbox for integrative structure modeling.

    PubMed

    Jeschke, Gunnar

    2017-08-11

    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.

  20. Integrated Catadioptric Pickup with Ferrofluidic Cooling Structure

    NASA Astrophysics Data System (ADS)

    Onozawa, Kazutoshi; Yamanaka, Kazuhiko; Okuda, Takuya; Tojo, Tomoaki; Iijima, Shinichi; Ueda, Daisuke; Kubo, Junichi; Kitagawa, Seiichro

    2006-02-01

    We have developed a novel integrated catadioptric pickup with a ferrofluidic cooling structure for digital versatile discs (DVDs). To miniaturize the optical system, we made the catadioptric system on a moving head. The catadioptric system consists of a holographic catadioptric lens (HCL), a reflective mirror, a laser diode (LD), and a photodiode IC (PDIC). The HCL has a holographic surface, an aspherical mirror and two aspherical surfaces. This system realized the integration of all optical components into the moving head. The height of the optical system was 8.6 mm including the working distance. To realize efficient heat transfer without sacrificing the motion of the moving head, we developed a cooling structure in which gaps between magnets and coils are filled with ferrofluid. The thermal characteristics were as good as those of conventional optical pickups, proving that the ferrofluidic cooling structure has superior cooling performance. The ferrofluid did not sacrifice the motion of the moving head because of its fluidity.

  1. Quantifying the structural integrity of nanorod arrays.

    PubMed

    Thöle, Florian; Xue, Longjian; HEß, Claudia; Hillebrand, Reinald; Gorb, Stanislav N; Steinhart, Martin

    2017-02-01

    Arrays of aligned nanorods oriented perpendicular to a support, which are accessible by top-down lithography or by means of shape-defining hard templates, have received increasing interest as sensor components, components for nanophotonics and nanoelectronics, substrates for tissue engineering, surfaces having specific adhesive or antiadhesive properties and as surfaces with customized wettability. Agglomeration of the nanorods deteriorates the performance of components based on nanorod arrays. A comprehensive body of literature deals with mechanical failure mechanisms of nanorods and design criteria for mechanically stable nanorod arrays. However, the structural integrity of nanorod arrays is commonly evaluated only visually and qualitatively. We use real-space analysis of microscopic images to quantify the fraction of condensed nanorods in nanorod arrays. We suggest the number of array elements apparent in the micrographs divided by the number of array elements a defect-free array would contain in the same area, referred to as integrity fraction, as a measure of structural array integrity. Reproducible procedures to determine the imaged number of array elements are introduced. Thus, quantitative comparisons of different nanorod arrays, or of one nanorod array at different stages of its use, are possible. Structural integrities of identical nanorod arrays differing only in the length of the nanorods are exemplarily analysed.

  2. Multithreaded parsing for predicting RNA secondary structures.

    PubMed

    Al-Mulhem, Muhammed S

    2010-01-01

    Many computational approaches have been developed for modelling and analysing the RNA secondary structure. These approaches are based on diverse methods such as grammars, dynamic programming, matching and evolutionary algorithms. This paper proposes a new parsing algorithm for the prediction of RNA secondary structures. The proposed algorithm is based on the shift-reduce LR parsing algorithm for programming languages. It has two main contributions: it extends the LR parsing algorithm by using a Stochastic Context-Free Grammar (SCFG) instead of Context-Free Grammar (CFG) for parsing RNA secondary structures; it extends the LR parsing algorithm by using a multithreaded approach to handle the LR parsing conflicts resulting from the use of ambiguous grammars.

  3. Development of Improved Surface Integral Methods for Jet Aeroacoustic Predictions

    NASA Technical Reports Server (NTRS)

    Pilon, Anthony R.; Lyrintzis, Anastasios S.

    1997-01-01

    The accurate prediction of aerodynamically generated noise has become an important goal over the past decade. Aeroacoustics must now be an integral part of the aircraft design process. The direct calculation of aerodynamically generated noise with CFD-like algorithms is plausible. However, large computer time and memory requirements often make these predictions impractical. It is therefore necessary to separate the aeroacoustics problem into two parts, one in which aerodynamic sound sources are determined, and another in which the propagating sound is calculated. This idea is applied in acoustic analogy methods. However, in the acoustic analogy, the determination of far-field sound requires the solution of a volume integral. This volume integration again leads to impractical computer requirements. An alternative to the volume integrations can be found in the Kirchhoff method. In this method, Green's theorem for the linear wave equation is used to determine sound propagation based on quantities on a surface surrounding the source region. The change from volume to surface integrals represents a tremendous savings in the computer resources required for an accurate prediction. This work is concerned with the development of enhancements of the Kirchhoff method for use in a wide variety of aeroacoustics problems. This enhanced method, the modified Kirchhoff method, is shown to be a Green's function solution of Lighthill's equation. It is also shown rigorously to be identical to the methods of Ffowcs Williams and Hawkings. This allows for development of versatile computer codes which can easily alternate between the different Kirchhoff and Ffowcs Williams-Hawkings formulations, using the most appropriate method for the problem at hand. The modified Kirchhoff method is developed primarily for use in jet aeroacoustics predictions. Applications of the method are shown for two dimensional and three dimensional jet flows. Additionally, the enhancements are generalized so that

  4. The structure of integral dimensions: contrasting topological and Cartesian representations.

    PubMed

    Jones, Matt; Goldstone, Robert L

    2013-02-01

    Diverse evidence shows that perceptually integral dimensions, such as those composing color, are represented holistically. However, the nature of these holistic representations is poorly understood. Extant theories, such as those founded on multidimensional scaling or general recognition theory, model integral stimulus spaces using a Cartesian coordinate system, just as with spaces defined by separable dimensions. This approach entails a rich geometrical structure that has never been questioned but may not be psychologically meaningful for integral dimensions. In particular, Cartesian models carry a notion of orthogonality of component dimensions, such that if 1 dimension is diagnostic for a classification or discrimination task, another can be selected as uniquely irrelevant. This article advances an alternative model in which integral dimensions are characterized as topological spaces. The Cartesian and topological models are tested in a series of experiments using the perceptual-learning phenomenon of dimension differentiation, whereby discrimination training with integral-dimension stimuli can induce an analytic representation of those stimuli. Under the present task design, the 2 models make contrasting predictions regarding the analytic representation that will be learned. Results consistently support the Cartesian model. These findings indicate that perceptual representations of integral dimensions are surprisingly structured, despite their holistic, unanalyzed nature.

  5. Improved network community structure improves function prediction

    PubMed Central

    Lee, Juyong; Gross, Steven P.; Lee, Jooyoung

    2013-01-01

    We are overwhelmed by experimental data, and need better ways to understand large interaction datasets. While clustering related nodes in such networks—known as community detection—appears a promising approach, detecting such communities is computationally difficult. Further, how to best use such community information has not been determined. Here, within the context of protein function prediction, we address both issues. First, we apply a novel method that generates improved modularity solutions than the current state of the art. Second, we develop a better method to use this community information to predict proteins' functions. We discuss when and why this community information is important. Our results should be useful for two distinct scientific communities: first, those using various cost functions to detect community structure, where our new optimization approach will improve solutions, and second, those working to extract novel functional information about individual nodes from large interaction datasets. PMID:23852097

  6. Posterror slowing predicts rule-based but not information-integration category learning.

    PubMed

    Tam, Helen; Maddox, W Todd; Huang-Pollock, Cynthia L

    2013-12-01

    We examined whether error monitoring, operationalized as the degree to which individuals slow down after committing an error (i.e., posterror slowing), is differentially important in the learning of rule-based versus information-integration category structures. Rule-based categories are most efficiently solved through the application of an explicit verbal strategy (e.g., "sort by color"). In contrast, information-integration categories are believed to be learned in a trial-by-trial, associative manner. Our results indicated that posterror slowing predicts enhanced rule-based but not information-integration category learning. Implications for multiple category-learning systems are discussed.

  7. Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields

    NASA Astrophysics Data System (ADS)

    Wang, Sheng; Peng, Jian; Ma, Jianzhu; Xu, Jinbo

    2016-01-01

    Protein secondary structure (SS) prediction is important for studying protein structure and function. When only the sequence (profile) information is used as input feature, currently the best predictors can obtain ~80% Q3 accuracy, which has not been improved in the past decade. Here we present DeepCNF (Deep Convolutional Neural Fields) for protein SS prediction. DeepCNF is a Deep Learning extension of Conditional Neural Fields (CNF), which is an integration of Conditional Random Fields (CRF) and shallow neural networks. DeepCNF can model not only complex sequence-structure relationship by a deep hierarchical architecture, but also interdependency between adjacent SS labels, so it is much more powerful than CNF. Experimental results show that DeepCNF can obtain ~84% Q3 accuracy, ~85% SOV score, and ~72% Q8 accuracy, respectively, on the CASP and CAMEO test proteins, greatly outperforming currently popular predictors. As a general framework, DeepCNF can be used to predict other protein structure properties such as contact number, disorder regions, and solvent accessibility.

  8. Predicting protein structures with a multiplayer online game.

    PubMed

    Cooper, Seth; Khatib, Firas; Treuille, Adrien; Barbero, Janos; Lee, Jeehyung; Beenen, Michael; Leaver-Fay, Andrew; Baker, David; Popović, Zoran; Players, Foldit

    2010-08-05

    People exert large amounts of problem-solving effort playing computer games. Simple image- and text-recognition tasks have been successfully 'crowd-sourced' through games, but it is not clear if more complex scientific problems can be solved with human-directed computing. Protein structure prediction is one such problem: locating the biologically relevant native conformation of a protein is a formidable computational challenge given the very large size of the search space. Here we describe Foldit, a multiplayer online game that engages non-scientists in solving hard prediction problems. Foldit players interact with protein structures using direct manipulation tools and user-friendly versions of algorithms from the Rosetta structure prediction methodology, while they compete and collaborate to optimize the computed energy. We show that top-ranked Foldit players excel at solving challenging structure refinement problems in which substantial backbone rearrangements are necessary to achieve the burial of hydrophobic residues. Players working collaboratively develop a rich assortment of new strategies and algorithms; unlike computational approaches, they explore not only the conformational space but also the space of possible search strategies. The integration of human visual problem-solving and strategy development capabilities with traditional computational algorithms through interactive multiplayer games is a powerful new approach to solving computationally-limited scientific problems.

  9. Integrated structural-aerodynamic design optimization

    NASA Technical Reports Server (NTRS)

    Haftka, R. T.; Kao, P. J.; Grossman, B.; Polen, D.; Sobieszczanski-Sobieski, J.

    1988-01-01

    This paper focuses on the processes of simultaneous aerodynamic and structural wing design as a prototype for design integration, with emphasis on the major difficulty associated with multidisciplinary design optimization processes, their enormous computational costs. Methods are presented for reducing this computational burden through the development of efficient methods for cross-sensitivity calculations and the implementation of approximate optimization procedures. Utilizing a modular sensitivity analysis approach, it is shown that the sensitivities can be computed without the expensive calculation of the derivatives of the aerodynamic influence coefficient matrix, and the derivatives of the structural flexibility matrix. The same process is used to efficiently evaluate the sensitivities of the wing divergence constraint, which should be particularly useful, not only in problems of complete integrated aircraft design, but also in aeroelastic tailoring applications.

  10. Structural Integrity of a Wind Tunnel Balance

    NASA Technical Reports Server (NTRS)

    Karkehabadi, R.; Rhew, R. D.

    2004-01-01

    The National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) has been designing strain-gage balances for utilization in wind tunnels since its inception. The utilization of balances span over a wide variety of aerodynamic tests. A force balance is an inherently critically stressed component due to the requirements of measurement sensitivity. Research and analyses are done in order to investigate the structural integrity of the balances as well as developing an understanding of their performance in order to enhance their capability. Maximum loading occurs when all 6 components of the loads are applied simultaneously with their maximum value allowed (limit load). This circumstance normally does not occur in the wind tunnel. However, if it occurs, is the balance capable of handling the loads with an acceptable factor of safety? LaRC Balance 1621 was modeled and meshed in PATRAN for analysis in NASTRAN. For a complete analysis, it is necessary to consider all the load cases as well as use dense mesh near all the edges. Because of computer limitations, it is not possible to have one model with the dense mesh near all edges. In the present study, a dense mesh is limited to the surface corners where the cage and axial sections meet. Four different load combinations are used for the current analysis. Linear analysis is performed for each load case. In the case where the stress value is above linear elastic region, it is necessary to perform nonlinear analysis. It is also important to investigate the variables limiting the structural integrity of the balances. In order to investigate the possibility of modifying the existing balances to enhance the structural integrity, some modifications are done on this balance. The structural integrity of the balance after modification is investigated.

  11. Predicting road accidents: Structural time series approach

    NASA Astrophysics Data System (ADS)

    Junus, Noor Wahida Md; Ismail, Mohd Tahir

    2014-07-01

    In this paper, the model for occurrence of road accidents in Malaysia between the years of 1970 to 2010 was developed and throughout this model the number of road accidents have been predicted by using the structural time series approach. The models are developed by using stepwise method and the residual of each step has been analyzed. The accuracy of the model is analyzed by using the mean absolute percentage error (MAPE) and the best model is chosen based on the smallest Akaike information criterion (AIC) value. A structural time series approach found that local linear trend model is the best model to represent the road accidents. This model allows level and slope component to be varied over time. In addition, this approach also provides useful information on improving the conventional time series method.

  12. Predicting Protein Function via Semantic Integration of Multiple Networks.

    PubMed

    Yu, Guoxian; Fu, Guangyuan; Wang, Jun; Zhu, Hailong

    2016-01-01

    Determining the biological functions of proteins is one of the key challenges in the post-genomic era. The rapidly accumulated large volumes of proteomic and genomic data drives to develop computational models for automatically predicting protein function in large scale. Recent approaches focus on integrating multiple heterogeneous data sources and they often get better results than methods that use single data source alone. In this paper, we investigate how to integrate multiple biological data sources with the biological knowledge, i.e., Gene Ontology (GO), for protein function prediction. We propose a method, called SimNet, to Semantically integrate multiple functional association Networks derived from heterogenous data sources. SimNet firstly utilizes GO annotations of proteins to capture the semantic similarity between proteins and introduces a semantic kernel based on the similarity. Next, SimNet constructs a composite network, obtained as a weighted summation of individual networks, and aligns the network with the kernel to get the weights assigned to individual networks. Then, it applies a network-based classifier on the composite network to predict protein function. Experiment results on heterogenous proteomic data sources of Yeast, Human, Mouse, and Fly show that, SimNet not only achieves better (or comparable) results than other related competitive approaches, but also takes much less time. The Matlab codes of SimNet are available at https://sites.google.com/site/guoxian85/simnet.

  13. UK Environmental Prediction - integration and evaluation at the convective scale

    NASA Astrophysics Data System (ADS)

    Lewis, Huw; Brunet, Gilbert; Harris, Chris; Best, Martin; Saulter, Andrew; Holt, Jason; Bricheno, Lucy; Brerton, Ashley; Reynard, Nick; Blyth, Eleanor; Martinez de la Torre, Alberto

    2015-04-01

    It has long been understood that accurate prediction and warning of the impacts of severe weather requires an integrated approach to forecasting. This was well demonstrated in the UK throughout winter 2013/14 when an exceptional run of severe winter storms, often with damaging high winds and intense rainfall led to significant damage from the large waves and storm surge along coastlines, and from saturated soils, high river flows and significant flooding inland. The substantial impacts on individuals, businesses and infrastructure indicate a pressing need to understand better the value that might be delivered through more integrated environmental prediction. To address this need, the Met Office, Centre for Ecology & Hydrology and National Oceanography Centre have begun to develop the foundations of a coupled high resolution probabilistic forecast system for the UK at km-scale. This links together existing model components of the atmosphere, coastal ocean, land surface and hydrology. Our initial focus on a 2-year Prototype project will demonstrate the UK coupled prediction concept in research mode, including an analysis of the winter 2013/14 storms and its impacts. By linking science development to operational collaborations such as the UK Natural Hazards Partnership, we can ensure that science priorities are rooted in user requirements. This presentation will provide an overview of UK environmental prediction activities and an update on progress during the first year of the Prototype project. We will present initial results from the coupled model development and discuss the challenges to realise the potential of integrated regional coupled forecasting for improving predictions and applications.

  14. Structure Prediction and Validation of the ERK8 Kinase Domain

    PubMed Central

    Strambi, Angela; Mori, Mattia; Rossi, Matteo; Colecchia, David; Manetti, Fabrizio; Carlomagno, Francesca; Botta, Maurizio; Chiariello, Mario

    2013-01-01

    Extracellular signal-regulated kinase 8 (ERK8) has been already implicated in cell transformation and in the protection of genomic integrity and, therefore, proposed as a novel potential therapeutic target for cancer. In the absence of a crystal structure, we developed a three-dimensional model for its kinase domain. To validate our model we applied a structure-based virtual screening protocol consisting of pharmacophore screening and molecular docking. Experimental characterization of the hit compounds confirmed that a high percentage of the identified scaffolds was able to inhibit ERK8. We also confirmed an ATP competitive mechanism of action for the two best-performing molecules. Ultimately, we identified an ERK8 drug-resistant “gatekeeper” mutant that corroborated the predicted molecular binding mode, confirming the reliability of the generated structure. We expect that our model will be a valuable tool for the development of specific ERK8 kinase inhibitors. PMID:23326322

  15. Phylogenetic approaches to natural product structure prediction.

    PubMed

    Ziemert, Nadine; Jensen, Paul R

    2012-01-01

    Phylogenetics is the study of the evolutionary relatedness among groups of organisms. Molecular phylogenetics uses sequence data to infer these relationships for both organisms and the genes they maintain. With the large amount of publicly available sequence data, phylogenetic inference has become increasingly important in all fields of biology. In the case of natural product research, phylogenetic relationships are proving to be highly informative in terms of delineating the architecture and function of the genes involved in secondary metabolite biosynthesis. Polyketide synthases and nonribosomal peptide synthetases provide model examples in which individual domain phylogenies display different predictive capacities, resolving features ranging from substrate specificity to structural motifs associated with the final metabolic product. This chapter provides examples in which phylogeny has proven effective in terms of predicting functional or structural aspects of secondary metabolism. The basics of how to build a reliable phylogenetic tree are explained along with information about programs and tools that can be used for this purpose. Furthermore, it introduces the Natural Product Domain Seeker, a recently developed Web tool that employs phylogenetic logic to classify ketosynthase and condensation domains based on established enzyme architecture and biochemical function. Copyright © 2012 Elsevier Inc. All rights reserved.

  16. Structural network efficiency predicts conversion to dementia

    PubMed Central

    Tuladhar, Anil M.; van Uden, Ingeborg W.M.; Rutten-Jacobs, Loes C.A.; Lawrence, Andrew; van der Holst, Helena; van Norden, Anouk; de Laat, Karlijn; van Dijk, Ewoud; Claassen, Jurgen A.H.R.; Kessels, Roy P.C.; Markus, Hugh S.; Norris, David G.

    2016-01-01

    Objective: To examine whether structural network connectivity at baseline predicts incident all-cause dementia in a prospective hospital-based cohort of elderly participants with MRI evidence of small vessel disease (SVD). Methods: A total of 436 participants from the Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort (RUN DMC), a prospective hospital-based cohort of elderly without dementia with cerebral SVD, were included in 2006. During follow-up (2011–2012), dementia was diagnosed. The structural network was constructed from baseline diffusion tensor imaging followed by deterministic tractography and measures of efficiency using graph theory were calculated. Cox proportional regression analyses were conducted. Results: During 5 years of follow-up, 32 patients developed dementia. MRI markers for SVD were strongly associated with network measures. Patients with dementia showed lower total network strength and global and local efficiency at baseline as compared with the group without dementia. Lower global network efficiency was independently associated with increased risk of incident all-cause dementia (hazard ratio 0.63, 95% confidence interval 0.42–0.96, p = 0.032); in contrast, individual SVD markers including lacunes, white matter hyperintensities volume, and atrophy were not independently associated. Conclusions: These results support a role of network disruption playing a pivotal role in the genesis of dementia in SVD, and suggest network analysis of the connectivity of white matter has potential as a predictive marker in the disease. PMID:26888983

  17. Initial Integration of Noise Prediction Tools for Acoustic Scattering Effects

    NASA Technical Reports Server (NTRS)

    Nark, Douglas M.; Burley, Casey L.; Tinetti, Ana; Rawls, John W.

    2008-01-01

    This effort provides an initial glimpse at NASA capabilities available in predicting the scattering of fan noise from a non-conventional aircraft configuration. The Aircraft NOise Prediction Program, Fast Scattering Code, and the Rotorcraft Noise Model were coupled to provide increased fidelity models of scattering effects on engine fan noise sources. The integration of these codes led to the identification of several keys issues entailed in applying such multi-fidelity approaches. In particular, for prediction at noise certification points, the inclusion of distributed sources leads to complications with the source semi-sphere approach. Computational resource requirements limit the use of the higher fidelity scattering code to predict radiated sound pressure levels for full scale configurations at relevant frequencies. And, the ability to more accurately represent complex shielding surfaces in current lower fidelity models is necessary for general application to scattering predictions. This initial step in determining the potential benefits/costs of these new methods over the existing capabilities illustrates a number of the issues that must be addressed in the development of next generation aircraft system noise prediction tools.

  18. Tank System Integrated Model: A Cryogenic Tank Performance Prediction Program

    NASA Technical Reports Server (NTRS)

    Bolshinskiy, L. G.; Hedayat, A.; Hastings, L. J.; Sutherlin, S. G.; Schnell, A. R.; Moder, J. P.

    2017-01-01

    Accurate predictions of the thermodynamic state of the cryogenic propellants, pressurization rate, and performance of pressure control techniques in cryogenic tanks are required for development of cryogenic fluid long-duration storage technology and planning for future space exploration missions. This Technical Memorandum (TM) presents the analytical tool, Tank System Integrated Model (TankSIM), which can be used for modeling pressure control and predicting the behavior of cryogenic propellant for long-term storage for future space missions. Utilizing TankSIM, the following processes can be modeled: tank self-pressurization, boiloff, ullage venting, mixing, and condensation on the tank wall. This TM also includes comparisons of TankSIM program predictions with the test data andexamples of multiphase mission calculations.

  19. Integrated support structure for GASCAN 2

    NASA Technical Reports Server (NTRS)

    1990-01-01

    The focus of the Worcester Polytechnic Institute (WPI) Advanced Space Design Program was the preliminary design of the Integrated Support Structure for GASCAN II, a Get Away Special canister donated by the MITRE Corporation. Two teams of three students each worked on the support structure. There was a structural design team and a thermal design team. The structure will carry three experiments also undergoing preliminary design this year, the mu-gravity Ignition Experiment, the Rotational Flow in Low Gravity Experiment, and the Ionospheric Properties and Propagation Experiment. The structural design team was responsible for the layout of the GASCAN and the preliminary design of the structure itself. They produced the physical interface specifications defining the baseline weights and volumes for the equipment and produced layout drawings of the system. The team produced static and modal finite element analysis of the structure using ANSYS. The thermal design team was responsible for the power and timing requirements of the payload and for the identification and preliminary analysis of potential thermal problems. The team produced the power, timing, and energy interface specifications and assisted in the development of the specification of the battery pack. The thermal parameters of each experiment were cataloged and the experiments were subjected to worst case heat transfer scenarios.

  20. Structural integrity of future aging airplanes

    NASA Astrophysics Data System (ADS)

    McGuire, Jack F.; Goranson, Ulf G.

    1992-07-01

    A multitude of design considerations is involved in ensuring the structural integrity of Boeing jet transports that have common design concepts validated by extensive analyses, tests, and three decades of service. As airplanes approach their design service objectives, the incidences of fatigue and corrosion may become widespread. Continuing airworthiness of the aging jet fleet requires diligent performance from the manufacturer, the airlines, and airworthiness authorities. Aging fleet support includes timely development of supplemental structural inspection documents applicable to selected older airplanes, teardown inspections of high-time airframes retired from service, fatigue testing of older airframes, and structural surveys of more than 130 airplanes operated throughout the world. Lessons learned from these activities are incorporated in service bulletin recommendations, production line modifications, and design manual updates. An overview of traditional Boeing fleet support activities and the anticipated benefits for future generations of commercial airplanes based on the continuous design improvement process are presented.

  1. Structural integrity of future aging airplanes

    NASA Technical Reports Server (NTRS)

    Mcguire, Jack F.; Goranson, Ulf G.

    1992-01-01

    A multitude of design considerations is involved in ensuring the structural integrity of Boeing jet transports that have common design concepts validated by extensive analyses, tests, and three decades of service. As airplanes approach their design service objectives, the incidences of fatigue and corrosion may become widespread. Continuing airworthiness of the aging jet fleet requires diligent performance from the manufacturer, the airlines, and airworthiness authorities. Aging fleet support includes timely development of supplemental structural inspection documents applicable to selected older airplanes, teardown inspections of high-time airframes retired from service, fatigue testing of older airframes, and structural surveys of more than 130 airplanes operated throughout the world. Lessons learned from these activities are incorporated in service bulletin recommendations, production line modifications, and design manual updates. An overview of traditional Boeing fleet support activities and the anticipated benefits for future generations of commercial airplanes based on the continuous design improvement process are presented.

  2. Predicted and experimental structures of integrins and beta-propellers.

    PubMed

    Springer, Timothy A

    2002-12-01

    Integrins and other cell surface receptors have been fertile grounds for structure prediction experiments. Recently determined structures show remarkable successes, especially with beta-propeller domain predictions, and also reveal how ligand binding by integrins is conformationally regulated.

  3. Evaluation, analysis and prediction of geologic structures

    NASA Astrophysics Data System (ADS)

    Woodward, Nicholas B.

    2012-08-01

    Balanced cross-sections claim to be better because they apply a rigorous set of rules to develop the conceptual model of the structures present in an area. Balanced cross-sections can be further improved and become more useful to understanding real physical problems by collection of additional data such as seismic reflection surveys, collection of additional stratigraphic data, or collection of rock fabric information. The additional information validates the initial model and provides details on deformation conditions and on local rock responses to the deformation. Although individual cross-sections are two dimensional, the objective of evaluation and analysis of deformed regions should be three dimensional whenever possible to recognize the challenges of the real world. Subsurface system analysis derived from the hydrologic community emphasizes conceptual model development through model verification, validation, uncertainty quantification, benchmarking and meta-analysis. Their approach includes many steps informally used by the structural geology community but in a much more explicit way. Newer geological applications of structural geology would benefit from this more rigorous approach for designing and doing performance predictions as technological needs become more socially sensitive such as for carbon storage sites, new areas of energy exploration in higher population density areas, or for nuclear waste storage facilities.

  4. Integrated design of structures, controls, and materials

    NASA Technical Reports Server (NTRS)

    Blankenship, G. L.

    1994-01-01

    In this talk we shall discuss algorithms and CAD tools for the design and analysis of structures for high performance applications using advanced composite materials. An extensive mathematical theory for optimal structural (e.g., shape) design was developed over the past thirty years. Aspects of this theory have been used in the design of components for hypersonic vehicles and thermal diffusion systems based on homogeneous materials. Enhancement of the design methods to include optimization of the microstructure of the component is a significant innovation which can lead to major enhancements in component performance. Our work is focused on the adaptation of existing theories of optimal structural design (e.g., optimal shape design) to treat the design of structures using advanced composite materials (e.g., fiber reinforced, resin matrix materials). In this talk we shall discuss models and algorithms for the design of simple structures from composite materials, focussing on a problem in thermal management. We shall also discuss methods for the integration of active structural controls into the design process.

  5. Self assembled structures for 3D integration

    NASA Astrophysics Data System (ADS)

    Rao, Madhav

    Three dimensional (3D) micro-scale structures attached to a silicon substrate have various applications in microelectronics. However, formation of 3D structures using conventional micro-fabrication techniques are not efficient and require precise control of processing parameters. Self assembly is a method for creating 3D structures that takes advantage of surface area minimization phenomena. Solder based self assembly (SBSA), the subject of this dissertation, uses solder as a facilitator in the formation of 3D structures from 2D patterns. Etching a sacrificial layer underneath a portion of the 2D pattern allows the solder reflow step to pull those areas out of the substrate plane resulting in a folded 3D structure. Initial studies using the SBSA method demonstrated low yields in the formation of five different polyhedra. The failures in folding were primarily attributed to nonuniform solder deposition on the underlying metal pads. The dip soldering method was analyzed and subsequently refined. A modified dip soldering process provided improved yield among the polyhedra. Solder bridging referred as joining of solder deposited on different metal patterns in an entity influenced the folding mechanism. In general, design parameters such as small gap-spacings and thick metal pads were found to favor solder bridging for all patterns studied. Two types of soldering: face and edge soldering were analyzed. Face soldering refers to the application of solder on the entire metal face. Edge soldering indicates application of solder only on the edges of the metal face. Mechanical grinding showed that face soldered SBSA structures were void free and robust in nature. In addition, the face soldered 3D structures provide a consistent heat resistant solder standoff height that serve as attachments in the integration of dissimilar electronic technologies. Face soldered 3D structures were developed on the underlying conducting channel to determine the thermo-electric reliability of

  6. Atomic vapor spectroscopy in integrated photonic structures

    SciTech Connect

    Ritter, Ralf; Kübler, Harald; Pfau, Tilman; Löw, Robert; Gruhler, Nico; Pernice, Wolfram

    2015-07-27

    We investigate an integrated optical chip immersed in atomic vapor providing several waveguide geometries for spectroscopy applications. The narrow-band transmission through a silicon nitride waveguide and interferometer is altered when the guided light is coupled to a vapor of rubidium atoms via the evanescent tail of the waveguide mode. We use grating couplers to couple between the waveguide mode and the radiating wave, which allow for addressing arbitrary coupling positions on the chip surface. The evanescent atom-light interaction can be numerically simulated and shows excellent agreement with our experimental data. This work demonstrates a next step towards miniaturization and integration of alkali atom spectroscopy and provides a platform for further fundamental studies of complex waveguide structures.

  7. Departure Queue Prediction for Strategic and Tactical Surface Scheduler Integration

    NASA Technical Reports Server (NTRS)

    Zelinski, Shannon; Windhorst, Robert

    2016-01-01

    A departure metering concept to be demonstrated at Charlotte Douglas International Airport (CLT) will integrate strategic and tactical surface scheduling components to enable the respective collaborative decision making and improved efficiency benefits these two methods of scheduling provide. This study analyzes the effect of tactical scheduling on strategic scheduler predictability. Strategic queue predictions and target gate pushback times to achieve a desired queue length are compared between fast time simulations of CLT surface operations with and without tactical scheduling. The use of variable departure rates as a strategic scheduler input was shown to substantially improve queue predictions over static departure rates. With target queue length calibration, the strategic scheduler can be tuned to produce average delays within one minute of the tactical scheduler. However, root mean square differences between strategic and tactical delays were between 12 and 15 minutes due to the different methods the strategic and tactical schedulers use to predict takeoff times and generate gate pushback clearances. This demonstrates how difficult it is for the strategic scheduler to predict tactical scheduler assigned gate delays on an individual flight basis as the tactical scheduler adjusts departure sequence to accommodate arrival interactions. Strategic/tactical scheduler compatibility may be improved by providing more arrival information to the strategic scheduler and stabilizing tactical scheduler changes to runway sequence in response to arrivals.

  8. Integrated Aeromechanics with Three-Dimensional Solid-Multibody Structures

    NASA Technical Reports Server (NTRS)

    Datta, Anubhav; Johnson, Wayne

    2014-01-01

    A full three-dimensional finite element-multibody structural dynamic solver is coupled to a three-dimensional Reynolds-averaged Navier-Stokes solver for the prediction of integrated aeromechanical stresses and strains on a rotor blade in forward flight. The objective is to lay the foundations of all major pieces of an integrated three-dimensional rotor dynamic analysis - from model construction to aeromechanical solution to stress/strain calculation. The primary focus is on the aeromechanical solution. Two types of three-dimensional CFD/CSD interfaces are constructed for this purpose with an emphasis on resolving errors from geometry mis-match so that initial-stage approximate structural geometries can also be effectively analyzed. A three-dimensional structural model is constructed as an approximation to a UH-60A-like fully articulated rotor. The aerodynamic model is identical to the UH-60A rotor. For preliminary validation measurements from a UH-60A high speed flight is used where CFD coupling is essential to capture the advancing side tip transonic effects. The key conclusion is that an integrated aeromechanical analysis is indeed possible with three-dimensional structural dynamics but requires a careful description of its geometry and discretization of its parts.

  9. Blind protein structure prediction using accelerated free-energy simulations

    PubMed Central

    Perez, Alberto; Morrone, Joseph A.; Brini, Emiliano; MacCallum, Justin L.; Dill, Ken A.

    2016-01-01

    We report a key proof of principle of a new acceleration method [Modeling Employing Limited Data (MELD)] for predicting protein structures by molecular dynamics simulation. It shows that such Boltzmann-satisfying techniques are now sufficiently fast and accurate to predict native protein structures in a limited test within the Critical Assessment of Structure Prediction (CASP) community-wide blind competition. PMID:27847872

  10. Disturbance metrics predict a wetland Vegetation Index of Biotic Integrity

    USGS Publications Warehouse

    Stapanian, Martin A.; Mack, John; Adams, Jean V.; Gara, Brian; Micacchion, Mick

    2013-01-01

    Indices of biological integrity of wetlands based on vascular plants (VIBIs) have been developed in many areas in the USA. Knowledge of the best predictors of VIBIs would enable management agencies to make better decisions regarding mitigation site selection and performance monitoring criteria. We use a novel statistical technique to develop predictive models for an established index of wetland vegetation integrity (Ohio VIBI), using as independent variables 20 indices and metrics of habitat quality, wetland disturbance, and buffer area land use from 149 wetlands in Ohio, USA. For emergent and forest wetlands, predictive models explained 61% and 54% of the variability, respectively, in Ohio VIBI scores. In both cases the most important predictor of Ohio VIBI score was a metric that assessed habitat alteration and development in the wetland. Of secondary importance as a predictor was a metric that assessed microtopography, interspersion, and quality of vegetation communities in the wetland. Metrics and indices assessing disturbance and land use of the buffer area were generally poor predictors of Ohio VIBI scores. Our results suggest that vegetation integrity of emergent and forest wetlands could be most directly enhanced by minimizing substrate and habitat disturbance within the wetland. Such efforts could include reducing or eliminating any practices that disturb the soil profile, such as nutrient enrichment from adjacent farm land, mowing, grazing, or cutting or removing woody plants.

  11. Optimizing nondecomposable loss functions in structured prediction.

    PubMed

    Ranjbar, Mani; Lan, Tian; Wang, Yang; Robinovitch, Steven N; Li, Ze-Nian; Mori, Greg

    2013-04-01

    We develop an algorithm for structured prediction with nondecomposable performance measures. The algorithm learns parameters of Markov Random Fields (MRFs) and can be applied to multivariate performance measures. Examples include performance measures such as Fβ score (natural language processing), intersection over union (object category segmentation), Precision/Recall at k (search engines), and ROC area (binary classifiers). We attack this optimization problem by approximating the loss function with a piecewise linear function. The loss augmented inference forms a Quadratic Program (QP), which we solve using LP relaxation. We apply this approach to two tasks: object class-specific segmentation and human action retrieval from videos. We show significant improvement over baseline approaches that either use simple loss functions or simple scoring functions on the PASCAL VOC and H3D Segmentation datasets, and a nursing home action recognition dataset.

  12. Boundary-Layer Receptivity and Integrated Transition Prediction

    NASA Technical Reports Server (NTRS)

    Chang, Chau-Lyan; Choudhari, Meelan

    2005-01-01

    The adjoint parabold stability equations (PSE) formulation is used to calculate the boundary layer receptivity to localized surface roughness and suction for compressible boundary layers. Receptivity efficiency functions predicted by the adjoint PSE approach agree well with results based on other nonparallel methods including linearized Navier-Stokes equations for both Tollmien-Schlichting waves and crossflow instability in swept wing boundary layers. The receptivity efficiency function can be regarded as the Green's function to the disturbance amplitude evolution in a nonparallel (growing) boundary layer. Given the Fourier transformed geometry factor distribution along the chordwise direction, the linear disturbance amplitude evolution for a finite size, distributed nonuniformity can be computed by evaluating the integral effects of both disturbance generation and linear amplification. The synergistic approach via the linear adjoint PSE for receptivity and nonlinear PSE for disturbance evolution downstream of the leading edge forms the basis for an integrated transition prediction tool. Eventually, such physics-based, high fidelity prediction methods could simulate the transition process from the disturbance generation through the nonlinear breakdown in a holistic manner.

  13. Predicting missing links via structural similarity

    NASA Astrophysics Data System (ADS)

    Lyu, Guo-Dong; Fan, Chang-Jun; Yu, Lian-Fei; Xiu, Bao-Xin; Zhang, Wei-Ming

    2015-04-01

    Predicting missing links in networks plays a significant role in modern science. On the basis of structural similarity, our paper proposes a new node-similarity-based measure called biased resource allocation (BRA), which is motivated by the resource allocation (RA) measure. Comparisons between BRA and nine well-known node-similarity-based measures on five real networks indicate that BRA performs no worse than RA, which was the best node-similarity-based index in previous researches. Afterwards, based on localPath (LP) and Katz measure, we propose another two improved measures, named Im-LocalPath and Im-Katz respectively. Numerical results show that the prediction accuracy of both Im-LP and Im-Katz measure improve compared with the original LP and Katz measure. Finally, a new path-similarity-based measure and its improved measure, called LYU and Im-LYU measure, are proposed and especially, Im-LYU measure is shown to perform more remarkably than other mentioned measures.

  14. Challenges for the aircraft structural integrity program

    NASA Technical Reports Server (NTRS)

    Lincoln, John W.

    1994-01-01

    Thirty-six years ago the United States Air Force established the USAF Aircraft Structural Integrity Program (ASIP) because flight safety had been degraded by fatigue failures of operational aircraft. This initial program evolved, but has been stable since the issuance of MIL-STD-1530A in 1975. Today, the program faces new challenges because of a need to maintain aircraft longer in an environment of reduced funding levels. Also, there is increased pressure to reduce cost of the acquisition of new aircraft. It is the purpose of this paper to discuss the challenges for the ASIP and identify the changes in the program that will meet these challenges in the future.

  15. Integrating Multiple Evidence Sources to Predict Adverse Drug Reactions Based on a Systems Pharmacology Model

    PubMed Central

    Cao, D-S; Xiao, N; Li, Y-J; Zeng, W-B; Liang, Y-Z; Lu, A-P; Xu, Q-S; Chen, AF

    2015-01-01

    Identifying potential adverse drug reactions (ADRs) is critically important for drug discovery and public health. Here we developed a multiple evidence fusion (MEF) method for the large-scale prediction of drug ADRs that can handle both approved drugs and novel molecules. MEF is based on the similarity reference by collaborative filtering, and integrates multiple similarity measures from various data types, taking advantage of the complementarity in the data. We used MEF to integrate drug-related and ADR-related data from multiple levels, including the network structural data formed by known drug–ADR relationships for predicting likely unknown ADRs. On cross-validation, it obtains high sensitivity and specificity, substantially outperforming existing methods that utilize single or a few data types. We validated our prediction by their overlap with drug–ADR associations that are known in databases. The proposed computational method could be used for complementary hypothesis generation and rapid analysis of potential drug–ADR interactions. PMID:26451329

  16. Dynamic kirigami structures for integrated solar tracking

    PubMed Central

    Lamoureux, Aaron; Lee, Kyusang; Shlian, Matthew; Forrest, Stephen R.; Shtein, Max

    2015-01-01

    Optical tracking is often combined with conventional flat panel solar cells to maximize electrical power generation over the course of a day. However, conventional trackers are complex and often require costly and cumbersome structural components to support system weight. Here we use kirigami (the art of paper cutting) to realize novel solar cells where tracking is integral to the structure at the substrate level. Specifically, an elegant cut pattern is made in thin-film gallium arsenide solar cells, which are then stretched to produce an array of tilted surface elements which can be controlled to within ±1°. We analyze the combined optical and mechanical properties of the tracking system, and demonstrate a mechanically robust system with optical tracking efficiencies matching conventional trackers. This design suggests a pathway towards enabling new applications for solar tracking, as well as inspiring a broader range of optoelectronic and mechanical devices. PMID:26348820

  17. Dynamic kirigami structures for integrated solar tracking

    NASA Astrophysics Data System (ADS)

    Lamoureux, Aaron; Lee, Kyusang; Shlian, Matthew; Forrest, Stephen R.; Shtein, Max

    2015-09-01

    Optical tracking is often combined with conventional flat panel solar cells to maximize electrical power generation over the course of a day. However, conventional trackers are complex and often require costly and cumbersome structural components to support system weight. Here we use kirigami (the art of paper cutting) to realize novel solar cells where tracking is integral to the structure at the substrate level. Specifically, an elegant cut pattern is made in thin-film gallium arsenide solar cells, which are then stretched to produce an array of tilted surface elements which can be controlled to within +/-1°. We analyze the combined optical and mechanical properties of the tracking system, and demonstrate a mechanically robust system with optical tracking efficiencies matching conventional trackers. This design suggests a pathway towards enabling new applications for solar tracking, as well as inspiring a broader range of optoelectronic and mechanical devices.

