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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. Integrating chemical footprinting data into RNA secondary structure prediction.

    PubMed

    Zarringhalam, Kourosh; Meyer, Michelle M; Dotu, Ivan; Chuang, Jeffrey H; Clote, Peter

    2012-01-01

    Chemical and enzymatic footprinting experiments, such as shape (selective 2'-hydroxyl acylation analyzed by primer extension), yield important information about RNA secondary structure. Indeed, since the [Formula: see text]-hydroxyl is reactive at flexible (loop) regions, but unreactive at base-paired regions, shape yields quantitative data about which RNA nucleotides are base-paired. Recently, low error rates in secondary structure prediction have been reported for three RNAs of moderate size, by including base stacking pseudo-energy terms derived from shape data into the computation of minimum free energy secondary structure. Here, we describe a novel method, RNAsc (RNA soft constraints), which includes pseudo-energy terms for each nucleotide position, rather than only for base stacking positions. We prove that RNAsc is self-consistent, in the sense that the nucleotide-specific probabilities of being unpaired in the low energy Boltzmann ensemble always become more closely correlated with the input shape data after application of RNAsc. From this mathematical perspective, the secondary structure predicted by RNAsc should be 'correct', in as much as the shape data is 'correct'. We benchmark RNAsc against the previously mentioned method for eight RNAs, for which both shape data and native structures are known, to find the same accuracy in 7 out of 8 cases, and an improvement of 25% in one case. Furthermore, we present what appears to be the first direct comparison of shape data and in-line probing data, by comparing yeast asp-tRNA shape data from the literature with data from in-line probing experiments we have recently performed. With respect to several criteria, we find that shape data appear to be more robust than in-line probing data, at least in the case of asp-tRNA.

  3. 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.

  4. Superfamily Assignments for the Yeast Proteome through Integration of Structure Prediction with the Gene Ontology

    PubMed Central

    Malmström, Lars; Riffle, Michael; Strauss, Charlie E. M; Chivian, Dylan; Davis, Trisha N; Bonneau, Richard; Baker, David

    2007-01-01

    Saccharomyces cerevisiae is one of the best-studied model organisms, yet the three-dimensional structure and molecular function of many yeast proteins remain unknown. Yeast proteins were parsed into 14,934 domains, and those lacking sequence similarity to proteins of known structure were folded using the Rosetta de novo structure prediction method on the World Community Grid. This structural data was integrated with process, component, and function annotations from the Saccharomyces Genome Database to assign yeast protein domains to SCOP superfamilies using a simple Bayesian approach. We have predicted the structure of 3,338 putative domains and assigned SCOP superfamily annotations to 581 of them. We have also assigned structural annotations to 7,094 predicted domains based on fold recognition and homology modeling methods. The domain predictions and structural information are available in an online database at http://rd.plos.org/10.1371_journal.pbio.0050076_01. PMID:17373854

  5. Superfamily assignments for the yeast proteome through integration of structure prediction with the gene ontology.

    PubMed

    Malmström, Lars; Riffle, Michael; Strauss, Charlie E M; Chivian, Dylan; Davis, Trisha N; Bonneau, Richard; Baker, David

    2007-04-01

    Saccharomyces cerevisiae is one of the best-studied model organisms, yet the three-dimensional structure and molecular function of many yeast proteins remain unknown. Yeast proteins were parsed into 14,934 domains, and those lacking sequence similarity to proteins of known structure were folded using the Rosetta de novo structure prediction method on the World Community Grid. This structural data was integrated with process, component, and function annotations from the Saccharomyces Genome Database to assign yeast protein domains to SCOP superfamilies using a simple Bayesian approach. We have predicted the structure of 3,338 putative domains and assigned SCOP superfamily annotations to 581 of them. We have also assigned structural annotations to 7,094 predicted domains based on fold recognition and homology modeling methods. The domain predictions and structural information are available in an online database at http://rd.plos.org/10.1371_journal.pbio.0050076_01.

  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. Structure-based prediction of transcription factor binding specificity using an integrative energy function

    PubMed Central

    Farrel, Alvin; Murphy, Jonathan; Guo, Jun-tao

    2016-01-01

    Transcription factors (TFs) regulate gene expression through binding to specific target DNA sites. Accurate annotation of transcription factor binding sites (TFBSs) at genome scale represents an essential step toward our understanding of gene regulation networks. In this article, we present a structure-based method for computational prediction of TFBSs using a novel, integrative energy (IE) function. The new energy function combines a multibody (MB) knowledge-based potential and two atomic energy terms (hydrogen bond and π interaction) that might not be accurately captured by the knowledge-based potential owing to the mean force nature and low count problem. We applied the new energy function to the TFBS prediction using a non-redundant dataset that consists of TFs from 12 different families. Our results show that the new IE function improves the prediction accuracy over the knowledge-based, statistical potentials, especially for homeodomain TFs, the second largest TF family in mammals. Contact: jguo4@uncc.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307632

  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. Integrity of medial temporal structures may predict better improvement of spatial neglect with prism adaptation treatment

    PubMed Central

    Goedert, Kelly M.; Shah, Priyanka; Foundas, Anne L.; Barrett, A. M.

    2013-01-01

    Prism adaptation treatment (PAT) is a promising rehabilitative method for functional recovery in persons with spatial neglect. Previous research suggests that PAT improves motor-intentional “aiming” deficits that frequently occur with frontal lesions. To test whether presence of frontal lesions predicted better improvement of spatial neglect after PAT, the current study evaluated neglect-specific improvement in functional activities (assessment with the Catherine Bergego Scale) over time in 21 right-brain-damaged stroke survivors with left-sided spatial neglect. The results demonstrated that neglect patients' functional activities improved after two weeks of PAT and continued improving for four weeks. Such functional improvement did not occur equally in all of the participants: Neglect patients with lesions involving the frontal cortex (n=13) experienced significantly better functional improvement than did those without frontal lesions (n=8). More importantly, voxel-based lesion-behavior mapping (VLBM) revealed that in comparison to the group of patients without frontal lesions, the frontal-lesioned neglect patients had intact regions in the medial temporal areas, the superior temporal areas, and the inferior longitudinal fasciculus. The medial cortical and subcortical areas in the temporal lobe were especially distinguished in the “frontal lesion” group. The findings suggest that the integrity of medial temporal structures may play an important role in supporting functional improvement after PAT. PMID:22941243

  10. Integrity of medial temporal structures may predict better improvement of spatial neglect with prism adaptation treatment.

    PubMed

    Chen, Peii; Goedert, Kelly M; Shah, Priyanka; Foundas, Anne L; Barrett, A M

    2014-09-01

    Prism adaptation treatment (PAT) is a promising rehabilitative method for functional recovery in persons with spatial neglect. Previous research suggests that PAT improves motor-intentional "aiming" deficits that frequently occur with frontal lesions. To test whether presence of frontal lesions predicted better improvement of spatial neglect after PAT, the current study evaluated neglect-specific improvement in functional activities (assessment with the Catherine Bergego Scale) over time in 21 right-brain-damaged stroke survivors with left-sided spatial neglect. The results demonstrated that neglect patients' functional activities improved after two weeks of PAT and continued improving for four weeks. Such functional improvement did not occur equally in all of the participants: Neglect patients with lesions involving the frontal cortex (n = 13) experienced significantly better functional improvement than did those without frontal lesions (n = 8). More importantly, voxel-based lesion-behavior mapping (VLBM) revealed that in comparison to the group of patients without frontal lesions, the frontal-lesioned neglect patients had intact regions in the medial temporal areas, the superior temporal areas, and the inferior longitudinal fasciculus. The medial cortical and subcortical areas in the temporal lobe were especially distinguished in the "frontal lesion" group. The findings suggest that the integrity of medial temporal structures may play an important role in supporting functional improvement after PAT.

  11. 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.

  12. An integrative structure-based framework for predicting biological effects mediated by antipeptide antibodies.

    PubMed

    Caoili, Salvador Eugenio C

    2015-12-01

    A general framework is presented for predicting quantitative biological effects mediated by antipeptide antibodies, primarily on the basis of antigen structure (possibly featuring intrinsic disorder) analyzed to estimate epitope-paratope binding affinities, which in turn is considered within the context of dose-response relationships as regards antibody concentration. This is illustrated mainly using an approach based on protein structural energetics, whereby expected amounts of solvent-accessible surface area buried upon epitope-paratope binding are related to the corresponding binding affinity, which is estimated from putative B-cell epitope structure with implicit treatment of paratope structure, for antipeptide antibodies either reacting with peptides or cross-reacting with cognate protein antigens. Key methods described are implemented in SAPPHIRE/SUITE (Structural-energetic Analysis Program for Predicting Humoral Immune Response Epitopes/SAPPHIRE User Interface Tool Ensemble; publicly accessible via http://freeshell.de/~badong/suite.htm). Representative results thus obtained are compared with published experimental data on binding affinities and quantitative biological effects, with special attention to loss of paratope sidechain conformational entropy (neglected in previous analyses) and in light of key in-vivo constraints on antigen-antibody binding affinity and antibody-mediated effects. Implications for further refinement of B-cell epitope prediction methods are discussed as regards envisioned biomedical applications including the development of prophylactic and therapeutic antibodies, peptide-based vaccines and immunodiagnostics. PMID:26410103

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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

  19. 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

    2015-09-01

    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.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. Prediction of estrogen receptor binding for 58,000 chemicals using an integrated system of a tree-based model with structural alerts.

    PubMed Central

    Hong, Huixiao; Tong, Weida; Fang, Hong; Shi, Leming; Xie, Qian; Wu, Jie; Perkins, Roger; Walker, John D; Branham, William; Sheehan, Daniel M

    2002-01-01

    A number of environmental chemicals, by mimicking natural hormones, can disrupt endocrine function in experimental animals, wildlife, and humans. These chemicals, called "endocrine-disrupting chemicals" (EDCs), are such a scientific and public concern that screening and testing 58,000 chemicals for EDC activities is now statutorily mandated. Computational chemistry tools are important to biologists because they identify chemicals most important for in vitro and in vivo studies. Here we used a computational approach with integration of two rejection filters, a tree-based model, and three structural alerts to predict and prioritize estrogen receptor (ER) ligands. The models were developed using data for 232 structurally diverse chemicals (training set) with a 10(6) range of relative binding affinities (RBAs); we then validated the models by predicting ER RBAs for 463 chemicals that had ER activity data (testing set). The integrated model gave a lower false negative rate than any single component for both training and testing sets. When the integrated model was applied to approximately 58,000 potential EDCs, 80% (approximately 46,000 chemicals) were predicted to have negligible potential (log RBA < -4.5, with log RBA = 2.0 for estradiol) to bind ER. The ability to process large numbers of chemicals to predict inactivity for ER binding and to categorically prioritize the remainder provides one biologic measure to prioritize chemicals for entry into more expensive assays (most chemicals have no biologic data of any kind). The general approach for predicting ER binding reported here may be applied to other receptors and/or reversible binding mechanisms involved in endocrine disruption. PMID:11781162

  5. 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.

  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. Identification of miRNA-Mediated Core Gene Module for Glioma Patient Prediction by Integrating High-Throughput miRNA, mRNA Expression and Pathway Structure

    PubMed Central

    Han, Junwei; Shang, Desi; Zhang, Yunpeng; Zhang, Wei; Yao, Qianlan; Han, Lei; Xu, Yanjun; Yan, Wei; Bao, Zhaoshi; You, Gan; Jiang, Tao; Kang, Chunsheng; Li, Xia

    2014-01-01

    The prognosis of glioma patients is usually poor, especially in patients with glioblastoma (World Health Organization (WHO) grade IV). The regulatory functions of microRNA (miRNA) on genes have important implications in glioma cell survival. However, there are not many studies that have investigated glioma survival by integrating miRNAs and genes while also considering pathway structure. In this study, we performed sample-matched miRNA and mRNA expression profilings to systematically analyze glioma patient survival. During this analytical process, we developed pathway-based random walk to identify a glioma core miRNA-gene module, simultaneously considering pathway structure information and multi-level involvement of miRNAs and genes. The core miRNA-gene module we identified was comprised of four apparent sub-modules; all four sub-modules displayed a significant correlation with patient survival in the testing set (P-values≤0.001). Notably, one sub-module that consisted of 6 miRNAs and 26 genes also correlated with survival time in the high-grade subgroup (WHO grade III and IV), P-value = 0.0062. Furthermore, the 26-gene expression signature from this sub-module had robust predictive power in four independent, publicly available glioma datasets. Our findings suggested that the expression signatures, which were identified by integration of miRNA and gene level, were closely associated with overall survival among the glioma patients with various grades. PMID:24809850

  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. 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.

  10. 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.

  11. 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. PMID:22965837

  12. 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.

  13. De Novo Protein Structure Prediction

    NASA Astrophysics Data System (ADS)

    Hung, Ling-Hong; Ngan, Shing-Chung; Samudrala, Ram

    An unparalleled amount of sequence data is being made available from large-scale genome sequencing efforts. The data provide a shortcut to the determination of the function of a gene of interest, as long as there is an existing sequenced gene with similar sequence and of known function. This has spurred structural genomic initiatives with the goal of determining as many protein folds as possible (Brenner and Levitt, 2000; Burley, 2000; Brenner, 2001; Heinemann et al., 2001). The purpose of this is twofold: First, the structure of a gene product can often lead to direct inference of its function. Second, since the function of a protein is dependent on its structure, direct comparison of the structures of gene products can be more sensitive than the comparison of sequences of genes for detecting homology. Presently, structural determination by crystallography and NMR techniques is still slow and expensive in terms of manpower and resources, despite attempts to automate the processes. Computer structure prediction algorithms, while not providing the accuracy of the traditional techniques, are extremely quick and inexpensive and can provide useful low-resolution data for structure comparisons (Bonneau and Baker, 2001). Given the immense number of structures which the structural genomic projects are attempting to solve, there would be a considerable gain even if the computer structure prediction approach were applicable to a subset of proteins.

  14. 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

  15. FINDSITE-metal: Integrating evolutionary information and machine learning for structure-based metal binding site prediction at the proteome level

    PubMed Central

    Brylinski, Michal; Skolnick, Jeffrey

    2010-01-01

    The rapid accumulation of gene sequences, many of which are hypothetical proteins with unknown function, has stimulated the development of accurate computational tools for protein function prediction with evolution/structure-based approaches showing considerable promise. In this paper, we present FINDSITE-metal, a new threading-based method designed specifically to detect metal binding sites in modeled protein structures. Comprehensive benchmarks using different quality protein structures show that weakly homologous protein models provide sufficient structural information for quite accurate annotation by FINDSITE-metal. Combining structure/evolutionary information with machine learning results in highly accurate metal binding annotations; for protein models constructed by TASSER, whose average Cα RMSD from the native structure is 8.9 Å, 59.5% (71.9%) of the best of top five predicted metal locations are within 4 Å (8 Å) from a bound metal in the crystal structure. For most of the targets, multiple metal binding sites are detected with the best predicted binding site at rank 1 and within the top 2 ranks in 65.6% and 83.1% of the cases, respectively. Furthermore, for iron, copper, zinc, calcium and magnesium ions, the binding metal can be predicted with high, typically 70-90%, accuracy. FINDSITE-metal also provides a set of confidence indexes that help assess the reliability of predictions. Finally, we describe the proteome-wide application of FINDSITE-metal that quantifies the metal binding complement of the human proteome. FINDSITE-metal is freely available to the academic community at http://cssb.biology.gatech.edu/findsite-metal/. PMID:21287609

  16. Integrating multiple networks for protein function prediction

    PubMed Central

    2015-01-01

    Background High throughput techniques produce multiple functional association networks. Integrating these networks can enhance the accuracy of protein function prediction. Many algorithms have been introduced to generate a composite network, which is obtained as a weighted sum of individual networks. The weight assigned to an individual network reflects its benefit towards the protein functional annotation inference. A classifier is then trained on the composite network for predicting protein functions. However, since these techniques model the optimization of the composite network and the prediction tasks as separate objectives, the resulting composite network is not necessarily optimal for the follow-up protein function prediction. Results We address this issue by modeling the optimization of the composite network and the prediction problems within a unified objective function. In particular, we use a kernel target alignment technique and the loss function of a network based classifier to jointly adjust the weights assigned to the individual networks. We show that the proposed method, called MNet, can achieve a performance that is superior (with respect to different evaluation criteria) to related techniques using the multiple networks of four example species (yeast, human, mouse, and fly) annotated with thousands (or hundreds) of GO terms. Conclusion MNet can effectively integrate multiple networks for protein function prediction and is robust to the input parameters. Supplementary data is available at https://sites.google.com/site/guoxian85/home/mnet. The Matlab code of MNet is available upon request. PMID:25707434

  17. 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

  18. An Integrated Approach to Predictive Genomic Analytics

    SciTech Connect

    McDermott, Jason E.; Sanfilippo, Antonio P.; Taylor, Ronald C.; Baddeley, Robert L.; Riensche, Roderick M.; Jensen, Russell S.

    2010-08-02

    A variety of methods and algorithms have recently been employed in the analysis of gene expression data, including reverse-engineering and knowledge-based pathway modeling, semantic gene similarity, network analysis and clustering. These methods and algorithms address different subparts of the same overall challenge and need to be applied in combination to address predictive genomic analysis as a whole. In this paper, we present an integrated approach to predictive genomic analysis that achieves this objective and describe an application of the approach to the study of neuroprotection in stroke.

  19. Prediction of Landslide using Integration Technique

    NASA Astrophysics Data System (ADS)

    Saro, Lee; Hyun-Joo, Oh

    2010-05-01

    Integrated techniques were developed, applied, and verified for analysis of landslide susceptibility in Jinbu-myeon, Korea using a Geographic Information System (GIS). Landslide locations were identified in the Jinbu-myeon area from interpretation of digital aerial photographs and field surveys. The topographic, soil, forest, geologic, lineament and land cover data were collected, processed and constructed into a spatial database using GIS data. The factors that influence landslide occurrence, such as slope, aspect, curvature, Topographic Wetness Index (TWI), and Stream Power Index (SPI) of the topography, were calculated from the topographic database. Texture, material, drainage, effective soil thickness and topographic were extracted from the soil database, and type, age, diameter and density of timber were extracted form the forest database. The lithology was extracted from the geological database and lineaments were detected from hillshade map. The structural geologist interpreted the hillshade map and detected the lineaments. The land cover was classified based on the SPOT satellite image. By using the constructed spatial database, the relationships between the detected landslide locations and the seventeen related factors were identified and quantified by likelihood ratio, weight of evidence, logistic regression and artificial neural networks models. The relationships were used as factor ratings in the overlay analysis to create landslide susceptibility indexes and maps. Then the four landslide susceptibility maps were reflected in new input factors and combined using likelihood ratio, weight of evidence, logistic regression and artificial neural network models to make better susceptibility map. All of the susceptibility maps were verified by comparison with known landslide locations, which were not used during the training of the individual models. As the result, the combined landslide susceptibility maps used landslide-related new four input factors showed

  20. 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.

  1. 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.

  2. 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

    NASA Astrophysics Data System (ADS)

    Woodhouse, Mark J.; Behnke, Sonja A.

    2014-08-01

    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.

  3. RNAComposer and RNA 3D structure prediction for nanotechnology.

    PubMed

    Biesiada, Marcin; Pachulska-Wieczorek, Katarzyna; Adamiak, Ryszard W; Purzycka, Katarzyna J

    2016-07-01

    RNAs adopt specific, stable tertiary architectures to perform their activities. Knowledge of RNA tertiary structure is fundamental to understand RNA functions beginning with transcription and ending with turnover. Contrary to advanced RNA secondary structure prediction algorithms, which allow good accuracy when experimental data are integrated into the prediction, tertiary structure prediction of large RNAs still remains a significant challenge. However, the field of RNA tertiary structure prediction is rapidly developing and new computational methods based on different strategies are emerging. RNAComposer is a user-friendly and freely available server for 3D structure prediction of RNA up to 500 nucleotide residues. RNAComposer employs fully automated fragment assembly based on RNA secondary structure specified by the user. Importantly, this method allows incorporation of distance restraints derived from the experimental data to strengthen the 3D predictions. The potential and limitations of RNAComposer are discussed and an application to RNA design for nanotechnology is presented.

  4. 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…

  5. 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. PMID:25977759

  6. 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.

  7. 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

  8. Integrated Predictive Simulations of Sawtooth Oscillations

    NASA Astrophysics Data System (ADS)

    Nguyen, Canh N.; Bateman, G.; Kritz, A.; Porcelli, Franco

    2002-11-01

    The Porcelli model for sawtooth oscillations(F. Porcelli, et al.,) Plasma Phys. Control. Fusion 38, 2163 (1996), which provides a set of criteria for the triggering of sawtooth oscillations, has been implemented in the 11/2D BALDUR integrated predictive modeling code. In this code, sources, sinks and transport are computed self-consistently. In the Porcelli sawtooth model, sawteeth are triggered by any of three criteria for the m=1 mode: 1) kink modes when stabilization by fast ion precession fails, 2) kink modes when diamagnetic rotation stailization fails, and 3) drift tearing modes localized near the q=1 magnetic surface, when stabilization by kinetic layer and rotational effects fails. BALDUR simulations of JET and DIII-D discharges using the theory-based Multi-Mode transport model (MMM95) indicate that most of the sawteeth are triggered by the third criterion, and this criterion is found to be sensitive to the relative amount of magnetic reconnection during each sawtooth crash. The trigger is less frequent when there is more magnetic reconnection. The sawtooth period predicted by the Porcelli model in BALDUR simulations fluctuates in time, which is also observed in experiments. ^Supported by DoE contract DE-FG02-92-ER-54141 equilibrium, energy and particle transport fluxes, sources such as neutral beam heating, sinks such as impurity radiation, and the results of large scale instabilities such as sawtooth oscillations in tokamak plasmas.

  9. Theoretical prediction of crystal structures of rubrene

    NASA Astrophysics Data System (ADS)

    Obata, Shigeaki; Miura, Toshiaki; Shimoi, Yukihiro

    2014-01-01

    We theoretically predict crystal structures and molecular arrangements for rubrene molecule using CONFLEX program and compare them with the experimental ones. The most, second-most, and fourth-most stable predicted crystal structures show good agreement with the triclinic, orthorhombic, and monoclinic polymorphs of rubrene, respectively. The change in molecular conformation is also predicted between crystalline and gas phases: the tetracene backbone takes flat conformation in crystalline phase as in the observed structure. Meanwhile, it is twisted in gas phase. The theoretical prediction method used in this work provides the successful results on the determination of the three kinds of crystal structures and molecular arrangements for rubrene molecule.

  10. 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

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. An integrated compartmental model for prediction of indoor radon concentrations

    SciTech Connect

    Al-Ahmady, K.K.; Hintenlang, D.E.

    1995-12-31

    A carefully selected, heavily instrumented, and fully controlled experimental facility dedicated to research was used to investigate the interaction and effects of key parameters related to the indoor radon problem. Mechanistic and empirical models have been developed in which they return pressure differentials in response to indoor radon driving forces inputs. A semi-diurnal natural pumping model of radon-rich soil gas was based on an exponentially damped response of the sub-slab air volume pressure to changes in atmospheric pressure. A wind-induced pressure differentials model was based on the conservation of energy of the wind speed between the main stream and the structure shell corrected to the effect of wind fluctuation and direction. A temperature-induced pressure differential model was based on the linear approximation of the weakly exponentially-dependent pressures between two temperature zones under hydrostatic equilibrium. Mathematical frameworks were developed to incorporate driving force models into an integrated compartmental model allowed predictions of time-integrated and time-dependent indoor radon concentrations. The integrated predictions are in good agreement with the observed concentrations at the research site.

  17. 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/.

  18. 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.

  19. The MULTICOM protein tertiary structure prediction system.

    PubMed

    Li, Jilong; Bhattacharya, Debswapna; Cao, Renzhi; Adhikari, Badri; Deng, Xin; Eickholt, Jesse; Cheng, Jianlin

    2014-01-01

    With the expansion of genomics and proteomics data aided by the rapid progress of next-generation sequencing technologies, computational prediction of protein three-dimensional structure is an essential part of modern structural genomics initiatives. Prediction of protein structure through understanding of the theories behind protein sequence-structure relationship, however, remains one of the most challenging problems in contemporary life sciences. Here, we describe MULTICOM, a multi-level combination technique, intended to predict moderate- to high-resolution structure of a protein through a novel approach of combining multiple sources of complementary information derived from the experimentally solved protein structures in the Protein Data Bank. The MULTICOM web server is freely available at http://sysbio.rnet.missouri.edu/multicom_toolbox/.

  20. Predicting White Matter Integrity from Multiple Common Genetic Variants

    PubMed Central

    Kohannim, Omid; Jahanshad, Neda; Braskie, Meredith N; Stein, Jason L; Chiang, Ming-Chang; Reese, April H; Hibar, Derrek P; Toga, Arthur W; McMahon, Katie L; de Zubicaray, Greig I; Medland, Sarah E; Montgomery, Grant W; Martin, Nicholas G; Wright, Margaret J; Thompson, Paul M

    2012-01-01

    Several common genetic variants have recently been discovered that appear to influence white matter microstructure, as measured by diffusion tensor imaging (DTI). Each genetic variant explains only a small proportion of the variance in brain microstructure, so we set out to explore their combined effect on the white matter integrity of the corpus callosum. We measured six common candidate single-nucleotide polymorphisms (SNPs) in the COMT, NTRK1, BDNF, ErbB4, CLU, and HFE genes, and investigated their individual and aggregate effects on white matter structure in 395 healthy adult twins and siblings (age: 20–30 years). All subjects were scanned with 4-tesla 94-direction high angular resolution diffusion imaging. When combined using mixed-effects linear regression, a joint model based on five of the candidate SNPs (COMT, NTRK1, ErbB4, CLU, and HFE) explained ∼6% of the variance in the average fractional anisotropy (FA) of the corpus callosum. This predictive model had detectable effects on FA at 82% of the corpus callosum voxels, including the genu, body, and splenium. Predicting the brain's fiber microstructure from genotypes may ultimately help in early risk assessment, and eventually, in personalized treatment for neuropsychiatric disorders in which brain integrity and connectivity are affected. PMID:22510721

  1. Interface Structure Prediction from First-Principles

    SciTech Connect

    Zhao, Xin; Shu, Qiang; Nguyen, Manh Cuong; Wang, Yangang; Ji, Min; Xiang, Hongjun; Ho, Kai-Ming; Gong, Xingao; Wang, Cai-Zhuang

    2014-05-08

    Information about the atomic structures at solid–solid interfaces is crucial for understanding and predicting the performance of materials. Due to the complexity of the interfaces, it is very challenging to resolve their atomic structures using either experimental techniques or computer simulations. In this paper, we present an efficient first-principles computational method for interface structure prediction based on an adaptive genetic algorithm. This approach significantly reduces the computational cost, while retaining the accuracy of first-principles prediction. The method is applied to the investigation of both stoichiometric and nonstoichiometric SrTiO3 Σ3(112)[1¯10] grain boundaries with unit cell containing up to 200 atoms. Several novel low-energy structures are discovered, which provide fresh insights into the structure and stability of the grain boundaries.

  2. Inference on biological mechanisms using an integrated phenotype prediction model.

    PubMed

    Enomoto, Yumi; Ushijima, Masaru; Miyata, Satoshi; Matsuura, Masaaki; Ohtaki, Megu

    2008-03-01

    We propose a methodology for constructing an integrated phenotype prediction model that accounts for multiple pathways regulating a targeted phenotype. The method uses multiple prediction models, each expressing a particular pattern of gene-to-gene interrelationship, such as epistasis. We also propose a methodology using Gene Ontology annotations to infer a biological mechanism from the integrated phenotype prediction model. To construct the integrated models, we employed multiple logistic regression models using a two-step learning approach to examine a number of patterns of gene-to-gene interrelationships. We first selected individual prediction models with acceptable goodness of fit, and then combined the models. The resulting integrated model predicts phenotype as a logical sum of predicted results from the individual models. We used published microarray data on neuroblastoma from Ohira et al (2005) for illustration, constructing an integrated model to predict prognosis and infer the biological mechanisms controlling prognosis. Although the resulting integrated model comprised a small number of genes compared to a previously reported analysis of these data, the model demonstrated excellent performance, with an error rate of 0.12 in a validation analysis. Gene Ontology analysis suggested that prognosis of patients with neuroblastoma may be influenced by biological processes such as cell growth, G-protein signaling, phosphoinositide-mediated signaling, alcohol metabolism, glycolysis, neurophysiological processes, and catecholamine catabolism. PMID:18578362

  3. Interval prediction in structural dynamic analysis

    NASA Technical Reports Server (NTRS)

    Hasselman, Timothy K.; Chrostowski, Jon D.; Ross, Timothy J.

    1992-01-01

    Methods for assessing the predictive accuracy of structural dynamic models are examined with attention given to the effects of modal mass, stiffness, and damping uncertainties. The methods are based on a nondeterministic analysis called 'interval prediction' in which interval variables are used to describe parameters and responses that are unknown. Statistical databases for generic modeling uncertainties are derived from experimental data and incorporated analytically to evaluate responses. Covariance matrices of modal mass, stiffness, and damping parameters are propagated numerically in models of large space structures by means of three methods. The test data tend to fall within the predicted intervals of uncertainty determined by the statistical databases. The present findings demonstrate the suitability of using data from previously analyzed and tested space structures for assessing the predictive accuracy of an analytical model.

  4. Prediction in ungauged estuaries: An integrated theory

    NASA Astrophysics Data System (ADS)

    Savenije, Hubert H. G.

    2015-04-01

    Many estuaries in the world are ungauged. The International Association of Hydrological Sciences completed its science decade on Prediction in Ungauged Basins (PUB) in 2012 (Hrachowitz et al.). Prediction on the basis of limited data is a challenge in hydrology, but not less so in estuaries, where data on fundamental processes are often lacking. In this paper, relatively simple, but science-based, methods are presented that allow researchers, engineers, and water managers to obtain first-order estimates of essential process parameters in estuaries, such as the estuary depth, the tidal amplitude, the tidal excursion, the phase lag, and the salt water intrusion, on the basis of readily obtainable information, such as topographical maps and tidal tables. These apparently simple relationships are assumed to result from the capacity of freely erodible water bodies to adjust themselves to external drivers and to dissipate the free energy from these drivers as efficiently as possible. Thus, it is assumed that these systems operate close to their thermodynamic limit, resulting in predictable patterns that can be described by relatively simple equations. Although still much has to be done to develop an overall physics-based theory, this does not prevent us from making use of the empirical "laws" that we observe in alluvial estuaries.

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

    PubMed Central

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

    2010-01-01

    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 Cα 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 Å, 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. PMID:19927325

  6. Predicting the Fatigue life of Structures

    NASA Technical Reports Server (NTRS)

    Besuner, P. M.; Harris, D. O.; Thomas, J. M.; Allison, D. E.; Bannantine, J. M.; Brown, S. B.; Davis, C. S.; Derbalian, G. A.; Eischen, J. W.; Fowler, G. F.; Osteraas, J. D.; Robinson, J. N.; Sire, R. A.; Vroman, G. A.

    1985-01-01

    Report reviews fracture-mechanics technology for predicting life expectancy of structural components subjected to cyclic loads. Report covers analytical tools for modeling and forecasting subcritical fatigue-crack growth in structures. It emphasizes use of tools in practical, day-to-day problems of engineering design, development, and decisionmaking.

  7. 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

  8. Predicting protein dynamics from structural ensembles

    NASA Astrophysics Data System (ADS)

    Copperman, J.; Guenza, M. G.

    2015-12-01

    The biological properties of proteins are uniquely determined by their structure and dynamics. A protein in solution populates a structural ensemble of metastable configurations around the global fold. From overall rotation to local fluctuations, the dynamics of proteins can cover several orders of magnitude in time scales. We propose a simulation-free coarse-grained approach which utilizes knowledge of the important metastable folded states of the protein to predict the protein dynamics. This approach is based upon the Langevin Equation for Protein Dynamics (LE4PD), a Langevin formalism in the coordinates of the protein backbone. The linear modes of this Langevin formalism organize the fluctuations of the protein, so that more extended dynamical cooperativity relates to increasing energy barriers to mode diffusion. The accuracy of the LE4PD is verified by analyzing the predicted dynamics across a set of seven different proteins for which both relaxation data and NMR solution structures are available. Using experimental NMR conformers as the input structural ensembles, LE4PD predicts quantitatively accurate results, with correlation coefficient ρ = 0.93 to NMR backbone relaxation measurements for the seven proteins. The NMR solution structure derived ensemble and predicted dynamical relaxation is compared with molecular dynamics simulation-derived structural ensembles and LE4PD predictions and is consistent in the time scale of the simulations. The use of the experimental NMR conformers frees the approach from computationally demanding simulations.

  9. 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.

  10. 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.

  11. Microgravity Disturbance Predictions in the Combustion Integrated Rack

    NASA Astrophysics Data System (ADS)

    Just, M.; Grodsinsky, Carlos M.

    2002-01-01

    This paper will focus on the approach used to characterize microgravity disturbances in the Combustion Integrated Rack (CIR), currently scheduled for launch to the International Space Station (ISS) in 2005. Microgravity experiments contained within the CIR are extremely sensitive to vibratory and transient disturbances originating on-board and off-board the rack. Therefore, several techniques are implemented to isolate the critical science locations from external vibration. A combined testing and analysis approach is utilized to predict the resulting microgravity levels at the critical science location. The major topics to be addressed are: 1) CIR Vibration Isolation Approaches, 2) Disturbance Sources and Characterization, 3) Microgravity Predictive Modeling, 4) Science Microgravity Requirements, 6) Microgravity Control, and 7) On-Orbit Disturbance Measurement. The CIR is using the Passive Rack Isolation System (PaRIS) to isolate the rack from offboard rack disturbances. By utilizing this system, CIR is connected to the U.S. Lab module structure by either 13 or 14 umbilical lines and 8 spring / damper isolators. Some on-board CIR disturbers are locally isolated by grommets or wire ropes. CIR's environmental and science on board support equipment such as air circulation fans, pumps, water flow, air flow, solenoid valves, and computer hard drives cause disturbances within the rack. These disturbers along with the rack structure must be characterized to predict whether the on-orbit vibration levels during experimentation exceed the specified science microgravity vibration level requirements. Both vibratory and transient disturbance conditions are addressed. Disturbance levels/analytical inputs are obtained for each individual disturber in a "free floating" condition in the Glenn Research Center (GRC) Microgravity Emissions Lab (MEL). Flight spare hardware is tested on an Orbital Replacement Unit (ORU) basis. Based on test and analysis, maximum disturbance level

  12. Predicting polymeric crystal structures by evolutionary algorithms

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

    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.

  13. 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.

  14. Structural integrity of intelligent materials and structures

    NASA Astrophysics Data System (ADS)

    Sullivan, Brian J.; Buesking, Kent W.

    1994-02-01

    This report focuses on the development of micromechanical algorithms for shape memory alloy composite materials. The composite cylinders assemblage algorithm was utilized to determine the effective thermomechanical properties of shape memory alloy composites. The mathematical development based on this micromechanical model was coded and exercised to predict the response of shape memory alloy fiber/elastomer matrix composites to arbitrary mechanical and thermal loadings.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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. PMID:23702539

  20. [Changing structures--Integrating health].

    PubMed

    Plaumann, M; Lehmann, F; Pawils, S; Walter, U

    2015-09-01

    Changes in (municipal) structures for the improvement of health are often required but, in contrast to behavioural measures, less frequently implemented and scientifically evaluated. Results on this subject for Germany are scarce. In recent years, municipal prevention and health promotion programmes received new impetus from the expansion of the German "Early Assistance" initiative. Early assistance programmes to help children grow up healthy initiated municipal processes such as the establishment of networks between health services and youth welfare services, prevention chains and nationwide initiatives. This has moved issues such as equal opportunities for health into the centre of politically driven structural development efforts. Neighbourhood management groups and municipal round tables on prevention-specific topics etc. have been established throughout Germany. Regarding this structural development, 6 projects from the field of prevention research give a good indication as to how the structure of municipal concepts can be effectively implemented.

  1. Secondary Structure Prediction of Single Sequences Using RNAstructure.

    PubMed

    Xu, Zhenjiang Zech; Mathews, David H

    2016-01-01

    RNA secondary structure is often predicted using folding thermodynamics. RNAstructure is a software package that includes structure prediction by free energy minimization, prediction of base pairing probabilities, prediction of structures composed of highly probably base pairs, and prediction of structures with pseudoknots. A user-friendly graphical user interface is provided, and this interface works on Windows, Apple OS X, and Linux. This chapter provides protocols for using RNAstructure for structure prediction. PMID:27665590

  2. Plated lamination structures for integrated magnetic devices

    DOEpatents

    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.

  3. 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/

  4. 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.

  5. Prediction of packing of secondary structure.

    PubMed

    Nagano, K; Ponnuswamy, P K

    1984-01-01

    An improved method of picking up candidates for predicting the packing arrangement of beta-strands and alpha-helices of the alpha/beta type domains is described here. The method of judging whether the region of the protein would fold into the alpha/beta type or not is also described. The folding constraints of globular proteins are analysed and presented in this article for application to the prediction of packing of secondary structure. The analysis of the residue-fluctuations is also applicable for the purpose.

  6. Predicting Social Integration in the Community among College Students

    ERIC Educational Resources Information Center

    Herrero, Juan; Gracia, Enrique

    2004-01-01

    This article aims to examine determinants of social integration in the community among college students. Two-wave panel data from an undergraduate student sample (N = 310) was used to explore the effects of multiple sets of variables (personal, interpersonal, and situational) on social integration in the community. Structural equation analysis…

  7. 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.

  8. 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.

  9. NASA airframe structural integrity program

    NASA Technical Reports Server (NTRS)

    Harris, Charles E.

    1990-01-01

    NASA initiated a research program with the long-term objective of supporting the aerospace industry in addressing issues related to the aging of the commercial transport fleet. The program combines advanced fatigue crack growth prediction methodology with innovative nondestructive examination technology with the focus on multi-stage damage (MSD) at rivited connections. A fracture mechanics evaluation of the concept of pressure proof testing the fuselage to screen for MSD was completed. A successful laboratory demonstration of the ability of the thermal flux method to detect disbonds at rivited lap splice joints was conducted. All long-term program elements were initiated, and the plans for the methodology verification program are being coordinated with the airframe manufacturers.

  10. NASA airframe structural integrity program

    NASA Technical Reports Server (NTRS)

    Harris, Charles E.

    1991-01-01

    NASA has initiated a research program with the long-term objective of supporting the aerospace industry in addressing issues related to the aging commercial transport fleet. The interdisciplinary program combines advanced fatigue crack growth prediction methodology with innovative nondestructive examination technology with the focus on multi-site damage (MSD) at riveted connections. A fracture mechanics evaluation of the concept of pressure proof testing the fuselage to screen for MSD has been completed. Also, a successful laboratory demonstration of the ability of the thermal flux method to detect disbonds at riveted lap splice joints has been conducted. All long-term program elements have been initiated and the plans for the methodology verification program are being coordinated with the airframe manufacturers.

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. Prediction of Drug Combinations by Integrating Molecular and Pharmacological Data

    PubMed Central

    Zhao, Xing-Ming; Iskar, Murat; Zeller, Georg; Kuhn, Michael; van Noort, Vera; Bork, Peer

    2011-01-01

    Combinatorial therapy is a promising strategy for combating complex disorders due to improved efficacy and reduced side effects. However, screening new drug combinations exhaustively is impractical considering all possible combinations between drugs. Here, we present a novel computational approach to predict drug combinations by integrating molecular and pharmacological data. Specifically, drugs are represented by a set of their properties, such as their targets or indications. By integrating several of these features, we show that feature patterns enriched in approved drug combinations are not only predictive for new drug combinations but also provide insights into mechanisms underlying combinatorial therapy. Further analysis confirmed that among our top ranked predictions of effective combinations, 69% are supported by literature, while the others represent novel potential drug combinations. We believe that our proposed approach can help to limit the search space of drug combinations and provide a new way to effectively utilize existing drugs for new purposes. PMID:22219721

  18. 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.

  19. 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.

  20. 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.

