Learning about the internal structure of categories through classification and feature inference.

PubMed

Jee, Benjamin D; Wiley, Jennifer

2014-01-01

Previous research on category learning has found that classification tasks produce representations that are skewed toward diagnostic feature dimensions, whereas feature inference tasks lead to richer representations of within-category structure. Yet, prior studies often measure category knowledge through tasks that involve identifying only the typical features of a category. This neglects an important aspect of a category's internal structure: how typical and atypical features are distributed within a category. The present experiments tested the hypothesis that inference learning results in richer knowledge of internal category structure than classification learning. We introduced several new measures to probe learners' representations of within-category structure. Experiment 1 found that participants in the inference condition learned and used a wider range of feature dimensions than classification learners. Classification learners, however, were more sensitive to the presence of atypical features within categories. Experiment 2 provided converging evidence that classification learners were more likely to incorporate atypical features into their representations. Inference learners were less likely to encode atypical category features, even in a "partial inference" condition that focused learners' attention on the feature dimensions relevant to classification. Overall, these results are contrary to the hypothesis that inference learning produces superior knowledge of within-category structure. Although inference learning promoted representations that included a broad range of category-typical features, classification learning promoted greater sensitivity to the distribution of typical and atypical features within categories.

Feature-Based Morphometry: Discovering Group-related Anatomical Patterns

PubMed Central

Toews, Matthew; Wells, William; Collins, D. Louis; Arbel, Tal

2015-01-01

This paper presents feature-based morphometry (FBM), a new, fully data-driven technique for discovering patterns of group-related anatomical structure in volumetric imagery. In contrast to most morphometry methods which assume one-to-one correspondence between subjects, FBM explicitly aims to identify distinctive anatomical patterns that may only be present in subsets of subjects, due to disease or anatomical variability. The image is modeled as a collage of generic, localized image features that need not be present in all subjects. Scale-space theory is applied to analyze image features at the characteristic scale of underlying anatomical structures, instead of at arbitrary scales such as global or voxel-level. A probabilistic model describes features in terms of their appearance, geometry, and relationship to subject groups, and is automatically learned from a set of subject images and group labels. Features resulting from learning correspond to group-related anatomical structures that can potentially be used as image biomarkers of disease or as a basis for computer-aided diagnosis. The relationship between features and groups is quantified by the likelihood of feature occurrence within a specific group vs. the rest of the population, and feature significance is quantified in terms of the false discovery rate. Experiments validate FBM clinically in the analysis of normal (NC) and Alzheimer's (AD) brain images using the freely available OASIS database. FBM automatically identifies known structural differences between NC and AD subjects in a fully data-driven fashion, and an equal error classification rate of 0.80 is achieved for subjects aged 60-80 years exhibiting mild AD (CDR=1). PMID:19853047

New breast cancer prognostic factors identified by computer-aided image analysis of HE stained histopathology images

PubMed Central

Chen, Jia-Mei; Qu, Ai-Ping; Wang, Lin-Wei; Yuan, Jing-Ping; Yang, Fang; Xiang, Qing-Ming; Maskey, Ninu; Yang, Gui-Fang; Liu, Juan; Li, Yan

2015-01-01

Computer-aided image analysis (CAI) can help objectively quantify morphologic features of hematoxylin-eosin (HE) histopathology images and provide potentially useful prognostic information on breast cancer. We performed a CAI workflow on 1,150 HE images from 230 patients with invasive ductal carcinoma (IDC) of the breast. We used a pixel-wise support vector machine classifier for tumor nests (TNs)-stroma segmentation, and a marker-controlled watershed algorithm for nuclei segmentation. 730 morphologic parameters were extracted after segmentation, and 12 parameters identified by Kaplan-Meier analysis were significantly associated with 8-year disease free survival (P < 0.05 for all). Moreover, four image features including TNs feature (HR 1.327, 95%CI [1.001 - 1.759], P = 0.049), TNs cell nuclei feature (HR 0.729, 95%CI [0.537 - 0.989], P = 0.042), TNs cell density (HR 1.625, 95%CI [1.177 - 2.244], P = 0.003), and stromal cell structure feature (HR 1.596, 95%CI [1.142 - 2.229], P = 0.006) were identified by multivariate Cox proportional hazards model to be new independent prognostic factors. The results indicated that CAI can assist the pathologist in extracting prognostic information from HE histopathology images for IDC. The TNs feature, TNs cell nuclei feature, TNs cell density, and stromal cell structure feature could be new prognostic factors. PMID:26022540

Unraveling Appalachian tectonics: domain analysis of topographic lineaments in Pennsylvania

NASA Astrophysics Data System (ADS)

Karimi, B.; Schon, K.; Nussbaum, G. W.; Storer, N. D.; McGuire, J. L.; Hardcastle, K.

2016-12-01

Litho-tectonic provinces provide different components of a regions' tectonic history, and are identified as spatial entities with common structural elements, or a number of contiguous related elements. The province boundaries are easily identified when geomorphic expressions are distinct, or significant rock exposure allows for little uncertainty. When exposures are limited, locations of boundaries between provinces are uncertain. In such instances, satellite imagery can be quite advantageous, as tectonically sourced features (faults, folds, fractures, and joints) may exert a strong control on topographic patterns by creating pathways for weathering and erosion. Lineament analyses of topography often focus on well-pronounced tectonic features to interpret regional tectonics. We suggest that lineament analyses including all topographic features may include more subtle tectonic features, resulting in the identification of minor heterogeneities within litho-tectonic provinces. Our study focuses on Appalachian tectonics, specifically in Pennsylvania (PA), home to the Appalachian Orocline and 5 distinct tectonic provinces. Using hillshades from a digital elevation model (DEM) of PA, we manually pick all topographic lineaments 1 km or greater, discriminating only against man-made structures. The final lineament coverage of the state is subdivided into smaller areas for which rose diagrams were prepared. The dominant lineament trends were compared and associated with known structural features. Peaks with no known source are marked as possible tectonic features requiring further research. A domain analysis is performed on the lineament data to identify the extent and interplay of swarms, followed by an investigation of their azimuthal compatibility. We present the results of our domain analysis of all topographic lineaments in the context of identifying litho-tectonic provinces associated with Appalachian tectonics in Pennsylvania, and possible heterogeneities within them.

On the structural context and identification of enzyme catalytic residues.

PubMed

Chien, Yu-Tung; Huang, Shao-Wei

2013-01-01

Enzymes play important roles in most of the biological processes. Although only a small fraction of residues are directly involved in catalytic reactions, these catalytic residues are the most crucial parts in enzymes. The study of the fundamental and unique features of catalytic residues benefits the understanding of enzyme functions and catalytic mechanisms. In this work, we analyze the structural context of catalytic residues based on theoretical and experimental structure flexibility. The results show that catalytic residues have distinct structural features and context. Their neighboring residues, whether sequence or structure neighbors within specific range, are usually structurally more rigid than those of noncatalytic residues. The structural context feature is combined with support vector machine to identify catalytic residues from enzyme structure. The prediction results are better or comparable to those of recent structure-based prediction methods.

Geological map of parts of the state of Sao Paulo based on LANDSAT images. [Brazil

NASA Technical Reports Server (NTRS)

Dejususparada, N. (Principal Investigator); Amaral, G.; Liu, C. C.; Filho, R. A.

1979-01-01

The author has identified the following significant results. Interpretation of LANDSAT images revealed the subdivision of the Bauru formation into three distinct lithofacies. Delineation of structural features yielded new information on paleoenvironmental reconstitution and hydrogeology. Structural features and photogeological units were revealed in the precambrian basement at the eastern portion of the state.

Money-center structures in dynamic banking systems

NASA Astrophysics Data System (ADS)

Li, Shouwei; Zhang, Minghui

2016-10-01

In this paper, we propose a dynamic model for banking systems based on the description of balance sheets. It generates some features identified through empirical analysis. Through simulation analysis of the model, we find that banking systems have the feature of money-center structures, that bank asset distributions are power-law distributions, and that contract size distributions are log-normal distributions.

Prediction of plant pre-microRNAs and their microRNAs in genome-scale sequences using structure-sequence features and support vector machine.

PubMed

Meng, Jun; Liu, Dong; Sun, Chao; Luan, Yushi

2014-12-30

MicroRNAs (miRNAs) are a family of non-coding RNAs approximately 21 nucleotides in length that play pivotal roles at the post-transcriptional level in animals, plants and viruses. These molecules silence their target genes by degrading transcription or suppressing translation. Studies have shown that miRNAs are involved in biological responses to a variety of biotic and abiotic stresses. Identification of these molecules and their targets can aid the understanding of regulatory processes. Recently, prediction methods based on machine learning have been widely used for miRNA prediction. However, most of these methods were designed for mammalian miRNA prediction, and few are available for predicting miRNAs in the pre-miRNAs of specific plant species. Although the complete Solanum lycopersicum genome has been published, only 77 Solanum lycopersicum miRNAs have been identified, far less than the estimated number. Therefore, it is essential to develop a prediction method based on machine learning to identify new plant miRNAs. A novel classification model based on a support vector machine (SVM) was trained to identify real and pseudo plant pre-miRNAs together with their miRNAs. An initial set of 152 novel features related to sequential structures was used to train the model. By applying feature selection, we obtained the best subset of 47 features for use with the Back Support Vector Machine-Recursive Feature Elimination (B-SVM-RFE) method for the classification of plant pre-miRNAs. Using this method, 63 features were obtained for plant miRNA classification. We then developed an integrated classification model, miPlantPreMat, which comprises MiPlantPre and MiPlantMat, to identify plant pre-miRNAs and their miRNAs. This model achieved approximately 90% accuracy using plant datasets from nine plant species, including Arabidopsis thaliana, Glycine max, Oryza sativa, Physcomitrella patens, Medicago truncatula, Sorghum bicolor, Arabidopsis lyrata, Zea mays and Solanum lycopersicum. Using miPlantPreMat, 522 Solanum lycopersicum miRNAs were identified in the Solanum lycopersicum genome sequence. We developed an integrated classification model, miPlantPreMat, based on structure-sequence features and SVM. MiPlantPreMat was used to identify both plant pre-miRNAs and the corresponding mature miRNAs. An improved feature selection method was proposed, resulting in high classification accuracy, sensitivity and specificity.

Taxonomy of Caribbean Tourism Alcohol Venues: Implications for HIV Transmission*

PubMed Central

GUILAMO-RAMOS, Vincent; JACCARD, James; MCCARTHY, Katharine; QUIÑONES, Zahira; LUSHIN, Viktor; SKINNER-DAY, Molly; PADILLA, Mark; MEISTERLIN, Leah

2013-01-01

Background Tourism areas represent ecologies of heightened HIV vulnerability characterized by a disproportionate concentration of alcohol venues. Limited research has explored how alcohol venues facilitate HIV transmission. Methods We spatially mapped locations of alcohol venues in a Dominican tourism town and conducted a venue-based survey of key informants (n=135) focused on three facets of alcohol venues: structural features, type of patrons, and HIV risk behaviors. Using latent class analysis, we identified evidence-based typologies of alcohol venues for each of the three facets. Focused contrasts identified the co-occurrence of classes of structural features, classes of types of patrons, and classes of HIV risk behavior, thus elaborating the nature of high risk venues. Results We identified three categories of venue structural features, three for venue patrons, and five for HIV risk behaviors. Analysis revealed that alcohol venues with the greatest structural risks (e.g., sex work on site with lack of HIV prevention services) were most likely frequented by the venue patron category characterized by high population-mixing between locals and foreign tourists, who were in turn most likely to engage in the riskiest behaviors. Conclusion Our results highlight the stratification of venue patrons into groups who engage in behaviors of varying risk in structural settings that vary in risk. The convergence of high-risk patron groups in alcohol venues with the greatest structural risk suggests these locations have potential for HIV transmission. Policymakers and prevention scientists can use these methods and data to target HIV prevention resources to identified priority areas. PMID:23478154

Taxonomy of Caribbean tourism alcohol venues: implications for HIV transmission.

PubMed

Guilamo-Ramos, Vincent; Jaccard, James; McCarthy, Katharine; Quiñones, Zahira; Lushin, Viktor; Skinner-Day, Molly; Padilla, Mark; Meisterlin, Leah

2013-09-01

Tourism areas represent ecologies of heightened HIV vulnerability characterized by a disproportionate concentration of alcohol venues. Limited research has explored how alcohol venues facilitate HIV transmission. We spatially mapped locations of alcohol venues in a Dominican tourism town and conducted a venue-based survey of key informants (n=135) focused on three facets of alcohol venues: structural features, type of patrons, and HIV risk behaviors. Using latent class analysis, we identified evidence-based typologies of alcohol venues for each of the three facets. Focused contrasts identified the co-occurrence of classes of structural features, classes of types of patrons, and classes of HIV risk behavior, thus elaborating the nature of high risk venues. We identified three categories of venue structural features, three for venue patrons, and five for HIV risk behaviors. Analysis revealed that alcohol venues with the greatest structural risks (e.g. sex work on-site with lack of HIV prevention services) were most likely frequented by the venue patron category characterized by high population-mixing between locals and foreign tourists, who were in turn most likely to engage in the riskiest behaviors. Our results highlight the stratification of venue patrons into groups who engage in behaviors of varying risk in structural settings that vary in risk. The convergence of high-risk patron groups in alcohol venues with the greatest structural risk suggests these locations have potential for HIV transmission. Policymakers and prevention scientists can use these methods and data to target HIV prevention resources to identified priority areas. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

The Features of Female Managers' Personality Traits in Organization

ERIC Educational Resources Information Center

Gabdreeva, Guzel Sh.; Khalfieva, Alisa R.