  18. Dynamic kirigami structures for integrated solar tracking.

    PubMed

    Lamoureux, Aaron; Lee, Kyusang; Shlian, Matthew; Forrest, Stephen R; Shtein, Max

    2015-09-08

    Optical tracking is often combined with conventional flat panel solar cells to maximize electrical power generation over the course of a day. However, conventional trackers are complex and often require costly and cumbersome structural components to support system weight. Here we use kirigami (the art of paper cutting) to realize novel solar cells where tracking is integral to the structure at the substrate level. Specifically, an elegant cut pattern is made in thin-film gallium arsenide solar cells, which are then stretched to produce an array of tilted surface elements which can be controlled to within ±1°. We analyze the combined optical and mechanical properties of the tracking system, and demonstrate a mechanically robust system with optical tracking efficiencies matching conventional trackers. This design suggests a pathway towards enabling new applications for solar tracking, as well as inspiring a broader range of optoelectronic and mechanical devices.

  19. Crystal structure prediction of rigid molecules.

    PubMed

    Elking, Dennis M; Fusti-Molnar, Laszlo; Nichols, Anthony

    2016-08-01

    A non-polarizable force field based on atomic multipoles fit to reproduce experimental crystal properties and ab initio gas-phase dimers is described. The Ewald method is used to calculate both long-range electrostatic and 1/r(6) dispersion energies of crystals. The dispersion energy of a crystal calculated by a cutoff method is shown to converge slowly to the exact Ewald result. A method for constraining space-group symmetry during unit-cell optimization is derived. Results for locally optimizing 4427 unit cells including volume, cell parameters, unit-cell r.m.s.d. and CPU timings are given for both flexible and rigid molecule optimization. An algorithm for randomly generating rigid molecule crystals is described. Using the correct experimentally determined space group, the average and maximum number of random crystals needed to find the correct experimental structure is given for 2440 rigid single component crystals. The force field energy rank of the correct experimental structure is presented for the same set of 2440 rigid single component crystals assuming the correct space group. A complete crystal prediction is performed for two rigid molecules by searching over the 32 most probable space groups.

  20. Structure prediction of magnetosome-associated proteins

    PubMed Central

    Nudelman, Hila; Zarivach, Raz

    2014-01-01

    Magnetotactic bacteria (MTB) are Gram-negative bacteria that can navigate along geomagnetic fields. This ability is a result of a unique intracellular organelle, the magnetosome. These organelles are composed of membrane-enclosed magnetite (Fe3O4) or greigite (Fe3S4) crystals ordered into chains along the cell. Magnetosome formation, assembly, and magnetic nano-crystal biomineralization are controlled by magnetosome-associated proteins (MAPs). Most MAP-encoding genes are located in a conserved genomic region – the magnetosome island (MAI). The MAI appears to be conserved in all MTB that were analyzed so far, although the MAI size and organization differs between species. It was shown that MAI deletion leads to a non-magnetic phenotype, further highlighting its important role in magnetosome formation. Today, about 28 proteins are known to be involved in magnetosome formation, but the structures and functions of most MAPs are unknown. To reveal the structure–function relationship of MAPs we used bioinformatics tools in order to build homology models as a way to understand their possible role in magnetosome formation. Here we present a predicted 3D structural models’ overview for all known Magnetospirillum gryphiswaldense strain MSR-1 MAPs. PMID:24523717

  1. Visual-motor integration skills: accuracy of predicting reading.

    PubMed

    Santi, Kristi L; Francis, David J; Currie, Debra; Wang, Qianqian

    2015-02-01

    This article investigated the contribution of visual-motor integration (VMI) to reading ability when known predictors of later reading outcomes were also present in the data analysis. Participants included 778 first and second grade students from a large diverse urban district in Texas. The data were analyzed using multiple regression models with a forced entry of predictors for each regression model, and each model was run separately for each outcome. The results indicate that VMI drops out of the prediction models once more reading- and language-specific skills are introduced. Although VMI skills make a statistically significant contribution in some aspects of the regression model, the reduction in contribution reduces the predictive validity of VMI skills. Therefore, a VMI skill measure will not sufficiently determine if a child has a reading disability.

  2. Reactor pressure vessel structural integrity research

    SciTech Connect

    Pennell, W.E.; Corwin, W.R.

    1995-04-01

    Development continues on the technology used to assess the safety of irradiation-embrittled nuclear reactor pressure vessels (RPVs) containing flaws. Fracture mechanics tests on RPV steel, coupled with detailed elastic-plastic finite-element analyses of the crack-tip stress fields, have shown that (1) constraint relaxation at the crack tip of shallows surface flaws results in increased data scatter but no increase in the lower-bound fracture toughness, (2) the nil ductility temperature (NDT) performs better than the reference temperature for nil ductility transition (RT{sub NDT}) as a normalizing parameter for shallow-flaw fracture toughness data, (3) biaxial loading can reduce the shallow-flaw fracture toughness, (4) stress-based dual-parameter fracture toughness correlations cannot predict the effect of biaxial loading on a shallow-flaw fracture toughness because in-plane stresses at the crack tip are not influenced by biaxial loading, and (5) an implicit strain-based dual-parameter fracture toughness correlation can predict the effect of biaxial loading on shallow-flaw fracture toughness. Experimental irradiation investigations have shown that (1) the irradiation-induced shift in Charpy V-notch vs temperature behavior may not be adequate to conservatively assess fracture toughness shifts due to embrittlement, and (2) the wide global variations of initial chemistry and fracture properties of a nominally uniform material within a pressure vessel may confound accurate integrity assessments that require baseline properties.

  3. Structural integrity of engineering composite materials: a cracking good yarn.

    PubMed

    Beaumont, Peter W R; Soutis, Costas

    2016-07-13

    Predicting precisely where a crack will develop in a material under stress and exactly when in time catastrophic fracture of the component will occur is one the oldest unsolved mysteries in the design and building of large-scale engineering structures. Where human life depends upon engineering ingenuity, the burden of testing to prove a 'fracture safe design' is immense. Fitness considerations for long-life implementation of large composite structures include understanding phenomena such as impact, fatigue, creep and stress corrosion cracking that affect reliability, life expectancy and durability of structure. Structural integrity analysis treats the design, the materials used, and figures out how best components and parts can be joined, and takes service duty into account. However, there are conflicting aims in the complete design process of designing simultaneously for high efficiency and safety assurance throughout an economically viable lifetime with an acceptable level of risk. This article is part of the themed issue 'Multiscale modelling of the structural integrity of composite materials'. © 2016 The Author(s).

  4. Structural integrity of engineering composite materials: a cracking good yarn

    PubMed Central

    Beaumont, Peter W. R.

    2016-01-01

    Predicting precisely where a crack will develop in a material under stress and exactly when in time catastrophic fracture of the component will occur is one the oldest unsolved mysteries in the design and building of large-scale engineering structures. Where human life depends upon engineering ingenuity, the burden of testing to prove a ‘fracture safe design’ is immense. Fitness considerations for long-life implementation of large composite structures include understanding phenomena such as impact, fatigue, creep and stress corrosion cracking that affect reliability, life expectancy and durability of structure. Structural integrity analysis treats the design, the materials used, and figures out how best components and parts can be joined, and takes service duty into account. However, there are conflicting aims in the complete design process of designing simultaneously for high efficiency and safety assurance throughout an economically viable lifetime with an acceptable level of risk. This article is part of the themed issue ‘Multiscale modelling of the structural integrity of composite materials’. PMID:27242293

  5. Neighborhood Integration and Connectivity Predict Cognitive Performance and Decline

    PubMed Central

    Ferdous, Farhana; Diaz Moore, Keith; Burns, Jeffrey M.

    2015-01-01

    Objective: Neighborhood characteristics may be important for promoting walking, but little research has focused on older adults, especially those with cognitive impairment. We evaluated the role of neighborhood characteristics on cognitive function and decline over a 2-year period adjusting for measures of walking. Method: In a study of 64 older adults with and without mild Alzheimer’s disease (AD), we evaluated neighborhood integration and connectivity using geographical information systems data and space syntax analysis. In multiple regression analyses, we used these characteristics to predict 2-year declines in factor analytically derived cognitive scores (attention, verbal memory, mental status) adjusting for age, sex, education, and self-reported walking. Results: Neighborhood integration and connectivity predicted cognitive performance at baseline, and changes in cognitive performance over 2 years. The relationships between neighborhood characteristics and cognitive performance were not fully explained by self-reported walking. Discussion: Clearer definitions of specific neighborhood characteristics associated with walkability are needed to better understand the mechanisms by which neighborhoods may impact cognitive outcomes. These results have implications for measuring neighborhood characteristics, design and maintenance of living spaces, and interventions to increase walking among older adults. We offer suggestions for future research measuring neighborhood characteristics and cognitive function. PMID:26504889

  6. Integrated uncertainty assessment of flow predictions in a Swiss catchment

    NASA Astrophysics Data System (ADS)

    Honti, M.; Stamm, C.; Reichert, P.

    2012-04-01

    Despite the vivid scientific debate on the suitability of RCM predictions for hydrological forecasting, impact studies relying on climatic input data and hydrological models are still the exclusive methods to provide some insight into the expected evolution of streams in the close future. While the climatic uncertainty is usually considered being dominant in such studies, more and more sophisticated uncertainty assessment methods reveal that the uncertainty of our hydrological models has been systematically underestimated by inappropriate assessment methods and that our predictive power for the present conditions can be as weak as it was considered for the future. The integrated treatment of various uncertainty sources allows us to quantify the overall predictive uncertainty for such studies and to decide if the anticipated impacts are relevant compared to the existing uncertainty. The Mönchaltorfer Aa catchment (46 km2) in Switzerland was modelled as a case study. A conceptual rainfall-runoff model was calibrated on measured discharge data with Bayesian parameter inference assuming a statistical error process that can account for various uncertainty sources. Climatic input data were produced by statistical downscaling from the outputs of 10 ENSEMBLES GCM-RCM model chains for the A1B emission scenario with the time horizon of 2050. Hourly rainfall data were produced with the Neyman-Scott rectangular pulses model (Rodriguez-Iturbe et al. 1987) while other weather parameters were generated on daily scale with the UKCP09 weather generator (Murphy et al. 2009). Expected landuse changes were assessed by creating divergent regional storylines from countrywide socio-economic scenarios. Despite the good performance of the hydrological model (Nash-Sutcliffe =0.8), its total predictive uncertainty was significant even for the present conditions. Due to the significant contribution of input uncertainty, individual flood peaks could be predicted with poor confidence. However

  7. Integrated tools for biomolecular sequence-based function prediction as exemplified by the ANNOTATOR software environment.

    PubMed

    Schneider, Georg; Wildpaner, Michael; Sirota, Fernanda L; Maurer-Stroh, Sebastian; Eisenhaber, Birgit; Eisenhaber, Frank

    2010-01-01

    Given the amount of sequence data available today, in silico function prediction, which often includes detecting distant evolutionary relationships, requires sophisticated bioinformatic workflows. The algorithms behind these workflows exhibit complex data structures; they need the ability to spawn subtasks and tend to demand large amounts of resources. Performing sequence analytic tasks by manually invoking individual function prediction algorithms having to transform between differing input and output formats has become increasingly obsolete. After a period of linking individual predictors using ad hoc scripts, a number of integrated platforms are finally emerging. We present the ANNOTATOR software environment as an advanced example of such a platform.

  8. An integrated uncertainty and ensemble-based data assimilation approach for improved operational streamflow predictions

    NASA Astrophysics Data System (ADS)

    He, M.; Hogue, T. S.; Margulis, S. A.; Franz, K. J.

    2012-03-01

    The current study proposes an integrated uncertainty and ensemble-based data assimilation framework (ICEA) and evaluates its viability in providing operational streamflow predictions via assimilating snow water equivalent (SWE) data. This step-wise framework applies a parameter uncertainty analysis algorithm (ISURF) to identify the uncertainty structure of sensitive model parameters, which is subsequently formulated into an Ensemble Kalman Filter (EnKF) to generate updated snow states for streamflow prediction. The framework is coupled to the US National Weather Service (NWS) snow and rainfall-runoff models. Its applicability is demonstrated for an operational basin of a western River Forecast Center (RFC) of the NWS. Performance of the framework is evaluated against existing operational baseline (RFC predictions), the stand-alone ISURF and the stand-alone EnKF. Results indicate that the ensemble-mean prediction of ICEA considerably outperforms predictions from the other three scenarios investigated, particularly in the context of predicting high flows (top 5th percentile). The ICEA streamflow ensemble predictions capture the variability of the observed streamflow well, however the ensemble is not wide enough to consistently contain the range of streamflow observations in the study basin. Our findings indicate that the ICEA has the potential to supplement the current operational (deterministic) forecasting method in terms of providing improved single-valued (e.g., ensemble mean) streamflow predictions as well as meaningful ensemble predictions.

  9. An integrated uncertainty and ensemble-based data assimilation approach for improved operational streamflow predictions

    NASA Astrophysics Data System (ADS)

    He, M.; Hogue, T. S.; Margulis, S. A.; Franz, K. J.

    2011-08-01

    The current study proposes an integrated uncertainty and ensemble-based data assimilation framework (ICEA) and evaluates its viability in providing operational streamflow predictions via assimilating snow water equivalent (SWE) data. This step-wise framework applies a parameter uncertainty analysis algorithm (ISURF) to identify the uncertainty structure of sensitive model parameters, which is subsequently formulated into an Ensemble Kalman Filter (EnKF) to generate updated snow states for streamflow prediction. The framework is coupled to the US National Weather Service (NWS) snow and rainfall-runoff models. Its applicability is demonstrated for an operational basin of a western River Forecast Center (RFC) of the NWS. Performance of the framework is evaluated against existing operational baseline (RFC predictions), the stand-alone ISURF, and the stand-alone EnKF. Results indicate that the ensemble-mean prediction of ICEA considerably outperforms predictions from the other three scenarios investigated, particularly in the context of predicting high flows (top 5th percentile). The ICEA streamflow ensemble predictions capture the variability of the observed streamflow well, however the ensemble is not wide enough to consistently contain the range of streamflow observations in the study basin. Our findings indicate that the ICEA has the potential to supplement the current operational (deterministic) forecasting method in terms of providing improved single-valued (e.g., ensemble mean) streamflow predictions as well as meaningful ensemble predictions.

  10. High Cycle Fatigue Prediction for Mistuned Bladed Disks with Fully Coupled Fluid-Structural Interaction

    DTIC Science & Technology

    2006-06-01

    vibration and flutter boundary of 2D NACA 64A010 transonic airfoil, 3D plate wing structural response. The predicted results agree well with benchmark...CFD code coupled with a structural integrator based on the convolution integral to obtain the flutter boundary for a NACA 64A010 airfoil[10]. Alonso and...validation case of the scheme for moving grid system, the forced pitching NACA 64A010 airfoil is calculated. For this transonic airfoil, the Reynolds

  11. Enhanced Composites Integrity Through Structural Health Monitoring

    NASA Astrophysics Data System (ADS)

    Giurgiutiu, Victor; Soutis, Constantinos

    2012-10-01

    This paper discusses the topic of how the integrity of safety-critical structural composites can be enhanced by the use of structural health monitoring (SHM) techniques. The paper starts with a presentation of how the certification of flight-critical composite structures can be achieved within the framework of civil aviation safety authority requirements. Typical composites damage mechanisms, which make this process substantially different from that for metallic materials are discussed. The opportunities presented by the use of SHM techniques in future civil aircraft developments are explained. The paper then focuses on active SHM with piezoelectric wafer active sensors (PWAS). After reviewing the PWAS-based SHM options, the paper follows with a discussion of the specifics of guided wave propagation in composites and PWAS-tuning effects. The paper presents a number of experimental results for damage detection in simple flat unidirectional and quasi-isotropic composite specimens. Calibrated through holes of increasing diameter and impact damage of various energies and velocities are considered. The paper ends with conclusions and suggestions for further work.

  12. Integrated Force Method for Indeterminate Structures

    NASA Technical Reports Server (NTRS)

    Hopkins, Dale A.; Halford, Gary R.; Patnaik, Surya N.

    2008-01-01

    Two methods of solving indeterminate structural-mechanics problems have been developed as products of research on the theory of strain compatibility. In these methods, stresses are considered to be the primary unknowns (in contrast to strains and displacements being considered as the primary unknowns in some prior methods). One of these methods, denoted the integrated force method (IFM), makes it possible to compute stresses, strains, and displacements with high fidelity by use of modest finite-element models that entail relatively small amounts of computation. The other method, denoted the completed Beltrami Mitchell formulation (CBMF), enables direct determination of stresses in an elastic continuum with general boundary conditions, without the need to first calculate displacements as in traditional methods. The equilibrium equation, the compatibility condition, and the material law are the three fundamental concepts of the theory of structures. For almost 150 years, it has been commonly supposed that the theory is complete. However, until now, the understanding of the compatibility condition remained incomplete, and the compatibility condition was confused with the continuity condition. Furthermore, the compatibility condition as applied to structures in its previous incomplete form was inconsistent with the strain formulation in elasticity.

  13. Structure of nonevaporating sprays - Measurements and predictions

    NASA Technical Reports Server (NTRS)

    Solomon, A. S. P.; Shuen, J.-S.; Zhang, Q.-F.; Faeth, G. M.

    1984-01-01

    Structure measurements were completed within the dilute portion of axisymmetric nonevaporating sprays (SMD of 30 and 87 microns) injected into a still air environment, including: mean and fluctuating gas velocities and Reynolds stress using laser-Doppler anemometry; mean liquid fluxes using isokinetic sampling; drop sizes using slide impaction; and drop sizes and velocities using multiflash photography. The new measurements were used to evaluate three representative models of sprays: (1) a locally homogeneous flow (LHF) model, where slip between the phases was neglected; (2) a deterministic separated flow (DSF) model, where slip was considered but effects of drop interaction with turbulent fluctuations were ignored; and (3) a stochastic separated flow (SSF) model, where effects of both interphase slip and turbulent fluctuations were considered using random sampling for turbulence properties in conjunction with random-walk computations for drop motion. The LHF and DSF models were unsatisfactory for present test conditions-both underestimating flow widths and the rate of spread of drops. In contrast, the SSF model provided reasonably accurate predictions, including effects of enhanced spreading rates of sprays due to drop dispersion by turbulence, with all empirical parameters fixed from earlier work.

  14. Integrative structural modeling with small angle X-ray scattering profiles

    PubMed Central

    2012-01-01

    Recent technological advances enabled high-throughput collection of Small Angle X-ray Scattering (SAXS) profiles of biological macromolecules. Thus, computational methods for integrating SAXS profiles into structural modeling are needed more than ever. Here, we review specifically the use of SAXS profiles for the structural modeling of proteins, nucleic acids, and their complexes. First, the approaches for computing theoretical SAXS profiles from structures are presented. Second, computational methods for predicting protein structures, dynamics of proteins in solution, and assembly structures are covered. Third, we discuss the use of SAXS profiles in integrative structure modeling approaches that depend simultaneously on several data types. PMID:22800408

  15. Pattern uniformity control in integrated structures

    NASA Astrophysics Data System (ADS)

    Kobayashi, Shinji; Okada, Soichiro; Shimura, Satoru; Nafus, Kathleen; Fonseca, Carlos; Biesemans, Serge; Enomoto, Masashi

    2017-03-01

    In our previous paper dealing with multi-patterning, we proposed a new indicator to quantify the quality of final wafer pattern transfer, called interactive pattern fidelity error (IPFE). It detects patterning failures resulting from any source of variation in creating integrated patterns. IPFE is a function of overlay and edge placement error (EPE) of all layers comprising the final pattern (i.e. lower and upper layers). In this paper, we extend the use cases with Via in additional to the bridge case (Block on Spacer). We propose an IPFE budget and CD budget using simple geometric and statistical models with analysis of a variance (ANOVA). In addition, we validate the model with experimental data. From the experimental results, improvements in overlay, local-CDU (LCDU) of contact hole (CH) or pillar patterns (especially, stochastic pattern noise (SPN)) and pitch walking are all critical to meet budget requirements. We also provide a special note about the importance of the line length used in analyzing LWR. We find that IPFE and CD budget requirements are consistent to the table of the ITRS's technical requirement. Therefore the IPFE concept can be adopted for a variety of integrated structures comprising digital logic circuits. Finally, we suggest how to use IPFE for yield management and optimization requirements for each process.

  16. Structural integrity of nuclear reactor pressure vessels

    NASA Astrophysics Data System (ADS)

    Knott, John F.

    2013-09-01

    The paper starts from concerns expressed by Sir Alan Cottrell, in the early 1970s, related to the safety of the pressurized water reactor (PWR) proposed at that time for the next phase of electrical power generation. It proceeds to describe the design and operation of nuclear generation plant and gives details of the manufacture of PWR reactor pressure vessels (RPVs). Attention is paid to stress-relief cracking and under-clad cracking, experienced with early RPVs, explaining the mechanisms for these forms of cracking and the means taken to avoid them. Particular note is made of the contribution of non-destructive inspection to structural integrity. Factors affecting brittle fracture in RPV steels are described: in particular, effects of neutron irradiation. The use of fracture mechanics to assess defect tolerance is explained, together with the failure assessment diagram embodied in the R6 procedure. There is discussion of the Master Curve and how it incorporates effects of irradiation on fracture toughness. Dangers associated with extrapolation of data to low probabilities are illustrated. The treatment of fatigue-crack growth is described, in the context of transients that may be experienced in the operation of PWR plant. Detailed attention is paid to the thermal shock associated with a large loss-of-coolant accident. The final section reviews the arguments advanced to justify 'Incredibility of Failure' and how these are incorporated in assessments of the integrity of existing plant and proposed 'new build' PWR pressure vessels.

  17. Integrated structural repair of a producing FPSO

    SciTech Connect

    Johnson, P.R.; Smith, T.A.

    1997-07-01

    The state of the art in FPSO design is advancing rapidly. The long-term reliability of FPSO systems has improved as maintenance issues, have received greater emphasis in both new-builds and conversions. Despite this new emphasis, problems will still arise and repairs will still be required. Ultimately, the ability of any FPSO to stay on location and on production will depend on the scope of repairs which can be economically performed in-situ. In 1994 and 1995, Marathon Petroleum Indonesia Limited (MPIL) performed an in-situ repair on the FPSO Kakap Natuna. The scope and complexity of this work suggests there are few, if any, limits on in-situ structural repairs which can be successfully performed on a producing FPSO. The use of an integrated execution strategy for the repairs greatly reduced their cost.

  18. Information theory provides a comprehensive framework for the evaluation of protein structure predictions

    PubMed Central

    Swanson, Rosemarie; Vannucci, Marina; Tsai, Jerry W.

    2008-01-01

    Protein structure prediction has a number of important ad hoc similarity measures for evaluating predictions, but would benefit from a measure that is able to provide a common framework for a broad range of comparisons. Here we show that a mutual information-like measure can provide a comprehensive framework for evaluating protein structure prediction of all types. We discuss the concept of information, its application to secondary structure, and the obstacle to applying it to 3D structure. Based on insights from the secondary structure case, we present an approach to work around the 3D difficulties, and develop a method to measure the mutual information provided by a 3D structure prediction. We integrate the evaluation of all types of protein structure prediction into a single frame work, and compare the amount of information provided by various prediction methods, including secondary structure prediction. Within this broadened framework, the idea that structure is better preserved than sequence during evolution is evaluated quantitatively for the globin family. A nearly perfect sequence match in the globin family corresponds to about 300 bits of information, whereas a nearly perfect structural match for the same two proteins corresponds to about 2500 bits of information, where bits of information describes the probability of obtaining a match of similar closeness by chance. Mutual information provides both a theoretical basis for evaluating structure similarity and an explanatory surround for existing similarity measures. PMID:18704942

  19. Integrating hydrology within a fully coupled environmental prediction system

    NASA Astrophysics Data System (ADS)

    Best, Martin; Lewis, Huw; Ashton, Heather; Blyth, Eleanor; Martinez, Alberto

    2017-04-01

    Historically the hydrological community and the community developing the land surface component of atmospheric models have both been tasked with representing the terrestrial hydrological cycle, but have focused on different ends, namely streamflow and evaporation respectively. To date the lack of computational resources and representative observations have limited the integration of the skills within these two communities. However, this is no longer the case. In addition, the drive toward fully integrated high resolution environmental prediction systems, coupling atmosphere, land and ocean on regional domains, requires an accurate representation for all aspects of terrestrial hydrology. Hence a new focus is emerging to integrate improved hydrological processes within the land surface components of atmospheric models. The UK Environmental Prediction (UKEP) project is a research experiment aimed at understanding the potential benefits for detailed environmental forecasting from a fully coupled atmosphere/land/ocean system at km-scale resolution for the UK. The prototype model utilises the Joint UK Land Environment Simulator (JULES) as its land surface component, coupled to the RFM river flow model. Although JULES has been previously used for climate studies that close the global water cycle, the JULES/RFM system has not been comprehensively evaluated for its ability to simulate river discharge. In this study we attempt some initial evaluation of the JULES/RFM system for all aspects of the terrestrial hydrological cycle, including evaporation, soil moisture and streamflow. In addition, comparisons are made between the results from the fully coupled environmental prediction system and stand alone JULES/RFM simulations forced by atmospheric driving data from the UK weather forecasting model. This provides an opportunity to assess the impact of fully coupled versus a one way coupled response for terrestrial hydrology. Finally we consider the potential for coupling JULES

  20. Integral Airframe Structures (IAS): Validated Feasibility Study of Integrally Stiffened Metallic Fuselage Panels for Reducing Manufacturing Costs

    NASA Technical Reports Server (NTRS)

    Munroe, J.; Wilkins, K.; Gruber, M.; Domack, Marcia S. (Technical Monitor)

    2000-01-01

    The Integral Airframe Structures (IAS) program investigated the feasibility of using "integrally stiffened" construction for commercial transport fuselage structure. The objective of the program was to demonstrate structural performance and weight equal to current "built-up" structure with lower manufacturing cost. Testing evaluated mechanical properties, structural details, joint performance, repair, static compression, and two-bay crack residual strength panels. Alloys evaluated included 7050-T7451 plate, 7050-T74511 extrusion, 6013-T6511x extrusion, and 7475-T7351 plate. Structural performance was evaluated with a large 7475-T7351 pressure test that included the arrest of a two-bay longitudinal crack, and a measure of residual strength for a two-bay crack centered on a broken frame. Analysis predictions for the two-bay longitudinal crack panel correlated well with the test results. Analysis activity conducted by the IAS team strongly indicates that current analysis tools predict integral structural behavior as accurately as built-up structure. The cost study results indicated that, compared to built-up fabrication methods, high-speed machining structure from aluminum plate would yield a recurring cost savings of 61%. Part count dropped from 78 individual parts on a baseline panel to just 7 parts for machined IAS structure.

  1. Role of contamination on the bondline integrity of composite structures

    SciTech Connect

    Shang, Xu

    2013-01-01

    Adhesively bonding composite structures have many applications in aerospace, automotive and submarine industries. The adhesive bonding joints have substantial advantage over the traditional metallic mechanical bonding joints, such as rivet and welding. However, the adhesive bonding joints require additional steps of surface preparation and cleaning to ensure consistent bond strength. In application, the adhesively bonded joints are exposed to environmental degradation and industrial solvent contaminates. Accordingly, the assurance of reliability of bonded composite structures requires detailed investigation of the role of contaminates on bondline integrity. This dissertation focuses on assessing the contaminates effect on the adhesive bondline integrity. A combined experimental and numerical framework is developed to study the contamination effect on the adhesive mechanical properties and adhesive joint strength. The bondline integrity were examined for a system of adhesive (EA9394) and the carbonfiber system (Hexply IM7/8552), after being subjected to different level of exposures to aviation hydraulic fluids and mold cleaning agents. A testing protocol based on nanoindentation for initial screening is used to predict the interfacial fracture characteristics after exposure to contamination. It is found the adhesive modulus and stiffness dropped by up to 10% for the hydraulic fluid contaminates, suggesting increase of the plastic dissipation within the bondline. However, the trend for the cleaning agent was not clear since the modulus drop while its hardness increased.

  2. Structural integrated sensor and actuator systems for active flow control

    NASA Astrophysics Data System (ADS)

    Behr, Christian; Schwerter, Martin; Leester-Schädel, Monika; Wierach, Peter; Dietzel, Andreas; Sinapius, Michael

    2016-04-01

    An adaptive flow separation control system is designed and implemented as an essential part of a novel high-lift device for future aircraft. The system consists of MEMS pressure sensors to determine the flow conditions and adaptive lips to regulate the mass flow and the velocity of a wall near stream over the internally blown Coanda flap. By the oscillating lip the mass flow in the blowing slot changes dynamically, consequently the momentum exchange of the boundary layer over a high lift flap required mass flow can be reduced. These new compact and highly integrated systems provide a real-time monitoring and manipulation of the flow conditions. In this context the integration of pressure sensors into flow sensing airfoils of composite material is investigated. Mechanical and electrical properties of the integrated sensors are investigated under mechanical loads during tensile tests. The sensors contain a reference pressure chamber isolated to the ambient by a deformable membrane with integrated piezoresistors connected as a Wheatstone bridge, which outputs voltage signals depending on the ambient pressure. The composite material in which the sensors are embedded consists of 22 individual layers of unidirectional glass fiber reinforced plastic (GFRP) prepreg. The results of the experiments are used for adapting the design of the sensors and the layout of the laminate to ensure an optimized flux of force in highly loaded structures primarily for future aeronautical applications. It can be shown that the pressure sensor withstands the embedding process into fiber composites with full functional capability and predictable behavior under stress.

  3. Assessing the Accuracy of Template-Based Structure Prediction Metaservers by Comparison with Structural Genomics Structures

    PubMed Central

    Gront, Dominik; Grabowski, Marek; Raynor, John; Tkaczuk, Karolina L.; Minor, Wladek

    2014-01-01

    The explosion of the size of the universe of known protein sequences has stimulated two complementary approaches to structural mapping of these sequences: theoretical structure prediction and experimental determination by structural genomics (SG). In this work, we assess the accuracy of structure prediction by two automated template-based structure prediction metaservers (genesilico.pl and bioinfo.pl) by measuring the structural similarity of the predicted models to corresponding experimental models determined a posteriori. Of 199 targets chosen from SG programs, the metaservers predicted the structures of about a fourth of them “correctly.” (In this case, “correct” was defined as placing more than 70% of the alpha carbon atoms in the model within 2 Å of the experimentally determined positions.) Almost all of the targets that could be modeled to this accuracy were those with an available template in the Protein Data Bank (PDB) with more than 25% sequence identity. The majority of those SG targets with lower sequence identity to structures in the PDB were not predicted by the metaservers with this accuracy. We also compared metaserver results to CASP8 results, finding that the models obtained by participants in the CASP competition were significantly better than those produced by the metaservers. PMID:23086054

  4. RNA-SSPT: RNA Secondary Structure Prediction Tools

    PubMed Central

    Ahmad, Freed; Mahboob, Shahid; Gulzar, Tahsin; din, Salah U; Hanif, Tanzeela; Ahmad, Hifza; Afzal, Muhammad

    2013-01-01

    The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes. PMID:24250115

  5. Statistical energy analysis response prediction methods for structural systems

    NASA Technical Reports Server (NTRS)

    Davis, R. F.

    1979-01-01

    The results of an effort to document methods for accomplishing response predictions for commonly encountered aerospace structural configurations is presented. Application of these methods to specified aerospace structure to provide sample analyses is included. An applications manual, with the structural analyses appended as example problems is given. Comparisons of the response predictions with measured data are provided for three of the example problems.

  6. RNA-SSPT: RNA Secondary Structure Prediction Tools.

    PubMed

    Ahmad, Freed; Mahboob, Shahid; Gulzar, Tahsin; Din, Salah U; Hanif, Tanzeela; Ahmad, Hifza; Afzal, Muhammad

    2013-01-01

    The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes.

  7. Incorporating Network Structure in Integrative Analysis of Cancer Prognosis Data

    PubMed Central

    Liu, Jin; Huang, Jian; Ma, Shuangge

    2014-01-01

    In high-throughput cancer genomic studies, markers identified from the analysis of single datasets may have unsatisfactory properties because of low sample sizes. Integrative analysis pools and analyzes raw data from multiple studies, and can effectively increase sample size and lead to improved marker identification results. In this study, we consider the integrative analysis of multiple high-throughput cancer prognosis studies. In the existing integrative analysis studies, the interplay among genes, which can be described using the network structure, has not been effectively accounted for. In network analysis, tightly-connected nodes (genes) are more likely to have related biological functions and similar regression coefficients. The goal of this study is to develop an analysis approach that can incorporate the gene network structure in integrative analysis. To this end, we adopt an AFT (accelerated failure time) model to describe survival. A weighted least squares approach, which has low computational cost, is adopted for estimation. For marker selection, we propose a new penalization approach. The proposed penalty is composed of two parts. The first part is a group MCP penalty, and conducts gene selection. The second part is a Laplacian penalty, and smoothes the differences of coefficients for tightly-connected genes. A group coordinate descent approach is developed to compute the proposed estimate. Simulation study shows satisfactory performance of the proposed approach when there exist moderate to strong correlations among genes. We analyze three lung cancer prognosis datasets, and demonstrate that incorporating the network structure can lead to the identification of important genes and improved prediction performance. PMID:23161517

  8. I-TASSER: a unified platform for automated protein structure and function prediction.

    PubMed

    Roy, Ambrish; Kucukural, Alper; Zhang, Yang

    2010-04-01

    The iterative threading assembly refinement (I-TASSER) server is an integrated platform for automated protein structure and function prediction based on the sequence-to-structure-to-function paradigm. Starting from an amino acid sequence, I-TASSER first generates three-dimensional (3D) atomic models from multiple threading alignments and iterative structural assembly simulations. The function of the protein is then inferred by structurally matching the 3D models with other known proteins. The output from a typical server run contains full-length secondary and tertiary structure predictions, and functional annotations on ligand-binding sites, Enzyme Commission numbers and Gene Ontology terms. An estimate of accuracy of the predictions is provided based on the confidence score of the modeling. This protocol provides new insights and guidelines for designing of online server systems for the state-of-the-art protein structure and function predictions. The server is available at http://zhanglab.ccmb.med.umich.edu/I-TASSER.

  9. Comparative and integrative analysis of RNA structural profiling data: current practices and emerging questions.

    PubMed

    Choudhary, Krishna; Deng, Fei; Aviran, Sharon

    2017-03-01

    Structure profiling experiments provide single-nucleotide information on RNA structure. Recent advances in chemistry combined with application of high-throughput sequencing have enabled structure profiling at transcriptome scale and in living cells, creating unprecedented opportunities for RNA biology. Propelled by these experimental advances, massive data with ever-increasing diversity and complexity have been generated, which give rise to new challenges in interpreting and analyzing these data. We review current practices in analysis of structure profiling data with emphasis on comparative and integrative analysis as well as highlight emerging questions. Comparative analysis has revealed structural patterns across transcriptomes and has become an integral component of recent profiling studies. Additionally, profiling data can be integrated into traditional structure prediction algorithms to improve prediction accuracy. To keep pace with experimental developments, methods to facilitate, enhance and refine such analyses are needed. Parallel advances in analysis methodology will complement profiling technologies and help them reach their full potential.

  10. A Predictive Structural Model of the Primate Connectome

    PubMed Central

    Beul, Sarah F.; Barbas, Helen; Hilgetag, Claus C.

    2017-01-01

    Anatomical connectivity imposes strong constraints on brain function, but there is no general agreement about principles that govern its organization. Based on extensive quantitative data, we tested the power of three factors to predict connections of the primate cerebral cortex: architectonic similarity (structural model), spatial proximity (distance model) and thickness similarity (thickness model). Architectonic similarity showed the strongest and most consistent influence on connection features. This parameter was strongly associated with the presence or absence of inter-areal connections and when integrated with spatial distance, the factor allowed predicting the existence of projections with very high accuracy. Moreover, architectonic similarity was strongly related to the laminar pattern of projection origins, and the absolute number of cortical connections of an area. By contrast, cortical thickness similarity and distance were not systematically related to connection features. These findings suggest that cortical architecture provides a general organizing principle for connections in the primate brain, providing further support for the well-corroborated structural model. PMID:28256558

  11. Developing a comprehensive training curriculum for integrated predictive maintenance

    NASA Astrophysics Data System (ADS)

    Wurzbach, Richard N.

    2002-03-01

    On-line equipment condition monitoring is a critical component of the world-class production and safety histories of many successful nuclear plant operators. From addressing availability and operability concerns of nuclear safety-related equipment to increasing profitability through support system reliability and reduced maintenance costs, Predictive Maintenance programs have increasingly become a vital contribution to the maintenance and operation decisions of nuclear facilities. In recent years, significant advancements have been made in the quality and portability of many of the instruments being used, and software improvements have been made as well. However, the single most influential component of the success of these programs is the impact of a trained and experienced team of personnel putting this technology to work. Changes in the nature of the power generation industry brought on by competition, mergers, and acquisitions, has taken the historically stable personnel environment of power generation and created a very dynamic situation. As a result, many facilities have seen a significant turnover in personnel in key positions, including predictive maintenance personnel. It has become the challenge for many nuclear operators to maintain the consistent contribution of quality data and information from predictive maintenance that has become important in the overall equipment decision process. These challenges can be met through the implementation of quality training to predictive maintenance personnel and regular updating and re-certification of key technology holders. The use of data management tools and services aid in the sharing of information across sites within an operating company, and with experts who can contribute value-added data management and analysis. The overall effectiveness of predictive maintenance programs can be improved through the incorporation of newly developed comprehensive technology training courses. These courses address the use of

  12. Integrated Cox's model for predicting survival time of glioblastoma multiforme.

    PubMed

    Ai, Zhibing; Li, Longti; Fu, Rui; Lu, Jing-Min; He, Jing-Dong; Li, Sen

    2017-04-01

    Glioblastoma multiforme is the most common primary brain tumor and is highly lethal. This study aims to figure out signatures for predicting the survival time of patients with glioblastoma multiforme. Clinical information, messenger RNA expression, microRNA expression, and single-nucleotide polymorphism array data of patients with glioblastoma multiforme were retrieved from The Cancer Genome Atlas. Patients were separated into two groups by using 1 year as a cutoff, and a logistic regression model was used to figure out any variables that can predict whether the patient was able to live longer than 1 year. Furthermore, Cox's model was used to find out features that were correlated with the survival time. Finally, a Cox model integrated the significant clinical variables, messenger RNA expression, microRNA expression, and single-nucleotide polymorphism was built. Although the classification method failed, signatures of clinical features, messenger RNA expression levels, and microRNA expression levels were figured out by using Cox's model. However, no single-nucleotide polymorphisms related to prognosis were found. The selected clinical features were age at initial diagnosis, Karnofsky score, and race, all of which had been suggested to correlate with survival time. Both of the two significant microRNAs, microRNA-221 and microRNA-222, were targeted to p27(Kip1) protein, which implied the important role of p27(Kip1) on the prognosis of glioblastoma multiforme patients. Our results suggested that survival modeling was more suitable than classification to figure out prognostic biomarkers for patients with glioblastoma multiforme. An integrated model containing clinical features, messenger RNA levels, and microRNA expression levels was built, which has the potential to be used in clinics and thus to improve the survival status of glioblastoma multiforme patients.