  1. 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…

  2. Evolutionary Structure Prediction of Stoichiometric Compounds

    NASA Astrophysics Data System (ADS)

    Zhu, Qiang; Oganov, Artem

    2014-03-01

    In general, for a given ionic compound AmBn\\ at ambient pressure condition, its stoichiometry reflects the valence state ratio between per chemical specie (i.e., the charges for each anion and cation). However, compounds under high pressure exhibit significantly behavior, compared to those analogs at ambient condition. Here we developed a method to solve the crystal structure prediction problem based on the evolutionary algorithms, which can predict both the stable compounds and their crystal structures at arbitrary P,T-conditions, given just the set of chemical elements. By applying this method to a wide range of binary ionic systems (Na-Cl, Mg-O, Xe-O, Cs-F, etc), we discovered a lot of compounds with brand new stoichimetries which can become thermodynamically stable. Further electronic structure analysis on these novel compounds indicates that several factors can contribute to this extraordinary phenomenon: (1) polyatomic anions; (2) free electron localization; (3) emergence of new valence states; (4) metallization. In particular, part of the results have been confirmed by experiment, which warrants that this approach can play a crucial role in new materials design under extreme pressure conditions. This work is funded by DARPA (Grants No. W31P4Q1210008 and W31P4Q1310005), NSF (EAR-1114313 and DMR-1231586).

  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. Integration of genomic datasets to predict protein complexes in yeast.

    PubMed

    Jansen, Ronald; Lan, Ning; Qian, Jiang; Gerstein, Mark

    2002-01-01

    The ultimate goal of functional genomics is to define the function of all the genes in the genome of an organism. A large body of information of the biological roles of genes has been accumulated and aggregated in the past decades of research, both from traditional experiments detailing the role of individual genes and proteins, and from newer experimental strategies that aim to characterize gene function on a genomic scale. It is clear that the goal of functional genomics can only be achieved by integrating information and data sources from the variety of these different experiments. Integration of different data is thus an important challenge for bioinformatics. The integration of different data sources often helps to uncover non-obvious relationships between genes, but there are also two further benefits. First, it is likely that whenever information from multiple independent sources agrees, it should be more valid and reliable. Secondly, by looking at the union of multiple sources, one can cover larger parts of the genome. This is obvious for integrating results from multiple single gene or protein experiments, but also necessary for many of the results from genome-wide experiments since they are often confined to certain (although sizable) subsets of the genome. In this paper, we explore an example of such a data integration procedure. We focus on the prediction of membership in protein complexes for individual genes. For this, we recruit six different data sources that include expression profiles, interaction data, essentiality and localization information. Each of these data sources individually contains some weakly predictive information with respect to protein complexes, but we show how this prediction can be improved by combining all of them. Supplementary information is available at http:// bioinfo.mbb.yale.edu/integrate/interactions/. PMID:12836664

  5. A Cohesive and Integrated Platform for Immunogenicity Prediction.

    PubMed

    Dimitrov, Ivan; Atanasova, Mariyana; Patronov, Atanas; Flower, Darren R; Doytchinova, Irini

    2016-01-01

    In silico methods for immunogenicity prediction mine the enormous quantity of data arising from deciphered genomes and proteomes to identify immunogenic proteins. While high and productive immunogenicity is essential for vaccines, therapeutic proteins and monoclonal antibodies should be minimally immunogenic. Here, we present a cohesive platform for immunogenicity and MHC class I and/or II binding affinity prediction. The platform integrates three quasi-independent modular servers: VaxiJen, EpiJen, and EpiTOP. VaxiJen (http://www.ddg-pharmfac.net/vaxijen) predicts immunogenicity of proteins of different origin; EpiJen (http://www.ddg-pharmfac.net/epijen) predicts peptide binding to MHC class I proteins; and EpiTOP (http://www.ddg-pharmfac.net/epitop) predicts peptide binding to MHC class II proteins. The platform is freely accessible and user-friendly. The protocol for immunogenicity prediction is demonstrated by selecting immunogenic proteins from Mycobacterium tuberculosis and predicting how the peptide epitopes within them bind to MHC class I and class II proteins. PMID:27076336

  6. PREDICTION INTERVALS FOR INTEGRALS OF GAUSSIAN RANDOM FIELDS

    PubMed Central

    De Oliveira, Victor; Kone, Bazoumana

    2014-01-01

    Methodology is proposed for the construction of prediction intervals for integrals of Gaussian random fields over bounded regions (called block averages in the geostatistical literature) based on observations at a finite set of sampling locations. Two bootstrap calibration algorithms are proposed, termed indirect and direct, aimed at improving upon plug-in prediction intervals in terms of coverage probability. A simulation study is carried out that illustrates the effectiveness of both procedures, and these procedures are applied to estimate block averages of chromium traces in a potentially contaminated region in Switzerland. PMID:25431507

  7. Service life prediction of reinforced concrete structures

    SciTech Connect

    Liang, M.T.; Wang, K.L.; Liang, C.H.

    1999-09-01

    This paper is focused on the estimation of durability and service life of reinforced concrete structures. Assuming that the chloride ion in concrete can be absorbed on tricalcium aluminate, calcium silicate hydrate, and by other constituents of hardened cement paste, hydrated or not, the exact analytical solution of the governing partial differential equation together with its boundary and initial conditions can be obtained through nondimensional parameters and Laplace's transform. When the results of an exact analytical solution using suitable parameters were compared with the results of previous experimental work, the differences were found to be very small. This suggests that the absorption model is of considerable value. The exact analytical solution with the saturation parameter and time and diffusion coefficients under different effective electrical potential could be used to predict both the experimental results and the service life of reinforced concrete structures.

  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

    2010-08-01

    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. Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields.

    PubMed

    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. PMID:26752681

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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,…

  15. Structure prediction of magnetosome-associated proteins.

    PubMed

    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.

  16. Tunable resonant structures for photonic integrated circuits

    NASA Astrophysics Data System (ADS)

    Ptasinski, Joanna Nina

    Photonics is an evolving field allowing for optical devices to be made cost effectively using standard semiconductor fabrication techniques, which in turn enables integration with microelectronic chips. Chip scale photonics will play an increasing role in the future of communications as the demand for bandwidth and reduced power consumption per bit continues to grow. Tunable optical circuit components are one of the essential technologies in the development of photonic analogues for classical electronic devices, where tunable photonic resonant structures allow for altering of their electromagnetic spectrum and find applications in optical switching, filtering, buffering, lasers and biosensors. The scope of this work is focused on tunable resonant structures for photonic integrated circuits. Specifically, this work demonstrates active tuning of silicon photonic resonant structures using the properties of dye doped nematic liquid crystals, temperature stabilization of silicon photonics using the passive properties of liquid crystals, and the effects of low density plasma enhanced chemical vapor deposition (PECVD) claddings on ring resonator device performance.

  17. Structure Prediction for Multicomponent Materials Using Biminima

    NASA Astrophysics Data System (ADS)

    Schebarchov, D.; Wales, D. J.

    2014-10-01

    The potential energy surface of a heteroparticle system will contain points that are local minima in both coordinate space and permutation space for the different species. We introduce the term biminima to describe these special points, and we formulate a deterministic scheme for finding them. Our search algorithm generates a converging sequence of particle-identity swaps, each accompanied by a number of local geometry relaxations. For selected binary atomic clusters of size N=NA+NB≤98, convergence to a biminimum on average takes 3NANB relaxations, and the number of biminima grows with the preference for mixing. The new framework unifies continuous and combinatorial optimization, providing a powerful tool for structure prediction and rational design of multicomponent materials.

  18. Topological Predictions for Integral Membrane Channel and Carrier Proteins

    PubMed Central

    Abhinay, Reddy; Jaehoon, Cho; Sam, Ling; Vamsee, Reddy; Maksim, Shlykov; Milton, Saier

    2014-01-01

    We evaluated topological predictions for nine different programs, HMMTOP, TMHMM, SVMTOP, DAS, SOSUI, TOPCONS, PHOBIUS, MEMSAT-SVM (hereinafter referred to as MEMSAT), and SPOCTOPUS. These programs were first evaluated using four large topologically well-defined families of secondary transporters, and the three best programs were further evaluated using topologically more diverse families of channels and carriers. In the initial studies, the order of accuracy was: SPOCTOPUS>MEMSAT>HMMTOP>TOPCONS>PHOBIUS>TMHMM>SVMTOP>DAS>S OSUI. Some families, such as the Sugar Porter family (2.A.1.1) of the Major Facilitator Superfamily (MFS; TC# 2.A.1) and the Amino acid/Polyamine/Organocation (APC) Family (TC# 2.A.3), were correctly predicted with high accuracy while others, such as the Mitochondrial Carrier (MC) (TC# 2.A.29) and the K+ transporter (Trk) families (TC# 2.A.38), were predicted with much lower accuracy. For small, topologically homogeneous families, SPOCTOPUS and MEMSAT were generally most reliable, while with large, more diverse superfamilies, HMMTOP often proved to have the greatest prediction accuracy. We next developed a novel program, TM-STATS, that tabulates HMMTOP, SPOCTOPUS or MEMSAT-based topological predictions for any subdivision (class, subclass, superfamily, family, subfamily, or any combination of these) of the Transporter Classification Database (TCDB; www.tcdb.org) and examined the following subclasses: α-type channel proteins (TC subclasses 1.A and 1.E), secreted poreforming toxins (TC subclass 1.C) and secondary carriers (subclass 2.A). Histograms 3 were generated for each of these subclasses, and the results were analyzed according to subclass, family and protein. The results provide an update of topological predictions for integral membrane transport proteins as well as guides for the development of more reliable topological prediction programs, taking family-specific characteristics into account. PMID:24992992

  19. 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.

  20. 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.

  1. Functional structure of biological communities predicts ecosystem multifunctionality.

    PubMed

    Mouillot, David; Villéger, Sébastien; Scherer-Lorenzen, Michael; Mason, Norman W H

    2011-01-01

    The accelerating rate of change in biodiversity patterns, mediated by ever increasing human pressures and global warming, demands a better understanding of the relationship between the structure of biological communities and ecosystem functioning (BEF). Recent investigations suggest that the functional structure of communities, i.e. the composition and diversity of functional traits, is the main driver of ecological processes. However, the predictive power of BEF research is still low, the integration of all components of functional community structure as predictors is still lacking, and the multifunctionality of ecosystems (i.e. rates of multiple processes) must be considered. Here, using a multiple-processes framework from grassland biodiversity experiments, we show that functional identity of species and functional divergence among species, rather than species diversity per se, together promote the level of ecosystem multifunctionality with a predictive power of 80%. Our results suggest that primary productivity and decomposition rates, two key ecosystem processes upon which the global carbon cycle depends, are primarily sustained by specialist species, i.e. those that hold specialized combinations of traits and perform particular functions. Contrary to studies focusing on single ecosystem functions and considering species richness as the sole measure of biodiversity, we found a linear and non-saturating effect of the functional structure of communities on ecosystem multifunctionality. Thus, sustaining multiple ecological processes would require focusing on trait dominance and on the degree of community specialization, even in species-rich assemblages.

  2. Integrated predictive modelling simulations of burning plasma experiment designs

    NASA Astrophysics Data System (ADS)

    Bateman, Glenn; Onjun, Thawatchai; Kritz, Arnold H.

    2003-11-01

    Models for the height of the pedestal at the edge of H-mode plasmas (Onjun T et al 2002 Phys. Plasmas 9 5018) are used together with the Multi-Mode core transport model (Bateman G et al 1998 Phys. Plasmas 5 1793) in the BALDUR integrated predictive modelling code to predict the performance of the ITER (Aymar A et al 2002 Plasma Phys. Control. Fusion 44 519), FIRE (Meade D M et al 2001 Fusion Technol. 39 336), and IGNITOR (Coppi B et al 2001 Nucl. Fusion 41 1253) fusion reactor designs. The simulation protocol used in this paper is tested by comparing predicted temperature and density profiles against experimental data from 33 H-mode discharges in the JET (Rebut P H et al 1985 Nucl. Fusion 25 1011) and DIII-D (Luxon J L et al 1985 Fusion Technol. 8 441) tokamaks. The sensitivities of the predictions are evaluated for the burning plasma experimental designs by using variations of the pedestal temperature model that are one standard deviation above and below the standard model. Simulations of the fusion reactor designs are carried out for scans in which the plasma density and auxiliary heating power are varied.

  3. 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.

  4. 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

  5. Neighborhood Integration and Connectivity Predict Cognitive Performance and Decline

    PubMed Central

    Watts, Amber; Ferdous, Farhana; Moore, Keith Diaz; 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. Prediction of Secondary Structures Conserved in Multiple RNA Sequences.

    PubMed

    Xu, Zhenjiang Zech; Mathews, David H

    2016-01-01

    RNA structure is conserved by evolution to a greater extent than sequence. Predicting the conserved structure for multiple homologous sequences can be much more accurate than predicting the structure for a single sequence. RNAstructure is a software package that includes the programs Dynalign, Multilign, TurboFold, and PARTS for predicting conserved RNA secondary structure. This chapter provides protocols for using these programs. PMID:27665591

  7. 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.

  8. Computer-aided prediction of RNA secondary structures.

    PubMed Central

    Auron, P E; Rindone, W P; Vary, C P; Celentano, J J; Vournakis, J N

    1982-01-01

    A brief survey of computer algorithms that have been developed to generate predictions of the secondary structures of RNA molecules is presented. Two particular methods are described in some detail. The first utilizes a thermodynamic energy minimization algorithm that takes into account the likelihood that short-range folding tends to be favored over long-range interactions. The second utilizes an interactive computer graphic modelling algorithm that enables the user to consider thermodynamic criteria as well as structural data obtained by nuclease susceptibility, chemical reactivity and phylogenetic studies. Examples of structures for prokaryotic 16S and 23S ribosomal RNAs, several eukaryotic 5S ribosomal RNAs and rabbit beta-globin messenger RNA are presented as case studies in order to describe the two techniques. Anm argument is made for integrating the two approaches presented in this paper, enabling the user to generate proposed structures using thermodynamic criteria, allowing interactive refinement of these structures through the application of experimentally derived data. PMID:6174937

  9. Integrated cortical structural marker for Alzheimer's disease.

    PubMed

    Ming, Jing; Harms, Michael P; Morris, John C; Beg, M Faisal; Wang, Lei

    2015-01-01

    In this article, we propose an approach to integrate cortical morphology measures for improving the discrimination of individuals with and without very mild Alzheimer's disease (AD). FreeSurfer was applied to scans collected from 83 participants with very mild AD and 124 cognitively normal individuals. We generated cortex thickness, white matter convexity (aka "sulcal depth"), and white matter surface metric distortion measures on a normalized surface atlas in this first study to integrate high resolution gray matter thickness and white matter surface geometric measures in identifying very mild AD. Principal component analysis was applied to each individual structural measure to generate eigenvectors. Discrimination power based on individual and combined measures are compared, based on stepwise logistic regression and 10-fold cross-validation. Global AD likelihood index and surface-based likelihood maps were also generated. Our results show complementary patterns on the cortical surface between thickness, which reflects gray matter atrophy, convexity, which reflects white matter sulcal depth changes and metric distortion, which reflects white matter surface area changes. The classifier integrating all 3 types of surface measures significantly improved classification performance compared with classification based on single measures. The principal component analysis-based approach provides a framework for achieving high discrimination power by integrating high-dimensional data, and this method could be very powerful in future studies for early diagnosis of diseases that are known to be associated with abnormal gyral and sulcal patterns. PMID:25444604

  10. iStable: off-the-shelf predictor integration for predicting protein stability changes

    PubMed Central

    2013-01-01

    Background Mutation of a single amino acid residue can cause changes in a protein, which could then lead to a loss of protein function. Predicting the protein stability changes can provide several possible candidates for the novel protein designing. Although many prediction tools are available, the conflicting prediction results from different tools could cause confusion to users. Results We proposed an integrated predictor, iStable, with grid computing architecture constructed by using sequence information and prediction results from different element predictors. In the learning model, several machine learning methods were evaluated and adopted the support vector machine as an integrator, while not just choosing the majority answer given by element predictors. Furthermore, the role of the sequence information played was analyzed in our model, and an 11-window size was determined. On the other hand, iStable is available with two different input types: structural and sequential. After training and cross-validation, iStable has better performance than all of the element predictors on several datasets. Under different classifications and conditions for validation, this study has also shown better overall performance in different types of secondary structures, relative solvent accessibility circumstances, protein memberships in different superfamilies, and experimental conditions. Conclusions The trained and validated version of iStable provides an accurate approach for prediction of protein stability changes. iStable is freely available online at: http://predictor.nchu.edu.tw/iStable. PMID:23369171

  11. Using the RNAstructure Software Package to Predict Conserved RNA Structures.

    PubMed

    Mathews, David H

    2014-01-01

    The structures of many non-coding RNA (ncRNA) are conserved by evolution to a greater extent than their sequences. By predicting the conserved structure of two or more homologous sequences, the accuracy of secondary structure prediction can be improved as compared to structure prediction for a single sequence. This unit provides protocols for the use of four programs in the RNAstructure suite for prediction of conserved structures, Multilign, TurboFold, Dynalign, and PARTS. These programs can be run via Web servers, on the command line, or with graphical interfaces.

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. Structure prediction and analysis of neuraminidase sequence variants.

    PubMed

    Thayer, Kelly M

    2016-07-01

    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 highly mutable influenza virus protein neuraminidase, which is the key target in the development of therapeutics. In light of recent pandemics, understanding how mutations confer drug resistance, which translates at the molecular level to understanding how different sequence variants differ, constitutes an area of great interest because of the ramifications in public health. This lab targets upper level undergraduate biochemistry students, and aims to introduce tools to be used to explore protein folding and protein visualization in the context of the neuraminidase case study. Students proceed to critically evaluate the folded models by comparison with crystallographic structures. When validity is established, they fold a neuraminidase sequence for which a structure is not available. Through structural alignment and visual inspection of the 150 loop, students gain molecular insight into two possible conformations of the protein, which are actively being studied. Folding the third chosen sequence mimics a true research environment in allowing students to generate a structure from a sequence for which a structure was not previously available, and to assess whether their particular variant has an open or closed loop. From this vantage, they are then challenged to speculate about the connection between loop conformation and drug susceptibility. © 2016 by The International Union of Biochemistry and Molecular Biology, 44(4):361-376, 2016. PMID:26900942

  17. Experiment-Assisted Secondary Structure Prediction with RNAstructure.

    PubMed

    Xu, Zhenjiang Zech; Mathews, David H

    2016-01-01

    Experimental probing data can be used to improve the accuracy of RNA secondary structure prediction. The software package RNAstructure can take advantage of enzymatic cleavage data, FMN cleavage data, traditional chemical modification reactivity data, and SHAPE reactivity data for secondary structure modeling. This chapter provides protocols for using experimental probing data with RNAstructure to restrain or constrain RNA secondary structure prediction. PMID:27665598

  18. 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. PMID:24250115

  19. 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.

  20. 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.

  1. Mathematical structure of relativistic Coulomb integrals

    NASA Astrophysics Data System (ADS)

    Suslov, Sergei K.

    2010-03-01

    We show that the diagonal matrix elements , where O={1,β,iαnβ} are the standard Dirac matrix operators and the angular brackets denote the quantum-mechanical average for the relativistic Coulomb problem, may be considered as difference analogs of the radial wave functions. Such structure provides an independent way of obtaining closed forms of these matrix elements by elementary methods of the theory of difference equations without explicit evaluation of the integrals. Three-term recurrence relations for each of these expectation values are derived as a by-product. Transformation formulas for the corresponding generalized hypergeometric series are discussed.

  2. 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

  3. An Improved Numerical Integration Method for Springback Predictions

    NASA Astrophysics Data System (ADS)

    Ibrahim, R.; Smith, L. M.; Golovashchenko, Sergey F.

    2011-08-01

    In this investigation, the focus is on the springback of steel sheets in V-die air bending. A full replication to a numerical integration algorithm presented rigorously in [1] to predict the springback in air bending was performed and confirmed successfully. Algorithm alteration and extensions were proposed here. The altered approach used in solving the moment equation numerically resulted in springback values much closer to the trend presented by the experimental data, Although investigation here extended to use a more realistic work-hardening model, the differences in the springback values obtained by both hardening models were almost negligible. The algorithm was extended to be applied on thin sheets down to 0.8 mm. Results show that this extension is possible as verified by FEA and other published experiments on TRIP steel sheets.

  4. 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.

  5. 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

  6. Dynamic kirigami structures for integrated solar tracking.

    PubMed

    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

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. Reactor pressure vessel structural integrity research

    SciTech Connect

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

    1994-12-31

    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 shallow 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 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.

  12. Pathogenesis and prediction of diabetes mellitus: lessons from integrative physiology.

    PubMed

    Bergman, Richard N

    2002-10-01

    The molecular revolution in biology is providing an exponentially increasing body of data regarding subcellular events in normal and pathological conditions. The task of integrating even a small part of this deluge of information is a formidable challenge. Many integrative regulatory principles are still unknown. The present article argues that important principles may be discovered by the repetitive experimental testing of simple isomorphic computer or mathematical models of biological regulation. The system regulating the blood glucose is used as an example. Implicit in a minimal model, postulated more than 20 years ago, were specific but untested assumptions. These assumptions, which were tested over the ensuing decades, have enriched our understanding of metabolic regulation and the causes of diabetes. Currently accepted concepts emerging from modeling include: (a) the importance of sluggish insulin transport across the capillary endothelium in stimulation of glucose uptake; (b) the single gateway concept, that insulin transport across endothelium of adipose tissue suppresses free fatty acids, which act in turn to reduce endogenous glucose production by the liver; (c) the importance of the single gateway mechanism in the metabolic syndrome, whereby increased fat in the abdominal compartment relates to insulin resistance and risk for type 2 diabetes; and (d) the hyperbolic relationship between insulin action and insulin secretion, which provides an accurate prediction of diabetes risk. It is hoped that the experience with the metabolic system will provide a metaphor for other regulatory systems less subjected to critical quantitative analysis. Such analysis may well lead to analogous conceptual understanding of other important integrated biological systems, and provide approaches for early intervention in the pathogenic process of other chronic and devastating diseases.

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

    NASA Technical Reports Server (NTRS)

    Liu, W. K.

    1983-01-01

    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 difficult 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.

  14. 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'. PMID:27242293

  15. 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

  16. 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'.

  17. Predicting meningococcal disease outbreaks in structured populations.

    PubMed

    Ranta, J; Mäkelä, P H; Arjas, E

    2004-03-30

    Rational decision making on whether some form of intervention would be necessary to control the spread of a meningococcal epidemic is based on predictions concerning its potential natural progression. Unfortunately, reliable predictions are difficult to make during the early stages of an outbreak. A stochastic discrete time epidemic model was applied to adaptively predict the development of outbreaks of meningococcal disease in 'closed' populations such as military garrisons or boarding schools, which are further divided into subgroups called 'units'. The performance of the adaptive method was assessed by using 3 simulated epidemics representing substantially different realizations in a 'garrison' of 20 units, with 68 men in each. Predictions of the weekly number of disease cases, of the number of carriers, and of the number of new infections were computed. Simulations suggest that predictions based only on the observed numbers of disease cases are generally inaccurate. These predictions can be improved if temporal observations on asymptomatic carriers in different units are utilized together with observed time series of the disease. A sample of 15 per cent from all units can be sufficient for a major improvement if the alternative is to obtain a full sample of only some units. Exploiting fully such information requires computer intensive Markov chain Monte Carlo methods. PMID:15027081

  18. 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.

  19. 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

    2015-01-01

    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

  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. Integrated transient thermal-structural finite element analysis

    NASA Technical Reports Server (NTRS)

    Thornton, E. A.; Dechaumphai, P.; Wieting, A. R.; Tamma, K. K.

    1981-01-01

    An integrated thermal structural finite element approach for efficient coupling of transient thermal and structural analysis is presented. Integrated thermal structural rod and one dimensional axisymmetric elements considering conduction and convection are developed and used in transient thermal structural applications. The improved accuracy of the integrated approach is illustrated by comparisons with exact transient heat conduction elasticity solutions and conventional finite element thermal finite element structural analyses.

  3. 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.

  4. 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.

  5. Structural coding versus free-energy predictive coding.

    PubMed

    van der Helm, Peter A

    2016-06-01

    Focusing on visual perceptual organization, this article contrasts the free-energy (FE) version of predictive coding (a recent Bayesian approach) to structural coding (a long-standing representational approach). Both use free-energy minimization as metaphor for processing in the brain, but their formal elaborations of this metaphor are fundamentally different. FE predictive coding formalizes it by minimization of prediction errors, whereas structural coding formalizes it by minimization of the descriptive complexity of predictions. Here, both sides are evaluated. A conclusion regarding competence is that FE predictive coding uses a powerful modeling technique, but that structural coding has more explanatory power. A conclusion regarding performance is that FE predictive coding-though more detailed in its account of neurophysiological data-provides a less compelling cognitive architecture than that of structural coding, which, for instance, supplies formal support for the computationally powerful role it attributes to neuronal synchronization.

  6. SAM-T08, HMM-based protein structure prediction

    PubMed Central

    Karplus, Kevin

    2009-01-01

    The SAM-T08 web server is a protein structure prediction server that provides several useful intermediate results in addition to the final predicted 3D structure: three multiple sequence alignments of putative homologs using different iterated search procedures, prediction of local structure features including various backbone and burial properties, calibrated E-values for the significance of template searches of PDB and residue–residue contact predictions. The server has been validated as part of the CASP8 assessment of structure prediction as having good performance across all classes of predictions. The SAM-T08 server is available at http://compbio.soe.ucsc.edu/SAM_T08/T08-query.html PMID:19483096

  7. 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…

  8. Prediction of binary hard-sphere crystal structures.

    PubMed

    Filion, Laura; Dijkstra, Marjolein

    2009-04-01

    We present a method based on a combination of a genetic algorithm and Monte Carlo simulations to predict close-packed crystal structures in hard-core systems. We employ this method to predict the binary crystal structures in a mixture of large and small hard spheres with various stoichiometries and diameter ratios between 0.4 and 0.84. In addition to known binary hard-sphere crystal structures similar to NaCl and AlB2, we predict additional crystal structures with the symmetry of CrB, gammaCuTi, alphaIrV, HgBr2, AuTe2, Ag2Se, and various structures for which an atomic analog was not found. In order to determine the crystal structures at infinite pressures, we calculate the maximum packing density as a function of size ratio for the crystal structures predicted by our GA using a simulated annealing approach. PMID:19518387

  9. 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.

  10. Defining and predicting structurally conserved regions in protein superfamilies

    PubMed Central

    Huang, Ivan K.; Grishin, Nick V.

    2013-01-01

    Motivation: The structures of homologous proteins are generally better conserved than their sequences. This phenomenon is demonstrated by the prevalence of structurally conserved regions (SCRs) even in highly divergent protein families. Defining SCRs requires the comparison of two or more homologous structures and is affected by their availability and divergence, and our ability to deduce structurally equivalent positions among them. In the absence of multiple homologous structures, it is necessary to predict SCRs of a protein using information from only a set of homologous sequences and (if available) a single structure. Accurate SCR predictions can benefit homology modelling and sequence alignment. Results: Using pairwise DaliLite alignments among a set of homologous structures, we devised a simple measure of structural conservation, termed structural conservation index (SCI). SCI was used to distinguish SCRs from non-SCRs. A database of SCRs was compiled from 386 SCOP superfamilies containing 6489 protein domains. Artificial neural networks were then trained to predict SCRs with various features deduced from a single structure and homologous sequences. Assessment of the predictions via a 5-fold cross-validation method revealed that predictions based on features derived from a single structure perform similarly to ones based on homologous sequences, while combining sequence and structural features was optimal in terms of accuracy (0.755) and Matthews correlation coefficient (0.476). These results suggest that even without information from multiple structures, it is still possible to effectively predict SCRs for a protein. Finally, inspection of the structures with the worst predictions pinpoints difficulties in SCR definitions. Availability: The SCR database and the prediction server can be found at http://prodata.swmed.edu/SCR. Contact: 91huangi@gmail.com or grishin@chop.swmed.edu Supplementary information: Supplementary data are available at Bioinformatics

  11. Inhomogeneous Lens Structures for Integrated Optics.

    NASA Astrophysics Data System (ADS)

    Finlayson, Neil

    Available from UMI in association with The British Library. Requires signed TDF. The thesis is concerned with the design, analysis, fabrication and evaluation of integrated optic lenses which are inhomogeneous either in physical shape or in refractive index profile. Connections are made between the study of these lenses and the exciting new field of optical computing. A special class of non-uniform lenses forms the main area of interest in the present study. Historically, the development of these lenses has followed two distinct lines. In one method the optical path is made to vary directly, whilst the other method involves controlling the physical path, and thus the optical path, through the principle of equivalence. The dual development has been continued in the field of integrated optics, where lenses based on direct control of the optical path are termed variable-index lenses and those based on physical path control are termed geodesic lenses. The perfect variable -index lens studied in this work was the well-known Luneburg lens. The design formulae for both types of lens are presented. A simpler lens, of spherical geometry, is also presented. Chapter three investigates the problems involved in modelling fabrication conditions in a thermal-evaporation -in-vacuum environment so that lens profiles can actually be constructed. Chapter four goes into methods of tracing rays through these lenses in some detail. The beam-propagation method (BPM) is used to study diffraction and associated effects in inhomogeneous lenses. Negative focal shifts are reported which are not predicted by geometrical optics or the usual approximate diffraction theories. The fabrication of lenses is considered. Planar waveguide measurements carried out on the various materials used in the study are presented. A major problem in the fabrication of geodesic lenses, that of obtaining a uniform waveguide layer over the complete lens area, is dealt with in some detail. Extensive tests on the

  12. 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.

  13. 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

  14. 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.

  15. 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. PMID:27560616

  16. 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.

  17. 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. PMID:27373145

  18. 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.

  19. Genome-wide Membrane Protein Structure Prediction

    PubMed Central

    Piccoli, Stefano; Suku, Eda; Garonzi, Marianna; Giorgetti, Alejandro

    2013-01-01

    Transmembrane proteins allow cells to extensively communicate with the external world in a very accurate and specific way. They form principal nodes in several signaling pathways and attract large interest in therapeutic intervention, as the majority pharmaceutical compounds target membrane proteins. Thus, according to the current genome annotation methods, a detailed structural/functional characterization at the protein level of each of the elements codified in the genome is also required. The extreme difficulty in obtaining high-resolution three-dimensional structures, calls for computational approaches. Here we review to which extent the efforts made in the last few years, combining the structural characterization of membrane proteins with protein bioinformatics techniques, could help describing membrane proteins at a genome-wide scale. In particular we analyze the use of comparative modeling techniques as a way of overcoming the lack of high-resolution three-dimensional structures in the human membrane proteome. PMID:24403851

  20. 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.

  1. 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.

  2. 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.

  3. Novel and efficient RNA secondary structure prediction using hierarchical folding.

    PubMed

    Jabbari, Hosna; Condon, Anne; Zhao, Shelly

    2008-03-01

    Algorithms for prediction of RNA secondary structure-the set of base pairs that form when an RNA molecule folds-are valuable to biologists who aim to understand RNA structure and function. Improving the accuracy and efficiency of prediction methods is an ongoing challenge, particularly for pseudoknotted secondary structures, in which base pairs overlap. This challenge is biologically important, since pseudoknotted structures play essential roles in functions of many RNA molecules, such as splicing and ribosomal frameshifting. State-of-the-art methods, which are based on free energy minimization, have high run-time complexity (typically Theta(n(5)) or worse), and can handle (minimize over) only limited types of pseudoknotted structures. We propose a new approach for prediction of pseudoknotted structures, motivated by the hypothesis that RNA structures fold hierarchically, with pseudoknot-free (non-overlapping) base pairs forming first, and pseudoknots forming later so as to minimize energy relative to the folded pseudoknot-free structure. Our HFold algorithm uses two-phase energy minimization to predict hierarchically formed secondary structures in O(n(3)) time, matching the complexity of the best algorithms for pseudoknot-free secondary structure prediction via energy minimization. Our algorithm can handle a wide range of biological structures, including kissing hairpins and nested kissing hairpins, which have previously required Theta(n(6)) time.

  4. 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

  5. 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.

  6. Structural prediction for scandium carbide monolayer sheet

    NASA Astrophysics Data System (ADS)

    Ma, Hong-Man; Wang, Jing; Zhao, Hui-Yan; Zhang, Dong-Bo; Liu, Ying

    2016-09-01

    A two-dimensional tetragonal scandium carbide monolayer sheet has been constructed and studied using density functional theory. The results show that the scandium carbide sheet is stable and exhibits a novel tetracoordinated quasiplanar structure, as favored by the hybridization between Sc-3d orbitals and C-2p orbitals. Calculations of the phonon dispersion as well as molecular dynamics simulations also demonstrate the structural stability of this scandium carbide monolayer sheet. Electronic properties show that the scandium carbide monolayer sheet is metallic and non-magnetic.

  7. Experimental Validation of an Integrated Controls-Structures Design Methodology

    NASA Technical Reports Server (NTRS)

    Maghami, Peiman G.; Gupta, Sandeep; Elliot, Kenny B.; Walz, Joseph E.

    1996-01-01

    The first experimental validation of an integrated controls-structures design methodology for a class of large order, flexible space structures is described. Integrated redesign of the controls-structures-interaction evolutionary model, a laboratory testbed at NASA Langley, was described earlier. The redesigned structure was fabricated, assembled in the laboratory, and experimentally tested against the original structure. Experimental results indicate that the structure redesigned using the integrated design methodology requires significantly less average control power than the nominal structure with control-optimized designs, while maintaining the required line-of-sight pointing performance. Thus, the superiority of the integrated design methodology over the conventional design approach is experimentally demonstrated. Furthermore, amenability of the integrated design structure to other control strategies is evaluated, both analytically and experimentally. Using Linear-Quadratic-Guassian optimal dissipative controllers, it is observed that the redesigned structure leads to significantly improved performance with alternate controllers as well.

  8. Mixed time integration methods for transient thermal analysis of structures, appendix 5

    NASA Technical Reports Server (NTRS)

    Liu, W. K.

    1982-01-01

    Mixed time integration methods for transient thermal analysis of structures are studied. An efficient solution procedure for predicting the thermal behavior of aerospace vehicle structures was developed. A 2D finite element computer program incorporating these methodologies is being implemented. The performance of these mixed time finite element algorithms can then be evaluated employing the proposed example problem.

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

    PubMed

    Yang, Jianyi; Zhang, Yang

    2015-01-01

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

  10. Automated RNA 3D Structure Prediction with RNAComposer.

    PubMed

    Biesiada, Marcin; Purzycka, Katarzyna J; Szachniuk, Marta; Blazewicz, Jacek; Adamiak, Ryszard W

    2016-01-01

    RNAs adopt specific structures to perform their activities and these are critical to virtually all RNA-mediated processes. Because of difficulties in experimentally assessing structures of large RNAs using NMR, X-ray crystallography, or cryo-microscopy, there is currently great demand for new high-resolution 3D structure prediction methods. Recently we reported on RNAComposer, a knowledge-based method for the fully automated RNA 3D structure prediction from a user-defined secondary structure. RNAComposer method is especially suited for structural biology users. Since our initial report in 2012, both servers, freely available at http://rnacomposer.ibch.poznan.pl and http://rnacomposer.cs.put.poznan.pl have been often visited. Therefore this chapter provides guidance for using RNAComposer and discusses points that should be considered when predicting 3D RNA structure. An application example presents current scope and limitations of RNAComposer. PMID:27665601

  11. 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.

  12. 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

  13. Bimetric structure formation: Non-Gaussian predictions

    SciTech Connect

    Magueijo, Joao; Noller, Johannes; Piazza, Federico

    2010-08-15

    The minimal bimetric theory employing a disformal transformation between matter and gravity metrics is known to produce exactly scale-invariant fluctuations. It has a purely equilateral non-Gaussian signal, with an amplitude smaller than that of Dirac Born Infeld inflation (with opposite sign) but larger than standard inflation. We consider nonminimal bimetric models, where the coupling B appearing in the disformal transformation g-circumflex{sub {mu}{nu}}=g{sub {mu}{nu}}-B{partial_derivative}{sub {mu}{phi}{partial_derivative}{nu}{phi}} can run with {phi}. For power-law B({phi}) these models predict tilted spectra. For each value of the spectral index, a distinctive distortion to the equilateral property can be found. The constraint between this distortion and the spectral index can be seen as a 'consistency relation' for nonminimal bimetric models.

  14. Bimetric structure formation: Non-Gaussian predictions

    NASA Astrophysics Data System (ADS)

    Magueijo, João; Noller, Johannes; Piazza, Federico

    2010-08-01

    The minimal bimetric theory employing a disformal transformation between matter and gravity metrics is known to produce exactly scale-invariant fluctuations. It has a purely equilateral non-Gaussian signal, with an amplitude smaller than that of Dirac Born Infeld inflation (with opposite sign) but larger than standard inflation. We consider nonminimal bimetric models, where the coupling B appearing in the disformal transformation g^μν=gμν-B∂μϕ∂νϕ can run with ϕ. For power-law B(ϕ) these models predict tilted spectra. For each value of the spectral index, a distinctive distortion to the equilateral property can be found. The constraint between this distortion and the spectral index can be seen as a “consistency relation” for nonminimal bimetric models.

  15. 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.

  16. 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.

  17. 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.

  18. A multilayer evaluation approach for protein structure prediction and model quality assessment.

    PubMed

    Zhang, Jingfen; Wang, Qingguo; Vantasin, Kittinun; Zhang, Jiong; He, Zhiquan; Kosztin, Ioan; Shang, Yi; Xu, Dong

    2011-01-01

    Protein tertiary structures are essential for studying functions of proteins at molecular level. An indispensable approach for protein structure solution is computational prediction. Most protein structure prediction methods generate candidate models first and select the best candidates by model quality assessment (QA). In many cases, good models can be produced, but the QA tools fail to select the best ones from the candidate model pool. Because of incomplete understanding of protein folding, each QA method only reflects partial facets of a structure model and thus has limited discerning power with no one consistently outperforming others. In this article, we developed a set of new QA methods, including two QA methods for evaluating target/template alignments, a molecular dynamics (MD)-based QA method, and three consensus QA methods with selected references to reveal new facets of protein structures complementary to the existing methods. Moreover, the underlying relationship among different QA methods were analyzed and then integrated into a multilayer evaluation approach to guide the model generation and model selection in prediction. All methods are integrated and implemented into an innovative and improved prediction system hereafter referred to as MUFOLD. In CASP8 and CASP9, MUFOLD has demonstrated the proof of the principles in terms of both QA discerning power and structure prediction accuracy. PMID:21997706

  19. A multilayer evaluation approach for protein structure prediction and model quality assessment.

    PubMed

    Zhang, Jingfen; Wang, Qingguo; Vantasin, Kittinun; Zhang, Jiong; He, Zhiquan; Kosztin, Ioan; Shang, Yi; Xu, Dong

    2011-01-01

    Protein tertiary structures are essential for studying functions of proteins at molecular level. An indispensable approach for protein structure solution is computational prediction. Most protein structure prediction methods generate candidate models first and select the best candidates by model quality assessment (QA). In many cases, good models can be produced, but the QA tools fail to select the best ones from the candidate model pool. Because of incomplete understanding of protein folding, each QA method only reflects partial facets of a structure model and thus has limited discerning power with no one consistently outperforming others. In this article, we developed a set of new QA methods, including two QA methods for evaluating target/template alignments, a molecular dynamics (MD)-based QA method, and three consensus QA methods with selected references to reveal new facets of protein structures complementary to the existing methods. Moreover, the underlying relationship among different QA methods were analyzed and then integrated into a multilayer evaluation approach to guide the model generation and model selection in prediction. All methods are integrated and implemented into an innovative and improved prediction system hereafter referred to as MUFOLD. In CASP8 and CASP9, MUFOLD has demonstrated the proof of the principles in terms of both QA discerning power and structure prediction accuracy.