2016-01-01

The relevance of the "female" management features study is driven by the active penetration of women to management in various fields and the emergence of a new social category "Business-women". The article contains the results of a study aimed to identify the features of personal properties and structure of low-level,…

MODAL TRACKING of A Structural Device: A Subspace Identification Approach

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

Candy, J. V.; Franco, S. N.; Ruggiero, E. L.

Mechanical devices operating in an environment contaminated by noise, uncertainties, and extraneous disturbances lead to low signal-to-noise-ratios creating an extremely challenging processing problem. To detect/classify a device subsystem from noisy data, it is necessary to identify unique signatures or particular features. An obvious feature would be resonant (modal) frequencies emitted during its normal operation. In this report, we discuss a model-based approach to incorporate these physical features into a dynamic structure that can be used for such an identification. The approach we take after pre-processing the raw vibration data and removing any extraneous disturbances is to obtain a representation ofmore » the structurally unknown device along with its subsystems that capture these salient features. One approach is to recognize that unique modal frequencies (sinusoidal lines) appear in the estimated power spectrum that are solely characteristic of the device under investigation. Therefore, the objective of this effort is based on constructing a black box model of the device that captures these physical features that can be exploited to “diagnose” whether or not the particular device subsystem (track/detect/classify) is operating normally from noisy vibrational data. Here we discuss the application of a modern system identification approach based on stochastic subspace realization techniques capable of both (1) identifying the underlying black-box structure thereby enabling the extraction of structural modes that can be used for analysis and modal tracking as well as (2) indicators of condition and possible changes from normal operation.« less

Investigation of LANDSAT imagery on correlations between ore deposits and major shield structures in Finland. [Baltic Shield

NASA Technical Reports Server (NTRS)

Tuominen, H. V. (Principal Investigator); Kuosmanen, V.

1975-01-01

The author has identified the following significant results. On the central Baltic Shield, the concept of drainage patterns can be extended to smaller scales in which case many cultural features become involved to the spatial patterns influenced by bedrock structure. Features resulting from agriculture activity and timbering often exaggerate the influence of the bedrock on the image texture.

Advances in the REDCAT software package

PubMed Central

2013-01-01

Background Residual Dipolar Couplings (RDCs) have emerged in the past two decades as an informative source of experimental restraints for the study of structure and dynamics of biological macromolecules and complexes. The REDCAT software package was previously introduced for the analysis of molecular structures using RDC data. Here we report additional features that have been included in this software package in order to expand the scope of its analyses. We first discuss the features that enhance REDCATs user-friendly nature, such as the integration of a number of analyses into one single operation and enabling convenient examination of a structural ensemble in order to identify the most suitable structure. We then describe the new features which expand the scope of RDC analyses, performing exercises that utilize both synthetic and experimental data to illustrate and evaluate different features with regard to structure refinement and structure validation. Results We establish the seamless interaction that takes place between REDCAT, VMD, and Xplor-NIH in demonstrations that utilize our newly developed REDCAT-VMD and XplorGUI interfaces. These modules enable visualization of RDC analysis results on the molecular structure displayed in VMD and refinement of structures with Xplor-NIH, respectively. We also highlight REDCAT’s Error-Analysis feature in reporting the localized fitness of a structure to RDC data, which provides a more effective means of recognizing local structural anomalies. This allows for structurally sound regions of a molecule to be identified, and for any refinement efforts to be focused solely on locally distorted regions. Conclusions The newly engineered REDCAT software package, which is available for download via the WWW from http://ifestos.cse.sc.edu, has been developed in the Object Oriented C++ environment. Our most recent enhancements to REDCAT serve to provide a more complete RDC analysis suite, while also accommodating a more user-friendly experience, and will be of great interest to the community of researchers and developers since it hides the complications of software development. PMID:24098943

Permafrost features on Earth and Mars: Similarities, differences

NASA Technical Reports Server (NTRS)

Joens, H. P.

1985-01-01

Typical permafrost features on Earth are polygonal structures, pingos and soli-/gelifluxion features. In areas around the poles and in mountain ranges the precipitation accumulates to inland ice or ice streams. On Mars the same features were identified: polygonal features cover the larger part of the northern lowlands indicating probably an ice wedge-/sand wedge system or desiccation cracks. These features indicate the extend of large mud accumulations which seem to be related to large outflow events of the chaotic terrains. The shore line of this mud accumulation is indicated by a special set of relief types. In some areas large pingo-like hills were identified. In the vicinity of the largest martian volcano, Olympus Mons, the melting of underlying permafrost and/or ground ice led to the downslope sliding of large parts of the primary shield which formed the aureole around Olympus Mons. Glacier-like features are identified along the escarpment which separates the Southern Uplands from the Northern Lowlands.

Protein structure based prediction of catalytic residues.

PubMed

Fajardo, J Eduardo; Fiser, Andras

2013-02-22

Worldwide structural genomics projects continue to release new protein structures at an unprecedented pace, so far nearly 6000, but only about 60% of these proteins have any sort of functional annotation. We explored a range of features that can be used for the prediction of functional residues given a known three-dimensional structure. These features include various centrality measures of nodes in graphs of interacting residues: closeness, betweenness and page-rank centrality. We also analyzed the distance of functional amino acids to the general center of mass (GCM) of the structure, relative solvent accessibility (RSA), and the use of relative entropy as a measure of sequence conservation. From the selected features, neural networks were trained to identify catalytic residues. We found that using distance to the GCM together with amino acid type provide a good discriminant function, when combined independently with sequence conservation. Using an independent test set of 29 annotated protein structures, the method returned 411 of the initial 9262 residues as the most likely to be involved in function. The output 411 residues contain 70 of the annotated 111 catalytic residues. This represents an approximately 14-fold enrichment of catalytic residues on the entire input set (corresponding to a sensitivity of 63% and a precision of 17%), a performance competitive with that of other state-of-the-art methods. We found that several of the graph based measures utilize the same underlying feature of protein structures, which can be simply and more effectively captured with the distance to GCM definition. This also has the added the advantage of simplicity and easy implementation. Meanwhile sequence conservation remains by far the most influential feature in identifying functional residues. We also found that due the rapid changes in size and composition of sequence databases, conservation calculations must be recalibrated for specific reference databases.

Structural Features of Algebraic Quantum Notations

ERIC Educational Resources Information Center

Gire, Elizabeth; Price, Edward

2015-01-01

The formalism of quantum mechanics includes a rich collection of representations for describing quantum systems, including functions, graphs, matrices, histograms of probabilities, and Dirac notation. The varied features of these representations affect how computations are performed. For example, identifying probabilities of measurement outcomes…

Local kernel nonparametric discriminant analysis for adaptive extraction of complex structures

NASA Astrophysics Data System (ADS)

Li, Quanbao; Wei, Fajie; Zhou, Shenghan

2017-05-01

The linear discriminant analysis (LDA) is one of popular means for linear feature extraction. It usually performs well when the global data structure is consistent with the local data structure. Other frequently-used approaches of feature extraction usually require linear, independence, or large sample condition. However, in real world applications, these assumptions are not always satisfied or cannot be tested. In this paper, we introduce an adaptive method, local kernel nonparametric discriminant analysis (LKNDA), which integrates conventional discriminant analysis with nonparametric statistics. LKNDA is adept in identifying both complex nonlinear structures and the ad hoc rule. Six simulation cases demonstrate that LKNDA have both parametric and nonparametric algorithm advantages and higher classification accuracy. Quartic unilateral kernel function may provide better robustness of prediction than other functions. LKNDA gives an alternative solution for discriminant cases of complex nonlinear feature extraction or unknown feature extraction. At last, the application of LKNDA in the complex feature extraction of financial market activities is proposed.

Ligand-based and structure-based approaches in identifying ideal pharmacophore against c-Jun N-terminal kinase-3.

PubMed

Kumar, B V S Suneel; Kotla, Rohith; Buddiga, Revanth; Roy, Jyoti; Singh, Sardar Shamshair; Gundla, Rambabu; Ravikumar, Muttineni; Sarma, Jagarlapudi A R P

2011-01-01

Structure and ligand based pharmacophore modeling and docking studies carried out using diversified set of c-Jun N-terminal kinase-3 (JNK3) inhibitors are presented in this paper. Ligand based pharmacophore model (LBPM) was developed for 106 inhibitors of JNK3 using a training set of 21 compounds to reveal structural and chemical features necessary for these molecules to inhibit JNK3. Hypo1 consisted of two hydrogen bond acceptors (HBA), one hydrogen bond donor (HBD), and a hydrophobic (HY) feature with a correlation coefficient (r²) of 0.950. This pharmacophore model was validated using test set containing 85 inhibitors and had a good r² of 0.846. All the molecules were docked using Glide software and interestingly, all the docked conformations showed hydrogen bond interactions with important hinge region amino acids (Gln155 and Met149)and these interactions were compared with Hypo1 features. The results of ligand based pharmacophore model (LBPM)and docking studies are validated each other. The structure based pharmacophore model (SBPM) studies have identified additional features, two hydrogen bond donors and one hydrogen bond acceptor. The combination of these methodologies is useful in designing ideal pharmacophore which provides a powerful tool for the discovery of novel and selective JNK3 inhibitors.

Labyrinths, columns and cavities: new internal features of pollen grain walls in the Acanthaceae detected by FIB-SEM.

PubMed

House, Alisoun; Balkwill, Kevin

2016-03-01

External pollen grain morphology has been widely used in the taxonomy and systematics of flowering plants, especially the Acanthaceae which are noted for pollen diversity. However internal pollen wall features have received far less attention due to the difficulty of examining the wall structure. Advancing technology in the field of microscopy has made it possible, with the use of a focused ion beam-scanning electron microscope (FIB-SEM), to view the structure of pollen grain walls in far greater detail and in three dimensions. In this study the wall structures of 13 species from the Acanthaceae were investigated for features of potential systematic relevance. FIB-SEM was applied to obtain precise cross sections of pollen grains at selected positions for examining the wall ultrastructure. Exploratory studies of the exine have thus far identified five basic structural types. The investigations also show that similar external pollen wall features may have a distinctly different internal structure. FIB-SEM studies have revealed diverse internal pollen wall features which may now be investigated for their systematic and functional significance.

Designing Professional Development That Works.

ERIC Educational Resources Information Center

Birman, Beatrice F.; Desimone, Laura; Porter, Andrew C.; Garet, Michael S.

2000-01-01

By studying survey data from 1,000 teachers participating in a Title II workshop, researchers identified three structural features (form, duration, and collective participation) that set a proper context for professional development. Three core features of professional-development learning experience include content focus, active learning, and…

Computational Identification of Genomic Features That Influence 3D Chromatin Domain Formation.

PubMed

Mourad, Raphaël; Cuvier, Olivier

2016-05-01

Recent advances in long-range Hi-C contact mapping have revealed the importance of the 3D structure of chromosomes in gene expression. A current challenge is to identify the key molecular drivers of this 3D structure. Several genomic features, such as architectural proteins and functional elements, were shown to be enriched at topological domain borders using classical enrichment tests. Here we propose multiple logistic regression to identify those genomic features that positively or negatively influence domain border establishment or maintenance. The model is flexible, and can account for statistical interactions among multiple genomic features. Using both simulated and real data, we show that our model outperforms enrichment test and non-parametric models, such as random forests, for the identification of genomic features that influence domain borders. Using Drosophila Hi-C data at a very high resolution of 1 kb, our model suggests that, among architectural proteins, BEAF-32 and CP190 are the main positive drivers of 3D domain borders. In humans, our model identifies well-known architectural proteins CTCF and cohesin, as well as ZNF143 and Polycomb group proteins as positive drivers of domain borders. The model also reveals the existence of several negative drivers that counteract the presence of domain borders including P300, RXRA, BCL11A and ELK1.

Computational Identification of Genomic Features That Influence 3D Chromatin Domain Formation

PubMed Central

Mourad, Raphaël; Cuvier, Olivier

2016-01-01

Recent advances in long-range Hi-C contact mapping have revealed the importance of the 3D structure of chromosomes in gene expression. A current challenge is to identify the key molecular drivers of this 3D structure. Several genomic features, such as architectural proteins and functional elements, were shown to be enriched at topological domain borders using classical enrichment tests. Here we propose multiple logistic regression to identify those genomic features that positively or negatively influence domain border establishment or maintenance. The model is flexible, and can account for statistical interactions among multiple genomic features. Using both simulated and real data, we show that our model outperforms enrichment test and non-parametric models, such as random forests, for the identification of genomic features that influence domain borders. Using Drosophila Hi-C data at a very high resolution of 1 kb, our model suggests that, among architectural proteins, BEAF-32 and CP190 are the main positive drivers of 3D domain borders. In humans, our model identifies well-known architectural proteins CTCF and cohesin, as well as ZNF143 and Polycomb group proteins as positive drivers of domain borders. The model also reveals the existence of several negative drivers that counteract the presence of domain borders including P300, RXRA, BCL11A and ELK1. PMID:27203237

A network model of the interbank market

NASA Astrophysics Data System (ADS)

Li, Shouwei; He, Jianmin; Zhuang, Yaming

2010-12-01

This work introduces a network model of an interbank market based on interbank credit lending relationships. It generates some network features identified through empirical analysis. The critical issue to construct an interbank network is to decide the edges among banks, which is realized in this paper based on the interbank’s degree of trust. Through simulation analysis of the interbank network model, some typical structural features are identified in our interbank network, which are also proved to exist in real interbank networks. They are namely, a low clustering coefficient and a relatively short average path length, community structures, and a two-power-law distribution of out-degree and in-degree.