  13. An integrated modeling approach to predict flooding on urban basin.

    PubMed

    Dey, Ashis Kumar; Kamioka, Seiji

    2007-01-01

    Correct prediction of flood extents in urban catchments has become a challenging issue. The traditional urban drainage models that consider only the sewerage-network are able to simulate the drainage system correctly until there is no overflow from the network inlet or manhole. When such overflows exist due to insufficient drainage capacity of downstream pipes or channels, it becomes difficult to reproduce the actual flood extents using these traditional one-phase simulation techniques. On the other hand, the traditional 2D models that simulate the surface flooding resulting from rainfall and/or levee break do not consider the sewerage network. As a result, the correct flooding situation is rarely addressed from those available traditional 1D and 2D models. This paper presents an integrated model that simultaneously simulates the sewerage network, river network and 2D mesh network to get correct flood extents. The model has been successfully applied into the Tenpaku basin (Nagoya, Japan), which experienced severe flooding with a maximum flood depth more than 1.5 m on September 11, 2000 when heavy rainfall, 580 mm in 28 hrs (return period > 100 yr), occurred over the catchments. Close agreements between the simulated flood depths and observed data ensure that the present integrated modeling approach is able to reproduce the urban flooding situation accurately, which rarely can be obtained through the traditional 1D and 2D modeling approaches.

  14. Integrated hydro-bacterial modelling for predicting bathing water quality

    NASA Astrophysics Data System (ADS)

    Huang, Guoxian; Falconer, Roger A.; Lin, Binliang

    2017-03-01

    In recent years health risks associated with the non-compliance of bathing water quality have received increasing worldwide attention. However, it is particularly challenging to establish the source of any non-compliance, due to the complex nature of the source of faecal indicator organisms, and the fate and delivery processes and scarcity of field measured data in many catchments and estuaries. In the current study an integrated hydro-bacterial model, linking a catchment, 1-D model and 2-D model were integrated to simulate the adsorption-desorption processes of faecal bacteria to and from sediment particles in river, estuarine and coastal waters, respectively. The model was then validated using hydrodynamic, sediment and faecal bacteria concentration data, measured in 2012, in the Ribble river and estuary, and along the Fylde coast, UK. Particular emphasis has been placed on the mechanism of faecal bacteria transport and decay through the deposition and resuspension of suspended sediments. The results showed that by coupling the E.coli concentration with the sediment transport processes, the accuracy of the predicted E.coli levels was improved. A series of scenario runs were then carried out to investigate the impacts of different management scenarios on the E.coli concentration levels in the coastal bathing water sites around Liverpool Bay, UK. The model results show that the level of compliance with the new EU bathing water standards can be improved significantly by extending outfalls and/or reducing urban sources by typically 50%.

  15. A comprehensive comparison of comparative RNA structure prediction approaches

    PubMed Central

    Gardner, Paul P; Giegerich, Robert

    2004-01-01

    Background An increasing number of researchers have released novel RNA structure analysis and prediction algorithms for comparative approaches to structure prediction. Yet, independent benchmarking of these algorithms is rarely performed as is now common practice for protein-folding, gene-finding and multiple-sequence-alignment algorithms. Results Here we evaluate a number of RNA folding algorithms using reliable RNA data-sets and compare their relative performance. Conclusions We conclude that comparative data can enhance structure prediction but structure-prediction-algorithms vary widely in terms of both sensitivity and selectivity across different lengths and homologies. Furthermore, we outline some directions for future research. PMID:15458580

  16. Model Predictive Control of Integrated Gasification Combined Cycle Power Plants

    SciTech Connect

    B. Wayne Bequette; Priyadarshi Mahapatra

    2010-08-31

    The primary project objectives were to understand how the process design of an integrated gasification combined cycle (IGCC) power plant affects the dynamic operability and controllability of the process. Steady-state and dynamic simulation models were developed to predict the process behavior during typical transients that occur in plant operation. Advanced control strategies were developed to improve the ability of the process to follow changes in the power load demand, and to improve performance during transitions between power levels. Another objective of the proposed work was to educate graduate and undergraduate students in the application of process systems and control to coal technology. Educational materials were developed for use in engineering courses to further broaden this exposure to many students. ASPENTECH software was used to perform steady-state and dynamic simulations of an IGCC power plant. Linear systems analysis techniques were used to assess the steady-state and dynamic operability of the power plant under various plant operating conditions. Model predictive control (MPC) strategies were developed to improve the dynamic operation of the power plants. MATLAB and SIMULINK software were used for systems analysis and control system design, and the SIMULINK functionality in ASPEN DYNAMICS was used to test the control strategies on the simulated process. Project funds were used to support a Ph.D. student to receive education and training in coal technology and the application of modeling and simulation techniques.

  17. Cluster and Integral In-Orbit Solar Array Performance Prediction

    NASA Astrophysics Data System (ADS)

    d'Accolti, Gianfelice; Gonzalez, Jose Ramon; Taylor, Stephen; Escoubet, Philippe; Volpp, Juergen; Southworth, Richard; Bordoni, Emanuela

    2014-08-01

    Solar array in-orbit performance prediction is a key point to allow the extension of a mission, especially when margins of few watts are of paramount importance to keep working instruments relevant to its continuation. This is the case of the four Cluster satellites whose mission survival was depending on 10 to 15 Watts, a quantity normally neglected or absorbed in the simulation error. This verification was carried out after the first 12 years in orbit, with the aim of requesting a mission extension up to 2017. In order to verify if the solar array could deliver the requested power to satisfy the mission needs, ESA's Solar Generator Section reviewed its performance at a very detailed level. The approach followed produced four cases with different levels of probability. With this method, the data retrieved from the telemetry have been fitted with a very high degree of accuracy. The approach followed for Integral is slightly different. In this case the orbit is quite different, very eccentric and with a low perigee that crosses the trapped particle belts at some periods during the orbital evolution. The main implication of this fact lies in the higher doses of radiation and in the difficulty of making a reliable prediction. This situation has been overcome by assuming safety margins for the radiation dose to ensure the operation of solar array under the mission request.

  18. Integrated in silico approaches for the prediction of Ames test mutagenicity

    NASA Astrophysics Data System (ADS)

    Modi, Sandeep; Li, Jin; Malcomber, Sophie; Moore, Claire; Scott, Andrew; White, Andrew; Carmichael, Paul

    2012-09-01

    The bacterial reverse mutation assay (Ames test) is a biological assay used to assess the mutagenic potential of chemical compounds. In this paper approaches for the development of an in silico mutagenicity screening tool are described. Three individual in silico models, which cover both structure activity relationship methods (SARs) and quantitative structure activity relationship methods (QSARs), were built using three different modelling techniques: (1) an in-house alert model: which uses SAR approach where alerts are generated based on experts judgements; (2) a kNN approach (k-Nearest Neighbours), which is a QSAR model where a prediction is given based on outcomes of its k chemical neighbours; (3) a naive Bayesian model (NB), which is another QSAR model, where a prediction is derived using a Bayesian formula through preselected identified informative chemical features (e.g., physico-chemical, structural descriptors). These in silico models, were compared against two well-known alert models (DEREK and ToxTree) and also against three different consensus approaches (Categorical Bayesian Integration Approach (CBI), Partial Least Squares Discriminate Analysis (PLS-DA) and simple majority vote approach). By applying these integration methods on the validation sets it was shown that both integration models (PLS-DA and CBI) achieved better performance than any of the individual models or consensus obtained by simple majority rule. In conclusion, the recommendation of this paper is that when obtaining consensus predictions for Ames mutagenicity, approaches like PLS-DA or CBI should be the first choice for the integration as compared to a simple majority vote approach.

  19. PROSPER: An Integrated Feature-Based Tool for Predicting Protease Substrate Cleavage Sites

    PubMed Central

    Perry, Andrew J.; Akutsu, Tatsuya; Webb, Geoffrey I.; Whisstock, James C.; Pike, Robert N.

    2012-01-01

    The ability to catalytically cleave protein substrates after synthesis is fundamental for all forms of life. Accordingly, site-specific proteolysis is one of the most important post-translational modifications. The key to understanding the physiological role of a protease is to identify its natural substrate(s). Knowledge of the substrate specificity of a protease can dramatically improve our ability to predict its target protein substrates, but this information must be utilized in an effective manner in order to efficiently identify protein substrates by in silico approaches. To address this problem, we present PROSPER, an integrated feature-based server for in silico identification of protease substrates and their cleavage sites for twenty-four different proteases. PROSPER utilizes established specificity information for these proteases (derived from the MEROPS database) with a machine learning approach to predict protease cleavage sites by using different, but complementary sequence and structure characteristics. Features used by PROSPER include local amino acid sequence profile, predicted secondary structure, solvent accessibility and predicted native disorder. Thus, for proteases with known amino acid specificity, PROSPER provides a convenient, pre-prepared tool for use in identifying protein substrates for the enzymes. Systematic prediction analysis for the twenty-four proteases thus far included in the database revealed that the features we have included in the tool strongly improve performance in terms of cleavage site prediction, as evidenced by their contribution to performance improvement in terms of identifying known cleavage sites in substrates for these enzymes. In comparison with two state-of-the-art prediction tools, PoPS and SitePrediction, PROSPER achieves greater accuracy and coverage. To our knowledge, PROSPER is the first comprehensive server capable of predicting cleavage sites of multiple proteases within a single substrate sequence using

  20. Energy-Efficient Integration of Continuous Context Sensing and Prediction into Smartwatches

    PubMed Central

    Rawassizadeh, Reza; Tomitsch, Martin; Nourizadeh, Manouchehr; Momeni, Elaheh; Peery, Aaron; Ulanova, Liudmila; Pazzani, Michael

    2015-01-01

    As the availability and use of wearables increases, they are becoming a promising platform for context sensing and context analysis. Smartwatches are a particularly interesting platform for this purpose, as they offer salient advantages, such as their proximity to the human body. However, they also have limitations associated with their small form factor, such as processing power and battery life, which makes it difficult to simply transfer smartphone-based context sensing and prediction models to smartwatches. In this paper, we introduce an energy-efficient, generic, integrated framework for continuous context sensing and prediction on smartwatches. Our work extends previous approaches for context sensing and prediction on wrist-mounted wearables that perform predictive analytics outside the device. We offer a generic sensing module and a novel energy-efficient, on-device prediction module that is based on a semantic abstraction approach to convert sensor data into meaningful information objects, similar to human perception of a behavior. Through six evaluations, we analyze the energy efficiency of our framework modules, identify the optimal file structure for data access and demonstrate an increase in accuracy of prediction through our semantic abstraction method. The proposed framework is hardware independent and can serve as a reference model for implementing context sensing and prediction on small wearable devices beyond smartwatches, such as body-mounted cameras. PMID:26370997

  1. Energy-Efficient Integration of Continuous Context Sensing and Prediction into Smartwatches.

    PubMed

    Rawassizadeh, Reza; Tomitsch, Martin; Nourizadeh, Manouchehr; Momeni, Elaheh; Peery, Aaron; Ulanova, Liudmila; Pazzani, Michael

    2015-09-08

    As the availability and use of wearables increases, they are becoming a promising platform for context sensing and context analysis. Smartwatches are a particularly interesting platform for this purpose, as they offer salient advantages, such as their proximity to the human body. However, they also have limitations associated with their small form factor, such as processing power and battery life, which makes it difficult to simply transfer smartphone-based context sensing and prediction models to smartwatches. In this paper, we introduce an energy-efficient, generic, integrated framework for continuous context sensing and prediction on smartwatches. Our work extends previous approaches for context sensing and prediction on wrist-mounted wearables that perform predictive analytics outside the device. We offer a generic sensing module and a novel energy-efficient, on-device prediction module that is based on a semantic abstraction approach to convert sensor data into meaningful information objects, similar to human perception of a behavior. Through six evaluations, we analyze the energy efficiency of our framework modules, identify the optimal file structure for data access and demonstrate an increase in accuracy of prediction through our semantic abstraction method. The proposed framework is hardware independent and can serve as a reference model for implementing context sensing and prediction on small wearable devices beyond smartwatches, such as body-mounted cameras.

  2. Protein short loop prediction in terms of a structural alphabet.

    PubMed

    Tyagi, Manoj; Bornot, Aurélie; Offmann, Bernard; de Brevern, Alexandre G

    2009-08-01

    Loops connect regular secondary structures. In many instances, they are known to play crucial biological roles. To bypass the limitation of secondary structure description, we previously defined a structural alphabet composed of 16 structural prototypes, called Protein Blocks (PBs). It leads to an accurate description of every region of 3D protein backbones and has been used in local structure prediction. In the present study, we used our structural alphabet to predict the loops connecting two repetitive structures. Thus, we showed interest to take into account the flanking regions, leading to prediction rate improvement up to 19.8%, but we also underline the sensitivity of such an approach. This research can be used to propose different structures for the loops and to probe and sample their flexibility. It is a useful tool for ab initio loop prediction and leads to insights into flexible docking approach.

  3. On the significance of an RNA tertiary structure prediction

    PubMed Central

    Hajdin, Christine E.; Ding, Feng; Dokholyan, Nikolay V.; Weeks, Kevin M.

    2010-01-01

    Tertiary structure prediction is important for understanding structure–function relationships for RNAs whose structures are unknown and for characterizing RNA states recalcitrant to direct analysis. However, it is unknown what root-mean-square deviation (RMSD) corresponds to a statistically significant RNA tertiary structure prediction. We use discrete molecular dynamics to generate RNA-like folds for structures up to 161 nucleotides (nt) that have complex tertiary interactions and then determine the RMSD distribution between these decoys. These distributions are Gaussian-like. The mean RMSD increases with RNA length and is smaller if secondary structure constraints are imposed while generating decoys. The compactness of RNA molecules with true tertiary folds is intermediate between closely packed spheres and a freely jointed chain. We use this scaling relationship to define an expression relating RMSD with the confidence that a structure prediction is better than that expected by chance. This is the prediction significance, and corresponds to a P-value. For a 100-nt RNA, the RMSD of predicted structures should be within 25 Å of the accepted structure to reach the P ≤ 0.01 level if the secondary structure is predicted de novo and within 14 Å if secondary structure information is used as a constraint. This significance approach should be useful for evaluating diverse RNA structure prediction and molecular modeling algorithms. PMID:20498460

  4. Spaceflight Effect on White Matter Structural Integrity

    NASA Technical Reports Server (NTRS)

    Lee, Jessica K.; Kopplemans, Vincent; Paternack, Ofer; Bloomberg, Jacob J.; Mulavara, Ajitkumar P.; Seidler, Rachael D.

    2017-01-01

    Recent reports of elevated brain white matter hyperintensity (WMH) counts and volume in postflight astronaut MRIs suggest that further examination of spaceflight's impact on the microstructure of brain white matter is warranted. To this end, retrospective longitudinal diffusion-weighted MRI scans obtained from 15 astronauts were evaluated. In light of the recent reports of microgravity-induced cephalad fluid shift and gray matter atrophy seen in astronauts, we applied a technique to estimate diffusion tensor imaging (DTI) metrics corrected for free water contamination. This approach enabled the analysis of white matter tissue-specific alterations that are unrelated to fluid shifts, occurring from before spaceflight to after landing. After spaceflight, decreased fractional anisotropy (FA) values were detected in an area encompassing the superior and inferior longitudinal fasciculi and the inferior fronto-occipital fasciculus. Increased radial diffusivity (RD) and decreased axial diffusivity (AD) were also detected within overlapping regions. In addition, FA values in the corticospinal tract decreased and RD measures in the precentral gyrus white matter increased from before to after flight. The results show disrupted structural connectivity of white matter in tracts involved in visuospatial processing, vestibular function, and movement control as a result of spaceflight. The findings may help us understand the structural underpinnings of the extensive spaceflight-induced sensorimotor remodeling. Prospective longitudinal assessment of the white matter integrity in astronauts is needed to characterize the evolution of white matter microstructural changes associated with spaceflight, their behavioral consequences, and the time course of recovery. Supported by a grant from the National Space Biomedical Research Institute, NASA NCC 9-58.

  5. Crack Turning in Integrally Stiffened Aircraft Structures

    NASA Technical Reports Server (NTRS)

    Pettit, Richard Glen

    2000-01-01

    Current emphasis in the aircraft industry toward reducing manufacturing cost has created a renewed interest in integrally stiffened structures. Crack turning has been identified as an approach to improve the damage tolerance and fail-safety of this class of structures. A desired behavior is for skin cracks to turn before reaching a stiffener, instead of growing straight through. A crack in a pressurized fuselage encounters high T-stress as it nears the stiffener--a condition favorable to crack turning. Also, the tear resistance of aluminum alloys typically varies with crack orientation, a form of anisotropy that can influence the crack path. The present work addresses these issues with a study of crack turning in two-dimensions, including the effects of both T-stress and fracture anisotropy. Both effects are shown to have relation to the process zone size, an interaction that is central to this study. Following an introduction to the problem, the T-stress effect is studied for a slightly curved semi-infinite crack with a cohesive process zone, yielding a closed form expression for the future crack path in an infinite medium. For a given initial crack tip curvature and tensile T-stress, the crack path instability is found to increase with process zone size. Fracture orthotropy is treated using a simple function to interpolate between the two principal fracture resistance values in two-dimensions. An extension to three-dimensions interpolates between the six principal values of fracture resistance. Also discussed is the transition between mode I and mode II fracture in metals. For isotropic materials, there is evidence that the crack seeks out a direction of either local symmetry (pure mode I) or local asymmetry (pure mode II) growth. For orthotropic materials the favored states are not pure modal, and have mode mixity that is a function of crack orientation.

  6. Predicting crystal structure by merging data mining with quantum mechanics.

    PubMed

    Fischer, Christopher C; Tibbetts, Kevin J; Morgan, Dane; Ceder, Gerbrand

    2006-08-01

    Modern methods of quantum mechanics have proved to be effective tools to understand and even predict materials properties. An essential element of the materials design process, relevant to both new materials and the optimization of existing ones, is knowing which crystal structures will form in an alloy system. Crystal structure can only be predicted effectively with quantum mechanics if an algorithm to direct the search through the large space of possible structures is found. We present a new approach to the prediction of structure that rigorously mines correlations embodied within experimental data and uses them to direct quantum mechanical techniques efficiently towards the stable crystal structure of materials.

  7. Structural integration in hypoxia-inducible factors

    SciTech Connect

    Wu, Dalei; Potluri, Nalini; Lu, Jingping; Kim, Youngchang; Rastinejad, Fraydoon

    2015-08-20

    The hypoxia-inducible factors (HIFs) coordinate cellular adaptations to low oxygen stress by regulating transcriptional programs in erythropoiesis, angiogenesis and metabolism. These programs promote the growth and progression of many tumours, making HIFs attractive anticancer targets. Transcriptionally active HIFs consist of HIF-alpha and ARNT (also called HIF-1 beta) subunits. Here we describe crystal structures for each of mouse HIF-2 alpha-ARNT and HIF-1 alpha-ARNT heterodimers in states that include bound small molecules and their hypoxia response element. A highly integrated quaternary architecture is shared by HIF-2 alpha-ARNT and HIF-1 alpha-ARNT, wherein ARNT spirals around the outside of each HIF-alpha subunit. Five distinct pockets are observed that permit small-molecule binding, including PAS domain encapsulated sites and an interfacial cavity formed through subunit heterodimerization. The DNA-reading head rotates, extends and cooperates with a distal PAS domain to bind hypoxia response elements. HIF-alpha mutations linked to human cancers map to sensitive sites that establish DNA binding and the stability of PAS domains and pockets.

  8. Assessment of structural integrity of wooden poles

    NASA Astrophysics Data System (ADS)

    Craighead, Ian A.; Thackery, Steve; Redstall, Martin; Thomas, Matthew R.

    2000-05-01

    Despite recent advances in the development of new materials, wood continues to be used globally for the support of overhead cable networks used by telecommunications and electrical utility companies. As a natural material, wood is subject to decay and will eventually fail, causing disruption to services and danger to public and company personnel. Internal decay, due to basidomycetes fungi or attack by termites, can progress rapidly and is often difficult to detect by casual inspection. The traditional method of testing poles for decay involves hitting them with a hammer and listening to the sound that results. However, evidence suggests that a large number of poles are replaced unnecessarily and a significant number of poles continue to fail unexpectedly in service. Therefore, a more accurate method of assessing the structural integrity of wooden poles is required. Over the last 25 years there have been a number of attempts at improving decay detection. Techniques such as ultrasound, drilling X rays etc. have been developed but have generally failed to improve upon the practicality and accuracy of the traditional testing method. The paper describes the use of signal processing techniques to analyze the acoustic response of the pole and thereby determine the presence of decay. Development of a prototype meter is described and the results of initial tests on several hundred poles are presented.

  9. Attachment theory and theory of planned behavior: an integrative model predicting underage drinking.

    PubMed

    Lac, Andrew; Crano, William D; Berger, Dale E; Alvaro, Eusebio M

    2013-08-01

    Research indicates that peer and maternal bonds play important but sometimes contrasting roles in the outcomes of children. Less is known about attachment bonds to these 2 reference groups in young adults. Using a sample of 351 participants (18 to 20 years of age), the research integrated two theoretical traditions: attachment theory and theory of planned behavior (TPB). The predictive contribution of both theories was examined in the context of underage adult alcohol use. Using full structural equation modeling, results substantiated the hypotheses that secure peer attachment positively predicted norms and behavioral control toward alcohol, but secure maternal attachment inversely predicted attitudes and behavioral control toward alcohol. Alcohol attitudes, norms, and behavioral control each uniquely explained alcohol intentions, which anticipated an increase in alcohol behavior 1 month later. The hypothesized processes were statistically corroborated by tests of indirect and total effects. These findings support recommendations for programs designed to curtail risky levels of underage drinking using the tenets of attachment theory and TPB.

  10. Critical Features of Fragment Libraries for Protein Structure Prediction.

    PubMed

    Trevizani, Raphael; Custódio, Fábio Lima; Dos Santos, Karina Baptista; Dardenne, Laurent Emmanuel

    2017-01-01

    The use of fragment libraries is a popular approach among protein structure prediction methods and has proven to substantially improve the quality of predicted structures. However, some vital aspects of a fragment library that influence the accuracy of modeling a native structure remain to be determined. This study investigates some of these features. Particularly, we analyze the effect of using secondary structure prediction guiding fragments selection, different fragments sizes and the effect of structural clustering of fragments within libraries. To have a clearer view of how these factors affect protein structure prediction, we isolated the process of model building by fragment assembly from some common limitations associated with prediction methods, e.g., imprecise energy functions and optimization algorithms, by employing an exact structure-based objective function under a greedy algorithm. Our results indicate that shorter fragments reproduce the native structure more accurately than the longer. Libraries composed of multiple fragment lengths generate even better structures, where longer fragments show to be more useful at the beginning of the simulations. The use of many different fragment sizes shows little improvement when compared to predictions carried out with libraries that comprise only three different fragment sizes. Models obtained from libraries built using only sequence similarity are, on average, better than those built with a secondary structure prediction bias. However, we found that the use of secondary structure prediction allows greater reduction of the search space, which is invaluable for prediction methods. The results of this study can be critical guidelines for the use of fragment libraries in protein structure prediction.

  11. Critical Features of Fragment Libraries for Protein Structure Prediction

    PubMed Central

    dos Santos, Karina Baptista

    2017-01-01

    The use of fragment libraries is a popular approach among protein structure prediction methods and has proven to substantially improve the quality of predicted structures. However, some vital aspects of a fragment library that influence the accuracy of modeling a native structure remain to be determined. This study investigates some of these features. Particularly, we analyze the effect of using secondary structure prediction guiding fragments selection, different fragments sizes and the effect of structural clustering of fragments within libraries. To have a clearer view of how these factors affect protein structure prediction, we isolated the process of model building by fragment assembly from some common limitations associated with prediction methods, e.g., imprecise energy functions and optimization algorithms, by employing an exact structure-based objective function under a greedy algorithm. Our results indicate that shorter fragments reproduce the native structure more accurately than the longer. Libraries composed of multiple fragment lengths generate even better structures, where longer fragments show to be more useful at the beginning of the simulations. The use of many different fragment sizes shows little improvement when compared to predictions carried out with libraries that comprise only three different fragment sizes. Models obtained from libraries built using only sequence similarity are, on average, better than those built with a secondary structure prediction bias. However, we found that the use of secondary structure prediction allows greater reduction of the search space, which is invaluable for prediction methods. The results of this study can be critical guidelines for the use of fragment libraries in protein structure prediction. PMID:28085928

  12. Hippocampal structure predicts cortical indices of reactivation of related items.

    PubMed

    Walker, John A; Low, Kathy A; Fletcher, Mark A; Cohen, Neal J; Gratton, Gabriele; Fabiani, Monica

    2017-01-27

    One of the key components of relational memory is the ability to bind together the constituent elements of a memory experience, and this ability is thought to be supported by the hippocampus. Previously we had shown that these relational bindings can be used to reactivate the cortical processors of an absent item in the presence of a relationally bound associate (Walker et al., 2014). Specifically, we recorded the event-related optical signal (EROS) when presenting the scene of a face-scene pair during a preview period immediately preceding a test display, and demonstrated reactivation of a face-processing cortical area (the superior temporal sulcus, STS) for scenes that had been previously paired with faces, relative to scenes that had not. Here we combined the EROS measures during the same preview paradigm with anatomical estimates of hippocampal integrity (structural MRI measures of hippocampal volume and diffusion tensor imaging measures of mean fractional anisotropy and diffusivity) to provide evidence that the hippocampus is mediating this reactivation phenomenon. The study was run in a sample of older adults aged 55-87, taking advantage of the high amount of hippocampal variability present in aging. We replicated the functional reactivation of STS during the preview period, specific to scenes previously paired with faces. Crucially, we also found that this phenomenon is correlated with structural hippocampus integrity. Both STS reactivation and hippocampal structure predicted subsequent recognition performance. These data support the theory that relational memory is sustained by an interaction between hippocampal and cortical sensory processing regions, and that these functions may be at the basis of episodic memory changes in normal aging.

  13. Integrated numerical prediction of atomization process of liquid hydrogen jet

    NASA Astrophysics Data System (ADS)

    Ishimoto, Jun; Ohira, Katsuhide; Okabayashi, Kazuki; Chitose, Keiko

    2008-05-01

    The 3-D structure of the liquid atomization behavior of an LH jet flow through a pinhole nozzle is numerically investigated and visualized by a new type of integrated simulation technique. The present computational fluid dynamics (CFD) analysis focuses on the thermodynamic effect on the consecutive breakup of a cryogenic liquid column, the formation of a liquid film, and the generation of droplets in the outlet section of the pinhole nozzle. Utilizing the governing equations for a high-speed turbulent cryogenic jet flow through a pinhole nozzle based on the thermal nonequilibrium LES-VOF model in conjunction with the CSF model, an integrated parallel computation is performed to clarify the detailed atomization process of a high-speed LH2 jet flow through a pinhole nozzle and to acquire data, which is difficult to confirm by experiment, such as atomization length, liquid core shape, droplet-size distribution, spray angle, droplet velocity profiles, and thermal field surrounding the atomizing jet flow. According to the present computation, the cryogenic atomization rate and the LH2 droplets-gas two-phase flow characteristics are found to be controlled by the turbulence perturbation upstream of the pinhole nozzle, hydrodynamic instabilities at the gas-liquid interface and shear stress between the liquid core and the periphery of the LH2 jet. Furthermore, calculation of the effect of cryogenic atomization on the jet thermal field shows that such atomization extensively enhances the thermal diffusion surrounding the LH2 jet flow.

  14. Machine learning integration for predicting the effect of single amino acid substitutions on protein stability.

    PubMed

    Ozen, Ayşegül; Gönen, Mehmet; Alpaydan, Ethem; Haliloğlu, Türkan

    2009-10-19

    Computational prediction of protein stability change due to single-site amino acid substitutions is of interest in protein design and analysis. We consider the following four ways to improve the performance of the currently available predictors: (1) We include additional sequence- and structure-based features, namely, the amino acid substitution likelihoods, the equilibrium fluctuations of the alpha- and beta-carbon atoms, and the packing density. (2) By implementing different machine learning integration approaches, we combine information from different features or representations. (3) We compare classification vs. regression methods to predict the sign vs. the output of stability change. (4) We allow a reject option for doubtful cases where the risk of misclassification is high. We investigate three different approaches: early, intermediate and late integration, which respectively combine features, kernels over feature subsets, and decisions. We perform simulations on two data sets: (1) S1615 is used in previous studies, (2) S2783 is the updated version (as of July 2, 2009) extracted also from ProTherm. For S1615 data set, our highest accuracy using both sequence and structure information is 0.842 on cross-validation and 0.904 on testing using early integration. Newly added features, namely, local compositional packing and the mobility extent of the mutated residues, improve accuracy significantly with intermediate integration. For S2783 data set, we also train regression methods to estimate not only the sign but also the amount of stability change and apply risk-based classification to reject when the learner has low confidence and the loss of misclassification is high. The highest accuracy is 0.835 on cross-validation and 0.832 on testing using only sequence information. The percentage of false positives can be decreased to less than 0.005 by rejecting 10 per cent using late integration. We find that in both early and late integration, combining inputs or

  15. Integrative neuroscience approach to predict ADHD stimulant response.

    PubMed

    Hermens, Daniel F; Rowe, Donald L; Gordon, Evian; Williams, Leanne M

    2006-05-01

    Despite high rates of prescription, little is known about the long-term consequences of stimulant medication therapy for attention-deficit hyperactivity disorder (ADHD) sufferers. Historically, the clinical use of stimulants for ADHD has been based on trial and error before optimal therapy is reached. Concurrently, scientific research on the mechanism of action of stimulants has influenced neurobiological models of ADHD, but has not always informed their prescription. Whilst the two main stimulant types (methylphenidate and dexamphetamine) have numerous similarities, they also differ (slightly) in mechanism and possibly individual response. A further issue relates to differences in cost and availability compounded by the expectation for stimulants to be effective in ameliorating a broad spectrum of ADHD-related symptoms. Thus, there is an increasing need for treating clinicians to prescribe not only the most effective drug, but also the most appropriate dose with the associated release mechanism and schedule for each ADHD patient presented. In this regard, the field is witnessing an emergence of the personalized medicine approach to ADHD, in which treatment decisions are tailored to each individual. This shift requires a new approach to research into treatment response prediction. Given the heterogeneity of ADHD, a profile of information may be required to capture the most sensitive predictors of treatment response in individuals. These profiles will also benefit from the integration of data from clinical rating scales with more direct measures of cognition and brain function. In conclusion, there is a need to establish a more robust normative framework as the baseline for treatment, as well as diagnostic decisions, and as discussed, the growth of integrated neuroscience databases will be important in this regard.

  16. Simultaneous prediction of protein secondary structure and transmembrane spans.

    PubMed

    Leman, Julia Koehler; Mueller, Ralf; Karakas, Mert; Woetzel, Nils; Meiler, Jens

    2013-07-01

    Prediction of transmembrane spans and secondary structure from the protein sequence is generally the first step in the structural characterization of (membrane) proteins. Preference of a stretch of amino acids in a protein to form secondary structure and being placed in the membrane are correlated. Nevertheless, current methods predict either secondary structure or individual transmembrane states. We introduce a method that simultaneously predicts the secondary structure and transmembrane spans from the protein sequence. This approach not only eliminates the necessity to create a consensus prediction from possibly contradicting outputs of several predictors but bears the potential to predict conformational switches, i.e., sequence regions that have a high probability to change for example from a coil conformation in solution to an α-helical transmembrane state. An artificial neural network was trained on databases of 177 membrane proteins and 6048 soluble proteins. The output is a 3 × 3 dimensional probability matrix for each residue in the sequence that combines three secondary structure types (helix, strand, coil) and three environment types (membrane core, interface, solution). The prediction accuracies are 70.3% for nine possible states, 73.2% for three-state secondary structure prediction, and 94.8% for three-state transmembrane span prediction. These accuracies are comparable to state-of-the-art predictors of secondary structure (e.g., Psipred) or transmembrane placement (e.g., OCTOPUS). The method is available as web server and for download at www.meilerlab.org. Copyright © 2013 Wiley Periodicals, Inc.

  17. Lewis Structures Are Models for Predicting Molecular Structure, Not Electronic Structure

    NASA Astrophysics Data System (ADS)

    Purser, Gordon H.

    1999-07-01

    This article argues against a close relationship between Lewis dot structures and electron structure obtained from quantum mechanical calculations. Lewis structures are a powerful tool for structure prediction, though they are classical models of bonding and do not predict electronic structure. The "best" Lewis structures are those that, when combined with the VSEPR model, allow the accurate prediction of molecular properties, such as polarity, bond length, bond angle, and bond strength. These structures are achieved by minimizing formal charges within the molecule, even if it requires an expanded octet on atoms beyond the second period. Lewis structures that show an expanded octet do not imply full d-orbital involvement in the bonding. They suggest that the presence of low-lying d-orbitals is important in producing observed molecular structures. Based on this work, the presence of electron density, not a large separation in charge, is responsible for the short bond lengths and large angles in species containing nonmetal atoms from beyond the second period. This result contradicts results obtained from natural population analysis, a method that attempts to derive Lewis structures from molecular orbital calculations.

  18. Structure prediction: Encoding evolution of porous solids

    NASA Astrophysics Data System (ADS)

    Mellot-Draznieks, Caroline; Cheetham, Anthony K.

    2017-01-01

    The design and prediction of network topology is challenging, even when the components' principle interactions are strong. Now, frameworks with relatively weak 'chiral recognition' between organic building blocks have been synthesized and rationalized in silico -- an important development in the reticular synthesis of molecular crystals.

  19. Predicting Career Advancement with Structural Equation Modelling

    ERIC Educational Resources Information Center

    Heimler, Ronald; Rosenberg, Stuart; Morote, Elsa-Sofia

    2012-01-01

    Purpose: The purpose of this paper is to use the authors' prior findings concerning basic employability skills in order to determine which skills best predict career advancement potential. Design/methodology/approach: Utilizing survey responses of human resource managers, the employability skills showing the largest relationships to career…

  20. Predicting Career Advancement with Structural Equation Modelling

    ERIC Educational Resources Information Center

    Heimler, Ronald; Rosenberg, Stuart; Morote, Elsa-Sofia

    2012-01-01

    Purpose: The purpose of this paper is to use the authors' prior findings concerning basic employability skills in order to determine which skills best predict career advancement potential. Design/methodology/approach: Utilizing survey responses of human resource managers, the employability skills showing the largest relationships to career…

  1. Prediction of Protein Structure Using Surface Accessibility Data

    PubMed Central

    Hartlmüller, Christoph; Göbl, Christoph

    2016-01-01

    Abstract An approach to the de novo structure prediction of proteins is described that relies on surface accessibility data from NMR paramagnetic relaxation enhancements by a soluble paramagnetic compound (sPRE). This method exploits the distance‐to‐surface information encoded in the sPRE data in the chemical shift‐based CS‐Rosetta de novo structure prediction framework to generate reliable structural models. For several proteins, it is demonstrated that surface accessibility data is an excellent measure of the correct protein fold in the early stages of the computational folding algorithm and significantly improves accuracy and convergence of the standard Rosetta structure prediction approach. PMID:27560616

  2. Precision Imaging: more descriptive, predictive and integrative imaging.

    PubMed

    Frangi, Alejandro F; Taylor, Zeike A; Gooya, Ali

    2016-10-01

    Medical image analysis has grown into a matured field challenged by progress made across all medical imaging technologies and more recent breakthroughs in biological imaging. The cross-fertilisation between medical image analysis, biomedical imaging physics and technology, and domain knowledge from medicine and biology has spurred a truly interdisciplinary effort that stretched outside the original boundaries of the disciplines that gave birth to this field and created stimulating and enriching synergies. Consideration on how the field has evolved and the experience of the work carried out over the last 15 years in our centre, has led us to envision a future emphasis of medical imaging in Precision Imaging. Precision Imaging is not a new discipline but rather a distinct emphasis in medical imaging borne at the cross-roads between, and unifying the efforts behind mechanistic and phenomenological model-based imaging. It captures three main directions in the effort to deal with the information deluge in imaging sciences, and thus achieve wisdom from data, information, and knowledge. Precision Imaging is finally characterised by being descriptive, predictive and integrative about the imaged object. This paper provides a brief and personal perspective on how the field has evolved, summarises and formalises our vision of Precision Imaging for Precision Medicine, and highlights some connections with past research and current trends in the field.

  3. Investigation of threaded fastener structural integrity

    NASA Technical Reports Server (NTRS)

    1977-01-01

    Technical nondestructive evaluation approaches to the determination of fastener integrity were assessed. Existing instruments and methods used to measure stress or strain were examined, with particular interest in fastener shank stress. Industry procedures being followed were evaluated to establish fastener integrity criteria.

  4. Reliability of toxicological determination for predicting ecological integrity in freshwater systems

    SciTech Connect

    Birge, W.J.; Kercher, M.; Zuiderveen, J.

    1994-12-31

    Over an 8-year period, on-site biomonitoring studies were conducted on four freshwater systems that varied in order, gradient, substrate composition and community structure. One objective was to evaluate the reliability of toxicological findings for predicting ecological integrity. Impact from one or more point-source discharges varied among the different systems from slight to severe in effluent receiving areas and decreased incrementally with distance downstream. Studies were performed at 8 or more stations selected for comparable conditions, including upstream reference and downstream recovery areas. On-site toxicological evaluations were performed with 7-day tests using Ceriodaphnia dubia and fathead minnow embryo-larval tests. Test water was changed daily with fresh collections. Ecological conditions were analyzed using the Rapid Bioassessment Protocol III, Brillouin and Shannon-Weaver indices, cluster analysis and traditional methods (e.q., species richness, diversity, functional groups). In streams with heavy to extreme impact near the effluent outfall, fathead minnow toxicity data correlated significantly with ecological parameters, giving good predictability of ecological integrity. However, in other systems, toxicological endpoints were marginal to unreliable in predicting slight to moderate ecological impact or initial stages of recovery. Attrition of macroinvertebrate species by 20 to 30% resulted without observing consistent trends in toxicity. Neither biodiversity nor abundance of aquatic life could be predicted with confidence when the pattern of ecological impact was not decisive.

  5. Neural network definitions of highly predictable protein secondary structure classes

    SciTech Connect

    Lapedes, A. |; Steeg, E.; Farber, R.

    1994-02-01

    We use two co-evolving neural networks to determine new classes of protein secondary structure which are significantly more predictable from local amino sequence than the conventional secondary structure classification. Accurate prediction of the conventional secondary structure classes: alpha helix, beta strand, and coil, from primary sequence has long been an important problem in computational molecular biology. Neural networks have been a popular method to attempt to predict these conventional secondary structure classes. Accuracy has been disappointingly low. The algorithm presented here uses neural networks to similtaneously examine both sequence and structure data, and to evolve new classes of secondary structure that can be predicted from sequence with significantly higher accuracy than the conventional classes. These new classes have both similarities to, and differences with the conventional alpha helix, beta strand and coil.

  6. Prediction of chemical carcinogenicity from molecular structure.

    PubMed

    Sun, Hongmao

    2004-01-01

    Carcinogens represent a serious threat to human health. In vivo determination of carcinogenicity is time-consuming and expensive, thus in silico models to predict chemical carcinogenicity are highly desirable for virtual screening of compound libraries of both pharmaceutically and other commercially interesting molecules. In the present study, a PLS-DA (partial least squares discriminant analysis) model was developed to predict carcinogenicities in each of four rodent models: male mouse (MM), female mouse (FM), male rat (MR), and female rat (FR). The data set that was used contained over 520 compounds from both the NTP and the FDA databases. All the models were built from the same molecular descriptor system, which is based on atom typing [Sun, H. J. Chem. Inf. Comput. Sci. 2004, 44, 748-757], enabling the comparison of atomic contributions to carcinogenicity with respect to species and gender. Using four components, the models were able to achieve excellent fitting and prediction, with r(2) = 0.987 and q(2) = 0.944 for MM, r(2) = 0.985 and q(2) = 0.950 for FM, r(2) = 0.989 and q(2) = 0.962 for MR, and r(2) = 0.990 and q(2) = 0.965 for FR. The models were further validated by response permutation testing and external validation, and the results indicated that the models were both statistically significant and predictive. Variable influence on projection (VIP) analysis identified the key atom types and fragments that contributed to carcinogenicities and response differences across species and gender.