  20. Computational methods in sequence and structure prediction

    NASA Astrophysics Data System (ADS)

    Lang, Caiyi

    This dissertation is organized into two parts. In the first part, we will discuss three computational methods for cis-regulatory element recognition in three different gene regulatory networks as the following: (a) Using a comprehensive "Phylogenetic Footprinting Comparison" method, we will investigate the promoter sequence structures of three enzymes (PAL, CHS and DFR) that catalyze sequential steps in the pathway from phenylalanine to anthocyanins in plants. Our result shows there exists a putative cis-regulatory element "AC(C/G)TAC(C)" in the upstream of these enzyme genes. We propose this cis-regulatory element to be responsible for the genetic regulation of these three enzymes and this element, might also be the binding site for MYB class transcription factor PAP1. (b) We will investigate the role of the Arabidopsis gene glutamate receptor 1.1 (AtGLR1.1) in C and N metabolism by utilizing the microarray data we obtained from AtGLR1.1 deficient lines (antiAtGLR1.1). We focus our investigation on the putatively co-regulated transcript profile of 876 genes we have collected in antiAtGLR1.1 lines. By (a) scanning the occurrence of several groups of known abscisic acid (ABA) related cisregulatory elements in the upstream regions of 876 Arabidopsis genes; and (b) exhaustive scanning of all possible 6-10 bps motif occurrence in the upstream regions of the same set of genes, we are able to make a quantative estimation on the enrichment level of each of the cis-regulatory element candidates. We finally conclude that one specific cis-regulatory element group, called "ABRE" elements, are statistically highly enriched within the 876-gene group as compared to their occurrence within the genome. (c) We will introduce a new general purpose algorithm, called "fuzzy REDUCE1", which we have developed recently for automated cis-regulatory element identification. In the second part, we will discuss our newly devised protein design framework. With this framework we have developed

  1. Structure of orbitofrontal cortex predicts social influence

    PubMed Central

    Campbell-Meiklejohn, Daniel K.; Kanai, Ryota; Bahrami, Bahador; Bach, Dominik R.; Dolan, Raymond J.; Roepstorff, Andreas; Frith, Chris D.

    2012-01-01

    Summary Some people conform more than others. Across different contexts, this tendency is a fairly stable trait [1]. This stability suggests that the tendency to conform might have an anatomical correlate [2]. Values that one associates with available options, from foods to political candidates, help to guide choices and behaviour. These values can often be updated by the expressed preferences of other people as much as by independent experience. In this correspondence, we report a linear relationship between grey matter volume (GM) in a region of lateral orbitofrontal cortex (lOFCGM) and the tendency to shift reported desire for objects toward values expressed by other people. This effect was found in precisely the same region in each brain hemisphere. lOFCGM also predicted the functional hemodynamic response in the middle frontal gyrus to discovering that someone else's values contrast with one's own. These findings indicate that the tendency to conform one's values to those expressed by other people has an anatomical correlate in the human brain. PMID:22361146

  2. 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

  3. JPred4: a protein secondary structure prediction server.

    PubMed

    Drozdetskiy, Alexey; Cole, Christian; Procter, James; Barton, Geoffrey J

    2015-07-01

    JPred4 (http://www.compbio.dundee.ac.uk/jpred4) is the latest version of the popular JPred protein secondary structure prediction server which provides predictions by the JNet algorithm, one of the most accurate methods for secondary structure prediction. In addition to protein secondary structure, JPred also makes predictions of solvent accessibility and coiled-coil regions. The JPred service runs up to 94 000 jobs per month and has carried out over 1.5 million predictions in total for users in 179 countries. The JPred4 web server has been re-implemented in the Bootstrap framework and JavaScript to improve its design, usability and accessibility from mobile devices. JPred4 features higher accuracy, with a blind three-state (α-helix, β-strand and coil) secondary structure prediction accuracy of 82.0% while solvent accessibility prediction accuracy has been raised to 90% for residues <5% accessible. Reporting of results is enhanced both on the website and through the optional email summaries and batch submission results. Predictions are now presented in SVG format with options to view full multiple sequence alignments with and without gaps and insertions. Finally, the help-pages have been updated and tool-tips added as well as step-by-step tutorials. PMID:25883141

  4. JPred4: a protein secondary structure prediction server

    PubMed Central

    Drozdetskiy, Alexey; Cole, Christian; Procter, James; Barton, Geoffrey J.

    2015-01-01

    JPred4 (http://www.compbio.dundee.ac.uk/jpred4) is the latest version of the popular JPred protein secondary structure prediction server which provides predictions by the JNet algorithm, one of the most accurate methods for secondary structure prediction. In addition to protein secondary structure, JPred also makes predictions of solvent accessibility and coiled-coil regions. The JPred service runs up to 94 000 jobs per month and has carried out over 1.5 million predictions in total for users in 179 countries. The JPred4 web server has been re-implemented in the Bootstrap framework and JavaScript to improve its design, usability and accessibility from mobile devices. JPred4 features higher accuracy, with a blind three-state (α-helix, β-strand and coil) secondary structure prediction accuracy of 82.0% while solvent accessibility prediction accuracy has been raised to 90% for residues <5% accessible. Reporting of results is enhanced both on the website and through the optional email summaries and batch submission results. Predictions are now presented in SVG format with options to view full multiple sequence alignments with and without gaps and insertions. Finally, the help-pages have been updated and tool-tips added as well as step-by-step tutorials. PMID:25883141

  5. Gogny HFB prediction of nuclear structure properties

    SciTech Connect

    Goriely, S.; Hilaire, S.; Girod, M.

    2011-10-28

    Large scale mean field calculations from proton to neutron drip lines have been performed using the Hartree-Fock-Bogoliubov method based on the Gogny nucleon-nucleon effective interaction. This extensive study has shown the ability of the method to reproduce bulk nuclear structure data available experimentally. This includes nuclear masses, radii, matter densities, deformations, moment of inertia as well as collective mode (low energy and giant resonances). In particular, the first mass table based on a Gogny-Hartree-Fock-Bogolyubov calculation including an explicit and coherent account of all the quadrupole correlation energies is presented. The rms deviation with respect to essentially all the available mass data is 798 keV. Nearly 8000 nuclei have been studied under the axial symmetry hypothesis and going beyond the mean-field approach.

  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. Predicting RNA secondary structures from sequence and probing data.

    PubMed

    Lorenz, Ronny; Wolfinger, Michael T; Tanzer, Andrea; Hofacker, Ivo L

    2016-07-01

    RNA secondary structures have proven essential for understanding the regulatory functions performed by RNA such as microRNAs, bacterial small RNAs, or riboswitches. This success is in part due to the availability of efficient computational methods for predicting RNA secondary structures. Recent advances focus on dealing with the inherent uncertainty of prediction by considering the ensemble of possible structures rather than the single most stable one. Moreover, the advent of high-throughput structural probing has spurred the development of computational methods that incorporate such experimental data as auxiliary information.

  8. 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

  9. Combining Evolutionary Information and an Iterative Sampling Strategy for Accurate Protein Structure Prediction.

    PubMed

    Braun, Tatjana; Koehler Leman, Julia; Lange, Oliver F

    2015-12-01

    Recent work has shown that the accuracy of ab initio structure prediction can be significantly improved by integrating evolutionary information in form of intra-protein residue-residue contacts. Following this seminal result, much effort is put into the improvement of contact predictions. However, there is also a substantial need to develop structure prediction protocols tailored to the type of restraints gained by contact predictions. Here, we present a structure prediction protocol that combines evolutionary information with the resolution-adapted structural recombination approach of Rosetta, called RASREC. Compared to the classic Rosetta ab initio protocol, RASREC achieves improved sampling, better convergence and higher robustness against incorrect distance restraints, making it the ideal sampling strategy for the stated problem. To demonstrate the accuracy of our protocol, we tested the approach on a diverse set of 28 globular proteins. Our method is able to converge for 26 out of the 28 targets and improves the average TM-score of the entire benchmark set from 0.55 to 0.72 when compared to the top ranked models obtained by the EVFold web server using identical contact predictions. Using a smaller benchmark, we furthermore show that the prediction accuracy of our method is only slightly reduced when the contact prediction accuracy is comparatively low. This observation is of special interest for protein sequences that only have a limited number of homologs.

  10. RNACluster: An integrated tool for RNA secondary structure comparison and clustering.

    PubMed

    Liu, Qi; Olman, V; Liu, Huiqing; Ye, Xiuzi; Qiu, Shilun; Xu, Ying

    2008-07-15

    RNA structure comparison is a fundamental problem in structural biology, structural chemistry, and bioinformatics. It can be used for analysis of RNA energy landscapes, conformational switches, and facilitating RNA structure prediction. The purpose of our integrated tool RNACluster is twofold: to provide a platform for computing and comparison of different distances between RNA secondary structures, and to perform cluster identification to derive useful information of RNA structure ensembles, using a minimum spanning tree (MST) based clustering algorithm. RNACluster employs a cluster identification approach based on a MST representation of the RNA ensemble data and currently supports six distance measures between RNA secondary structures. RNACluster provides a user-friendly graphical interface to allow a user to compare different structural distances, analyze the structure ensembles, and visualize predicted structural clusters. PMID:18271070

  11. RNACluster: An integrated tool for RNA secondary structure comparison and clustering.

    PubMed

    Liu, Qi; Olman, V; Liu, Huiqing; Ye, Xiuzi; Qiu, Shilun; Xu, Ying

    2008-07-15

    RNA structure comparison is a fundamental problem in structural biology, structural chemistry, and bioinformatics. It can be used for analysis of RNA energy landscapes, conformational switches, and facilitating RNA structure prediction. The purpose of our integrated tool RNACluster is twofold: to provide a platform for computing and comparison of different distances between RNA secondary structures, and to perform cluster identification to derive useful information of RNA structure ensembles, using a minimum spanning tree (MST) based clustering algorithm. RNACluster employs a cluster identification approach based on a MST representation of the RNA ensemble data and currently supports six distance measures between RNA secondary structures. RNACluster provides a user-friendly graphical interface to allow a user to compare different structural distances, analyze the structure ensembles, and visualize predicted structural clusters.

  12. 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

  13. 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.

  14. Structural integrity and fatigue crack propagation life assessment of welded and weld-repaired structures

    NASA Astrophysics Data System (ADS)

    Alam, Mohammad Shah

    2005-11-01

    Structural integrity is the science and technology of the margin between safety and disaster. Proper evaluation of the structural integrity and fatigue life of any structure (aircraft, ship, railways, bridges, gas and oil transmission pipelines, etc.) is important to ensure the public safety, environmental protection, and economical consideration. Catastrophic failure of any structure can be avoided if structural integrity is assessed and necessary precaution is taken appropriately. Structural integrity includes tasks in many areas, such as structural analysis, failure analysis, nondestructive testing, corrosion, fatigue and creep analysis, metallurgy and materials, fracture mechanics, fatigue life assessment, welding metallurgy, development of repairing technologies, structural monitoring and instrumentation etc. In this research fatigue life assessment of welded and weld-repaired joints is studied both in numerically and experimentally. A new approach for the simulation of fatigue crack growth in two elastic materials has been developed and specifically, the concept has been applied to butt-welded joint in a straight plate and in tubular joints. In the proposed method, the formation of new surface is represented by an interface element based on the interface potential energy. This method overcomes the limitation of crack growth at an artificial rate of one element length per cycle. In this method the crack propagates only when the applied load reaches the critical bonding strength. The predicted results compares well with experimental results. The Gas Metal Arc welding processes has been simulated to predict post-weld distortion, residual stresses and development of restraining forces in a butt-welded joint. The effect of welding defects and bi-axial interaction of a circular porosity and a solidification crack on fatigue crack propagation life of butt-welded joints has also been investigated. After a weld has been repaired, the specimen was tested in a universal

  15. SAbPred: a structure-based antibody prediction server

    PubMed Central

    Dunbar, James; Krawczyk, Konrad; Leem, Jinwoo; Marks, Claire; Nowak, Jaroslaw; Regep, Cristian; Georges, Guy; Kelm, Sebastian; Popovic, Bojana; Deane, Charlotte M.

    2016-01-01

    SAbPred is a server that makes predictions of the properties of antibodies focusing on their structures. Antibody informatics tools can help improve our understanding of immune responses to disease and aid in the design and engineering of therapeutic molecules. SAbPred is a single platform containing multiple applications which can: number and align sequences; automatically generate antibody variable fragment homology models; annotate such models with estimated accuracy alongside sequence and structural properties including potential developability issues; predict paratope residues; and predict epitope patches on protein antigens. The server is available at http://opig.stats.ox.ac.uk/webapps/sabpred. PMID:27131379

  16. GSAFold: a new application of GSA to protein structure prediction.

    PubMed

    Melo, Marcelo C R; Bernardi, Rafael C; Fernandes, Tácio V A; Pascutti, Pedro G

    2012-08-01

    The folding process defines three-dimensional protein structures from their amino acid chains. A protein's structure determines its activity and properties; thus knowing such conformation on an atomic level is essential for both basic and applied studies of protein function and dynamics. However, the acquisition of such structures by experimental methods is slow and expensive, and current computational methods mostly depend on previously known structures to determine new ones. Here we present a new software called GSAFold that applies the generalized simulated annealing (GSA) algorithm on ab initio protein structure prediction. The GSA is a stochastic search algorithm employed in energy minimization and used in global optimization problems, especially those that depend on long-range interactions, such as gravity models and conformation optimization of small molecules. This new implementation applies, for the first time in ab initio protein structure prediction, an analytical inverse for the Visitation function of GSA. It also employs the broadly used NAMD Molecular Dynamics package to carry out energy calculations, allowing the user to select different force fields and parameterizations. Moreover, the software also allows the execution of several simulations simultaneously. Applications that depend on protein structures include rational drug design and structure-based protein function prediction. Applying GSAFold in a test peptide, it was possible to predict the structure of mastoparan-X to a root mean square deviation of 3.00 Å. PMID:22622959

  17. 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.

  18. Integrated transient thermal-structural finite element analysis

    NASA Technical Reports Server (NTRS)

    Thornton, E. A.; Decahaumphai, P.; Tamma, K. K.; Wieting, A. R.

    1981-01-01

    An integrated thermal-structural finite element approach for efficient coupling of transient thermal and structural analysis is presented. New integrated thermal-structural rod and one dimensional axisymmetric elements considering conduction and convection are developed and used in transient thermal-structural applications. The improved accuracy of the integrated approach is illustrated by comparisons with exact transient heat conduction-elasticity solutions and conventional finite element thermal-finite element structural analyses. Results indicate that the approach offers significant potential for further development with other elements.

  19. 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.

  20. 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

    2015-12-01

    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

  1. Reliability of toxicological biomonitoring for predicting ecological integrity in freshwater systems

    SciTech Connect

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

    1995-12-31

    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 monitoring in predicting ecological integrity. Impact from one or more point-source discharges varied among the stream systems from slight to severe in effluent receiving areas and decreased incrementally with downstream distance. Studies were performed at monitoring stations selected for comparable conditions, including upstream reference and downstream recovery areas. On-site toxicological evaluations were performed using Ceriodaphnia dubia three brood tests and fathead minnow embryo larval tests. Test water was changed daily with fresh collections. Ecological conditions were analyzed using the Rapid Bioassessment Protocol 3, Brillouin and Shannon-Weaver indices, cluster analysis and traditional methods (e.g., species richness, diversity, functional groups, indicator species). 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 condition. 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% occurred in areas in which there were no consistent trends in toxicity. Neither biodiversity nor abundance of aquatic life could be predicted with certainty using ambient toxicity tests under circumstances of moderate to slight ecological impact.

  2. 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.

  3. 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

  4. 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.

  5. Text Prediction on Structured Data Entry in Healthcare

    PubMed Central

    Hua, L.; Wang, S.; Gong, Y.

    2014-01-01

    Summary Background Structured data entry pervades computerized patient safety event reporting systems and serves as a key component in collecting patient-related information in electronic health records. Clinicians would spend more time being with patients and arrive at a high probability of proper diagnosis and treatment, if data entry can be completed efficiently and effectively. Historically it has been proven text prediction holds potential for human performance regarding data entry in a variety of research areas. Objective This study aimed at examining a function of text prediction proposed for increasing efficiency and data quality in structured data entry. Methods We employed a two-group randomized design with fifty-two nurses in this usability study. Each participant was assigned the task of reporting patient falls by answering multiple choice questions either with or without the text prediction function. t-test statistics and linear regression model were applied to analyzing the results of the two groups. Results While both groups of participants exhibited a good capacity of accomplishing the assigned task, the results were an overall 13.0% time reduction and 3.9% increase of response accuracy for the group utilizing the prediction function. Conclusion As a primary attempt investigating the effectiveness of text prediction in healthcare, study findings validated the necessity of text prediction to structured date entry, and laid the ground for further research improving the effectiveness of text prediction in clinical settings. PMID:24734137

  6. Coarse-Grained Prediction of RNA Loop Structures

    PubMed Central

    Liu, Liang; Chen, Shi-Jie

    2012-01-01

    One of the key issues in the theoretical prediction of RNA folding is the prediction of loop structure from the sequence. RNA loop free energies are dependent on the loop sequence content. However, most current models account only for the loop length-dependence. The previously developed “Vfold” model (a coarse-grained RNA folding model) provides an effective method to generate the complete ensemble of coarse-grained RNA loop and junction conformations. However, due to the lack of sequence-dependent scoring parameters, the method is unable to identify the native and near-native structures from the sequence. In this study, using a previously developed iterative method for extracting the knowledge-based potential parameters from the known structures, we derive a set of dinucleotide-based statistical potentials for RNA loops and junctions. A unique advantage of the approach is its ability to go beyond the the (known) native structures by accounting for the full free energy landscape, including all the nonnative folds. The benchmark tests indicate that for given loop/junction sequences, the statistical potentials enable successful predictions for the coarse-grained 3D structures from the complete conformational ensemble generated by the Vfold model. The predicted coarse-grained structures can provide useful initial folds for further detailed structural refinement. PMID:23144887

  7. 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.

  8. 3D protein structure prediction using Imperialist Competitive algorithm and half sphere exposure prediction.

    PubMed

    Khaji, Erfan; Karami, Masoumeh; Garkani-Nejad, Zahra

    2016-02-21

    Predicting the native structure of proteins based on half-sphere exposure and contact numbers has been studied deeply within recent years. Online predictors of these vectors and secondary structures of amino acids sequences have made it possible to design a function for the folding process. By choosing variant structures and directs for each secondary structure, a random conformation can be generated, and a potential function can then be assigned. Minimizing the potential function utilizing meta-heuristic algorithms is the final step of finding the native structure of a given amino acid sequence. In this work, Imperialist Competitive algorithm was used in order to accelerate the process of minimization. Moreover, we applied an adaptive procedure to apply revolutionary changes. Finally, we considered a more accurate tool for prediction of secondary structure. The results of the computational experiments on standard benchmark show the superiority of the new algorithm over the previous methods with similar potential function. PMID:26718864

  9. 3D protein structure prediction using Imperialist Competitive algorithm and half sphere exposure prediction.

    PubMed

    Khaji, Erfan; Karami, Masoumeh; Garkani-Nejad, Zahra

    2016-02-21

    Predicting the native structure of proteins based on half-sphere exposure and contact numbers has been studied deeply within recent years. Online predictors of these vectors and secondary structures of amino acids sequences have made it possible to design a function for the folding process. By choosing variant structures and directs for each secondary structure, a random conformation can be generated, and a potential function can then be assigned. Minimizing the potential function utilizing meta-heuristic algorithms is the final step of finding the native structure of a given amino acid sequence. In this work, Imperialist Competitive algorithm was used in order to accelerate the process of minimization. Moreover, we applied an adaptive procedure to apply revolutionary changes. Finally, we considered a more accurate tool for prediction of secondary structure. The results of the computational experiments on standard benchmark show the superiority of the new algorithm over the previous methods with similar potential function.

  10. Geophysical Model on Fracture Prediction of Reef Complexes integrated with Geological Study

    NASA Astrophysics Data System (ADS)

    Wang, C.; Lu, Y.; Liu, Z.; Xing, F.; Chen, L.

    2013-12-01

    Fracture prediction is important for gas production of fractured carbonate reservoir. Yuanba Gas Field, located in the low-amplitude structural zone of central Sichuan Basin, is the second largest carbonate reservoir in Sichuan Basin, SW China. Vast majority of natural gas is embedded in Changsingian (Late Permian) reef complexes of this area. Influenced primarily by eluviation and secondary diagenesis (recrystallization and dissolution) instead of multistage tectonic activities, the distribution and characteristics of Dissolution Pores and Fractures (DPF) are complex, irregular geometrical shape and stochastic spatial distribution. This results in the difficulty of fracture prediction through routine geological methods such as coherence technique and curvature analysis. In this case, we provide a novel way integrating of sedimentary facies and innovative geophysical techniques including Anisotropy Coherence Technique (ACT) and Fracture Intensity Inversion (FII). This is an effective methodology for prediction of characteristics of DPF in different facies, without intense tectonic movements. Based on the heterogenity of DPF, seismic waveform characteristics cause various coherence value within different scanning direction. But the anisotropy coherence values of non-DPF zone are numerical consistency. Analyzing the abnormal coherence values of one point, ACT can determine whether DPF develop. Combing with fracture intensity curves and genetic inversion, FII can quantify the fracture strength and establish the relationship between facies and fracture intensity. The results indicate that the characteristics of DPF varying with facies are the result of different diagenesis and petrophysical property. (1) DPF develop intensely in reef, with geophysical characteristic of high coherence value in ACT and high fracture intensity in FII. It is the result of dolomitization which destroys primary skeletal structure and forms intercrystal pores and intergranular pores. (2

  11. 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

  12. Predicting the protein-protein interactions using primary structures with predicted protein surface

    PubMed Central

    2010-01-01

    Background Many biological functions involve various protein-protein interactions (PPIs). Elucidating such interactions is crucial for understanding general principles of cellular systems. Previous studies have shown the potential of predicting PPIs based on only sequence information. Compared to approaches that require other auxiliary information, these sequence-based approaches can be applied to a broader range of applications. Results This study presents a novel sequence-based method based on the assumption that protein-protein interactions are more related to amino acids at the surface than those at the core. The present method considers surface information and maintains the advantage of relying on only sequence data by including an accessible surface area (ASA) predictor recently proposed by the authors. This study also reports the experiments conducted to evaluate a) the performance of PPI prediction achieved by including the predicted surface and b) the quality of the predicted surface in comparison with the surface obtained from structures. The experimental results show that surface information helps to predict interacting protein pairs. Furthermore, the prediction performance achieved by using the surface estimated with the ASA predictor is close to that using the surface obtained from protein structures. Conclusion This work presents a sequence-based method that takes into account surface information for predicting PPIs. The proposed procedure of surface identification improves the prediction performance with an F-measure of 5.1%. The extracted surfaces are also valuable in other biomedical applications that require similar information. PMID:20122202

  13. 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.

  14. 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.

  15. Structural basis for retroviral integration into nucleosomes

    PubMed Central

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

    2015-01-01

    Retroviral integration is catalyzed by a tetramer of integrase (IN) assembled on viral DNA ends in a stable complex, known as the intasome1,2. 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 (EM) 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 (SHL) ±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. PMID:26061770

  16. 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.

  17. 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.

  18. Systems pharmacology to predict drug toxicity: integration across levels of biological organization.

    PubMed

    Bai, Jane P F; Abernethy, Darrell R

    2013-01-01

    To achieve sensitive and specific mechanism-based prediction of drug toxicity, the tools of systems pharmacology will be integrated using structured ontological approaches, analytics, mathematics, and statistics. Success of this effort is based on the assumption that a systems network that consists of drug-induced perturbations of physiological functions can be characterized. This network spans the hierarchy of biological organization, from gene to mRNA to protein to intracellular organelle to cell to organ to organism. It is populated with data from each of these levels of biological organization. These data, from disparate sources, include the published literature, drug development archives of all approved drugs and drug candidates that did not complete development, and various toxicity databases and adverse event reporting systems. The network contains interrelated genomics, transcriptomics, and metabolomics data, as well as organ and physiological functional data that are derived from the universe of information that describes and analyzes drug toxicity. Here we describe advances in bioinformatics, computer sciences, next-generation sequencing, and systems biology that create the opportunity for integrated systems pharmacology-based prediction of drug safety.

  19. 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.

  20. 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/.

  1. 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

  2. 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.

  3. 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.

  4. 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),...

  5. PredictProtein—an open resource for online prediction of protein structural and functional features

    PubMed Central

    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

    2014-01-01

    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. PMID:24799431

  6. Using theoretical descriptors in structure activity relationships: Validating toxicity predictions

    SciTech Connect

    Famini, G.R.; Wilson, L.Y.; Chester, N.A.; Sterling, P.A.

    1995-12-01

    Quantitative Structure Activity Relationships (QSAR) and Linear Free Energy Relationships (LFER) are very useful for correlating toxicological data, and in characterizating trends in terms of structural and electronic effects. Several years ago, we developed a series of equations correlating a number of toxicity tests with theoretically determined descriptors. One of these tests was the Microtox test, using the degradation in light from Photobacteriurn phosphoreum. Recently, several new compounds have been tested in our laboratory using the Microtox test, and compared against the predicted values. The agreement between experimental and theoretical results will be discussed, as will reasons for {open_quotes}good{close_quotes} or {open_quotes}poor{close_quotes} predictions.

  7. Integrated proteomics pipeline yields novel biomarkers for predicting preeclampsia.

    PubMed

    Myers, Jenny E; Tuytten, Robin; Thomas, Grégoire; Laroy, Wouter; Kas, Koen; Vanpoucke, Griet; Roberts, Claire T; Kenny, Louise C; Simpson, Nigel A B; Baker, Philip N; North, Robyn A

    2013-06-01

    Preeclampsia, a hypertensive pregnancy complication, is largely unpredictable in healthy nulliparous pregnant women. Accurate preeclampsia prediction in this population would transform antenatal care. To identify novel protein markers relevant to the prediction of preeclampsia, a 3-step mass spectrometric work flow was applied. On selection of candidate biomarkers, mostly from an unbiased discovery experiment (19 women), targeted quantitation was used to verify and validate candidate biomarkers in 2 independent cohorts from the SCOPE (SCreening fOr Pregnancy Endpoints) study. Candidate proteins were measured in plasma specimens collected at 19 to 21 weeks' gestation from 100 women who later developed preeclampsia and 200 women without preeclampsia recruited from Australia and New Zealand. Protein levels (n=25), age, and blood pressure were then analyzed using logistic regression to identify multimarker models (maximum 6 markers) that met predefined criteria: sensitivity ≥50% at 20% positive predictive value. These 44 algorithms were then tested in an independent European cohort (n=300) yielding 8 validated models. These 8 models detected 50% to 56% of preeclampsia cases in the training and validation sets; the detection rate for preterm preeclampsia cases was 80%. Validated models combine insulin-like growth factor acid labile subunit and soluble endoglin, supplemented with maximally 4 markers of placental growth factor, serine peptidase inhibitor Kunitz type 1, melanoma cell adhesion molecule, selenoprotein P, and blood pressure. Predictive performances were maintained when exchanging mass spectrometry measurements with ELISA measurements for insulin-like growth factor acid labile subunit. In conclusion, we demonstrated that biomarker combinations centered on insulin-like growth factor acid labile subunit have the potential to predict preeclampsia in healthy nulliparous women.

  8. 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.

  9. 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. PMID:11063780

  10. 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.

  11. Accurate Prediction of Transposon-Derived piRNAs by Integrating Various Sequential and Physicochemical Features

    PubMed Central

    Luo, Longqiang; Li, Dingfang; Zhang, Wen; Tu, Shikui; Zhu, Xiaopeng; Tian, Gang

    2016-01-01

    Background Piwi-interacting RNA (piRNA) is the largest class of small non-coding RNA molecules. The transposon-derived piRNA prediction can enrich the research contents of small ncRNAs as well as help to further understand generation mechanism of gamete. Methods In this paper, we attempt to differentiate transposon-derived piRNAs from non-piRNAs based on their sequential and physicochemical features by using machine learning methods. We explore six sequence-derived features, i.e. spectrum profile, mismatch profile, subsequence profile, position-specific scoring matrix, pseudo dinucleotide composition and local structure-sequence triplet elements, and systematically evaluate their performances for transposon-derived piRNA prediction. Finally, we consider two approaches: direct combination and ensemble learning to integrate useful features and achieve high-accuracy prediction models. Results We construct three datasets, covering three species: Human, Mouse and Drosophila, and evaluate the performances of prediction models by 10-fold cross validation. In the computational experiments, direct combination models achieve AUC of 0.917, 0.922 and 0.992 on Human, Mouse and Drosophila, respectively; ensemble learning models achieve AUC of 0.922, 0.926 and 0.994 on the three datasets. Conclusions Compared with other state-of-the-art methods, our methods can lead to better performances. In conclusion, the proposed methods are promising for the transposon-derived piRNA prediction. The source codes and datasets are available in S1 File. PMID:27074043

  12. 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.

  13. 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.

  14. 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.

  15. 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. PMID:23127300

  16. 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

  17. Integration of radar and Landsat imagery for structural analysis

    SciTech Connect

    Dodge, R.L.

    1986-05-01

    Radar imagery contains information on texture, structural orientation, and topography that augments data interpretable from Landsat Multispectral Scanner and Thematic Mapper data. Integrating data available from these two remote-sensing systems results in a more complete interpretation of surface features related to subsurface structures. Examples of improved interpretation emphasize the importance of radar's variable illumination azimuth for recognizing structural trends in addition to those seen on Landsat data. Also, textural detail and increased resolution from radar imagery improve the interpretability of fracture patterns and fracture density, and high resolution and variable illumination angle enhance topographic detail and recognition of structurally controlled topography. Tonal variations in the visible-near infrared, seen on Landsat data, can be related to fracture density, structurally controlled soil moisture conditions, and structurally controlled topography. Integrating the surface expression of structural features on the two types of data results in better maps of the surface expression of subsurface structures. Examples presented illustrate applications of such integrated analysis. Data from Landsat and radar sensors can be integrated visually, during the interpretation process, or digitally. Both approaches have advantages; visual integration is more practical for regional analysis, and digital integration can be applied in high-graded areas.

  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. 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

  20. 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.

  1. 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.

  2. 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.

  3. (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/. PMID:25943546

  4. (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/.

  5. 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.

  6. 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.

  7. 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.

  8. Integrated structure/control law design by multilevel optimization

    NASA Technical Reports Server (NTRS)

    Gilbert, Michael G.; Schmidt, David K.

    1989-01-01

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

  9. 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.

  10. 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.

  11. 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.

  12. Structural prediction of peptides bound to MHC class I.

    PubMed

    Fagerberg, Theres; Cerottini, Jean-Charles; Michielin, Olivier

    2006-02-17

    An ab initio structure prediction approach adapted to the peptide-major histocompatibility complex (MHC) class I system is presented. Based on structure comparisons of a large set of peptide-MHC class I complexes, a molecular dynamics protocol is proposed using simulated annealing (SA) cycles to sample the conformational space of the peptide in its fixed MHC environment. A set of 14 peptide-human leukocyte antigen (HLA) A0201 and 27 peptide-non-HLA A0201 complexes for which X-ray structures are available is used to test the accuracy of the prediction method. For each complex, 1000 peptide conformers are obtained from the SA sampling. A graph theory clustering algorithm based on heavy atom root-mean-square deviation (RMSD) values is applied to the sampled conformers. The clusters are ranked using cluster size, mean effective or conformational free energies, with solvation free energies computed using Generalized Born MV 2 (GB-MV2) and Poisson-Boltzmann (PB) continuum models. The final conformation is chosen as the center of the best-ranked cluster. With conformational free energies, the overall prediction success is 83% using a 1.00 Angstroms crystal RMSD criterion for main-chain atoms, and 76% using a 1.50 Angstroms RMSD criterion for heavy atoms. The prediction success is even higher for the set of 14 peptide-HLA A0201 complexes: 100% of the peptides have main-chain RMSD values < or =1.00 Angstroms and 93% of the peptides have heavy atom RMSD values < or =1.50 Angstroms. This structure prediction method can be applied to complexes of natural or modified antigenic peptides in their MHC environment with the aim to perform rational structure-based optimizations of tumor vaccines.

  13. Building integrated ontological knowledge structures with efficient approximation algorithms.

    PubMed

    Xiang, Yang; Janga, Sarath Chandra

    2015-01-01

    The integration of ontologies builds knowledge structures which brings new understanding on existing terminologies and their associations. With the steady increase in the number of ontologies, automatic integration of ontologies is preferable over manual solutions in many applications. However, available works on ontology integration are largely heuristic without guarantees on the quality of the integration results. In this work, we focus on the integration of ontologies with hierarchical structures. We identified optimal structures in this problem and proposed optimal and efficient approximation algorithms for integrating a pair of ontologies. Furthermore, we extend the basic problem to address the integration of a large number of ontologies, and correspondingly we proposed an efficient approximation algorithm for integrating multiple ontologies. The empirical study on both real ontologies and synthetic data demonstrates the effectiveness of our proposed approaches. In addition, the results of integration between gene ontology and National Drug File Reference Terminology suggest that our method provides a novel way to perform association studies between biomedical terms. PMID:26550571

  14. Building integrated ontological knowledge structures with efficient approximation algorithms.

    PubMed

    Xiang, Yang; Janga, Sarath Chandra

    2015-01-01

    The integration of ontologies builds knowledge structures which brings new understanding on existing terminologies and their associations. With the steady increase in the number of ontologies, automatic integration of ontologies is preferable over manual solutions in many applications. However, available works on ontology integration are largely heuristic without guarantees on the quality of the integration results. In this work, we focus on the integration of ontologies with hierarchical structures. We identified optimal structures in this problem and proposed optimal and efficient approximation algorithms for integrating a pair of ontologies. Furthermore, we extend the basic problem to address the integration of a large number of ontologies, and correspondingly we proposed an efficient approximation algorithm for integrating multiple ontologies. The empirical study on both real ontologies and synthetic data demonstrates the effectiveness of our proposed approaches. In addition, the results of integration between gene ontology and National Drug File Reference Terminology suggest that our method provides a novel way to perform association studies between biomedical terms.

  15. 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.

  16. 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.

  17. Behavior predicts genes structure in a wild primate group.

    PubMed Central

    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

    1996-01-01

    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. PMID:8650172

  18. A dynamic programming algorithm for RNA structure prediction including pseudoknots.

    PubMed

    Rivas, E; Eddy, S R

    1999-02-01

    We describe a dynamic programming algorithm for predicting optimal RNA secondary structure, including pseudoknots. The algorithm has a worst case complexity of O(N6) in time and O(N4) in storage. The description of the algorithm is complex, which led us to adopt a useful graphical representation (Feynman diagrams) borrowed from quantum field theory. We present an implementation of the algorithm that generates the optimal minimum energy structure for a single RNA sequence, using standard RNA folding thermodynamic parameters augmented by a few parameters describing the thermodynamic stability of pseudoknots. We demonstrate the properties of the algorithm by using it to predict structures for several small pseudoknotted and non-pseudoknotted RNAs. Although the time and memory demands of the algorithm are steep, we believe this is the first algorithm to be able to fold optimal (minimum energy) pseudoknotted RNAs with the accepted RNA thermodynamic model.

  19. Structural Integrity and Microstructure of NA^+ Conducting Ceramics

    NASA Astrophysics Data System (ADS)

    Lipinska, Kristina; Kalita, Patricia; Hemmers, Oliver; Sinogeikin, Stanislav; Shebanova, Olga; Yang, Wenge; Mariotto, Gino

    2010-03-01

    Oxides with the general formula of Na1+x Zr2 Six P3-x O12 , known as Nasicon, are fast Na+ ion-conducting materials with important electrochemical applications and many functional properties, often attributed to their unique structural features. Comparative, in situ studies of the limits of structural integrity were performed for selected Nasicon materials, using synchrotron x-ray diffraction and diamond anvil cell technology. We show how different processing conditions produce crystalline structures with specific morphology. We discuss the bulk modulus, the compressibility and the influence of the volume fraction of primary and secondary crystalline phases on the overall Nasicon structural integrity.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. Predicting inclusion behaviour and framework structures in organic crystals.

    PubMed

    Cruz-Cabeza, Aurora J; Day, Graeme M; Jones, William

    2009-12-01

    We have used well-established computational methods to generate and explore the crystal structure landscapes of four organic molecules of well-known inclusion behaviour. Using these methods, we are able to generate both close-packed crystal structures and high-energy open frameworks containing voids of molecular dimensions. Some of these high-energy open frameworks correspond to real structures observed experimentally when the appropriate guest molecules are present during crystallisation. We propose a combination of crystal structure prediction methodologies with structure rankings based on relative lattice energy and solvent-accessible volume as a way of selecting likely inclusion frameworks completely ab initio. This methodology can be used as part of a rational strategy in the design of inclusion compounds, and also for the anticipation of inclusion behaviour in organic molecules. PMID:19876969

  5. 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

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

    NASA Astrophysics Data System (ADS)

    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.

  7. '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

  8. 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.

  9. Benchmark data sets for structure-based computational target prediction.

    PubMed

    Schomburg, Karen T; Rarey, Matthias

    2014-08-25

    Structure-based computational target prediction methods identify potential targets for a bioactive compound. Methods based on protein-ligand docking so far face many challenges, where the greatest probably is the ranking of true targets in a large data set of protein structures. Currently, no standard data sets for evaluation exist, rendering comparison and demonstration of improvements of methods cumbersome. Therefore, we propose two data sets and evaluation strategies for a meaningful evaluation of new target prediction methods, i.e., a small data set consisting of three target classes for detailed proof-of-concept and selectivity studies and a large data set consisting of 7992 protein structures and 72 drug-like ligands allowing statistical evaluation with performance metrics on a drug-like chemical space. Both data sets are built from openly available resources, and any information needed to perform the described experiments is reported. We describe the composition of the data sets, the setup of screening experiments, and the evaluation strategy. Performance metrics capable to measure the early recognition of enrichments like AUC, BEDROC, and NSLR are proposed. We apply a sequence-based target prediction method to the large data set to analyze its content of nontrivial evaluation cases. The proposed data sets are used for method evaluation of our new inverse screening method iRAISE. The small data set reveals the method's capability and limitations to selectively distinguish between rather similar protein structures. The large data set simulates real target identification scenarios. iRAISE achieves in 55% excellent or good enrichment a median AUC of 0.67 and RMSDs below 2.0 Å for 74% and was able to predict the first true target in 59 out of 72 cases in the top 2% of the protein data set of about 8000 structures.

  10. 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/.

  11. Measuring and Predicting the Internal Structure of Semiconductor Nanocrystals through Raman Spectroscopy.

    PubMed

    Mukherjee, Prabuddha; Lim, Sung Jun; Wrobel, Tomasz P; Bhargava, Rohit; Smith, Andrew M

    2016-08-31

    Nanocrystals composed of mixed chemical domains have diverse properties that are driving their integration in next-generation electronics, light sources, and biosensors. However, the precise spatial distribution of elements within these particles is difficult to measure and control, yet profoundly impacts their quality and performance. Here we synthesized a unique series of 42 different quantum dot nanocrystals, composed of two chemical domains (CdS:CdSe), arranged in 7 alloy and (core)shell structural classes. Chemometric analyses of far-field Raman spectra accurately classified their internal structures from their vibrational signatures. These classifications provide direct insight into the elemental arrangement of the alloy as well as an independent prediction of fluorescence quantum yield. This nondestructive, rapid approach can be broadly applied to greatly enhance our capacity to measure, predict and monitor multicomponent nanomaterials for precise tuning of their structures and properties. PMID:27472011

  12. 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

  13. 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.

  14. 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.

  15. Virality Prediction and Community Structure in Social Networks

    PubMed Central

    Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol

    2013-01-01

    How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications. PMID:23982106

  16. Virality Prediction and Community Structure in Social Networks

    NASA Astrophysics Data System (ADS)

    Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol

    2013-08-01

    How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications.

  17. Structure-Based Prediction of Protein-Folding Transition Paths.

    PubMed

    Jacobs, William M; Shakhnovich, Eugene I

    2016-09-01

    We propose a general theory to describe the distribution of protein-folding transition paths. We show that transition paths follow a predictable sequence of high-free-energy transient states that are separated by free-energy barriers. Each transient state corresponds to the assembly of one or more discrete, cooperative units, which are determined directly from the native structure. We show that the transition state on a folding pathway is reached when a small number of critical contacts are formed between a specific set of substructures, after which folding proceeds downhill in free energy. This approach suggests a natural resolution for distinguishing parallel folding pathways and provides a simple means to predict the rate-limiting step in a folding reaction. Our theory identifies a common folding mechanism for proteins with diverse native structures and establishes general principles for the self-assembly of polymers with specific interactions. PMID:27602721

  18. Structure-Based Prediction of Protein-Folding Transition Paths

    NASA Astrophysics Data System (ADS)

    Jacobs, William M.; Shakhnovich, Eugene I.

    2016-09-01

    We propose a general theory to describe the distribution of protein-folding transition paths. We show that transition paths follow a predictable sequence of high-free-energy transient states that are separated by free-energy barriers. Each transient state corresponds to the assembly of one or more discrete, cooperative units, which are determined directly from the native structure. We show that the transition state on a folding pathway is reached when a small number of critical contacts are formed between a specific set of substructures, after which folding proceeds downhill in free energy. This approach suggests a natural resolution for distinguishing parallel folding pathways and provides a simple means to predict the rate-limiting step in a folding reaction. Our theory identifies a common folding mechanism for proteins with diverse native structures and establishes general principles for the self-assembly of polymers with specific interactions.