Designing attractive gamification features for collaborative storytelling websites.

PubMed

Hsu, Shang Hwa; Chang, Jen-Wei; Lee, Chun-Chia

2013-06-01

Gamification design is considered as the predictor of collaborative storytelling websites' success. Although aforementioned studies have mentioned a broad range of factors that may influence gamification, they neither depicted the actual design features nor relative attractiveness among them. This study aims to identify attractive gamification features for collaborative storytelling websites. We first constructed a hierarchical system structure of gamification design of collaborative storytelling websites and conducted a focus group interview with eighteen frequent users to identify 35gamification features. After that, this study determined the relative attractiveness of these gamification features by administrating an online survey to 6333 collaborative storytelling websites users. The results indicated that the top 10 most attractive gamification features could account for more than 50% of attractiveness among these 35 gamification features. The feature of unpredictable time pressure is important to website users, yet not revealed in previous relevant studies. Implications of the findings were discussed.

Classification and Lateralization of Temporal Lobe Epilepsies with and without Hippocampal Atrophy Based on Whole-Brain Automatic MRI Segmentation

PubMed Central

Keihaninejad, Shiva; Heckemann, Rolf A.; Gousias, Ioannis S.; Hajnal, Joseph V.; Duncan, John S.; Aljabar, Paul; Rueckert, Daniel; Hammers, Alexander

2012-01-01

Brain images contain information suitable for automatically sorting subjects into categories such as healthy controls and patients. We sought to identify morphometric criteria for distinguishing controls (n = 28) from patients with unilateral temporal lobe epilepsy (TLE), 60 with and 20 without hippocampal atrophy (TLE-HA and TLE-N, respectively), and for determining the presumed side of seizure onset. The framework employs multi-atlas segmentation to estimate the volumes of 83 brain structures. A kernel-based separability criterion was then used to identify structures whose volumes discriminate between the groups. Next, we applied support vector machines (SVM) to the selected set for classification on the basis of volumes. We also computed pairwise similarities between all subjects and used spectral analysis to convert these into per-subject features. SVM was again applied to these feature data. After training on a subgroup, all TLE-HA patients were correctly distinguished from controls, achieving an accuracy of 96 ± 2% in both classification schemes. For TLE-N patients, the accuracy was 86 ± 2% based on structural volumes and 91 ± 3% using spectral analysis. Structures discriminating between patients and controls were mainly localized ipsilaterally to the presumed seizure focus. For the TLE-HA group, they were mainly in the temporal lobe; for the TLE-N group they included orbitofrontal regions, as well as the ipsilateral substantia nigra. Correct lateralization of the presumed seizure onset zone was achieved using hippocampi and parahippocampal gyri in all TLE-HA patients using either classification scheme; in the TLE-N patients, lateralization was accurate based on structural volumes in 86 ± 4%, and in 94 ± 4% with the spectral analysis approach. Unilateral TLE has imaging features that can be identified automatically, even when they are invisible to human experts. Such morphometric image features may serve as classification and lateralization criteria. The technique also detects unsuspected distinguishing features like the substantia nigra, warranting further study. PMID:22523539

The geomorphology of Ceres

USGS Publications Warehouse

Buczkowski, D.L.; Schmidt, B.E.; Williams, D.A.; Mest, S.C.; Scully, J.E.C.; Ermakov, A.; Preusker, F.; Schenk, P.; Otto, K. A.; Hiesinger, H.; O'Brien, D.; Marchi, S.; Sizemore, H.G.; Hughson, K.; Chilton, H.; Bland, M.; Byrne, S.; Schorghofer, N.; Platz, T.; Jaumann, R.; Roatsch, T.; Sykes, M. V.; Nathues, A.; De Sanctis, M.C.; Raymond, C.A.; Russell, C.T.

2016-01-01

Analysis of Dawn spacecraft Framing Camera image data allows evaluation of the topography and geomorphology of features on the surface of Ceres. The dwarf planet is dominated by numerous craters, but other features are also common. Linear structures include both those associated with impact craters and those that do not appear to have any correlation to an impact event. Abundant lobate flows are identified, and numerous domical features are found at a range of scales. Features suggestive of near-surface ice, cryomagmatism, and cryovolcanism have been identified. Although spectroscopic analysis has currently detected surface water ice at only one location on Ceres, the identification of these potentially ice-related features suggests that there may be at least some ice in localized regions in the crust.

Long-term memory for temporal structure: evidence form the identification of well-known and novel songs.

PubMed

Schulkind, M D

1999-09-01

In three experiments, long-term memory for temporal structure was examined by having participants identify both well-known (e.g., "I've Been Working on the Railroad") and novel songs. The target songs were subjected to a number of rhythmic alterations, to assess the importance of four critical features of identification performance. The four critical features were meter, phrasing, rhythmic contour (ordinal scaling of note durations), and the ratio of successive durations. In contrast with previous work, the unaltered version of each song was identified significantly better than any altered version. This indicates that rhythm is stored in long-term memory. Furthermore, the results demonstrated that all four critical features play a role in the identification of songs. These results held for both well-known and novel tunes.

Structure and Characteristics of the Stepfamily: Implications for Counseling.

ERIC Educational Resources Information Center

Cobia, Debra C.

1996-01-01

Describes the development, structure, and characteristics of the stepfamily and distinguishes these features from those of traditional, intact families. Identifies stepfamily concerns, addressing these as typical transitional issues rather than as insurmountable problems, and presents four stages of developmental and structural changes for…

High-throughput screening for thermoelectric sulphides by using crystal structure features as descriptors

NASA Astrophysics Data System (ADS)

Zhang, Ruizhi; Du, Baoli; Chen, Kan; Reece, Mike; Materials Research Insititute Team

With the increasing computational power and reliable databases, high-throughput screening is playing a more and more important role in the search of new thermoelectric materials. Rather than the well established density functional theory (DFT) calculation based methods, we propose an alternative approach to screen for new TE materials: using crystal structural features as 'descriptors'. We show that a non-distorted transition metal sulphide polyhedral network can be a good descriptor for high power factor according to crystal filed theory. By using Cu/S containing compounds as an example, 1600+ Cu/S containing entries in the Inorganic Crystal Structure Database (ICSD) were screened, and of those 84 phases are identified as promising thermoelectric materials. The screening results are validated by both electronic structure calculations and experimental results from the literature. We also fabricated some new compounds to test our screening results. Another advantage of using crystal structure features as descriptors is that we can easily establish structural relationships between the identified phases. Based on this, two material design approaches are discussed: 1) High-pressure synthesis of metastable phase; 2) In-situ 2-phase composites with coherent interface. This work was supported by a Marie Curie International Incoming Fellowship of the European Community Human Potential Program.

Solving the mystery of the internal structure of casein micelles.

PubMed

Ingham, B; Erlangga, G D; Smialowska, A; Kirby, N M; Wang, C; Matia-Merino, L; Haverkamp, R G; Carr, A J

2015-04-14

The interpretation of milk X-ray and neutron scattering data in relation to the internal structure of the casein micelle is an ongoing debate. We performed resonant X-ray scattering measurements on liquid milk and conclusively identified key scattering features, namely those corresponding to the size of and the distance between colloidal calcium phosphate particles. An X-ray scattering feature commonly assigned to the particle size is instead due to protein inhomogeneities.

Identifying the distinct features of geometric structures for hole trapping to generate radicals on rutile TiO₂(110) in photooxidation using density functional theory calculations with hybrid functional.

PubMed

Wang, Dong; Wang, Haifeng; Hu, P

2015-01-21

Using density functional theory calculations with HSE 06 functional, we obtained the structures of spin-polarized radicals on rutile TiO2(110), which is crucial to understand the photooxidation at the atomic level, and further calculate the thermodynamic stabilities of these radicals. By analyzing the results, we identify the structural features for hole trapping in the system, and reveal the mutual effects among the geometric structures, the energy levels of trapped hole states and their hole trapping capacities. Furthermore, the results from HSE 06 functional are compared to those from DFT + U and the stability trend of radicals against the number of slabs is tested. The effect of trapped holes on two important steps of the oxygen evolution reaction, i.e. water dissociation and the oxygen removal, is investigated and discussed.

Aeroelastic characteristics of composite bearingless rotor blades

NASA Technical Reports Server (NTRS)

Bielawa, R. L.

1976-01-01

Owing to the inherent unique structural features of composite bearingless rotors, various assumptions upon which conventional rotor aeroelastic analyses are formulated, are violated. Three such features identified are highly nonlinear and time-varying structural twist, structural redundancy in bending and torsion, and for certain configurations a strongly coupled low frequency bending-torsion mode. An examination of these aeroelastic considerations and appropriate formulations required for accurate analyses of such rotor systems is presented. Also presented are test results from a dynamically scaled model rotor and complementary analytic results obtained with the appropriately reformulated aeroelastic analysis.

Multi-disciplinary team meetings in stroke rehabilitation: an observation study and conceptual framework.

PubMed

Tyson, S F; Burton, L; McGovern, A

2014-12-01

To explore how multi-disciplinary team meetings operate in stroke rehabilitation. Non-participant observation of multi-disciplinary team meetings and semi-structured interviews with attending staff. Twelve meetings were observed (at least one at each site) and 18 staff (one psychologist, one social worker; four nurses; four physiotherapists four occupational therapists, two speech and language therapists, one stroke co-ordinator and one stroke ward manager) were interviewed in eight in-patient stroke rehabilitation units. Multi-disciplinary team meetings in stroke rehabilitation were complex, demanding and highly varied. A model emerged which identified the main inputs to influence conduct of the meetings were personal contributions of the members and structure and format of the meetings. These were mediated by the team climate and leadership skills of the chair. The desired outputs; clinical decisions and the attributes of apparently effective meetings were identified by the staff. A notable difference between the meetings that staff considered effective and those that were not, was their structure and format. Successful meetings tended to feature a set agenda, structured documentation; formal use of measurement tools; pre-meeting preparation and skilled chairing. These features were often absent in meetings perceived to be ineffective. The main features of operation of multi-disciplinary team meetings have been identified which will enable assessment tools and interventions to improve effectiveness to be developed. © The Author(s) 2014.

[Regression analysis to select native-like structures from decoys of antigen-antibody docking].

PubMed

Chen, Zhengshan; Chi, Xiangyang; Fan, Pengfei; Zhang, Guanying; Wang, Meirong; Yu, Changming; Chen, Wei

2018-06-25

Given the increasing exploitation of antibodies in different contexts such as molecular diagnostics and therapeutics, it would be beneficial to unravel properties of antigen-antibody interaction with modeling of computational protein-protein docking, especially, in the absence of a cocrystal structure. However, obtaining a native-like antigen-antibody structure remains challenging due in part to failing to reliably discriminate accurate from inaccurate structures among tens of thousands of decoys after computational docking with existing scoring function. We hypothesized that some important physicochemical and energetic features could be used to describe antigen-antibody interfaces and identify native-like antigen-antibody structure. We prepared a dataset, a subset of Protein-Protein Docking Benchmark Version 4.0, comprising 37 nonredundant 3D structures of antigen-antibody complexes, and used it to train and test multivariate logistic regression equation which took several important physicochemical and energetic features of decoys as dependent variables. Our results indicate that the ability to identify native-like structures of our method is superior to ZRANK and ZDOCK score for the subset of antigen-antibody complexes. And then, we use our method in workflow of predicting epitope of anti-Ebola glycoprotein monoclonal antibody-4G7 and identify three accurate residues in its epitope.

A Spatial View of the Interpersonal Structure of Family Interviews: Similarities and Differences Across Counselors.

ERIC Educational Resources Information Center

Friedlander, Myrna L.; Highlen, Pamela S.

1984-01-01

Examined the interpersonal structures of interviews by Ackerman, Bowen, Jackson, and Whitaker with the same family to identify common features across counselors. Multidimensional scaling provided a spatial representation of the hidden structure in the communication patterns of these interviews. Correlations indicated counselors' interactions were…

The geomorphology of Ceres.

PubMed

Buczkowski, D L; Schmidt, B E; Williams, D A; Mest, S C; Scully, J E C; Ermakov, A I; Preusker, F; Schenk, P; Otto, K A; Hiesinger, H; O'Brien, D; Marchi, S; Sizemore, H; Hughson, K; Chilton, H; Bland, M; Byrne, S; Schorghofer, N; Platz, T; Jaumann, R; Roatsch, T; Sykes, M V; Nathues, A; De Sanctis, M C; Raymond, C A; Russell, C T

2016-09-02

Analysis of Dawn spacecraft Framing Camera image data allows evaluation of the topography and geomorphology of features on the surface of Ceres. The dwarf planet is dominated by numerous craters, but other features are also common. Linear structures include both those associated with impact craters and those that do not appear to have any correlation to an impact event. Abundant lobate flows are identified, and numerous domical features are found at a range of scales. Features suggestive of near-surface ice, cryomagmatism, and cryovolcanism have been identified. Although spectroscopic analysis has currently detected surface water ice at only one location on Ceres, the identification of these potentially ice-related features suggests that there may be at least some ice in localized regions in the crust. Copyright © 2016, American Association for the Advancement of Science.