  7. Fatigue Prediction for Composite Materials and Structures

    DTIC Science & Technology

    2005-10-01

    Eugenio OÑATE CIMNE (International Center for Numerical Methods in Engineering) Building C-1, Campus Nord UPC -C/ Gran Capitán s/n 08034 Barcelona...SPAIN * salomon@cimne.upc.edu ABSTRACT The objective of this paper is to present a new computational methodology for predicting the durability of... methodology is validated using experimental data from tests on CFRR composite material samples. 1.0 INTRODUCTION Fatigue is defined as "the process

  8. Protein structure prediction from sequence variation

    PubMed Central

    Marks, Debora S; Hopf, Thomas A; Sander, Chris

    2015-01-01

    Genomic sequences contain rich evolutionary information about functional constraints on macromolecules such as proteins. This information can be efficiently mined to detect evolutionary couplings between residues in proteins and address the long-standing challenge to compute protein three-dimensional structures from amino acid sequences. Substantial progress has recently been made on this problem owing to the explosive growth in available sequences and the application of global statistical methods. In addition to three-dimensional structure, the improved understanding of covariation may help identify functional residues involved in ligand binding, protein-complex formation and conformational changes. We expect computation of covariation patterns to complement experimental structural biology in elucidating the full spectrum of protein structures, their functional interactions and evolutionary dynamics. PMID:23138306

  9. A manufacturer's approach to ensure long term structural integrity

    NASA Technical Reports Server (NTRS)

    Ansell, Hans; Fredriksson, Billy; Holm, Ingvar

    1992-01-01

    The main features of the design concepts for the Saab 340 and Saab 2000 aircraft are described with respect to structural integrity and high reliability. Also described is the approach taken at Saab Aircraft to ensure structural integrity and high reliability. The concepts of global and local loads and sequences, and the fatigue and damage tolerance sizing and their verification are discussed. Also described is quality assurance in the production and structural maintenance program. Structural repair and feedback from operators are also covered.

  10. A manufacturer's approach to ensure long term structural integrity

    NASA Technical Reports Server (NTRS)

    Ansell, Hans; Fredriksson, Billy; Holm, Ingvar

    1992-01-01

    The main features of the design concepts for the Saab 340 and Saab 2000 aircraft are described with respect to structural integrity and high reliability. Also described is the approach taken at Saab Aircraft to ensure structural integrity and high reliability. The concepts of global and local loads and sequences, and the fatigue and damage tolerance sizing and their verification are discussed. Also described is quality assurance in the production and structural maintenance program. Structural repair and feedback from operators are also covered.

  11. Lifetime Reliability Prediction of Ceramic Structures Under Transient Thermomechanical Loads

    NASA Technical Reports Server (NTRS)

    Nemeth, Noel N.; Jadaan, Osama J.; Gyekenyesi, John P.

    2005-01-01

    An analytical methodology is developed to predict the probability of survival (reliability) of ceramic components subjected to harsh thermomechanical loads that can vary with time (transient reliability analysis). This capability enables more accurate prediction of ceramic component integrity against fracture in situations such as turbine startup and shutdown, operational vibrations, atmospheric reentry, or other rapid heating or cooling situations (thermal shock). The transient reliability analysis methodology developed herein incorporates the following features: fast-fracture transient analysis (reliability analysis without slow crack growth, SCG); transient analysis with SCG (reliability analysis with time-dependent damage due to SCG); a computationally efficient algorithm to compute the reliability for components subjected to repeated transient loading (block loading); cyclic fatigue modeling using a combined SCG and Walker fatigue law; proof testing for transient loads; and Weibull and fatigue parameters that are allowed to vary with temperature or time. Component-to-component variation in strength (stochastic strength response) is accounted for with the Weibull distribution, and either the principle of independent action or the Batdorf theory is used to predict the effect of multiaxial stresses on reliability. The reliability analysis can be performed either as a function of the component surface (for surface-distributed flaws) or component volume (for volume-distributed flaws). The transient reliability analysis capability has been added to the NASA CARES/ Life (Ceramic Analysis and Reliability Evaluation of Structures/Life) code. CARES/Life was also updated to interface with commercially available finite element analysis software, such as ANSYS, when used to model the effects of transient load histories. Examples are provided to demonstrate the features of the methodology as implemented in the CARES/Life program.

  12. Cancer Pharmacogenomics: Integrating Discoveries in Basic, Clinical and Population Sciences to Advance Predictive Cancer Care

    Cancer.gov

    Cancer Pharmacogenomics: Integrating Discoveries in Basic, Clinical and Population Sciences to Advance Predictive Cancer Care, a 2010 workshop sponsored by the Epidemiology and Genomics Research Program.

  13. Characterization and Prediction of Protein Flexibility Based on Structural Alphabets

    PubMed Central

    Liu, Bin

    2016-01-01

    Motivation. To assist efforts in determining and exploring the functional properties of proteins, it is desirable to characterize and predict protein flexibilities. Results. In this study, the conformational entropy is used as an indicator of the protein flexibility. We first explore whether the conformational change can capture the protein flexibility. The well-defined decoy structures are converted into one-dimensional series of letters from a structural alphabet. Four different structure alphabets, including the secondary structure in 3-class and 8-class, the PB structure alphabet (16-letter), and the DW structure alphabet (28-letter), are investigated. The conformational entropy is then calculated from the structure alphabet letters. Some of the proteins show high correlation between the conformation entropy and the protein flexibility. We then predict the protein flexibility from basic amino acid sequence. The local structures are predicted by the dual-layer model and the conformational entropy of the predicted class distribution is then calculated. The results show that the conformational entropy is a good indicator of the protein flexibility, but false positives remain a problem. The DW structure alphabet performs the best, which means that more subtle local structures can be captured by large number of structure alphabet letters. Overall this study provides a simple and efficient method for the characterization and prediction of the protein flexibility. PMID:27660756

  14. Quaternary structure predictions of transmembrane proteins starting from the monomer: a docking-based approach

    PubMed Central

    Casciari, D; Seeber, M; Fanelli, F

    2006-01-01

    Background We introduce a computational protocol for effective predictions of the supramolecular organization of integral transmembrane proteins, starting from the monomer. Despite the demonstrated constitutive and functional importance of supramolecular assemblies of transmembrane subunits or proteins, effective tools for structure predictions of such assemblies are still lacking. Our computational approach consists in rigid-body docking samplings, starting from the docking of two identical copies of a given monomer. Each docking run is followed by membrane topology filtering and cluster analysis. Prediction of the native oligomer is therefore accomplished by a number of progressive growing steps, each made of one docking run, filtering and cluster analysis. With this approach, knowledge about the oligomerization status of the protein is required neither for improving sampling nor for the filtering step. Furthermore, there are no size-limitations in the systems under study, which are not limited to the transmembrane domains but include also the water-soluble portions. Results Benchmarks of the approach were done on ten homo-oligomeric membrane proteins with known quaternary structure. For all these systems, predictions led to native-like quaternary structures, i.e. with Cα-RMSDs lower than 2.5 Å from the native oligomer, regardless of the resolution of the structural models. Conclusion Collectively, the results of this study emphasize the effectiveness of the prediction protocol that will be extensively challenged in quaternary structure predictions of other integral membrane proteins. PMID:16836758

  15. Revealing how network structure affects accuracy of link prediction

    NASA Astrophysics Data System (ADS)

    Yang, Jin-Xuan; Zhang, Xiao-Dong

    2017-08-01

    Link prediction plays an important role in network reconstruction and network evolution. The network structure affects the accuracy of link prediction, which is an interesting problem. In this paper we use common neighbors and the Gini coefficient to reveal the relation between them, which can provide a good reference for the choice of a suitable link prediction algorithm according to the network structure. Moreover, the statistical analysis reveals correlation between the common neighbors index, Gini coefficient index and other indices to describe the network structure, such as Laplacian eigenvalues, clustering coefficient, degree heterogeneity, and assortativity of network. Furthermore, a new method to predict missing links is proposed. The experimental results show that the proposed algorithm yields better prediction accuracy and robustness to the network structure than existing currently used methods for a variety of real-world networks.

  16. A physical approach to protein structure prediction: CASP4 results

    SciTech Connect

    Crivelli, Silvia; Eskow, Elizabeth; Bader, Brett; Lamberti, Vincent; Byrd, Richard; Schnabel, Robert; Head-Gordon, Teresa

    2001-02-27

    We describe our global optimization method called Stochastic Perturbation with Soft Constraints (SPSC), which uses information from known proteins to predict secondary structure, but not in the tertiary structure predictions or in generating the terms of the physics-based energy function. Our approach is also characterized by the use of an all atom energy function that includes a novel hydrophobic solvation function derived from experiments that shows promising ability for energy discrimination against misfolded structures. We present the results obtained using our SPSC method and energy function for blind prediction in the 4th Critical Assessment of Techniques for Protein Structure Prediction (CASP4) competition, and show that our approach is more effective on targets for which less information from known proteins is available. In fact our SPSC method produced the best prediction for one of the most difficult targets of the competition, a new fold protein of 240 amino acids.

  17. Drug-target interaction prediction from chemical, genomic and pharmacological data in an integrated framework

    PubMed Central

    Yamanishi, Yoshihiro; Kotera, Masaaki; Kanehisa, Minoru; Goto, Susumu

    2010-01-01

    Motivation: In silico prediction of drug–target interactions from heterogeneous biological data is critical in the search for drugs and therapeutic targets for known diseases such as cancers. There is therefore a strong incentive to develop new methods capable of detecting these potential drug–target interactions efficiently. Results: In this article, we investigate the relationship between the chemical space, the pharmacological space and the topology of drug–target interaction networks, and show that drug–target interactions are more correlated with pharmacological effect similarity than with chemical structure similarity. We then develop a new method to predict unknown drug–target interactions from chemical, genomic and pharmacological data on a large scale. The proposed method consists of two steps: (i) prediction of pharmacological effects from chemical structures of given compounds and (ii) inference of unknown drug–target interactions based on the pharmacological effect similarity in the framework of supervised bipartite graph inference. The originality of the proposed method lies in the prediction of potential pharmacological similarity for any drug candidate compounds and in the integration of chemical, genomic and pharmacological data in a unified framework. In the results, we make predictions for four classes of important drug–target interactions involving enzymes, ion channels, GPCRs and nuclear receptors. Our comprehensively predicted drug–target interaction networks enable us to suggest many potential drug–target interactions and to increase research productivity toward genomic drug discovery. Supplementary information: Datasets and all prediction results are available at http://cbio.ensmp.fr/~yyamanishi/pharmaco/. Availability: Softwares are available upon request. Contact: yoshihiro.yamanishi@ensmp.fr PMID:20529913

  18. Integration of Design, Thermal, Structural, and Optical Analysis, Including Thermal Animation

    NASA Technical Reports Server (NTRS)

    Amundsen, Ruth M.

    1993-01-01

    In many industries there has recently been a concerted movement toward 'quality management' and the issue of how to accomplish work more efficiently. Part of this effort is focused on concurrent engineering; the idea of integrating the design and analysis processes so that they are not separate, sequential processes (often involving design rework due to analytical findings) but instead form an integrated system with smooth transfers of information. Presented herein are several specific examples of concurrent engineering methods being carried out at Langley Research Center (LaRC): integration of thermal, structural and optical analyses to predict changes in optical performance based on thermal and structural effects; integration of the CAD design process with thermal and structural analyses; and integration of analysis and presentation by animating the thermal response of a system as an active color map -- a highly effective visual indication of heat flow.

  19. Integrable structure in discrete shell membrane theory

    PubMed Central

    Schief, W. K.

    2014-01-01

    We present natural discrete analogues of two integrable classes of shell membranes. By construction, these discrete shell membranes are in equilibrium with respect to suitably chosen internal stresses and external forces. The integrability of the underlying equilibrium equations is proved by relating the geometry of the discrete shell membranes to discrete O surface theory. We establish connections with generalized barycentric coordinates and nine-point centres and identify a discrete version of the classical Gauss equation of surface theory. PMID:24808755

  20. Structural Prediction and Experimental Verification of Three New Ferroelectric Materials

    NASA Astrophysics Data System (ADS)

    Arbogast, D. J.; Foster, M. C.; Nielson, R. M.; Photinos, P. J.; Abrahams, S. C.

    1999-05-01

    Aminoguanidinium hexafluorozirconate, potassium niobyl silicate and fresnoite are typical members of a growing group of materials predicted to be new ferroelectrics by the application of structural criteria. Following prediction, undergraduate chemistry majors prepare and physics majors measure the dielectric properties of each. Experimental results will be presented for the three title materials in verification of their predicted property. In addition to the structural criteria on which the predictions depend, the circuits built locally and other instrumentation used for measuring ac and dc hysteresis, the thermal and frequency dependence of the dielectric permittivity, the thermal dependence of the spontaneous polarization and also the pyroelectric coefficient will be presented.

  1. Protein Structure and Function Prediction Using I-TASSER.

    PubMed

    Yang, Jianyi; Zhang, Yang

    2015-12-17

    I-TASSER is a hierarchical protocol for automated protein structure prediction and structure-based function annotation. Starting from the amino acid sequence of target proteins, I-TASSER first generates full-length atomic structural models from multiple threading alignments and iterative structural assembly simulations followed by atomic-level structure refinement. The biological functions of the protein, including ligand-binding sites, enzyme commission number, and gene ontology terms, are then inferred from known protein function databases based on sequence and structure profile comparisons. I-TASSER is freely available as both an on-line server and a stand-alone package. This unit describes how to use the I-TASSER protocol to generate structure and function prediction and how to interpret the prediction results, as well as alternative approaches for further improving the I-TASSER modeling quality for distant-homologous and multi-domain protein targets. Copyright © 2015 John Wiley & Sons, Inc.

  2. Integrating remotely sensed fires for predicting deforestation for REDD.

    PubMed

    Armenteras, Dolors; Gibbes, Cerian; Anaya, Jesús A; Dávalos, Liliana M

    2017-06-01

    Fire is an important tool in tropical forest management, as it alters forest composition, structure, and the carbon budget. The United Nations program on Reducing Emissions from Deforestation and Forest Degradation (REDD+) aims to sustainably manage forests, as well as to conserve and enhance their carbon stocks. Despite the crucial role of fire management, decision-making on REDD+ interventions fails to systematically include fires. Here, we address this critical knowledge gap in two ways. First, we review REDD+ projects and programs to assess the inclusion of fires in monitoring, reporting, and verification (MRV) systems. Second, we model the relationship between fire and forest for a pilot site in Colombia using near-real-time (NRT) fire monitoring data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). The literature review revealed fire remains to be incorporated as a key component of MRV systems. Spatially explicit modeling of land use change showed the probability of deforestation declined sharply with increasing distance to the nearest fire the preceding year (multi-year model area under the curve [AUC] 0.82). Deforestation predictions based on the model performed better than the official REDD early-warning system. The model AUC for 2013 and 2014 was 0.81, compared to 0.52 for the early-warning system in 2013 and 0.68 in 2014. This demonstrates NRT fire monitoring is a powerful tool to predict sites of forest deforestation. Applying new, publicly available, and open-access NRT fire data should be an essential element of early-warning systems to detect and prevent deforestation. Our results provide tools for improving both the current MRV systems, and the deforestation early-warning system in Colombia. © 2017 by the Ecological Society of America.

  3. Simultaneous prediction of RNA secondary structure and helix coaxial stacking.

    PubMed

    Shareghi, Pooya; Wang, Yingfeng; Malmberg, Russell; Cai, Liming

    2012-06-11

    RNA secondary structure plays a scaffolding role for RNA tertiary conformation. Accurate secondary structure prediction can not only identify double-stranded helices and single stranded-loops but also help provide information for potential tertiary interaction motifs critical to the 3D conformation. The average accuracy in ab initio prediction remains 70%; performance improvement has only been limited to short RNA sequences. The prediction of tertiary interaction motifs is difficult without multiple, related sequences that are usually not available. This paper presents research that aims to improve the secondary structure prediction performance and to develop a capability to predict coaxial stacking between helices. Coaxial stacking positions two helices on the same axis, a tertiary motif present in almost all junctions that account for a high percentage of RNA tertiary structures. This research identified energetic rules for coaxial stacks and geometric constraints on stack combinations, which were applied to developing an efficient dynamic programming application for simultaneous prediction of secondary structure and coaxial stacking. Results on a number of non-coding RNA data sets, of short and moderately long lengths, show a performance improvement (specially on tRNAs) for secondary structure prediction when compared with existing methods. The program also demonstrates a capability for prediction of coaxial stacking. The significant leap of performance on tRNAs demonstrated in this work suggests that a breakthrough to a higher performance in RNA secondary structure prediction may lie in understanding contributions from tertiary motifs critical to the structure, as such information can be used to constrain geometrically as well as energetically the space of RNA secondary structure.

  4. Simultaneous prediction of RNA secondary structure and helix coaxial stacking

    PubMed Central

    2012-01-01

    Background RNA secondary structure plays a scaffolding role for RNA tertiary conformation. Accurate secondary structure prediction can not only identify double-stranded helices and single stranded-loops but also help provide information for potential tertiary interaction motifs critical to the 3D conformation. The average accuracy in ab initio prediction remains 70%; performance improvement has only been limited to short RNA sequences. The prediction of tertiary interaction motifs is difficult without multiple, related sequences that are usually not available. This paper presents research that aims to improve the secondary structure prediction performance and to develop a capability to predict coaxial stacking between helices. Coaxial stacking positions two helices on the same axis, a tertiary motif present in almost all junctions that account for a high percentage of RNA tertiary structures. Results This research identified energetic rules for coaxial stacks and geometric constraints on stack combinations, which were applied to developing an efficient dynamic programming application for simultaneous prediction of secondary structure and coaxial stacking. Results on a number of non-coding RNA data sets, of short and moderately long lengths, show a performance improvement (specially on tRNAs) for secondary structure prediction when compared with existing methods. The program also demonstrates a capability for prediction of coaxial stacking. Conclusions The significant leap of performance on tRNAs demonstrated in this work suggests that a breakthrough to a higher performance in RNA secondary structure prediction may lie in understanding contributions from tertiary motifs critical to the structure, as such information can be used to constrain geometrically as well as energetically the space of RNA secondary structure. PMID:22759616

  5. Tetrahedron-tiling method for crystal structure prediction

    NASA Astrophysics Data System (ADS)

    Hong, Qi-Jun; Yasi, Joseph; van de Walle, Axel

    2017-07-01

    Reliable and robust methods of predicting the crystal structure of a compound, based only on its chemical composition, is crucial to the study of materials and their applications. Despite considerable ongoing research efforts, crystal structure prediction remains a challenging problem that demands large computational resources. Here we propose an efficient approach for first-principles crystal structure prediction. The new method explores and finds crystal structures by tiling together elementary tetrahedra that are energetically favorable and geometrically matching each other. This approach has three distinguishing features: a favorable building unit, an efficient calculation of local energy, and a stochastic Monte Carlo simulation of crystal growth. By applying the method to the crystal structure prediction of various materials, we demonstrate its validity and potential as a promising alternative to current methods.

  6. Direct-Coupling Analysis of nucleotide coevolution facilitates RNA secondary and tertiary structure prediction.

    PubMed

    De Leonardis, Eleonora; Lutz, Benjamin; Ratz, Sebastian; Cocco, Simona; Monasson, Rémi; Schug, Alexander; Weigt, Martin

    2015-12-02

    Despite the biological importance of non-coding RNA, their structural characterization remains challenging. Making use of the rapidly growing sequence databases, we analyze nucleotide coevolution across homologous sequences via Direct-Coupling Analysis to detect nucleotide-nucleotide contacts. For a representative set of riboswitches, we show that the results of Direct-Coupling Analysis in combination with a generalized Nussinov algorithm systematically improve the results of RNA secondary structure prediction beyond traditional covariance approaches based on mutual information. Even more importantly, we show that the results of Direct-Coupling Analysis are enriched in tertiary structure contacts. By integrating these predictions into molecular modeling tools, systematically improved tertiary structure predictions can be obtained, as compared to using secondary structure information alone. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  7. Direct-Coupling Analysis of nucleotide coevolution facilitates RNA secondary and tertiary structure prediction

    PubMed Central

    De Leonardis, Eleonora; Lutz, Benjamin; Ratz, Sebastian; Cocco, Simona; Monasson, Rémi; Schug, Alexander; Weigt, Martin

    2015-01-01

    Despite the biological importance of non-coding RNA, their structural characterization remains challenging. Making use of the rapidly growing sequence databases, we analyze nucleotide coevolution across homologous sequences via Direct-Coupling Analysis to detect nucleotide-nucleotide contacts. For a representative set of riboswitches, we show that the results of Direct-Coupling Analysis in combination with a generalized Nussinov algorithm systematically improve the results of RNA secondary structure prediction beyond traditional covariance approaches based on mutual information. Even more importantly, we show that the results of Direct-Coupling Analysis are enriched in tertiary structure contacts. By integrating these predictions into molecular modeling tools, systematically improved tertiary structure predictions can be obtained, as compared to using secondary structure information alone. PMID:26420827

  8. Integrating prokaryotes and eukaryotes: DNA transposases in light of structure

    PubMed Central

    Hickman, Alison Burgess; Chandler, Michael; Dyda, Fred

    2011-01-01

    DNA rearrangements are important in genome function and evolution. Genetic material can be rearranged inadvertently during processes such as DNA repair, or can be moved in a controlled manner by enzymes specifically dedicated to the task. DNA transposases comprise one class of such enzymes. These move DNA segments known as transposons to new locations, without the need for sequence homology between transposon and target site. Several biochemically distinct pathways have evolved for DNA transposition, and genetic and biochemical studies have provided valuable insights into many of these. However, structural information on transposases – particularly with DNA substrates – has proven elusive in most cases. On the other hand, large-scale genome sequencing projects have led to an explosion in the number of annotated prokaryotic and eukaryotic mobile elements. Here, we briefly review biochemical and mechanistic aspects of DNA transposition, and propose that integrating sequence information with structural information using bioinformatics tools such as secondary structure prediction and protein threading can lead not only to an additional level of understanding but possibly also to testable hypotheses regarding transposition mechanisms. Detailed understanding of transposition pathways is a prerequisite for the long-term goal of exploiting DNA transposons as genetic tools and as a basis for genetic medical applications. PMID:20067338

  9. Structure and stability prediction of compounds with evolutionary algorithms.

    PubMed

    Revard, Benjamin C; Tipton, William W; Hennig, Richard G

    2014-01-01

    Crystal structure prediction is a long-standing challenge in the physical sciences. In recent years, much practical success has been had by framing it as a global optimization problem, leveraging the existence of increasingly robust and accurate free energy calculations. This optimization problem has often been solved using evolutionary algorithms (EAs). However, many choices are possible when designing an EA for structure prediction, and innovation in the field is ongoing. We review the current state of evolutionary algorithms for crystal structure and composition prediction and discuss the details of methodological and algorithmic choices. Finally, we review the application of these algorithms to many systems of practical and fundamental scientific interest.

  10. Integration of Multi-Modal Biomedical Data to Predict Cancer Grade and Patient Survival.

    PubMed

    Phan, John H; Hoffman, Ryan; Kothari, Sonal; Wu, Po-Yen; Wang, May D

    2016-02-01

    The Big Data era in Biomedical research has resulted in large-cohort data repositories such as The Cancer Genome Atlas (TCGA). These repositories routinely contain hundreds of matched patient samples for genomic, proteomic, imaging, and clinical data modalities, enabling holistic and multi-modal integrative analysis of human disease. Using TCGA renal and ovarian cancer data, we conducted a novel investigation of multi-modal data integration by combining histopathological image and RNA-seq data. We compared the performances of two integrative prediction methods: majority vote and stacked generalization. Results indicate that integration of multiple data modalities improves prediction of cancer grade and outcome. Specifically, stacked generalization, a method that integrates multiple data modalities to produce a single prediction result, outperforms both single-data-modality prediction and majority vote. Moreover, stacked generalization reveals the contribution of each data modality (and specific features within each data modality) to the final prediction result and may provide biological insights to explain prediction performance.

  11. How Neighborhood Poverty Structures Types and Levels of Social Integration.

    PubMed

    Marcus, Andrea Fleisch; Echeverria, Sandra E; Holland, Bart K; Abraido-Lanza, Ana F; Passannante, Marian R

    2015-09-01

    Social integration is fundamental to health and well-being. However, few studies have explored how neighborhood contexts pattern types and levels of social integration that individuals experience. We examined how neighborhood poverty structures two dimensions of social integration: integration with neighbors and social integration more generally. Using data from the United States Third National Health and Nutrition Examination Survey, we linked study participants to percent poverty in their neighborhood of residence (N = 16,040). Social integration was assessed using a modified Social Network Index and neighborhood integration based on yearly visits with neighbors. We fit multivariate logistic regression models that accounted for the complex survey design. Living in high poverty neighborhoods was associated with lower social integration but higher visits with neighbors. Neighborhood poverty distinctly patterns social integration, demonstrating that contexts shape the extent and quality of social relationships.

  12. Ensemble-based prediction of RNA secondary structures.

    PubMed

    Aghaeepour, Nima; Hoos, Holger H

    2013-04-24

    Accurate structure prediction methods play an important role for the understanding of RNA function. Energy-based, pseudoknot-free secondary structure prediction is one of the most widely used and versatile approaches, and improved methods for this task have received much attention over the past five years. Despite the impressive progress that as been achieved in this area, existing evaluations of the prediction accuracy achieved by various algorithms do not provide a comprehensive, statistically sound assessment. Furthermore, while there is increasing evidence that no prediction algorithm consistently outperforms all others, no work has been done to exploit the complementary strengths of multiple approaches. In this work, we present two contributions to the area of RNA secondary structure prediction. Firstly, we use state-of-the-art, resampling-based statistical methods together with a previously published and increasingly widely used dataset of high-quality RNA structures to conduct a comprehensive evaluation of existing RNA secondary structure prediction procedures. The results from this evaluation clarify the performance relationship between ten well-known existing energy-based pseudoknot-free RNA secondary structure prediction methods and clearly demonstrate the progress that has been achieved in recent years. Secondly, we introduce AveRNA, a generic and powerful method for combining a set of existing secondary structure prediction procedures into an ensemble-based method that achieves significantly higher prediction accuracies than obtained from any of its component procedures. Our new, ensemble-based method, AveRNA, improves the state of the art for energy-based, pseudoknot-free RNA secondary structure prediction by exploiting the complementary strengths of multiple existing prediction procedures, as demonstrated using a state-of-the-art statistical resampling approach. In addition, AveRNA allows an intuitive and effective control of the trade-off between

  13. Ensemble-based prediction of RNA secondary structures

    PubMed Central

    2013-01-01

    Background Accurate structure prediction methods play an important role for the understanding of RNA function. Energy-based, pseudoknot-free secondary structure prediction is one of the most widely used and versatile approaches, and improved methods for this task have received much attention over the past five years. Despite the impressive progress that as been achieved in this area, existing evaluations of the prediction accuracy achieved by various algorithms do not provide a comprehensive, statistically sound assessment. Furthermore, while there is increasing evidence that no prediction algorithm consistently outperforms all others, no work has been done to exploit the complementary strengths of multiple approaches. Results In this work, we present two contributions to the area of RNA secondary structure prediction. Firstly, we use state-of-the-art, resampling-based statistical methods together with a previously published and increasingly widely used dataset of high-quality RNA structures to conduct a comprehensive evaluation of existing RNA secondary structure prediction procedures. The results from this evaluation clarify the performance relationship between ten well-known existing energy-based pseudoknot-free RNA secondary structure prediction methods and clearly demonstrate the progress that has been achieved in recent years. Secondly, we introduce AveRNA, a generic and powerful method for combining a set of existing secondary structure prediction procedures into an ensemble-based method that achieves significantly higher prediction accuracies than obtained from any of its component procedures. Conclusions Our new, ensemble-based method, AveRNA, improves the state of the art for energy-based, pseudoknot-free RNA secondary structure prediction by exploiting the complementary strengths of multiple existing prediction procedures, as demonstrated using a state-of-the-art statistical resampling approach. In addition, AveRNA allows an intuitive and effective

  14. Data integration of structured and unstructured sources for assigning clinical codes to patient stays

    PubMed Central

    Luyckx, Kim; Luyten, Léon; Daelemans, Walter; Van den Bulcke, Tim

    2016-01-01

    Objective Enormous amounts of healthcare data are becoming increasingly accessible through the large-scale adoption of electronic health records. In this work, structured and unstructured (textual) data are combined to assign clinical diagnostic and procedural codes (specifically ICD-9-CM) to patient stays. We investigate whether integrating these heterogeneous data types improves prediction strength compared to using the data types in isolation. Methods Two separate data integration approaches were evaluated. Early data integration combines features of several sources within a single model, and late data integration learns a separate model per data source and combines these predictions with a meta-learner. This is evaluated on data sources and clinical codes from a broad set of medical specialties. Results When compared with the best individual prediction source, late data integration leads to improvements in predictive power (eg, overall F-measure increased from 30.6% to 38.3% for International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnostic codes), while early data integration is less consistent. The predictive strength strongly differs between medical specialties, both for ICD-9-CM diagnostic and procedural codes. Discussion Structured data provides complementary information to unstructured data (and vice versa) for predicting ICD-9-CM codes. This can be captured most effectively by the proposed late data integration approach. Conclusions We demonstrated that models using multiple electronic health record data sources systematically outperform models using data sources in isolation in the task of predicting ICD-9-CM codes over a broad range of medical specialties. PMID:26316458

  15. Data integration of structured and unstructured sources for assigning clinical codes to patient stays.

    PubMed

    Scheurwegs, Elyne; Luyckx, Kim; Luyten, Léon; Daelemans, Walter; Van den Bulcke, Tim

    2016-04-01

    Enormous amounts of healthcare data are becoming increasingly accessible through the large-scale adoption of electronic health records. In this work, structured and unstructured (textual) data are combined to assign clinical diagnostic and procedural codes (specifically ICD-9-CM) to patient stays. We investigate whether integrating these heterogeneous data types improves prediction strength compared to using the data types in isolation. Two separate data integration approaches were evaluated. Early data integration combines features of several sources within a single model, and late data integration learns a separate model per data source and combines these predictions with a meta-learner. This is evaluated on data sources and clinical codes from a broad set of medical specialties. When compared with the best individual prediction source, late data integration leads to improvements in predictive power (eg, overall F-measure increased from 30.6% to 38.3% for International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnostic codes), while early data integration is less consistent. The predictive strength strongly differs between medical specialties, both for ICD-9-CM diagnostic and procedural codes. Structured data provides complementary information to unstructured data (and vice versa) for predicting ICD-9-CM codes. This can be captured most effectively by the proposed late data integration approach. We demonstrated that models using multiple electronic health record data sources systematically outperform models using data sources in isolation in the task of predicting ICD-9-CM codes over a broad range of medical specialties. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  16. Predicting drug-target interactions by dual-network integrated logistic matrix factorization

    PubMed Central

    Hao, Ming; Bryant, Stephen H.; Wang, Yanli

    2017-01-01

    In this work, we propose a dual-network integrated logistic matrix factorization (DNILMF) algorithm to predict potential drug-target interactions (DTI). The prediction procedure consists of four steps: (1) inferring new drug/target profiles and constructing profile kernel matrix; (2) diffusing drug profile kernel matrix with drug structure kernel matrix; (3) diffusing target profile kernel matrix with target sequence kernel matrix; and (4) building DNILMF model and smoothing new drug/target predictions based on their neighbors. We compare our algorithm with the state-of-the-art method based on the benchmark dataset. Results indicate that the DNILMF algorithm outperforms the previously reported approaches in terms of AUPR (area under precision-recall curve) and AUC (area under curve of receiver operating characteristic) based on the 5 trials of 10-fold cross-validation. We conclude that the performance improvement depends on not only the proposed objective function, but also the used nonlinear diffusion technique which is important but under studied in the DTI prediction field. In addition, we also compile a new DTI dataset for increasing the diversity of currently available benchmark datasets. The top prediction results for the new dataset are confirmed by experimental studies or supported by other computational research. PMID:28079135

  17. Predicting drug-target interactions by dual-network integrated logistic matrix factorization

    NASA Astrophysics Data System (ADS)

    Hao, Ming; Bryant, Stephen H.; Wang, Yanli

    2017-01-01

    In this work, we propose a dual-network integrated logistic matrix factorization (DNILMF) algorithm to predict potential drug-target interactions (DTI). The prediction procedure consists of four steps: (1) inferring new drug/target profiles and constructing profile kernel matrix; (2) diffusing drug profile kernel matrix with drug structure kernel matrix; (3) diffusing target profile kernel matrix with target sequence kernel matrix; and (4) building DNILMF model and smoothing new drug/target predictions based on their neighbors. We compare our algorithm with the state-of-the-art method based on the benchmark dataset. Results indicate that the DNILMF algorithm outperforms the previously reported approaches in terms of AUPR (area under precision-recall curve) and AUC (area under curve of receiver operating characteristic) based on the 5 trials of 10-fold cross-validation. We conclude that the performance improvement depends on not only the proposed objective function, but also the used nonlinear diffusion technique which is important but under studied in the DTI prediction field. In addition, we also compile a new DTI dataset for increasing the diversity of currently available benchmark datasets. The top prediction results for the new dataset are confirmed by experimental studies or supported by other computational research.

  18. Structural basis for retroviral integration into nucleosomes.

    PubMed

    Maskell, Daniel P; Renault, Ludovic; Serrao, Erik; Lesbats, Paul; Matadeen, Rishi; Hare, Stephen; Lindemann, Dirk; Engelman, Alan N; Costa, Alessandro; Cherepanov, Peter

    2015-07-16

    Retroviral integration is catalysed by a tetramer of integrase (IN) assembled on viral DNA ends in a stable complex, known as the intasome. How the intasome interfaces with chromosomal DNA, which exists in the form of nucleosomal arrays, is currently unknown. Here we show that the prototype foamy virus (PFV) intasome is proficient at stable capture of nucleosomes as targets for integration. Single-particle cryo-electron microscopy reveals a multivalent intasome-nucleosome interface involving both gyres of nucleosomal DNA and one H2A-H2B heterodimer. While the histone octamer remains intact, the DNA is lifted from the surface of the H2A-H2B heterodimer to allow integration at strongly preferred superhelix location ±3.5 positions. Amino acid substitutions disrupting these contacts impinge on the ability of the intasome to engage nucleosomes in vitro and redistribute viral integration sites on the genomic scale. Our findings elucidate the molecular basis for nucleosome capture by the viral DNA recombination machinery and the underlying nucleosome plasticity that allows integration.

  19. Integrated Control Using the SOFFT Control Structure

    NASA Technical Reports Server (NTRS)

    Halyo, Nesim

    1996-01-01

    The need for integrated/constrained control systems has become clearer as advanced aircraft introduced new coupled subsystems such as new propulsion subsystems with thrust vectoring and new aerodynamic designs. In this study, we develop an integrated control design methodology which accomodates constraints among subsystem variables while using the Stochastic Optimal Feedforward/Feedback Control Technique (SOFFT) thus maintaining all the advantages of the SOFFT approach. The Integrated SOFFT Control methodology uses a centralized feedforward control and a constrained feedback control law. The control thus takes advantage of the known coupling among the subsystems while maintaining the identity of subsystems for validation purposes and the simplicity of the feedback law to understand the system response in complicated nonlinear scenarios. The Variable-Gain Output Feedback Control methodology (including constant gain output feedback) is extended to accommodate equality constraints. A gain computation algorithm is developed. The designer can set the cross-gains between two variables or subsystems to zero or another value and optimize the remaining gains subject to the constraint. An integrated control law is designed for a modified F-15 SMTD aircraft model with coupled airframe and propulsion subsystems using the Integrated SOFFT Control methodology to produce a set of desired flying qualities.

  20. Structural class prediction of protein using novel feature extraction method from chaos game representation of predicted secondary structure.

    PubMed

    Zhang, Lichao; Kong, Liang; Han, Xiaodong; Lv, Jinfeng

    2016-07-07

    Protein structural class prediction plays an important role in protein structure and function analysis, drug design and many other biological applications. Extracting good representation from protein sequence is fundamental for this prediction task. In recent years, although several secondary structure based feature extraction strategies have been specially proposed for low-similarity protein sequences, the prediction accuracy still remains limited. To explore the potential of secondary structure information, this study proposed a novel feature extraction method from the chaos game representation of predicted secondary structure to mainly capture sequence order information and secondary structure segments distribution information in a given protein sequence. Several kinds of prediction accuracies obtained by the jackknife test are reported on three widely used low-similarity benchmark datasets (25PDB, 1189 and 640). Compared with the state-of-the-art prediction methods, the proposed method achieves the highest overall accuracies on all the three datasets. The experimental results confirm that the proposed feature extraction method is effective for accurate prediction of protein structural class. Moreover, it is anticipated that the proposed method could be extended to other graphical representations of protein sequence and be helpful in future research. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. Protein contact prediction by integrating joint evolutionary coupling analysis and supervised learning.

    PubMed

    Ma, Jianzhu; Wang, Sheng; Wang, Zhiyong; Xu, Jinbo

    2015-11-01

    Protein contact prediction is important for protein structure and functional study. Both evolutionary coupling (EC) analysis and supervised machine learning methods have been developed, making use of different information sources. However, contact prediction is still challenging especially for proteins without a large number of sequence homologs. This article presents a group graphical lasso (GGL) method for contact prediction that integrates joint multi-family EC analysis and supervised learning to improve accuracy on proteins without many sequence homologs. Different from existing single-family EC analysis that uses residue coevolution information in only the target protein family, our joint EC analysis uses residue coevolution in both the target family and its related families, which may have divergent sequences but similar folds. To implement this, we model a set of related protein families using Gaussian graphical models and then coestimate their parameters by maximum-likelihood, subject to the constraint that these parameters shall be similar to some degree. Our GGL method can also integrate supervised learning methods to further improve accuracy. Experiments show that our method outperforms existing methods on proteins without thousands of sequence homologs, and that our method performs better on both conserved and family-specific contacts. See http://raptorx.uchicago.edu/ContactMap/ for a web server implementing the method. j3xu@ttic.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  2. Objective Eulerian Coherent Structures Predict Drifter Motion

    NASA Astrophysics Data System (ADS)

    Serra, Mattia; Haller, George

    2017-04-01

    Recent results show that Objective Eulerian Coherent Structures (OECSs) (Serra, M. and Haller, G., Chaos 26(5), 2016) reveal the correct, frame-independent locations of instantaneous saddle-type material behavior in unsteady flows. Using an unsteady ocean surface velocity field reconstructed from high-frequency-radar measurements, we compute attracting OECSs in a region of the North-East coast of the US, where drifter trajectories are also available. Remarkably, we find that despite their non-passive and inertial dynamics, drifters align rapidly with nearby attracting OECSs. At the same time, the drifter attractors remain completely hidden in instantaneous streamlines plots and in the Okubo-Weiss field.