  19. One Single Static Measurement Predicts Wave Localization in Complex Structures

    NASA Astrophysics Data System (ADS)

    Lefebvre, Gautier; Gondel, Alexane; Dubois, Marc; Atlan, Michael; Feppon, Florian; Labbé, Aimé; Gillot, Camille; Garelli, Alix; Ernoult, Maxence; Mayboroda, Svitlana; Filoche, Marcel; Sebbah, Patrick

    2016-08-01

    A recent theoretical breakthrough has brought a new tool, called the localization landscape, for predicting the localization regions of vibration modes in complex or disordered systems. Here, we report on the first experiment which measures the localization landscape and demonstrates its predictive power. Holographic measurement of the static deformation under uniform load of a thin plate with complex geometry provides direct access to the landscape function. When put in vibration, this system shows modes precisely confined within the subregions delineated by the landscape function. Also the maxima of this function match the measured eigenfrequencies, while the minima of the valley network gives the frequencies at which modes become extended. This approach fully characterizes the low frequency spectrum of a complex structure from a single static measurement. It paves the way for controlling and engineering eigenmodes in any vibratory system, especially where a structural or microscopic description is not accessible.

  20. Virality prediction and community structure in social networks.

    PubMed

    Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol

    2013-01-01

    How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications. PMID:23982106

  1. Virality prediction and community structure in social networks.

    PubMed

    Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol

    2013-01-01

    How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications.

  2. One Single Static Measurement Predicts Wave Localization in Complex Structures.

    PubMed

    Lefebvre, Gautier; Gondel, Alexane; Dubois, Marc; Atlan, Michael; Feppon, Florian; Labbé, Aimé; Gillot, Camille; Garelli, Alix; Ernoult, Maxence; Mayboroda, Svitlana; Filoche, Marcel; Sebbah, Patrick

    2016-08-12

    A recent theoretical breakthrough has brought a new tool, called the localization landscape, for predicting the localization regions of vibration modes in complex or disordered systems. Here, we report on the first experiment which measures the localization landscape and demonstrates its predictive power. Holographic measurement of the static deformation under uniform load of a thin plate with complex geometry provides direct access to the landscape function. When put in vibration, this system shows modes precisely confined within the subregions delineated by the landscape function. Also the maxima of this function match the measured eigenfrequencies, while the minima of the valley network gives the frequencies at which modes become extended. This approach fully characterizes the low frequency spectrum of a complex structure from a single static measurement. It paves the way for controlling and engineering eigenmodes in any vibratory system, especially where a structural or microscopic description is not accessible. PMID:27563967

  3. 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.

  4. An Integrated Multiscale Approach to River Flood Prediction Using a Land-Surface Hydrology Model

    NASA Astrophysics Data System (ADS)

    Mackey, B. P.; Barros, A. P.; Krishnamurti, T. N.

    2005-05-01

    This work outlines and demonstrates a comprehensive hydrometeorological flood forecasting system that is interdisciplinary in nature, multiscale in its approach, and state-of-the-art in its use of forecasting techniques. This integrated approach links both meteorological and hydrological tools in order to realize a more accurate prediction of major flood events three to six days in advance. One focus is on a new non-linear method to improve global multi-model superensemble precipitation forecasts with an emphasis on successful prediction of intense rain areas. On average, the skill from such a technique is higher and the bias lower than any of the individual member models, and the overall character of the precipitation distribution is maintained through the 5-day forecast period. In addition, global and nested regional spectral models are integrated in hindcast mode. Output from such models as well as from the superensemble is used as forcing input to a physically-based, spatially-distributed hydrology model in order to predict streamflow response during selected flood events. In this terrestrial hydrology prediction system, a dynamical water routing scheme and other physical parameterizations are used in conjunction with a 3-D hydrologic model that keeps track of surface water and energy budgets, including surface-subsurface interactions, groundwater and hydraulic river routing. Experiments are run for the Limpopo River basin in southeastern Africa, where massive flooding occurred in both years 2000 and 2001. An important intermediate step in this process is the downscaling of the precipitation forecasts from the course resolution atmospheric models to the much finer resolution (1 to 10 km) required by the hydrology model. For this purpose, we examined the space-time scaling behavior of simulated precipitation fields from the NWP models at different resolutions and devised a simple physically-based multifractal downscaling algorithm that relies on the scaling

  5. Predicting the integration of overlapping memories by decoding mnemonic processing states during learning.

    PubMed

    Richter, Franziska R; Chanales, Avi J H; Kuhl, Brice A

    2016-01-01

    The hippocampal memory system is thought to alternate between two opposing processing states: encoding and retrieval. When present experience overlaps with past experience, this creates a potential tradeoff between encoding the present and retrieving the past. This tradeoff may be resolved by memory integration-that is, by forming a mnemonic representation that links present experience with overlapping past experience. Here, we used fMRI decoding analyses to predict when - and establish how - past and present experiences become integrated in memory. In an initial experiment, we alternately instructed subjects to adopt encoding, retrieval or integration states during overlapping learning. We then trained across-subject pattern classifiers to 'read out' the instructed processing states from fMRI activity patterns. We show that an integration state was clearly dissociable from encoding or retrieval states. Moreover, trial-by-trial fluctuations in decoded evidence for an integration state during learning reliably predicted behavioral expressions of successful memory integration. Strikingly, the decoding algorithm also successfully predicted specific instances of spontaneous memory integration in an entirely independent sample of subjects for whom processing state instructions were not administered. Finally, we show that medial prefrontal cortex and hippocampus differentially contribute to encoding, retrieval, and integration states: whereas hippocampus signals the tradeoff between encoding vs. retrieval states, medial prefrontal cortex actively represents past experience in relation to new learning.

  6. 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.

  7. Effects of scale in predicting global structural response

    NASA Technical Reports Server (NTRS)

    Deo, R. B.; Kan, H. P.

    1991-01-01

    Analytical techniques for scale-up effects were reviewed. The advantages and limitations of applying the principles of similitude to composite structures is summarized and illustrated by simple examples. An analytical procedure was formulated to design scale models of an axially compressed composite cylinder. A building-block approach was outlined where each structural detail is analyzed independently and the probable failure sequence of a selected component is predicted, taking into account load redistribution subsequent to first element failure. Details of this building-block approach are under development.

  8. Unravelling the structure of species extinction risk for predictive conservation science.

    PubMed

    Lee, Tien Ming; Jetz, Walter

    2011-05-01

    Extinction risk varies across species and space owing to the combined and interactive effects of ecology/life history and geography. For predictive conservation science to be effective, large datasets and integrative models that quantify the relative importance of potential factors and separate rapidly changing from relatively static threat drivers are urgently required. Here, we integrate and map in space the relative and joint effects of key correlates of The International Union for Conservation of Nature-assessed extinction risk for 8700 living birds. Extinction risk varies significantly with species' broad-scale environmental niche, geographical range size, and life-history and ecological traits such as body size, developmental mode, primary diet and foraging height. Even at this broad scale, simple quantifications of past human encroachment across species' ranges emerge as key in predicting extinction risk, supporting the use of land-cover change projections for estimating future threat in an integrative setting. A final joint model explains much of the interspecific variation in extinction risk and provides a remarkably strong prediction of its observed global geography. Our approach unravels the species-level structure underlying geographical gradients in extinction risk and offers a means of disentangling static from changing components of current and future threat. This reconciliation of intrinsic and extrinsic, and of past and future extinction risk factors may offer a critical step towards a more continuous, forward-looking assessment of species' threat status based on geographically explicit environmental change projections, potentially advancing global predictive conservation science.

  9. An integrated probabilistic approach for gene function prediction using multiple sources of high-throughput data.

    PubMed

    Zhang, Chao; Joshi, Trupti; Lin, Guan Ning; Xu, Dong

    2008-01-01

    Characterising gene function is one of the major challenging tasks in the post-genomic era. Various approaches have been developed to integrate multiple sources of high-throughput data to predict gene function. Most of those approaches are just used for research purpose and have not been implemented as publicly available tools. Even for those implemented applications, almost all of them are still web-based 'prediction servers' that have to be managed by specialists. This paper introduces a systematic method for integrating various sources of high-throughput data to predict gene function and analyse our prediction results and evaluates its performances based on the competition for mouse gene function prediction (MouseFunc). A stand-alone Java-based software package 'GeneFAS' is freely available at http://digbio. missouri.eduigenefas.

  10. Protein secondary structure prediction using logic-based machine learning.

    PubMed

    Muggleton, S; King, R D; Sternberg, M J

    1992-10-01

    Many attempts have been made to solve the problem of predicting protein secondary structure from the primary sequence but the best performance results are still disappointing. In this paper, the use of a machine learning algorithm which allows relational descriptions is shown to lead to improved performance. The Inductive Logic Programming computer program, Golem, was applied to learning secondary structure prediction rules for alpha/alpha domain type proteins. The input to the program consisted of 12 non-homologous proteins (1612 residues) of known structure, together with a background knowledge describing the chemical and physical properties of the residues. Golem learned a small set of rules that predict which residues are part of the alpha-helices--based on their positional relationships and chemical and physical properties. The rules were tested on four independent non-homologous proteins (416 residues) giving an accuracy of 81% (+/- 2%). This is an improvement, on identical data, over the previously reported result of 73% by King and Sternberg (1990, J. Mol. Biol., 216, 441-457) using the machine learning program PROMIS, and of 72% using the standard Garnier-Osguthorpe-Robson method. The best previously reported result in the literature for the alpha/alpha domain type is 76%, achieved using a neural net approach. Machine learning also has the advantage over neural network and statistical methods in producing more understandable results. PMID:1480619

  11. Improved hybrid optimization algorithm for 3D protein structure prediction.

    PubMed

    Zhou, Changjun; Hou, Caixia; Wei, Xiaopeng; Zhang, Qiang

    2014-07-01

    A new improved hybrid optimization algorithm - PGATS algorithm, which is based on toy off-lattice model, is presented for dealing with three-dimensional protein structure prediction problems. The algorithm combines the particle swarm optimization (PSO), genetic algorithm (GA), and tabu search (TS) algorithms. Otherwise, we also take some different improved strategies. The factor of stochastic disturbance is joined in the particle swarm optimization to improve the search ability; the operations of crossover and mutation that are in the genetic algorithm are changed to a kind of random liner method; at last tabu search algorithm is improved by appending a mutation operator. Through the combination of a variety of strategies and algorithms, the protein structure prediction (PSP) in a 3D off-lattice model is achieved. The PSP problem is an NP-hard problem, but the problem can be attributed to a global optimization problem of multi-extremum and multi-parameters. This is the theoretical principle of the hybrid optimization algorithm that is proposed in this paper. The algorithm combines local search and global search, which overcomes the shortcoming of a single algorithm, giving full play to the advantage of each algorithm. In the current universal standard sequences, Fibonacci sequences and real protein sequences are certified. Experiments show that the proposed new method outperforms single algorithms on the accuracy of calculating the protein sequence energy value, which is proved to be an effective way to predict the structure of proteins. PMID:25069136

  12. Improving protein structure prediction using multiple sequence-based contact predictions

    PubMed Central

    Wu, Sitao; Szilagyi, Andras; Zhang, Yang

    2011-01-01

    Summary Although residue-residue contact maps dictate the topology of proteins, sequence-based ab initio contact predictions have been found little use in actual structure prediction due to the low accuracy. We developed a composite set of nine SVM-based contact predictors which are used in I-TASSER simulation in combination with sparse template contact restraints. When testing the strategy on 273 non-homologous targets, remarkable improvements of I-TASSER models were observed for both easy and hard targets, with P-value by student s t-test below 0.00001 and 0.001, respectively. In several cases, TM-score increases by >30%, which essentially converts “non-foldable” targets into “foldable” ones. In CASP9, I-TASSER employed ab initio contact predictions, and generated models for 26 FM targets with a GDT-score 16% and 44% higher than the second and third best servers from other groups, respectively. These findings demonstrate a new avenue to improve the accuracy of protein structure prediction especially for free-modeling targets. PMID:21827953

  13. Drug repositioning by kernel-based integration of molecular structure, molecular activity, and phenotype data.

    PubMed

    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.

  14. Tensile-integrity structural concepts for the lunar surface

    NASA Astrophysics Data System (ADS)

    Benaroya, H.; Ettouney, M.

    This paper suggests the use of tension cable structures of a particular type, Tensegrity structures, for a lunar base. Tensegric shells can be a system of bars and cable net. The shell attains its topology and stiffness when the bars are prestressed against the cable net. In its final configuration, no bar is in contact with another. Tensegric shells and other configurations are self sustaining. Unlike inflatable structures, they do not depend on internal pressurization for their integrity.

  15. Sequence-only evolutionary and predicted structural features for the prediction of stability changes in protein mutants

    PubMed Central

    2013-01-01

    Background Even a single amino acid substitution in a protein sequence may result in significant changes in protein stability, structure, and therefore in protein function as well. In the post-genomic era, computational methods for predicting stability changes from only the sequence of a protein are of importance. While evolutionary relationships of protein mutations can be extracted from large protein databases holding millions of protein sequences, relevant evolutionary features for the prediction of stability changes have not been proposed. Also, the use of predicted structural features in situations when a protein structure is not available has not been explored. Results We proposed a number of evolutionary and predicted structural features for the prediction of stability changes and analysed which of them capture the determinants of protein stability the best. We trained and evaluated our machine learning method on a non-redundant data set of experimentally measured stability changes. When only the direction of the stability change was predicted, we found that the best performance improvement can be achieved by the combination of the evolutionary features mutation likelihood and SIFTscore in conjunction with the predicted structural feature secondary structure. The same two evolutionary features in the combination with the predicted structural feature accessible surface area achieved the lowest error when the prediction of actual values of stability changes was assessed. Compared to similar studies, our method achieved improvements in prediction performance. Conclusion Although the strongest feature for the prediction of stability changes appears to be the vector of amino acid identities in the sequential neighbourhood of the mutation, the most relevant combination of evolutionary and predicted structural features further improves prediction performance. Even the predicted structural features, which did not perform well on their own, turn out to be beneficial

  16. 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

  17. 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

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

    PubMed Central

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

    2016-01-01

    Background 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. Methods 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. Results 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. Conclusion 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. PMID:26959647

  19. Graphlet kernels for prediction of functional residues in protein structures.

    PubMed

    Vacic, Vladimir; Iakoucheva, Lilia M; Lonardi, Stefano; Radivojac, Predrag

    2010-01-01

    We introduce a novel graph-based kernel method for annotating functional residues in protein structures. A structure is first modeled as a protein contact graph, where nodes correspond to residues and edges connect spatially neighboring residues. Each vertex in the graph is then represented as a vector of counts of labeled non-isomorphic subgraphs (graphlets), centered on the vertex of interest. A similarity measure between two vertices is expressed as the inner product of their respective count vectors and is used in a supervised learning framework to classify protein residues. We evaluated our method on two function prediction problems: identification of catalytic residues in proteins, which is a well-studied problem suitable for benchmarking, and a much less explored problem of predicting phosphorylation sites in protein structures. The performance of the graphlet kernel approach was then compared against two alternative methods, a sequence-based predictor and our implementation of the FEATURE framework. On both tasks, the graphlet kernel performed favorably; however, the margin of difference was considerably higher on the problem of phosphorylation site prediction. While there is data that phosphorylation sites are preferentially positioned in intrinsically disordered regions, we provide evidence that for the sites that are located in structured regions, neither the surface accessibility alone nor the averaged measures calculated from the residue microenvironments utilized by FEATURE were sufficient to achieve high accuracy. The key benefit of the graphlet representation is its ability to capture neighborhood similarities in protein structures via enumerating the patterns of local connectivity in the corresponding labeled graphs.

  20. Ocean circulation model predicts high genetic structure observed in a long-lived pelagic developer.

    PubMed

    Sunday, J M; Popovic, I; Palen, W J; Foreman, M G G; Hart, M W

    2014-10-01

    Understanding the movement of genes and individuals across marine seascapes is a long-standing challenge in marine ecology and can inform our understanding of local adaptation, the persistence and movement of populations, and the spatial scale of effective management. Patterns of gene flow in the ocean are often inferred based on population genetic analyses coupled with knowledge of species' dispersive life histories. However, genetic structure is the result of time-integrated processes and may not capture present-day connectivity between populations. Here, we use a high-resolution oceanographic circulation model to predict larval dispersal along the complex coastline of western Canada that includes the transition between two well-studied zoogeographic provinces. We simulate dispersal in a benthic sea star with a 6-10 week pelagic larval phase and test predictions of this model against previously observed genetic structure including a strong phylogeographic break within the zoogeographical transition zone. We also test predictions with new genetic sampling in a site within the phylogeographic break. We find that the coupled genetic and circulation model predicts the high degree of genetic structure observed in this species, despite its long pelagic duration. High genetic structure on this complex coastline can thus be explained through ocean circulation patterns, which tend to retain passive larvae within 20-50 km of their parents, suggesting a necessity for close-knit design of Marine Protected Area networks.

  1. Improved Displacement Transfer Functions for Structure Deformed Shape Predictions Using Discretely Distributed Surface Strains

    NASA Technical Reports Server (NTRS)

    Ko, William L.; Fleischer, Van Tran

    2012-01-01

    In the formulations of earlier Displacement Transfer Functions for structure shape predictions, the surface strain distributions, along a strain-sensing line, were represented with piecewise linear functions. To improve the shape-prediction accuracies, Improved Displacement Transfer Functions were formulated using piecewise nonlinear strain representations. Through discretization of an embedded beam (depth-wise cross section of a structure along a strain-sensing line) into multiple small domains, piecewise nonlinear functions were used to describe the surface strain distributions along the discretized embedded beam. Such piecewise approach enabled the piecewise integrations of the embedded beam curvature equations to yield slope and deflection equations in recursive forms. The resulting Improved Displacement Transfer Functions, written in summation forms, were expressed in terms of beam geometrical parameters and surface strains along the strain-sensing line. By feeding the surface strains into the Improved Displacement Transfer Functions, structural deflections could be calculated at multiple points for mapping out the overall structural deformed shapes for visual display. The shape-prediction accuracies of the Improved Displacement Transfer Functions were then examined in view of finite-element-calculated deflections using different tapered cantilever tubular beams. It was found that by using the piecewise nonlinear strain representations, the shape-prediction accuracies could be greatly improved, especially for highly-tapered cantilever tubular beams.

  2. Ocean circulation model predicts high genetic structure observed in a long-lived pelagic developer.

    PubMed

    Sunday, J M; Popovic, I; Palen, W J; Foreman, M G G; Hart, M W

    2014-10-01

    Understanding the movement of genes and individuals across marine seascapes is a long-standing challenge in marine ecology and can inform our understanding of local adaptation, the persistence and movement of populations, and the spatial scale of effective management. Patterns of gene flow in the ocean are often inferred based on population genetic analyses coupled with knowledge of species' dispersive life histories. However, genetic structure is the result of time-integrated processes and may not capture present-day connectivity between populations. Here, we use a high-resolution oceanographic circulation model to predict larval dispersal along the complex coastline of western Canada that includes the transition between two well-studied zoogeographic provinces. We simulate dispersal in a benthic sea star with a 6-10 week pelagic larval phase and test predictions of this model against previously observed genetic structure including a strong phylogeographic break within the zoogeographical transition zone. We also test predictions with new genetic sampling in a site within the phylogeographic break. We find that the coupled genetic and circulation model predicts the high degree of genetic structure observed in this species, despite its long pelagic duration. High genetic structure on this complex coastline can thus be explained through ocean circulation patterns, which tend to retain passive larvae within 20-50 km of their parents, suggesting a necessity for close-knit design of Marine Protected Area networks. PMID:25231198

  3. 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

  4. How Good Are Simplified Models for Protein Structure Prediction?

    PubMed Central

    Newton, M. A. Hakim; Rashid, Mahmood A.; Pham, Duc Nghia; Sattar, Abdul

    2014-01-01

    Protein structure prediction (PSP) has been one of the most challenging problems in computational biology for several decades. The challenge is largely due to the complexity of the all-atomic details and the unknown nature of the energy function. Researchers have therefore used simplified energy models that consider interaction potentials only between the amino acid monomers in contact on discrete lattices. The restricted nature of the lattices and the energy models poses a twofold concern regarding the assessment of the models. Can a native or a very close structure be obtained when structures are mapped to lattices? Can the contact based energy models on discrete lattices guide the search towards the native structures? In this paper, we use the protein chain lattice fitting (PCLF) problem to address the first concern; we developed a constraint-based local search algorithm for the PCLF problem for cubic and face-centered cubic lattices and found very close lattice fits for the native structures. For the second concern, we use a number of techniques to sample the conformation space and find correlations between energy functions and root mean square deviation (RMSD) distance of the lattice-based structures with the native structures. Our analysis reveals weakness of several contact based energy models used that are popular in PSP. PMID:24876837

  5. 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.

  6. Structure Prediction: New Insights into Decrypting Long Noncoding RNAs

    PubMed Central

    Yan, Kun; Arfat, Yasir; Li, Dijie; Zhao, Fan; Chen, Zhihao; Yin, Chong; Sun, Yulong; Hu, Lifang; Yang, Tuanmin; Qian, Airong

    2016-01-01

    Long noncoding RNAs (lncRNAs), which form a diverse class of RNAs, remain the least understood type of noncoding RNAs in terms of their nature and identification. Emerging evidence has revealed that a small number of newly discovered lncRNAs perform important and complex biological functions such as dosage compensation, chromatin regulation, genomic imprinting, and nuclear organization. However, understanding the wide range of functions of lncRNAs related to various processes of cellular networks remains a great experimental challenge. Structural versatility is critical for RNAs to perform various functions and provides new insights into probing the functions of lncRNAs. In recent years, the computational method of RNA structure prediction has been developed to analyze the structure of lncRNAs. This novel methodology has provided basic but indispensable information for the rapid, large-scale and in-depth research of lncRNAs. This review focuses on mainstream RNA structure prediction methods at the secondary and tertiary levels to offer an additional approach to investigating the functions of lncRNAs. PMID:26805815

  7. Prediction of gene expression in embryonic structures of Drosophila melanogaster.

    PubMed

    Samsonova, Anastasia A; Niranjan, Mahesan; Russell, Steven; Brazma, Alvis

    2007-07-01

    Understanding how sets of genes are coordinately regulated in space and time to generate the diversity of cell types that characterise complex metazoans is a major challenge in modern biology. The use of high-throughput approaches, such as large-scale in situ hybridisation and genome-wide expression profiling via DNA microarrays, is beginning to provide insights into the complexities of development. However, in many organisms the collection and annotation of comprehensive in situ localisation data is a difficult and time-consuming task. Here, we present a widely applicable computational approach, integrating developmental time-course microarray data with annotated in situ hybridisation studies, that facilitates the de novo prediction of tissue-specific expression for genes that have no in vivo gene expression localisation data available. Using a classification approach, trained with data from microarray and in situ hybridisation studies of gene expression during Drosophila embryonic development, we made a set of predictions on the tissue-specific expression of Drosophila genes that have not been systematically characterised by in situ hybridisation experiments. The reliability of our predictions is confirmed by literature-derived annotations in FlyBase, by overrepresentation of Gene Ontology biological process annotations, and, in a selected set, by detailed gene-specific studies from the literature. Our novel organism-independent method will be of considerable utility in enriching the annotation of gene function and expression in complex multicellular organisms.

  8. EVO—Evolutionary algorithm for crystal structure prediction

    NASA Astrophysics Data System (ADS)

    Bahmann, Silvia; Kortus, Jens

    2013-06-01

    We present EVO—an evolution strategy designed for crystal structure search and prediction. The concept and main features of biological evolution such as creation of diversity and survival of the fittest have been transferred to crystal structure prediction. EVO successfully demonstrates its applicability to find crystal structures of the elements of the 3rd main group with their different spacegroups. For this we used the number of atoms in the conventional cell and multiples of it. Running EVO with different numbers of carbon atoms per unit cell yields graphite as the lowest energy structure as well as a diamond-like structure, both in one run. Our implementation also supports the search for 2D structures and was able to find a boron sheet with structural features so far not considered in literature. Program summaryProgram title: EVO Catalogue identifier: AEOZ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEOZ_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License version 3 No. of lines in distributed program, including test data, etc.: 23488 No. of bytes in distributed program, including test data, etc.: 1830122 Distribution format: tar.gz Programming language: Python. Computer: No limitations known. Operating system: Linux. RAM: Negligible compared to the requirements of the electronic structure programs used Classification: 7.8. External routines: Quantum ESPRESSO (http://www.quantum-espresso.org/), GULP (https://projects.ivec.org/gulp/) Nature of problem: Crystal structure search is a global optimisation problem in 3N+3 dimensions where N is the number of atoms in the unit cell. The high dimensional search space is accompanied by an unknown energy landscape. Solution method: Evolutionary algorithms transfer the main features of biological evolution to use them in global searches. The combination of the "survival of the fittest" (deterministic) and the

  9. Structure-dynamics relationships in bursting neuronal networks revealed using a prediction framework.

    PubMed

    Mäki-Marttunen, Tuomo; Aćimović, Jugoslava; Ruohonen, Keijo; Linne, Marja-Leena

    2013-01-01

    The question of how the structure of a neuronal network affects its functionality has gained a lot of attention in neuroscience. However, the vast majority of the studies on structure-dynamics relationships consider few types of network structures and assess limited numbers of structural measures. In this in silico study, we employ a wide diversity of network topologies and search among many possibilities the aspects of structure that have the greatest effect on the network excitability. The network activity is simulated using two point-neuron models, where the neurons are activated by noisy fluctuation of the membrane potential and their connections are described by chemical synapse models, and statistics on the number and quality of the emergent network bursts are collected for each network type. We apply a prediction framework to the obtained data in order to find out the most relevant aspects of network structure. In this framework, predictors that use different sets of graph-theoretic measures are trained to estimate the activity properties, such as burst count or burst length, of the networks. The performances of these predictors are compared with each other. We show that the best performance in prediction of activity properties for networks with sharp in-degree distribution is obtained when the prediction is based on clustering coefficient. By contrast, for networks with broad in-degree distribution, the maximum eigenvalue of the connectivity graph gives the most accurate prediction. The results shown for small ([Formula: see text]) networks hold with few exceptions when different neuron models, different choices of neuron population and different average degrees are applied. We confirm our conclusions using larger ([Formula: see text]) networks as well. Our findings reveal the relevance of different aspects of network structure from the viewpoint of network excitability, and our integrative method could serve as a general framework for structure

  10. 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.

  11. 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.

  12. 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.

  13. Prediction of three-dimensional transmembrane helical protein structures

    NASA Astrophysics Data System (ADS)

    Barth, Patrick

    Membrane proteins are critical to living cells and their dysfunction can lead to serious diseases. High-resolution structures of these proteins would provide very valuable information for designing eficient therapies but membrane protein crystallization is a major bottleneck. As an important alternative approach, methods for predicting membrane protein structures have been developed in recent years. This chapter focuses on the problem of modeling the structure of transmembrane helical proteins, and describes recent advancements, current limitations, and future challenges facing de novo modeling, modeling with experimental constraints, and high-resolution comparative modeling of these proteins. Abbreviations: MP, membrane protein; SP, water-soluble protein; RMSD, root-mean square deviation; Cα RMSD, root-mean square deviation over Cα atoms; TM, transmembrane; TMH, transmembrane helix; GPCR, G protein-coupled receptor; 3D, three dimensional; NMR, nuclear magnetic resonance spectroscopy; EPR, electron paramagnetic resonance spectroscopy; FTIR, Fourier transform infrared spectroscopy.

  14. Predicting the stability of large structured food webs.

    PubMed

    Allesina, Stefano; Grilli, Jacopo; Barabás, György; Tang, Si; Aljadeff, Johnatan; Maritan, Amos

    2015-01-01

    The stability of ecological systems has been a long-standing focus of ecology. Recently, tools from random matrix theory have identified the main drivers of stability in ecological communities whose network structure is random. However, empirical food webs differ greatly from random graphs. For example, their degree distribution is broader, they contain few trophic cycles, and they are almost interval. Here we derive an approximation for the stability of food webs whose structure is generated by the cascade model, in which 'larger' species consume 'smaller' ones. We predict the stability of these food webs with great accuracy, and our approximation also works well for food webs whose structure is determined empirically or by the niche model. We find that intervality and broad degree distributions tend to stabilize food webs, and that average interaction strength has little influence on stability, compared with the effect of variance and correlation. PMID:26198207

  15. Predicting the stability of large structured food webs

    PubMed Central

    Allesina, Stefano; Grilli, Jacopo; Barabás, György; Tang, Si; Aljadeff, Johnatan; Maritan, Amos

    2015-01-01

    The stability of ecological systems has been a long-standing focus of ecology. Recently, tools from random matrix theory have identified the main drivers of stability in ecological communities whose network structure is random. However, empirical food webs differ greatly from random graphs. For example, their degree distribution is broader, they contain few trophic cycles, and they are almost interval. Here we derive an approximation for the stability of food webs whose structure is generated by the cascade model, in which ‘larger' species consume ‘smaller' ones. We predict the stability of these food webs with great accuracy, and our approximation also works well for food webs whose structure is determined empirically or by the niche model. We find that intervality and broad degree distributions tend to stabilize food webs, and that average interaction strength has little influence on stability, compared with the effect of variance and correlation. PMID:26198207

  16. Predicting the stability of large structured food webs.

    PubMed

    Allesina, Stefano; Grilli, Jacopo; Barabás, György; Tang, Si; Aljadeff, Johnatan; Maritan, Amos

    2015-07-22

    The stability of ecological systems has been a long-standing focus of ecology. Recently, tools from random matrix theory have identified the main drivers of stability in ecological communities whose network structure is random. However, empirical food webs differ greatly from random graphs. For example, their degree distribution is broader, they contain few trophic cycles, and they are almost interval. Here we derive an approximation for the stability of food webs whose structure is generated by the cascade model, in which 'larger' species consume 'smaller' ones. We predict the stability of these food webs with great accuracy, and our approximation also works well for food webs whose structure is determined empirically or by the niche model. We find that intervality and broad degree distributions tend to stabilize food webs, and that average interaction strength has little influence on stability, compared with the effect of variance and correlation.

  17. Predictive modeling of multicellular structure formation by using Cellular Particle Dynamics simulations

    NASA Astrophysics Data System (ADS)

    McCune, Matthew; Shafiee, Ashkan; Forgacs, Gabor; Kosztin, Ioan

    2014-03-01

    Cellular Particle Dynamics (CPD) is an effective computational method for describing and predicting the time evolution of biomechanical relaxation processes of multicellular systems. A typical example is the fusion of spheroidal bioink particles during post bioprinting structure formation. In CPD cells are modeled as an ensemble of cellular particles (CPs) that interact via short-range contact interactions, characterized by an attractive (adhesive interaction) and a repulsive (excluded volume interaction) component. The time evolution of the spatial conformation of the multicellular system is determined by following the trajectories of all CPs through integration of their equations of motion. CPD was successfully applied to describe and predict the fusion of 3D tissue construct involving identical spherical aggregates. Here, we demonstrate that CPD can also predict tissue formation involving uneven spherical aggregates whose volumes decrease during the fusion process. Work supported by NSF [PHY-0957914]. Computer time provided by the University of Missouri Bioinformatics Consortium.

  18. Predicting modes of toxic action from chemical structure: an overview.

    PubMed

    Bradbury, S P

    1994-01-01

    In the field of environmental toxicology, and especially aquatic toxicology, quantitative structure activity relationships (QSARs) have developed as scientifically-credible tools for predicting the toxicity of chemicals when little or no empirical data are available. A basic and fundamental understanding of toxicological principles has been considered crucial to the continued acceptance and application of these techniques as biologically relevant. As a consequence, there has been an evolution of QSAR development and application from that of a chemical-class perspective to one that is more consistent with assumptions regarding modes of toxic action. The assessment of a compound's likely mode of toxic action is critical for a correct QSAR selection; incorrect mode of action-based QSAR selections can result in 10- to 1000-fold errors in toxicity predictions. The establishment of toxicologically-credible techniques to assess mode of toxic action from chemical structure requires toxicodynamic knowledge bases that are clearly defined with regard to exposure regimes and biological models/endpoints and based on compounds that adequately span the diversity of chemicals anticipated for future applications. With such knowledge bases classification systems, including rule-based experts systems, have been established for use in predictive aquatic toxicology applications. PMID:8790641

  19. RNAex: an RNA secondary structure prediction server enhanced by high-throughput structure-probing data.

    PubMed

    Wu, Yang; Qu, Rihao; Huang, Yiming; Shi, Binbin; Liu, Mengrong; Li, Yang; Lu, Zhi John

    2016-07-01

    Several high-throughput technologies have been developed to probe RNA base pairs and loops at the transcriptome level in multiple species. However, to obtain the final RNA secondary structure, extensive effort and considerable expertise is required to statistically process the probing data and combine them with free energy models. Therefore, we developed an RNA secondary structure prediction server that is enhanced by experimental data (RNAex). RNAex is a web interface that enables non-specialists to easily access cutting-edge structure-probing data and predict RNA secondary structures enhanced by in vivo and in vitro data. RNAex annotates the RNA editing, RNA modification and SNP sites on the predicted structures. It provides four structure-folding methods, restrained MaxExpect, SeqFold, RNAstructure (Fold) and RNAfold that can be selected by the user. The performance of these four folding methods has been verified by previous publications on known structures. We re-mapped the raw sequencing data of the probing experiments to the whole genome for each species. RNAex thus enables users to predict secondary structures for both known and novel RNA transcripts in human, mouse, yeast and Arabidopsis The RNAex web server is available at http://RNAex.ncrnalab.org/.

  20. RNAex: an RNA secondary structure prediction server enhanced by high-throughput structure-probing data

    PubMed Central

    Wu, Yang; Qu, Rihao; Huang, Yiming; Shi, Binbin; Liu, Mengrong; Li, Yang; Lu, Zhi John

    2016-01-01

    Several high-throughput technologies have been developed to probe RNA base pairs and loops at the transcriptome level in multiple species. However, to obtain the final RNA secondary structure, extensive effort and considerable expertise is required to statistically process the probing data and combine them with free energy models. Therefore, we developed an RNA secondary structure prediction server that is enhanced by experimental data (RNAex). RNAex is a web interface that enables non-specialists to easily access cutting-edge structure-probing data and predict RNA secondary structures enhanced by in vivo and in vitro data. RNAex annotates the RNA editing, RNA modification and SNP sites on the predicted structures. It provides four structure-folding methods, restrained MaxExpect, SeqFold, RNAstructure (Fold) and RNAfold that can be selected by the user. The performance of these four folding methods has been verified by previous publications on known structures. We re-mapped the raw sequencing data of the probing experiments to the whole genome for each species. RNAex thus enables users to predict secondary structures for both known and novel RNA transcripts in human, mouse, yeast and Arabidopsis. The RNAex web server is available at http://RNAex.ncrnalab.org/. PMID:27137891

  1. 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.

  2. Ligand-Target Prediction by Structural Network Biology Using nAnnoLyze

    PubMed Central

    Martínez-Jiménez, Francisco; Marti-Renom, Marc A.

    2015-01-01

    Target identification is essential for drug design, drug-drug interaction prediction, dosage adjustment and side effect anticipation. Specifically, the knowledge of structural details is essential for understanding the mode of action of a compound on a target protein. Here, we present nAnnoLyze, a method for target identification that relies on the hypothesis that structurally similar binding sites bind similar ligands. nAnnoLyze integrates structural information into a bipartite network of interactions and similarities to predict structurally detailed compound-protein interactions at proteome scale. The method was benchmarked on a dataset of 6,282 pairs of known interacting ligand-target pairs reaching a 0.96 of area under the Receiver Operating Characteristic curve (AUC) when using the drug names as an input feature for the classifier, and a 0.70 of AUC for “anonymous” compounds or compounds not present in the training set. nAnnoLyze resulted in higher accuracies than its predecessor, AnnoLyze. We applied the method to predict interactions for all the compounds in the DrugBank database with each human protein structure and provide examples of target identification for known drugs against human diseases. The accuracy and applicability of our method to any compound indicate that a comparative docking approach such as nAnnoLyze enables large-scale annotation and analysis of compound–protein interactions and thus may benefit drug development. PMID:25816344

  3. Predicting protein ligand binding sites by combining evolutionary sequence conservation and 3D structure.

    PubMed

    Capra, John A; Laskowski, Roman A; Thornton, Janet M; Singh, Mona; Funkhouser, Thomas A

    2009-12-01

    Identifying a protein's functional sites is an important step towards characterizing its molecular function. Numerous structure- and sequence-based methods have been developed for this problem. Here we introduce ConCavity, a small molecule binding site prediction algorithm that integrates evolutionary sequence conservation estimates with structure-based methods for identifying protein surface cavities. In large-scale testing on a diverse set of single- and multi-chain protein structures, we show that ConCavity substantially outperforms existing methods for identifying both 3D ligand binding pockets and individual ligand binding residues. As part of our testing, we perform one of the first direct comparisons of conservation-based and structure-based methods. We find that the two approaches provide largely complementary information, which can be combined to improve upon either approach alone. We also demonstrate that ConCavity has state-of-the-art performance in predicting catalytic sites and drug binding pockets. Overall, the algorithms and analysis presented here significantly improve our ability to identify ligand binding sites and further advance our understanding of the relationship between evolutionary sequence conservation and structural and functional attributes of proteins. Data, source code, and prediction visualizations are available on the ConCavity web site (http://compbio.cs.princeton.edu/concavity/).

  4. Addressing the Role of Conformational Diversity in Protein Structure Prediction.

    PubMed

    Palopoli, Nicolas; Monzon, Alexander Miguel; Parisi, Gustavo; Fornasari, Maria Silvina

    2016-01-01

    Computational modeling of tertiary structures has become of standard use to study proteins that lack experimental characterization. Unfortunately, 3D structure prediction methods and model quality assessment programs often overlook that an ensemble of conformers in equilibrium populates the native state of proteins. In this work we collected sets of publicly available protein models and the corresponding target structures experimentally solved and studied how they describe the conformational diversity of the protein. For each protein, we assessed the quality of the models against known conformers by several standard measures and identified those models ranked best. We found that model rankings are defined by both the selected target conformer and the similarity measure used. 70% of the proteins in our datasets show that different models are structurally closest to different conformers of the same protein target. We observed that model building protocols such as template-based or ab initio approaches describe in similar ways the conformational diversity of the protein, although for template-based methods this description may depend on the sequence similarity between target and template sequences. Taken together, our results support the idea that protein structure modeling could help to identify members of the native ensemble, highlight the importance of considering conformational diversity in protein 3D quality evaluations and endorse the study of the variability of the native structure for a meaningful biological analysis. PMID:27159429

  5. Addressing the Role of Conformational Diversity in Protein Structure Prediction

    PubMed Central

    Parisi, Gustavo; Fornasari, Maria Silvina

    2016-01-01

    Computational modeling of tertiary structures has become of standard use to study proteins that lack experimental characterization. Unfortunately, 3D structure prediction methods and model quality assessment programs often overlook that an ensemble of conformers in equilibrium populates the native state of proteins. In this work we collected sets of publicly available protein models and the corresponding target structures experimentally solved and studied how they describe the conformational diversity of the protein. For each protein, we assessed the quality of the models against known conformers by several standard measures and identified those models ranked best. We found that model rankings are defined by both the selected target conformer and the similarity measure used. 70% of the proteins in our datasets show that different models are structurally closest to different conformers of the same protein target. We observed that model building protocols such as template-based or ab initio approaches describe in similar ways the conformational diversity of the protein, although for template-based methods this description may depend on the sequence similarity between target and template sequences. Taken together, our results support the idea that protein structure modeling could help to identify members of the native ensemble, highlight the importance of considering conformational diversity in protein 3D quality evaluations and endorse the study of the variability of the native structure for a meaningful biological analysis. PMID:27159429

  6. An Integrated Children Disease Prediction Tool within a Special Social Network.

    PubMed

    Apostolova Trpkovska, Marika; Yildirim Yayilgan, Sule; Besimi, Adrian

    2016-01-01

    This paper proposes a social network with an integrated children disease prediction system developed by the use of the specially designed Children General Disease Ontology (CGDO). This ontology consists of children diseases and their relationship with symptoms and Semantic Web Rule Language (SWRL rules) that are specially designed for predicting diseases. The prediction process starts by filling data about the appeared signs and symptoms by the user which are after that mapped with the CGDO ontology. Once the data are mapped, the prediction results are presented. The phase of prediction executes the rules which extract the predicted disease details based on the SWRL rule specified. The motivation behind the development of this system is to spread knowledge about the children diseases and their symptoms in a very simple way using the specialized social networking website www.emama.mk. PMID:27071879

  7. An Integrated Children Disease Prediction Tool within a Special Social Network.

    PubMed

    Apostolova Trpkovska, Marika; Yildirim Yayilgan, Sule; Besimi, Adrian

    2016-01-01

    This paper proposes a social network with an integrated children disease prediction system developed by the use of the specially designed Children General Disease Ontology (CGDO). This ontology consists of children diseases and their relationship with symptoms and Semantic Web Rule Language (SWRL rules) that are specially designed for predicting diseases. The prediction process starts by filling data about the appeared signs and symptoms by the user which are after that mapped with the CGDO ontology. Once the data are mapped, the prediction results are presented. The phase of prediction executes the rules which extract the predicted disease details based on the SWRL rule specified. The motivation behind the development of this system is to spread knowledge about the children diseases and their symptoms in a very simple way using the specialized social networking website www.emama.mk.