A diagnosis model for early Tourette syndrome children based on brain structural network characteristics

NASA Astrophysics Data System (ADS)

Wen, Hongwei; Liu, Yue; Wang, Jieqiong; Zhang, Jishui; Peng, Yun; He, Huiguang

2016-03-01

Tourette syndrome (TS) is a childhood-onset neurobehavioral disorder characterized by the presence of multiple motor and vocal tics. Tic generation has been linked to disturbed networks of brain areas involved in planning, controlling and execution of action. The aim of our work is to select topological characteristics of structural network which were most efficient for estimating the classification models to identify early TS children. Here we employed the diffusion tensor imaging (DTI) and deterministic tractography to construct the structural networks of 44 TS children and 48 age and gender matched healthy children. We calculated four different connection matrices (fiber number, mean FA, averaged fiber length weighted and binary matrices) and then applied graph theoretical methods to extract the regional nodal characteristics of structural network. For each weighted or binary network, nodal degree, nodal efficiency and nodal betweenness were selected as features. Support Vector Machine Recursive Feature Extraction (SVM-RFE) algorithm was used to estimate the best feature subset for classification. The accuracy of 88.26% evaluated by a nested cross validation was achieved on combing best feature subset of each network characteristic. The identified discriminative brain nodes mostly located in the basal ganglia and frontal cortico-cortical networks involved in TS children which was associated with tic severity. Our study holds promise for early identification and predicting prognosis of TS children.

regSNPs-splicing: a tool for prioritizing synonymous single-nucleotide substitution.

PubMed

Zhang, Xinjun; Li, Meng; Lin, Hai; Rao, Xi; Feng, Weixing; Yang, Yuedong; Mort, Matthew; Cooper, David N; Wang, Yue; Wang, Yadong; Wells, Clark; Zhou, Yaoqi; Liu, Yunlong

2017-09-01

While synonymous single-nucleotide variants (sSNVs) have largely been unstudied, since they do not alter protein sequence, mounting evidence suggests that they may affect RNA conformation, splicing, and the stability of nascent-mRNAs to promote various diseases. Accurately prioritizing deleterious sSNVs from a pool of neutral ones can significantly improve our ability of selecting functional genetic variants identified from various genome-sequencing projects, and, therefore, advance our understanding of disease etiology. In this study, we develop a computational algorithm to prioritize sSNVs based on their impact on mRNA splicing and protein function. In addition to genomic features that potentially affect splicing regulation, our proposed algorithm also includes dozens structural features that characterize the functions of alternatively spliced exons on protein function. Our systematical evaluation on thousands of sSNVs suggests that several structural features, including intrinsic disorder protein scores, solvent accessible surface areas, protein secondary structures, and known and predicted protein family domains, show significant differences between disease-causing and neutral sSNVs. Our result suggests that the protein structure features offer an added dimension of information while distinguishing disease-causing and neutral synonymous variants. The inclusion of structural features increases the predictive accuracy for functional sSNV prioritization.

Structure and Function in Homodimeric Enzymes: Simulations of Cooperative and Independent Functional Motions.

PubMed

Wells, Stephen A; van der Kamp, Marc W; McGeagh, John D; Mulholland, Adrian J

2015-01-01

Large-scale conformational change is a common feature in the catalytic cycles of enzymes. Many enzymes function as homodimers with active sites that contain elements from both chains. Symmetric and anti-symmetric cooperative motions in homodimers can potentially lead to correlated active site opening and/or closure, likely to be important for ligand binding and release. Here, we examine such motions in two different domain-swapped homodimeric enzymes: the DcpS scavenger decapping enzyme and citrate synthase. We use and compare two types of all-atom simulations: conventional molecular dynamics simulations to identify physically meaningful conformational ensembles, and rapid geometric simulations of flexible motion, biased along normal mode directions, to identify relevant motions encoded in the protein structure. The results indicate that the opening/closure motions are intrinsic features of both unliganded enzymes. In DcpS, conformational change is dominated by an anti-symmetric cooperative motion, causing one active site to close as the other opens; however a symmetric motion is also significant. In CS, we identify that both symmetric (suggested by crystallography) and asymmetric motions are features of the protein structure, and as a result the behaviour in solution is largely non-cooperative. The agreement between two modelling approaches using very different levels of theory indicates that the behaviours are indeed intrinsic to the protein structures. Geometric simulations correctly identify and explore large amplitudes of motion, while molecular dynamics simulations indicate the ranges of motion that are energetically feasible. Together, the simulation approaches are able to reveal unexpected functionally relevant motions, and highlight differences between enzymes.

Structure and Function in Homodimeric Enzymes: Simulations of Cooperative and Independent Functional Motions

PubMed Central

McGeagh, John D.; Mulholland, Adrian J.

2015-01-01

Large-scale conformational change is a common feature in the catalytic cycles of enzymes. Many enzymes function as homodimers with active sites that contain elements from both chains. Symmetric and anti-symmetric cooperative motions in homodimers can potentially lead to correlated active site opening and/or closure, likely to be important for ligand binding and release. Here, we examine such motions in two different domain-swapped homodimeric enzymes: the DcpS scavenger decapping enzyme and citrate synthase. We use and compare two types of all-atom simulations: conventional molecular dynamics simulations to identify physically meaningful conformational ensembles, and rapid geometric simulations of flexible motion, biased along normal mode directions, to identify relevant motions encoded in the protein structure. The results indicate that the opening/closure motions are intrinsic features of both unliganded enzymes. In DcpS, conformational change is dominated by an anti-symmetric cooperative motion, causing one active site to close as the other opens; however a symmetric motion is also significant. In CS, we identify that both symmetric (suggested by crystallography) and asymmetric motions are features of the protein structure, and as a result the behaviour in solution is largely non-cooperative. The agreement between two modelling approaches using very different levels of theory indicates that the behaviours are indeed intrinsic to the protein structures. Geometric simulations correctly identify and explore large amplitudes of motion, while molecular dynamics simulations indicate the ranges of motion that are energetically feasible. Together, the simulation approaches are able to reveal unexpected functionally relevant motions, and highlight differences between enzymes. PMID:26241964

Common structural features of cholesterol binding sites in crystallized soluble proteins

PubMed Central

Bukiya, Anna N.; Dopico, Alejandro M.

2017-01-01

Cholesterol-protein interactions are essential for the architectural organization of cell membranes and for lipid metabolism. While cholesterol-sensing motifs in transmembrane proteins have been identified, little is known about cholesterol recognition by soluble proteins. We reviewed the structural characteristics of binding sites for cholesterol and cholesterol sulfate from crystallographic structures available in the Protein Data Bank. This analysis unveiled key features of cholesterol-binding sites that are present in either all or the majority of sites: i) the cholesterol molecule is generally positioned between protein domains that have an organized secondary structure; ii) the cholesterol hydroxyl/sulfo group is often partnered by Asn, Gln, and/or Tyr, while the hydrophobic part of cholesterol interacts with Leu, Ile, Val, and/or Phe; iii) cholesterol hydrogen-bonding partners are often found on α-helices, while amino acids that interact with cholesterol’s hydrophobic core have a slight preference for β-strands and secondary structure-lacking protein areas; iv) the steroid’s C21 and C26 constitute the “hot spots” most often seen for steroid-protein hydrophobic interactions; v) common “cold spots” are C8–C10, C13, and C17, at which contacts with the proteins were not detected. Several common features we identified for soluble protein-steroid interaction appear evolutionarily conserved. PMID:28420706

Using a Word Association Test for the Assessment of High School Students' Cognitive Structures on Dissolution

ERIC Educational Resources Information Center

Derman, Aysegul; Eilks, Ingo

2016-01-01

Understanding students' cognitive structures in a specific knowledge domain helps to determine the ''what, how and why'' features of such knowledge, so that we can take these structures into consideration in teaching. The purpose of the present study was to identify students' cognitive structures about solution and dissolution concepts. The study…

Joint source based analysis of multiple brain structures in studying major depressive disorder

NASA Astrophysics Data System (ADS)

Ramezani, Mahdi; Rasoulian, Abtin; Hollenstein, Tom; Harkness, Kate; Johnsrude, Ingrid; Abolmaesumi, Purang

2014-03-01

We propose a joint Source-Based Analysis (jSBA) framework to identify brain structural variations in patients with Major Depressive Disorder (MDD). In this framework, features representing position, orientation and size (i.e. pose), shape, and local tissue composition are extracted. Subsequently, simultaneous analysis of these features within a joint analysis method is performed to generate the basis sources that show signi cant di erences between subjects with MDD and those in healthy control. Moreover, in a cross-validation leave- one-out experiment, we use a Fisher Linear Discriminant (FLD) classi er to identify individuals within the MDD group. Results show that we can classify the MDD subjects with an accuracy of 76% solely based on the information gathered from the joint analysis of pose, shape, and tissue composition in multiple brain structures.

Identifying Structural Flow Defects in Disordered Solids Using Machine-Learning Methods

NASA Astrophysics Data System (ADS)

Cubuk, E. D.; Schoenholz, S. S.; Rieser, J. M.; Malone, B. D.; Rottler, J.; Durian, D. J.; Kaxiras, E.; Liu, A. J.

2015-03-01

We use machine-learning methods on local structure to identify flow defects—or particles susceptible to rearrangement—in jammed and glassy systems. We apply this method successfully to two very different systems: a two-dimensional experimental realization of a granular pillar under compression and a Lennard-Jones glass in both two and three dimensions above and below its glass transition temperature. We also identify characteristics of flow defects that differentiate them from the rest of the sample. Our results show it is possible to discern subtle structural features responsible for heterogeneous dynamics observed across a broad range of disordered materials.

Protein structure based prediction of catalytic residues

PubMed Central

2013-01-01

Background Worldwide structural genomics projects continue to release new protein structures at an unprecedented pace, so far nearly 6000, but only about 60% of these proteins have any sort of functional annotation. Results We explored a range of features that can be used for the prediction of functional residues given a known three-dimensional structure. These features include various centrality measures of nodes in graphs of interacting residues: closeness, betweenness and page-rank centrality. We also analyzed the distance of functional amino acids to the general center of mass (GCM) of the structure, relative solvent accessibility (RSA), and the use of relative entropy as a measure of sequence conservation. From the selected features, neural networks were trained to identify catalytic residues. We found that using distance to the GCM together with amino acid type provide a good discriminant function, when combined independently with sequence conservation. Using an independent test set of 29 annotated protein structures, the method returned 411 of the initial 9262 residues as the most likely to be involved in function. The output 411 residues contain 70 of the annotated 111 catalytic residues. This represents an approximately 14-fold enrichment of catalytic residues on the entire input set (corresponding to a sensitivity of 63% and a precision of 17%), a performance competitive with that of other state-of-the-art methods. Conclusions We found that several of the graph based measures utilize the same underlying feature of protein structures, which can be simply and more effectively captured with the distance to GCM definition. This also has the added the advantage of simplicity and easy implementation. Meanwhile sequence conservation remains by far the most influential feature in identifying functional residues. We also found that due the rapid changes in size and composition of sequence databases, conservation calculations must be recalibrated for specific reference databases. PMID:23433045

Automated Recognition of 3D Features in GPIR Images

NASA Technical Reports Server (NTRS)

Park, Han; Stough, Timothy; Fijany, Amir

2007-01-01

A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a directed-graph data structure. Relative to past approaches, this multiaxis approach offers the advantages of more reliable detections, better discrimination of objects, and provision of redundant information, which can be helpful in filling gaps in feature recognition by one of the component algorithms. The image-processing class also includes postprocessing algorithms that enhance identified features to prepare them for further scrutiny by human analysts (see figure). Enhancement of images as a postprocessing step is a significant departure from traditional practice, in which enhancement of images is a preprocessing step.

Conserved and variable domains of RNase MRP RNA.

PubMed

Dávila López, Marcela; Rosenblad, Magnus Alm; Samuelsson, Tore

2009-01-01

Ribonuclease MRP is a eukaryotic ribonucleoprotein complex consisting of one RNA molecule and 7-10 protein subunits. One important function of MRP is to catalyze an endonucleolytic cleavage during processing of rRNA precursors. RNase MRP is evolutionary related to RNase P which is critical for tRNA processing. A large number of MRP RNA sequences that now are available have been used to identify conserved primary and secondary structure features of the molecule. MRP RNA has structural features in common with P RNA such as a conserved catalytic core, but it also has unique features and is characterized by a domain highly variable between species. Information regarding primary and secondary structure features is of interest not only in basic studies of the function of MRP RNA, but also because mutations in the RNA give rise to human genetic diseases such as cartilage-hair hypoplasia.

Fine-Scale Analysis Reveals Cryptic Landscape Genetic Structure in Desert Tortoises

PubMed Central

Latch, Emily K.; Boarman, William I.; Walde, Andrew; Fleischer, Robert C.