  3. WeFold: A Coopetition for Protein Structure Prediction

    PubMed Central

    Khoury, George A.; Liwo, Adam; Khatib, Firas; Zhou, Hongyi; Chopra, Gaurav; Bacardit, Jaume; Bortot, Leandro O.; Faccioli, Rodrigo A.; Deng, Xin; He, Yi; Krupa, Pawel; Li, Jilong; Mozolewska, Magdalena A.; Sieradzan, Adam K.; Smadbeck, James; Wirecki, Tomasz; Cooper, Seth; Flatten, Jeff; Xu, Kefan; Baker, David; Cheng, Jianlin; Delbem, Alexandre C. B.; Floudas, Christodoulos A.; Keasar, Chen; Levitt, Michael; Popović, Zoran; Scheraga, Harold A.; Skolnick, Jeffrey; Crivelli, Silvia N.; Players, Foldit

    2014-01-01

    The protein structure prediction problem continues to elude scientists. Despite the introduction of many methods, only modest gains were made over the last decade for certain classes of prediction targets. To address this challenge, a social-media based worldwide collaborative effort, named WeFold, was undertaken by thirteen labs. During the collaboration, the labs were simultaneously competing with each other. Here, we present the first attempt at “coopetition” in scientific research applied to the protein structure prediction and refinement problems. The coopetition was possible by allowing the participating labs to contribute different components of their protein structure prediction pipelines and create new hybrid pipelines that they tested during CASP10. This manuscript describes both successes and areas needing improvement as identified throughout the first WeFold experiment and discusses the efforts that are underway to advance this initiative. A footprint of all contributions and structures are publicly accessible at http://www.wefold.org. PMID:24677212

  4. WeFold: a coopetition for protein structure prediction.

    PubMed

    Khoury, George A; Liwo, Adam; Khatib, Firas; Zhou, Hongyi; Chopra, Gaurav; Bacardit, Jaume; Bortot, Leandro O; Faccioli, Rodrigo A; Deng, Xin; He, Yi; Krupa, Pawel; Li, Jilong; Mozolewska, Magdalena A; Sieradzan, Adam K; Smadbeck, James; Wirecki, Tomasz; Cooper, Seth; Flatten, Jeff; Xu, Kefan; Baker, David; Cheng, Jianlin; Delbem, Alexandre C B; Floudas, Christodoulos A; Keasar, Chen; Levitt, Michael; Popović, Zoran; Scheraga, Harold A; Skolnick, Jeffrey; Crivelli, Silvia N

    2014-09-01

    The protein structure prediction problem continues to elude scientists. Despite the introduction of many methods, only modest gains were made over the last decade for certain classes of prediction targets. To address this challenge, a social-media based worldwide collaborative effort, named WeFold, was undertaken by 13 labs. During the collaboration, the laboratories were simultaneously competing with each other. Here, we present the first attempt at "coopetition" in scientific research applied to the protein structure prediction and refinement problems. The coopetition was possible by allowing the participating labs to contribute different components of their protein structure prediction pipelines and create new hybrid pipelines that they tested during CASP10. This manuscript describes both successes and areas needing improvement as identified throughout the first WeFold experiment and discusses the efforts that are underway to advance this initiative. A footprint of all contributions and structures are publicly accessible at http://www.wefold.org. © 2014 Wiley Periodicals, Inc.

  5. Fast large-scale clustering of protein structures using Gauss integrals.

    PubMed

    Harder, Tim; Borg, Mikael; Boomsma, Wouter; Røgen, Peter; Hamelryck, Thomas

    2012-02-15

    Clustering protein structures is an important task in structural bioinformatics. De novo structure prediction, for example, often involves a clustering step for finding the best prediction. Other applications include assigning proteins to fold families and analyzing molecular dynamics trajectories. We present Pleiades, a novel approach to clustering protein structures with a rigorous mathematical underpinning. The method approximates clustering based on the root mean square deviation by first mapping structures to Gauss integral vectors--which were introduced by Røgen and co-workers--and subsequently performing K-means clustering. Compared to current methods, Pleiades dramatically improves on the time needed to perform clustering, and can cluster a significantly larger number of structures, while providing state-of-the-art results. The number of low energy structures generated in a typical folding study, which is in the order of 50,000 structures, can be clustered within seconds to minutes.

  6. A predictive structural model for bulk metallic glasses

    PubMed Central

    Laws, K. J.; Miracle, D. B.; Ferry, M.

    2015-01-01

    Great progress has been made in understanding the atomic structure of metallic glasses, but there is still no clear connection between atomic structure and glass-forming ability. Here we give new insights into perhaps the most important question in the field of amorphous metals: how can glass-forming ability be predicted from atomic structure? We give a new approach to modelling metallic glass atomic structures by solving three long-standing problems: we discover a new family of structural defects that discourage glass formation; we impose efficient local packing around all atoms simultaneously; and we enforce structural self-consistency. Fewer than a dozen binary structures satisfy these constraints, but extra degrees of freedom in structures with three or more different atom sizes significantly expand the number of relatively stable, ‘bulk' metallic glasses. The present work gives a new approach towards achieving the long-sought goal of a predictive capability for bulk metallic glasses. PMID:26370667

  7. A predictive structural model for bulk metallic glasses.

    PubMed

    Laws, K J; Miracle, D B; Ferry, M

    2015-09-15

    Great progress has been made in understanding the atomic structure of metallic glasses, but there is still no clear connection between atomic structure and glass-forming ability. Here we give new insights into perhaps the most important question in the field of amorphous metals: how can glass-forming ability be predicted from atomic structure? We give a new approach to modelling metallic glass atomic structures by solving three long-standing problems: we discover a new family of structural defects that discourage glass formation; we impose efficient local packing around all atoms simultaneously; and we enforce structural self-consistency. Fewer than a dozen binary structures satisfy these constraints, but extra degrees of freedom in structures with three or more different atom sizes significantly expand the number of relatively stable, 'bulk' metallic glasses. The present work gives a new approach towards achieving the long-sought goal of a predictive capability for bulk metallic glasses.

  8. Structurally Integrated X-Band Array Development

    DTIC Science & Technology

    2006-10-01

    work in progress towards the development of a very large structural x-band electronically scanned array (ESA). A building block approach that...significant structural testing from coupon through large scale structural validation have been complete and is reported. The active array testing will...mechanical performance, so trades could be used to develop the most promising configuration. This involved evaluating coupons to understand the

  9. Proteochemometric modelling coupled to in silico target prediction: an integrated approach for the simultaneous prediction of polypharmacology and binding affinity/potency of small molecules.

    PubMed

    Paricharak, Shardul; Cortés-Ciriano, Isidro; IJzerman, Adriaan P; Malliavin, Thérèse E; Bender, Andreas

    2015-01-01

    The rampant increase of public bioactivity databases has fostered the development of computational chemogenomics methodologies to evaluate potential ligand-target interactions (polypharmacology) both in a qualitative and quantitative way. Bayesian target prediction algorithms predict the probability of an interaction between a compound and a panel of targets, thus assessing compound polypharmacology qualitatively, whereas structure-activity relationship techniques are able to provide quantitative bioactivity predictions. We propose an integrated drug discovery pipeline combining in silico target prediction and proteochemometric modelling (PCM) for the respective prediction of compound polypharmacology and potency/affinity. The proposed pipeline was evaluated on the retrospective discovery of Plasmodium falciparum DHFR inhibitors. The qualitative in silico target prediction model comprised 553,084 ligand-target associations (a total of 262,174 compounds), covering 3,481 protein targets and used protein domain annotations to extrapolate predictions across species. The prediction of bioactivities for plasmodial DHFR led to a recall value of 79% and a precision of 100%, where the latter high value arises from the structural similarity of plasmodial DHFR inhibitors and T. gondii DHFR inhibitors in the training set. Quantitative PCM models were then trained on a dataset comprising 20 eukaryotic, protozoan and bacterial DHFR sequences, and 1,505 distinct compounds (in total 3,099 data points). The most predictive PCM model exhibited R (2) 0 test and RMSEtest values of 0.79 and 0.59 pIC50 units respectively, which was shown to outperform models based exclusively on compound (R (2) 0 test/RMSEtest = 0.63/0.78) and target information (R (2) 0 test/RMSEtest = 0.09/1.22), as well as inductive transfer knowledge between targets, with respective R (2) 0 test and RMSEtest values of 0.76 and 0.63 pIC50 units. Finally, both methods were integrated to predict the protein

  10. PSPP: A Protein Structure Prediction Pipeline for Computing Clusters

    DTIC Science & Technology

    2009-07-01

    scoring ab initio models are annotated by structural comparison against the Structural Classification of Proteins ( SCOP ) fold database. Furthermore...Protein ( SCOP ) database [11]). Finally, if no matches are made in this search, the 3-D atomic structure of the protein domain must be built ab initio, i.e...Fold recognition/threading [34] [60] PSIPRED Jones Secondary structure prediction [21] [61] Rosetta Baker Ab initio folder [41] [62] SCOP /ASTRAL Chothia

  11. Structural features based genome-wide characterization and prediction of nucleosome organization

    PubMed Central

    2012-01-01

    Background Nucleosome distribution along chromatin dictates genomic DNA accessibility and thus profoundly influences gene expression. However, the underlying mechanism of nucleosome formation remains elusive. Here, taking a structural perspective, we systematically explored nucleosome formation potential of genomic sequences and the effect on chromatin organization and gene expression in S. cerevisiae. Results We analyzed twelve structural features related to flexibility, curvature and energy of DNA sequences. The results showed that some structural features such as DNA denaturation, DNA-bending stiffness, Stacking energy, Z-DNA, Propeller twist and free energy, were highly correlated with in vitro and in vivo nucleosome occupancy. Specifically, they can be classified into two classes, one positively and the other negatively correlated with nucleosome occupancy. These two kinds of structural features facilitated nucleosome binding in centromere regions and repressed nucleosome formation in the promoter regions of protein-coding genes to mediate transcriptional regulation. Based on these analyses, we integrated all twelve structural features in a model to predict more accurately nucleosome occupancy in vivo than the existing methods that mainly depend on sequence compositional features. Furthermore, we developed a novel approach, named DLaNe, that located nucleosomes by detecting peaks of structural profiles, and built a meta predictor to integrate information from different structural features. As a comparison, we also constructed a hidden Markov model (HMM) to locate nucleosomes based on the profiles of these structural features. The result showed that the meta DLaNe and HMM-based method performed better than the existing methods, demonstrating the power of these structural features in predicting nucleosome positions. Conclusions Our analysis revealed that DNA structures significantly contribute to nucleosome organization and influence chromatin structure and gene

  12. An integrated approach to structural genomics.

    PubMed

    Heinemann, U; Frevert, J; Hofmann, K; Illing, G; Maurer, C; Oschkinat, H; Saenger, W

    2000-01-01

    Structural genomics aims at determining a set of protein structures that will represent all domain folds present in the biosphere. These structures can be used as the basis for the homology modelling of the majority of all remaining protein domains or, indeed, proteins. Structural genomics therefore promises to provide a comprehensive structural description of the protein universe. To achieve this, a broad scientific effort is required. The Berlin-based "Protein Structure Factory" (PSF) plans to contribute to this effort by setting up a local infrastructure for the low-cost, high-throughput analysis of soluble human proteins. In close collaboration with the German Human Genome Project (DHGP) protein-coding genes will be expressed in Escherichia coli or yeast. Affinity-tagged proteins will be purified semi-automatically for biophysical characterization and structure analysis by X-ray diffraction methods and NMR spectroscopy. In all steps of the structure analysis process, possibilities for automation, parallelization and standardization will be explored. Major new facilities that are created for the PSF include a robotic station for large-scale protein crystallization, an NMR center and an experimental station for protein crystallography at the synchrotron storage ring BESSY II in Berlin.

  13. Integrated aerodynamic/structural design of a sailplane wing

    NASA Technical Reports Server (NTRS)

    Grossman, B.; Gurdal, Z.; Haftka, R. T.; Strauch, G. J.; Eppard, W. M.

    1986-01-01

    Using lifting-line theory and beam analysis, the geometry (planiform and twist) and composite material structural sizes (skin thickness, spar cap, and web thickness) were designed for a sailplane wing, subject to both structural and aerodynamic constraints. For all elements, the integrated design (simultaneously designing the aerodynamics and the structure) was superior in terms of performance and weight to the sequential design (where the aerodynamic geometry is designed to maximize the performance, following which a structural/aeroelastic design minimizes the weight). Integrated designs produced less rigid, higher aspect ratio wings with favorable aerodynamic/structural interactions.

  14. Efficient pairwise RNA structure prediction using probabilistic alignment constraints in Dynalign

    PubMed Central

    2007-01-01

    Background Joint alignment and secondary structure prediction of two RNA sequences can significantly improve the accuracy of the structural predictions. Methods addressing this problem, however, are forced to employ constraints that reduce computation by restricting the alignments and/or structures (i.e. folds) that are permissible. In this paper, a new methodology is presented for the purpose of establishing alignment constraints based on nucleotide alignment and insertion posterior probabilities. Using a hidden Markov model, posterior probabilities of alignment and insertion are computed for all possible pairings of nucleotide positions from the two sequences. These alignment and insertion posterior probabilities are additively combined to obtain probabilities of co-incidence for nucleotide position pairs. A suitable alignment constraint is obtained by thresholding the co-incidence probabilities. The constraint is integrated with Dynalign, a free energy minimization algorithm for joint alignment and secondary structure prediction. The resulting method is benchmarked against the previous version of Dynalign and against other programs for pairwise RNA structure prediction. Results The proposed technique eliminates manual parameter selection in Dynalign and provides significant computational time savings in comparison to prior constraints in Dynalign while simultaneously providing a small improvement in the structural prediction accuracy. Savings are also realized in memory. In experiments over a 5S RNA dataset with average sequence length of approximately 120 nucleotides, the method reduces computation by a factor of 2. The method performs favorably in comparison to other programs for pairwise RNA structure prediction: yielding better accuracy, on average, and requiring significantly lesser computational resources. Conclusion Probabilistic analysis can be utilized in order to automate the determination of alignment constraints for pairwise RNA structure prediction

  15. 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.

  16. Improving structure-based function prediction using molecular dynamics

    PubMed Central

    Glazer, Dariya S.; Radmer, Randall J.; Altman, Russ B.

    2009-01-01

    Summary The number of molecules with solved three-dimensional structure but unknown function is increasing rapidly. Particularly problematic are novel folds with little detectable similarity to molecules of known function. Experimental assays can determine the functions of such molecules, but are time-consuming and expensive. Computational approaches can identify potential functional sites; however, these approaches generally rely on single static structures and do not use information about dynamics. In fact, structural dynamics can enhance function prediction: we coupled molecular dynamics simulations with structure-based function prediction algorithms that identify Ca2+ binding sites. When applied to 11 challenging proteins, both methods showed substantial improvement in performance, revealing 22 more sites in one case and 12 more in the other, with a modest increase in apparent false positives. Thus, we show that treating molecules as dynamic entities improves the performance of structure-based function prediction methods. PMID:19604472

  17. High-speed prediction of crystal structures for organic molecules

    NASA Astrophysics Data System (ADS)

    Obata, Shigeaki; Goto, Hitoshi

    2015-02-01

    We developed a master-worker type parallel algorithm for allocating tasks of crystal structure optimizations to distributed compute nodes, in order to improve a performance of simulations for crystal structure predictions. The performance experiments were demonstrated on TUT-ADSIM supercomputer system (HITACHI HA8000-tc/HT210). The experimental results show that our parallel algorithm could achieve speed-ups of 214 and 179 times using 256 processor cores on crystal structure optimizations in predictions of crystal structures for 3-aza-bicyclo(3.3.1)nonane-2,4-dione and 2-diazo-3,5-cyclohexadiene-1-one, respectively. We expect that this parallel algorithm is always possible to reduce computational costs of any crystal structure predictions.

  18. 2. View, structures in Systems Integration Laboratory complex, looking north. ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    2. View, structures in Systems Integration Laboratory complex, looking north. The Components Test Laboratory (T-27) is located in the immediate foreground. Immediately uphill to the left of T-27 is the Boiler Chiller Plant (T-28H). To the left of T-28H is the Oxidizer Conditioning Structure (T-28D). Behind the T-28D is the Long-Term Oxidizer Silo (T-28B). The twin gantry structure at the left is the Systems Integration Laboratory (T-28). - Air Force Plant PJKS, Systems Integration Laboratory, Waterton Canyon Road & Colorado Highway 121, Lakewood, Jefferson County, CO

  19. Evaluation of several lightweight stochastic context-free grammars for RNA secondary structure prediction

    PubMed Central

    Dowell, Robin D; Eddy, Sean R

    2004-01-01

    Background RNA secondary structure prediction methods based on probabilistic modeling can be developed using stochastic context-free grammars (SCFGs). Such methods can readily combine different sources of information that can be expressed probabilistically, such as an evolutionary model of comparative RNA sequence analysis and a biophysical model of structure plausibility. However, the number of free parameters in an integrated model for consensus RNA structure prediction can become untenable if the underlying SCFG design is too complex. Thus a key question is, what small, simple SCFG designs perform best for RNA secondary structure prediction? Results Nine different small SCFGs were implemented to explore the tradeoffs between model complexity and prediction accuracy. Each model was tested for single sequence structure prediction accuracy on a benchmark set of RNA secondary structures. Conclusions Four SCFG designs had prediction accuracies near the performance of current energy minimization programs. One of these designs, introduced by Knudsen and Hein in their PFOLD algorithm, has only 21 free parameters and is significantly simpler than the others. PMID:15180907

  20. A new stochastic systems approach to structural integrity

    NASA Technical Reports Server (NTRS)

    Provan, James W.; Farhangdoost, Khalil

    1994-01-01

    This paper develops improved stochastic models for the description of a large variety of fatigue crack growth phenomena that occur in components of considerable importance to the functionality and reliability of complex engineering structures. In essence, the models are based on the McGill-Markov and Closure-Lognormal stochastic processes. Not only do these models have the capability of predicting the statistical dispersion of crack growth rates, they also, by incorporating the concept of crack closure, have the capability of transferring stochastic crack growth properties measured under ideal laboratory conditions to situations of industrial significance, such as those occurring under adverse loading and/or environmental conditions. The primary data required in order to be in a position to estimate the pertinent parameters of these stochastic models are obtained from a statistically significant number of replicate tests. In this paper, both the theory and the experimental technique are illustrated using a Ti-6Al-4V alloy. Finally, important structural integrity, reliability, availability and maintainability concepts are developed and illustrated.

  1. 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

  2. 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.

  3. Full-length RNA structure prediction of the HIV-1 genome reveals a conserved core domain

    PubMed Central

    Sükösd, Zsuzsanna; Andersen, Ebbe S.; Seemann, Stefan E.; Jensen, Mads Krogh; Hansen, Mathias; Gorodkin, Jan; Kjems, Jørgen

    2015-01-01

    A distance constrained secondary structural model of the ≈10 kb RNA genome of the HIV-1 has been predicted but higher-order structures, involving long distance interactions, are currently unknown. We present the first global RNA secondary structure model for the HIV-1 genome, which integrates both comparative structure analysis and information from experimental data in a full-length prediction without distance constraints. Besides recovering known structural elements, we predict several novel structural elements that are conserved in HIV-1 evolution. Our results also indicate that the structure of the HIV-1 genome is highly variable in most regions, with a limited number of stable and conserved RNA secondary structures. Most interesting, a set of long distance interactions form a core organizing structure (COS) that organize the genome into three major structural domains. Despite overlapping protein-coding regions the COS is supported by a particular high frequency of compensatory base changes, suggesting functional importance for this element. This new structural element potentially organizes the whole genome into three major domains protruding from a conserved core structure with potential roles in replication and evolution for the virus. PMID:26476446

  4. Full-length RNA structure prediction of the HIV-1 genome reveals a conserved core domain.

    PubMed

    Sükösd, Zsuzsanna; Andersen, Ebbe S; Seemann, Stefan E; Jensen, Mads Krogh; Hansen, Mathias; Gorodkin, Jan; Kjems, Jørgen

    2015-12-02

    A distance constrained secondary structural model of the ≈10 kb RNA genome of the HIV-1 has been predicted but higher-order structures, involving long distance interactions, are currently unknown. We present the first global RNA secondary structure model for the HIV-1 genome, which integrates both comparative structure analysis and information from experimental data in a full-length prediction without distance constraints. Besides recovering known structural elements, we predict several novel structural elements that are conserved in HIV-1 evolution. Our results also indicate that the structure of the HIV-1 genome is highly variable in most regions, with a limited number of stable and conserved RNA secondary structures. Most interesting, a set of long distance interactions form a core organizing structure (COS) that organize the genome into three major structural domains. Despite overlapping protein-coding regions the COS is supported by a particular high frequency of compensatory base changes, suggesting functional importance for this element. This new structural element potentially organizes the whole genome into three major domains protruding from a conserved core structure with potential roles in replication and evolution for the virus.

  5. Microfabricated structures for integrated DNA analysis.

    PubMed Central

    Burns, M A; Mastrangelo, C H; Sammarco, T S; Man, F P; Webster, J R; Johnsons, B N; Foerster, B; Jones, D; Fields, Y; Kaiser, A R; Burke, D T

    1996-01-01

    Photolithographic micromachining of silicon is a candidate technology for the construction of high-throughput DNA analysis devices. However, the development of complex silicon microfabricated systems has been hindered in part by the lack of a simple, versatile pumping method for integrating individual components. Here we describe a surface-tension-based pump able to move discrete nanoliter drops through enclosed channels using only local heating. This thermocapillary pump can accurately mix, measure, and divide drops by simple electronic control. In addition, we have constructed thermal-cycling chambers, gel electrophoresis channels, and radiolabeled DNA detectors that are compatible with the fabrication of thermocapillary pump channels. Since all of the components are made by conventional photolithographic techniques, they can be assembled into more complex integrated systems. The combination of pump and components into self-contained miniaturized devices may provide significant improvements in DNA analysis speed, portability, and cost. The potential of microfabricated systems lies in the low unit cost of silicon-based construction and in the efficient sample handling afforded by component integration. Images Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 PMID:8643614

  6. Integrating electrostatic adhesion to composite structures

    NASA Astrophysics Data System (ADS)

    Heath, Callum J. C.; Bond, Ian P.; Potter, Kevin D.

    2015-04-01

    Additional functionality within load bearing components holds potential for adding value to a structure, design or product. We consider the adaptation of an established technology, electrostatic adhesion or electroadhesion, for application in glass fibre reinforced polymer (GFRP) composite materials. Electroadhesion uses high potential difference (~2-3 kV) between co-planar electrodes to generate temporary holding forces to both electrically conductive and nonconductive contact surfaces. Using a combination of established fabrication techniques, electroadhesive elements are co-cured within a composite host structure during manufacture. This provides an almost symbiotic relationship between the electroadhesive and the composite structure, with the electroadhesive providing an additional functionality, whilst the epoxy matrix material of the composite acts as a dielectric for the high voltage electrodes of the device. Silicone rubber coated devices have been shown to offer high shear load (85kPa) capability for GFRP components held together using this technique. Through careful control of the connection interface, we consider the incorporation of these devices within complete composite structures for additional functionality. The ability to vary the internal connectivity of structural elements could allow for incremental changes in connectivity between discrete sub-structures, potentially introducing variable stiffness to the global structure.

  7. Brain structure predicts risk for obesity ☆

    PubMed Central

    Smucny, Jason; Cornier, Marc-Andre; Eichman, Lindsay C.; Thomas, Elizabeth A.; Bechtell, Jamie L.; Tregellas, Jason R.

    2014-01-01

    The neurobiology of obesity is poorly understood. Here we report findings of a study designed to examine the differences in brain regional gray matter volume in adults recruited as either Obese Prone or Obese Resistant based on self-identification, body mass index, and personal/family weight history. Magnetic resonance imaging was performed in 28 Obese Prone (14 male, 14 female) and 25 Obese Resistant (13 male, 12 female) healthy adults. Voxel-based morphometry was used to identify gray matter volume differences between groups. Gray matter volume was found to be lower in the insula, medial orbitofrontal cortex and cerebellum in Obese Prone, as compared to Obese Resistant individuals. Adjusting for body fat mass did not impact these results. Insula gray matter volume was negatively correlated with leptin concentration and measures of hunger. These findings suggest that individuals at risk for weight gain have structural differences in brain regions known to be important in energy intake regulation, and that these differences, particularly in the insula, may be related to leptin. PMID:22963736

  8. Ceramide structure predicts tumor ganglioside immunosuppressive activity.

    PubMed Central

    Ladisch, S; Li, R; Olson, E

    1994-01-01

    Molecular determinants of biological activity of gangliosides are generally believed to be carbohydrate in nature. However, our studies of immunomodulation by highly purified naturally occurring tumor gangliosides provide another perspective: while the immunosuppressive activity of gangliosides requires the intact molecule (both carbohydrate and ceramide moieties), ceramide structure strikingly influences ganglioside immunosuppressive activity. Molecular species of human neuroblastoma GD2 ganglioside in which the ceramide contains a shorter fatty acyl chain (C16:0, C18:0) were 6- to 10-fold more active than those with a longer fatty acyl chain (C22:0/C24:1, C24:0). These findings were confirmed in studies of ceramide species of human leukemia sialosylparagloboside and murine lymphoma GalNAcGM1b. Gangliosides that contain shorter-chain fatty acids (and are most immunosuppressive) are known to be preferentially shed by tumor cells. Therefore, the results suggest that the tumor cell is optimized to protect itself from host immune destruction by selective shedding of highly active ceramide species of gangliosides. Images PMID:8127917

  9. Analysis and Design of Fuselage Structures Including Residual Strength Prediction Methodology

    NASA Technical Reports Server (NTRS)

    Knight, Norman F.

    1998-01-01

    The goal of this research project is to develop and assess methodologies for the design and analysis of fuselage structures accounting for residual strength. Two primary objectives are included in this research activity: development of structural analysis methodology for predicting residual strength of fuselage shell-type structures; and the development of accurate, efficient analysis, design and optimization tool for fuselage shell structures. Assessment of these tools for robustness, efficient, and usage in a fuselage shell design environment will be integrated with these two primary research objectives.

  10. Solid Propellant Grain Structural Integrity Analysis

    NASA Technical Reports Server (NTRS)

    1973-01-01

    The structural properties of solid propellant rocket grains were studied to determine the propellant resistance to stresses. Grain geometry, thermal properties, mechanical properties, and failure modes are discussed along with design criteria and recommended practices.

  11. DUET: a server for predicting effects of mutations on protein stability using an integrated computational approach.

    PubMed

    Pires, Douglas E V; Ascher, David B; Blundell, Tom L

    2014-07-01

    Cancer genome and other sequencing initiatives are generating extensive data on non-synonymous single nucleotide polymorphisms (nsSNPs) in human and other genomes. In order to understand the impacts of nsSNPs on the structure and function of the proteome, as well as to guide protein engineering, accurate in silicomethodologies are required to study and predict their effects on protein stability. Despite the diversity of available computational methods in the literature, none has proven accurate and dependable on its own under all scenarios where mutation analysis is required. Here we present DUET, a web server for an integrated computational approach to study missense mutations in proteins. DUET consolidates two complementary approaches (mCSM and SDM) in a consensus prediction, obtained by combining the results of the separate methods in an optimized predictor using Support Vector Machines (SVM). We demonstrate that the proposed method improves overall accuracy of the predictions in comparison with either method individually and performs as well as or better than similar methods. The DUET web server is freely and openly available at http://structure.bioc.cam.ac.uk/duet.

  12. Predicting sugar consumption: Application of an integrated dual-process, dual-phase model.

    PubMed

    Hagger, Martin S; Trost, Nadine; Keech, Jacob J; Chan, Derwin K C; Hamilton, Kyra

    2017-09-01

    Excess consumption of added dietary sugars is related to multiple metabolic problems and adverse health conditions. Identifying the modifiable social cognitive and motivational constructs that predict sugar consumption is important to inform behavioral interventions aimed at reducing sugar intake. We tested the efficacy of an integrated dual-process, dual-phase model derived from multiple theories to predict sugar consumption. Using a prospective design, university students (N = 90) completed initial measures of the reflective (autonomous and controlled motivation, intentions, attitudes, subjective norm, perceived behavioral control), impulsive (implicit attitudes), volitional (action and coping planning), and behavioral (past sugar consumption) components of the proposed model. Self-reported sugar consumption was measured two weeks later. A structural equation model revealed that intentions, implicit attitudes, and, indirectly, autonomous motivation to reduce sugar consumption had small, significant effects on sugar consumption. Attitudes, subjective norm, and, indirectly, autonomous motivation to reduce sugar consumption predicted intentions. There were no effects of the planning constructs. Model effects were independent of the effects of past sugar consumption. The model identified the relative contribution of reflective and impulsive components in predicting sugar consumption. Given the prominent role of the impulsive component, interventions that assist individuals in managing cues-to-action and behavioral monitoring are likely to be effective in regulating sugar consumption. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. Evolving networks-Using past structure to predict the future

    NASA Astrophysics Data System (ADS)

    Shang, Ke-ke; Yan, Wei-sheng; Small, Michael

    2016-08-01

    Many previous studies on link prediction have focused on using common neighbors to predict the existence of links between pairs of nodes. More broadly, research into the structural properties of evolving temporal networks and temporal link prediction methods have recently attracted increasing attention. In this study, for the first time, we examine the use of links between a pair of nodes to predict their common neighbors and analyze the relationship between the weight and the structure in static networks, evolving networks, and in the corresponding randomized networks. We propose both new unweighted and weighted prediction methods and use six kinds of real networks to test our algorithms. In unweighted networks, we find that if a pair of nodes connect to each other in the current network, they will have a higher probability to connect common nodes both in the current and the future networks-and the probability will decrease with the increase of the number of neighbors. Furthermore, we find that the original networks have their particular structure and statistical characteristics which benefit link prediction. In weighted networks, the prediction algorithm performance of networks which are dominated by human factors decrease with the decrease of weight and are in general better in static networks. Furthermore, we find that geographical position and link weight both have significant influence on the transport network. Moreover, the evolving financial network has the lowest predictability. In addition, we find that the structure of non-social networks has more robustness than social networks. The structure of engineering networks has both best predictability and also robustness.

  14. Referent Predictability Is Affected by Syntactic Structure: Evidence from Chinese

    ERIC Educational Resources Information Center

    Cheng, Wei; Almor, Amit

    2017-01-01

    This paper examines the effect of syntactic structures on referent predictability. Focusing on stimulus-experiencer (SE) verbs, we conducted two sentence-completion experiments in Chinese by contrasting SE verbs in three structures (active canonical, active "ba," and passive). The results showed that although verb semantics and discourse…

  15. Referent Predictability Is Affected by Syntactic Structure: Evidence from Chinese

    ERIC Educational Resources Information Center

    Cheng, Wei; Almor, Amit

    2017-01-01

    This paper examines the effect of syntactic structures on referent predictability. Focusing on stimulus-experiencer (SE) verbs, we conducted two sentence-completion experiments in Chinese by contrasting SE verbs in three structures (active canonical, active "ba," and passive). The results showed that although verb semantics and discourse…

  16. DSSTox EPA Integrated Risk Information System Structure ...

    EPA Pesticide Factsheets

    EPA's Integrated Risk Information System (IRIS) database was developed and is maintained by EPA's Office of Research and Developement, National Center for Environmental Assessment. IRIS is a database of human health effects that may result from exposure to various substances found in the environment. The information in IRIS is intended for those without extensive training in toxicology, but with some knowledge of sciences. IRIS chemical files contain descriptive and quantitative information in oral reference doses and inhalation reference concentrations and hazard identification, oral slope factors, and oral and inhalation unit risks for carcinogenic effects.

  17. Integrable Structure of Multispecies Zero Range Process

    NASA Astrophysics Data System (ADS)

    Kuniba, Atsuo; Okado, Masato; Watanabe, Satoshi

    2017-06-01

    We present a brief review on integrability of multispecies zero range process in one dimension introduced recently. The topics range over stochastic R matrices of quantum affine algebra U_q (A^{(1)}_n), matrix product construction of stationary states for periodic systems, q-boson representation of Zamolodchikov-Faddeev algebra, etc. We also introduce new commuting Markov transfer matrices having a mixed boundary condition and prove the factorization of a family of R matrices associated with the tetrahedron equation and generalized quantum groups at a special point of the spectral parameter.

  18. Electromechanical co-design and experiment of structurally integrated antenna

    NASA Astrophysics Data System (ADS)

    Zhou, Jinzhu; Huang, Jin; Song, Liwei; Zhang, Dan; Ma, Yunchao

    2015-03-01

    This paper proposes an electromechanical co-design method of a structurally integrated antenna to simultaneously meet mechanical and electrical requirements. The method consists of three stages. The first stage involves finishing an initial design of the microstrip antenna without a facesheet or honeycomb, according to some predefined performances. Subsequently, the facesheet and honeycomb of the structurally integrated antenna are designed using an electromechanical co-design optimization. Based on the results from the first and second stages, a fine full-wave electromagnetic model is developed and the coarse design results are further optimized to meet the electrical performance. The co-design method is applied to the design of a 2.5 GHz structurally integrated antenna, and then the designed antenna is fabricated. Experiments from the mechanical and electrical performances are conducted, and the results confirm the effectiveness of the co-design method. This method shows great promise for the multidisciplinary design of a structurally integrated antenna.

  19. Embedded Sensor Array Development for Composite Structure Integrity Monitoring

    SciTech Connect

    Kumar, A.; Bryan, W. L.; Clonts, L. G.; Franks, S.

    2007-06-26

    The purpose of this Cooperative Research and Development Agreement (CRADA) between UT-Battelle, LLC (the "Contractor") and Accellent Technologies, Inc. (the "Participant") was for the development of an embedded ultrasonic sensor system for composite structure integrity monitoring.

  20. Internally directed cognition and mindfulness: an integrative perspective derived from predictive and reactive control systems theory

    PubMed Central

    Tops, Mattie; Boksem, Maarten A. S.; Quirin, Markus; IJzerman, Hans; Koole, Sander L.

    2013-01-01

    In the present paper, we will apply the predictive and reactive control systems (PARCS) theory as a framework that integrates competing theories of neural substrates of awareness by describing the “default mode network” (DMN) and anterior insula (AI) as parts of two different behavioral and homeostatic control systems. The DMN, a network that becomes active at rest when there is no external stimulation or task to perform, has been implicated in self-reflective awareness and prospection. By contrast, the AI is associated with awareness and task-related attention. This has led to competing theories stressing the role of the DMN in self-awareness vs. the role of interoceptive and emotional information integration in the AI in awareness of the emotional moment. In PARCS, the respective functions of the DMN and AI in a specific control system explains their association with different qualities of awareness, and how mental states can shift from one state (e.g., prospective self-reflection) to the other (e.g., awareness of the emotional moment) depending on the relative dominance of control systems. These shifts between reactive and predictive control are part of processes that enable the intake of novel information, integration of this novel information within existing knowledge structures, and the creation of a continuous personal context in which novel information can be integrated and understood. As such, PARCS can explain key characteristics of mental states, such as their temporal and spatial focus (e.g., a focus on the here and now vs. the future; a first person vs. a third person perspective). PARCS further relates mental states to brain states and functions, such as activation of the DMN or hemispheric asymmetry in frontal cortical functions. Together, PARCS deepens the understanding of a broad range of mental states, including mindfulness, mind wandering, rumination, autobiographical memory, imagery, and the experience of self. PMID:24904455

  1. Fracture control procedures for aircraft structural integrity

    NASA Technical Reports Server (NTRS)

    Wood, H. A.

    1972-01-01

    The application of applied fracture mechanics in the design, analysis, and qualification of aircraft structural systems are reviewed. Recent service experiences are cited. Current trends in high-strength materials application are reviewed with particular emphasis on the manner in which fracture toughness and structural efficiency may affect the material selection process. General fracture control procedures are reviewed in depth with specific reference to the impact of inspectability, structural arrangement, and material on proposed analysis requirements for safe crack growth. The relative impact on allowable design stress is indicated by example. Design criteria, material, and analysis requirements for implementation of fracture control procedures are reviewed together with limitations in current available data techniques. A summary of items which require further study and attention is presented.

  2. Prediction of Protein Structure Using Surface Accessibility Data.

    PubMed

    Hartlmüller, Christoph; Göbl, Christoph; Madl, Tobias

    2016-09-19

    An approach to the de novo structure prediction of proteins is described that relies on surface accessibility data from NMR paramagnetic relaxation enhancements by a soluble paramagnetic compound (sPRE). This method exploits the distance-to-surface information encoded in the sPRE data in the chemical shift-based CS-Rosetta de novo structure prediction framework to generate reliable structural models. For several proteins, it is demonstrated that surface accessibility data is an excellent measure of the correct protein fold in the early stages of the computational folding algorithm and significantly improves accuracy and convergence of the standard Rosetta structure prediction approach. © 2016 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

  3. Predicting Secondary Structural Folding Kinetics for Nucleic Acids

    PubMed Central

    Zhao, Peinan; Zhang, Wen-Bing; Chen, Shi-Jie

    2010-01-01

    Abstract We report a new computational approach to the prediction of RNA secondary structure folding kinetics. In this approach, each elementary kinetic step is represented as the transformation between two secondary structures that differ by a helix. Based on the free energy landscape analysis, we identify three types of dominant pathways and the rate constants for the kinetic steps: 1), formation; 2), disruption of a helix stem; and 3), helix formation with concomitant partial melting of a competing (incompatible) helix. The third pathway, termed the tunneling pathway, is the low-barrier dominant pathway for the conversion between two incompatible helices. Comparisons with experimental data indicate that this new method is quite reliable in predicting the kinetics for RNA secondary structural folding and structural rearrangements. The approach presented here may provide a robust first step for further systematic development of a predictive theory for the folding kinetics for large RNAs. PMID:20409482

  4. Structure Prediction of RNA Loops with a Probabilistic Approach

    PubMed Central

    Li, Jun; Zhang, Jian; Wang, Jun; Li, Wenfei; Wang, Wei

    2016-01-01

    The knowledge of the tertiary structure of RNA loops is important for understanding their functions. In this work we develop an efficient approach named RNApps, specifically designed for predicting the tertiary structure of RNA loops, including hairpin loops, internal loops, and multi-way junction loops. It includes a probabilistic coarse-grained RNA model, an all-atom statistical energy function, a sequential Monte Carlo growth algorithm, and a simulated annealing procedure. The approach is tested with a dataset including nine RNA loops, a 23S ribosomal RNA, and a large dataset containing 876 RNAs. The performance is evaluated and compared with a homology modeling based predictor and an ab initio predictor. It is found that RNApps has comparable performance with the former one and outdoes the latter in terms of structure predictions. The approach holds great promise for accurate and efficient RNA tertiary structure prediction. PMID:27494763

  5. Integration of relational and hierarchical network information for protein function prediction.

    PubMed

    Jiang, Xiaoyu; Nariai, Naoki; Steffen, Martin; Kasif, Simon; Kolaczyk, Eric D

    2008-08-22

    In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO) database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions. We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing. A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor) and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased positive predictive value), and that this increase is

  6. Addressable-Matrix Integrated-Circuit Test Structure

    NASA Technical Reports Server (NTRS)

    Sayah, Hoshyar R.; Buehler, Martin G.

    1991-01-01

    Method of quality control based on use of row- and column-addressable test structure speeds collection of data on widths of resistor lines and coverage of steps in integrated circuits. By use of straightforward mathematical model, line widths and step coverages deduced from measurements of electrical resistances in each of various combinations of lines, steps, and bridges addressable in test structure. Intended for use in evaluating processes and equipment used in manufacture of application-specific integrated circuits.

  7. Space Launch System Integrated Structural Test b-roll

    NASA Image and Video Library

    2017-04-19

    Integrated Structural Test at test stand 4699 at Marshall Space Flight Center: 1. Launch Vehicle Stage Adapter (LVSA) install to 4699 - 00:05 2. Interim Cryogenic Propulsion stage (ICPS) install to 4699 00:20 3. Orion Stage Adapter (OSA) install to 4699 00:56 4. Integrated Structural Test control room 01:10 5. Animation of stacking LVSA, ICPS & OSA in test stand 02:46

  8. Protein structure prediction enhanced with evolutionary diversity : SPEED.

    SciTech Connect

    DeBartolo, J.; Hocky, G.; Wilde, M.; Xu, J.; Freed, K. F.; Sosnick, T. R.; Univ. of Chicago; Toyota Technological Inst. at Chicago

    2010-03-01

    For naturally occurring proteins, similar sequence implies similar structure. Consequently, multiple sequence alignments (MSAs) often are used in template-based modeling of protein structure and have been incorporated into fragment-based assembly methods. Our previous homology-free structure prediction study introduced an algorithm that mimics the folding pathway by coupling the formation of secondary and tertiary structure. Moves in the Monte Carlo procedure involve only a change in a single pair of {phi},{psi} backbone dihedral angles that are obtained from a Protein Data Bank-based distribution appropriate for each amino acid, conditional on the type and conformation of the flanking residues. We improve this method by using MSAs to enrich the sampling distribution, but in a manner that does not require structural knowledge of any protein sequence (i.e., not homologous fragment insertion). In combination with other tools, including clustering and refinement, the accuracies of the predicted secondary and tertiary structures are substantially improved and a global and position-resolved measure of confidence is introduced for the accuracy of the predictions. Performance of the method in the Critical Assessment of Structure Prediction (CASP8) is discussed.