  8. Predicting Structural Behavior of Filament Wound Composite Pressure Vessel Using Three Dimensional Shell Analysis

    NASA Astrophysics Data System (ADS)

    Madhavi, M.; Venkat, R.

    2014-01-01

    Fiber reinforced polymer composite materials with their higher specific strength, moduli and tailorability characteristics will result in reduction of weight of the structure. The composite pressure vessels with integrated end domes develop hoop stresses that are twice longitudinal stresses and when isotropic materials like metals are used for development of the hardware and the material is not fully utilized in the longitudinal/meridional direction resulting in over weight components. The determination of a proper winding angles and thickness is very important to decrease manufacturing difficulties and to increase structural efficiency. In the present study a methodology is developed to understand structural characteristics of filament wound pressure vessels with integrated end domes. Progressive ply wise failure analysis of composite pressure vessel with geodesic end domes is carried out to determine matrix crack failure, burst pressure values at various positions of the shell. A three dimensional finite element analysis is computed to predict the deformations and stresses in the composite pressure vessel. The proposed method could save the time to design filament wound structures, to check whether the ply design is safe for the given input conditions and also can be adapted to non-geodesic structures. The results can be utilized to understand structural characteristics of filament wound pressure vessels with integrated end domes. This approach can be adopted for various applications like solid rocket motor casings, automobile fuel storage tanks and chemical storage tanks. Based on the predictions a composite pressure vessel is designed and developed. Hydraulic test is performed on the composite pressure vessel till the burst pressure.

  9. FOURIER ANALYSIS OF EXTENDED FINE STRUCTURE WITH AUTOREGRESSIVE PREDICTION

    SciTech Connect

    Barton, J.; Shirley, D.A.

    1985-01-01

    Autoregressive prediction is adapted to double the resolution of Angle-Resolved Photoemission Extended Fine Structure (ARPEFS) Fourier transforms. Even with the optimal taper (weighting function), the commonly used taper-and-transform Fourier method has limited resolution: it assumes the signal is zero beyond the limits of the measurement. By seeking the Fourier spectrum of an infinite extent oscillation consistent with the measurements but otherwise having maximum entropy, the errors caused by finite data range can be reduced. Our procedure developed to implement this concept applies autoregressive prediction to extrapolate the signal to an extent controlled by a taper width. Difficulties encountered when processing actual ARPEFS data are discussed. A key feature of this approach is the ability to convert improved measurements (signal-to-noise or point density) into improved Fourier resolution.

  10. An Automated Bayesian Framework for Integrative Gene Expression Analysis and Predictive Medicine

    PubMed Central

    Parikh, Neena; Zollanvari, Amin; Alterovitz, Gil

    2012-01-01

    Motivation This work constructs a closed loop Bayesian Network framework for predictive medicine via integrative analysis of publicly available gene expression findings pertaining to various diseases. Results: An automated pipeline was successfully constructed. Integrative models were made based on gene expression data obtained from GEO experiments relating to four different diseases using Bayesian statistical methods. Many of these models demonstrated a high level of accuracy and predictive ability. The approach described in this paper can be applied to any complex disorder and can include any number and type of genome-scale studies. PMID:22779059

  11. Multi-omics integration accurately predicts cellular state in unexplored conditions for Escherichia coli

    PubMed Central

    Kim, Minseung; Rai, Navneet; Zorraquino, Violeta; Tagkopoulos, Ilias

    2016-01-01

    A significant obstacle in training predictive cell models is the lack of integrated data sources. We develop semi-supervised normalization pipelines and perform experimental characterization (growth, transcriptional, proteome) to create Ecomics, a consistent, quality-controlled multi-omics compendium for Escherichia coli with cohesive meta-data information. We then use this resource to train a multi-scale model that integrates four omics layers to predict genome-wide concentrations and growth dynamics. The genetic and environmental ontology reconstructed from the omics data is substantially different and complementary to the genetic and chemical ontologies. The integration of different layers confers an incremental increase in the prediction performance, as does the information about the known gene regulatory and protein-protein interactions. The predictive performance of the model ranges from 0.54 to 0.87 for the various omics layers, which far exceeds various baselines. This work provides an integrative framework of omics-driven predictive modelling that is broadly applicable to guide biological discovery. PMID:27713404

  12. Cortical structure predicts success in performing musical transformation judgments.

    PubMed

    Foster, Nicholas E V; Zatorre, Robert J

    2010-10-15

    Recognizing melodies by their interval structure, or "relative pitch," is a fundamental aspect of musical perception. By using relative pitch, we are able to recognize tunes regardless of the key in which they are played. We sought to determine the cortical areas important for relative pitch processing using two morphometric techniques. Cortical differences have been reported in musicians within right auditory cortex (AC), a region considered important for pitch-based processing, and we have previously reported a functional correlation between relative pitch processing in the anterior intraparietal sulcus (IPS). We addressed the hypothesis that regional variation of cortical structure within AC and IPS is related to relative pitch ability using two anatomical techniques, cortical thickness (CT) analysis and voxel-based morphometry (VBM) of magnetic resonance imaging data. Persons with variable amounts of formal musical training were tested on a melody transposition task, as well as two musical control tasks and a speech control task. We found that gray matter concentration and cortical thickness in right Heschl's sulcus and bilateral IPS both predicted relative pitch task performance and correlated to a lesser extent with performance on the two musical control tasks. After factoring out variance explained by musical training, only relative pitch performance was predicted by cortical structure in these regions. These results directly demonstrate the functional relevance of previously reported anatomical differences in the auditory cortex of musicians. The findings in the IPS provide further support for the existence of a multimodal network for systematic transformation of stimulus information in this region. PMID:20600982

  13. ArchPRED: a template based loop structure prediction server.

    PubMed

    Fernandez-Fuentes, Narcis; Zhai, Jun; Fiser, András

    2006-07-01

    ArchPRED server (http://www.fiserlab.org/servers/archpred) implements a novel fragment-search based method for predicting loop conformations. The inputs to the server are the atomic coordinates of the query protein and the position of the loop. The algorithm selects candidate loop fragments from a regularly updated loop library (Search Space) by matching the length, the types of bracing secondary structures of the query and by satisfying the geometrical restraints imposed by the stem residues. Subsequently, candidate loops are inserted in the query protein framework where their side chains are rebuilt and their fit is assessed by the root mean square deviation (r.m.s.d.) of stem regions and by the number of rigid body clashes with the environment. In the final step remaining candidate loops are ranked by a Z-score that combines information on sequence similarity and fit of predicted and observed [/psi] main chain dihedral angle propensities. The final loop conformation is built in the protein structure and annealed in the environment using conjugate gradient minimization. The prediction method was benchmarked on artificially prepared search datasets where all trivial sequence similarities on the SCOP superfamily level were removed. Under these conditions it was possible to predict loops of length 4, 8 and 12 with coverage of 98, 78 and 28% with at least of 0.22, 1.38 and 2.47 A of r.m.s.d. accuracy, respectively. In a head to head comparison on loops extracted from freshly deposited new protein folds the current method outperformed in a approximately 5:1 ratio an earlier developed database search method. PMID:16844985

  14. Tailor-made force fields for crystal-structure prediction.

    PubMed

    Neumann, Marcus A

    2008-08-14

    A general procedure is presented to derive a complete set of force-field parameters for flexible molecules in the crystalline state on a case-by-case basis. The force-field parameters are fitted to the electrostatic potential as well as to accurate energies and forces generated by means of a hybrid method that combines solid-state density functional theory (DFT) calculations with an empirical van der Waals correction. All DFT calculations are carried out with the VASP program. The mathematical structure of the force field, the generation of reference data, the choice of the figure of merit, the optimization algorithm, and the parameter-refinement strategy are discussed in detail. The approach is applied to cyclohexane-1,4-dione, a small flexible ring. The tailor-made force field obtained for cyclohexane-1,4-dione is used to search for low-energy crystal packings in all 230 space groups with one molecule per asymmetric unit, and the most stable crystal structures are reoptimized in a second step with the hybrid method. The experimental crystal structure is found as the most stable predicted crystal structure both with the tailor-made force field and the hybrid method. The same methodology has also been applied successfully to the four compounds of the fourth CCDC blind test on crystal-structure prediction. For the five aforementioned compounds, the root-mean-square deviations between lattice energies calculated with the tailor-made force fields and the hybrid method range from 0.024 to 0.053 kcal/mol per atom around an average value of 0.034 kcal/mol per atom.

  15. Tailor-made force fields for crystal-structure prediction.

    PubMed

    Neumann, Marcus A

    2008-08-14

    A general procedure is presented to derive a complete set of force-field parameters for flexible molecules in the crystalline state on a case-by-case basis. The force-field parameters are fitted to the electrostatic potential as well as to accurate energies and forces generated by means of a hybrid method that combines solid-state density functional theory (DFT) calculations with an empirical van der Waals correction. All DFT calculations are carried out with the VASP program. The mathematical structure of the force field, the generation of reference data, the choice of the figure of merit, the optimization algorithm, and the parameter-refinement strategy are discussed in detail. The approach is applied to cyclohexane-1,4-dione, a small flexible ring. The tailor-made force field obtained for cyclohexane-1,4-dione is used to search for low-energy crystal packings in all 230 space groups with one molecule per asymmetric unit, and the most stable crystal structures are reoptimized in a second step with the hybrid method. The experimental crystal structure is found as the most stable predicted crystal structure both with the tailor-made force field and the hybrid method. The same methodology has also been applied successfully to the four compounds of the fourth CCDC blind test on crystal-structure prediction. For the five aforementioned compounds, the root-mean-square deviations between lattice energies calculated with the tailor-made force fields and the hybrid method range from 0.024 to 0.053 kcal/mol per atom around an average value of 0.034 kcal/mol per atom. PMID:18642947

  16. Predicting US Infants' and Toddlers' TV/Video Viewing Rates: Mothers' Cognitions and Structural Life Circumstances.

    PubMed

    Vaala, Sarah E; Hornik, Robert C

    2014-04-01

    There has been rising international concern over media use with children under two. As little is known about the factors associated with more or less viewing among very young children, this study examines maternal factors predictive of TV/video viewing rates among American infants and toddlers. Guided by the Integrative Model of Behavioral Prediction, this survey study examines relationships between children's rates of TV/video viewing and their mothers' structural life circumstances (e.g., number of children in the home; mother's screen use), and cognitions (e.g., attitudes; norms). Results suggest that mothers' structural circumstances and cognitions respectively contribute independent explanatory power to the prediction of children's TV/video viewing. Influence of structural circumstances is partially mediated through cognitions. Mothers' attitudes as well as their own TV/video viewing behavior were particularly predictive of children's viewing. Implications of these findings for international efforts to understand and reduce infant/toddler TV/video exposure are discussed. PMID:25489335

  17. Structural brain MRI trait polygenic score prediction of cognitive abilities

    PubMed Central

    Luciano, Michelle; Marioni, Riccardo E; Hernández, Maria Valdés; Maniega, Susana Munoz; Hamilton, Iona F; Royle, Natalie A.; Scotland, Generation; Chauhan, Ganesh; Bis, Joshua C.; Debette, Stephanie; DeCarli, Charles; Fornage, Myriam; Schmidt, Reinhold; Ikram, M. Arfan; Launer, Lenore J.; Seshadri, Sudha; Bastin, Mark E.; Porteous, David J.; Wardlaw, Joanna; Deary, Ian J

    2016-01-01

    Structural brain magnetic resonance imaging (MRI) traits share part of their genetic variance with cognitive traits. Here, we use genetic association results from large meta-analytic studies of genome-wide association for brain infarcts, white matter hyperintensities, intracranial, hippocampal and total brain volumes to estimate polygenic scores for these traits in three Scottish samples: Generation Scotland: Scottish Family Health Study (GS:SFHS), and the Lothian Birth Cohorts of 1936 (LBC1936) and 1921 (LBC1921). These five brain MRI trait polygenic scores were then used to 1) predict corresponding MRI traits in the LBC1936 (numbers ranged 573 to 630 across traits) and 2) predict cognitive traits in all three cohorts (in 8,115 to 8,250 persons). In the LBC1936, all MRI phenotypic traits were correlated with at least one cognitive measure; and polygenic prediction of MRI traits was observed for intracranial volume. Meta-analysis of the correlations between MRI polygenic scores and cognitive traits revealed a significant negative correlation (maximal r=0.08) between the hippocampal volume polygenic score and measures of global cognitive ability collected in childhood and in old age in the Lothian Birth Cohorts. The lack of association to a related general cognitive measure when including the GS:SFHS points to either type 1 error or the importance of using prediction samples that closely match the demographics of the genome-wide association samples from which prediction is based. Ideally, these analyses should be repeated in larger samples with data on both MRI and cognition, and using MRI GWA results from even larger meta-analysis studies. PMID:26427786

  18. Predicting the structure of the light-harvesting complex II of Rhodospirillum molischianum.

    PubMed Central

    Hu, X.; Xu, D.; Hamer, K.; Schulten, K.; Koepke, J.; Michel, H.

    1995-01-01

    We attempted to predict through computer modeling the structure of the light-harvesting complex II (LH-II) of Rhodospirillum molischianum, before the impending publication of the structure of a homologous protein solved by means of X-ray diffraction. The protein studied is an integral membrane protein of 16 independent polypeptides, 8 alpha-apoproteins and 8 beta-apoproteins, which aggregate and bind to 24 bacteriochlorophyll-a's and 12 lycopenes. Available diffraction data of a crystal of the protein, which could not be phased due to a lack of heavy metal derivatives, served to test the predicted structure, guiding the search. In order to determine the secondary structure, hydropathy analysis was performed to identify the putative transmembrane segments and multiple sequence alignment propensity analyses were used to pinpoint the exact sites of the 20-residue-long transmembrane segment and the 4-residue-long terminal sequence at both ends, which were independently verified and improved by homology modeling. A consensus assignment for the secondary structure was derived from a combination of all the prediction methods used. Three-dimensional structures for the alpha- and the beta-apoprotein were built by comparative modeling. The resulting tertiary structures are combined, using X-PLOR, into an alpha beta dimer pair with bacteriochlorophyll-a's attached under constraints provided by site-directed mutagenesis and spectral data. The alpha beta dimer pairs were then aggregated into a quaternary structure through further molecular dynamics simulations and energy minimization. The structure of LH-II so determined is an octamer of alpha beta heterodimers forming a ring with a diameter of 70 A. PMID:8528066

  19. Structure prediction and targeted synthesis: a new NanN2 diazenide crystalline structure

    SciTech Connect

    Zhang, Xiuwen; Zunger, Alex; Trimarchi, Giancarlo

    2010-01-01

    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-statestructures 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{sub n} N{sub 2} , manifesting homopolar N–N bonds. The previously predicted Na{sub 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{sub 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{sub 3} -type). The currently predicted (negative formation enthalpy) diazenide Na{sub 2} N{sub 2} completes the series of previously known BaN{sub 2} and SrN{sub 2} diazenides where the metal sublattice transfers charge into the empty N{sub 2} Π{sub 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{sub 2} N{sub 2} predicted here will be interesting.

  20. Integrating Mass Spectrometry of Intact Protein Complexes into Structural Proteomics

    PubMed Central

    Hyung, Suk-Joon; Ruotolo, Brandon T.

    2013-01-01

    Summary Mass spectrometry analysis of intact protein complexes has emerged as an established technology for assessing the composition and connectivity within dynamic, heterogeneous multiprotein complexes at low concentrations and in the context of mixtures. As this technology continues to move forward, one of the main challenges is to integrate the information content of such intact protein complex measurements with other mass spectrometry approaches in structural biology. Methods such as H/D exchange, oxidative foot-printing, chemical cross-linking, affinity purification, and ion mobility separation add complementary information that allows access to every level of protein structure and organization. Here, we survey the structural information that can be retrieved by such experiments, demonstrate the applicability of integrative mass spectrometry approaches in structural proteomics, and look to the future to explore upcoming innovations in this rapidly-advancing area. PMID:22611037

  1. Crack Turning and Arrest Mechanisms for Integral Structure

    NASA Technical Reports Server (NTRS)

    Pettit, Richard; Ingraffea, Anthony

    1999-01-01

    In the course of several years of research efforts to predict crack turning and flapping in aircraft fuselage structures and other problems related to crack turning, the 2nd order maximum tangential stress theory has been identified as the theory most capable of predicting the observed test results. This theory requires knowledge of a material specific characteristic length, and also a computation of the stress intensity factors and the T-stress, or second order term in the asymptotic stress field in the vicinity of the crack tip. A characteristic length, r(sub c), is proposed for ductile materials pertaining to the onset of plastic instability, as opposed to the void spacing theories espoused by previous investigators. For the plane stress case, an approximate estimate of r(sub c), is obtained from the asymptotic field for strain hardening materials given by Hutchinson, Rice and Rosengren (HRR). A previous study using of high order finite element methods to calculate T-stresses by contour integrals resulted in extremely high accuracy values obtained for selected test specimen geometries, and a theoretical error estimation parameter was defined. In the present study, it is shown that a large portion of the error in finite element computations of both K and T are systematic, and can be corrected after the initial solution if the finite element implementation utilizes a similar crack tip discretization scheme for all problems. This scheme is applied for two-dimensional problems to a both a p-version finite element code, showing that sufficiently accurate values of both K(sub I) and T can be obtained with fairly low order elements if correction is used. T-stress correction coefficients are also developed for the singular crack tip rosette utilized in the adaptive mesh finite element code FRANC2D, and shown to reduce the error in the computed T-stress significantly. Stress intensity factor correction was not attempted for FRANC2D because it employs a highly accurate

  2. Failure prediction of thin beryllium sheets used in spacecraft structures

    NASA Technical Reports Server (NTRS)

    Roschke, Paul N.; Papados, Photios; Mascorro, Edward

    1991-01-01

    In an attempt to predict failure for cross-rolled beryllium sheet structures, high order macroscopic failure criteria are used. These require the knowledge of in-plane uniaxial and shear strengths. Test results are included for in-plane biaxial tension, uniaxial compression for two different material orientations, and shear. All beryllium specimens have the same chemical composition. In addition, all experimental work was performed in a controlled laboratory environment. Numerical simulation complements these tests. A brief bibliography supplements references listed in a previous report.

  3. The sequential structure of brain activation predicts skill.

    PubMed

    Anderson, John R; Bothell, Daniel; Fincham, Jon M; Moon, Jungaa

    2016-01-29

    In an fMRI study, participants were trained to play a complex video game. They were scanned early and then again after substantial practice. While better players showed greater activation in one region (right dorsal striatum) their relative skill was better diagnosed by considering the sequential structure of whole brain activation. Using a cognitive model that played this game, we extracted a characterization of the mental states that are involved in playing a game and the statistical structure of the transitions among these states. There was a strong correspondence between this measure of sequential structure and the skill of different players. Using multi-voxel pattern analysis, it was possible to recognize, with relatively high accuracy, the cognitive states participants were in during particular scans. We used the sequential structure of these activation-recognized states to predict the skill of individual players. These findings indicate that important features about information-processing strategies can be identified from a model-based analysis of the sequential structure of brain activation. PMID:26707716

  4. Offspring social network structure predicts fitness in families

    PubMed Central

    Royle, Nick J.; Pike, Thomas W.; Heeb, Philipp; Richner, Heinz; Kölliker, Mathias

    2012-01-01

    Social structures such as families emerge as outcomes of behavioural interactions among individuals, and can evolve over time if families with particular types of social structures tend to leave more individuals in subsequent generations. The social behaviour of interacting individuals is typically analysed as a series of multiple dyadic (pair-wise) interactions, rather than a network of interactions among multiple individuals. However, in species where parents feed dependant young, interactions within families nearly always involve more than two individuals simultaneously. Such social networks of interactions at least partly reflect conflicts of interest over the provision of costly parental investment. Consequently, variation in family network structure reflects variation in how conflicts of interest are resolved among family members. Despite its importance in understanding the evolution of emergent properties of social organization such as family life and cooperation, nothing is currently known about how selection acts on the structure of social networks. Here, we show that the social network structure of broods of begging nestling great tits Parus major predicts fitness in families. Although selection at the level of the individual favours large nestlings, selection at the level of the kin-group primarily favours families that resolve conflicts most effectively. PMID:23097505

  5. Integrated control/structure optimization by multilevel decomposition

    NASA Technical Reports Server (NTRS)

    Zeiler, Thomas A.; Gilbert, Michael G.

    1990-01-01

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

  6. Modeling the Dependency Structure of Integrated Intensity Processes

    PubMed Central

    Ma, Yong-Ki

    2015-01-01

    This paper studies an important issue of dependence structure. To model this structure, the intensities within the Cox processes are driven by dependent shot noise processes, where jumps occur simultaneously and their sizes are correlated. The joint survival probability of the integrated intensities is explicitly obtained from the copula with exponential marginal distributions. Subsequently, this result can provide a very useful guide for credit risk management. PMID:26270638

  7. Integrated control/structure optimization by multilevel decomposition

    NASA Technical Reports Server (NTRS)

    Zeiler, Thomas A.; Gilbert, Michael G.

    1990-01-01

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

  8. 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 structurally sound for continued service. Recommendations are provided for continued monitoring of the Calcined Solids Storage Facilities.

  9. Novel semantic similarity measure improves an integrative approach to predicting gene functional associations

    PubMed Central

    2013-01-01

    Background Elucidation of the direct/indirect protein interactions and gene associations is required to fully understand the workings of the cell. This can be achieved through the use of both low- and high-throughput biological experiments and in silico methods. We present GAP (Gene functional Association Predictor), an integrative method for predicting and characterizing gene functional associations. GAP integrates different biological features using a novel taxonomy-based semantic similarity measure in predicting and prioritizing high-quality putative gene associations. The proposed similarity measure increases information gain from the available gene annotations. The annotation information is incorporated from several public pathway databases, Gene Ontology annotations as well as drug and disease associations from the scientific literature. Results We evaluated GAP by comparing its prediction performance with several other well-known functional interaction prediction tools over a comprehensive dataset of known direct and indirect interactions, and observed significantly better prediction performance. We also selected a small set of GAP’s highly-scored novel predicted pairs (i.e., currently not found in any known database or dataset), and by manually searching the literature for experimental evidence accessible in the public domain, we confirmed different categories of predicted functional associations with available evidence of interaction. We also provided extra supporting evidence for subset of the predicted functionally-associated pairs using an expert curated database of genes associated to autism spectrum disorders. Conclusions GAP’s predicted “functional interactome” contains ≈1M highly-scored predicted functional associations out of which about 90% are novel (i.e., not experimentally validated). GAP’s novel predictions connect disconnected components and singletons to the main connected component of the known interactome. It can, therefore, be

  10. Integrated structural and optical modeling of the orbiting stellar interferometer

    NASA Astrophysics Data System (ADS)

    Shaklan, Stuart B.; Yu, Jeffrey W.; Briggs, Hugh C.

    1993-11-01

    The Integrated Modeling of Optical Systems (IMOS) Integration Workbench at JPL has been used to model the effects of structural perturbations on the optics in the proposed Orbiting Stellar Interferometer (OSI). OSI consists of 3 pairs of interferometers and delay lines attached to a 7.5 meter truss. They are interferometrically monitored from a separate boom by a laser metrology system. The spatially distributed nature of the science instrument calls for a high level of integration between the optics and support structure. Because OSI is designed to achieve micro-arcsecond astrometry, many of its alignment, stability, and knowledge tolerances are in the submicron regime. The spacecraft will be subject to vibrations caused by reaction wheels and on-board equipment, as well as thermal strain due to solar and terrestrial heating. These perturbations affect optical parameters such as optical path differences and beam co-parallelism which are critical to instrument performance. IMOS provides an environment that allows one to design and perturb the structure, attach optics to structural or non-structural nodes, trace rays, and analyze the impact of mechanical perturbations on optical performance. This tool makes it simple to change the structure and immediately see performance enhancement/degradation. We have employed IMOS to analyze the effect of reaction wheel disturbances on the optical path difference in both the science and metrology interferometers.

  11. Predicting fracture in micron-scale polycrystalline silicon MEMS structures.

    SciTech Connect

    Hazra, Siddharth S.; de Boer, Maarten Pieter; Boyce, Brad Lee; Ohlhausen, James Anthony; Foulk, James W., III; Reedy, Earl David, Jr.

    2010-09-01

    Designing reliable MEMS structures presents numerous challenges. Polycrystalline silicon fractures in a brittle manner with considerable variability in measured strength. Furthermore, it is not clear how to use a measured tensile strength distribution to predict the strength of a complex MEMS structure. To address such issues, two recently developed high throughput MEMS tensile test techniques have been used to measure strength distribution tails. The measured tensile strength distributions enable the definition of a threshold strength as well as an inferred maximum flaw size. The nature of strength-controlling flaws has been identified and sources of the observed variation in strength investigated. A double edge-notched specimen geometry was also tested to study the effect of a severe, micron-scale stress concentration on the measured strength distribution. Strength-based, Weibull-based, and fracture mechanics-based failure analyses were performed and compared with the experimental results.

  12. Methods for evaluating the predictive accuracy of structural dynamic models

    NASA Technical Reports Server (NTRS)

    Hasselman, T. K.; Chrostowski, Jon D.

    1990-01-01

    Uncertainty of frequency response using the fuzzy set method and on-orbit response prediction using laboratory test data to refine an analytical model are emphasized with respect to large space structures. Two aspects of the fuzzy set approach were investigated relative to its application to large structural dynamics problems: (1) minimizing the number of parameters involved in computing possible intervals; and (2) the treatment of extrema which may occur in the parameter space enclosed by all possible combinations of the important parameters of the model. Extensive printer graphics were added to the SSID code to help facilitate model verification, and an application of this code to the LaRC Ten Bay Truss is included in the appendix to illustrate this graphics capability.

  13. Prediction of Halocarbon Toxicity from Structure: A Hierarchical QSAR Approach

    SciTech Connect

    Gute, B D; Balasubramanian, K; Geiss, K; Basak, S C

    2003-04-11

    Mathematical structural invariants and quantum theoretical descriptors have been used extensively in quantitative structure-activity relationships (QSARs) for the estimation of pharmaceutical activities, biological properties, physicochemical properties, and the toxicities of chemicals. Recently our research team has explored the relative importance of various levels of chemodescriptors, i.e., topostructural, topochemical, geometrical, and quantum theoretical descriptors, in property estimation. This study examines the contribution of chemodescriptors ranging from topostructural to quantum theoretic calculations up to the Gaussian STO-3G level in the prediction of the toxicity of a set of twenty halocarbons. We also report the results of experimental cell-level toxicity studies on these twenty halocarbons to validate our models.

  14. Factors Influencing Progressive Failure Analysis Predictions for Laminated Composite Structure

    NASA Technical Reports Server (NTRS)

    Knight, Norman F., Jr.

    2008-01-01

    Progressive failure material modeling methods used for structural analysis including failure initiation and material degradation are presented. Different failure initiation criteria and material degradation models are described that define progressive failure formulations. These progressive failure formulations are implemented in a user-defined material model for use with a nonlinear finite element analysis tool. The failure initiation criteria include the maximum stress criteria, maximum strain criteria, the Tsai-Wu failure polynomial, and the Hashin criteria. The material degradation model is based on the ply-discounting approach where the local material constitutive coefficients are degraded. Applications and extensions of the progressive failure analysis material model address two-dimensional plate and shell finite elements and three-dimensional solid finite elements. Implementation details are described in the present paper. Parametric studies for laminated composite structures are discussed to illustrate the features of the progressive failure modeling methods that have been implemented and to demonstrate their influence on progressive failure analysis predictions.

  15. Development of Probabilistic Structural Analysis Integrated with Manufacturing Processes

    NASA Technical Reports Server (NTRS)

    Pai, Shantaram S.; Nagpal, Vinod K.

    2007-01-01

    An effort has been initiated to integrate manufacturing process simulations with probabilistic structural analyses in order to capture the important impacts of manufacturing uncertainties on component stress levels and life. Two physics-based manufacturing process models (one for powdered metal forging and the other for annular deformation resistance welding) have been linked to the NESSUS structural analysis code. This paper describes the methodology developed to perform this integration including several examples. Although this effort is still underway, particularly for full integration of a probabilistic analysis, the progress to date has been encouraging and a software interface that implements the methodology has been developed. The purpose of this paper is to report this preliminary development.

  16. Integrated Modeling Activities for the James Webb Space Telescope (JWST): Structural-Thermal-Optical Analysis

    NASA Technical Reports Server (NTRS)

    Johnston, John D.; Parrish, Keith; Howard, Joseph M.; Mosier, Gary E.; McGinnis, Mark; Bluth, Marcel; Kim, Kevin; Ha, Hong Q.

    2004-01-01

    This is a continuation of a series of papers on modeling activities for JWST. The structural-thermal- optical, often referred to as "STOP", analysis process is used to predict the effect of thermal distortion on optical performance. The benchmark STOP analysis for JWST assesses the effect of an observatory slew on wavefront error. The paper begins an overview of multi-disciplinary engineering analysis, or integrated modeling, which is a critical element of the JWST mission. The STOP analysis process is then described. This process consists of the following steps: thermal analysis, structural analysis, and optical analysis. Temperatures predicted using geometric and thermal math models are mapped to the structural finite element model in order to predict thermally-induced deformations. Motions and deformations at optical surfaces are input to optical models and optical performance is predicted using either an optical ray trace or WFE estimation techniques based on prior ray traces or first order optics. Following the discussion of the analysis process, results based on models representing the design at the time of the System Requirements Review. In addition to baseline performance predictions, sensitivity studies are performed to assess modeling uncertainties. Of particular interest is the sensitivity of optical performance to uncertainties in temperature predictions and variations in metal properties. The paper concludes with a discussion of modeling uncertainty as it pertains to STOP analysis.

  17. STRUCTURAL INTEGRITY MONITORING FOR IMPROVED DRINKING WATER INFRASTRUCTURE SUSTAINABILITY

    EPA Science Inventory

    Structural integrity monitoring (SIM) is the systematic detection, location, and quantification of pipe wall damage or associated indicators. Each of the adverse situations below has the potential to be reduced by more effective and economical SIM of water mains:
    1) the dr...

  18. Integration of fluidic jet actuators in composite structures

    NASA Astrophysics Data System (ADS)

    Schueller, Martin; Lipowski, Mathias; Schirmer, Eckart; Walther, Marco; Otto, Thomas; Geßner, Thomas; Kroll, Lothar

    2015-04-01

    Fluidic Actuated Flow Control (FAFC) has been introduced as a technology that influences the boundary layer by actively blowing air through slots or holes in the aircraft skin or wind turbine rotor blade. Modern wing structures are or will be manufactured using composite materials. In these state of the art systems, AFC actuators are integrated in a hybrid approach. The new idea is to directly integrate the active fluidic elements (such as SJAs and PJAs) and their components in the structure of the airfoil. Consequently, the integration of such fluidic devices must fit the manufacturing process and the material properties of the composite structure. The challenge is to integrate temperature-sensitive active elements and to realize fluidic cavities at the same time. The transducer elements will be provided for the manufacturing steps using roll-to-roll processes. The fluidic parts of the actuators will be manufactured using the MuCell® process that provides on the one hand the defined reproduction of the fluidic structures and, on the other hand, a high light weight index. Based on the first design concept, a demonstrator was developed in order to proof the design approach. The output velocity on the exit was measured using a hot-wire anemometer.

  19. Structured Set Intra Prediction With Discriminative Learning in a Max-Margin Markov Network for High Efficiency Video Coding

    PubMed Central

    Dai, Wenrui; Xiong, Hongkai; Jiang, Xiaoqian; Chen, Chang Wen

    2014-01-01

    This paper proposes a novel model on intra coding for High Efficiency Video Coding (HEVC), which simultaneously predicts blocks of pixels with optimal rate distortion. It utilizes the spatial statistical correlation for the optimal prediction based on 2-D contexts, in addition to formulating the data-driven structural interdependences to make the prediction error coherent with the probability distribution, which is desirable for successful transform and coding. The structured set prediction model incorporates a max-margin Markov network (M3N) to regulate and optimize multiple block predictions. The model parameters are learned by discriminating the actual pixel value from other possible estimates to maximize the margin (i.e., decision boundary bandwidth). Compared to existing methods that focus on minimizing prediction error, the M3N-based model adaptively maintains the coherence for a set of predictions. Specifically, the proposed model concurrently optimizes a set of predictions by associating the loss for individual blocks to the joint distribution of succeeding discrete cosine transform coefficients. When the sample size grows, the prediction error is asymptotically upper bounded by the training error under the decomposable loss function. As an internal step, we optimize the underlying Markov network structure to find states that achieve the maximal energy using expectation propagation. For validation, we integrate the proposed model into HEVC for optimal mode selection on rate-distortion optimization. The proposed prediction model obtains up to 2.85% bit rate reduction and achieves better visual quality in comparison to the HEVC intra coding. PMID:25505829

  20. Generic eukaryotic core promoter prediction using structural features of DNA.

    PubMed

    Abeel, Thomas; Saeys, Yvan; Bonnet, Eric; Rouzé, Pierre; Van de Peer, Yves

    2008-02-01

    Despite many recent efforts, in silico identification of promoter regions is still in its infancy. However, the accurate identification and delineation of promoter regions is important for several reasons, such as improving genome annotation and devising experiments to study and understand transcriptional regulation. Current methods to identify the core region of promoters require large amounts of high-quality training data and often behave like black box models that output predictions that are difficult to interpret. Here, we present a novel approach for predicting promoters in whole-genome sequences by using large-scale structural properties of DNA. Our technique requires no training, is applicable to many eukaryotic genomes, and performs extremely well in comparison with the best available promoter prediction programs. Moreover, it is fast, simple in design, and has no size constraints, and the results are easily interpretable. We compared our approach with 14 current state-of-the-art implementations using human gene and transcription start site data and analyzed the ENCODE region in more detail. We also validated our method on 12 additional eukaryotic genomes, including vertebrates, invertebrates, plants, fungi, and protists.

  1. Drug-target interaction prediction by integrating chemical, genomic, functional and pharmacological data.

    PubMed

    Yang, Fan; Xu, Jinbo; Zeng, Jianyang

    2014-01-01

    In silico prediction of unknown drug-target interactions (DTIs) has become a popular tool for drug repositioning and drug development. A key challenge in DTI prediction lies in integrating multiple types of data for accurate DTI prediction. Although recent studies have demonstrated that genomic, chemical and pharmacological data can provide reliable information for DTI prediction, it remains unclear whether functional information on proteins can also contribute to this task. Little work has been developed to combine such information with other data to identify new interactions between drugs and targets. In this paper, we introduce functional data into DTI prediction and construct biological space for targets using the functional similarity measure. We present a probabilistic graphical model, called conditional random field (CRF), to systematically integrate genomic, chemical, functional and pharmacological data plus the topology of DTI networks into a unified framework to predict missing DTIs. Tests on two benchmark datasets show that our method can achieve excellent prediction performance with the area under the precision-recall curve (AUPR) up to 94.9. These results demonstrate that our CRF model can successfully exploit heterogeneous data to capture the latent correlations of DTIs, and thus will be practically useful for drug repositioning. Supplementary Material is available at http://iiis.tsinghua.edu.cn/~compbio/papers/psb2014/psb2014_sm.pdf. PMID:24297542

  2. The application study on the multi-scales integrated prediction method to fractured reservoir description

    NASA Astrophysics Data System (ADS)

    Chen, Shuang-Quan; Zeng, Lian-Bo; Huang, Ping; Sun, Shao-Han; Zhang, Wan-Lu; Li, Xiang-Yang

    2016-03-01

    In this paper, we implement three scales of fracture integrated prediction study by classifying it to macro- (> 1/4 λ), meso- (> 1/100 λ and < 1/4 λ) and micro- (< 1/100 λ) scales. Based on the multi-scales rock physics modelling technique, the seismic azimuthal anisotropy characteristic is analyzed for distinguishing the fractures of meso-scale. Furthermore, by integrating geological core fracture description, image well-logging fracture interpretation, seismic attributes macro-scale fracture prediction and core slice micro-scale fracture characterization, an comprehensive multi-scale fracture prediction methodology and technique workflow are proposed by using geology, well-logging and seismic multi-attributes. Firstly, utilizing the geology core slice observation (Fractures description) and image well-logging data interpretation results, the main governing factors of fracture development are obtained, and then the control factors of the development of regional macro-scale fractures are carried out via modelling of the tectonic stress field. For the meso-scale fracture description, the poststack geometric attributes are used to describe the macro-scale fracture as well, the prestack attenuation seismic attribute is used to predict the meso-scale fracture. Finally, by combining lithological statistic inversion with superposed results of faults, the relationship of the meso-scale fractures, lithology and faults can be reasonably interpreted and the cause of meso-scale fractures can be verified. The micro-scale fracture description is mainly implemented by using the electron microscope scanning of cores. Therefore, the development of fractures in reservoirs is assessed by valuating three classes of fracture prediction results. An integrated fracture prediction application to a real field in Sichuan basin, where limestone reservoir fractures developed, is implemented. The application results in the study area indicates that the proposed multi-scales integrated

  3. Statistical Potentials for Hairpin and Internal Loops Improve the Accuracy of the Predicted RNA Structure

    PubMed Central

    Gardner, David P.; Ren, Pengyu; Ozer, Stuart; Gutell, Robin R.

    2011-01-01

    RNA is directly associated with a growing number of functions within the cell. The accurate prediction of different RNAs higher-order structure from their nucleic acid sequences will provide insight into their functions and molecular mechanics. We have been determining statistical potentials for a collection of structural elements that is larger than the number of structural elements determined with experimentally determined energy values. The experimentally derived free-energies and the statistical potentials for canonical base pair stacks are analogous, demonstrating that statistical potentials derived from comparative data can be used as an alternative energetic parameter. A new computational infrastructure - RNA Comparative Analysis Database (rCAD) - that utilizes a relational database was developed to manipulate and analyze very large sequence alignments and secondary structure datasets. Using rCAD, a richer set of energetic parameters for RNA fundamental structural elements including hairpin and internal loops was determined. A new version of RNAfold was developed to utilize these statistical potentials. Overall, these new statistical potentials for hairpin and internal loops integrated into the new version of RNAfold demonstrated significant improvements in the prediction accuracy of RNA secondary structure. PMID:21889515

  4. Evaluation of the information content of RNA structure mapping data for secondary structure prediction.

    PubMed

    Quarrier, Scott; Martin, Joshua S; Davis-Neulander, Lauren; Beauregard, Arthur; Laederach, Alain

    2010-06-01

    Structure mapping experiments (using probes such as dimethyl sulfate [DMS], kethoxal, and T1 and V1 RNases) are used to determine the secondary structures of RNA molecules. The process is iterative, combining the results of several probes with constrained minimum free-energy calculations to produce a model of the structure. We aim to evaluate whether particular probes provide more structural information, and specifically, how noise in the data affects the predictions. Our approach involves generating "decoy" RNA structures (using the sFold Boltzmann sampling procedure) and evaluating whether we are able to identify the correct structure from this ensemble of structures. We show that with perfect information, we are always able to identify the optimal structure for five RNAs of known structure. We then collected orthogonal structure mapping data (DMS and RNase T1 digest) under several solution conditions using our high-throughput capillary automated footprinting analysis (CAFA) technique on two group I introns of known structure. Analysis of these data reveals the error rates in the data under optimal (low salt) and suboptimal solution conditions (high MgCl(2)). We show that despite these errors, our computational approach is less sensitive to experimental noise than traditional constraint-based structure prediction algorithms. Finally, we propose a novel approach for visualizing the interaction of chemical and enzymatic mapping data with RNA structure. We project the data onto the first two dimensions of a multidimensional scaling of the sFold-generated decoy structures. We are able to directly visualize the structural information content of structure mapping data and reconcile multiple data sets.