2011-01-01

Characterizing the effects of landscape features on genetic variation is essential for understanding how landscapes shape patterns of gene flow and spatial genetic structure of populations. Most landscape genetics studies have focused on patterns of gene flow at a regional scale. However, the genetic structure of populations at a local scale may be influenced by a unique suite of landscape variables that have little bearing on connectivity patterns observed at broader spatial scales. We investigated fine-scale spatial patterns of genetic variation and gene flow in relation to features of the landscape in desert tortoise (Gopherus agassizii), using 859 tortoises genotyped at 16 microsatellite loci with associated data on geographic location, sex, elevation, slope, and soil type, and spatial relationship to putative barriers (power lines, roads). We used spatially explicit and non-explicit Bayesian clustering algorithms to partition the sample into discrete clusters, and characterize the relationships between genetic distance and ecological variables to identify factors with the greatest influence on gene flow at a local scale. Desert tortoises exhibit weak genetic structure at a local scale, and we identified two subpopulations across the study area. Although genetic differentiation between the subpopulations was low, our landscape genetic analysis identified both natural (slope) and anthropogenic (roads) landscape variables that have significantly influenced gene flow within this local population. We show that desert tortoise movements at a local scale are influenced by features of the landscape, and that these features are different than those that influence gene flow at larger scales. Our findings are important for desert tortoise conservation and management, particularly in light of recent translocation efforts in the region. More generally, our results indicate that recent landscape changes can affect gene flow at a local scale and that their effects can be detected almost immediately. PMID:22132143

Fine-scale analysis reveals cryptic landscape genetic structure in desert tortoises.

PubMed

Latch, Emily K; Boarman, William I; Walde, Andrew; Fleischer, Robert C

2011-01-01

Characterizing the effects of landscape features on genetic variation is essential for understanding how landscapes shape patterns of gene flow and spatial genetic structure of populations. Most landscape genetics studies have focused on patterns of gene flow at a regional scale. However, the genetic structure of populations at a local scale may be influenced by a unique suite of landscape variables that have little bearing on connectivity patterns observed at broader spatial scales. We investigated fine-scale spatial patterns of genetic variation and gene flow in relation to features of the landscape in desert tortoise (Gopherus agassizii), using 859 tortoises genotyped at 16 microsatellite loci with associated data on geographic location, sex, elevation, slope, and soil type, and spatial relationship to putative barriers (power lines, roads). We used spatially explicit and non-explicit Bayesian clustering algorithms to partition the sample into discrete clusters, and characterize the relationships between genetic distance and ecological variables to identify factors with the greatest influence on gene flow at a local scale. Desert tortoises exhibit weak genetic structure at a local scale, and we identified two subpopulations across the study area. Although genetic differentiation between the subpopulations was low, our landscape genetic analysis identified both natural (slope) and anthropogenic (roads) landscape variables that have significantly influenced gene flow within this local population. We show that desert tortoise movements at a local scale are influenced by features of the landscape, and that these features are different than those that influence gene flow at larger scales. Our findings are important for desert tortoise conservation and management, particularly in light of recent translocation efforts in the region. More generally, our results indicate that recent landscape changes can affect gene flow at a local scale and that their effects can be detected almost immediately.

Image processing tool for automatic feature recognition and quantification

DOEpatents

Chen, Xing; Stoddard, Ryan J.

2017-05-02

A system for defining structures within an image is described. The system includes reading of an input file, preprocessing the input file while preserving metadata such as scale information and then detecting features of the input file. In one version the detection first uses an edge detector followed by identification of features using a Hough transform. The output of the process is identified elements within the image.

Structural anomalies in undoped Gallium Arsenide observed in high resolution diffraction imaging with monochromatic synchrotron radiation

NASA Technical Reports Server (NTRS)

Steiner, B.; Kuriyama, M.; Dobbyn, R. C.; Laor, U.; Larson, D.; Brown, M.

1988-01-01

Novel, streak-like disruption features restricted to the plane of diffraction have recently been observed in images obtained by synchrotron radiation diffraction from undoped, semi-insulating gallium arsenide crystals. These features were identified as ensembles of very thin platelets or interfaces lying in (110) planes, and a structural model consisting of antiphase domain boundaries was proposed. We report here the other principal features observed in high resolution monochromatic synchrotron radiation diffraction images: (quasi) cellular structure; linear, very low-angle subgrain boundaries in (110) directions, and surface stripes in a (110) direction. In addition, we report systematic differences in the acceptance angle for images involving various diffraction vectors. When these observations are considered together, a unifying picture emerges. The presence of ensembles of thin (110) antiphase platelet regions or boundaries is generally consistent not only with the streak-like diffraction features but with the other features reported here as well. For the formation of such regions we propose two mechanisms, operating in parallel, that appear to be consistent with the various defect features observed by a variety of techniques.

Structural anomalies in undoped gallium arsenide observed in high-resolution diffraction imaging with monochromatic synchrotron radiation

NASA Technical Reports Server (NTRS)

Steiner, B.; Kuriyama, M.; Dobbyn, R. C.; Laor, U.; Larson, D.

1989-01-01

Novel, streak-like disruption features restricted to the plane of diffraction have recently been observed in images obtained by synchrotron radiation diffraction from undoped, semi-insulating gallium arsenide crystals. These features were identified as ensembles of very thin platelets or interfaces lying in (110) planes, and a structural model consisting of antiphase domain boundaries was proposed. We report here the other principal features observed in high resolution monochromatic synchrotron radiation diffraction images: (quasi) cellular structure; linear, very low-angle subgrain boundaries in (110) directions, and surface stripes in a (110) direction. In addition, we report systematic differences in the acceptance angle for images involving various diffraction vectors. When these observations are considered together, a unifying picture emerges. The presence of ensembles of thin (110) antiphase platelet regions or boundaries is generally consistent not only with the streak-like diffraction features but with the other features reported here as well. For the formation of such regions we propose two mechanisms, operating in parallel, that appear to be consistent with the various defect features observed by a variety of techniques.

Reducing Sweeping Frequencies in Microwave NDT Employing Machine Learning Feature Selection

PubMed Central

Moomen, Abdelniser; Ali, Abdulbaset; Ramahi, Omar M.

2016-01-01

Nondestructive Testing (NDT) assessment of materials’ health condition is useful for classifying healthy from unhealthy structures or detecting flaws in metallic or dielectric structures. Performing structural health testing for coated/uncoated metallic or dielectric materials with the same testing equipment requires a testing method that can work on metallics and dielectrics such as microwave testing. Reducing complexity and expenses associated with current diagnostic practices of microwave NDT of structural health requires an effective and intelligent approach based on feature selection and classification techniques of machine learning. Current microwave NDT methods in general based on measuring variation in the S-matrix over the entire operating frequency ranges of the sensors. For instance, assessing the health of metallic structures using a microwave sensor depends on the reflection or/and transmission coefficient measurements as a function of the sweeping frequencies of the operating band. The aim of this work is reducing sweeping frequencies using machine learning feature selection techniques. By treating sweeping frequencies as features, the number of top important features can be identified, then only the most influential features (frequencies) are considered when building the microwave NDT equipment. The proposed method of reducing sweeping frequencies was validated experimentally using a waveguide sensor and a metallic plate with different cracks. Among the investigated feature selection techniques are information gain, gain ratio, relief, chi-squared. The effectiveness of the selected features were validated through performance evaluations of various classification models; namely, Nearest Neighbor, Neural Networks, Random Forest, and Support Vector Machine. Results showed good crack classification accuracy rates after employing feature selection algorithms. PMID:27104533

Extracting and identifying concrete structural defects in GPR images

NASA Astrophysics Data System (ADS)

Ye, Qiling; Jiao, Liangbao; Liu, Chuanxin; Cao, Xuehong; Huston, Dryver; Xia, Tian

2018-03-01

Traditionally most GPR data interpretations are performed manually. With the advancement of computing technologies, how to automate GPR data interpretation to achieve high efficiency and accuracy has become an active research subject. In this paper, analytical characterizations of major defects in concrete structures, including delamination, air void and moisture in GPR images, are performed. In the study, the image features of different defects are compared. Algorithms are developed for defect feature extraction and identification. For validations, both simulation results and field test data are utilized.

Prediction of Protein-Protein Interaction Sites by Random Forest Algorithm with mRMR and IFS

PubMed Central

Li, Bi-Qing; Feng, Kai-Yan; Chen, Lei; Huang, Tao; Cai, Yu-Dong

2012-01-01

Prediction of protein-protein interaction (PPI) sites is one of the most challenging problems in computational biology. Although great progress has been made by employing various machine learning approaches with numerous characteristic features, the problem is still far from being solved. In this study, we developed a novel predictor based on Random Forest (RF) algorithm with the Minimum Redundancy Maximal Relevance (mRMR) method followed by incremental feature selection (IFS). We incorporated features of physicochemical/biochemical properties, sequence conservation, residual disorder, secondary structure and solvent accessibility. We also included five 3D structural features to predict protein-protein interaction sites and achieved an overall accuracy of 0.672997 and MCC of 0.347977. Feature analysis showed that 3D structural features such as Depth Index (DPX) and surface curvature (SC) contributed most to the prediction of protein-protein interaction sites. It was also shown via site-specific feature analysis that the features of individual residues from PPI sites contribute most to the determination of protein-protein interaction sites. It is anticipated that our prediction method will become a useful tool for identifying PPI sites, and that the feature analysis described in this paper will provide useful insights into the mechanisms of interaction. PMID:22937126

Structural lineament and pattern analysis of Missouri, using LANDSAT imagery

NASA Technical Reports Server (NTRS)

Martin, J. A.; Kisvarsanyi, G. (Principal Investigator)

1977-01-01

The author has identified the following significant results. Major linear, circular, and arcuate traces were observed on LANDSAT imagery of Missouri. Lineaments plotted within the state boundaries range from 20 to nearly 500 km in length. Several extend into adjoining states. Lineaments plots indicate a distinct pattern and in general reflect structural features of the Precambrian basement of the platform. Coincidence of lineaments traced from the imagery and known structural features in Missouri is high, thus supporting a causative relation between them. The lineament pattern apparently reveals a fundamental style of the deformation of the intracontinental craton. Dozens of heretofore unknown linear features related to epirogenic movements and deformation of this segment of the continental crust were delineated. Lineaments and mineralization are interrelated in a geometrically classifiable pattern.

Elements of the Chicxulub Impact Structure as Revealed in SRTM and Surface GPS Topographic Data

NASA Technical Reports Server (NTRS)

Kinsland, Gary L.; Sanchez, Gary; Kobrick, Michael; Cardador, Manuel Hurtado

2003-01-01

Pope et al. [1] utilized the elevations from the Petroleos Mexicanos (PEMEX) gravity data files to show that the main component of the surface expression of the Chicxulub Impact Structure is a roughly semi-circular, lowrelief depression about 90 km in diameter. They also identified other topographic features and the elements of the buried impact, which possibly led to the development of these features. These are summarized in Table 1. Kinsland et al. [2] presented a connection between these topographic anomalies, small gravity anomalies and buried structure of the impact. Very recently we have acquired digital topography data from NASA s Shuttle Radar Topography Mission (SRTM). Our subset covers 6 square degrees from 20deg N 91degW to 22deg N 88degW (corner to corner) with a pixel size of about 90m. This area includes all of the identified portion of the crater on land.

A feature-based approach to modeling protein-protein interaction hot spots.

PubMed

Cho, Kyu-il; Kim, Dongsup; Lee, Doheon

2009-05-01

Identifying features that effectively represent the energetic contribution of an individual interface residue to the interactions between proteins remains problematic. Here, we present several new features and show that they are more effective than conventional features. By combining the proposed features with conventional features, we develop a predictive model for interaction hot spots. Initially, 54 multifaceted features, composed of different levels of information including structure, sequence and molecular interaction information, are quantified. Then, to identify the best subset of features for predicting hot spots, feature selection is performed using a decision tree. Based on the selected features, a predictive model for hot spots is created using support vector machine (SVM) and tested on an independent test set. Our model shows better overall predictive accuracy than previous methods such as the alanine scanning methods Robetta and FOLDEF, and the knowledge-based method KFC. Subsequent analysis yields several findings about hot spots. As expected, hot spots have a larger relative surface area burial and are more hydrophobic than other residues. Unexpectedly, however, residue conservation displays a rather complicated tendency depending on the types of protein complexes, indicating that this feature is not good for identifying hot spots. Of the selected features, the weighted atomic packing density, relative surface area burial and weighted hydrophobicity are the top 3, with the weighted atomic packing density proving to be the most effective feature for predicting hot spots. Notably, we find that hot spots are closely related to pi-related interactions, especially pi . . . pi interactions.

In silico quantitative structure-toxicity relationship study of aromatic nitro compounds.

PubMed

Pasha, Farhan Ahmad; Neaz, Mohammad Morshed; Cho, Seung Joo; Ansari, Mohiuddin; Mishra, Sunil Kumar; Tiwari, Sharvan

2009-05-01

Small molecules often have toxicities that are a function of molecular structural features. Minor variations in structural features can make large difference in such toxicity. Consequently, in silico techniques may be used to correlate such molecular toxicities with their structural features. Relative to nine different sets of aromatic nitro compounds having known observed toxicities against different targets, we developed ligand-based 2D quantitative structure-toxicity relationship models using 20 selected topological descriptors. The topological descriptors have several advantages such as conformational independency, facile and less time-consuming computation to yield good results. Multiple linear regression analysis was used to correlate variations of toxicity with molecular properties. The information index on molecular size, lopping centric index and Kier flexibility index were identified as fundamental descriptors for different kinds of toxicity, and further showed that molecular size, branching and molecular flexibility might be particularly important factors in quantitative structure-toxicity relationship analysis. This study revealed that topological descriptor-guided quantitative structure-toxicity relationship provided a very useful, cost and time-efficient, in silico tool for describing small-molecule toxicities.

Choosing the Right Solution Approach: The Crucial Role of Situational Knowledge in Electricity and Magnetism

ERIC Educational Resources Information Center

Savelsbergh, Elwin R.; de Jong, Ton; Ferguson-Hessler, Monica G. M.