  9. Integrated optical interrogation of micro-structures

    DOEpatents

    Evans, III, Boyd M.; Datskos, Panagiotis G.; Rajic, Slobodan

    2003-01-01

    The invention is an integrated optical sensing element for detecting and measuring changes in position or deflection. A deflectable member, such as a microcantilever, is configured to receive a light beam. A waveguide, such as an optical waveguide or an optical fiber, is positioned to redirect light towards the deflectable member. The waveguide can be incorporated into the deflectable member or disposed adjacent to the deflectable member. Means for measuring the extent of position change or deflection of the deflectable member by receiving the light beam from the deflectable member, such as a photodetector or interferometer, receives the reflected light beam from the deflectable member. Changes in the light beam are correlated to the changes in position or deflection of the deflectable member. A plurality of deflectable members can be arranged in a matrix or an array to provide one or two-dimensional imaging or sensing capabilities.

  10. Clathrate Structure Determination by Combining Crystal Structure Prediction with Computational and Experimental (129) Xe NMR Spectroscopy.

    PubMed

    Selent, Marcin; Nyman, Jonas; Roukala, Juho; Ilczyszyn, Marek; Oilunkaniemi, Raija; Bygrave, Peter J; Laitinen, Risto; Jokisaari, Jukka; Day, Graeme M; Lantto, Perttu

    2017-01-23

    An approach is presented for the structure determination of clathrates using NMR spectroscopy of enclathrated xenon to select from a set of predicted crystal structures. Crystal structure prediction methods have been used to generate an ensemble of putative structures of o- and m-fluorophenol, whose previously unknown clathrate structures have been studied by (129) Xe NMR spectroscopy. The high sensitivity of the (129) Xe chemical shift tensor to the chemical environment and shape of the crystalline cavity makes it ideal as a probe for porous materials. The experimental powder NMR spectra can be used to directly confirm or reject hypothetical crystal structures generated by computational prediction, whose chemical shift tensors have been simulated using density functional theory. For each fluorophenol isomer one predicted crystal structure was found, whose measured and computed chemical shift tensors agree within experimental and computational error margins and these are thus proposed as the true fluorophenol xenon clathrate structures.

  11. Blind Test of Physics-Based Prediction of Protein Structures

    PubMed Central

    Shell, M. Scott; Ozkan, S. Banu; Voelz, Vincent; Wu, Guohong Albert; Dill, Ken A.

    2009-01-01

    We report here a multiprotein blind test of a computer method to predict native protein structures based solely on an all-atom physics-based force field. We use the AMBER 96 potential function with an implicit (GB/SA) model of solvation, combined with replica-exchange molecular-dynamics simulations. Coarse conformational sampling is performed using the zipping and assembly method (ZAM), an approach that is designed to mimic the putative physical routes of protein folding. ZAM was applied to the folding of six proteins, from 76 to 112 monomers in length, in CASP7, a community-wide blind test of protein structure prediction. Because these predictions have about the same level of accuracy as typical bioinformatics methods, and do not utilize information from databases of known native structures, this work opens up the possibility of predicting the structures of membrane proteins, synthetic peptides, or other foldable polymers, for which there is little prior knowledge of native structures. This approach may also be useful for predicting physical protein folding routes, non-native conformations, and other physical properties from amino acid sequences. PMID:19186130

  12. Blind test of physics-based prediction of protein structures.

    PubMed

    Shell, M Scott; Ozkan, S Banu; Voelz, Vincent; Wu, Guohong Albert; Dill, Ken A

    2009-02-01

    We report here a multiprotein blind test of a computer method to predict native protein structures based solely on an all-atom physics-based force field. We use the AMBER 96 potential function with an implicit (GB/SA) model of solvation, combined with replica-exchange molecular-dynamics simulations. Coarse conformational sampling is performed using the zipping and assembly method (ZAM), an approach that is designed to mimic the putative physical routes of protein folding. ZAM was applied to the folding of six proteins, from 76 to 112 monomers in length, in CASP7, a community-wide blind test of protein structure prediction. Because these predictions have about the same level of accuracy as typical bioinformatics methods, and do not utilize information from databases of known native structures, this work opens up the possibility of predicting the structures of membrane proteins, synthetic peptides, or other foldable polymers, for which there is little prior knowledge of native structures. This approach may also be useful for predicting physical protein folding routes, non-native conformations, and other physical properties from amino acid sequences.

  13. Statistical evaluation of improvement in RNA secondary structure prediction

    PubMed Central

    Xu, Zhenjiang; Almudevar, Anthony; Mathews, David H.

    2012-01-01

    With discovery of diverse roles for RNA, its centrality in cellular functions has become increasingly apparent. A number of algorithms have been developed to predict RNA secondary structure. Their performance has been benchmarked by comparing structure predictions to reference secondary structures. Generally, algorithms are compared against each other and one is selected as best without statistical testing to determine whether the improvement is significant. In this work, it is demonstrated that the prediction accuracies of methods correlate with each other over sets of sequences. One possible reason for this correlation is that many algorithms use the same underlying principles. A set of benchmarks published previously for programs that predict a structure common to three or more sequences is statistically analyzed as an example to show that it can be rigorously evaluated using paired two-sample t-tests. Finally, a pipeline of statistical analyses is proposed to guide the choice of data set size and performance assessment for benchmarks of structure prediction. The pipeline is applied using 5S rRNA sequences as an example. PMID:22139940

  14. Global identification predicts gay-male identity integration and well-being among Turkish gay men.

    PubMed

    Koc, Yasin; Vignoles, Vivian L

    2016-12-01

    In most parts of the world, hegemonic masculinity requires men to endorse traditional masculine ideals, one of which is rejection of homosexuality. Wherever hegemonic masculinity favours heterosexuality over homosexuality, gay males may feel under pressure to negotiate their conflicting male gender and gay sexual identities to maintain positive self-perceptions. However, globalization, as a source of intercultural interaction, might provide a beneficial context for people wishing to create alternative masculinities in the face of hegemonic masculinity. Hence, we tested if global identification would predict higher levels of gay-male identity integration, and indirectly subjective well-being, via alternative masculinity representations for gay and male identities. A community sample of 219 gay and bisexual men from Turkey completed the study. Structural equation modelling revealed that global identification positively predicted gay-male identity integration, and indirectly subjective well-being; however, alternative masculinity representations did not mediate this relationship. Our findings illustrate how identity categories in different domains can intersect and affect each other in complex ways. Moreover, we discuss mental health and well-being implications for gay men living in cultures where they experience high levels of prejudice and stigma. © 2016 The British Psychological Society.

  15. 1. View, structures in Systems Integration Laboratory complex, looking northwest. ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    1. View, structures in Systems Integration Laboratory complex, looking northwest. The twin gantry structure in the center is the Systems Integration Laboratory (T-28). To its immediate left in the foreground is a truck well, concrete retaining wall, piping, and stack associated with the oxidizer vault storage area. To the immediate right of T-28 is the concrete Signal Transfer Building (T-28A). At the extreme right is the Long-Term Hydrazine Silo (T-28E). - Air Force Plant PJKS, Systems Integration Laboratory, Waterton Canyon Road & Colorado Highway 121, Lakewood, Jefferson County, CO

  16. Integrating Structure with Power in Battery Materials

    DTIC Science & Technology

    2007-09-01

    LiOTf Glass , Silica Silica Ethox. (30) Bis-A PEO 550 Acrylate PEO 1,000k Alumina Alumina 3.2 Experimental Chemicals were handled in a glove...samples, received from Sartomer Company, Inc., were mixed thoroughly with the appropriate amount of lithium triflate in a glass vial. Dissolution...enhances the structural capacity of the composite. A layer of glass fabric is also included in the design, to ensure electrical isolation of the anode

  17. A Bayesian approach to improved calibration and prediction of groundwater models with structural error

    NASA Astrophysics Data System (ADS)

    Xu, Tianfang; Valocchi, Albert J.

    2015-11-01

    Numerical groundwater flow and solute transport models are usually subject to model structural error due to simplification and/or misrepresentation of the real system, which raises questions regarding the suitability of conventional least squares regression-based (LSR) calibration. We present a new framework that explicitly describes the model structural error statistically in an inductive, data-driven way. We adopt a fully Bayesian approach that integrates Gaussian process error models into the calibration, prediction, and uncertainty analysis of groundwater flow models. We test the usefulness of the fully Bayesian approach with a synthetic case study of the impact of pumping on surface-ground water interaction. We illustrate through this example that the Bayesian parameter posterior distributions differ significantly from parameters estimated by conventional LSR, which does not account for model structural error. For the latter method, parameter compensation for model structural error leads to biased, overconfident prediction under changing pumping condition. In contrast, integrating Gaussian process error models significantly reduces predictive bias and leads to prediction intervals that are more consistent with validation data. Finally, we carry out a generalized LSR recalibration step to assimilate the Bayesian prediction while preserving mass conservation and other physical constraints, using a full error covariance matrix obtained from Bayesian results. It is found that the recalibrated model achieved lower predictive bias compared to the model calibrated using conventional LSR. The results highlight the importance of explicit treatment of model structural error especially in circumstances where subsequent decision-making and risk analysis require accurate prediction and uncertainty quantification.

  18. Integrative Structural Biomechanical Concepts of Ankylosing Spondylitis

    PubMed Central

    Masi, Alfonse T.; Nair, Kalyani; Andonian, Brian J.; Prus, Kristina M.; Kelly, Joseph; Sanchez, Jose R.; Henderson, Jacqueline

    2011-01-01

    Ankylosing spondylitis (AS) is not fully explained by inflammatory processes. Clinical, epidemiological, genetic, and course of disease features indicate additional host-related risk processes and predispositions. Collectively, the pattern of predisposition to onset in adolescent and young adult ages, male preponderance, and widely varied severity of AS is unique among rheumatic diseases. However, this pattern could reflect biomechanical and structural differences between the sexes, naturally occurring musculoskeletal changes over life cycles, and a population polymorphism. During juvenile development, the body is more flexible and weaker than during adolescent maturation and young adulthood, when strengthening and stiffening considerably increase. During middle and later ages, the musculoskeletal system again weakens. The novel concept of an innate axial myofascial hypertonicity reflects basic mechanobiological principles in human function, tissue reactivity, and pathology. However, these processes have been little studied and require critical testing. The proposed physical mechanisms likely interact with recognized immunobiological pathways. The structural biomechanical processes and tissue reactions might possibly precede initiation of other AS-related pathways. Research in the combined structural mechanobiology and immunobiology processes promises to improve understanding of the initiation and perpetuation of AS than prevailing concepts. The combined processes might better explain characteristic enthesopathic and inflammatory processes in AS. PMID:22216409

  19. Integrated aerodynamic-structural-control wing design

    NASA Technical Reports Server (NTRS)

    Rais-Rohani, M.; Haftka, R. T.; Grossman, B.; Unger, E. R.

    1992-01-01

    The aerodynamic-structural-control design of a forward-swept composite wing for a high subsonic transport aircraft is considered. The structural analysis is based on a finite-element method. The aerodynamic calculations are based on a vortex-lattice method, and the control calculations are based on an output feedback control. The wing is designed for minimum weight subject to structural, performance/aerodynamic and control constraints. Efficient methods are used to calculate the control-deflection and control-effectiveness sensitivities which appear as second-order derivatives in the control constraint equations. To suppress the aeroelastic divergence of the forward-swept wing, and to reduce the gross weight of the design aircraft, two separate cases are studied: (1) combined application of aeroelastic tailoring and active controls; and (2) aeroelastic tailoring alone. The results of this study indicated that, for this particular example, aeroelastic tailoring is sufficient for suppressing the aeroelastic divergence, and the use of active controls was not necessary.

  20. Correlating structural order with structural rearrangement in dusty plasma liquids: can structural rearrangement be predicted by static structural information?

    PubMed

    Su, Yen-Shuo; Liu, Yu-Hsuan; I, Lin

    2012-11-09

    Whether the static microstructural order information is strongly correlated with the subsequent structural rearrangement (SR) and their predicting power for SR are investigated experimentally in the quenched dusty plasma liquid with microheterogeneities. The poor local structural order is found to be a good alarm to identify the soft spot and predict the short term SR. For the site with good structural order, the persistent time for sustaining the structural memory until SR has a large mean value but a broad distribution. The deviation of the local structural order from that averaged over nearest neighbors serves as a good second alarm to further sort out the short time SR sites. It has the similar sorting power to that using the temporal fluctuation of the local structural order over a small time interval.

  1. The Evolving Contribution of Mass Spectrometry to Integrative Structural Biology.

    PubMed

    Faini, Marco; Stengel, Florian; Aebersold, Ruedi

    2016-06-01

    Protein complexes are key catalysts and regulators for the majority of cellular processes. Unveiling their assembly and structure is essential to understanding their function and mechanism of action. Although conventional structural techniques such as X-ray crystallography and NMR have solved the structure of important protein complexes, they cannot consistently deal with dynamic and heterogeneous assemblies, limiting their applications to small scale experiments. A novel methodological paradigm, integrative structural biology, aims at overcoming such limitations by combining complementary data sources into a comprehensive structural model. Recent applications have shown that a range of mass spectrometry (MS) techniques are able to generate interaction and spatial restraints (cross-linking MS) information on native complexes or to study the stoichiometry and connectivity of entire assemblies (native MS) rapidly, reliably, and from small amounts of substrate. Although these techniques by themselves do not solve structures, they do provide invaluable structural information and are thus ideally suited to contribute to integrative modeling efforts. The group of Brian Chait has made seminal contributions in the use of mass spectrometric techniques to study protein complexes. In this perspective, we honor the contributions of the Chait group and discuss concepts and milestones of integrative structural biology. We also review recent examples of integration of structural MS techniques with an emphasis on cross-linking MS. We then speculate on future MS applications that would unravel the dynamic nature of protein complexes upon diverse cellular states. Graphical Abstract ᅟ.

  2. SPOT-Seq-RNA: predicting protein-RNA complex structure and RNA-binding function by fold recognition and binding affinity prediction.

    PubMed

    Yang, Yuedong; Zhao, Huiying; Wang, Jihua; Zhou, Yaoqi

    2014-01-01

    RNA-binding proteins (RBPs) play key roles in RNA metabolism and post-transcriptional regulation. Computational methods have been developed separately for prediction of RBPs and RNA-binding residues by machine-learning techniques and prediction of protein-RNA complex structures by rigid or semiflexible structure-to-structure docking. Here, we describe a template-based technique called SPOT-Seq-RNA that integrates prediction of RBPs, RNA-binding residues, and protein-RNA complex structures into a single package. This integration is achieved by combining template-based structure-prediction software, SPARKS X, with binding affinity prediction software, DRNA. This tool yields reasonable sensitivity (46 %) and high precision (84 %) for an independent test set of 215 RBPs and 5,766 non-RBPs. SPOT-Seq-RNA is computationally efficient for genome-scale prediction of RBPs and protein-RNA complex structures. Its application to human genome study has revealed a similar sensitivity and ability to uncover hundreds of novel RBPs beyond simple homology. The online server and downloadable version of SPOT-Seq-RNA are available at http://sparks-lab.org/server/SPOT-Seq-RNA/.

  3. Integrated controls-structures optimization of a large space structure

    NASA Technical Reports Server (NTRS)

    Padula, Sharon L.; Walsh, Joanne L.; Sandridge, Chris A.; Haftka, Raphael T.

    1990-01-01

    A technique for the simultaneous optimization of structural and control elements of a large space structure is developed and demonstrated for a test problem, the NASA COFS-I Mast Flight System. General-purpose control and structural-analysis codes are applied directly to a large detailed model, with realistic objective and constraint functions. The steps in the process (structural optimization, control optimization, and system coordination) are described and illustrated with diagrams; the numerical implementation (using different computers for different steps) is discussed; and results showing significant design improvements in three COFS-I configurations are presented in graphs. When the weights of both structure and power-generating equipment are taken into account, a 40-bay truss design is found to be better than designs with 42 or 44 bays.

  4. Contingency Table Browser − prediction of early stage protein structure

    PubMed Central

    Kalinowska, Barbara; Krzykalski, Artur; Roterman, Irena

    2015-01-01

    The Early Stage (ES) intermediate represents the starting structure in protein folding simulations based on the Fuzzy Oil Drop (FOD) model. The accuracy of FOD predictions is greatly dependent on the accuracy of the chosen intermediate. A suitable intermediate can be constructed using the sequence-structure relationship information contained in the so-called contingency table − this table expresses the likelihood of encountering various structural motifs for each tetrapeptide fragment in the amino acid sequence. The limited accuracy with which such structures could previously be predicted provided the motivation for a more indepth study of the contingency table itself. The Contingency Table Browser is a tool which can visualize, search and analyze the table. Our work presents possible applications of Contingency Table Browser, among them − analysis of specific protein sequences from the point of view of their structural ambiguity. PMID:26664034

  5. Contingency Table Browser - prediction of early stage protein structure.

    PubMed

    Kalinowska, Barbara; Krzykalski, Artur; Roterman, Irena

    2015-01-01

    The Early Stage (ES) intermediate represents the starting structure in protein folding simulations based on the Fuzzy Oil Drop (FOD) model. The accuracy of FOD predictions is greatly dependent on the accuracy of the chosen intermediate. A suitable intermediate can be constructed using the sequence-structure relationship information contained in the so-called contingency table - this table expresses the likelihood of encountering various structural motifs for each tetrapeptide fragment in the amino acid sequence. The limited accuracy with which such structures could previously be predicted provided the motivation for a more indepth study of the contingency table itself. The Contingency Table Browser is a tool which can visualize, search and analyze the table. Our work presents possible applications of Contingency Table Browser, among them - analysis of specific protein sequences from the point of view of their structural ambiguity.

  6. RNA folding: structure prediction, folding kinetics and ion electrostatics.

    PubMed

    Tan, Zhijie; Zhang, Wenbing; Shi, Yazhou; Wang, Fenghua

    2015-01-01

    Beyond the "traditional" functions such as gene storage, transport and protein synthesis, recent discoveries reveal that RNAs have important "new" biological functions including the RNA silence and gene regulation of riboswitch. Such functions of noncoding RNAs are strongly coupled to the RNA structures and proper structure change, which naturally leads to the RNA folding problem including structure prediction and folding kinetics. Due to the polyanionic nature of RNAs, RNA folding structure, stability and kinetics are strongly coupled to the ion condition of solution. The main focus of this chapter is to review the recent progress in the three major aspects in RNA folding problem: structure prediction, folding kinetics and ion electrostatics. This chapter will introduce both the recent experimental and theoretical progress, while emphasize the theoretical modelling on the three aspects in RNA folding.

  7. Toward the Prediction of Organic Hydrate Crystal Structures.

    PubMed

    Hulme, Ashley T; Price, Sarah L

    2007-07-01

    Lattice energy minimization studies on four ordered crystal structures of ice and 22 hydrates of approximately rigid organic molecules (along with 11 corresponding anhydrate structures) were used to establish a model potential scheme, based on the use of a distributed multipole electrostatic model, that can reasonably reproduce the crystal structures. Transferring the empirical repulsion-dispersion potentials for organic oxygen and polar hydrogen atoms to water appears more successful for modeling ice phases than using common water potentials derived from liquid properties. Lattice energy differences are reasonable but quite sensitive to the exact conformation of water and the organic molecule used in the rigid molecule modeling. This potential scheme was used to test a new approach of predicting the crystal structure of 5-azauracil monohydrate (an isolated site hydrate) based on seeking dense crystal packings of 66 5-azauracil···water hydrogen-bonded clusters, derived from an analysis of hydrate hydrogen bond geometries involving the carbonyl- and aza-group acceptors in the Cambridge Structural Database. The known structure was found within 5 kJ mol(-1) of the global minimum in static lattice energy and as the third most stable structure, within 1 kJ mol(-1), when thermal effects at ambient temperature were considered. Thus, although the computational prediction of whether an organic molecule will crystallize in a hydrated form poses many challenges, the prediction of plausible structures for hydrogen-bonded monohydrates is now possible.

  8. A life prediction model for laminated composite structural components

    NASA Technical Reports Server (NTRS)

    Allen, David H.

    1990-01-01

    A life prediction methodology for laminated continuous fiber composites subjected to fatigue loading conditions was developed. A summary is presented of research completed. A phenomenological damage evolution law was formulated for matrix cracking which is independent of stacking sequence. Mechanistic and physical support was developed for the phenomenological evolution law proposed above. The damage evolution law proposed above was implemented to a finite element computer program. And preliminary predictions were obtained for a structural component undergoing fatigue loading induced damage.

  9. Integrating models to predict regional haze from wildland fire.

    Treesearch

    D. McKenzie; S.M. O' Neill; N. Larkin; R.A. Norheim

    2006-01-01

    Visibility impairment from regional haze is a significant problem throughout the continental United States. A substantial portion of regional haze is produced by smoke from prescribed and wildland fires. Here we describe the integration of four simulation models, an array of GIS raster layers, and a set of algorithms for fire-danger calculations into a modeling...

  10. An Integrated and Interdisciplinary Model for Predicting the Risk of Injury and Death in Future Earthquakes.

    PubMed

    Shapira, Stav; Novack, Lena; Bar-Dayan, Yaron; Aharonson-Daniel, Limor

    2016-01-01

    A comprehensive technique for earthquake-related casualty estimation remains an unmet challenge. This study aims to integrate risk factors related to characteristics of the exposed population and to the built environment in order to improve communities' preparedness and response capabilities and to mitigate future consequences. An innovative model was formulated based on a widely used loss estimation model (HAZUS) by integrating four human-related risk factors (age, gender, physical disability and socioeconomic status) that were identified through a systematic review and meta-analysis of epidemiological data. The common effect measures of these factors were calculated and entered to the existing model's algorithm using logistic regression equations. Sensitivity analysis was performed by conducting a casualty estimation simulation in a high-vulnerability risk area in Israel. the integrated model outcomes indicated an increase in the total number of casualties compared with the prediction of the traditional model; with regard to specific injury levels an increase was demonstrated in the number of expected fatalities and in the severely and moderately injured, and a decrease was noted in the lightly injured. Urban areas with higher populations at risk rates were found more vulnerable in this regard. The proposed model offers a novel approach that allows quantification of the combined impact of human-related and structural factors on the results of earthquake casualty modelling. Investing efforts in reducing human vulnerability and increasing resilience prior to an occurrence of an earthquake could lead to a possible decrease in the expected number of casualties.

  11. Algebraic Structure of Cut Feynman Integrals and the Diagrammatic Coaction

    NASA Astrophysics Data System (ADS)

    Abreu, Samuel; Britto, Ruth; Duhr, Claude; Gardi, Einan

    2017-08-01

    We study the algebraic and analytic structure of Feynman integrals by proposing an operation that maps an integral into pairs of integrals obtained from a master integrand and a corresponding master contour. This operation is a coaction. It reduces to the known coaction on multiple polylogarithms, but applies more generally, e.g., to hypergeometric functions. The coaction also applies to generic one-loop Feynman integrals with any configuration of internal and external masses, and in dimensional regularization. In this case, we demonstrate that it can be given a diagrammatic representation purely in terms of operations on graphs, namely, contractions and cuts of edges. The coaction gives direct access to (iterated) discontinuities of Feynman integrals and facilitates a straightforward derivation of the differential equations they admit. In particular, the differential equations for any one-loop integral are determined by the diagrammatic coaction using limited information about their maximal, next-to-maximal, and next-to-next-to-maximal cuts.

  12. A new protein structure representation for efficient protein function prediction.

    PubMed

    Maghawry, Huda A; Mostafa, Mostafa G M; Gharib, Tarek F

    2014-12-01

    One of the challenging problems in bioinformatics is the prediction of protein function. Protein function is the main key that can be used to classify different proteins. Protein function can be inferred experimentally with very small throughput or computationally with very high throughput. Computational methods are sequence based or structure based. Structure-based methods produce more accurate protein function prediction. In this article, we propose a new protein structure representation for efficient protein function prediction. The representation is based on three-dimensional patterns of protein residues. In the analysis, we used protein function based on enzyme activity through six mechanistically diverse enzyme superfamilies: amidohydrolase, crotonase, haloacid dehalogenase, isoprenoid synthase type I, and vicinal oxygen chelate. We applied three different classification methods, naïve Bayes, k-nearest neighbors, and random forest, to predict the enzyme superfamily of a given protein. The prediction accuracy using the proposed representation outperforms a recently introduced representation method that is based only on the distance patterns. The results show that the proposed representation achieved prediction accuracy up to 98%, with improvement of about 10% on average.

  13. PROTEUS2: a web server for comprehensive protein structure prediction and structure-based annotation.

    PubMed

    Montgomerie, Scott; Cruz, Joseph A; Shrivastava, Savita; Arndt, David; Berjanskii, Mark; Wishart, David S

    2008-07-01

    PROTEUS2 is a web server designed to support comprehensive protein structure prediction and structure-based annotation. PROTEUS2 accepts either single sequences (for directed studies) or multiple sequences (for whole proteome annotation) and predicts the secondary and, if possible, tertiary structure of the query protein(s). Unlike most other tools or servers, PROTEUS2 bundles signal peptide identification, transmembrane helix prediction, transmembrane beta-strand prediction, secondary structure prediction (for soluble proteins) and homology modeling (i.e. 3D structure generation) into a single prediction pipeline. Using a combination of progressive multi-sequence alignment, structure-based mapping, hidden Markov models, multi-component neural nets and up-to-date databases of known secondary structure assignments, PROTEUS is able to achieve among the highest reported levels of predictive accuracy for signal peptides (Q2 = 94%), membrane spanning helices (Q2 = 87%) and secondary structure (Q3 score of 81.3%). PROTEUS2's homology modeling services also provide high quality 3D models that compare favorably with those generated by SWISS-MODEL and 3D JigSaw (within 0.2 A RMSD). The average PROTEUS2 prediction takes approximately 3 min per query sequence. The PROTEUS2 server along with source code for many of its modules is accessible a http://wishart.biology.ualberta.ca/proteus2.

  14. 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.

  15. Structural Integrity and Durability of Reusable Space Propulsion Systems

    NASA Technical Reports Server (NTRS)

    1987-01-01

    A two-day conference on the structural integrity and durability of reusable space propulsion systems was held on May 12 and 13, 1987, at the NASA Lewis research Center. Aerothermodynamic loads; instrumentation; fatigue, fracture, and constitutive modeling; and structural dynamics were discussed.

  16. Integrating Biological and Chemical Data for Hepatotoxicity Prediction (SOT)

    EPA Science Inventory

    The U.S. EPA ToxCastTM program is screening thousands of environmental chemicals for bioactivity using hundreds of high-throughput in vitro assays to build predictive models of toxicity. A set of 677 chemicals were represented by 711 bioactivity descriptors (from ToxCast assays),...

  17. Integrating Biological and Chemical Data for Hepatotoxicity Prediction (SOT)

    EPA Science Inventory

    The U.S. EPA ToxCastTM program is screening thousands of environmental chemicals for bioactivity using hundreds of high-throughput in vitro assays to build predictive models of toxicity. A set of 677 chemicals were represented by 711 bioactivity descriptors (from ToxCast assays),...

  18. Predicting phenology by integrating ecology, evolution and climate science

    USGS Publications Warehouse

    Pau, Stephanie; Wolkovich, Elizabeth M.; Cook, Benjamin I.; Davies, T. Jonathan; Kraft, Nathan J.B.; Bolmgren, Kjell; Betancourt, Julio L.; Cleland, Elsa E.

    2011-01-01

    Forecasting how species and ecosystems will respond to climate change has been a major aim of ecology in recent years. Much of this research has focused on phenology — the timing of life-history events. Phenology has well-demonstrated links to climate, from genetic to landscape scales; yet our ability to explain and predict variation in phenology across species, habitats and time remains poor. Here, we outline how merging approaches from ecology, climate science and evolutionary biology can advance research on phenological responses to climate variability. Using insight into seasonal and interannual climate variability combined with niche theory and community phylogenetics, we develop a predictive approach for species' reponses to changing climate. Our approach predicts that species occupying higher latitudes or the early growing season should be most sensitive to climate and have the most phylogenetically conserved phenologies. We further predict that temperate species will respond to climate change by shifting in time, while tropical species will respond by shifting space, or by evolving. Although we focus here on plant phenology, our approach is broadly applicable to ecological research of plant responses to climate variability.

  19. An Integrative Predictive Model of Coronary Artery Calcification in Arteriosclerosis

    PubMed Central

    McGeachie, Michael; Ramoni, Rachel L Badovinac; Mychaleckyj, Josyf C.; Furie, Karen L; Dreyfuss, Jonathan M.; Liu, Yongmei; Herrington, David; Guo, Xiuqing; Lima, João A.; Post, Wendy; Rotter, Jerome I.; Rich, Stephen; Sale, Michèle; Ramoni, Marco F.

    2010-01-01

    Background: Many different genetic and clinical factors have been identified as causes or contributors to atherosclerosis. We present a model of preclinical atherosclerosis based on genetic and clinical data that predicts the presence of coronary artery calcification in healthy Americans of European descent aged 45 to 84 in the Multi-Ethnic Study of Atherosclerosis (MESA). Methods and Results: We assessed 712 individuals for the presence or absence of coronary artery calcification, and their genotypes for 2882 single-nucleotide polymorphisms (SNPs). Using these SNPs and relevant clinical data, a Bayesian network that predicts the presence of coronary calcification was constructed. The model contains 13 SNPs (from genes AGTR1, ALOX15, INSR, PRKAB1, IL1R2, ESR2, KCNK1, FBLN5, PPARA, VEGFA, PON1, TDRD6, PLA2G7, and one ancestry informative marker) and 5 clinical variables (sex, age, weight, smoking, and diabetes) and achieves 85% predictive accuracy, as measured by area under the ROC curve (AUC). This is a significant (p < 0.001) improvement upon models using just the SNP data or using just the clinical variables. Conclusions: We present an investigation of joint genetic and clinical factors associated with atherosclerosis that shows predictive results for both cases, and enhanced performance for the combination. PMID:19948975

  20. Fast and accurate automatic structure prediction with HHpred.

    PubMed

    Hildebrand, Andrea; Remmert, Michael; Biegert, Andreas; Söding, Johannes

    2009-01-01

    Automated protein structure prediction is becoming a mainstream tool for biological research. This has been fueled by steady improvements of publicly available automated servers over the last decade, in particular their ability to build good homology models for an increasing number of targets by reliably detecting and aligning more and more remotely homologous templates. Here, we describe the three fully automated versions of the HHpred server that participated in the community-wide blind protein structure prediction competition CASP8. What makes HHpred unique is the combination of usability, short response times (typically under 15 min) and a model accuracy that is competitive with those of the best servers in CASP8.

  1. HOPE: a homotopy optimization method for protein structure prediction.

    PubMed

    Dunlavy, Daniel M; O'Leary, Dianne P; Klimov, Dmitri; Thirumalai, D

    2005-12-01

    We use a homotopy optimization method, HOPE, to minimize the potential energy associated with a protein model. The method uses the minimum energy conformation of one protein as a template to predict the lowest energy structure of a query sequence. This objective is achieved by following a path of conformations determined by a homotopy between the potential energy functions for the two proteins. Ensembles of solutions are produced by perturbing conformations along the path, increasing the likelihood of predicting correct structures. Successful results are presented for pairs of homologous proteins, where HOPE is compared to a variant of Newton's method and to simulated annealing.

  2. An Integrated Approach to Predicting Carbon Dioxide Storage Capacity in Carbonate Reservoirs

    NASA Astrophysics Data System (ADS)

    Smith, M. M.; Hao, Y.; Mason, H. E.; Carroll, S.

    2015-12-01

    Carbonate reservoirs are widespread globally but pose unique challenges for geologic carbon dioxide (CO2) storage due to the reactive nature of carbonate minerals and the inherently heterogeneous pore structures of these rock types. Carbonate mineral dissolution resulting from CO2-acidified fluids may actually create new storage capacity, but predicting the extent and location of enhanced storage is complicated by the presence of pore size distributions spanning orders of magnitude as well as common microfractures. To address this issue, core samples spanning a wide range of depths and predicted permeabilities were procured from wells drilled into the Weyburn-Midale reservoir from the IEA GHG's CO2 Monitoring and Storage Project, Saskatchewan, Canada; and from the Arbuckle dolomite at the Kansas Geological Survey's South-central Kansas CO2 Project. Our approach integrated non-invasive characterization, complex core-flooding experiments, and 3-D reactive transport simulations to calibrate relevant CO2 storage relationships among fluid flow, porosity, permeability, and chemical reactivity. The resulting observations from this work permit us to constrain (and place uncertainty limits on) some of the model parameters needed for estimating evolving reservoir CO2 storage capacity. The challenge remains, however, as to how to best interpret and implement these observations at the actual reservoir scale. We present our key findings from these projects and recommendations for storage capacity predictions. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  3. A novel approach to improve numerical weather prediction skills by using anomaly integration and historical data

    NASA Astrophysics Data System (ADS)

    Peng, Xindong; Che, Yuzhang; Chang, Jun

    2013-08-01

    Using the concept of anomaly integration and historical climate data, we have developed a novel operational framework to implement deterministic numerical weather prediction within 15 days. Real-case validation shows pronounced improvements in the forecasts of global geopotential heights in 20 out of 30 cases with the Community Atmosphere Model version 3.0. Seven other cases are marginally improved, and only three are deteriorated, in which all are ameliorated within the first-week period. The average of the 30 cases shows an obvious increase of anomaly correlation coefficient (ACC) and a decrease of root mean square error (RMSE) of the geopotential height over global, hemispherical, and tropical zones. Significant amelioration on tropical circulation is displayed within the first-week prediction. The forecasting skill is extended by 0.6 day in terms of days of the ACC greater than 0.6 for 500 hPa 30 case averaged geopotential height on global scale. The 30 case mean ACC and RMSE of 500 hPa temperature show the increment of 0.2 and -1.6 K, respectively, in the first-week prediction. In the case of January 2008, much more reasonable horizontal distribution and vertical structure are achieved in bias-corrected model geopotential height, temperature, relative humidity, and horizontal wind components in comparison to reanalysis data. In spite of a need for additional storage of historical modeling data, the new method does not increase computational costs and therefore is suitable for routine application.

  4. Application of integrated fluid-thermal-structural analysis methods

    NASA Technical Reports Server (NTRS)

    Wieting, Allan R.; Dechaumphai, Pramote; Bey, Kim S.; Thornton, Earl A.; Morgan, Ken

    1988-01-01

    Hypersonic vehicles operate in a hostile aerothermal environment which has a significant impact on their aerothermostructural performance. Significant coupling occurs between the aerodynamic flow field, structural heat transfer, and structural response creating a multidisciplinary interaction. Interfacing state-of-the-art disciplinary analysis methods is not efficient, hence interdisciplinary analysis methods integrated into a single aerothermostructural analyzer are needed. The NASA Langley Research Center is developing such methods in an analyzer called LIFTS (Langley Integrated Fluid-Thermal-Structural) analyzer. The evolution and status of LIFTS is reviewed and illustrated through applications.

  5. Application of integrated fluid-thermal structural analysis methods

    NASA Technical Reports Server (NTRS)

    Wieting, Allan R.; Dechaumphai, Pramote; Bey, Kim S.; Thornton, Earl A.; Morgan, Ken

    1988-01-01

    Hypersonic vehicles operate in a hostile aerothermal environment which has a significant impact on their aerothermostructural performance. Significant coupling occurs between the aerodynamic flow field, structural heat transfer, and structural response creating a multidisciplinary interaction. Interfacing state-of-the-art disciplinary analysis methods are not efficient, hence interdisciplinary analysis methods integrated into a single aerothermostructural analyzer are needed. The NASA Langley Research Center is developing such methods in an analyzer called LIFTS (Langley Integrated Fluid-Thermal-Structural) analyzer. The evolution and status of LIFTS is reviewed and illustrated through applications.

  6. Adaptive modelling of structured molecular representations for toxicity prediction

    NASA Astrophysics Data System (ADS)

    Bertinetto, Carlo; Duce, Celia; Micheli, Alessio; Solaro, Roberto; Tiné, Maria Rosaria

    2012-12-01

    We investigated the possibility of modelling structure-toxicity relationships by direct treatment of the molecular structure (without using descriptors) through an adaptive model able to retain the appropriate structural information. With respect to traditional descriptor-based approaches, this provides a more general and flexible way to tackle prediction problems that is particularly suitable when little or no background knowledge is available. Our method employs a tree-structured molecular representation, which is processed by a recursive neural network (RNN). To explore the realization of RNN modelling in toxicological problems, we employed a data set containing growth impairment concentrations (IGC50) for Tetrahymena pyriformis.

  7. Finite Element Prediction of Acoustic Scattering and Radiation from Submerged Elastic Structures

    NASA Technical Reports Server (NTRS)

    Everstine, G. C.; Henderson, F. M.; Lipman, R. R.

    1984-01-01

    A finite element formulation is derived for the scattering and radiation of acoustic waves from submerged elastic structures. The formulation uses as fundamental unknowns the displacement in the structure and a velocity potential in the field. Symmetric coefficient matrices result. The outer boundary of the fluid region is terminated with an approximate local wave-absorbing boundary condition which assumes that outgoing waves are locally planar. The finite element model is capable of predicting only the near-field acoustic pressures. Far-field sound pressure levels may be determined by integrating the surface pressures and velocities over the wet boundary of the structure using the Helmholtz integral. Comparison of finite element results with analytic results show excellent agreement. The coupled fluid-structure problem may be solved with general purpose finite element codes by using an analogy between the equations of elasticity and the wave equation of linear acoustics.

  8. Integrated Controls-Structures Design Methodology for Flexible Spacecraft

    NASA Technical Reports Server (NTRS)

    Maghami, P. G.; Joshi, S. M.; Price, D. B.

    1995-01-01

    This paper proposes an approach for the design of flexible spacecraft, wherein the structural design and the control system design are performed simultaneously. The integrated design problem is posed as an optimization problem in which both the structural parameters and the control system parameters constitute the design variables, which are used to optimize a common objective function, thereby resulting in an optimal overall design. The approach is demonstrated by application to the integrated design of a geostationary platform, and to a ground-based flexible structure experiment. The numerical results obtained indicate that the integrated design approach generally yields spacecraft designs that are substantially superior to the conventional approach, wherein the structural design and control design are performed sequentially.

  9. PCI-SS: MISO dynamic nonlinear protein secondary structure prediction.

    PubMed

    Green, James R; Korenberg, Michael J; Aboul-Magd, Mohammed O

    2009-07-17

    Since the function of a protein is largely dictated by its three dimensional configuration, determining a protein's structure is of fundamental importance to biology. Here we report on a novel approach to determining the one dimensional secondary structure of proteins (distinguishing alpha-helices, beta-strands, and non-regular structures) from primary sequence data which makes use of Parallel Cascade Identification (PCI), a powerful technique from the field of nonlinear system identification. Using PSI-BLAST divergent evolutionary profiles as input data, dynamic nonlinear systems are built through a black-box approach to model the process of protein folding. Genetic algorithms (GAs) are applied in order to optimize the architectural parameters of the PCI models. The three-state prediction problem is broken down into a combination of three binary sub-problems and protein structure classifiers are built using 2 layers of PCI classifiers. Careful construction of the optimization, training, and test datasets ensures that no homology exists between any training and testing data. A detailed comparison between PCI and 9 contemporary methods is provided over a set of 125 new protein chains guaranteed to be dissimilar to all training data. Unlike other secondary structure prediction methods, here a web service is developed to provide both human- and machine-readable interfaces to PCI-based protein secondary structure prediction. This server, called PCI-SS, is available at http://bioinf.sce.carleton.ca/PCISS. In addition to a dynamic PHP-generated web interface for humans, a Simple Object Access Protocol (SOAP) interface is added to permit invocation of the PCI-SS service remotely. This machine-readable interface facilitates incorporation of PCI-SS into multi-faceted systems biology analysis pipelines requiring protein secondary structure information, and greatly simplifies high-throughput analyses. XML is used to represent the input protein sequence data and also to encode

  10. Sizing Structures and Predicting Weight of a Spacecraft

    NASA Technical Reports Server (NTRS)

    Cerro, Jeffrey; Shore, C. P.

    2006-01-01

    EZDESIT is a computer program for choosing the sizes of structural components and predicting the weight of a spacecraft, aircraft, or other vehicle. In designing a vehicle, EZDESIT is used in conjunction with a finite-element structural- analysis program: Each structural component is sized within EZDESIT to withstand the loads expected to be encountered during operation, then the weights of all the structural finite elements are added to obtain the structural weight of the vehicle. The sizing of the structural components elements also alters the stiffness properties of the finiteelement model. The finite-element analysis and structural component sizing are iterated until the weight of the vehicle converges to a prescribed iterative difference.