  5. Evaluation of the information content of RNA structure mapping data for secondary structure prediction.

    PubMed

    Quarrier, Scott; Martin, Joshua S; Davis-Neulander, Lauren; Beauregard, Arthur; Laederach, Alain

    2010-06-01

    Structure mapping experiments (using probes such as dimethyl sulfate [DMS], kethoxal, and T1 and V1 RNases) are used to determine the secondary structures of RNA molecules. The process is iterative, combining the results of several probes with constrained minimum free-energy calculations to produce a model of the structure. We aim to evaluate whether particular probes provide more structural information, and specifically, how noise in the data affects the predictions. Our approach involves generating "decoy" RNA structures (using the sFold Boltzmann sampling procedure) and evaluating whether we are able to identify the correct structure from this ensemble of structures. We show that with perfect information, we are always able to identify the optimal structure for five RNAs of known structure. We then collected orthogonal structure mapping data (DMS and RNase T1 digest) under several solution conditions using our high-throughput capillary automated footprinting analysis (CAFA) technique on two group I introns of known structure. Analysis of these data reveals the error rates in the data under optimal (low salt) and suboptimal solution conditions (high MgCl(2)). We show that despite these errors, our computational approach is less sensitive to experimental noise than traditional constraint-based structure prediction algorithms. Finally, we propose a novel approach for visualizing the interaction of chemical and enzymatic mapping data with RNA structure. We project the data onto the first two dimensions of a multidimensional scaling of the sFold-generated decoy structures. We are able to directly visualize the structural information content of structure mapping data and reconcile multiple data sets. PMID:20413617

  6. RNAalifold: improved consensus structure prediction for RNA alignments

    PubMed Central

    Bernhart, Stephan H; Hofacker, Ivo L; Will, Sebastian; Gruber, Andreas R; Stadler, Peter F

    2008-01-01

    Background The prediction of a consensus structure for a set of related RNAs is an important first step for subsequent analyses. RNAalifold, which computes the minimum energy structure that is simultaneously formed by a set of aligned sequences, is one of the oldest and most widely used tools for this task. In recent years, several alternative approaches have been advocated, pointing to several shortcomings of the original RNAalifold approach. Results We show that the accuracy of RNAalifold predictions can be improved substantially by introducing a different, more rational handling of alignment gaps, and by replacing the rather simplistic model of covariance scoring with more sophisticated RIBOSUM-like scoring matrices. These improvements are achieved without compromising the computational efficiency of the algorithm. We show here that the new version of RNAalifold not only outperforms the old one, but also several other tools recently developed, on different datasets. Conclusion The new version of RNAalifold not only can replace the old one for almost any application but it is also competitive with other approaches including those based on SCFGs, maximum expected accuracy, or hierarchical nearest neighbor classifiers. PMID:19014431

  7. Structure-Based Predictive model for Coal Char Combustion.

    SciTech Connect

    Hurt, R.; Colo, J; Essenhigh, R.; Hadad, C; Stanley, E.

    1997-09-24

    During the third quarter of this project, progress was made on both major technical tasks. Progress was made in the chemistry department at OSU on the calculation of thermodynamic properties for a number of model organic compounds. Modelling work was carried out at Brown to adapt a thermodynamic model of carbonaceous mesophase formation, originally applied to pitch carbonization, to the prediction of coke texture in coal combustion. This latter work makes use of the FG-DVC model of coal pyrolysis developed by Advanced Fuel Research to specify the pool of aromatic clusters that participate in the order/disorder transition. This modelling approach shows promise for the mechanistic prediction of the rank dependence of char structure and will therefore be pursued further. Crystalline ordering phenomena were also observed in a model char prepared from phenol-formaldehyde carbonized at 900{degrees}C and 1300{degrees}C using high-resolution TEM fringe imaging. Dramatic changes occur in the structure between 900 and 1300{degrees}C, making this char a suitable candidate for upcoming in situ work on the hot stage TEM. Work also proceeded on molecular dynamics simulations at Boston University and on equipment modification and testing for the combustion experiments with widely varying flame types at Ohio State.

  8. Comparison of SWAT Predictions with Stream Biological Integrity Observations in an Agricultural Watershed

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The SWAT model is calibrated with USGS data for an agricultural watershed located on the Eastern Shore of Maryland. Model predictions of runoff, sediment, nitrogen and phosphorus amounts, at the outlet of sub-watersheds, are compared to measurements of stream biological integrity conducted throughou...

  9. Predicting carbon dynamics in integrated production systems in Brazil using the CQESTR model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Process-based carbon models are research tools to predict management impact on soil organic carbon (SOC) and options to increase SOC stocks and reduce CO2. The CQESTR model was used to examine the effect of soil management practices, including integrated crop-livestock system (iCLS), and various sc...

  10. Dopamine Neurons, Input Integration, and Reward Prediction Errors: E Pluribus Unum.

    PubMed

    Floresco, Stan B

    2016-09-21

    Dopamine neurons encode errors in reward prediction, yet understanding how they integrate information from different subcortical inputs to generate these signals has remained elusive. In this issue of Neuron, Tian et al. (2016) shed new light onto these underlying mechanisms. PMID:27657447

  11. Diagnostic, Predictive and Compositional Modeling with Data Mining in Integrated Learning Environments

    ERIC Educational Resources Information Center

    Lee, Chien-Sing

    2007-01-01

    Models represent a set of generic patterns to test hypotheses. This paper presents the CogMoLab student model in the context of an integrated learning environment. Three aspects are discussed: diagnostic and predictive modeling with respect to the issues of credit assignment and scalability and compositional modeling of the student profile in the…

  12. IN SILICO METHODOLOGIES FOR PREDICTIVE EVALUATION OF TOXICITY BASED ON INTEGRATION OF DATABASES

    EPA Science Inventory

    In silico methodologies for predictive evaluation of toxicity based on integration of databases

    Chihae Yang1 and Ann M. Richard2, 1LeadScope, Inc. 1245 Kinnear Rd. Columbus, OH. 43212 2National Health & Environmental Effects Research Lab, U.S. EPA, Research Triangle Park, ...

  13. Predicting Examination Performance Using an Expanded Integrated Hierarchical Model of Test Emotions and Achievement Goals

    ERIC Educational Resources Information Center

    Putwain, Dave; Deveney, Carolyn

    2009-01-01

    The aim of this study was to examine an expanded integrative hierarchical model of test emotions and achievement goal orientations in predicting the examination performance of undergraduate students. Achievement goals were theorised as mediating the relationship between test emotions and performance. 120 undergraduate students completed…

  14. COMPUTING THERAPY FOR PRECISION MEDICINE: COLLABORATIVE FILTERING INTEGRATES AND PREDICTS MULTI-ENTITY INTERACTIONS

    PubMed Central

    REGENBOGEN, SAM; WILKINS, ANGELA D.; LICHTARGE, OLIVIER

    2015-01-01

    Biomedicine produces copious information it cannot fully exploit. Specifically, there is considerable need to integrate knowledge from disparate studies to discover connections across domains. Here, we used a Collaborative Filtering approach, inspired by online recommendation algorithms, in which non-negative matrix factorization (NMF) predicts interactions among chemicals, genes, and diseases only from pairwise information about their interactions. Our approach, applied to matrices derived from the Comparative Toxicogenomics Database, successfully recovered Chemical-Disease, Chemical-Gene, and Disease-Gene networks in 10-fold cross-validation experiments. Additionally, we could predict each of these interaction matrices from the other two. Integrating all three CTD interaction matrices with NMF led to good predictions of STRING, an independent, external network of protein-protein interactions. Finally, this approach could integrate the CTD and STRING interaction data to improve Chemical-Gene cross-validation performance significantly, and, in a time-stamped study, it predicted information added to CTD after a given date, using only data prior to that date. We conclude that collaborative filtering can integrate information across multiple types of biological entities, and that as a first step towards precision medicine it can compute drug repurposing hypotheses. PMID:26776170

  15. Integrated Controls-Structures Design Methodology: Redesign of an Evolutionary Test Structure

    NASA Technical Reports Server (NTRS)

    Maghami, Peiman G.; Gupta, Sandeep; Elliot, Kenny B.; Joshi, Suresh M.

    1997-01-01

    An optimization-based integrated controls-structures design methodology for a class of flexible space structures is described, and the phase-0 Controls-Structures-Integration evolutionary model, a laboratory testbed at NASA Langley, is redesigned using this integrated design methodology. The integrated controls-structures design is posed as a nonlinear programming problem to minimize the control effort required to maintain a specified line-of-sight pointing performance, under persistent white noise disturbance. Static and dynamic dissipative control strategies are employed for feedback control, and parameters of these controllers are considered as the control design variables. Sizes of strut elements in various sections of the CEM are used as the structural design variables. Design guides for the struts are developed and employed in the integrated design process, to ensure that the redesigned structure can be effectively fabricated. The superiority of the integrated design methodology over the conventional design approach is demonstrated analytically by observing a significant reduction in the average control power needed to maintain specified pointing performance with the integrated design approach.

  16. RNA tertiary structure prediction with ModeRNA.

    PubMed

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

    2011-11-01

    Noncoding RNAs perform important roles in the cell. As their function is tightly connected with structure, and as experimental methods are time-consuming and expensive, the field of RNA structure prediction is developing rapidly. Here, we present a detailed study on using the ModeRNA software. The tool uses the comparative modeling approach and can be applied when a structural template is available and an alignment of reasonable quality can be performed. We guide the reader through the entire process of modeling Escherichia coli tRNA(Thr) in a conformation corresponding to the complex with an aminoacyl-tRNA synthetase (aaRS). We describe the choice of a template structure, preparation of input files, and explore three possible modeling strategies. In the end, we evaluate the resulting models using six alternative benchmarks. The ModeRNA software can be freely downloaded from http://iimcb.genesilico.pl/moderna/ under the conditions of the General Public License. It runs under LINUX, Windows and Mac OS. It is also available as a server at http://iimcb.genesilico.pl/modernaserver/. The models and the script to reproduce the study from this article are available at http://www.genesilico.pl/moderna/examples/.

  17. Protein structure prediction with local adjust tabu search algorithm

    PubMed Central

    2014-01-01

    Background Protein folding structure prediction is one of the most challenging problems in the bioinformatics domain. Because of the complexity of the realistic protein structure, the simplified structure model and the computational method should be adopted in the research. The AB off-lattice model is one of the simplification models, which only considers two classes of amino acids, hydrophobic (A) residues and hydrophilic (B) residues. Results The main work of this paper is to discuss how to optimize the lowest energy configurations in 2D off-lattice model and 3D off-lattice model by using Fibonacci sequences and real protein sequences. In order to avoid falling into local minimum and faster convergence to the global minimum, we introduce a novel method (SATS) to the protein structure problem, which combines simulated annealing algorithm and tabu search algorithm. Various strategies, such as the new encoding strategy, the adaptive neighborhood generation strategy and the local adjustment strategy, are adopted successfully for high-speed searching the optimal conformation corresponds to the lowest energy of the protein sequences. Experimental results show that some of the results obtained by the improved SATS are better than those reported in previous literatures, and we can sure that the lowest energy folding state for short Fibonacci sequences have been found. Conclusions Although the off-lattice models is not very realistic, they can reflect some important characteristics of the realistic protein. It can be found that 3D off-lattice model is more like native folding structure of the realistic protein than 2D off-lattice model. In addition, compared with some previous researches, the proposed hybrid algorithm can more effectively and more quickly search the spatial folding structure of a protein chain. PMID:25474708

  18. Crystal structure prediction from first principles: The crystal structures of glycine

    NASA Astrophysics Data System (ADS)

    Lund, Albert M.; Pagola, Gabriel I.; Orendt, Anita M.; Ferraro, Marta B.; Facelli, Julio C.

    2015-04-01

    Here we present the results of our unbiased searches of glycine polymorphs obtained using the genetic algorithms search implemented in MGAC, modified genetic algorithm for crystals, coupled with the local optimization and energy evaluation provided by Quantum Espresso. We demonstrate that it is possible to predict the crystal structures of a biomedical molecule using solely first principles calculations. We were able to find all the ambient pressure stable glycine polymorphs, which are found in the same energetic ordering as observed experimentally and the agreement between the experimental and predicted structures is of such accuracy that the two are visually almost indistinguishable.

  19. Crystal Structure Prediction from First Principles: The Crystal Structures of Glycine

    PubMed Central

    Lund, Albert M.; Pagola, Gabriel I.; Orendt, Anita M.; Ferraro, Marta B.; Facelli, Julio C.

    2015-01-01

    Here we present the results of our unbiased searches of glycine polymorphs obtained using the Genetic Algorithms search implemented in Modified Genetic Algorithm for Crystals coupled with the local optimization and energy evaluation provided by Quantum Espresso. We demonstrate that it is possible to predict the crystal structures of a biomedical molecule using solely first principles calculations. We were able to find all the ambient pressure stable glycine polymorphs, which are found in the same energetic ordering as observed experimentally and the agreement between the experimental and predicted structures is of such accuracy that the two are visually almost indistinguishable. PMID:25843964

  20. Improving the Effectiveness of Integral Property Calculation in a CSG Solid Modeling System by Exploiting Predictability

    NASA Technical Reports Server (NTRS)

    Clark, A. L.

    1985-01-01

    Integral property calculation is an important application for solid modeling systems. Algorithms for computing integral properties for various solid representation schemes are fairly well known. It is important to deigners and users of solid modeling systems to understand the behavior of such algorithms. Specifically the trade-off between execution time and accuracy is critical to effective use of integral property calculation. The average behavior of two algorithms for Constructive Solid Geometry (CSG) representations is investigated. Experimental results from the PADL-2 solid modeling system show that coarse decompositions can be used to predict execution time and error estimates for finer decompositions. Exploiting this predictability allow effective use of the algorithms in a solid modeling system.

  1. Subtask 2.4 - Integration and Synthesis in Climate Change Predictive Modeling

    SciTech Connect

    Jaroslav Solc

    2009-06-01

    The Energy & Environmental Research Center (EERC) completed a brief evaluation of the existing status of predictive modeling to assess options for integration of our previous paleohydrologic reconstructions and their synthesis with current global climate scenarios. Results of our research indicate that short-term data series available from modern instrumental records are not sufficient to reconstruct past hydrologic events or predict future ones. On the contrary, reconstruction of paleoclimate phenomena provided credible information on past climate cycles and confirmed their integration in the context of regional climate history is possible. Similarly to ice cores and other paleo proxies, acquired data represent an objective, credible tool for model calibration and validation of currently observed trends. It remains a subject of future research whether further refinement of our results and synthesis with regional and global climate observations could contribute to improvement and credibility of climate predictions on a regional and global scale.

  2. How evolutionary crystal structure prediction works--and why.

    PubMed

    Oganov, Artem R; Lyakhov, Andriy O; Valle, Mario

    2011-03-15

    Once the crystal structure of a chemical substance is known, many properties can be predicted reliably and routinely. Therefore if researchers could predict the crystal structure of a material before it is synthesized, they could significantly accelerate the discovery of new materials. In addition, the ability to predict crystal structures at arbitrary conditions of pressure and temperature is invaluable for the study of matter at extreme conditions, where experiments are difficult. Crystal structure prediction (CSP), the problem of finding the most stable arrangement of atoms given only the chemical composition, has long remained a major unsolved scientific problem. Two problems are entangled here: search, the efficient exploration of the multidimensional energy landscape, and ranking, the correct calculation of relative energies. For organic crystals, which contain a few molecules in the unit cell, search can be quite simple as long as a researcher does not need to include many possible isomers or conformations of the molecules; therefore ranking becomes the main challenge. For inorganic crystals, quantum mechanical methods often provide correct relative energies, making search the most critical problem. Recent developments provide useful practical methods for solving the search problem to a considerable extent. One can use simulated annealing, metadynamics, random sampling, basin hopping, minima hopping, and data mining. Genetic algorithms have been applied to crystals since 1995, but with limited success, which necessitated the development of a very different evolutionary algorithm. This Account reviews CSP using one of the major techniques, the hybrid evolutionary algorithm USPEX (Universal Structure Predictor: Evolutionary Xtallography). Using recent developments in the theory of energy landscapes, we unravel the reasons evolutionary techniques work for CSP and point out their limitations. We demonstrate that the energy landscapes of chemical systems have an

  3. Hypersonic vehicle structural weight prediction using parametric modeling, finite element modeling, and structural optimization

    NASA Astrophysics Data System (ADS)

    Ngo, Dung A.; Koshiba, David A.; Moses, Paul L.

    1993-04-01

    Detailed structural analysis/optimization is required in the conceptual design stage because of the combination of aerodynamic and aerothermodynamic environment. This is a time and manpower consuming activity which is exasperated by constant vehicle moldline changes as a configuration matures. A simple parametric math model is presented that takes into consideration static loads and the geometry and structural weight of a baseline hypersonic vehicle in predicting the structural weight of a new configuration scaled from the baseline. The approach in developing the math model was to consider a generic parametric cross-sectional geometry that could be used to approximate the baseline geometry and to predict the behavior of this baselne when it is scaled to provide performance and design benefits. This mathematical model, calibrated to finite element analysis and structural optimization sizing results, provides accurate weight prediction for a new configuration which has been moderately scaled from a thoroughly analyzed baseline configuration. This paper will present the structural optimization weight results and the math model weight predictions for a baseline configuration and 15 scaled configurations.

  4. Integrated approach for active coupling of structures and fluids

    NASA Technical Reports Server (NTRS)

    Guruswamy, Guru P.

    1989-01-01

    Strong coupling of structure and fluids is common in many engineering environments, particularly when the flow is nonlinear and very sensitive to structural motions. Such coupling can give rise to physically important phenomena, such as a dip in the transonic flutter boundary of a wing. The coupled phenomenon can be analyzed in closed form for simple cases that are defined by linear structural and fluid equations of motion. However, complex cases defined by nonlinear equations pose a more difficult task for solution. It is important to understand these nonlinear coupled problems, since they may lead to physically important new phenomena. Flow discontinuities, such as a shock wave, and structural discontinuities, such as a hinge line of a control surface of a wing, can magnify the coupled effects and give rise to new phenomena. To study such a strongly coupled phenomenon, an integrated approach is presented in this paper. The aerodynamic and structural equations of motion are simultaneously integrated by a time-accurate numerical scheme. The theoretical simulation is done using the time-accurate unsteady transonic aerodynamic equations coupled with modal structural equations of motion. As an example, the coupled effect of shock waves and hinge-line discontinuities are studied for aeroelastically flexible wings with active control surfaces. The simulation in this study is modeled in the time domain and can be extended to simulate accurately other systems where fluids and structures are strongly coupled.

  5. The integration of remote sensing data into global weather prediction, wave forecasting, and ocean circulation computer based systems

    NASA Technical Reports Server (NTRS)

    Pierson, W. J., Jr.

    1970-01-01

    Data from infrared imaging systems and satellite infrared spectrometer (SIRS) for determining sea surface temperature and the atmospheric structure in cloudless areas over the oceans are discussed. Although some interpretations differ, it is clear that simultaneous measurements of radar sea return and passive microwave temperature will provide estimates of the wind speed, and perhaps wind direction, over the oceans, especially in cloudless areas, for a wide range of wind speeds. The problem of integrating the data that would be obtained by a spacecraft, especially one with a combination radar-radiometer, into global analysis procedures for meteorological, wave, and oceanographic predictions is described.

  6. Predicting Anticancer Drug Responses Using a Dual-Layer Integrated Cell Line-Drug Network Model

    PubMed Central

    Fang, Yun; Wang, Jun; Zheng, Xiaoqi; Liu, X. Shirley

    2015-01-01

    The ability to predict the response of a cancer patient to a therapeutic agent is a major goal in modern oncology that should ultimately lead to personalized treatment. Existing approaches to predicting drug sensitivity rely primarily on profiling of cancer cell line panels that have been treated with different drugs and selecting genomic or functional genomic features to regress or classify the drug response. Here, we propose a dual-layer integrated cell line-drug network model, which uses both cell line similarity network (CSN) data and drug similarity network (DSN) data to predict the drug response of a given cell line using a weighted model. Using the Cancer Cell Line Encyclopedia (CCLE) and Cancer Genome Project (CGP) studies as benchmark datasets, our single-layer model with CSN or DSN and only a single parameter achieved a prediction performance comparable to the previously generated elastic net model. When using the dual-layer model integrating both CSN and DSN, our predicted response reached a 0.6 Pearson correlation coefficient with observed responses for most drugs, which is significantly better than the previous results using the elastic net model. We have also applied the dual-layer cell line-drug integrated network model to fill in the missing drug response values in the CGP dataset. Even though the dual-layer integrated cell line-drug network model does not specifically model mutation information, it correctly predicted that BRAF mutant cell lines would be more sensitive than BRAF wild-type cell lines to three MEK1/2 inhibitors tested. PMID:26418249

  7. Protein subcellular localization prediction based on compartment-specific features and structure conservation

    PubMed Central

    Su, Emily Chia-Yu; Chiu, Hua-Sheng; Lo, Allan; Hwang, Jenn-Kang; Sung, Ting-Yi; Hsu, Wen-Lian

    2007-01-01

    Background Protein subcellular localization is crucial for genome annotation, protein function prediction, and drug discovery. Determination of subcellular localization using experimental approaches is time-consuming; thus, computational approaches become highly desirable. Extensive studies of localization prediction have led to the development of several methods including composition-based and homology-based methods. However, their performance might be significantly degraded if homologous sequences are not detected. Moreover, methods that integrate various features could suffer from the problem of low coverage in high-throughput proteomic analyses due to the lack of information to characterize unknown proteins. Results We propose a hybrid prediction method for Gram-negative bacteria that combines a one-versus-one support vector machines (SVM) model and a structural homology approach. The SVM model comprises a number of binary classifiers, in which biological features derived from Gram-negative bacteria translocation pathways are incorporated. In the structural homology approach, we employ secondary structure alignment for structural similarity comparison and assign the known localization of the top-ranked protein as the predicted localization of a query protein. The hybrid method achieves overall accuracy of 93.7% and 93.2% using ten-fold cross-validation on the benchmark data sets. In the assessment of the evaluation data sets, our method also attains accurate prediction accuracy of 84.0%, especially when testing on sequences with a low level of homology to the training data. A three-way data split procedure is also incorporated to prevent overestimation of the predictive performance. In addition, we show that the prediction accuracy should be approximately 85% for non-redundant data sets of sequence identity less than 30%. Conclusion Our results demonstrate that biological features derived from Gram-negative bacteria translocation pathways yield a significant

  8. An optimization-based integrated controls-structures design methodology for flexible space structures

    NASA Technical Reports Server (NTRS)

    Maghami, Peiman G.; Joshi, Suresh M.; Armstrong, Ernest S.

    1993-01-01

    An approach for an optimization-based integrated controls-structures design is presented for a class of flexible spacecraft that require fine attitude pointing and vibration suppression. The integrated design problem is posed in the form of simultaneous optimization of both structural and control design variables. The approach is demonstrated by application to the integrated design of a generic space platform and to a model of a ground-based flexible structure. The numerical results obtained indicate that the integrated design approach can yield spacecraft designs that have substantially superior performance over a conventional design wherein the structural and control designs are performed sequentially. For example, a 40-percent reduction in the pointing error is observed along with a slight reduction in mass, or an almost twofold increase in the controlled performance is indicated with more than a 5-percent reduction in the overall mass of the spacecraft (a reduction of hundreds of kilograms).

  9. Prediction of brain-computer interface aptitude from individual brain structure

    PubMed Central

    Halder, S.; Varkuti, B.; Bogdan, M.; Kübler, A.; Rosenstiel, W.; Sitaram, R.; Birbaumer, N.

    2013-01-01

    Objective: Brain-computer interface (BCI) provide a non-muscular communication channel for patients with impairments of the motor system. A significant number of BCI users is unable to obtain voluntary control of a BCI-system in proper time. This makes methods that can be used to determine the aptitude of a user necessary. Methods: We hypothesized that integrity and connectivity of involved white matter connections may serve as a predictor of individual BCI-performance. Therefore, we analyzed structural data from anatomical scans and DTI of motor imagery BCI-users differentiated into high and low BCI-aptitude groups based on their overall performance. Results: Using a machine learning classification method we identified discriminating structural brain trait features and correlated the best features with a continuous measure of individual BCI-performance. Prediction of the aptitude group of each participant was possible with near perfect accuracy (one error). Conclusions: Tissue volumetric analysis yielded only poor classification results. In contrast, the structural integrity and myelination quality of deep white matter structures such as the Corpus Callosum, Cingulum, and Superior Fronto-Occipital Fascicle were positively correlated with individual BCI-performance. Significance: This confirms that structural brain traits contribute to individual performance in BCI use. PMID:23565083

  10. RNA-Puzzles: A CASP-like evaluation of RNA three-dimensional structure prediction

    PubMed Central

    Cruz, José Almeida; Blanchet, Marc-Frédérick; Boniecki, Michal; Bujnicki, Janusz M.; Chen, Shi-Jie; Cao, Song; Das, Rhiju; Ding, Feng; Dokholyan, Nikolay V.; Flores, Samuel Coulbourn; Huang, Lili; Lavender, Christopher A.; Lisi, Véronique; Major, François; Mikolajczak, Katarzyna; Patel, Dinshaw J.; Philips, Anna; Puton, Tomasz; Santalucia, John; Sijenyi, Fredrick; Hermann, Thomas; Rother, Kristian; Rother, Magdalena; Serganov, Alexander; Skorupski, Marcin; Soltysinski, Tomasz; Sripakdeevong, Parin; Tuszynska, Irina; Weeks, Kevin M.; Waldsich, Christina; Wildauer, Michael; Leontis, Neocles B.; Westhof, Eric

    2012-01-01

    We report the results of a first, collective, blind experiment in RNA three-dimensional (3D) structure prediction, encompassing three prediction puzzles. The goals are to assess the leading edge of RNA structure prediction techniques; compare existing methods and tools; and evaluate their relative strengths, weaknesses, and limitations in terms of sequence length and structural complexity. The results should give potential users insight into the suitability of available methods for different applications and facilitate efforts in the RNA structure prediction community in ongoing efforts to improve prediction tools. We also report the creation of an automated evaluation pipeline to facilitate the analysis of future RNA structure prediction exercises. PMID:22361291

  11. The extended evolutionary synthesis: its structure, assumptions and predictions

    PubMed Central

    Laland, Kevin N.; Uller, Tobias; Feldman, Marcus W.; Sterelny, Kim; Müller, Gerd B.; Moczek, Armin; Jablonka, Eva; Odling-Smee, John

    2015-01-01

    Scientific activities take place within the structured sets of ideas and assumptions that define a field and its practices. The conceptual framework of evolutionary biology emerged with the Modern Synthesis in the early twentieth century and has since expanded into a highly successful research program to explore the processes of diversification and adaptation. Nonetheless, the ability of that framework satisfactorily to accommodate the rapid advances in developmental biology, genomics and ecology has been questioned. We review some of these arguments, focusing on literatures (evo-devo, developmental plasticity, inclusive inheritance and niche construction) whose implications for evolution can be interpreted in two ways—one that preserves the internal structure of contemporary evolutionary theory and one that points towards an alternative conceptual framework. The latter, which we label the ‘extended evolutionary synthesis' (EES), retains the fundaments of evolutionary theory, but differs in its emphasis on the role of constructive processes in development and evolution, and reciprocal portrayals of causation. In the EES, developmental processes, operating through developmental bias, inclusive inheritance and niche construction, share responsibility for the direction and rate of evolution, the origin of character variation and organism–environment complementarity. We spell out the structure, core assumptions and novel predictions of the EES, and show how it can be deployed to stimulate and advance research in those fields that study or use evolutionary biology. PMID:26246559

  12. The extended evolutionary synthesis: its structure, assumptions and predictions.

    PubMed

    Laland, Kevin N; Uller, Tobias; Feldman, Marcus W; Sterelny, Kim; Müller, Gerd B; Moczek, Armin; Jablonka, Eva; Odling-Smee, John

    2015-08-22

    Scientific activities take place within the structured sets of ideas and assumptions that define a field and its practices. The conceptual framework of evolutionary biology emerged with the Modern Synthesis in the early twentieth century and has since expanded into a highly successful research program to explore the processes of diversification and adaptation. Nonetheless, the ability of that framework satisfactorily to accommodate the rapid advances in developmental biology, genomics and ecology has been questioned. We review some of these arguments, focusing on literatures (evo-devo, developmental plasticity, inclusive inheritance and niche construction) whose implications for evolution can be interpreted in two ways—one that preserves the internal structure of contemporary evolutionary theory and one that points towards an alternative conceptual framework. The latter, which we label the 'extended evolutionary synthesis' (EES), retains the fundaments of evolutionary theory, but differs in its emphasis on the role of constructive processes in development and evolution, and reciprocal portrayals of causation. In the EES, developmental processes, operating through developmental bias, inclusive inheritance and niche construction, share responsibility for the direction and rate of evolution, the origin of character variation and organism-environment complementarity. We spell out the structure, core assumptions and novel predictions of the EES, and show how it can be deployed to stimulate and advance research in those fields that study or use evolutionary biology.

  13. Integrating data sources to improve hydraulic head predictions : a hierarchical machine learning approach.

    SciTech Connect

    Michael, W. J.; Minsker, B. S.; Tcheng, D.; Valocchi, A. J.; Quinn, J. J.; Environmental Assessment; Univ. of Illinois

    2005-03-26

    This study investigates how machine learning methods can be used to improve hydraulic head predictions by integrating different types of data, including data from numerical models, in a hierarchical approach. A suite of four machine learning methods (decision trees, instance-based weighting, inverse distance weighting, and neural networks) are tested in several hierarchical configurations with different types of data from the 317/319 area at Argonne National Laboratory-East. The best machine learning model had a mean predicted head error 50% smaller than an existing MODFLOW numerical flow model, and a standard deviation of predicted head error 67% lower than the MODFLOW model, computed across all sampled locations used for calibrating the MODFLOW model. These predictions were obtained using decision trees trained with all historical quarterly data; the hourly head measurements were not as useful for prediction, most likely because of their poor spatial coverage. The results show promise for using hierarchical machine learning approaches to improve predictions and to identify the most essential types of data to guide future sampling efforts. Decision trees were also combined with an existing MODFLOW model to test their capabilities for updating numerical models to improve predictions as new data are collected. The combined model had a mean error 50% lower than the MODFLOW model alone. These results demonstrate that hierarchical machine learning approaches can be used to improve predictive performance of existing numerical models in areas with good data coverage. Further research is needed to compare this approach with methods such as Kalman filtering.

  14. Predictive coding and multisensory integration: an attentional account of the multisensory mind

    PubMed Central

    Talsma, Durk

    2015-01-01

    Multisensory integration involves a host of different cognitive processes, occurring at different stages of sensory processing. Here I argue that, despite recent insights suggesting that multisensory interactions can occur at very early latencies, the actual integration of individual sensory traces into an internally consistent mental representation is dependent on both top–down and bottom–up processes. Moreover, I argue that this integration is not limited to just sensory inputs, but that internal cognitive processes also shape the resulting mental representation. Studies showing that memory recall is affected by the initial multisensory context in which the stimuli were presented will be discussed, as well as several studies showing that mental imagery can affect multisensory illusions. This empirical evidence will be discussed from a predictive coding perspective, in which a central top–down attentional process is proposed to play a central role in coordinating the integration of all these inputs into a coherent mental representation. PMID:25859192

  15. Detecting and representing predictable structure during auditory scene analysis.

    PubMed

    Sohoglu, Ediz; Chait, Maria

    2016-01-01

    We use psychophysics and MEG to test how sensitivity to input statistics facilitates auditory-scene-analysis (ASA). Human subjects listened to 'scenes' comprised of concurrent tone-pip streams (sources). On occasional trials a new source appeared partway. Listeners were more accurate and quicker to detect source appearance in scenes comprised of temporally-regular (REG), rather than random (RAND), sources. MEG in passive listeners and those actively detecting appearance events revealed increased sustained activity in auditory and parietal cortex in REG relative to RAND scenes, emerging ~400 ms of scene-onset. Over and above this, appearance in REG scenes was associated with increased responses relative to RAND scenes. The effect of temporal structure on appearance-evoked responses was delayed when listeners were focused on the scenes relative to when listening passively, consistent with the notion that attention reduces 'surprise'. Overall, the results implicate a mechanism that tracks predictability of multiple concurrent sources to facilitate active and passive ASA.

  16. Structural Acoustic Prediction and Interior Noise Control Technology

    NASA Technical Reports Server (NTRS)

    Mathur, G. P.; Chin, C. L.; Simpson, M. A.; Lee, J. T.; Palumbo, Daniel L. (Technical Monitor)

    2001-01-01

    This report documents the results of Task 14, "Structural Acoustic Prediction and Interior Noise Control Technology". The task was to evaluate the performance of tuned foam elements (termed Smart Foam) both analytically and experimentally. Results taken from a three-dimensional finite element model of an active, tuned foam element are presented. Measurements of sound absorption and sound transmission loss were taken using the model. These results agree well with published data. Experimental performance data were taken in Boeing's Interior Noise Test Facility where 12 smart foam elements were applied to a 757 sidewall. Several configurations were tested. Noise reductions of 5-10 dB were achieved over the 200-800 Hz bandwidth of the controller. Accelerometers mounted on the panel provided a good reference for the controller. Configurations with far-field error microphones outperformed near-field cases.

  17. An RNA secondary structure prediction method based on minimum and suboptimal free energy structures.

    PubMed

    Fu, Haoyue; Yang, Lianping; Zhang, Xiangde

    2015-09-01

    The function of an RNA-molecule is mainly determined by its tertiary structures. And its secondary structure is an important determinant of its tertiary structure. The comparative methods usually give better results than the single-sequence methods. Based on minimum and suboptimal free energy structures, the paper presents a novel method for predicting conserved secondary structure of a group of related RNAs. In the method, the information from the known RNA structures is used as training data in a SVM (Support Vector Machine) classifier. Our method has been tested on the benchmark dataset given by Puton et al. The results show that the average sensitivity of our method is higher than that of other comparative methods such as CentroidAlifold, MXScrana, RNAalifold, and TurboFold. PMID:26100179

  18. High Precision Prediction of Functional Sites in Protein Structures

    PubMed Central

    Buturovic, Ljubomir; Wong, Mike; Tang, Grace W.; Altman, Russ B.; Petkovic, Dragutin

    2014-01-01

    We address the problem of assigning biological function to solved protein structures. Computational tools play a critical role in identifying potential active sites and informing screening decisions for further lab analysis. A critical parameter in the practical application of computational methods is the precision, or positive predictive value. Precision measures the level of confidence the user should have in a particular computed functional assignment. Low precision annotations lead to futile laboratory investigations and waste scarce research resources. In this paper we describe an advanced version of the protein function annotation system FEATURE, which achieved 99% precision and average recall of 95% across 20 representative functional sites. The system uses a Support Vector Machine classifier operating on the microenvironment of physicochemical features around an amino acid. We also compared performance of our method with state-of-the-art sequence-level annotator Pfam in terms of precision, recall and localization. To our knowledge, no other functional site annotator has been rigorously evaluated against these key criteria. The software and predictive models are incorporated into the WebFEATURE service at http://feature.stanford.edu/wf4.0-beta. PMID:24632601

  19. Engineering Property Prediction Tools for Tailored Polymer Composite Structures

    SciTech Connect

    Nguyen, Ba Nghiep; Foss, Peter; Wyzgoski, Michael; Trantina, Gerry; Kunc, Vlastimil; Schutte, Carol; Smith, Mark T.

    2009-12-23

    This report summarizes our FY 2009 research activities for the project titled:"Engineering Property Prediction Tools for Tailored Polymer Composite Structures." These activities include (i) the completion of the development of a fiber length attrition model for injection-molded long-fiber thermoplastics (LFTs), (ii) development of the a fatigue damage model for LFTs and its implementation in ABAQUS, (iii) development of an impact damage model for LFTs and its implementation in ABAQUS, (iv) development of characterization methods for fatigue testing, (v) characterization of creep and fatigue responses of glass-fiber/polyamide (PA6,6) and glass-fiber/polypropylene (PP), (vi) characterization of fiber length distribution along the flow length of glass/PA6,6 and glass-fiber/PP, and (vii) characterization of impact responses of glass-fiber/PA6,6. The fiber length attrition model accurately captures the fiber length distribution along the flow length of the studied glass-fiber/PP material. The fatigue damage model is able to predict the S-N and stiffness reduction data which are valuable to the fatigue design of LFTs. The impact damage model correctly captures damage accumulation observed in experiments of glass-fiber/PA6,6 plaques.Further work includes validations of these models for representative LFT materials and a complex LFT part.

  20. Can we predict lattice energy from molecular structure?

    PubMed

    Ouvrard, Carole; Mitchell, John B O

    2003-10-01

    By using simply the numbers of occurrences of different atom types as descriptors, a conceptually transparent and remarkably accurate model for the prediction of the enthalpies of sublimation of organic compounds has been generated. The atom types are defined on the basis of atomic number, hybridization state and bonded environment. Models of this kind were applied firstly to aliphatic hydrocarbons, secondly to both aliphatic and aromatic hydrocarbons, thirdly to a wide range of non-hydrogen-bonding molecules, and finally to a set of 226 organic compounds including 70 containing hydrogen-bond donors and acceptors. The final model gives squared correlation coefficients of 0.925 for the 226 compounds in the training set and 0.937 for an independent test set of 35 compounds. The success of such a simple model implies that the enthalpy of sublimation can be predicted accurately without knowledge of the crystal packing. This hypothesis is in turn consistent with the idea that, rather than being determined by the particular features of the lowest-energy packing, the lattice energy is similar for a number of hypothetical alternative crystal structures of a molecule.

  1. The eye in hand: predicting others' behavior by integrating multiple sources of information

    PubMed Central

    Pezzulo, Giovanni; Costantini, Marcello

    2015-01-01

    The ability to predict the outcome of other beings' actions confers significant adaptive advantages. Experiments have assessed that human action observation can use multiple information sources, but it is currently unknown how they are integrated and how conflicts between them are resolved. To address this issue, we designed an action observation paradigm requiring the integration of multiple, potentially conflicting sources of evidence about the action target: the actor's gaze direction, hand preshape, and arm trajectory, and their availability and relative uncertainty in time. In two experiments, we analyzed participants' action prediction ability by using eye tracking and behavioral measures. The results show that the information provided by the actor's gaze affected participants' explicit predictions. However, results also show that gaze information was disregarded as soon as information on the actor's hand preshape was available, and this latter information source had widespread effects on participants' prediction ability. Furthermore, as the action unfolded in time, participants relied increasingly more on the arm movement source, showing sensitivity to its increasing informativeness. Therefore, the results suggest that the brain forms a robust estimate of the actor's motor intention by integrating multiple sources of information. However, when informative motor cues such as a preshaped hand with a given grip are available and might help in selecting action targets, people tend to capitalize on such motor cues, thus turning out to be more accurate and fast in inferring the object to be manipulated by the other's hand. PMID:25568158

  2. Structure activity relationships: their function in biological prediction

    SciTech Connect

    Schultz, T.W.

    1982-01-01

    Quantitative structure activity relationships provide a means of ranking or predicting biological effects based on chemical structure. For each compound used to formulate a structure activity model two kinds of quantitative information are required: (1) biological activity and (2) molecular properties. Molecular properties are of three types: (1) molecular shape, (2) physiochemical parameters, and (3) abstract quantitations of molecular structure. Currently the two best descriptors are the hydrophobic parameter, log 1-octanol/water partition coefficient (log P), and the /sup 1/X/sup v/(one-chi-v) molecular connectivity index. Biological responses can be divided into three main categories: (1) non-specific effects due to membrane perturbation, (2) non-specific effects due to interaction with functional groups of proteins, and (3) specific effects due to interaction with receptors. Twenty-six synthetic fossil fuel-related nitrogen-containing aromatic compounds were examined to determine the quantitative correlation between log P and /sup 1/X/sup v/ and population growth impairment of Tetrahymena pyriformis. Nitro-containing compounds are the most active, followed by amino-containing compounds and azaarenes. Within each analog series activity increases with alkyl substitution and ring addition. The planar model log BR = 0.5564 log P + 0.3000 /sup 1/X/sup v/ -2.0138 was determined using mono-nitrogen substituted compounds. Attempts to extrapolate this model to dinitrogen-containing molecules were, for the most part, unsuccessful because of a change in mode of action from membrane perturbation to uncoupling of oxidative phosphoralation.