2011-01-01

Novice problem solvers are rather sensitive to surface problem features, and they often resort to trial and error formula matching rather than identifying an appropriate solution approach. These observations have been interpreted to imply that novices structure their knowledge according to surface features rather than according to problem type…

Model Analysis of Fine Structures of Student Models: An Example with Newton's Third Law.

ERIC Educational Resources Information Center

Bao, Lei; Hogg, Kirsten; Zollman, Dean

2002-01-01

Studies the role of context in students' uses of alternative conceptual models by using Newton's third law. Identifies four contextual features that are frequently used by students in their reasoning. Probes the effects of specific contextual features on student reasoning using a multiple-choice survey. (Contains 39 references.) (Author/YDS)

Bullying Experiences of Students with Social, Emotional and Behavioural Difficulties (SEBD)

ERIC Educational Resources Information Center

Brown Hajdukova, Eva; Hornby, Garry; Cushman, Penni

2016-01-01

This article is based on the accounts of 29 boys identified as having severe social, emotional and behavioural difficulties (SEBD) who were attending a residential school in New Zealand. Through in-depth, semi-structured and focus group interviews, a number of salient features of their schooling experiences emerged. One of these features was the…

Significant Centers of Tectonic Activity as Identified by Wrinkle Ridges for the Western Hemisphere of Mars

NASA Technical Reports Server (NTRS)

Anderson, R.C.; Haldemann, A. F. C.; Golombek, M. P.; Franklin, B. J.; Dohm, J. M.; Lias, J.

2000-01-01

The western hemisphere region of Mars has been the site of numerous scientific investigations regarding its tectonic evolution. For this region of Mars, the dominant tectonic region is the Tharsis province. Tharsis is characterized by an enormous system of radiating grabens and a circumferential system of wrinkle ridges. Past investigations of grabens associated with Tharsis have identified specific centers of tectonic activity. A recent structural analysis of the western hemisphere region of Mars which includes the Tharsis region, utilized 25,000 structures to determine the history of local and regional centers of tectonic activity based primarily on the spatial and temporal relationships of extensional features. This investigation revealed that Tharsis is more structurally complex (heterogeneous) than has been previously identified: it consists of numerous regional and local centers of tectonic activity (some are more dominant and/or more long lived than others). Here we use the same approach as Anderson et al. to determine whether the centers of tectonic activity that formed the extensional features also contributed to wrinkle ridge (compressional) formation.

Pharmacophore modeling and conformational analysis in the gas phase and in aqueous solution of regioisomeric melatonin analogs. A theoretical and experimental study

NASA Astrophysics Data System (ADS)

Mendoza-Figueroa, Humberto; Martínez-Gudiño, Gelacio; Villanueva-Luna, Jorge E.; Trujillo-Serrato, Joel J.; Morales-Ríos, Martha S.

2017-04-01

In this work, 2-(N-acylaminoalkyl)indoles 1a-1d, that incorporate a pMeOBn group at the 3-position of the indole ring were virtual screened as potential melatoninergic ligands by analog-based design study using pharmacophore modeling. Pharmacophore models for melatoninergic agonist and antagonist activity were developed in order to identify the molecular constraints that define the geometric relationship among chemical features in each model. The best hypothesis consisted of six features for agonists and eight features for antagonists. The models suggest that the agonists and antagonists can share the same 3D arrangement for the six common pharmacophoric elements identified: two hydrogen bond acceptors (HBA), one hydrogen bond donor (HBD), one hydrophobic area (H), and two aromatic rings (AR). The extra hydrofobic interaction might be used as criterion for identified the pharmacological antagonist profile. Based on the pharmacophore fit, it was found that structures 1c and 1d show a good structural overlay that meets the requirements for the antagonistic pharmacophore hypothesis. Molecular modeling studies using the PCM solvation model predicted that the most stable conformers of 1a-1d match the antagonist pharmacophore hypothesis in contrast to those in the gas phase. Structures 1a-1c were synthesized only but the activities were not tested.

Effects of lung disease on the three-dimensional structure and air flow pattern in the human airway tree

NASA Astrophysics Data System (ADS)

van de Moortele, Tristan; Nemes, Andras; Wendt, Christine; Coletti, Filippo

2016-11-01

The morphological features of the airway tree directly affect the air flow features during breathing, which determines the gas exchange and inhaled particle transport. Lung disease, Chronic Obstructive Pulmonary Disease (COPD) in this study, affects the structural features of the lungs, which in turn negatively affects the air flow through the airways. Here bronchial tree air volume geometries are segmented from Computed Tomography (CT) scans of healthy and diseased subjects. Geometrical analysis of the airway centerlines and corresponding cross-sectional areas provide insight into the specific effects of COPD on the airway structure. These geometries are also used to 3D print anatomically accurate, patient specific flow models. Three-component, three-dimensional velocity fields within these models are acquired using Magnetic Resonance Imaging (MRI). The three-dimensional flow fields provide insight into the change in flow patterns and features. Additionally, particle trajectories are determined using the velocity fields, to identify the fate of therapeutic and harmful inhaled aerosols. Correlation between disease-specific and patient-specific anatomical features with dysfunctional airflow patterns can be achieved by combining geometrical and flow analysis.

Prediction of active sites of enzymes by maximum relevance minimum redundancy (mRMR) feature selection.

PubMed

Gao, Yu-Fei; Li, Bi-Qing; Cai, Yu-Dong; Feng, Kai-Yan; Li, Zhan-Dong; Jiang, Yang

2013-01-27

Identification of catalytic residues plays a key role in understanding how enzymes work. Although numerous computational methods have been developed to predict catalytic residues and active sites, the prediction accuracy remains relatively low with high false positives. In this work, we developed a novel predictor based on the Random Forest algorithm (RF) aided by the maximum relevance minimum redundancy (mRMR) method and incremental feature selection (IFS). We incorporated features of physicochemical/biochemical properties, sequence conservation, residual disorder, secondary structure and solvent accessibility to predict active sites of enzymes and achieved an overall accuracy of 0.885687 and MCC of 0.689226 on an independent test dataset. Feature analysis showed that every category of the features except disorder contributed to the identification of active sites. It was also shown via the site-specific feature analysis that the features derived from the active site itself contributed most to the active site determination. Our prediction method may become a useful tool for identifying the active sites and the key features identified by the paper may provide valuable insights into the mechanism of catalysis.

Lamb wave detection of limpet mines on ship hulls.

PubMed

Bingham, Jill; Hinders, Mark; Friedman, Adam

2009-12-01

This paper describes the use of ultrasonic guided waves for identifying the mass loading due to underwater limpet mines on ship hulls. The Dynamic Wavelet Fingerprint Technique (DFWT) is used to render the guided wave mode information in two-dimensional binary images because the waveform features of interest are too subtle to identify in time domain. The use of wavelets allows both time and scale features from the original signals to be retained, and image processing can be used to automatically extract features that correspond to the arrival times of the guided wave modes. For further understanding of how the guided wave modes propagate through the real structures, a parallel processing, 3D elastic wave simulation is developed using the finite integration technique (EFIT). This full field, technique models situations that are too complex for analytical solutions, such as built up 3D structures. The simulations have produced informative visualizations of the guided wave modes in the structures as well as mimicking directly the output from sensors placed in the simulation space for direct comparison to experiments. Results from both drydock and in-water experiments with dummy mines are also shown.

TRANSAT-- method for detecting the conserved helices of functional RNA structures, including transient, pseudo-knotted and alternative structures.

PubMed

Wiebe, Nicholas J P; Meyer, Irmtraud M

2010-06-24

The prediction of functional RNA structures has attracted increased interest, as it allows us to study the potential functional roles of many genes. RNA structure prediction methods, however, assume that there is a unique functional RNA structure and also do not predict functional features required for in vivo folding. In order to understand how functional RNA structures form in vivo, we require sophisticated experiments or reliable prediction methods. So far, there exist only a few, experimentally validated transient RNA structures. On the computational side, there exist several computer programs which aim to predict the co-transcriptional folding pathway in vivo, but these make a range of simplifying assumptions and do not capture all features known to influence RNA folding in vivo. We want to investigate if evolutionarily related RNA genes fold in a similar way in vivo. To this end, we have developed a new computational method, Transat, which detects conserved helices of high statistical significance. We introduce the method, present a comprehensive performance evaluation and show that Transat is able to predict the structural features of known reference structures including pseudo-knotted ones as well as those of known alternative structural configurations. Transat can also identify unstructured sub-sequences bound by other molecules and provides evidence for new helices which may define folding pathways, supporting the notion that homologous RNA sequence not only assume a similar reference RNA structure, but also fold similarly. Finally, we show that the structural features predicted by Transat differ from those assuming thermodynamic equilibrium. Unlike the existing methods for predicting folding pathways, our method works in a comparative way. This has the disadvantage of not being able to predict features as function of time, but has the considerable advantage of highlighting conserved features and of not requiring a detailed knowledge of the cellular environment.

Application of MSS/LANDSAT images to the structural study of recent sedimentary areas: Campos Sedimentary Basin, Rio de Janeiro, Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Barbosa, M. P.

1983-01-01

Visual and computer aided interpretation of MSS/LANDSAT data identified linear and circular features which represent the ""reflexes'' of the crystalline basement structures in the Cenozoic sediments of the emergent part of the Campos Sedimentary Basin.

Supportability of a High-Yield-Stress Slurry in a New Stereolithography-Based Ceramic Fabrication Process

NASA Astrophysics Data System (ADS)

He, Li; Song, Xuan

2018-03-01

In recent years, ceramic fabrication using stereolithography (SLA) has gained in popularity because of its high accuracy and density that can be achieved in the final part of production. One of the key challenges in ceramic SLA is that support structures are required for building overhanging features, whereas removing these support structures without damaging the components is difficult. In this research, a suspension-enclosing projection-stereolithography process is developed to overcome this challenge. This process uses a high-yield-stress ceramic slurry as the feedstock material and exploits the elastic force of the material to support overhanging features without the need for building additional support structures. Ceramic slurries with different solid loadings are studied to identify the rheological properties most suitable for supporting overhanging features. An analytical model of a double doctor-blade module is established to obtain uniform and thin recoating layers from a high-yield-stress slurry. Several test cases highlight the feasibility of using a high-yield-stress slurry to support overhanging features in SLA.

Structural Mass Spectrometry of Proteins Using Hydroxyl Radical Based Protein Footprinting

PubMed Central

Wang, Liwen; Chance, Mark R.

2011-01-01

Structural MS is a rapidly growing field with many applications in basic research and pharmaceutical drug development. In this feature article the overall technology is described and several examples of how hydroxyl radical based footprinting MS can be used to map interfaces, evaluate protein structure, and identify ligand dependent conformational changes in proteins are described. PMID:21770468

Complex Spiral Structure in the HD 100546 Transitional Disk as Revealed by GPI and MagAO

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

Follette, Katherine B.; Macintosh, Bruce; Mullen, Wyatt

We present optical and near-infrared high-contrast images of the transitional disk HD 100546 taken with the Magellan Adaptive Optics system (MagAO) and the Gemini Planet Imager (GPI). GPI data include both polarized intensity and total intensity imagery, and MagAO data are taken in Simultaneous Differential Imaging mode at H α . The new GPI H -band total intensity data represent a significant enhancement in sensitivity and field rotation compared to previous data sets and enable a detailed exploration of substructure in the disk. The data are processed with a variety of differential imaging techniques (polarized, angular, reference, and simultaneous differentialmore » imaging) in an attempt to identify the disk structures that are most consistent across wavelengths, processing techniques, and algorithmic parameters. The inner disk cavity at 15 au is clearly resolved in multiple data sets, as are a variety of spiral features. While the cavity and spiral structures are identified at levels significantly distinct from the neighboring regions of the disk under several algorithms and with a range of algorithmic parameters, emission at the location of HD 100546 “ c ” varies from point-like under aggressive algorithmic parameters to a smooth continuous structure with conservative parameters, and is consistent with disk emission. Features identified in the HD 100546 disk bear qualitative similarity to computational models of a moderately inclined two-armed spiral disk, where projection effects and wrapping of the spiral arms around the star result in a number of truncated spiral features in forward-modeled images.« less

A feature-based approach to modeling protein–protein interaction hot spots

PubMed Central

Cho, Kyu-il; Kim, Dongsup; Lee, Doheon

2009-01-01

Identifying features that effectively represent the energetic contribution of an individual interface residue to the interactions between proteins remains problematic. Here, we present several new features and show that they are more effective than conventional features. By combining the proposed features with conventional features, we develop a predictive model for interaction hot spots. Initially, 54 multifaceted features, composed of different levels of information including structure, sequence and molecular interaction information, are quantified. Then, to identify the best subset of features for predicting hot spots, feature selection is performed using a decision tree. Based on the selected features, a predictive model for hot spots is created using support vector machine (SVM) and tested on an independent test set. Our model shows better overall predictive accuracy than previous methods such as the alanine scanning methods Robetta and FOLDEF, and the knowledge-based method KFC. Subsequent analysis yields several findings about hot spots. As expected, hot spots have a larger relative surface area burial and are more hydrophobic than other residues. Unexpectedly, however, residue conservation displays a rather complicated tendency depending on the types of protein complexes, indicating that this feature is not good for identifying hot spots. Of the selected features, the weighted atomic packing density, relative surface area burial and weighted hydrophobicity are the top 3, with the weighted atomic packing density proving to be the most effective feature for predicting hot spots. Notably, we find that hot spots are closely related to π–related interactions, especially π · · · π interactions. PMID:19273533

The future of primordial features with large-scale structure surveys

NASA Astrophysics Data System (ADS)

Chen, Xingang; Dvorkin, Cora; Huang, Zhiqi; Namjoo, Mohammad Hossein; Verde, Licia

2016-11-01

Primordial features are one of the most important extensions of the Standard Model of cosmology, providing a wealth of information on the primordial Universe, ranging from discrimination between inflation and alternative scenarios, new particle detection, to fine structures in the inflationary potential. We study the prospects of future large-scale structure (LSS) surveys on the detection and constraints of these features. We classify primordial feature models into several classes, and for each class we present a simple template of power spectrum that encodes the essential physics. We study how well the most ambitious LSS surveys proposed to date, including both spectroscopic and photometric surveys, will be able to improve the constraints with respect to the current Planck data. We find that these LSS surveys will significantly improve the experimental sensitivity on features signals that are oscillatory in scales, due to the 3D information. For a broad range of models, these surveys will be able to reduce the errors of the amplitudes of the features by a factor of 5 or more, including several interesting candidates identified in the recent Planck data. Therefore, LSS surveys offer an impressive opportunity for primordial feature discovery in the next decade or two. We also compare the advantages of both types of surveys.