  11. Integrated Design Software Predicts the Creep Life of Monolithic Ceramic Components

    NASA Technical Reports Server (NTRS)

    1996-01-01

    Significant improvements in propulsion and power generation for the next century will require revolutionary advances in high-temperature materials and structural design. Advanced ceramics are candidate materials for these elevated-temperature applications. As design protocols emerge for these material systems, designers must be aware of several innate features, including the degrading ability of ceramics to carry sustained load. Usually, time-dependent failure in ceramics occurs because of two different, delayedfailure mechanisms: slow crack growth and creep rupture. Slow crack growth initiates at a preexisting flaw and continues until a critical crack length is reached, causing catastrophic failure. Creep rupture, on the other hand, occurs because of bulk damage in the material: void nucleation and coalescence that eventually leads to macrocracks which then propagate to failure. Successful application of advanced ceramics depends on proper characterization of material behavior and the use of an appropriate design methodology. The life of a ceramic component can be predicted with the NASA Lewis Research Center's Ceramics Analysis and Reliability Evaluation of Structures (CARES) integrated design programs. CARES/CREEP determines the expected life of a component under creep conditions, and CARES/LIFE predicts the component life due to fast fracture and subcritical crack growth. The previously developed CARES/LIFE program has been used in numerous industrial and Government applications.

  12. Predictive Modeling and Integrative Physiology: The Physiome Projects

    PubMed Central

    Bassingthwaighte, James B.

    2012-01-01

    The fundamental paradigm in physiological research is integration. Biological researchers are now ready to define for a species a mathematical construct, the Physiome, the all-encompassing quantitative model of an organism. The goal of the human Physiome project is improved health care, through deep understanding of the organism, all the way down to the genes, reconciling contradictions and clarifying cause and effect. The strategies for accomplishing this long term aim include the systematic gathering of old and new knowledge into shared databases, and integrating the information into self consistent, reproducible, mathematical models. Multiscale models, for practicality, cover only a few levels at a time. Beginning at the middle level, the cell, where the knowledge base is largest and most secure, and the elements well defined as functional biophysical/biochemical modules, the plan is to work up to the organism level and down to the gene level, in the end providing clear linkages between phenotype and the genome. PMID:22919435

  13. Medical Group Structural Integration May Not Ensure That Care Is Integrated, From The Patient's Perspective.

    PubMed

    Kerrissey, Michaela J; Clark, Jonathan R; Friedberg, Mark W; Jiang, Wei; Fryer, Ashley K; Frean, Molly; Shortell, Stephen M; Ramsay, Patricia P; Casalino, Lawrence P; Singer, Sara J

    2017-05-01

    Structural integration is increasing among medical groups, but whether these changes yield care that is more integrated remains unclear. We explored the relationships between structural integration characteristics of 144 medical groups and perceptions of integrated care among their patients. Patients' perceptions were measured by a validated national survey of 3,067 Medicare beneficiaries with multiple chronic conditions across six domains that reflect knowledge and support of, and communication with, the patient. Medical groups' structural characteristics were taken from the National Study of Physician Organizations and included practice size, specialty mix, technological capabilities, and care management processes. Patients' survey responses were most favorable for the domain of test result communication and least favorable for the domain of provider support for medication and home health management. Medical groups' characteristics were not consistently associated with patients' perceptions of integrated care. However, compared to patients of primary care groups, patients of multispecialty groups had strong favorable perceptions of medical group staff knowledge of patients' medical histories. Opportunities exist to improve patient care, but structural integration of medical groups might not be sufficient for delivering care that patients perceive as integrated. Project HOPE—The People-to-People Health Foundation, Inc.

  14. Cloud Prediction of Protein Structure and Function with PredictProtein for Debian

    PubMed Central

    Kaján, László; Yachdav, Guy; Vicedo, Esmeralda; Steinegger, Martin; Mirdita, Milot; Angermüller, Christof; Böhm, Ariane; Domke, Simon; Ertl, Julia; Mertes, Christian; Reisinger, Eva; Rost, Burkhard

    2013-01-01

    We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome. PMID:23971032

  15. Cloud prediction of protein structure and function with PredictProtein for Debian.

    PubMed

    Kaján, László; Yachdav, Guy; Vicedo, Esmeralda; Steinegger, Martin; Mirdita, Milot; Angermüller, Christof; Böhm, Ariane; Domke, Simon; Ertl, Julia; Mertes, Christian; Reisinger, Eva; Staniewski, Cedric; Rost, Burkhard

    2013-01-01

    We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome.

  16. Integrated structural control design of large space structures

    SciTech Connect

    Allen, J.J.; Lauffer, J.P.

    1995-01-01

    Active control of structures has been under intensive development for the last ten years. Reference 2 reviews much of the identification and control technology for structural control developed during this time. The technology was initially focused on space structure and weapon applications; however, recently the technology is also being directed toward applications in manufacturing and transportation. Much of this technology focused on multiple-input/multiple-output (MIMO) identification and control methodology because many of the applications require a coordinated control involving multiple disturbances and control objectives where multiple actuators and sensors are necessary for high performance. There have been many optimal robust control methods developed for the design of MIMO robust control laws; however, there appears to be a significant gap between the theoretical development and experimental evaluation of control and identification methods to address structural control applications. Many methods have been developed for MIMO identification and control of structures, such as the Eigensystem Realization Algorithm (ERA), Q-Markov Covariance Equivalent Realization (Q-Markov COVER) for identification; and, Linear Quadratic Gaussian (LQG), Frequency Weighted LQG and H-/ii-synthesis methods for control. Upon implementation, many of the identification and control methods have shown limitations such as the excitation of unmodelled dynamics and sensitivity to system parameter variations. As a result, research on methods which address these problems have been conducted.

  17. PredictProtein--an open resource for online prediction of protein structural and functional features.

    PubMed

    Yachdav, Guy; Kloppmann, Edda; Kajan, Laszlo; Hecht, Maximilian; Goldberg, Tatyana; Hamp, Tobias; Hönigschmid, Peter; Schafferhans, Andrea; Roos, Manfred; Bernhofer, Michael; Richter, Lothar; Ashkenazy, Haim; Punta, Marco; Schlessinger, Avner; Bromberg, Yana; Schneider, Reinhard; Vriend, Gerrit; Sander, Chris; Ben-Tal, Nir; Rost, Burkhard

    2014-07-01

    PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with a protein sequence it returns: multiple sequence alignments, predicted aspects of structure (secondary structure, solvent accessibility, transmembrane helices (TMSEG) and strands, coiled-coil regions, disulfide bonds and disordered regions) and function. The service incorporates analysis methods for the identification of functional regions (ConSurf), homology-based inference of Gene Ontology terms (metastudent), comprehensive subcellular localization prediction (LocTree3), protein-protein binding sites (ISIS2), protein-polynucleotide binding sites (SomeNA) and predictions of the effect of point mutations (non-synonymous SNPs) on protein function (SNAP2). Our goal has always been to develop a system optimized to meet the demands of experimentalists not highly experienced in bioinformatics. To this end, the PredictProtein results are presented as both text and a series of intuitive, interactive and visually appealing figures. The web server and sources are available at http://ppopen.rostlab.org. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  18. Distance matrix-based approach to protein structure prediction.

    PubMed

    Kloczkowski, Andrzej; Jernigan, Robert L; Wu, Zhijun; Song, Guang; Yang, Lei; Kolinski, Andrzej; Pokarowski, Piotr

    2009-03-01

    Much structural information is encoded in the internal distances; a distance matrix-based approach can be used to predict protein structure and dynamics, and for structural refinement. Our approach is based on the square distance matrix D = [r(ij)(2)] containing all square distances between residues in proteins. This distance matrix contains more information than the contact matrix C, that has elements of either 0 or 1 depending on whether the distance r (ij) is greater or less than a cutoff value r (cutoff). We have performed spectral decomposition of the distance matrices D = sigma lambda(k)V(k)V(kT), in terms of eigenvalues lambda kappa and the corresponding eigenvectors v kappa and found that it contains at most five nonzero terms. A dominant eigenvector is proportional to r (2)--the square distance of points from the center of mass, with the next three being the principal components of the system of points. By predicting r (2) from the sequence we can approximate a distance matrix of a protein with an expected RMSD value of about 7.3 A, and by combining it with the prediction of the first principal component we can improve this approximation to 4.0 A. We can also explain the role of hydrophobic interactions for the protein structure, because r is highly correlated with the hydrophobic profile of the sequence. Moreover, r is highly correlated with several sequence profiles which are useful in protein structure prediction, such as contact number, the residue-wise contact order (RWCO) or mean square fluctuations (i.e. crystallographic temperature factors). We have also shown that the next three components are related to spatial directionality of the secondary structure elements, and they may be also predicted from the sequence, improving overall structure prediction. We have also shown that the large number of available HIV-1 protease structures provides a remarkable sampling of conformations, which can be viewed as direct structural information about the

  19. Structure-based Methods for Computational Protein Functional Site Prediction

    PubMed Central

    Dukka, B KC

    2013-01-01

    Due to the advent of high throughput sequencing techniques and structural genomic projects, the number of gene and protein sequences has been ever increasing. Computational methods to annotate these genes and proteins are even more indispensable. Proteins are important macromolecules and study of the function of proteins is an important problem in structural bioinformatics. This paper discusses a number of methods to predict protein functional site especially focusing on protein ligand binding site prediction. Initially, a short overview is presented on recent advances in methods for selection of homologous sequences. Furthermore, a few recent structural based approaches and sequence-and-structure based approaches for protein functional sites are discussed in details. PMID:24688745

  20. Prediction of Harmful Human Health Effects of Chemicals from Structure

    NASA Astrophysics Data System (ADS)

    Cronin, Mark T. D.

    There is a great need to assess the harmful effects of chemicals to which man is exposed. Various in silico techniques including chemical grouping and category formation, as well as the use of (Q)SARs can be applied to predict the toxicity of chemicals for a number of toxicological effects. This chapter provides an overview of the state of the art of the prediction of the harmful effects of chemicals to human health. A variety of existing data can be used to obtain information; many such data are formalized into freely available and commercial databases. (Q)SARs can be developed (as illustrated with reference to skin sensitization) for local and global data sets. In addition, chemical grouping techniques can be applied on "similar" chemicals to allow for read-across predictions. Many "expert systems" are now available that incorporate these approaches. With these in silico approaches available, the techniques to apply them successfully have become essential. Integration of different in silico approaches with each other, as well as with other alternative approaches, e.g., in vitro and -omics through the development of integrated testing strategies, will assist in the more efficient prediction of the harmful health effects of chemicals

  1. Development and Characterization of Multilayer Integrated Warhead Structure.

    DTIC Science & Technology

    1985-05-01

    the final concept. Steel castings ( 17 - 4PH ) were made and specimens were machined to characterize the structural properties of the concept. The pioperty...casting 17 - 4PH test specimens and characterizing these composite structures. It was anticipated that problem would occur in the transition . from...MULTILAYER Final Report INTEGRATED WARHEAD STRUCTURE 3/ 17 /83 to 9/30/84 G. PERFORMING ORG. REPORT NUMBER 7. AUTHOR(a) 0. CONTRACT OR GRANT NUMBER(s) D

  2. Structural design of integral tankage for advanced space transportation systems

    NASA Technical Reports Server (NTRS)

    Macconochie, I. O.; Davis, R. B.; Lemessurier, R. W.

    1982-01-01

    Fully reusable launch vehicle concepts being studied for post-Shuttle era transports present major challenges for the structural design of large propellant tankage. The dominant structural elements are internal tankage for both cryogenic and non-cryogenic propellants which must operate in a broad range of thermal environments while meeting requirements for low weight and reusability. Several approaches to integral tank design are discussed and an analysis of a hot structure honeycomb sandwich tank for a circular body vehicle is presented.

  3. Structural components of nuclear integrity with gene regulatory potential.

    PubMed

    Fenelon, Kelli D; Hopyan, Sevan

    2017-10-01

    The nucleus is a mechanosensitive and load-bearing structure. Structural components of the nucleus interact to maintain nuclear integrity and have become subjects of exciting research that is relevant to cell and developmental biology. Here we outline the boundaries of what is known about key architectural elements within the nucleus and highlight their potential structural and transcriptional regulatory functions. Copyright © 2017. Published by Elsevier Ltd.

  4. An integrated computer procedure for sizing composite airframe structures

    NASA Technical Reports Server (NTRS)

    Sobieszczanski-Sobieski, J.

    1979-01-01

    A computerized algorithm to generate cross-sectional dimensions and fiber orientations for composite airframe structures is described, and its application in a wing structural synthesis is established. The algorithm unifies computations of aeroelastic loads, stresses, and deflections, as well as optimal structural sizing and fiber orientations in an open-ended system of integrated computer programs. A finite-element analysis and a mathematical-optimization technique are discussed.

  5. Second-Order Structured Deformations: Relaxation, Integral Representation and Applications

    NASA Astrophysics Data System (ADS)

    Barroso, Ana Cristina; Matias, José; Morandotti, Marco; Owen, David R.

    2017-09-01

    Second-order structured deformations of continua provide an extension of the multiscale geometry of first-order structured deformations by taking into account the effects of submacroscopic bending and curving. We derive here an integral representation for a relaxed energy functional in the setting of second-order structured deformations. Our derivation covers inhomogeneous initial energy densities (i.e., with explicit dependence on the position); finally, we provide explicit formulas for bulk relaxed energies as well as anticipated applications.

  6. Exploration of Genomic, Proteomic, and Histopathological Image Data Integration Methods for Clinical Prediction

    PubMed Central

    Poruthoor, A.; Phan, J.H.; Kothari, S.; Wang, May D.

    2016-01-01

    The emergence of large multi-platform and multi-scale data repositories in biomedicine has enabled the exploration of data integration for holistic decision making. In this research, we investigate multi-modal genomic, proteomic, and histopathological image data integration for prediction of ovarian cancer clinical endpoints in The Cancer Genome Atlas (TCGA). Specifically, we study two data integration techniques, simple data concatenation and ensemble classification, to determine whether they can improve prediction of ovarian cancer grade or patient survival. Results indicate that integration via ensemble classification is more effective than simple data concatenation. We also highlight several key factors impacting data integration outcome such as predictability of endpoint, class prevalence, and unbalanced representation of features from different data modalities.

  7. OVERVIEW OF HANFORD SINGLE SHELL TANK (SST) STRUCTURAL INTEGRITY - 12123

    SciTech Connect

    RAST RS; RINKER MW; WASHENFELDER DJ; JOHNSON JB

    2012-01-25

    To improve the understanding of the single-shell tanks (SSTs) integrity, Washington River Protection Solutions, LLC (WRPS), the USDOE Hanford Site tank contractor, developed an enhanced Single-Shell Tank Integrity Project in 2009. An expert panel on SST integrity, consisting of various subject matters experts in industry and academia, was created to provide recommendations supporting the development of the project. This panel developed 33 recommendations in four main areas of interest: structural integrity, liner degradation, leak integrity and prevention, and mitigation of contamination migration. Seventeen of these recommendations were used to develop the basis for the M-45-10-1 Change Package for the Hanford Federal Agreement and Compliance Order, which is also known as the Tri-Party Agreement. The structural integrity of the tanks is a key element in completing the cleanup mission at the Hanford Site. There are eight primary recommendations related to the structural integrity of Hanford SSTs. Six recommendations are being implemented through current and planned activities. The structural integrity of the Hanford SSTs is being evaluated through analysis, monitoring, inspection, materials testing, and construction document review. Structural evaluation in the form of analysis is performed using modern finite element models generated in ANSYS{reg_sign} The analyses consider in-situ, thermal, operating loads and natural phenomena such as earthquakes. Structural analysis of 108 of 149 Hanford SSTs has concluded that the tanks are structurally sound and meet current industry standards. Analyses of the remaining Hanford SSTs are scheduled for FY2013. Hanford SSTs are monitored through a dome deflection program. The program looks for deflections of the tank dome greater than 1/4 inch. No such deflections have been recorded. The tanks are also subjected to visual inspection. Digital cameras record the interior surface of the concrete tank domes, looking for cracks and

  8. Overview of Hanford Single Shell Tank (SST) Structural Integrity

    SciTech Connect

    Rast, Richard S.; Washenfelder, Dennis J.; Johnson, Jeremy M.

    2013-11-14

    To improve the understanding of the single-shell tanks (SSTs) integrity, Washington River Protection Solutions, LLC (WRPS), the USDOE Hanford Site tank contractor, developed an enhanced Single-Shell Tank Integrity Project (SSTIP) in 2009. An expert panel on SST integrity, consisting of various subject matters experts in industry and academia, was created to provide recommendations supporting the development of the project. This panel developed 33 recommendations in four main areas of interest: structural integrity, liner degradation, leak integrity and prevention, and mitigation of contamination migration, Seventeen of these recommendations were used to develop the basis for the M-45-10-1 Change Package for the Hanford Federal Agreement and Compliance Order, which is also known as the Tri-Party Agreement. The structural integrity of the tanks is a key element in completing the cleanup mission at the Hanford Site. There are eight primary recommendations related to the structural integrity of Hanford Single-Shell Tanks. Six recommendations are being implemented through current and planned activities. The structural integrity of the Hanford is being evaluated through analysis, monitoring, inspection, materials testing, and construction document review. Structural evaluation in the form of analysis is performed using modern finite element models generated in ANSYS. The analyses consider in-situ, thermal, operating loads and natural phenomena such as earthquakes. Structural analysis of 108 of 149 Hanford Single-Shell Tanks has concluded that the tanks are structurally sound and meet current industry standards. Analysis of the remaining Hanford Single-Shell Tanks is scheduled for FY2014. Hanford Single-Shell Tanks are monitored through a dome deflection program. The program looks for deflections of the tank dome greater than 1/4 inch. No such deflections have been recorded. The tanks are also subjected to visual inspection. Digital cameras record the interior surface of

  9. Levels of Structural Integration and Facial Expressions of Negative Emotions.

    PubMed

    Bock, Astrid; Huber, Eva; Benecke, Cord

    2016-09-01

    For a clinically relevant understanding of facial displays of patients with mental disorders it is crucial to go beyond merely counting frequencies of facial expressions, but include the contextual information of the expression. We assume that patients with different levels of structural integration differ in the contextual embedding of their negative facial expressions of emotions. Facial affective behaviour of 80 female participants during an OPD interview was analysed using FACS (Facial Action Coding System) and the RFE coding system (Referencesof- Facial-Expression coding system; Bock et al. 2015).Using the RFE coding system, 2192 negative facial expressions of emotions were attributed to different references (e.g., interactive, self-related, object-related) by relying on contextual variables. Pure frequency of negative facial affect was not related to level of structural integration. Negative facial expressions of emotions directed towards the interviewer (interactive reference), as well as negative facial expressions directed towards the displayer's whole self were associated with lower levels of structural integration. In contrast, negative facial affects directed to single aspects of the self, to single aspects of objects, or to external situations were associated with higher levels of structural integration. The differentiation of references of facial affective behavior allows a deeper understanding of the connection between facial displays and structural levels of psychic integration.

  10. Integrating protein structural dynamics and evolutionary analysis with Bio3D.

    PubMed

    Skjærven, Lars; Yao, Xin-Qiu; Scarabelli, Guido; Grant, Barry J

    2014-12-10

    Popular bioinformatics approaches for studying protein functional dynamics include comparisons of crystallographic structures, molecular dynamics simulations and normal mode analysis. However, determining how observed displacements and predicted motions from these traditionally separate analyses relate to each other, as well as to the evolution of sequence, structure and function within large protein families, remains a considerable challenge. This is in part due to the general lack of tools that integrate information of molecular structure, dynamics and evolution. Here, we describe the integration of new methodologies for evolutionary sequence, structure and simulation analysis into the Bio3D package. This major update includes unique high-throughput normal mode analysis for examining and contrasting the dynamics of related proteins with non-identical sequences and structures, as well as new methods for quantifying dynamical couplings and their residue-wise dissection from correlation network analysis. These new methodologies are integrated with major biomolecular databases as well as established methods for evolutionary sequence and comparative structural analysis. New functionality for directly comparing results derived from normal modes, molecular dynamics and principal component analysis of heterogeneous experimental structure distributions is also included. We demonstrate these integrated capabilities with example applications to dihydrofolate reductase and heterotrimeric G-protein families along with a discussion of the mechanistic insight provided in each case. The integration of structural dynamics and evolutionary analysis in Bio3D enables researchers to go beyond a prediction of single protein dynamics to investigate dynamical features across large protein families. The Bio3D package is distributed with full source code and extensive documentation as a platform independent R package under a GPL2 license from http://thegrantlab.org/bio3d/ .

  11. Drug Repositioning by Kernel-Based Integration of Molecular Structure, Molecular Activity, and Phenotype Data

    PubMed Central

    Wang, Yongcui; Chen, Shilong; Deng, Naiyang; Wang, Yong

    2013-01-01

    Computational inference of novel therapeutic values for existing drugs, i.e., drug repositioning, offers the great prospect for faster and low-risk drug development. Previous researches have indicated that chemical structures, target proteins, and side-effects could provide rich information in drug similarity assessment and further disease similarity. However, each single data source is important in its own way and data integration holds the great promise to reposition drug more accurately. Here, we propose a new method for drug repositioning, PreDR (Predict Drug Repositioning), to integrate molecular structure, molecular activity, and phenotype data. Specifically, we characterize drug by profiling in chemical structure, target protein, and side-effects space, and define a kernel function to correlate drugs with diseases. Then we train a support vector machine (SVM) to computationally predict novel drug-disease interactions. PreDR is validated on a well-established drug-disease network with 1,933 interactions among 593 drugs and 313 diseases. By cross-validation, we find that chemical structure, drug target, and side-effects information are all predictive for drug-disease relationships. More experimentally observed drug-disease interactions can be revealed by integrating these three data sources. Comparison with existing methods demonstrates that PreDR is competitive both in accuracy and coverage. Follow-up database search and pathway analysis indicate that our new predictions are worthy of further experimental validation. Particularly several novel predictions are supported by clinical trials databases and this shows the significant prospects of PreDR in future drug treatment. In conclusion, our new method, PreDR, can serve as a useful tool in drug discovery to efficiently identify novel drug-disease interactions. In addition, our heterogeneous data integration framework can be applied to other problems. PMID:24244318

  12. A system structure for predictive relations in penetration mechanics

    NASA Astrophysics Data System (ADS)

    Korjack, Thomas A.

    1992-02-01

    The availability of a software system yielding quick numerical models to predict ballistic behavior is a requisite for any research laboratory engaged in material behavior. What is especially true about accessibility of rapid prototyping for terminal impaction is the enhancement of a system structure which will direct the specific material and impact situation towards a specific predictive model. This is of particular importance when the ranges of validity are at stake and the pertinent constraints associated with the impact are unknown. Hence, a compilation of semiempirical predictive penetration relations for various physical phenomena has been organized into a data structure for the purpose of developing a knowledge-based decision aided expert system to predict the terminal ballistic behavior of projectiles and targets. The ranges of validity and constraints of operation of each model were examined and cast into a decision tree structure to include target type, target material, projectile types, projectile materials, attack configuration, and performance or damage measures. This decision system implements many penetration relations, identifies formulas that match user-given conditions, and displays the predictive relation coincident with the match in addition to a numerical solution. The physical regimes under consideration encompass the hydrodynamic, transitional, and solid; the targets are either semi-infinite or plate, and the projectiles include kinetic and chemical energy. A preliminary databases has been constructed to allow further development of inductive and deductive reasoning techniques applied to ballistic situations involving terminal mechanics.

  13. (PS)2: protein structure prediction server version 3.0.

    PubMed

    Huang, Tsun-Tsao; Hwang, Jenn-Kang; Chen, Chu-Huang; Chu, Chih-Sheng; Lee, Chi-Wen; Chen, Chih-Chieh

    2015-07-01

    Protein complexes are involved in many biological processes. Examining coupling between subunits of a complex would be useful to understand the molecular basis of protein function. Here, our updated (PS)(2) web server predicts the three-dimensional structures of protein complexes based on comparative modeling; furthermore, this server examines the coupling between subunits of the predicted complex by combining structural and evolutionary considerations. The predicted complex structure could be indicated and visualized by Java-based 3D graphics viewers and the structural and evolutionary profiles are shown and compared chain-by-chain. For each subunit, considerations with or without the packing contribution of other subunits cause the differences in similarities between structural and evolutionary profiles, and these differences imply which form, complex or monomeric, is preferred in the biological condition for the subunit. We believe that the (PS)(2) server would be a useful tool for biologists who are interested not only in the structures of protein complexes but also in the coupling between subunits of the complexes. The (PS)(2) is freely available at http://ps2v3.life.nctu.edu.tw/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  14. CENTROIDFOLD: a web server for RNA secondary structure prediction.

    PubMed

    Sato, Kengo; Hamada, Michiaki; Asai, Kiyoshi; Mituyama, Toutai

    2009-07-01

    The CENTROIDFOLD web server (http://www.ncrna.org/centroidfold/) is a web application for RNA secondary structure prediction powered by one of the most accurate prediction engine. The server accepts two kinds of sequence data: a single RNA sequence and a multiple alignment of RNA sequences. It responses with a prediction result shown as a popular base-pair notation and a graph representation. PDF version of the graph representation is also available. For a multiple alignment sequence, the server predicts a common secondary structure. Usage of the server is quite simple. You can paste a single RNA sequence (FASTA or plain sequence text) or a multiple alignment (CLUSTAL-W format) into the textarea then click on the 'execute CentroidFold' button. The server quickly responses with a prediction result. The major advantage of this server is that it employs our original CentroidFold software as its prediction engine which scores the best accuracy in our benchmark results. Our web server is freely available with no login requirement.

  15. Efficient optimization of integrated aerodynamic-structural design

    NASA Technical Reports Server (NTRS)

    Haftka, R. T.; Grossman, B.; Eppard, W. M.; Kao, P. J.

    1987-01-01

    The introduction of composite materials is having a profound effect on the design process. Because these materials permit the designer to tailor material properties to improve structural, aerodynamic and acoustic performance, they require a more integrated multidisciplinary design process. Because of the complexity of the design process numerical optimization methods are required. The present paper is focused on a major difficulty associated with the multidisciplinary design optimization process - its enormous computational cost. We consider two approaches for reducing this computational burden: (1) development of efficient methods for cross-sensitivity calculation using perturbation methods; and (2) the use of approximate numerical optimization procedures. Our efforts are concentrated upon combined aerodynamic-structural optimization. Results are presented for the integrated design of a sailplane wing. The impact of our computational procedures on the computational costs of integrated costs of integrated designs are discussed.

  16. Structurally Integrated Coatings for Wear and Corrosion

    SciTech Connect

    Beardsley, M. Brad; Sebright, Jason L.

    2008-11-18

    Wear and corrosion of structures cuts across industries and continues to challenge materials scientists and engineers to develop cost effective solutions. Industries typically seek mature technologies that can be implemented for production with rapid or minimal development and have little appetite for the longer-term materials research and development required to solve complex problems. The collaborative work performed in this project addressed the complexity of this problem in a multi-year program that industries would be reluctant to undertake without government partnership. This effort built upon the prior development of Advanced Abrasion Resistant Materials conduct by Caterpillar Inc. under DOE Cooperative Agreement No. DE-FC26-01NT41054. In this referenced work, coatings were developed that exhibited significant wear life improvements over standard carburized heat treated steel in abrasive wear applications. The technology used in this referenced work, arc lamp fusing of thermal spray coatings, was one of the primary technical paths in this work effort. In addition to extending the capability of the coating technology to address corrosion issues, additional competitive coating technologies were evaluated to insure that the best technology was developed to meet the goals of the program. From this, plasma transferred arc (PTA) welding was selected as the second primary technology that was investigated. Specifically, this project developed improved, cost effective surfacing materials and processes for wear and corrosion resistance in both sliding and abrasive wear applications. Materials with wear and corrosion performance improvements that are 4 to 5 times greater than heat treated steels were developed. The materials developed were based on low cost material systems utilizing ferrous substrates and stainless steel type matrix with hard particulates formed from borides and carbides. Affordability was assessed against other competing hard surfacing or coating

  17. Quantitative genetics of shape in cricket wings: developmental integration in a functional structure.

    PubMed

    Klingenberg, Christian Peter; Debat, Vincent; Roff, Derek A

    2010-10-01

    The role of developmental and genetic integration for evolution is contentious. One hypothesis states that integration acts as a constraint on evolution, whereas an alternative is that developmental and genetic systems evolve to match the functional modularity of organisms. This study examined a morphological structure, the cricket wing, where developmental and functional modules are discordant, making it possible to distinguish the two alternatives. Wing shape was characterized with geometric morphometrics, quantitative genetic information was extracted using a full-sibling breeding design, and patterns of developmental integration were inferred from fluctuating asymmetry of wing shape. The patterns of genetic, phenotypic, and developmental integration were clearly similar, but not identical. Heritabilities for different shape variables varied widely, but no shape variables were devoid of genetic variation. Simulated selection for specific shape changes produced predicted responses with marked deflections due to the genetic covariance structure. Three hypotheses of modularity according to the wing structures involved in sound production were inconsistent with the genetic, phenotypic, or developmental covariance structure. Instead, there appears to be strong integration throughout the wing. The hypothesis that genetic and developmental integration evolve to match functional modularity can therefore be rejected for this example.

  18. The MEMPACK alpha-helical transmembrane protein structure prediction server

    PubMed Central

    Nugent, Timothy; Ward, Sean; Jones, David T.

    2011-01-01

    Motivation: The experimental difficulties of alpha-helical transmembrane protein structure determination make this class of protein an important target for sequence-based structure prediction tools. The MEMPACK prediction server allows users to submit a transmembrane protein sequence and returns transmembrane topology, lipid exposure, residue contacts, helix–helix interactions and helical packing arrangement predictions in both plain text and graphical formats using a number of novel machine learning-based algorithms. Availability: The server can be accessed as a new component of the PSIPRED portal by at http://bioinf.cs.ucl.ac.uk/psipred/. Contact: d.jones@cs.ucl.ac.uk; t.nugent@cs.ucl.ac.uk PMID:21349872

  19. Structural Damage Prediction and Analysis for Hypervelocity Impact: Consulting

    NASA Technical Reports Server (NTRS)

    1995-01-01

    A portion of the contract NAS8-38856, 'Structural Damage Prediction and Analysis for Hypervelocity Impacts,' from NASA Marshall Space Flight Center (MSFC), included consulting which was to be documented in the final report. This attachment to the final report contains memos produced as part of that consulting.

  20. Process for predicting structural performance of mechanical systems

    DOEpatents

    Gardner, David R.; Hendrickson, Bruce A.; Plimpton, Steven J.; Attaway, Stephen W.; Heinstein, Martin W.; Vaughan, Courtenay T.

    1998-01-01

    A process for predicting the structural performance of a mechanical system represents the mechanical system by a plurality of surface elements. The surface elements are grouped according to their location in the volume occupied by the mechanical system so that contacts between surface elements can be efficiently located. The process is well suited for efficient practice on multiprocessor computers.

  1. Process for predicting structural performance of mechanical systems

    DOEpatents

    Gardner, D.R.; Hendrickson, B.A.; Plimpton, S.J.; Attaway, S.W.; Heinstein, M.W.; Vaughan, C.T.

    1998-05-19

    A process for predicting the structural performance of a mechanical system represents the mechanical system by a plurality of surface elements. The surface elements are grouped according to their location in the volume occupied by the mechanical system so that contacts between surface elements can be efficiently located. The process is well suited for efficient practice on multiprocessor computers. 12 figs.

  2. Multiple methods integration for structural mechanics analysis and design

    NASA Technical Reports Server (NTRS)

    Housner, J. M.; Aminpour, M. A.

    1991-01-01

    A new research area of multiple methods integration is proposed for joining diverse methods of structural mechanics analysis which interact with one another. Three categories of multiple methods are defined: those in which a physical interface are well defined; those in which a physical interface is not well-defined, but selected; and those in which the interface is a mathematical transformation. Two fundamental integration procedures are presented that can be extended to integrate various methods (e.g., finite elements, Rayleigh Ritz, Galerkin, and integral methods) with one another. Since the finite element method will likely be the major method to be integrated, its enhanced robustness under element distortion is also examined and a new robust shell element is demonstrated.

  3. Multidimensional models for predicting muscle structure and fascicle pennation.

    PubMed

    Randhawa, Avleen; Wakeling, James M

    2015-10-07

    Pennation angles change during muscle contraction and must be tracked by muscle models. When muscles contract they can change in depth (distance between the bounding sheets of aponeurosis) or width, and this is related to pennation angle and muscle fascicle length. As a simplification to these relationships, many models of pennate muscle assume a constant distance between aponeuroses during contraction (constant depth). It is possible that these 1D models do not recreate the internal structure of muscles adequately, whereas 2D panel models that assume a constant panel area, or 3D models that assume a constant muscle volume may better predict the structural changes that occur within muscle during contraction. However, these ideas have never been validated in man. The purpose of this study was to test the accuracy with which 1D, 2D or 3D structural models of muscle could predict the pennation and muscle depth within the medial gastrocnemius (MG) and lateral gastrocnemius (LG) in man during ankle plantarflexions. The 1D model, by definition, was unable to account for changes in muscle depth. The 2D model predicted change in depth as the aponeurosis was loaded, but could only allow a decrease in depth as the aponeurosis is stretched. This was not sufficient to predict the increases in depth that occur in the LG during plantarflexion. The 3D model had the ability to predict either increases or decreases in depth during the ankle plantarflexions and predicted opposing changes in depth that occurred between the MG and LG, whilst simultaneously predicting the pennation more accurately than the 1D or 2D models. However, when using mean parameters, the 3D model performed no better than the more simple 1D model, and so if the intent of a model is purely to establish a good relation between fascicle length and pennation then the 1D model is a suitable choice for these muscles.

  4. Development of an integrated method for long-term water quality prediction using seasonal climate forecast

    NASA Astrophysics Data System (ADS)

    Cho, Jaepil; Shin, Chang-Min; Choi, Hwan-Kyu; Kim, Kyong-Hyeon; Choi, Ji-Yong

    2016-10-01

    The APEC Climate Center (APCC) produces climate prediction information utilizing a multi-climate model ensemble (MME) technique. In this study, four different downscaling methods, in accordance with the degree of utilizing the seasonal climate prediction information, were developed in order to improve predictability and to refine the spatial scale. These methods include: (1) the Simple Bias Correction (SBC) method, which directly uses APCC's dynamic prediction data with a 3 to 6 month lead time; (2) the Moving Window Regression (MWR) method, which indirectly utilizes dynamic prediction data; (3) the Climate Index Regression (CIR) method, which predominantly uses observation-based climate indices; and (4) the Integrated Time Regression (ITR) method, which uses predictors selected from both CIR and MWR. Then, a sampling-based temporal downscaling was conducted using the Mahalanobis distance method in order to create daily weather inputs to the Soil and Water Assessment Tool (SWAT) model. Long-term predictability of water quality within the Wecheon watershed of the Nakdong River Basin was evaluated. According to the Korean Ministry of Environment's Provisions of Water Quality Prediction and Response Measures, modeling-based predictability was evaluated by using 3-month lead prediction data issued in February, May, August, and November as model input of SWAT. Finally, an integrated approach, which takes into account various climate information and downscaling methods for water quality prediction, was presented. This integrated approach can be used to prevent potential problems caused by extreme climate in advance.

  5. Improved finite element methodology for integrated thermal structural analysis

    NASA Technical Reports Server (NTRS)

    Dechaumphai, P.; Thornton, E. A.

    1982-01-01

    An integrated thermal-structural finite element approach for efficient coupling of thermal and structural analysis is presented. New thermal finite elements which yield exact nodal and element temperatures for one dimensional linear steady state heat transfer problems are developed. A nodeless variable formulation is used to establish improved thermal finite elements for one dimensional nonlinear transient and two dimensional linear transient heat transfer problems. The thermal finite elements provide detailed temperature distributions without using additional element nodes and permit a common discretization with lower order congruent structural finite elements. The accuracy of the integrated approach is evaluated by comparisons with analytical solutions and conventional finite element thermal structural analyses for a number of academic and more realistic problems. Results indicate that the approach provides a significant improvement in the accuracy and efficiency of thermal stress analysis for structures with complex temperature distributions.

  6. Structural Integrity Evaluation of the Lear Fan 2100 Aircraft

    NASA Technical Reports Server (NTRS)

    Kan, H. P.; Dyer, T. A.

    1996-01-01

    An in-situ nondestructive inspection was conducted to detect manufacturing and assembly induced defects in the upper two wing surfaces (skin s) and upper fuselage skin of the Lear Fan 2100 aircraft E009. The effects of the defects, detected during the inspection, on the integrity of the structure was analytically evaluated. A systematic evaluation was also conducted to determine the damage tolerance capability of the upper wing skin against impact threats and assembly induced damage. The upper wing skin was divided into small regions for damage tolerance evaluations. Structural reliability, margin of safety, allowable strains, and allowable damage size were computed. The results indicated that the impact damage threat imposed on composite military aircraft structures is too severe for the Lear Fan 2100 upper wing skin. However, the structural integrity is not significantly degraded by the assembly induced damage for properly assembled structures, such as the E009 aircraft.

  7. Improved finite element methodology for integrated thermal structural analysis

    NASA Technical Reports Server (NTRS)

    Dechaumphai, P.; Thornton, E. A.

    1982-01-01

    An integrated thermal-structural finite element approach for efficient coupling of thermal and structural analyses is presented. New thermal finite elements which yield exact nodal and element temperature for one dimensional linear steady state heat transfer problems are developed. A nodeless variable formulation is used to establish improved thermal finite elements for one dimensional nonlinear transient and two dimensional linear transient heat transfer problems. The thermal finite elements provide detailed temperature distributions without using additional element nodes and permit a common discretization with lower order congruent structural finite elements. The accuracy of the integrated approach is evaluated by comparisons with analytical solutions and conventional finite element thermal-structural analyses for a number of academic and more realistic problems. Results indicate that the approach provides a significant improvement in the accuracy and efficiency of thermal stress analysis for structures with complex temperature distributions.

  8. Structural Integrity Evaluation of the Lear Fan 2100 Aircraft

    NASA Technical Reports Server (NTRS)

    Kan, H. P.; Dyer, T. A.

    1996-01-01

    An in-situ nondestructive inspection was conducted to detect manufacturing and assembly induced defects in the upper two wing surfaces (skin s) and upper fuselage skin of the Lear Fan 2100 aircraft E009. The effects of the defects, detected during the inspection, on the integrity of the structure was analytically evaluated. A systematic evaluation was also conducted to determine the damage tolerance capability of the upper wing skin against impact threats and assembly induced damage. The upper wing skin was divided into small regions for damage tolerance evaluations. Structural reliability, margin of safety, allowable strains, and allowable damage size were computed. The results indicated that the impact damage threat imposed on composite military aircraft structures is too severe for the Lear Fan 2100 upper wing skin. However, the structural integrity is not significantly degraded by the assembly induced damage for properly assembled structures, such as the E009 aircraft.

  9. Integrated fiber optic structural health sensors for inflatable space habitats

    NASA Astrophysics Data System (ADS)

    Ohanian, Osgar John; Garg, Naman; Castellucci, Matthew A.

    2017-04-01

    Inflatable space habitats offer many advantages for future space missions; however, the long term integrity of these flexible structures is a major concern in harsh space environments. Structural Health Monitoring (SHM) of these structures is essential to ensure safe operation, provide early warnings of damage, and measure structural changes over long periods of time. To address this problem, the authors have integrated distributed fiber optic strain sensors to measure loading and to identify the occurrence and location of damage in the straps and webbing used in the structural restraint layer. The fiber optic sensors employed use Rayleigh backscatter combined with optical frequency domain reflectometry to enable measurement of strain every 0.65 mm (0.026 inches) along the sensor. The Kevlar woven straps that were tested exhibited large permanent deformation during initial cycling and continued to exhibit hysteresis thereafter, but there was a consistent linear relationship between the sensor's measurement and the actual strain applied. Damage was intentionally applied to a tensioned strap, and the distributed strain measurement clearly identified a change in the strain profile centered on the location of the damage. This change in structural health was identified at a loading that was less than half of the ultimate loading that caused a structural failure. This sensing technique will be used to enable integrated SHM sensors to detect loading and damage in future inflatable space habitat structures.