  3. Solid-state NMR structures of integral membrane proteins.

    PubMed

    Patching, Simon G

    2015-01-01

    Solid-state NMR is unique for its ability to obtain three-dimensional structures and to measure atomic-resolution structural and dynamic information for membrane proteins in native lipid bilayers. An increasing number and complexity of integral membrane protein structures have been determined by solid-state NMR using two main methods. Oriented sample solid-state NMR uses macroscopically aligned lipid bilayers to obtain orientational restraints that define secondary structure and global fold of embedded peptides and proteins and their orientation and topology in lipid bilayers. Magic angle spinning (MAS) solid-state NMR uses unoriented rapidly spinning samples to obtain distance and torsion angle restraints that define tertiary structure and helix packing arrangements. Details of all current protein structures are described, highlighting developments in experimental strategy and other technological advancements. Some structures originate from combining solid- and solution-state NMR information and some have used solid-state NMR to refine X-ray crystal structures. Solid-state NMR has also validated the structures of proteins determined in different membrane mimetics by solution-state NMR and X-ray crystallography and is therefore complementary to other structural biology techniques. By continuing efforts in identifying membrane protein targets and developing expression, isotope labelling and sample preparation strategies, probe technology, NMR experiments, calculation and modelling methods and combination with other techniques, it should be feasible to determine the structures of many more membrane proteins of biological and biomedical importance using solid-state NMR. This will provide three-dimensional structures and atomic-resolution structural information for characterising ligand and drug interactions, dynamics and molecular mechanisms of membrane proteins under physiological lipid bilayer conditions.

  4. Solid-state NMR structures of integral membrane proteins.

    PubMed

    Patching, Simon G

    2015-01-01

    Solid-state NMR is unique for its ability to obtain three-dimensional structures and to measure atomic-resolution structural and dynamic information for membrane proteins in native lipid bilayers. An increasing number and complexity of integral membrane protein structures have been determined by solid-state NMR using two main methods. Oriented sample solid-state NMR uses macroscopically aligned lipid bilayers to obtain orientational restraints that define secondary structure and global fold of embedded peptides and proteins and their orientation and topology in lipid bilayers. Magic angle spinning (MAS) solid-state NMR uses unoriented rapidly spinning samples to obtain distance and torsion angle restraints that define tertiary structure and helix packing arrangements. Details of all current protein structures are described, highlighting developments in experimental strategy and other technological advancements. Some structures originate from combining solid- and solution-state NMR information and some have used solid-state NMR to refine X-ray crystal structures. Solid-state NMR has also validated the structures of proteins determined in different membrane mimetics by solution-state NMR and X-ray crystallography and is therefore complementary to other structural biology techniques. By continuing efforts in identifying membrane protein targets and developing expression, isotope labelling and sample preparation strategies, probe technology, NMR experiments, calculation and modelling methods and combination with other techniques, it should be feasible to determine the structures of many more membrane proteins of biological and biomedical importance using solid-state NMR. This will provide three-dimensional structures and atomic-resolution structural information for characterising ligand and drug interactions, dynamics and molecular mechanisms of membrane proteins under physiological lipid bilayer conditions. PMID:26857803

  5. Structural Integrity of Single Shell Tanks at Hanford - 9491

    SciTech Connect

    Rinker, Michael W.; Pilli, Siva Prasad; Karri, Naveen K.; Deibler, John E.; Johnson, Kenneth I.; Holbery, James D.; Mullen, O Dennis; Hurley, David E.

    2009-03-01

    The 149 Single Shell Tanks at the Hanford Site were constructed between the 1940’s and the 1960’s. Many of the tanks are either known or suspected to have leaked in the past. While the free liquids have been removed from the tanks, they still contain significant waste volumes. Recently, the tank farm operations contractor established a Single Shell Tank Integrity Program. Structural integrity is one aspect of the program. The structural analysis of the Single Shell Tanks has several challenging factors. There are several tank sizes and configurations that need to be analyzed. Tank capacities range from fifty-five thousand gallons to one-million gallons. The smallest tank type is approximately twenty feet in diameter, and the three other tank types are all seventy-five feet in diameter. Within each tank type there are varying concrete strengths, types of steel, tank floor arrangements, in-tank hardware, riser sizes and locations, and other appurtenances that need to be addressed. Furthermore, soil properties vary throughout the tank farms. The Pacific Northwest National Laboratory has been conducting preliminary structural analyses of the various single shell tank types to address these parameters. The preliminary analyses will assess which aspects of the tanks will require further detailed analysis. Evaluation criteria to which the tanks will be analyzed are also being developed for the Single Shell Tank Integrity Program. This information will be reviewed by the Single Shell Tank Integrity Expert Panel that has been formed to issue recommendations to the DOE and to the tank farm operations contractor regarding Single Shell Tank Integrity. This paper provides a summary of the preliminary analysis of the single shell tanks, a summary of the recommendations for the detailed analyses, and the proposed evaluation criteria by which the tanks will be judged.

  6. Geological and geomorphological study of the Amudariya syneclise (middle Asia) for petroleum-bearing structure prediction

    SciTech Connect

    Smirnova, I.

    1995-08-01

    The integrated analysis of geophysical, geological, geochemical, geomorphological and remotely sensed data was carried out using the computerized technology at two test sites of Amudaria syneclise: eastern part of the Charjou step and the area of gas field Gasly (Bukharskaya step). At the Charjou step the geological modelling of petroleum-bearing structures (anticlines, reefs) as well as different horizons of sedimentary cover was conducted. In the models we used the morphological parameters of structures from the depth of petroliferous units up to the surface by drilling and seismic data, gravity and magnetic data, geochemical characteristics of soils, characteristics of relief, landscape elements distribution, spectral characteristics extracted from remotely sensed data and others. The using in the models of the landscape data is based on the theory that landscape components, their distribution and changes are connected with deep geological structures due to neotectonic movements, alterations of the rocks covering petroleum pools and seeping fluids. The modelling of known structures allows to reveal the types of their expression in relief and to predict the location of these structures and their parameters (amplitude, size) on week investigated areas. The results of structural horizons modelling allow to compose the schemes of tectonic and petroleum zonation and to predict the spreading of rest formation on Charjou step. The results of retrospective multispectral satellite and field data processing have permitted to reveal the secondary gas pool formed at the depth near 200 meters after failure on exploration well. At the test site Gasly geomorphological investigations using retrospective aerial and satellite images were carried out for the study of geological consequences of large gas field exploitation in connection with two destructive earthquakes. We obtain the data connected with recent tectonic movement which may be used for prediction of the earthquakes.

  7. Approximation method to compute domain related integrals in structural studies

    NASA Astrophysics Data System (ADS)

    Oanta, E.; Panait, C.; Raicu, A.; Barhalescu, M.; Axinte, T.

    2015-11-01

    Various engineering calculi use integral calculus in theoretical models, i.e. analytical and numerical models. For usual problems, integrals have mathematical exact solutions. If the domain of integration is complicated, there may be used several methods to calculate the integral. The first idea is to divide the domain in smaller sub-domains for which there are direct calculus relations, i.e. in strength of materials the bending moment may be computed in some discrete points using the graphical integration of the shear force diagram, which usually has a simple shape. Another example is in mathematics, where the surface of a subgraph may be approximated by a set of rectangles or trapezoids used to calculate the definite integral. The goal of the work is to introduce our studies about the calculus of the integrals in the transverse section domains, computer aided solutions and a generalizing method. The aim of our research is to create general computer based methods to execute the calculi in structural studies. Thus, we define a Boolean algebra which operates with ‘simple’ shape domains. This algebraic standpoint uses addition and subtraction, conditioned by the sign of every ‘simple’ shape (-1 for the shapes to be subtracted). By ‘simple’ shape or ‘basic’ shape we define either shapes for which there are direct calculus relations, or domains for which their frontiers are approximated by known functions and the according calculus is carried out using an algorithm. The ‘basic’ shapes are linked to the calculus of the most significant stresses in the section, refined aspect which needs special attention. Starting from this idea, in the libraries of ‘basic’ shapes, there were included rectangles, ellipses and domains whose frontiers are approximated by spline functions. The domain triangularization methods suggested that another ‘basic’ shape to be considered is the triangle. The subsequent phase was to deduce the exact relations for the

  8. Integrative Analysis of Metabolic Models – from Structure to Dynamics

    PubMed Central

    Hartmann, Anja; Schreiber, Falk

    2015-01-01

    The characterization of biological systems with respect to their behavior and functionality based on versatile biochemical interactions is a major challenge. To understand these complex mechanisms at systems level modeling approaches are investigated. Different modeling formalisms allow metabolic models to be analyzed depending on the question to be solved, the biochemical knowledge and the availability of experimental data. Here, we describe a method for an integrative analysis of the structure and dynamics represented by qualitative and quantitative metabolic models. Using various formalisms, the metabolic model is analyzed from different perspectives. Determined structural and dynamic properties are visualized in the context of the metabolic model. Interaction techniques allow the exploration and visual analysis thereby leading to a broader understanding of the behavior and functionality of the underlying biological system. The System Biology Metabolic Model Framework (SBM2 – Framework) implements the developed method and, as an example, is applied for the integrative analysis of the crop plant potato. PMID:25674560

  9. Conformational States of Macromolecular Assemblies Explored by Integrative Structure Calculation

    PubMed Central

    Thalassinos, Konstantinos; Pandurangan, Arun Prasad; Xu, Min; Alber, Frank; Topf, Maya

    2013-01-01

    Summary A detailed description of macromolecular assemblies in multiple conformational states can be very valuable for understanding cellular processes. At present, structural determination of most assemblies in different biologically relevant conformations cannot be achieved by a single technique and thus requires an integrative approach that combines information from multiple sources. Different techniques require different computational methods to allow efficient and accurate data processing and analysis. Here, we summarize the latest advances and future challenges in computational methods that help the interpretation of data from two techniques—mass spectrometry and three-dimensional cryo-electron microscopy (with focus on alignment and classification of heterogeneous subtomograms from cryo-electron tomography). We evaluate how new developments in these two broad fields will lead to further integration with atomic structures to broaden our picture of the dynamic behavior of assemblies in their native environment. PMID:24010709

  10. Bionic intraocular lens with variable focus and integrated structure

    NASA Astrophysics Data System (ADS)

    Liang, Dan; Wang, Xuan-Yin; Du, Jia-Wei; Xiang, Ke

    2015-10-01

    This paper proposes a bionic accommodating intraocular lens (IOL) for ophthalmic surgery. The designed lens has a solid-liquid mixed integrated structure, which mainly consists of a support ring, elastic membrane, rigid lens, and optical liquid. The lens focus can be adjusted through the deformation of the lens front surface when compressed. The integrated structure of the IOL is presented, as well as a detailed description of the lens materials and fabrication process. Images under different radial pressures are captured, and the lens deformation process, accommodating range, density, and optical property are analyzed. The designed lens achieves a 14.6 D accommodating range under a radial pressure of 51.4 mN and a 0.24 mm alteration of the lens outer radius. The deformation property of the lens matches well with the characteristic of the eye and shows the potential to help patients fully recover their vision accommodation ability after the cataract surgery.

  11. Performance optimized, small structurally integrated ion thruster system

    NASA Technical Reports Server (NTRS)

    Hyman, J., Jr.

    1973-01-01

    A 5-cm structurally integrated ion thruster has been developed for attitude control and stationkeeping of synchronous satellites. As optimized with a conventional ion extraction system, the system demonstrates a thrust T = 0.47 mlb at a beam voltage of 1600 V, total mass efficiency of 76%, and electrical efficiency of 56%. Under the subject contract effort, no significant performance change was noted for operation with two dimensional electrostatic thrust-vectoring grids. Structural integrity with the vectoring grids was demonstrated for shock (+ or - 30 G), sinusoidal (9 G), and random (19.9 G rms) accelerations. System envelope is 31.2 cm long by 13.4 cm flange bolt circle, with a mass of 9.0 Kg, including 6.8 Kg mercury propellant.

  12. Protein structure prediction provides comparable performance to crystallographic structures in docking-based virtual screening.

    PubMed

    Du, Hongying; Brender, Jeffrey R; Zhang, Jian; Zhang, Yang

    2015-01-01

    Structure based virtual screening has largely been limited to protein targets for which either an experimental structure is available or a strongly homologous template exists so that a high-resolution model can be constructed. The performance of state of the art protein structure predictions in virtual screening in systems where only weakly homologous templates are available is largely untested. Using the challenging DUD database of structural decoys, we show here that even using templates with only weak sequence homology (<30% sequence identity) structural models can be constructed by I-TASSER which achieve comparable enrichment rates to using the experimental bound crystal structure in the majority of the cases studied. For 65% of the targets, the I-TASSER models, which are constructed essentially in the apo conformations, reached 70% of the virtual screening performance of using the holo-crystal structures. A correlation was observed between the success of I-TASSER in modeling the global fold and local structures in the binding pockets of the proteins versus the relative success in virtual screening. The virtual screening performance can be further improved by the recognition of chemical features of the ligand compounds. These results suggest that the combination of structure-based docking and advanced protein structure modeling methods should be a valuable approach to the large-scale drug screening and discovery studies, especially for the proteins lacking crystallographic structures.

  13. Efficient optimization of integrated aerodynamic-structural design

    NASA Technical Reports Server (NTRS)

    Haftka, R. T.; Grossman, B.; Eppard, W. M.; Kao, P. J.; Polen, D. M.

    1989-01-01

    Techniques for reducing the computational complexity of multidisciplinary design optimization (DO) of aerodynamic structures are described and demonstrated. The basic principles of aerodynamic and structural DO are reviewed; the formulation of the combined DO problem is outlined; and particular attention is given to (1) the application of perturbation methods to cross-sensitivity computations and (2) numerical approximation procedures. Trial DOs of a simple sailplane design are presented in tables and graphs and discussed in detail. The IBM 3090 CPU time for the entire integrated DO was reduced from an estimated 10 h to about 6 min.

  14. Structural Integrity and Durability of Reusable Space Propulsion Systems

    NASA Technical Reports Server (NTRS)

    1991-01-01

    A two-day conference on the structural integrity and durability of reusable space propulsion systems was held on 14 to 15 May 1991 at the NASA Lewis Research Center. Presentations were made by industry, university, and government researchers organized into four sessions: (1) aerothermodynamic loads; (2) instrumentation; (3) fatigue, fracture, and constitutive modeling; and (4) structural dynamics. The principle objectives were to disseminate research results and future plans in each of four areas. This publication contains extended abstracts and the visual material presented during the conference. Particular emphasis is placed on the Space Shuttle Main Engine (SSME) and the SSME turbopump.

  15. [Integrating information about imaging biomarkers into structured radiology reports].

    PubMed

    Pomar-Nadal, A; Pérez-Castillo, C; Alberich-Bayarri, A; García-Martí, G; Sanz Requena, R; Martí-Bonmatí, L

    2013-01-01

    Imaging biomarkers describe objective characteristics that are related to normal biological processes, diseases, or the response to treatment. They enable radiologists to incorporate into their reports data about structure, function, and tissue components. With the aim of taking maximum advantage of the quantification of medical images, we present a procedure to integrate imaging biomarkers into radiological reports, bringing the new paradigm of personal medicine closer to radiological workflow. In this manner, the results of quantification can complement traditional radiological diagnosis, improving accuracy and the evaluation of the efficacy of treatments. A more personalized, standardized, structured radiological report should include quantitative analyses to complement conventional qualitative reporting in selected cases.

  16. Structural Integrity Program for INTEC Calcined Solids Storage Facilities

    SciTech Connect

    Bryant, Jeffrey Whealdon; Nenni, Joseph A; Timothy S. Yoder

    2003-05-01

    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 structurally sound for continued service. Recommendations are provided for continued monitoring of the Calcined Solids Storage Facilities.

  17. Synthesis of aircraft structures using integrated design and analysis methods

    NASA Technical Reports Server (NTRS)

    Sobieszczanski-Sobieski, J.; Goetz, R. C.

    1978-01-01

    A systematic research is reported to develop and validate methods for structural sizing of an airframe designed with the use of composite materials and active controls. This research program includes procedures for computing aeroelastic loads, static and dynamic aeroelasticity, analysis and synthesis of active controls, and optimization techniques. Development of the methods is concerned with the most effective ways of integrating and sequencing the procedures in order to generate structural sizing and the associated active control system, which is optimal with respect to a given merit function constrained by strength and aeroelasticity requirements.

  18. Integrative Modeling Strategies for Predicting Drug Toxicities at the eTOX Project.

    PubMed

    Sanz, Ferran; Carrió, Pau; López, Oriol; Capoferri, Luigi; Kooi, Derk P; Vermeulen, Nico P E; Geerke, Daan P; Montanari, Floriane; Ecker, Gerhard F; Schwab, Christof H; Kleinöder, Thomas; Magdziarz, Tomasz; Pastor, Manuel

    2015-06-01

    Early prediction of safety issues in drug development is at the same time highly desirable and highly challenging. Recent advances emphasize the importance of understanding the whole chain of causal events leading to observable toxic outcomes. Here we describe an integrative modeling strategy based on these ideas that guided the design of eTOXsys, the prediction system used by the eTOX project. Essentially, eTOXsys consists of a central server that marshals requests to a collection of independent prediction models and offers a single user interface to the whole system. Every of such model lives in a self-contained virtual machine easy to maintain and install. All models produce toxicity-relevant predictions on their own but the results of some can be further integrated and upgrade its scale, yielding in vivo toxicity predictions. Technical aspects related with model implementation, maintenance and documentation are also discussed here. Finally, the kind of models currently implemented in eTOXsys is illustrated presenting three example models making use of diverse methodology (3D-QSAR and decision trees, Molecular Dynamics simulations and Linear Interaction Energy theory, and fingerprint-based QSAR).

  19. Extended Thermodynamic Integration: Efficient Prediction of Lambda Derivatives at Nonsimulated Points.

    PubMed

    Ruiter, Anita de; Oostenbrink, Chris

    2016-09-13

    Thermodynamic integration (TI) is one of the most commonly used free-energy calculation methods. The derivative of the Hamiltonian with respect to lambda, ⟨∂H/∂λ⟩, is determined at multiple λ-points. Because a numerical integration step is necessary, high curvature regions require simulations at densely spaced λ-points. Here, the principle of extended TI is introduced, where ⟨∂H/∂λ⟩ values are predicted at nonsimulated λ-points. On the basis of three model systems, it is shown that extended TI requires significantly fewer λ-points than regular TI to obtain similar accuracy. PMID:27494138

  20. Sensitivity method for integrated structure/active control law design

    NASA Technical Reports Server (NTRS)

    Gilbert, Michael G.

    1987-01-01

    The development is described of an integrated structure/active control law design methodology for aeroelastic aircraft applications. A short motivating introduction to aeroservoelasticity is given along with the need for integrated structures/controls design algorithms. Three alternative approaches to development of an integrated design method are briefly discussed with regards to complexity, coordination and tradeoff strategies, and the nature of the resulting solutions. This leads to the formulation of the proposed approach which is based on the concepts of sensitivity of optimum solutions and multi-level decompositions. The concept of sensitivity of optimum is explained in more detail and compared with traditional sensitivity concepts of classical control theory. The analytical sensitivity expressions for the solution of the linear, quadratic cost, Gaussian (LQG) control problem are summarized in terms of the linear regulator solution and the Kalman Filter solution. Numerical results for a state space aeroelastic model of the DAST ARW-II vehicle are given, showing the changes in aircraft responses to variations of a structural parameter, in this case first wing bending natural frequency.

  1. Poling of PVDF matrix composites for integrated structural load sensing

    NASA Astrophysics Data System (ADS)

    Haghiashtiani, Ghazaleh; Greminger, Michael A.; Zhao, Ping

    2014-03-01

    The purpose of this study is to create and evaluate a smart composite structure that can be used for integrated load sensing and structural health monitoring. In this structure, PVDF films are used as the matrix material instead of epoxy resin or other thermoplastics. The reinforcements are two layers of carbon fiber with one layer of Kevlar separating them. Due to the electrical conductivity properties of carbon fiber and the dielectric effect of Kevlar, the structure acts as a capacitor. Furthermore, the piezoelectric properties of the PVDF matrix can be used to monitor the response of the structure under applied loads. In order to exploit the piezoelectric properties of PVDF, the PVDF material must be polarized to align the dipole moments of its crystalline structure. The optimal condition for poling the structure was found by performing a 23 factorial design of experiment (DoE). The factors that were studied in DoE were temperature, voltage, and duration of poling. Finally, the response of the poled structure was monitored by exposing the samples to an applied load.

  2. Shape and secondary structure prediction for ncRNAs including pseudoknots based on linear SVM

    PubMed Central

    2013-01-01

    Background Accurate secondary structure prediction provides important information to undefirstafinding the tertiary structures and thus the functions of ncRNAs. However, the accuracy of the native structure derivation of ncRNAs is still not satisfactory, especially on sequences containing pseudoknots. It is recently shown that using the abstract shapes, which retain adjacency and nesting of structural features but disregard the length details of helix and loop regions, can improve the performance of structure prediction. In this work, we use SVM-based feature selection to derive the consensus abstract shape of homologous ncRNAs and apply the predicted shape to structure prediction including pseudoknots. Results Our approach was applied to predict shapes and secondary structures on hundreds of ncRNA data sets with and without psuedoknots. The experimental results show that we can achieve 18% higher accuracy in shape prediction than the state-of-the-art consensus shape prediction tools. Using predicted shapes in structure prediction allows us to achieve approximate 29% higher sensitivity and 10% higher positive predictive value than other pseudoknot prediction tools. Conclusions Extensive analysis of RNA properties based on SVM allows us to identify important properties of sequences and structures related to their shapes. The combination of mass data analysis and SVM-based feature selection makes our approach a promising method for shape and structure prediction. The implemented tools, Knot Shape and Knot Structure are open source software and can be downloaded at: http://www.cse.msu.edu/~achawana/KnotShape. PMID:23369147

  3. Prediction of grain structures in various solidification processes

    SciTech Connect

    Rappaz, M.; Gandin, C.A.; Desbiolles, J.L.; Thevoz, P.

    1996-03-01

    Grain structure formation during solidification can be simulated via the use of stochastic models providing the physical mechanisms of nucleation and dendrite growth are accounted for. With this goal in mind, a physically based cellular automaton (CA) model has been coupled with finite element (FE) heat flow computations and implemented into the code 3-MOS. The CA enmeshment of the solidifying domain with small square cells is first generated automatically from the FE mesh. Within each time-step, the variation of enthalpy at each node of the FE mesh is calculated using an implicit scheme and a Newton-type linearization method. After interpolation of the explicit temperature and of the enthalpy variation at the cell location, the nucleation and growth of grains are simulated using the CA algorithm. This algorithm accounts for the heterogeneous nucleation in the bulk and at the surface of the ingot, for the growth and preferential growth directions of the dendrites, and for microsegregation. The variation of volume fraction of solid at the cell location are then summed up at the FE nodes in order to find the new temperatures. This CAFE model, which allows the prediction and the visualization of grain structures during and after solidification, is applied to various solidification processes: the investment casting of turbine blades, the continuous casting of rods, and the laser remelting or welding of plates. Because the CAFE model is yet two-dimensional (2-D), the simulation results are compared in a qualitative way with experimental findings.

  4. Structure-Based Predictive model for Coal Char Combustion.

    SciTech Connect

    Hurt, R.; Calo, J.; Essenhigh, R.; Hadad, C.; Stanley, E.

    1997-06-25

    During the second quarter of this project, progress was made on both major technical tasks. Three parallel efforts were initiated on the modeling of carbon structural evolution. Structural ordering during carbonization was studied by a numerical simulation scheme proposed by Alan Kerstein involving molecular weight growth and rotational mobility. Work was also initiated to adapt a model of carbonaceous mesophase formation, originally developed under parallel NSF funding, to the prediction of coke texture. This latter work makes use of the FG-DVC model of coal pyrolysis developed by Advanced Fuel Research to specify the pool of aromatic clusters that participate in the order/disorder transition. Boston University has initiated molecular dynamics simulations of carbonization processes and Ohio State has begun theoretical treatment of surface reactions. Experimental work has also begun on model compound studies at Brown and on pilot-scale combustion systems with widely varying flame types at OSE. The work on mobility / growth models shows great promise and is discussed in detail in the body of the report.

  5. Neural networks for structural design - An integrated system implementation

    NASA Technical Reports Server (NTRS)

    Berke, Laszlo; Hafez, Wassim; Pao, Yoh-Han

    1992-01-01

    The development of powerful automated procedures to aid the creative designer is becoming increasingly critical for complex design tasks. In the work described here Artificial Neural Nets are applied to acquire structural analysis and optimization domain expertise. Based on initial instructions from the user an automated procedure generates random instances of structural analysis and/or optimization 'experiences' that cover a desired domain. It extracts training patterns from the created instances, constructs and trains an appropriate network architecture and checks the accuracy of net predictions. The final product is a trained neural net that can estimate analysis and/or optimization results instantaneously.

  6. Thermodynamics and structure of a two-dimensional electrolyte by integral equation theory

    SciTech Connect

    Aupic, Jana; Urbic, Tomaz

    2014-05-14

    Monte Carlo simulations and integral equation theory were used to predict the thermodynamics and structure of a two-dimensional Coulomb fluid. We checked the possibility that integral equations reproduce Kosterlitz-Thouless and vapor-liquid phase transitions of the electrolyte and critical points. Integral equation theory results were compared to Monte Carlo data and the correctness of selected closure relations was assessed. Among selected closures hypernetted-chain approximation results matched computer simulation data best, but these equations unfortunately break down at temperatures well above the Kosterlitz-Thouless transition. The Kovalenko-Hirata closure produces results even at very low temperatures and densities, but no sign of phase transition was detected.

  7. Analysis and prediction of integrated kinetic energy in Atlantic tropical cyclones

    NASA Astrophysics Data System (ADS)

    Kozar, Michael E.

    Integrated kinetic energy (IKE) is a recently developed metric that approximates the destructive potential of a tropical cyclone by assessing the size and strength of its wind field. Despite the potential usefulness of the IKE metric, there are few, if any, operational tools that are specifically designed to forecast IKE in real-time. Therefore, IKE and tropical cyclone structure are analyzed within historical Atlantic tropical cyclones from the past two decades in order to develop an understanding of the environmental and internal storm-driven processes that govern IKE variability. This analysis concurs with past research that IKE growth and decay is influenced by both traditional tropical cyclone development mechanisms and by other features such as extratropical transition and trough interactions. Using this framework, a series of statistical prediction tools are created in an effort to project IKE in Atlantic tropical cyclones from a series of relevant normalized input parameters. The resulting IKE prediction schemes are titled the "Statistical Prediction of Integrated Kinetic Energy (SPIKE)". The first version of SPIKE utilizes simple linear regression to project historical IKE quantities in a perfect prognostic mode for all storms between 1990 and 2011. This primitive model acts as a proof of concept, revealing that IKE can be skillfully forecasted relative to persistence out to 72 hours by even the simplest of statistical models if given accurate estimates of various metrics measured throughout the storm and its environment. The proof-of-concept version of SPIKE is improved upon in its second version, SPIKE2, by incorporating a more sophisticated system of adaptive statistical models. A system of artificial neural networks replaces the linear regression model to better capture the nonlinear relationships in the TC-environment system. In a perfect prognostic approach with analyzed input parameters, the neural networks outperform the linear models in nearly

  8. Heterogeneous Network Edge Prediction: A Data Integration Approach to Prioritize Disease-Associated Genes.

    PubMed

    Himmelstein, Daniel S; Baranzini, Sergio E

    2015-07-01

    The first decade of Genome Wide Association Studies (GWAS) has uncovered a wealth of disease-associated variants. Two important derivations will be the translation of this information into a multiscale understanding of pathogenic variants and leveraging existing data to increase the power of existing and future studies through prioritization. We explore edge prediction on heterogeneous networks--graphs with multiple node and edge types--for accomplishing both tasks. First we constructed a network with 18 node types--genes, diseases, tissues, pathophysiologies, and 14 MSigDB (molecular signatures database) collections--and 19 edge types from high-throughput publicly-available resources. From this network composed of 40,343 nodes and 1,608,168 edges, we extracted features that describe the topology between specific genes and diseases. Next, we trained a model from GWAS associations and predicted the probability of association between each protein-coding gene and each of 29 well-studied complex diseases. The model, which achieved 132-fold enrichment in precision at 10% recall, outperformed any individual domain, highlighting the benefit of integrative approaches. We identified pleiotropy, transcriptional signatures of perturbations, pathways, and protein interactions as influential mechanisms explaining pathogenesis. Our method successfully predicted the results (with AUROC = 0.79) from a withheld multiple sclerosis (MS) GWAS despite starting with only 13 previously associated genes. Finally, we combined our network predictions with statistical evidence of association to propose four novel MS genes, three of which (JAK2, REL, RUNX3) validated on the masked GWAS. Furthermore, our predictions provide biological support highlighting REL as the causal gene within its gene-rich locus. Users can browse all predictions online (http://het.io). Heterogeneous network edge prediction effectively prioritized genetic associations and provides a powerful new approach for data

  9. The Global Integrated Drought Monitoring and Prediction System (GIDMaPS): Overview and Capabilities

    NASA Astrophysics Data System (ADS)

    AghaKouchak, A.; Hao, Z.; Farahmand, A.; Nakhjiri, N.

    2013-12-01

    Development of reliable monitoring and prediction indices and tools are fundamental to drought preparedness and management. Motivated by the Global Drought Information Systems (GDIS) activities, this paper presents the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) which provides near real-time drought information using both remote sensing observations and model simulations. The monthly data from the NASA Modern-Era Retrospective analysis for Research and Applications (MERRA-Land), North American Land Data Assimilation System (NLDAS), and remotely sensed precipitation data are used as input to GIDMaPS. Numerous indices have been developed for drought monitoring based on various indicator variables (e.g., precipitation, soil moisture, water storage). Defining droughts based on a single variable (e.g., precipitation, soil moisture or runoff) may not be sufficient for reliable risk assessment and decision making. GIDMaPS provides drought information based on multiple indices including Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI) and the Multivariate Standardized Drought Index (MSDI) which combines SPI and SSI probabilistically. In other words, MSDI incorporates the meteorological and agricultural drought conditions for overall characterization of droughts. The seasonal prediction component of GIDMaPS is based on a persistence model which requires historical data and near-past observations. The seasonal drought prediction component is based on two input data sets (MERRA and NLDAS) and three drought indicators (SPI, SSI and MSDI). The drought prediction model provides the empirical probability of drought for different severity levels. In this presentation, both monitoring and prediction components of GIDMaPS will be discussed, and the results from several major droughts including the 2013 Namibia, 2012-2013 United States, 2011-2012 Horn of Africa, and 2010 Amazon Droughts will be presented. The results indicate

  10. Materials, Structures and Manufacturing: An Integrated Approach to Develop Expandable Structures

    NASA Technical Reports Server (NTRS)

    Belvin, W. Keith; Zander, Martin E.; Sleight, Daid W.; Connell, John; Holloway, Nancy; Palmieri, Frank

    2012-01-01

    Membrane dominated space structures are lightweight and package efficiently for launch; however, they must be expanded (deployed) in-orbit to achieve the desired geometry. These expandable structural systems include solar sails, solar power arrays, antennas, and numerous other large aperture devices that are used to collect, reflect and/or transmit electromagnetic radiation. In this work, an integrated approach to development of thin-film damage tolerant membranes is explored using advanced manufacturing. Bio-inspired hierarchical structures were printed on films using additive manufacturing to achieve improved tear resistance and to facilitate membrane deployment. High precision, robust expandable structures can be realized using materials that are both space durable and processable using additive manufacturing. Test results show this initial work produced higher tear resistance than neat film of equivalent mass. Future research and development opportunities for expandable structural systems designed using an integrated approach to structural design, manufacturing, and materials selection are discussed.

  11. Experimental validation of optimization-based integrated controls-structures design methodology for flexible space structures

    NASA Technical Reports Server (NTRS)

    Maghami, Peiman G.; Gupta, Sandeep; Joshi, Suresh M.; Walz, Joseph E.

    1993-01-01

    An optimization-based integrated design approach for flexible space structures is experimentally validated using three types of dissipative controllers, including static, dynamic, and LQG dissipative controllers. The nominal phase-0 of the controls structure interaction evolutional model (CEM) structure is redesigned to minimize the average control power required to maintain specified root-mean-square line-of-sight pointing error under persistent disturbances. The redesign structure, phase-1 CEM, was assembled and tested against phase-0 CEM. It is analytically and experimentally demonstrated that integrated controls-structures design is substantially superior to that obtained through the traditional sequential approach. The capability of a software design tool based on an automated design procedure in a unified environment for structural and control designs is demonstrated.

  12. Comparison and integration of deleteriousness prediction methods for nonsynonymous SNVs in whole exome sequencing studies

    PubMed Central

    Dong, Chengliang; Wei, Peng; Jian, Xueqiu; Gibbs, Richard; Boerwinkle, Eric; Wang, Kai; Liu, Xiaoming

    2015-01-01

    Accurate deleteriousness prediction for nonsynonymous variants is crucial for distinguishing pathogenic mutations from background polymorphisms in whole exome sequencing (WES) studies. Although many deleteriousness prediction methods have been developed, their prediction results are sometimes inconsistent with each other and their relative merits are still unclear in practical applications. To address these issues, we comprehensively evaluated the predictive performance of 18 current deleteriousness-scoring methods, including 11 function prediction scores (PolyPhen-2, SIFT, MutationTaster, Mutation Assessor, FATHMM, LRT, PANTHER, PhD-SNP, SNAP, SNPs&GO and MutPred), 3 conservation scores (GERP++, SiPhy and PhyloP) and 4 ensemble scores (CADD, PON-P, KGGSeq and CONDEL). We found that FATHMM and KGGSeq had the highest discriminative power among independent scores and ensemble scores, respectively. Moreover, to ensure unbiased performance evaluation of these prediction scores, we manually collected three distinct testing datasets, on which no current prediction scores were tuned. In addition, we developed two new ensemble scores that integrate nine independent scores and allele frequency. Our scores achieved the highest discriminative power compared with all the deleteriousness prediction scores tested and showed low false-positive prediction rate for benign yet rare nonsynonymous variants, which demonstrated the value of combining information from multiple orthologous approaches. Finally, to facilitate variant prioritization in WES studies, we have pre-computed our ensemble scores for 87 347 044 possible variants in the whole-exome and made them publicly available through the ANNOVAR software and the dbNSFP database. PMID:25552646

  13. Comparison and integration of deleteriousness prediction methods for nonsynonymous SNVs in whole exome sequencing studies.

    PubMed

    Dong, Chengliang; Wei, Peng; Jian, Xueqiu; Gibbs, Richard; Boerwinkle, Eric; Wang, Kai; Liu, Xiaoming

    2015-04-15

    Accurate deleteriousness prediction for nonsynonymous variants is crucial for distinguishing pathogenic mutations from background polymorphisms in whole exome sequencing (WES) studies. Although many deleteriousness prediction methods have been developed, their prediction results are sometimes inconsistent with each other and their relative merits are still unclear in practical applications. To address these issues, we comprehensively evaluated the predictive performance of 18 current deleteriousness-scoring methods, including 11 function prediction scores (PolyPhen-2, SIFT, MutationTaster, Mutation Assessor, FATHMM, LRT, PANTHER, PhD-SNP, SNAP, SNPs&GO and MutPred), 3 conservation scores (GERP++, SiPhy and PhyloP) and 4 ensemble scores (CADD, PON-P, KGGSeq and CONDEL). We found that FATHMM and KGGSeq had the highest discriminative power among independent scores and ensemble scores, respectively. Moreover, to ensure unbiased performance evaluation of these prediction scores, we manually collected three distinct testing datasets, on which no current prediction scores were tuned. In addition, we developed two new ensemble scores that integrate nine independent scores and allele frequency. Our scores achieved the highest discriminative power compared with all the deleteriousness prediction scores tested and showed low false-positive prediction rate for benign yet rare nonsynonymous variants, which demonstrated the value of combining information from multiple orthologous approaches. Finally, to facilitate variant prioritization in WES studies, we have pre-computed our ensemble scores for 87 347 044 possible variants in the whole-exome and made them publicly available through the ANNOVAR software and the dbNSFP database. PMID:25552646

  14. A Tool Preference Choice Method for RNA Secondary Structure Prediction by SVM with Statistical Tests

    PubMed Central

    Hor, Chiou-Yi; Yang, Chang-Biau; Chang, Chia-Hung; Tseng, Chiou-Ting; Chen, Hung-Hsin

    2013-01-01

    The Prediction of RNA secondary structures has drawn much attention from both biologists and computer scientists. Many useful tools have been developed for this purpose. These tools have their individual strengths and weaknesses. As a result, based on support vector machines (SVM), we propose a tool choice method which integrates three prediction tools: pknotsRG, RNAStructure, and NUPACK. Our method first extracts features from the target RNA sequence, and adopts two information-theoretic feature selection methods for feature ranking. We propose a method to combine feature selection and classifier fusion in an incremental manner. Our test data set contains 720 RNA sequences, where 225 pseudoknotted RNA sequences are obtained from PseudoBase, and 495 nested RNA sequences are obtained from RNA SSTRAND. The method serves as a preprocessing way in analyzing RNA sequences before the RNA secondary structure prediction tools are employed. In addition, the performance of various configurations is subject to statistical tests to examine their significance. The best base-pair accuracy achieved is 75.5%, which is obtained by the proposed incremental method, and is significantly higher than 68.8%, which is associated with the best predictor, pknotsRG. PMID:23641141

  15. Integrative EEG biomarkers predict progression to Alzheimer's disease at the MCI stage

    PubMed Central

    Poil, Simon-Shlomo; de Haan, Willem; van der Flier, Wiesje M.; Mansvelder, Huibert D.; Scheltens, Philip; Linkenkaer-Hansen, Klaus

    2013-01-01

    Alzheimer's disease (AD) is a devastating disorder of increasing prevalence in modern society. Mild cognitive impairment (MCI) is considered a transitional stage between normal aging and AD; however, not all subjects with MCI progress to AD. Prediction of conversion to AD at an early stage would enable an earlier, and potentially more effective, treatment of AD. Electroencephalography (EEG) biomarkers would provide a non-invasive and relatively cheap screening tool to predict conversion to AD; however, traditional EEG biomarkers have not been considered accurate enough to be useful in clinical practice. Here, we aim to combine the information from multiple EEG biomarkers into a diagnostic classification index in order to improve the accuracy of predicting conversion from MCI to AD within a 2-year period. We followed 86 patients initially diagnosed with MCI for 2 years during which 25 patients converted to AD. We show that multiple EEG biomarkers mainly related to activity in the beta-frequency range (13–30 Hz) can predict conversion from MCI to AD. Importantly, by integrating six EEG biomarkers into a diagnostic index using logistic regression the prediction improved compared with the classification using the individual biomarkers, with a sensitivity of 88% and specificity of 82%, compared with a sensitivity of 64% and specificity of 62% of the best individual biomarker in this index. In order to identify this diagnostic index we developed a data mining approach implemented in the Neurophysiological Biomarker Toolbox (http://www.nbtwiki.net/). We suggest that this approach can be used to identify optimal combinations of biomarkers (integrative biomarkers) also in other modalities. Potentially, these integrative biomarkers could be more sensitive to disease progression and response to therapeutic intervention. PMID:24106478

  16. Integrated design of electrical distribution systems: Phase balancing and phase prediction case studies

    NASA Astrophysics Data System (ADS)

    Dilek, Murat

    Distribution system analysis and design has experienced a gradual development over the past three decades. The once loosely assembled and largely ad hoc procedures have been progressing toward being well-organized. The increasing power of computers now allows for managing the large volumes of data and other obstacles inherent to distribution system studies. A variety of sophisticated optimization methods, which were impossible to conduct in the past, have been developed and successfully applied to distribution systems. Among the many procedures that deal with making decisions about the state and better operation of a distribution system, two decision support procedures will be addressed in this study: phase balancing and phase prediction. The former recommends re-phasing of single- and double-phase laterals in a radial distribution system in order to improve circuit loss while also maintaining/improving imbalances at various balance point locations. Phase balancing calculations are based on circuit loss information and current magnitudes that are calculated from a power flow solution. The phase balancing algorithm is designed to handle time-varying loads when evaluating phase moves that will result in improved circuit losses over all load points. Applied to radial distribution systems, the phase prediction algorithm attempts to predict the phases of single- and/or double phase laterals that have no phasing information previously recorded by the electric utility. In such an attempt, it uses available customer data and kW/kVar measurements taken at various locations in the system. It is shown that phase balancing is a special case of phase prediction. Building on the phase balancing and phase prediction design studies, this work introduces the concept of integrated design, an approach for coordinating the effects of various design calculations. Integrated design considers using results of multiple design applications rather than employing a single application for a

  17. The Application of a Boundary Integral Equation Method to the Prediction of Ducted Fan Engine Noise

    NASA Technical Reports Server (NTRS)

    Dunn, M. H.; Tweed, J.; Farassat, F.