The future of primordial features with large-scale structure surveys

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

Chen, Xingang; Namjoo, Mohammad Hossein; Dvorkin, Cora

2016-11-01

Primordial features are one of the most important extensions of the Standard Model of cosmology, providing a wealth of information on the primordial Universe, ranging from discrimination between inflation and alternative scenarios, new particle detection, to fine structures in the inflationary potential. We study the prospects of future large-scale structure (LSS) surveys on the detection and constraints of these features. We classify primordial feature models into several classes, and for each class we present a simple template of power spectrum that encodes the essential physics. We study how well the most ambitious LSS surveys proposed to date, including both spectroscopicmore » and photometric surveys, will be able to improve the constraints with respect to the current Planck data. We find that these LSS surveys will significantly improve the experimental sensitivity on features signals that are oscillatory in scales, due to the 3D information. For a broad range of models, these surveys will be able to reduce the errors of the amplitudes of the features by a factor of 5 or more, including several interesting candidates identified in the recent Planck data. Therefore, LSS surveys offer an impressive opportunity for primordial feature discovery in the next decade or two. We also compare the advantages of both types of surveys.« less

A comparative study of sequence- and structure-based features of small RNAs and other RNAs of bacteria.

PubMed

Barik, Amita; Das, Santasabuj

2018-01-02

Small RNAs (sRNAs) in bacteria have emerged as key players in transcriptional and post-transcriptional regulation of gene expression. Here, we present a statistical analysis of different sequence- and structure-related features of bacterial sRNAs to identify the descriptors that could discriminate sRNAs from other bacterial RNAs. We investigated a comprehensive and heterogeneous collection of 816 sRNAs, identified by northern blotting across 33 bacterial species and compared their various features with other classes of bacterial RNAs, such as tRNAs, rRNAs and mRNAs. We observed that sRNAs differed significantly from the rest with respect to G+C composition, normalized minimum free energy of folding, motif frequency and several RNA-folding parameters like base-pairing propensity, Shannon entropy and base-pair distance. Based on the selected features, we developed a predictive model using Random Forests (RF) method to classify the above four classes of RNAs. Our model displayed an overall predictive accuracy of 89.5%. These findings would help to differentiate bacterial sRNAs from other RNAs and further promote prediction of novel sRNAs in different bacterial species.

Research on recognition of the geologic framework of porphyry copper deposits on ERTS-1 imagery. [New Guinea, Alaska, and Colorado

NASA Technical Reports Server (NTRS)

Wilson, J. C. (Principal Investigator)

1975-01-01

The author has identified the following significant results. Many new linear and circular features were found. These features prompted novel tectonic classification and analysis especially in the Ray and Ely areas. Tectonic analyses of the Ok Tedi, Tanacross, and Silvertone areas follow conventional interpretations. Circular features are mapped in many cases and are interpreted as exposed or covered intrusive centers. The small circular features reported in the Ok Tedi test area are valid and useful correlations with tertiary intrusion and volcanism in this remote part of New Guinea. Several major faults of regional dimensions, such as the Denali fault in Alaska and the Colorado mineral belt structures in Colorado are detected in the imagery. Many more faults and regional structures are found in the imagery than exist on present maps.

Critical Song Features for Auditory Pattern Recognition in Crickets

PubMed Central

Meckenhäuser, Gundula; Hennig, R. Matthias; Nawrot, Martin P.

2013-01-01

Many different invertebrate and vertebrate species use acoustic communication for pair formation. In the cricket Gryllus bimaculatus, females recognize their species-specific calling song and localize singing males by positive phonotaxis. The song pattern of males has a clear structure consisting of brief and regular pulses that are grouped into repetitive chirps. Information is thus present on a short and a long time scale. Here, we ask which structural features of the song critically determine the phonotactic performance. To this end we employed artificial neural networks to analyze a large body of behavioral data that measured females’ phonotactic behavior under systematic variation of artificially generated song patterns. In a first step we used four non-redundant descriptive temporal features to predict the female response. The model prediction showed a high correlation with the experimental results. We used this behavioral model to explore the integration of the two different time scales. Our result suggested that only an attractive pulse structure in combination with an attractive chirp structure reliably induced phonotactic behavior to signals. In a further step we investigated all feature sets, each one consisting of a different combination of eight proposed temporal features. We identified feature sets of size two, three, and four that achieve highest prediction power by using the pulse period from the short time scale plus additional information from the long time scale. PMID:23437054

Application of PALSAR-2 remote sensing data for structural geology and topographic mapping in Kelantan river basin, Malaysia

NASA Astrophysics Data System (ADS)

Beiranvand Pour, Amin; Hashim, Mazlan

2016-06-01

Natural hazards of geological origin are one of major problem during heavy monsoons rainfall in Kelantan state, peninsular Malaysia. Several landslides occur in this region are obviously connected to geological and topographical features, every year. Satellite synthetic aperture radar (SAR) data are particularly applicable for detection of geological structural and topographical features in tropical conditions. In this study, Phased Array type L-band Synthetic Aperture Radar (PALSAR-2), remote sensing data were used to identify high potential risk and susceptible zones for landslide in the Kelantan river basin. Adaptive Local Sigma filter was selected and applied to accomplish speckle reduction and preserving both edges and features in PALSAR-2 fine mode observation images. Different polarization images were integrated to enhance geological structures. Additionally, directional filters were applied to the PALSAR-2 Local Sigma resultant image for edge enhancement and detailed identification of linear features. Several faults, drainage patterns and lithological contact layers were identified at regional scale. In order to assess the results, fieldwork and GPS survey were conducted in the landslide affected zones in the Kelantan river basin. Results demonstrate the most of the landslides were associated with N-S, NNW-SSE and NE-SW trending faults, angulate drainage pattern and metamorphic and Quaternary units. Consequently, geologic structural map were produced for Kelantan river basin using recent PALSAR-2 data, which could be broadly applicable for landslide hazard assessment and delineation of high potential risk and susceptible areas. Landslide mitigation programmes could be conducted in the landslide recurrence regions for reducing catastrophes leading to economic losses and death.

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

Ruan, D; Shao, W; Low, D

Purpose: To evaluate and test the hypothesis that plan quality may be systematically affected by treatment delivery techniques and target-tocritical structure geometric relationship in radiotherapy for brain tumor. Methods: Thirty-four consecutive brain tumor patients treated between 2011–2014 were analyzed. Among this cohort, 10 were planned with 3DCRT, 11 with RadipArc, and 13 with helical IMRT on TomoTherapy. The selected dosimetric endpoints (i.e., PTV V100, maximum brainstem/chiasm/ optic nerve doses) were considered as a vector in a highdimensional space. A Pareto analysis was performed to identify the subset of Pareto-efficient plans.The geometric relationships, specifically the overlapping volume and centroid-of-mass distance betweenmore » each critical structure to the PTV were extracted as potential geometric features. The classification-tree analyses were repeated using these geometric features with and without the treatment modality as an additional categorical predictor. In both scenarios, the dominant features to prognosticate the Pareto membership were identified and the tree structures to provide optimal inference were recorded. The classification performance was further analyzed to determine the role of treatment modality in affecting plan quality. Results: Seven Pareto-efficient plans were identified based on dosimetric endpoints (3 from 3DCRT, 3 from RapicArc, 1 from Tomo), which implies that the evaluated treatment modality may have a minor influence on plan quality. Classification trees with/without the treatment modality as a predictor both achieved accuracy of 88.2%: with 100% sensitivity and 87.1% specificity for the former, and 66.7% sensitivity and 96.0% specificity for the latter. The coincidence of accuracy from both analyses further indicates no-to-weak dependence of plan quality on treatment modality. Both analyses have identified the brainstem to PTV distance as the primary predictive feature for Pareto-efficiency. Conclusion: Pareto evaluation and classification-tree analyses have indicated that plan quality depends strongly on geometry for brain tumor, specifically PTV-tobrain-stem-distance but minimally on treatment modality.« less

Remote sensing of geologic mineral occurrences for the Colorado mineral belt using LANDSAT data

NASA Technical Reports Server (NTRS)

Carpenter, R. H. (Principal Investigator); Trexler, D. W.

1976-01-01

The author has identified the following significant results. LANDSAT imagery was examined as a practical and productive tool for mineral exploration along the Colorado Mineral Belt. An attempt was made to identify all large, active and/or abandoned mining districts on the imagery which initially were discovered by surface manifestations. A number of strong photolinements, circular features, and color anomalies were identified. Some of these form a part of the structural and igneous volcanic framework in which mineral deposits occur. No specific mineral deposits such as veins or porphyries were identified. Promising linear and concentric features were field checked at several locations. Some proved to be fault zones and calderas; others were strictly topographic features related to stream or glacial entrenchment. The Silverton Caldera region and the Idaho Springs-Central City district were chosen and studied as case histories to evaluate the application of LANDSAT imagery to mineral exploration. Evidence of specific mineralization related to ore deposits in these two areas were observed only on low level photography.

Ancestral multipartite units in light-responsive plant promoters have structural features correlating with specific phototransduction pathways.

PubMed Central

Argüello-Astorga, G R; Herrera-Estrella, L R

1996-01-01

Regulation of plant gene transcription by light is mediated by multipartite cis-regulatory units. Previous attempts to identify structural features that are common to all light-responsive elements (LREs) have been unsuccessful. To address the question of what is needed to confer photoresponsiveness to a promoter, the upstream sequences from more than 110 light-regulated plant genes were analyzed by a new, phylogenetic-structural method. As a result, 30 distinct conserved DNA module arrays (CMAs) associated with light-responsive promoter regions were identified. Several of these CMAs have remained invariant throughout the evolutionary radiation of angiosperms and are conserved between homologous genes as well as between members of different gene families. The identified CMAs share a gene superfamily-specific core that correlates with the particular phytochrome-dependent transduction pathway that controls their expression, i.e. ACCTA(A/C)C(A/C) for the cGMP-dependent phenylpropanoid metabolism-associated genes, and GATA(A/T)GR for the Ca2+/calmodulin-dependent photosynthesis-associated nuclear genes. In addition to suggesting a general model for the functional and structural organization of LREs, the data obtained in this study indicate that angiosperm LREs probably evolved from complex cis-acting elements involved in regulatory processes other than photoregulation in gymnosperms. PMID:8938415

An evaluation of the suitability of ERTS data for the purposes of petroleum exploration. [lithology and geological structure of Anadarko Basin of Oklahoma and Texas

NASA Technical Reports Server (NTRS)

Collins, R. J. (Principal Investigator); Mccown, F. P.; Stonis, L. P.; Petzel, G. J.; Everett, J. R.

1974-01-01

The author has identified the following significant results. ERTS-1 data give exploration geologists a new perspective for looking at the earth. The data are excellent for interpreting regional lithologic and structural relationships and quickly directing attention to areas of greatest exploration interest. Information derived from ERTS data useful for petroleum exploration include: linear features, general lithologic distribution, identification of various anomalous features, some details of structures controlling hydrocarbon accumulation, overall structural relationships, and the regional context of the exploration province. Many anomalies (particularly geomorphic anomalies) correlate with known features of petroleum exploration interest. Linears interpreted from the imagery that were checked in the field correlate with fractures. Bands 5 and 7 and color composite imagery acquired during the periods of maximum and minimum vegetation vigor are best for geologic interpretation. Preliminary analysis indicates that use of ERTS imagery can substantially reduce the cost of petroleum exploration in relatively unexplored areas.

What Experiences Do Expository Books on Recommended Book Lists Offer to K-2 Students?

ERIC Educational Resources Information Center

Kletzien, Sharon B.; Dreher, Mariam Jean

2017-01-01

Teachers can use expository texts to teach academic vocabulary, content knowledge, text structure, and text features. National associations' recommended book lists are often used to identify books for classrooms. Previously we identified expository texts on these lists from 2001-2002 and 2011-2012. The current study explored instructional…

Linguistic Legitimation of Political Events in Newspaper Discourse

ERIC Educational Resources Information Center

Ali, Marwah Kareem; Christopher, Anne A.; Nordin, Munif Zarirruddin Fikri B.