  10. Predictive modeling of neuroanatomic structures for brain atrophy detection

    NASA Astrophysics Data System (ADS)

    Hu, Xintao; Guo, Lei; Nie, Jingxin; Li, Kaiming; Liu, Tianming

    2010-03-01

    In this paper, we present an approach of predictive modeling of neuroanatomic structures for the detection of brain atrophy based on cross-sectional MRI image. The underlying premise of applying predictive modeling for atrophy detection is that brain atrophy is defined as significant deviation of part of the anatomy from what the remaining normal anatomy predicts for that part. The steps of predictive modeling are as follows. The central cortical surface under consideration is reconstructed from brain tissue map and Regions of Interests (ROI) on it are predicted from other reliable anatomies. The vertex pair-wise distance between the predicted vertex and the true one within the abnormal region is expected to be larger than that of the vertex in normal brain region. Change of white matter/gray matter ratio within a spherical region is used to identify the direction of vertex displacement. In this way, the severity of brain atrophy can be defined quantitatively by the displacements of those vertices. The proposed predictive modeling method has been evaluated by using both simulated atrophies and MRI images of Alzheimer's disease.

  11. Structure prediction and targeted synthesis: a new Na(n)N2 diazenide crystalline structure.

    PubMed

    Zhang, Xiuwen; Zunger, Alex; Trimarchi, Giancarlo

    2010-11-21

    Significant progress in theoretical and computational techniques for predicting stable crystal structures has recently begun to stimulate targeted synthesis of such predicted structures. Using a global space-group optimization (GSGO) approach that locates ground-state structures and stable stoichiometries from first-principles energy functionals by objectively starting from randomly selected lattice vectors and random atomic positions, we predict the first alkali diazenide compound Na(n)N(2), manifesting homopolar N-N bonds. The previously predicted Na(3)N structure manifests only heteropolar Na-N bonds and has positive formation enthalpy. It was calculated based on local Hartree-Fock relaxation of a fixed-structure type (Li(3)P-type) found by searching an electrostatic point-ion model. Synthesis attempts of this positive ΔH compound using activated nitrogen yielded another structure (anti-ReO(3)-type). The currently predicted (negative formation enthalpy) diazenide Na(2)N(2) completes the series of previously known BaN(2) and SrN(2) diazenides where the metal sublattice transfers charge into the empty N(2) Π(g) orbital. This points to a new class of alkali nitrides with fundamentally different bonding, i.e., homopolar rather than heteropolar bonds and, at the same time, illustrates some of the crucial subtleties and pitfalls involved in structure predictions versus planned synthesis. Attempts at synthesis of the stable Na(2)N(2) predicted here will be interesting.

  12. Predicting PDZ domain mediated protein interactions from structure

    PubMed Central

    2013-01-01

    Background PDZ domains are structural protein domains that recognize simple linear amino acid motifs, often at protein C-termini, and mediate protein-protein interactions (PPIs) in important biological processes, such as ion channel regulation, cell polarity and neural development. PDZ domain-peptide interaction predictors have been developed based on domain and peptide sequence information. Since domain structure is known to influence binding specificity, we hypothesized that structural information could be used to predict new interactions compared to sequence-based predictors. Results We developed a novel computational predictor of PDZ domain and C-terminal peptide interactions using a support vector machine trained with PDZ domain structure and peptide sequence information. Performance was estimated using extensive cross validation testing. We used the structure-based predictor to scan the human proteome for ligands of 218 PDZ domains and show that the predictions correspond to known PDZ domain-peptide interactions and PPIs in curated databases. The structure-based predictor is complementary to the sequence-based predictor, finding unique known and novel PPIs, and is less dependent on training–testing domain sequence similarity. We used a functional enrichment analysis of our hits to create a predicted map of PDZ domain biology. This map highlights PDZ domain involvement in diverse biological processes, some only found by the structure-based predictor. Based on this analysis, we predict novel PDZ domain involvement in xenobiotic metabolism and suggest new interactions for other processes including wound healing and Wnt signalling. Conclusions We built a structure-based predictor of PDZ domain-peptide interactions, which can be used to scan C-terminal proteomes for PDZ interactions. We also show that the structure-based predictor finds many known PDZ mediated PPIs in human that were not found by our previous sequence-based predictor and is less dependent on

  13. Automatic prediction of facial trait judgments: appearance vs. structural models.

    PubMed

    Rojas, Mario; Masip, David; Todorov, Alexander; Vitria, Jordi

    2011-01-01

    Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions.

  14. Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models

    PubMed Central

    Rojas Q., Mario; Masip, David; Todorov, Alexander; Vitria, Jordi

    2011-01-01

    Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions. PMID:21858069

  15. An Efficient Scheme for Crystal Structure Prediction Based on Structural Motifs

    DOE PAGES

    Zhu, Zizhong; Wu, Ping; Wu, Shunqing; ...

    2017-05-15

    An efficient scheme based on structural motifs is proposed for the crystal structure prediction of materials. The key advantage of the present method comes in two fold: first, the degrees of freedom of the system are greatly reduced, since each structural motif, regardless of its size, can always be described by a set of parameters (R, θ, φ) with five degrees of freedom; second, the motifs could always appear in the predicted structures when the energies of the structures are relatively low. Both features make the present scheme a very efficient method for predicting desired materials. The method has beenmore » applied to the case of LiFePO4, an important cathode material for lithium-ion batteries. Numerous new structures of LiFePO4 have been found, compared to those currently available, available, demonstrating the reliability of the present methodology and illustrating the promise of the concept of structural motifs.« less

  16. Integrating perception and problem solving to predict complex object behaviours

    NASA Astrophysics Data System (ADS)

    Lyons, Damian M.; Chaudhry, Sirhan; Agica, Marius; Monaco, John Vincent

    2010-04-01

    One of the objectives of Cognitive Robotics is to construct robot systems that can be directed to achieve realworld goals by high-level directions rather than complex, low-level robot programming. Such a system must have the ability to represent, problem-solve and learn about its environment as well as communicate with other agents. In previous work, we have proposed ADAPT, a Cognitive Architecture that views perception as top-down and goaloriented and part of the problem solving process. Our approach is linked to a SOAR-based problem-solving and learning framework. In this paper, we present an architecture for the perceptive and world modelling components of ADAPT and report on experimental results using this architecture to predict complex object behaviour. A novel aspect of our approach is a 'mirror system' that ensures that the modelled background and foreground objects are synchronized with observations and task-based expectations. This is based on our prior work on comparing real and synthetic images. We show results for a moving object that collides and rebounds from its environment, hence showing that this perception-based problem solving approach has the potential to be used to predict complex object motions.

  17. Integrated Strategy Improves the Prediction Accuracy of miRNA in Large Dataset

    PubMed Central

    Lipps, David; Devineni, Sree

    2016-01-01

    MiRNAs are short non-coding RNAs of about 22 nucleotides, which play critical roles in gene expression regulation. The biogenesis of miRNAs is largely determined by the sequence and structural features of their parental RNA molecules. Based on these features, multiple computational tools have been developed to predict if RNA transcripts contain miRNAs or not. Although being very successful, these predictors started to face multiple challenges in recent years. Many predictors were optimized using datasets of hundreds of miRNA samples. The sizes of these datasets are much smaller than the number of known miRNAs. Consequently, the prediction accuracy of these predictors in large dataset becomes unknown and needs to be re-tested. In addition, many predictors were optimized for either high sensitivity or high specificity. These optimization strategies may bring in serious limitations in applications. Moreover, to meet continuously raised expectations on these computational tools, improving the prediction accuracy becomes extremely important. In this study, a meta-predictor mirMeta was developed by integrating a set of non-linear transformations with meta-strategy. More specifically, the outputs of five individual predictors were first preprocessed using non-linear transformations, and then fed into an artificial neural network to make the meta-prediction. The prediction accuracy of meta-predictor was validated using both multi-fold cross-validation and independent dataset. The final accuracy of meta-predictor in newly-designed large dataset is improved by 7% to 93%. The meta-predictor is also proved to be less dependent on datasets, as well as has refined balance between sensitivity and specificity. This study has two folds of importance: First, it shows that the combination of non-linear transformations and artificial neural networks improves the prediction accuracy of individual predictors. Second, a new miRNA predictor with significantly improved prediction accuracy

  18. A performance comparison of integration algorithms in simulating flexible structures

    NASA Technical Reports Server (NTRS)

    Howe, R. M.

    1989-01-01

    Asymptotic formulas for the characteristic root errors as well as transfer function gain and phase errors are presented for a number of traditional and new integration methods. Normalized stability regions in the lambda h plane are compared for the various methods. In particular, it is shown that a modified form of Euler integration with root matching is an especially efficient method for simulating lightly-damped structural modes. The method has been used successfully for structural bending modes in the real-time simulation of missiles. Performance of this algorithm is compared with other special algorithms, including the state-transition method. A predictor-corrector version of the modified Euler algorithm permits it to be extended to the simulation of nonlinear models of the type likely to be obtained when using the discretized structure approach. Performance of the different integration methods is also compared for integration step sizes larger than those for which the asymptotic formulas are valid. It is concluded that many traditional integration methods, such as RD-4, are not competitive in the simulation of lightly damped structures.

  19. Prediction of RNA secondary structure, including pseudoknotting, by computer simulation.

    PubMed Central

    Abrahams, J P; van den Berg, M; van Batenburg, E; Pleij, C

    1990-01-01

    A computer program is presented which determines the secondary structure of linear RNA molecules by simulating a hypothetical process of folding. This process implies the concept of 'nucleation centres', regions in RNA which locally trigger the folding. During the simulation, the RNA is allowed to fold into pseudoknotted structures, unlike all other programs predicting RNA secondary structure. The simulation uses published, experimentally determined free energy values for nearest neighbour base pair stackings and loop regions, except for new extrapolated values for loops larger than seven nucleotides. The free energy value for a loop arising from pseudoknot formation is set to a single, estimated value of 4.2 kcal/mole. Especially in the case of long RNA sequences, our program appears superior to other secondary structure predicting programs described so far, as tests on tRNAs, the LSU intron of Tetrahymena thermophila and a number of plant viral RNAs show. In addition, pseudoknotted structures are often predicted successfully. The program is written in mainframe APL and is adapted to run on IBM compatible PCs, Atari ST and Macintosh personal computers. On an 8 MHz 8088 standard PC without coprocessor, using STSC APL, it folds a sequence of 700 nucleotides in one and a half hour. PMID:1693421

  20. RNA Secondary Structure Prediction Using High-throughput SHAPE

    PubMed Central

    Purzycka, Katarzyna J.; Rausch, Jason W.; Le Grice, Stuart F.J.

    2013-01-01

    Understanding the function of RNA involved in biological processes requires a thorough knowledge of RNA structure. Toward this end, the methodology dubbed "high-throughput selective 2' hydroxyl acylation analyzed by primer extension", or SHAPE, allows prediction of RNA secondary structure with single nucleotide resolution. This approach utilizes chemical probing agents that preferentially acylate single stranded or flexible regions of RNA in aqueous solution. Sites of chemical modification are detected by reverse transcription of the modified RNA, and the products of this reaction are fractionated by automated capillary electrophoresis (CE). Since reverse transcriptase pauses at those RNA nucleotides modified by the SHAPE reagents, the resulting cDNA library indirectly maps those ribonucleotides that are single stranded in the context of the folded RNA. Using ShapeFinder software, the electropherograms produced by automated CE are processed and converted into nucleotide reactivity tables that are themselves converted into pseudo-energy constraints used in the RNAStructure (v5.3) prediction algorithm. The two-dimensional RNA structures obtained by combining SHAPE probing with in silico RNA secondary structure prediction have been found to be far more accurate than structures obtained using either method alone. PMID:23748604

  1. Predicted structures of two proteins involved in human diseases.

    PubMed

    Zhou, H X; Wang, G

    2001-01-01

    Structures of 79 proteins involved in human diseases were predicted by sequence alignments with structural templates. The predicted structures for ALDP and CSA, proteins responsible for adrenoleukodystrophy and the Cockayne syndrome, respectively, were analyzed to elucidate the molecular basis of disease mutations. In particular we positioned residue P484 of ALDP in the homodimer interface. This positioning is consistent with a recent experimental finding that the mutation P484R significantly decreases the self-interaction of ALDP and suggests that the disease mechanism of this mutation lies in the impaired ALDP dimerization. We identified two new WD repeats in CSA and suggest that one of these forms part of the interaction surface with other proteins.

  2. Behavior predicts genes structure in a wild primate group.

    PubMed

    Altmann, J; Alberts, S C; Haines, S A; Dubach, J; Muruthi, P; Coote, T; Geffen, E; Cheesman, D J; Mututua, R S; Saiyalel, S N; Wayne, R K; Lacy, R C; Bruford, M W

    1996-06-11

    The predictability of genetic structure from social structure and differential mating success was tested in wild baboons. Baboon populations are subdivided into cohesive social groups that include multiple adults of both sexes. As in many mammals, males are the dispersing sex. Social structure and behavior successfully predicted molecular genetic measures of relatedness and variance in reproductive success. In the first quantitative test of the priority-of-access model among wild primates, the reproductive priority of dominant males was confirmed by molecular genetic analysis. However, the resultant high short-term variance in reproductive success did not translate into equally high long-term variance because male dominance status was unstable. An important consequence of high but unstable short-term variance is that age cohorts will tend to be paternal sibships and social groups will be genetically substructured by age.

  3. Three-dimensional protein structure prediction: Methods and computational strategies.

    PubMed

    Dorn, Márcio; E Silva, Mariel Barbachan; Buriol, Luciana S; Lamb, Luis C

    2014-10-12

    A long standing problem in structural bioinformatics is to determine the three-dimensional (3-D) structure of a protein when only a sequence of amino acid residues is given. Many computational methodologies and algorithms have been proposed as a solution to the 3-D Protein Structure Prediction (3-D-PSP) problem. These methods can be divided in four main classes: (a) first principle methods without database information; (b) first principle methods with database information; (c) fold recognition and threading methods; and (d) comparative modeling methods and sequence alignment strategies. Deterministic computational techniques, optimization techniques, data mining and machine learning approaches are typically used in the construction of computational solutions for the PSP problem. Our main goal with this work is to review the methods and computational strategies that are currently used in 3-D protein prediction.

  4. Predicted performance of an integrated modular engine system

    NASA Technical Reports Server (NTRS)

    Binder, Michael; Felder, James L.

    1993-01-01

    Space vehicle propulsion systems are traditionally comprised of a cluster of discrete engines, each with its own set of turbopumps, valves, and a thrust chamber. The Integrated Modular Engine (IME) concept proposes a vehicle propulsion system comprised of multiple turbopumps, valves, and thrust chambers which are all interconnected. The IME concept has potential advantages in fault-tolerance, weight, and operational efficiency compared with the traditional clustered engine configuration. The purpose of this study is to examine the steady-state performance of an IME system with various components removed to simulate fault conditions. An IME configuration for a hydrogen/oxygen expander cycle propulsion system with four sets of turbopumps and eight thrust chambers has been modeled using the Rocket Engine Transient Simulator (ROCETS) program. The nominal steady-state performance is simulated, as well as turbopump thrust chamber and duct failures. The impact of component failures on system performance is discussed in the context of the system's fault tolerant capabilities.

  5. Surface Integrity in Turning of Annealed Brass: Hardness Prediction

    NASA Astrophysics Data System (ADS)

    Zurita, O.; Di Graci, V.

    2012-07-01

    The purpose of this study was to obtain a comprehensive understanding of the effects of cutting parameters (depth of cut, feed rate, and cutting speed) on the surface integrity of, in terms of superficial hardening, annealed brass during a turning process. The results indicate that no significant phase transformations occurred for any of the turning conditions evaluated; however, microstructural changes were observed, as well as changes in the superficial hardness were measured. It was found that when the studied cutting parameters increase, the superficial hardness increases, with the cutting speed having less influence (2.56%), and feed rate having the greatest effect (22.67%). Finally, a mathematical expression is proposed, which relates the cutting parameters to the maximum hardness obtained for a given cutting condition.

  6. Predicted performance of an Integrated Modular Engine system

    NASA Technical Reports Server (NTRS)

    Binder, Michael; Felder, James L.

    1993-01-01

    Space vehicle propulsion systems are traditionally comprised of a cluster of discrete engines, each with its own set of turbopumps, valves, and a thrust chamber. The Integrated Modular Engine (IME) concept proposes a vehicle propulsion system comprised of multiple turbopumps, valves, and thrust chambers which are all interconnected. The IME concept has potential advantages in fault-tolerance, weight, and operational efficiency compared with the traditional clustered engine configuration. The purpose of this study is to examine the steady-state performance of an IME system with various components removed to simulate fault conditions. An IME configuration for a hydrogen/oxygen expander cycle propulsion system with four sets of turbopumps and eight thrust chambers has been modeled using the Rocket Engine Transient Simulator program. The nominal steady-state performance is simulated, as well as turbopump, thrust chamber, and duct failures. The impact of component failures on system performance is discussed in the context of the system's fault tolerant capabilities.

  7. Predicted performance of an Integrated Modular Engine system

    NASA Technical Reports Server (NTRS)

    Binder, Michael; Felder, James L.

    1993-01-01

    Space vehicle propulsion systems are traditionally comprised of a cluster of discrete engines, each with its own set of turbopumps, valves, and a thrust chamber. The Integrated Modular Engine (IME) concept proposes a vehicle propulsion system comprised of multiple turbopumps, valves, and thrust chambers which are all interconnected. The IME concept has potential advantages in fault-tolerance, weight, and operational efficiency compared with the traditional clustered engine configuration. The purpose of this study is to examine the steady-state performance of an IME system with various components removed to simulate fault conditions. An IME configuration for a hydrogen/oxygen expander cycle propulsion system with four sets of turbopumps and eight thrust chambers has been modeled using the Rocket Engine Transient Simulator program. The nominal steady-state performance is simulated, as well as turbopump, thrust chamber, and duct failures. The impact of component failures on system performance is discussed in the context of the system's fault tolerant capabilities.

  8. Integrative model for predicting thermal balance in exercising horses.

    PubMed

    Mostert, H J; Lund, R J; Guthrie, A J; Cilliers, P J

    1996-07-01

    A theoretical integrative model was developed to determine the heat balance of horses working in a given environment. This model included the following parameters: metabolic heat gain, solar heat gain, evaporative heat loss due to sweating, respiratory tract heat loss, radiation from the body and heat gain or loss due to convection and conduction. The model developed in this study includes an unique approach for estimating heat loss via evaporation of sweat from the animal's skin surface. Previous studies modelling evaporative heat dissipation were based on the volume of sweat loss. While it is known that the ambient conditions affect evaporation rate, these effects have not been adequately described. The present model assumes the horse's skin surface is adequately represented by a body of water and it describes the interaction of that water body with the atmosphere. It is assumed that sweat has thermodynamic characteristics equivalent to distilled water. Sweat, however, has high electrolyte and protein concentrations and anecdotal evidence has shown that the thermodynamic characteristics may be significantly affected. Further research is, therefore, required to confirm these characteristics for equine sweat. The model describes all factors known to affect the thermal balance of the horse working in a given environment. The relative significance of the various variables on the whole integrative model has been illustrated. The effect of ambient temperature and humidity on the evaporative heat loss, the most significant and critical avenue of heat dissipation, is defined and quantified. The model illustrates clearly how increasing relative humidity limits evaporative heat loss, which can be further compromised when horses exercise on treadmills with no air movement.

  9. Application of Functional Use Predictions to Aid in Structure ...

    EPA Pesticide Factsheets

    Humans are potentially exposed to thousands of anthropogenic chemicals in commerce. Recent work has shown that the bulk of this exposure may occur in near-field indoor environments (e.g., home, school, work, etc.). Advances in suspect screening analyses (SSA) now allow an improved understanding of the chemicals present in these environments. However, due to the nature of suspect screening techniques, investigators are often left with chemical formula predictions, with the possibility of many chemical structures matching to each formula. Here, newly developed quantitative structure-use relationship (QSUR) models are used to identify potential exposure sources for candidate structures. Previously, a suspect screening workflow was introduced and applied to house dust samples collected from the U.S. Department of Housing and Urban Development’s American Healthy Homes Survey (AHHS) [Rager, et al., Env. Int. 88 (2016)]. This workflow utilized the US EPA’s Distributed Structure-Searchable Toxicity (DSSTox) Database to link identified molecular features to molecular formulas, and ultimately chemical structures. Multiple QSUR models were applied to support the evaluation of candidate structures. These QSURs predict the likelihood of a chemical having a functional use commonly associated with consumer products having near-field use. For 3,228 structures identified as possible chemicals in AHHS house dust samples, we were able to obtain the required descriptors to appl

  10. Application of Functional Use Predictions to Aid in Structure ...

    EPA Pesticide Factsheets

    Humans are potentially exposed to thousands of anthropogenic chemicals in commerce. Recent work has shown that the bulk of this exposure may occur in near-field indoor environments (e.g., home, school, work, etc.). Advances in suspect screening analyses (SSA) now allow an improved understanding of the chemicals present in these environments. However, due to the nature of suspect screening techniques, investigators are often left with chemical formula predictions, with the possibility of many chemical structures matching to each formula. Here, newly developed quantitative structure-use relationship (QSUR) models are used to identify potential exposure sources for candidate structures. Previously, a suspect screening workflow was introduced and applied to house dust samples collected from the U.S. Department of Housing and Urban Development’s American Healthy Homes Survey (AHHS) [Rager, et al., Env. Int. 88 (2016)]. This workflow utilized the US EPA’s Distributed Structure-Searchable Toxicity (DSSTox) Database to link identified molecular features to molecular formulas, and ultimately chemical structures. Multiple QSUR models were applied to support the evaluation of candidate structures. These QSURs predict the likelihood of a chemical having a functional use commonly associated with consumer products having near-field use. For 3,228 structures identified as possible chemicals in AHHS house dust samples, we were able to obtain the required descriptors to appl

  11. A Model for Predicting Integrated Man-Machine System Reliability: Model Logic and Description

    DTIC Science & Technology

    1974-11-01

    A MODEL FOR PREDICTING INTEGRATED MAN-MACHINE SYSTEMS RELIABILITY prepared for Naval Si nand Deparrmem aw nr. Con :’III’lit UNCLASSIFIED...was substantially modified so as to allow its use for system reliability and system availability predictive purposes. The resultant new model is...from 4 to 20 members was substantially modified so as to allow its use for system reliability and system availability predictive purposes. The

  12. Solvent structure improves docking prediction in lectin-carbohydrate complexes.

    PubMed

    Gauto, Diego F; Petruk, Ariel A; Modenutti, Carlos P; Blanco, Juan I; Di Lella, Santiago; Martí, Marcelo A

    2013-02-01

    Recognition and complex formation between proteins and carbohydrates is a key issue in many important biological processes. Determination of the three-dimensional structure of such complexes is thus most relevant, but particularly challenging because of their usually low binding affinity. In silico docking methods have a long-standing tradition in predicting protein-ligand complexes, and allow a potentially fast exploration of a number of possible protein-carbohydrate complex structures. However, determining which of these predicted complexes represents the correct structure is not always straightforward. In this work, we present a modification of the scoring function provided by AutoDock4, a widely used docking software, on the basis of analysis of the solvent structure adjacent to the protein surface, as derived from molecular dynamics simulations, that allows the definition and characterization of regions with higher water occupancy than the bulk solvent, called water sites. They mimic the interaction held between the carbohydrate -OH groups and the protein. We used this information for an improved docking method in relation to its capacity to correctly predict the protein-carbohydrate complexes for a number of tested proteins, whose ligands range in size from mono- to tetrasaccharide. Our results show that the presented method significantly improves the docking predictions. The resulting solvent-structure-biased docking protocol, therefore, appears as a powerful tool for the design and optimization of development of glycomimetic drugs, while providing new insights into protein-carbohydrate interactions. Moreover, the achieved improvement also underscores the relevance of the solvent structure to the protein carbohydrate recognition process.

  13. A Fully Bayesian Approach to Improved Calibration and Prediction of Groundwater Models With Structure Error

    NASA Astrophysics Data System (ADS)

    Xu, T.; Valocchi, A. J.

    2014-12-01

    Effective water resource management typically relies on numerical models to analyse groundwater flow and solute transport processes. These models are usually subject to model structure error due to simplification and/or misrepresentation of the real system. As a result, the model outputs may systematically deviate from measurements, thus violating a key assumption for traditional regression-based calibration and uncertainty analysis. On the other hand, model structure error induced bias can be described statistically in an inductive, data-driven way based on historical model-to-measurement misfit. We adopt a fully Bayesian approach that integrates a Gaussian process error model to account for model structure error to the calibration, prediction and uncertainty analysis of groundwater models. The posterior distributions of parameters of the groundwater model and the Gaussian process error model are jointly inferred using DREAM, an efficient Markov chain Monte Carlo sampler. We test the usefulness of the fully Bayesian approach towards a synthetic case study of surface-ground water interaction under changing pumping conditions. We first illustrate through this example that traditional least squares regression without accounting for model structure error yields biased parameter estimates due to parameter compensation as well as biased predictions. In contrast, the Bayesian approach gives less biased parameter estimates. Moreover, the integration of a Gaussian process error model significantly reduces predictive bias and leads to prediction intervals that are more consistent with observations. The results highlight the importance of explicit treatment of model structure error especially in circumstances where subsequent decision-making and risk analysis require accurate prediction and uncertainty quantification. In addition, the data-driven error modelling approach is capable of extracting more information from observation data than using a groundwater model alone.

  14. 'Unite and conquer': enhanced prediction of protein subcellular localization by integrating multiple specialized tools

    PubMed Central

    Shen, Yao Qing; Burger, Gertraud

    2007-01-01

    Background Knowing the subcellular location of proteins provides clues to their function as well as the interconnectivity of biological processes. Dozens of tools are available for predicting protein location in the eukaryotic cell. Each tool performs well on certain data sets, but their predictions often disagree for a given protein. Since the individual tools each have particular strengths, we set out to integrate them in a way that optimally exploits their potential. The method we present here is applicable to various subcellular locations, but tailored for predicting whether or not a protein is localized in mitochondria. Knowledge of the mitochondrial proteome is relevant to understanding the role of this organelle in global cellular processes. Results In order to develop a method for enhanced prediction of subcellular localization, we integrated the outputs of available localization prediction tools by several strategies, and tested the performance of each strategy with known mitochondrial proteins. The accuracy obtained (up to 92%) surpasses by far the individual tools. The method of integration proved crucial to the performance. For the prediction of mitochondrion-located proteins, integration via a two-layer decision tree clearly outperforms simpler methods, as it allows emphasis of biologically relevant features such as the mitochondrial targeting peptide and transmembrane domains. Conclusion We developed an approach that enhances the prediction accuracy of mitochondrial proteins by uniting the strength of specialized tools. The combination of machine-learning based integration with biological expert knowledge leads to improved performance. This approach also alleviates the conundrum of how to choose between conflicting predictions. Our approach is easy to implement, and applicable to predicting subcellular locations other than mitochondria, as well as other biological features. For a trial of our approach, we provide a webservice for mitochondrial protein

  15. A graphic approach to evaluate algorithms of secondary structure prediction.

    PubMed

    Zhang, C T; Zhang, R

    2000-04-01

    Algorithms of secondary structure prediction have undergone the developments of nearly 30 years. However, the problem of how to appropriately evaluate and compare algorithms has not yet completely solved. A graphic method to evaluate algorithms of secondary structure prediction has been proposed here. Traditionally, the performance of an algorithm is evaluated by a number, i.e., accuracy of various definitions. Instead of a number, we use a graph to completely evaluate an algorithm, in which the mapping points are distributed in a three-dimensional space. Each point represents the predictive result of the secondary structure of a protein. Because the distribution of mapping points in the 3D space generally contains more information than a number or a set of numbers, it is expected that algorithms may be evaluated and compared by the proposed graphic method more objectively. Based on the point distribution, six evaluation parameters are proposed, which describe the overall performance of the algorithm evaluated. Furthermore, the graphic method is simple and intuitive. As an example of application, two advanced algorithms, i.e., the PHD and NNpredict methods, are evaluated and compared. It is shown that there is still much room for further improvement for both algorithms. It is pointed out that the accuracy for predicting either the alpha-helix or beta-strand in proteins with higher alpha-helix or beta-strand content, respectively, should be greatly improved for both algorithms.

  16. Integration of Multi-Modal Biomedical Data to Predict Cancer Grade and Patient Survival

    PubMed Central

    Phan, John H.; Hoffman, Ryan; Kothari, Sonal; Wu, Po-Yen; Wang, May D.

    2016-01-01

    The Big Data era in Biomedical research has resulted in large-cohort data repositories such as The Cancer Genome Atlas (TCGA). These repositories routinely contain hundreds of matched patient samples for genomic, proteomic, imaging, and clinical data modalities, enabling holistic and multi-modal integrative analysis of human disease. Using TCGA renal and ovarian cancer data, we conducted a novel investigation of multi-modal data integration by combining histopathological image and RNA-seq data. We compared the performances of two integrative prediction methods: majority vote and stacked generalization. Results indicate that integration of multiple data modalities improves prediction of cancer grade and outcome. Specifically, stacked generalization, a method that integrates multiple data modalities to produce a single prediction result, outperforms both single-data-modality prediction and majority vote. Moreover, stacked generalization reveals the contribution of each data modality (and specific features within each data modality) to the final prediction result and may provide biological insights to explain prediction performance. PMID:27493999

  17. An integrable system and associated integrable models as well as Hamiltonian structures

    NASA Astrophysics Data System (ADS)

    Tam, Hon-Wah; Zhang, Yufeng

    2012-10-01

    Starting from an existed Lie algebra introduces a new Lie algebra A1 = {e1, e2, e3} so that two isospectral Lax matrices are established. By employing the Tu scheme an integrable equation hierarchy denoted by IEH is obtained from which a few reduced evolution equations are presented. One of them is the mKdV equation. The elliptic variable solutions and three kinds of Darboux transformations for one coupled equation which is from the IEH are worked out, respectively. Finally, we take use of the Lie algebra A1 to generate eight higher-dimensional Lie algebras from which the linear integrable couplings, the nonlinear integrable couplings, and the bi-integrable couplings of the IEH are engendered, whose Hamiltonian structures are also obtained by the variational identity. Then further reduce one coupled integrable equation to get a nonlinear generalized mKdV equation.

  18. Integrating Transcriptomic and Proteomic Data Using Predictive Regulatory Network Models of Host Response to Pathogens

    PubMed Central

    Chasman, Deborah; Walters, Kevin B.; Lopes, Tiago J. S.; Eisfeld, Amie J.; Kawaoka, Yoshihiro; Roy, Sushmita

    2016-01-01

    Mammalian host response to pathogenic infections is controlled by a complex regulatory network connecting regulatory proteins such as transcription factors and signaling proteins to target genes. An important challenge in infectious disease research is to understand molecular similarities and differences in mammalian host response to diverse sets of pathogens. Recently, systems biology studies have produced rich collections of omic profiles measuring host response to infectious agents such as influenza viruses at multiple levels. To gain a comprehensive understanding of the regulatory network driving host response to multiple infectious agents, we integrated host transcriptomes and proteomes using a network-based approach. Our approach combines expression-based regulatory network inference, structured-sparsity based regression, and network information flow to infer putative physical regulatory programs for expression modules. We applied our approach to identify regulatory networks, modules and subnetworks that drive host response to multiple influenza infections. The inferred regulatory network and modules are significantly enriched for known pathways of immune response and implicate apoptosis, splicing, and interferon signaling processes in the differential response of viral infections of different pathogenicities. We used the learned network to prioritize regulators and study virus and time-point specific networks. RNAi-based knockdown of predicted regulators had significant impact on viral replication and include several previously unknown regulators. Taken together, our integrated analysis identified novel module level patterns that capture strain and pathogenicity-specific patterns of expression and helped identify important regulators of host response to influenza infection. PMID:27403523

  19. Integrating Transcriptomic and Proteomic Data Using Predictive Regulatory Network Models of Host Response to Pathogens.

    PubMed

    Chasman, Deborah; Walters, Kevin B; Lopes, Tiago J S; Eisfeld, Amie J; Kawaoka, Yoshihiro; Roy, Sushmita

    2016-07-01

    Mammalian host response to pathogenic infections is controlled by a complex regulatory network connecting regulatory proteins such as transcription factors and signaling proteins to target genes. An important challenge in infectious disease research is to understand molecular similarities and differences in mammalian host response to diverse sets of pathogens. Recently, systems biology studies have produced rich collections of omic profiles measuring host response to infectious agents such as influenza viruses at multiple levels. To gain a comprehensive understanding of the regulatory network driving host response to multiple infectious agents, we integrated host transcriptomes and proteomes using a network-based approach. Our approach combines expression-based regulatory network inference, structured-sparsity based regression, and network information flow to infer putative physical regulatory programs for expression modules. We applied our approach to identify regulatory networks, modules and subnetworks that drive host response to multiple influenza infections. The inferred regulatory network and modules are significantly enriched for known pathways of immune response and implicate apoptosis, splicing, and interferon signaling processes in the differential response of viral infections of different pathogenicities. We used the learned network to prioritize regulators and study virus and time-point specific networks. RNAi-based knockdown of predicted regulators had significant impact on viral replication and include several previously unknown regulators. Taken together, our integrated analysis identified novel module level patterns that capture strain and pathogenicity-specific patterns of expression and helped identify important regulators of host response to influenza infection.

  20. Multifunctional Structure for Exploration Rovers Integrating Power and Storage Capabilities

    NASA Astrophysics Data System (ADS)

    Atxaga, G.; Arrizabalaga, I.; Alonso, R.; Segura, M.; Mendizabal, M.; Marcos, J.; Cook, A.; Walker, S.; Foster, J.; Kireitseu, M.; Fontana, Q.

    2014-06-01

    A need for light-weight structures with a performance comparable to current solutions and which satisfies future scientific needs is identified to be important for future planetary surface exploration missions. Improvements are necessary on the reduction of the mass of the systems that constitute the Rover. Multifunctional structures are envisioned as possible breakthroughs in the recent advances to reduce space systems mass and volume.One of the activities of ROV-E project has dealt with the development of an external panel integrating solar cells in the external skin and using a battery as core of the structure. The integration of the battery in the structure provides mass and volume savings and therefore an increase the overall efficiency of the system.This paper summarizes the main findings obtained in this activity.

  1. Runoff prediction using an integrated hybrid modelling scheme

    NASA Astrophysics Data System (ADS)

    Remesan, Renji; Shamim, Muhammad Ali; Han, Dawei; Mathew, Jimson

    2009-06-01

    SummaryRainfall runoff is a very complicated process due to its nonlinear and multidimensional dynamics, and hence difficult to model. There are several options for a modeller to consider, for example: the type of input data to be used, the length of model calibration (training) data and whether or not the input data be treated as signals with different frequency bands so that they can be modelled separately. This paper describes a new hybrid modelling scheme to answer the above mentioned questions. The proposed methodology is based on a hybrid model integrating wavelet transformation, a modelling engine (Artificial Neural Network) and the Gamma Test. First, the Gamma Test is used to decide the required input data dimensions and its length. Second, the wavelet transformation decomposes the input signals into different frequency bands. Finally, a modelling engine (ANN in this study) is used to model the decomposed signals separately. The proposed scheme was tested using the Brue catchment, Southwest England, as a case study and has produced very positive results. The hybrid model outperforms all other models tested. This study has a wider implication in the hydrological modelling field since its general framework could be applied to other model combinations (e.g., model engine could be Support Vector Machines, neuro-fuzzy systems, or even a conceptual model. The signal decomposition could be carried out by Fourier transformation).

  2. Large-Deformation Displacement Transfer Functions for Shape Predictions of Highly Flexible Slender Aerospace Structures

    NASA Technical Reports Server (NTRS)

    Ko, William L.; Fleischer, Van Tran

    2013-01-01

    Large deformation displacement transfer functions were formulated for deformed shape predictions of highly flexible slender structures like aircraft wings. In the formulation, the embedded beam (depth wise cross section of structure along the surface strain sensing line) was first evenly discretized into multiple small domains, with surface strain sensing stations located at the domain junctures. Thus, the surface strain (bending strains) variation within each domain could be expressed with linear of nonlinear function. Such piecewise approach enabled piecewise integrations of the embedded beam curvature equations [classical (Eulerian), physical (Lagrangian), and shifted curvature equations] to yield closed form slope and deflection equations in recursive forms.

  3. PDBalert: automatic, recurrent remote homology tracking and protein structure prediction

    PubMed Central

    Agarwal, Vatsal; Remmert, Michael; Biegert, Andreas; Söding, Johannes

    2008-01-01

    Background During the last years, methods for remote homology detection have grown more and more sensitive and reliable. Automatic structure prediction servers relying on these methods can generate useful 3D models even below 20% sequence identity between the protein of interest and the known structure (template). When no homologs can be found in the protein structure database (PDB), the user would need to rerun the same search at regular intervals in order to make timely use of a template once it becomes available. Results PDBalert is a web-based automatic system that sends an email alert as soon as a structure with homology to a protein in the user's watch list is released to the PDB database or appears among the sequences on hold. The mail contains links to the search results and to an automatically generated 3D homology model. The sequence search is performed with the same software as used by the very sensitive and reliable remote homology detection server HHpred, which is based on pairwise comparison of Hidden Markov models. Conclusion PDBalert will accelerate the information flow from the PDB database to all those who can profit from the newly released protein structures for predicting the 3D structure or function of their proteins of interest. PMID:19025670

  4. Generalized Pattern Search Algorithm for Peptide Structure Prediction

    PubMed Central

    Nicosia, Giuseppe; Stracquadanio, Giovanni

    2008-01-01

    Finding the near-native structure of a protein is one of the most important open problems in structural biology and biological physics. The problem becomes dramatically more difficult when a given protein has no regular secondary structure or it does not show a fold similar to structures already known. This situation occurs frequently when we need to predict the tertiary structure of small molecules, called peptides. In this research work, we propose a new ab initio algorithm, the generalized pattern search algorithm, based on the well-known class of Search-and-Poll algorithms. We performed an extensive set of simulations over a well-known set of 44 peptides to investigate the robustness and reliability of the proposed algorithm, and we compared the peptide conformation with a state-of-the-art algorithm for peptide structure prediction known as PEPstr. In particular, we tested the algorithm on the instances proposed by the originators of PEPstr, to validate the proposed algorithm; the experimental results confirm that the generalized pattern search algorithm outperforms PEPstr by 21.17% in terms of average root mean-square deviation, RMSD Cα. PMID:18487293

  5. 3D-Fun: predicting enzyme function from structure.

    PubMed

    von Grotthuss, Marcin; Plewczynski, Dariusz; Vriend, Gert; Rychlewski, Leszek

    2008-07-01

    The 'omics' revolution is causing a flurry of data that all needs to be annotated for it to become useful. Sequences of proteins of unknown function can be annotated with a putative function by comparing them with proteins of known function. This form of annotation is typically performed with BLAST or similar software. Structural genomics is nowadays also bringing us three dimensional structures of proteins with unknown function. We present here software that can be used when sequence comparisons fail to determine the function of a protein with known structure but unknown function. The software, called 3D-Fun, is implemented as a server that runs at several European institutes and is freely available for everybody at all these sites. The 3D-Fun servers accept protein coordinates in the standard PDB format and compare them with all known protein structures by 3D structural superposition using the 3D-Hit software. If structural hits are found with proteins with known function, these are listed together with their function and some vital comparison statistics. This is conceptually very similar in 3D to what BLAST does in 1D. Additionally, the superposition results are displayed using interactive graphics facilities. Currently, the 3D-Fun system only predicts enzyme function but an expanded version with Gene Ontology predictions will be available soon. The server can be accessed at http://3dfun.bioinfo.pl/ or at http://3dfun.cmbi.ru.nl/.

  6. Structural Integrity Program for INTEC Calcined Solids Storage Facilities

    SciTech Connect

    Jeffrey Bryant

    2008-08-30

    This report documents the activities of the structural integrity program at the Idaho Nuclear Technology and Engineering Center relevant to the high-level waste Calcined Solids Storage Facilities and associated equipment, as required by DOE M 435.1-1, 'Radioactive Waste Management Manual'. Based on the evaluation documented in this report, the Calcined Solids Storage Facilities are not leaking and are s