    1999-01-01

    The prediction of ducted fan engine noise using a boundary integral equation method (BIEM) is considered. Governing equations for the BIEM are based on linearized acoustics and describe the scattering of incident sound by a thin, finite-length cylindrical duct in the presence of a uniform axial inflow. A classical boundary value problem (BVP) is derived that includes an axisymmetric, locally reacting liner on the duct interior. Using potential theory, the BVP is recast as a system of hypersingular boundary integral equations with subsidiary conditions. We describe the integral equation derivation and solution procedure in detail. The development of the computationally efficient ducted fan noise prediction program TBIEM3D, which implements the BIEM, and its utility in conducting parametric noise reduction studies are discussed. Unlike prediction methods based on spinning mode eigenfunction expansions, the BIEM does not require the decomposition of the interior acoustic field into its radial and axial components which, for the liner case, avoids the solution of a difficult complex eigenvalue problem. Numerical spectral studies are presented to illustrate the nexus between the eigenfunction expansion representation and BIEM results. We demonstrate BIEM liner capability by examining radiation patterns for several cases of practical interest.

  18. A novel predictive control algorithm and robust stability criteria for integrating processes.

    PubMed

    Zhang, Bin; Yang, Weimin; Zong, Hongyuan; Wu, Zhiyong; Zhang, Weidong

    2011-07-01

    This paper introduces a novel predictive controller for single-input/single-output (SISO) integrating systems, which can be directly applied without pre-stabilizing the process. The control algorithm is designed on the basis of the tested step response model. To produce a bounded system response along the finite predictive horizon, the effect of the integrating mode must be zeroed while unmeasured disturbances exist. Here, a novel predictive feedback error compensation method is proposed to eliminate the permanent offset between the setpoint and the process output while the integrating system is affected by load disturbance. Also, a rotator factor is introduced in the performance index, which is contributed to the improvement robustness of the closed-loop system. Then on the basis of Jury's dominant coefficient criterion, a robust stability condition of the resulted closed loop system is given. There are only two parameters which need to be tuned for the controller, and each has a clear physical meaning, which is convenient for implementation of the control algorithm. Lastly, simulations are given to illustrate that the proposed algorithm can provide excellent closed loop performance compared with some reported methods. PMID:21353217

  19. Enhancing fatigue life of cylinder-crown integrated structure by optimizing dimension

    NASA Astrophysics Data System (ADS)

    Zhang, Weiwei; Wang, Xiaosong; Wang, Zhongren; Yuan, Shijian

    2015-03-01

    Cylinder-crown integrated hydraulic press (CCIHP) is a new press structure. The hemispherical hydraulic cylinder also functions as a main portion of crown, which has lower weight and higher section modulus compared with the conventional hydraulic cylinder and press crown. As a result, the material strength capacity is better utilized. During the engineering design of cylinder-crown integrated structure, in order to increase the fatigue life, structural optimization on the basis of the adaptive macro genetic algorithms (AMGA) is first conducted to both reduce weight and decrease peak stress. It is shown that the magnitude of the maximum principal stress is decreased by 28.6%, and simultaneously the total weight is reduced by 4.4%. Subsequently, strain-controlled fatigue test is carried out, and the stress-strain hysteresis loops and cyclic hardening curve are obtained. Based on linear fit, the fatigue properties are calculated and used for the fatigue life prediction. It is shown that the predicted fatigue life is significantly increased from 157000 to 1070000 cycles after structural optimization. Finally, according to the optimization design, a 6300 kN CCIHP has been manufactured, and priority application has been also suggested.

  20. Can benthic community structure be used to predict the process of bioturbation in real ecosystems?

    NASA Astrophysics Data System (ADS)

    Queirós, Ana M.; Stephens, Nicholas; Cook, Richard; Ravaglioli, Chiara; Nunes, Joana; Dashfield, Sarah; Harris, Carolyn; Tilstone, Gavin H.; Fishwick, James; Braeckman, Ulrike; Somerfield, Paul J.; Widdicombe, Stephen

    2015-09-01

    Disentangling the roles of environmental change and natural environmental variability on biologically mediated ecosystem processes is paramount to predict future marine ecosystem functioning. Bioturbation, the biogenic mixing of sediments, has a regulating role in marine biogeochemical processes. However, our understanding of bioturbation as a community level process and of its environmental drivers is still limited by loose use of terminology, and a lack of consensus about what bioturbation is. To help resolve these challenges, this empirical study investigated the links between four different attributes of bioturbation (bioturbation depth, activity and distance, and biodiffusive transport); the ability of an index of bioturbation (BPc) to predict each of them; and their relation to seasonality, in a shallow coastal system - the Western Channel Observatory, UK. Bioturbation distance depended on changes in benthic community structure, while the other three attributes were more directly influenced by seasonality in food availability. In parallel, BPc successfully predicted bioturbation distance but not the other attributes of bioturbation. This study therefore highlights that community bioturbation results from this combination of processes responding to environmental variability at different time-scales. However, community level measurements of bioturbation across environmental variability are still scarce, and BPc is calculated using commonly available data on benthic community structure and the functional classification of invertebrates. Therefore, BPc could be used to support the growth of landscape scale bioturbation research, but future uses of the index need to consider which bioturbation attributes the index actually predicts. As BPc predicts bioturbation distance, estimated here using a random-walk model applicable to community settings, studies using either of the metrics should be directly comparable and contribute to a more integrated future for

  1. RegPredict: an integrated system for regulon inference in prokaryotes by comparative genomics approach

    SciTech Connect

    Novichkov, Pavel S.; Rodionov, Dmitry A.; Stavrovskaya, Elena D.; Novichkova, Elena S.; Kazakov, Alexey E.; Gelfand, Mikhail S.; Arkin, Adam P.; Mironov, Andrey A.; Dubchak, Inna

    2010-05-26

    RegPredict web server is designed to provide comparative genomics tools for reconstruction and analysis of microbial regulons using comparative genomics approach. The server allows the user to rapidly generate reference sets of regulons and regulatory motif profiles in a group of prokaryotic genomes. The new concept of a cluster of co-regulated orthologous operons allows the user to distribute the analysis of large regulons and to perform the comparative analysis of multiple clusters independently. Two major workflows currently implemented in RegPredict are: (i) regulon reconstruction for a known regulatory motif and (ii) ab initio inference of a novel regulon using several scenarios for the generation of starting gene sets. RegPredict provides a comprehensive collection of manually curated positional weight matrices of regulatory motifs. It is based on genomic sequences, ortholog and operon predictions from the MicrobesOnline. An interactive web interface of RegPredict integrates and presents diverse genomic and functional information about the candidate regulon members from several web resources. RegPredict is freely accessible at http://regpredict.lbl.gov.

  2. Prediction of clinical phenotypes in invasive breast carcinomas from the integration of radiomics and genomics data

    PubMed Central

    Guo, Wentian; Li, Hui; Zhu, Yitan; Lan, Li; Yang, Shengjie; Drukker, Karen; Morris, Elizabeth; Burnside, Elizabeth; Whitman, Gary; Giger, Maryellen L.; Ji, Yuan; TCGA Breast Phenotype Research Group

    2015-01-01

    Abstract. Genomic and radiomic imaging profiles of invasive breast carcinomas from The Cancer Genome Atlas and The Cancer Imaging Archive were integrated and a comprehensive analysis was conducted to predict clinical outcomes using the radiogenomic features. Variable selection via LASSO and logistic regression were used to select the most-predictive radiogenomic features for the clinical phenotypes, including pathological stage, lymph node metastasis, and status of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Cross-validation with receiver operating characteristic (ROC) analysis was performed and the area under the ROC curve (AUC) was employed as the prediction metric. Higher AUCs were obtained in the prediction of pathological stage, ER, and PR status than for lymph node metastasis and HER2 status. Overall, the prediction performances by genomics alone, radiomics alone, and combined radiogenomics features showed statistically significant correlations with clinical outcomes; however, improvement on the prediction performance by combining genomics and radiomics data was not found to be statistically significant, most likely due to the small sample size of 91 cancer cases with 38 radiomic features and 144 genomic features. PMID:26835491

  3. Brain systems for probabilistic and dynamic prediction: computational specificity and integration.

    PubMed

    O'Reilly, Jill X; Jbabdi, Saad; Rushworth, Matthew F S; Behrens, Timothy E J

    2013-09-01

    A computational approach to functional specialization suggests that brain systems can be characterized in terms of the types of computations they perform, rather than their sensory or behavioral domains. We contrasted the neural systems associated with two computationally distinct forms of predictive model: a reinforcement-learning model of the environment obtained through experience with discrete events, and continuous dynamic forward modeling. By manipulating the precision with which each type of prediction could be used, we caused participants to shift computational strategies within a single spatial prediction task. Hence (using fMRI) we showed that activity in two brain systems (typically associated with reward learning and motor control) could be dissociated in terms of the forms of computations that were performed there, even when both systems were used to make parallel predictions of the same event. A region in parietal cortex, which was sensitive to the divergence between the predictions of the models and anatomically connected to both computational networks, is proposed to mediate integration of the two predictive modes to produce a single behavioral output.

  4. Early amplitude-integrated electroencephalography predicts brain injury and neurological outcome in very preterm infants

    PubMed Central

    Song, Juan; Xu, Falin; Wang, Laishuan; Gao, Liang; Guo, Jiajia; Xia, Lei; Zhang, Yanhua; Zhou, Wenhao; Wang, Xiaoyang; Zhu, Changlian

    2015-01-01

    Early amplitude-integrated electroencephalography (aEEG) has been widely used in term infants with brain injury to predict neurodevelopmental outcomes; however, the prognostic value of early aEEG in preterm infants is unclear. We evaluated how well early aEEG could predict brain damage and long-term neurodevelopmental outcomes in very preterm infants compared with brain imaging assessments. We found that severe aEEG abnormalities (p = 0.000) and aEEG total score < 5 (p = 0.006) within 72 h after birth were positively correlated with white-matter damage, but aEEG abnormalities were not associated with intracranial hemorrhage (p = 0.186). Severe abnormalities in aEEG recordings, head ultrasound, and cranial magnetic resonance imaging (MRI) were all positively correlated with poor outcome at 18 months corrected age. The predictive power of poor outcomes of the aEEG and MRI combination was the same as the aEEG, MRI, and head ultrasound combination with a sensitivity of 52.4%, specificity of 96.2%, positive predictive value of 78.6%, and negative predictive value of 88.4%. These results indicate that severely abnormal aEEG recordings within 72 h after birth can predict white-matter damage and long-term poor outcomes in very preterm infants. Thus aEEG can be used as an early marker to monitor very preterm infants. PMID:26348553

  5. Early amplitude-integrated electroencephalography predicts brain injury and neurological outcome in very preterm infants.

    PubMed

    Song, Juan; Xu, Falin; Wang, Laishuan; Gao, Liang; Guo, Jiajia; Xia, Lei; Zhang, Yanhua; Zhou, Wenhao; Wang, Xiaoyang; Zhu, Changlian

    2015-09-08

    Early amplitude-integrated electroencephalography (aEEG) has been widely used in term infants with brain injury to predict neurodevelopmental outcomes; however, the prognostic value of early aEEG in preterm infants is unclear. We evaluated how well early aEEG could predict brain damage and long-term neurodevelopmental outcomes in very preterm infants compared with brain imaging assessments. We found that severe aEEG abnormalities (p=0.000) and aEEG total score<5 (p=0.006) within 72 h after birth were positively correlated with white-matter damage, but aEEG abnormalities were not associated with intracranial hemorrhage (p=0.186). Severe abnormalities in aEEG recordings, head ultrasound, and cranial magnetic resonance imaging (MRI) were all positively correlated with poor outcome at 18 months corrected age. The predictive power of poor outcomes of the aEEG and MRI combination was the same as the aEEG, MRI, and head ultrasound combination with a sensitivity of 52.4%, specificity of 96.2%, positive predictive value of 78.6%, and negative predictive value of 88.4%. These results indicate that severely abnormal aEEG recordings within 72 h after birth can predict white-matter damage and long-term poor outcomes in very preterm infants. Thus aEEG can be used as an early marker to monitor very preterm infants.

  6. Fluorescence microscopy for the characterization of structural integrity

    NASA Technical Reports Server (NTRS)

    Street, Kenneth W.; Leonhardt, Todd A.

    1991-01-01

    The absorption characteristics of light and the optical technique of fluorescence microscopy for enhancing metallographic interpretation are presented. Characterization of thermally sprayed coatings by optical microscopy suffers because of the tendency for misidentification of the microstructure produced by metallographic preparation. Gray scale, in bright field microscopy, is frequently the only means of differentiating the actual structural details of porosity, cracking, and debonding of coatings. Fluorescence microscopy is a technique that helps to distinguish the artifacts of metallographic preparation (pullout, cracking, debonding) from the microstructure of the specimen by color contrasting structural differences. Alternative instrumentation and the use of other dye systems are also discussed. The combination of epoxy vacuum infiltration with fluorescence microscopy to verify microstructural defects is an effective means to characterize advanced materials and to assess structural integrity.

  7. Music and language perception: expectations, structural integration, and cognitive sequencing.

    PubMed

    Tillmann, Barbara

    2012-10-01

    Music can be described as sequences of events that are structured in pitch and time. Studying music processing provides insight into how complex event sequences are learned, perceived, and represented by the brain. Given the temporal nature of sound, expectations, structural integration, and cognitive sequencing are central in music perception (i.e., which sounds are most likely to come next and at what moment should they occur?). This paper focuses on similarities in music and language cognition research, showing that music cognition research provides insight into the understanding of not only music processing but also language processing and the processing of other structured stimuli. The hypothesis of shared resources between music and language processing and of domain-general dynamic attention has motivated the development of research to test music as a means to stimulate sensory, cognitive, and motor processes.

  8. Failure prediction of thin beryllium sheets used in spacecraft structures

    NASA Technical Reports Server (NTRS)

    Roschke, Paul N.; Mascorro, Edward; Papados, Photios; Serna, Oscar R.

    1991-01-01

    The primary objective of this study is to develop a method for prediction of failure of thin beryllium sheets that undergo complex states of stress. Major components of the research include experimental evaluation of strength parameters for cross-rolled beryllium sheet, application of the Tsai-Wu failure criterion to plate bending problems, development of a high order failure criterion, application of the new criterion to a variety of structures, and incorporation of both failure criteria into a finite element code. A Tsai-Wu failure model for SR-200 sheet material is developed from available tensile data, experiments carried out by NASA on two circular plates, and compression and off-axis experiments performed in this study. The failure surface obtained from the resulting criterion forms an ellipsoid. By supplementing experimental data used in the the two-dimensional criterion and modifying previously suggested failure criteria, a multi-dimensional failure surface is proposed for thin beryllium structures. The new criterion for orthotropic material is represented by a failure surface in six-dimensional stress space. In order to determine coefficients of the governing equation, a number of uniaxial, biaxial, and triaxial experiments are required. Details of these experiments and a complementary ultrasonic investigation are described in detail. Finally, validity of the criterion and newly determined mechanical properties is established through experiments on structures composed of SR200 sheet material. These experiments include a plate-plug arrangement under a complex state of stress and a series of plates with an out-of-plane central point load. Both criteria have been incorporated into a general purpose finite element analysis code. Numerical simulation incrementally applied loads to a structural component that is being designed and checks each nodal point in the model for exceedance of a failure criterion. If stresses at all locations do not exceed the failure

  9. Development of a Robust and Integrated Methodology for Predicting the Reliability of Microelectronic Packaging Systems

    NASA Astrophysics Data System (ADS)

    Fallah-Adl, Ali

    Ball Grid Array (BGA) using lead-free or lead-rich solder materials are widely used as Second Level Interconnects (SLI) in mounting packaged components to the printed circuit board (PCB). The reliability of these solder joints is of significant importance to the performance of microelectronics components and systems. Product design/form-factor, solder material, manufacturing process, use condition, as well as, the inherent variabilities present in the system, greatly influence product reliability. Accurate reliability analysis requires an integrated approach to concurrently account for all these factors and their synergistic effects. Such an integrated and robust methodology can be used in design and development of new and advanced microelectronics systems and can provide significant improvement in cycle-time, cost, and reliability. IMPRPK approach is based on a probabilistic methodology, focusing on three major tasks of (1) Characterization of BGA solder joints to identify failure mechanisms and obtain statistical data, (2) Finite Element analysis (FEM) to predict system response needed for life prediction, and (3) development of a probabilistic methodology to predict the reliability, as well as, the sensitivity of the system to various parameters and the variabilities. These tasks and the predictive capabilities of IMPRPK in microelectronic reliability analysis are discussed.

  10. Focused attention vs. crossmodal signals paradigm: deriving predictions from the time-window-of-integration model.

    PubMed

    Colonius, Hans; Diederich, Adele

    2012-01-01

    In the crossmodal signals paradigm (CSP) participants are instructed to respond to a set of stimuli from different modalities, presented more or less simultaneously, as soon as a stimulus from any modality has been detected. In the focused attention paradigm (FAP), on the other hand, responses should only be made to a stimulus from a pre-defined target modality and stimuli from non-target modalities should be ignored. Whichever paradigm is being applied, a typical result is that responses tend to be faster to crossmodal stimuli than to unimodal stimuli, a phenomenon often referred to as "crossmodal interaction." Here, we investigate predictions of the time-window-of-integration (TWIN) modeling framework previously proposed by the authors. It is shown that TWIN makes specific qualitative and quantitative predictions on how the two paradigms differ with respect to the probability of multisensory integration and the amount of response enhancement, including the effect of stimulus intensity ("inverse effectiveness"). Introducing a decision-theoretic framework for TWIN further allows comparing the two paradigms with respect to the predicted optimal time window size and its dependence on the prior probability that the crossmodal stimulus information refers to the same event. In order to test these predictions, experimental studies that systematically compare crossmodal effects under stimulus conditions that are identical except for the CSP-FAP instruction should be performed in the future. PMID:22952460

  11. Predicting young adults' intentions to get the H1N1 vaccine: an integrated model.

    PubMed

    Yang, Z Janet

    2015-01-01

    Young adults 19 through 24 years of age were among the populations that had the highest frequency of infection from the 2009 H1N1 pandemic. However, over the 2009-2010 flu season, H1N1 vaccine uptake among college students nationwide was around 8%. To explore the social cognitive factors that influenced their intentions to get the H1N1 vaccine, this study compares the predictive power of the theory of planned behavior (TPB), the health belief model (HBM), and an integrated model. The final model shows that several HBM variables influenced behavioral intentions through the TPB variables. The results suggest that even though the TPB seemed a superior model for behavior prediction, the addition of the HBM variables could inform future theory development by offering health-specific constructs that potentially enhance the predictive validity of TPB variables. PMID:24870976

  12. Cross-scale integration of knowledge for predicting species ranges: a metamodeling framework

    PubMed Central

    Talluto, Matthew V.; Boulangeat, Isabelle; Ameztegui, Aitor; Aubin, Isabelle; Berteaux, Dominique; Butler, Alyssa; Doyon, Frédérik; Drever, C. Ronnie; Fortin, Marie-Josée; Franceschini, Tony; Liénard, Jean; McKenney, Dan; Solarik, Kevin A.; Strigul, Nikolay; Thuiller, Wilfried; Gravel, Dominique

    2016-01-01

    Aim Current interest in forecasting changes to species ranges have resulted in a multitude of approaches to species distribution models (SDMs). However, most approaches include only a small subset of the available information, and many ignore smaller-scale processes such as growth, fecundity, and dispersal. Furthermore, different approaches often produce divergent predictions with no simple method to reconcile them. Here, we present a flexible framework for integrating models at multiple scales using hierarchical Bayesian methods. Location Eastern North America (as an example). Methods Our framework builds a metamodel that is constrained by the results of multiple sub-models and provides probabilistic estimates of species presence. We applied our approach to a simulated dataset to demonstrate the integration of a correlative SDM with a theoretical model. In a second example, we built an integrated model combining the results of a physiological model with presence-absence data for sugar maple (Acer saccharum), an abundant tree native to eastern North America. Results For both examples, the integrated models successfully included information from all data sources and substantially improved the characterization of uncertainty. For the second example, the integrated model outperformed the source models with respect to uncertainty when modelling the present range of the species. When projecting into the future, the model provided a consensus view of two models that differed substantially in their predictions. Uncertainty was reduced where the models agreed and was greater where they diverged, providing a more realistic view of the state of knowledge than either source model. Main conclusions We conclude by discussing the potential applications of our method and its accessibility to applied ecologists. In ideal cases, our framework can be easily implemented using off-the-shelf software. The framework has wide potential for use in species distribution modelling and can

  13. Spatial structural integrity is important for adipose regeneration after transplantation.

    PubMed

    Yuan, Yi; Zhang, Shu; Gao, Jianhua; Lu, Feng

    2015-10-01

    Advances in structural fat transplantation technology have significantly improved the survival rate and stability of grafts. This study investigated the importance of the spatial structural integrity of adipose tissue for adipose regeneration after fat transplantation. We sought to enhance understanding of structural fat transplantation and optimize procedures used for the clinical acquisition, purification, and transplantation of adipose tissue. In an inactivated structuration adipose tissue model established by freezing at -20 °C for 3 days, nearly all cells were dead but the structure was intact. We transplanted this adipose tissue model (group A) or non-treated adipose tissue (group B) into GFP-expressing mice. Group B showed a higher graft survival percentage and less fibrosis than group A. The macrophage infiltration (F4/80) peak period was longer in group A than in group B. The change in vessel density (CD31) was similar in the two groups: it peaked at 4 weeks after transplantation and decreased thereafter. In both groups, the number of Ki67+ cells showed a similar trend. In comparison to group B, group A had more Ki67+ cells at 4-8 weeks after transplantation, but fewer of these cells at 12 weeks after transplantation. The intact spatial structure of adipose tissue, which is supported by adipocytes and extracellular matrix, provides a niche for adipogenesis and angiogenesis after fat transplantation.

  14. Structural Damage Prediction and Analysis for Hypervelocity Impact

    NASA Technical Reports Server (NTRS)

    Elfer, Norman

    1995-01-01

    It is necessary to integrate a wide variety of technical disciplines to provide an analysis of structural damage to a spacecraft due to hypervelocity impact. There are many uncertainties, and more detailed investigation is warranted, in each technical discipline. However, a total picture of the debris and meteoroid hazard is required to support manned spaceflight in general, and the international Space Station in particular. In the performance of this contract, besides producing a handbook, research and development was conducted in several different areas. The contract was broken into six separate tasks. Each task objectives and accomplishments will be reviewed in the following sections. The Handbook and separate task reports are contained as attachments to the final report. The final section summarizes all of the recommendations coming out of this study. The analyses and comments are general design guidelines and not necessarily applicable to final Space Station designs since several configuration and detailed design changes were being made during the course of this contract. Rather, the analyses and comments may indicate either a point-in-time concept analysis, available test data, or desirable protection goals, not hindered by the design and operation constraints faced by Space Station designers.

  15. Structural kinematics based damage zone prediction in gradient structures using vibration database

    NASA Astrophysics Data System (ADS)

    Talha, Mohammad; Ashokkumar, Chimpalthradi R.

    2014-05-01

    To explore the applications of functionally graded materials (FGMs) in dynamic structures, structural kinematics based health monitoring technique becomes an important problem. Depending upon the displacements in three dimensions, the health of the material to withstand dynamic loads is inferred in this paper, which is based on the net compressive and tensile displacements that each structural degree of freedom takes. These net displacements at each finite element node predicts damage zones of the FGM where the material is likely to fail due to a vibration response which is categorized according to loading condition. The damage zone prediction of a dynamically active FGMs plate have been accomplished using Reddy's higher-order theory. The constituent material properties are assumed to vary in the thickness direction according to the power-law behavior. The proposed C0 finite element model (FEM) is applied to get net tensile and compressive displacement distributions across the structures. A plate made of Aluminum/Ziconia is considered to illustrate the concept of structural kinematics-based health monitoring aspects of FGMs.

  16. Detecting and representing predictable structure during auditory scene analysis.

    PubMed

    Sohoglu, Ediz; Chait, Maria

    2016-01-01

    We use psychophysics and MEG to test how sensitivity to input statistics facilitates auditory-scene-analysis (ASA). Human subjects listened to 'scenes' comprised of concurrent tone-pip streams (sources). On occasional trials a new source appeared partway. Listeners were more accurate and quicker to detect source appearance in scenes comprised of temporally-regular (REG), rather than random (RAND), sources. MEG in passive listeners and those actively detecting appearance events revealed increased sustained activity in auditory and parietal cortex in REG relative to RAND scenes, emerging ~400 ms of scene-onset. Over and above this, appearance in REG scenes was associated with increased responses relative to RAND scenes. The effect of temporal structure on appearance-evoked responses was delayed when listeners were focused on the scenes relative to when listening passively, consistent with the notion that attention reduces 'surprise'. Overall, the results implicate a mechanism that tracks predictability of multiple concurrent sources to facilitate active and passive ASA. PMID:27602577

  17. Detecting and representing predictable structure during auditory scene analysis

    PubMed Central

    Sohoglu, Ediz; Chait, Maria

    2016-01-01

    We use psychophysics and MEG to test how sensitivity to input statistics facilitates auditory-scene-analysis (ASA). Human subjects listened to ‘scenes’ comprised of concurrent tone-pip streams (sources). On occasional trials a new source appeared partway. Listeners were more accurate and quicker to detect source appearance in scenes comprised of temporally-regular (REG), rather than random (RAND), sources. MEG in passive listeners and those actively detecting appearance events revealed increased sustained activity in auditory and parietal cortex in REG relative to RAND scenes, emerging ~400 ms of scene-onset. Over and above this, appearance in REG scenes was associated with increased responses relative to RAND scenes. The effect of temporal structure on appearance-evoked responses was delayed when listeners were focused on the scenes relative to when listening passively, consistent with the notion that attention reduces ‘surprise’. Overall, the results implicate a mechanism that tracks predictability of multiple concurrent sources to facilitate active and passive ASA. DOI: http://dx.doi.org/10.7554/eLife.19113.001 PMID:27602577

  18. Composite failure prediction of π-joint structures under bending

    NASA Astrophysics Data System (ADS)

    Huang, Hong-mei; Yuan, Shen-fang

    2012-03-01

    In this article, the composite -joint is investigated under bending loads. The "L" preform is the critical component regarding composite -joint failure. The study is presented in the failure detection of a carbon fiber composite -joint structure under bending loads using fiber Bragg grating (FBG) sensor. Firstly, based on the general finite element method (FEM) software, the 3-D finite element (FE) model of composite -joint is established, and the failure process and every lamina failure load of composite -joint are investigated by maximum stress criteria. Then, strain distributions along the length of FBG are extracted, and the reflection spectra of FBG are calculated according to the strain distribution. Finally, to verify the numerical results, a test scheme is performed and the experimental spectra of FBG are recorded. The experimental results indicate that the failure sequence and the corresponding critical loads of failure are consistent with the numerical predictions, and the computational error of failure load is less than 6.4%. Furthermore, it also verifies the feasibility of the damage detection system.

  19. Prediction of Silicon-Based Layered Structures for Optoelectronic Applications

    NASA Astrophysics Data System (ADS)

    Luo, Wei; Ma, Yanming; Gong, Xingao; Xiang, Hongjun; CCMG Team

    2015-03-01

    A method based on the particle swarm optimization (PSO) algorithm is presented to design quasi-two-dimensional (Q2D) materials. With this development, various single-layer and bi-layer materials in C, Si, Ge, Sn, and Pb were predicted. A new Si bi-layer structure is found to have a much-favored energy than the previously widely accepted configuration. Both single-layer and bi-layer Si materials have small band gaps, limiting their usages in optoelectronic applications. Hydrogenation has therefore been used to tune the electronic and optical properties of Si layers. We discover two hydrogenated materials of layered Si8H2andSi6H2 possessing quasi-direct band gaps of 0.75 eV and 1.59 eV, respectively. Their potential applications for light emitting diode and photovoltaics are proposed and discussed. Our study opened up the possibility of hydrogenated Si layered materials as next-generation optoelectronic devices.

  20. Predictive modeling of pedestal structure in KSTAR using EPED model

    SciTech Connect

    Han, Hyunsun; Kim, J. Y.; Kwon, Ohjin

    2013-10-15

    A predictive calculation is given for the structure of edge pedestal in the H-mode plasma of the KSTAR (Korea Superconducting Tokamak Advanced Research) device using the EPED model. Particularly, the dependence of pedestal width and height on various plasma parameters is studied in detail. The two codes, ELITE and HELENA, are utilized for the stability analysis of the peeling-ballooning and kinetic ballooning modes, respectively. Summarizing the main results, the pedestal slope and height have a strong dependence on plasma current, rapidly increasing with it, while the pedestal width is almost independent of it. The plasma density or collisionality gives initially a mild stabilization, increasing the pedestal slope and height, but above some threshold value its effect turns to a destabilization, reducing the pedestal width and height. Among several plasma shape parameters, the triangularity gives the most dominant effect, rapidly increasing the pedestal width and height, while the effect of elongation and squareness appears to be relatively weak. Implication of these edge results, particularly in relation to the global plasma performance, is discussed.

  1. Structure of an integral membrane sterol reductase from Methylomicrobium alcaliphilum

    PubMed Central

    Li, Xiaochun; Roberti, Rita; Blobel, Günter

    2014-01-01

    Sterols are essential biological molecules in the majority of life forms. Sterol reductases1 including Delta-14 sterol reductase (C14SR), 7-dehydrocholesterol reductase (DHCR7) and 24-dehydrocholesterol reductase (DHCR24) reduce specific carbon-carbon double bonds of the sterol moiety using a reducing cofactor during sterol biosynthesis. Lamin B Receptor2 (LBR), an integral inner nuclear membrane protein, also contains a functional C14SR domain. Here we report the crystal structure of a Delta-14 sterol reductase (maSR1) from the methanotrophic bacterium Methylomicrobium alcaliphilum 20Z, a homolog of human C14SR, LBR, and DHCR7, with the cofactor NADPH. The enzyme contains 10 transmembrane segments (TM). Its catalytic domain comprises the C-terminal half (containing TM6-10) and envelops two interconnected pockets, one of which faces the cytoplasm and houses NADPH, while the other one is accessible from the lipid bilayer. Comparison with a soluble steroid 5β-reductase structure3 suggests that the reducing end of NADPH meets the sterol substrate at the juncture of the two pockets. A sterol reductase activity assay proves maSR1 can reduce the double bond of a cholesterol biosynthetic intermediate demonstrating functional conservation to human C14SR. Therefore, our structure as a prototype of integral membrane sterol reductases provides molecular insight into mutations in DHCR7 and LBR for inborn human diseases. PMID:25307054

  2. Recursive protein modeling: a divide and conquer strategy for Protein Structure Prediction and its case study in CASP9.

    PubMed

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

    2012-06-01

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

  3. Integrating seasonal climate prediction and agricultural models for insights into agricultural practice

    PubMed Central

    Hansen, James W

    2005-01-01

    Interest in integrating crop simulation models with dynamic seasonal climate forecast models is expanding in response to a perceived opportunity to add value to seasonal climate forecasts for agriculture. Integrated modelling may help to address some obstacles to effective agricultural use of climate information. First, modelling can address the mismatch between farmers' needs and available operational forecasts. Probabilistic crop yield forecasts are directly relevant to farmers' livelihood decisions and, at a different scale, to early warning and market applications. Second, credible ex ante evidence of livelihood benefits, using integrated climate–crop–economic modelling in a value-of-information framework, may assist in the challenge of obtaining institutional, financial and political support; and inform targeting for greatest benefit. Third, integrated modelling can reduce the risk and learning time associated with adaptation and adoption, and related uncertainty on the part of advisors and advocates. It can provide insights to advisors, and enhance site-specific interpretation of recommendations when driven by spatial data. Model-based ‘discussion support systems’ contribute to learning and farmer–researcher dialogue. Integrated climate–crop modelling may play a genuine, but limited role in efforts to support climate risk management in agriculture, but only if they are used appropriately, with understanding of their capabilities and limitations, and with cautious evaluation of model predictions and of the insights that arises from model-based decision analysis. PMID:16433092

  4. ESB-Based Sensor Web Integration for the Prediction of Electric Power Supply System Vulnerability

    PubMed Central

    Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

    2013-01-01

    Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application. PMID:23955435

  5. ESB-based Sensor Web integration for the prediction of electric power supply system vulnerability.

    PubMed

    Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

    2013-08-15

    Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application.

  6. Prediction of Metabolic Gene Biomarkers for Neurodegenerative Disease by an Integrated Network-Based Approach

    PubMed Central

    Su, Xianming

    2015-01-01

    Neurodegenerative diseases (NDs), such as Parkinson's disease (PD) and Huntington's disease (HD), have become more and more common among aged people worldwide. One hallmark of NDs is the presence of intracellular accumulation of specific pathogenic proteins that may result from abnormal function of metabolic processes. Previously, we have developed a computational method named Met-express that predicted key enzyme-coding genes in cancer development by integrating cancer gene coexpression network with the metabolic network. Here, we applied Met-express to predict key enzyme-coding genes in both PD and HD. Functional enrichment analysis and literature review of predicted genes suggested that there might be some common pathogenic metabolic pathways for PD and HD. We further found that the predicted genes had significant functional association with known disease genes, with some of them already documented as biomarkers or therapeutic targets for NDs. As such, the predicted metabolic genes may be of use as novel biomarkers not only for ND diagnosis but also for potential therapeutic treatments. PMID:26064912

  7. The integration of ground investigations and radar images on rice yield prediction

    NASA Astrophysics Data System (ADS)

    Syu, Chien-Hui; Lo, Wei-Shen; Guo, Horng-Yuh

    2016-04-01

    Rice is the staple food and the largest crop in terms of area in Taiwan. Developing the real-time and accurate methods to predict rice yield of large area is important for food security. However, due to the size of rice fields is small and fragmented, and the disturbed weather in Taiwan. It difficult to acquire the information of cropping area and rice yield by optical satellite data, such as SPOT and FORMOSAT-2, because of the cloud cover commonly observed in the region. In contrast, the RADARSAT image data can overcome such problems due to which can penetrate through cloud. The aim of this study is to integrate the data of ground investigations and radar images to predict the rice yield of large area. We used the data of rice yield (ground investigation) and radar images to do regression analysis, and then predict the rice yield of large area. The results of ground investigation indicated that there were high correlation between sample sites yield and real harvest yield (R2 = 0.99), it reveals the investigating method has a high representativeness. The results of the prediction of rice yield by multi-temporal radar images indicated that there was high correlation between ground trust and yield estimation (R2 = 0.68, proof data, 6 fields), and the yield estimation accuracy is higher than 85%. Therefore, this study suggests the application of multi-temporal radar image data can effective and accurate to predict the paddy rice yield in Taiwan.

  8. SHELXT - integrated space-group and crystal-structure determination.

    PubMed

    Sheldrick, George M

    2015-01-01

    The new computer program SHELXT employs a novel dual-space algorithm to solve the phase problem for single-crystal reflection data expanded to the space group P1. Missing data are taken into account and the resolution extended if necessary. All space groups in the specified Laue group are tested to find which are consistent with the P1 phases. After applying the resulting origin shifts and space-group symmetry, the solutions are subject to further dual-space recycling followed by a peak search and summation of the electron density around each peak. Elements are assigned to give the best fit to the integrated peak densities and if necessary additional elements are considered. An isotropic refinement is followed for non-centrosymmetric space groups by the calculation of a Flack parameter and, if appropriate, inversion of the structure. The structure is assembled to maximize its connectivity and centred optimally in the unit cell. SHELXT has already solved many thousand structures with a high success rate, and is optimized for multiprocessor computers. It is, however, unsuitable for severely disordered and twinned structures because it is based on the assumption that the structure consists of atoms.

  9. Controls-structures integrated design optimization with shape variations

    NASA Technical Reports Server (NTRS)

    Koganti, Gopichand; Hou, Gene

    1993-01-01

    The shape design variables have been introduced into the set of design variables of the Controls-Structure Integrated (CSI) Design of space-structures. The importance of the shape variations in improving the design (obtained with only control and sizing variables) has been aptly illustrated. Two different types of design variables that describe the shape variations of the structure have been introduced. In the first case, the nodal coordinates have been considered as design variables. This has the inherent difficulty of having too many design variables. This not only is time consuming but also memory intensive and may not yield a manufacturable shape to the structure. The second approach has been introduced to overcome this difficulty. The structure is allowed to vary in a particular pre defined pattern. The coefficients of these patterns are considered as the shape design variables. The eigenvalue and eigenvector sensitivity equations with respect to these coefficient design variables have been developed and are used to approximate the eigenvalues and eigenvectors in a perturbed design.

  10. The effect of thermal stresses on the integrity of three built-up aircraft structures

    NASA Technical Reports Server (NTRS)

    Jenkins, J. M.

    1980-01-01

    A Mach 6 flight was simulated in order to examine heating effects on three frame/skin specimens. The specimens included: a titanium truss frame with a lockalloy skin; a stainless steel z-frame with a lockalloy skin; and a titanium z-frame with a lockalloy skin. Thermal stresses and temperature were measured on these specimens for the purpose of examining their efficiency, performance, and integrity. Measured thermal stresses were examined with respect to material yield strengths, buckling criteria, structural weight, and geometric locations. Principal thermal stresses were studied from the standpoint of uniaxial stress assumptions. Measured thermal stresses were compared to predicted values.

  11. A pathway-based data integration framework for prediction of disease progression

    PubMed Central

    Seoane, José A.; Day, Ian N. M.; Gaunt, Tom R.; Campbell, Colin

    2014-01-01

    Motivation: Within medical research there is an increasing trend toward deriving multiple types of data from the same individual. The most effective prognostic prediction methods should use all available data, as this maximizes the amount of information used. In this article, we consider a variety of learning strategies to boost prediction performance based on the use of all available data. Implementation: We consider data integration via the use of multiple kernel learning supervised learning methods. We propose a scheme in which feature selection by statistical score is performed separately per data type and by pathway membership. We further consider the introduction of a confidence measure for the class assignment, both to remove some ambiguously labeled datapoints from the training data and to implement a cautious classifier that only makes predictions when the associated confidence is high. Results: We use the METABRIC dataset for breast cancer, with prediction of survival at 2000 days from diagnosis. Predictive accuracy is improved by using kernels that exclusively use those genes, as features, which are known members of particular pathways. We show that yet further improvements can be made by using a range of additional kernels based on clinical covariates such as Estrogen Receptor (ER) status. Using this range of measures to improve prediction performance, we show that the test accuracy on new instances is nearly 80%, though predictions are only made on 69.2% of the patient cohort. Availability: https://github.com/jseoane/FSMKL Contact: J.Seoane@bristol.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24162466

  12. Evaluation and integration of existing methods for computational prediction of allergens

    PubMed Central

    2013-01-01

    Background Allergy involves a series of complex reactions and factors that contribute to the development of the disease and triggering of the symptoms, including rhinitis, asthma, atopic eczema, skin sensitivity, even acute and fatal anaphylactic shock. Prediction and evaluation of the potential allergenicity is of importance for safety evaluation of foods and other environment factors. Although several computational approaches for assessing the potential allergenicity of proteins have been developed, their performance and relative merits and shortcomings have not been compared systematically. Results To evaluate and improve the existing methods for allergen prediction, we collected an up-to-date definitive dataset consisting of 989 known allergens and massive putative non-allergens. The three most widely used allergen computational prediction approaches including sequence-, motif- and SVM-based (Support Vector Machine) methods were systematically compared using the defined parameters and we found that SVM-based method outperformed the other two methods with higher accuracy and specificity. The sequence-based method with the criteria defined by FAO/WHO (FAO: Food and Agriculture Organization of the United Nations; WHO: World Health Organization) has higher sensitivity of over 98%, but having a low specificity. The advantage of motif-based method is the ability to visualize the key motif within the allergen. Notably, the performances of the sequence-based method defined by FAO/WHO and motif eliciting strategy could be improved by the optimization of parameters. To facilitate the allergen prediction, we integrated these three methods in a web-based application proAP, which provides the global search of the known allergens and a powerful tool for allergen predication. Flexible parameter setting and batch prediction were also implemented. The proAP can be accessed at http://gmobl.sjtu.edu.cn/proAP/main.html. Conclusions This study comprehensively evaluated sequence

  13. Assessing time-