2016-01-01

This paper examines the discursive structures employed in legitimizing the event of U.S. forces withdrawal from Iraq and identifies them in relation to linguistic features. It attempts to describe the relation between language use and legitimation discursive structures in depicting political events. The paper focuses on the political event of U.S.…

The Latent Structure of Psychopathy in Youth: A Taxometric Investigation

ERIC Educational Resources Information Center

Vasey, Michael W.; Kotov, Roman; Frick, Paul J.; Loney, Bryan R.

2005-01-01

Using taxometric procedures, the latent structure of psychopathy was investigated in two studies of children and adolescents. Prior studies have identified a taxon (i.e., a natural category) associated with antisocial behavior in adults as well as children and adolescents. However, features of this taxon suggest that it is not psychopathy but…

Document boundary determination using structural and lexical analysis

NASA Astrophysics Data System (ADS)

Taghva, Kazem; Cartright, Marc-Allen

2009-01-01

The document boundary determination problem is the process of identifying individual documents in a stack of papers. In this paper, we report on a classification system for automation of this process. The system employs features based on document structure and lexical content. We also report on experimental results to support the effectiveness of this system.

Structural and functional connectional fingerprints in mild cognitive impairment and Alzheimer's disease patients.

PubMed

Son, Seong-Jin; Kim, Jonghoon; Park, Hyunjin

2017-01-01

Regional volume atrophy and functional degeneration are key imaging hallmarks of Alzheimer's disease (AD) in structural and functional magnetic resonance imaging (MRI), respectively. We jointly explored regional volume atrophy and functional connectivity to better characterize neuroimaging data of AD and mild cognitive impairment (MCI). All data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We compared regional volume atrophy and functional connectivity in 10 subcortical regions using structural MRI and resting-state functional MRI (rs-fMRI). Neuroimaging data of normal controls (NC) (n = 35), MCI (n = 40), and AD (n = 30) were compared. Significant differences of regional volumes and functional connectivity measures between groups were assessed using permutation tests in 10 regions. The regional volume atrophy and functional connectivity of identified regions were used as features for the random forest classifier to distinguish among three groups. The features of the identified regions were also regarded as connectional fingerprints that could distinctively separate a given group from the others. We identified a few regions with distinctive regional atrophy and functional connectivity patterns for NC, MCI, and AD groups. A three label classifier using the information of regional volume atrophy and functional connectivity of identified regions achieved classification accuracy of 53.33% to distinguish among NC, MCI, and AD. We identified distinctive regional atrophy and functional connectivity patterns that could be regarded as a connectional fingerprint.

Structural and functional connectional fingerprints in mild cognitive impairment and Alzheimer’s disease patients

PubMed Central

Son, Seong-Jin; Kim, Jonghoon

2017-01-01

Regional volume atrophy and functional degeneration are key imaging hallmarks of Alzheimer’s disease (AD) in structural and functional magnetic resonance imaging (MRI), respectively. We jointly explored regional volume atrophy and functional connectivity to better characterize neuroimaging data of AD and mild cognitive impairment (MCI). All data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We compared regional volume atrophy and functional connectivity in 10 subcortical regions using structural MRI and resting-state functional MRI (rs-fMRI). Neuroimaging data of normal controls (NC) (n = 35), MCI (n = 40), and AD (n = 30) were compared. Significant differences of regional volumes and functional connectivity measures between groups were assessed using permutation tests in 10 regions. The regional volume atrophy and functional connectivity of identified regions were used as features for the random forest classifier to distinguish among three groups. The features of the identified regions were also regarded as connectional fingerprints that could distinctively separate a given group from the others. We identified a few regions with distinctive regional atrophy and functional connectivity patterns for NC, MCI, and AD groups. A three label classifier using the information of regional volume atrophy and functional connectivity of identified regions achieved classification accuracy of 53.33% to distinguish among NC, MCI, and AD. We identified distinctive regional atrophy and functional connectivity patterns that could be regarded as a connectional fingerprint. PMID:28333946

A new diagnostic method of bolt loosening detection for thermal protection systems

NASA Astrophysics Data System (ADS)

Xie, Weihua; Meng, Songhe; Han, Jiecai; Du, Shanyi; Zhang, Boming; Yu, Dong

2009-07-01

Research and development efforts are underway to provide structural health monitoring systems to ensure the integrity of thermal protection system (TPS). An improved analytical method was proposed to assess the fastener integrity of a bolted structure in this paper. A new unsymmetrical washer was designed and fabricated, taking full advantage of piezoelectric ceramics (PZT) to play both roles as actuators and sensors, and using energy as the only extracted feature to identify abnormality. This diagnostic method is not restricted by the materials of the bracket, panel and base structure of the TPS whose condition is under inspection. A series of experiments on a metallic honeycomb sandwich panel were completed to demonstrate the capability of detecting bolt loosening on the TPS structure. Studies showed that this method can be used not only to identify the location of loosened bolts rapidly, but also to estimate the torque level of loosening bolts. Since that energy is the only extracted feature used to detect bolt loosening in this method, the diagnostic process become very simple and swift without sacrificing the accuracy of the results.

Latent topic discovery of clinical concepts from hospital discharge summaries of a heterogeneous patient cohort.

PubMed

Lehman, Li-Wei; Long, William; Saeed, Mohammed; Mark, Roger

2014-01-01

Patients in critical care often exhibit complex disease patterns. A fundamental challenge in clinical research is to identify clinical features that may be characteristic of adverse patient outcomes. In this work, we propose a data-driven approach for phenotype discovery of patients in critical care. We used Hierarchical Dirichlet Process (HDP) as a non-parametric topic modeling technique to automatically discover the latent "topic" structure of diseases, symptoms, and findings documented in hospital discharge summaries. We show that the latent topic structure can be used to reveal phenotypic patterns of diseases and symptoms shared across subgroups of a patient cohort, and may contain prognostic value in stratifying patients' post hospital discharge mortality risks. Using discharge summaries of a large patient cohort from the MIMIC II database, we evaluate the clinical utility of the discovered topic structure in identifying patients who are at high risk of mortality within one year post hospital discharge. We demonstrate that the learned topic structure has statistically significant associations with mortality post hospital discharge, and may provide valuable insights in defining new feature sets for predicting patient outcomes.

A naturalistic study of railway controllers.

PubMed

Farrington-Darby, T; Wilson, John R; Norris, B J; Clarke, Theresa

There is an increasing prevalence for work to be analysed through naturalistic study, especially using ethnographically derived methods of enquiry and qualitative field research. The relatively unexplored domain of railway control (in comparison to signalling) in the UK is described in terms of features derived from observations and semi-structured interviews. In addition, task diagrams (a technique taken from the Applied Cognitive Task Analysis toolkit) are used to represent controllers' core elements of work, i.e. to manage events or incidents, and to identify the challenging steps in the process. The work features identified, the task diagrams, and the steps identified as challenging form a basis from which future ergonomics studies on railway controllers in the UK will be carried out.

A Systematic Review of Behavioral Interventions to Reduce Condomless Sex and Increase HIV Testing for Latino MSM.

PubMed

Pérez, Ashley; Santamaria, E Karina; Operario, Don

2017-12-15

Latino men who have sex with men (MSM) in the United States are disproportionately affected by HIV, and there have been calls to improve availability of culturally sensitive HIV prevention programs for this population. This article provides a systematic review of intervention programs to reduce condomless sex and/or increase HIV testing among Latino MSM. We searched four electronic databases using a systematic review protocol, screened 1777 unique records, and identified ten interventions analyzing data from 2871 Latino MSM. Four studies reported reductions in condomless anal intercourse, and one reported reductions in number of sexual partners. All studies incorporated surface structure cultural features such as bilingual study recruitment, but the incorporation of deep structure cultural features, such as machismo and sexual silence, was lacking. There is a need for rigorously designed interventions that incorporate deep structure cultural features in order to reduce HIV among Latino MSM.

In vivo genome-wide profiling of RNA secondary structure reveals novel regulatory features.

PubMed

Ding, Yiliang; Tang, Yin; Kwok, Chun Kit; Zhang, Yu; Bevilacqua, Philip C; Assmann, Sarah M

2014-01-30

RNA structure has critical roles in processes ranging from ligand sensing to the regulation of translation, polyadenylation and splicing. However, a lack of genome-wide in vivo RNA structural data has limited our understanding of how RNA structure regulates gene expression in living cells. Here we present a high-throughput, genome-wide in vivo RNA structure probing method, structure-seq, in which dimethyl sulphate methylation of unprotected adenines and cytosines is identified by next-generation sequencing. Application of this method to Arabidopsis thaliana seedlings yielded the first in vivo genome-wide RNA structure map at nucleotide resolution for any organism, with quantitative structural information across more than 10,000 transcripts. Our analysis reveals a three-nucleotide periodic repeat pattern in the structure of coding regions, as well as a less-structured region immediately upstream of the start codon, and shows that these features are strongly correlated with translation efficiency. We also find patterns of strong and weak secondary structure at sites of alternative polyadenylation, as well as strong secondary structure at 5' splice sites that correlates with unspliced events. Notably, in vivo structures of messenger RNAs annotated for stress responses are poorly predicted in silico, whereas mRNA structures of genes related to cell function maintenance are well predicted. Global comparison of several structural features between these two categories shows that the mRNAs associated with stress responses tend to have more single-strandedness, longer maximal loop length and higher free energy per nucleotide, features that may allow these RNAs to undergo conformational changes in response to environmental conditions. Structure-seq allows the RNA structurome and its biological roles to be interrogated on a genome-wide scale and should be applicable to any organism.

Detecting sign-changing superconducting gap in LiFeAs using quasiparticle interference

NASA Astrophysics Data System (ADS)

Altenfeld, D.; Hirschfeld, P. J.; Mazin, I. I.; Eremin, I.

2018-02-01

Using a realistic ten-orbital tight-binding model Hamiltonian fitted to the angle-resolved photoemission spectroscopy data on LiFeAs, we analyze the temperature, frequency, and momentum dependencies of quasiparticle interference to identify gap sign changes in a qualitative way, following our original proposal [Phys. Rev. B 92, 184513 (2015), 10.1103/PhysRevB.92.184513]. We show that all features present for the simple two-band model for the sign-changing s+--wave superconducting gap employed previously are still present in the realistic tight-binding approximation and gap values observed experimentally. We discuss various superconducting gap structures proposed for LiFeAs and identify various features of these superconducting gap functions in the quasiparticle interference patterns. On the other hand, we show that it will be difficult to identify the more complicated possible sign structures of the hole pocket gaps in LiFeAs due to the smallness of the pockets and the near proximity of two of the gap energies.

Virtual screening studies on HIV-1 reverse transcriptase inhibitors to design potent leads.

PubMed

Vadivelan, S; Deeksha, T N; Arun, S; Machiraju, Pavan Kumar; Gundla, Rambabu; Sinha, Barij Nayan; Jagarlapudi, Sarma A R P

2011-03-01

The purpose of this study is to identify novel and potent inhibitors against HIV-1 reverse transcriptase (RT). The crystal structure of the most active ligand was converted into a feature-shaped query. This query was used to align molecules to generate statistically valid 3D-QSAR (r(2) = 0.873) and Pharmacophore models (HypoGen). The best HypoGen model consists of three Pharmacophore features (one hydrogen bond acceptor, one hydrophobic aliphatic and one ring aromatic) and further validated using known RT inhibitors. The designed novel inhibitors are further subjected to docking studies to reduce the number of false positives. We have identified and proposed some novel and potential lead molecules as reverse transcriptase inhibitors using analog and structure based studies. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

Intelligent feature selection techniques for pattern classification of Lamb wave signals

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

Hinders, Mark K.; Miller, Corey A.

2014-02-18

Lamb wave interaction with flaws is a complex, three-dimensional phenomenon, which often frustrates signal interpretation schemes based on mode arrival time shifts predicted by dispersion curves. As the flaw severity increases, scattering and mode conversion effects will often dominate the time-domain signals, obscuring available information about flaws because multiple modes may arrive on top of each other. Even for idealized flaw geometries the scattering and mode conversion behavior of Lamb waves is very complex. Here, multi-mode Lamb waves in a metal plate are propagated across a rectangular flat-bottom hole in a sequence of pitch-catch measurements corresponding to the double crossholemore » tomography geometry. The flaw is sequentially deepened, with the Lamb wave measurements repeated at each flaw depth. Lamb wave tomography reconstructions are used to identify which waveforms have interacted with the flaw and thereby carry information about its depth. Multiple features are extracted from each of the Lamb wave signals using wavelets, which are then fed to statistical pattern classification algorithms that identify flaw severity. In order to achieve the highest classification accuracy, an optimal feature space is required but it’s never known a priori which features are going to be best. For structural health monitoring we make use of the fact that physical flaws, such as corrosion, will only increase over time. This allows us to identify feature vectors which are topologically well-behaved by requiring that sequential classes “line up” in feature vector space. An intelligent feature selection routine is illustrated that identifies favorable class distributions in multi-dimensional feature spaces using computational homology theory. Betti numbers and formal classification accuracies are calculated for each feature space subset to establish a correlation between the topology of the class distribution and the corresponding classification accuracy.« less

Features of the Correlation Structure of Price Indices

PubMed Central

Gao, Xiangyun; An, Haizhong; Zhong, Weiqiong

2013-01-01

What are the features of the correlation structure of price indices? To answer this question, 5 types of price indices, including 195 specific price indices from 2003 to 2011, were selected as sample data. To build a weighted network of price indices each price index is represented by a vertex, and a positive correlation between two price indices is represented by an edge. We studied the features of the weighted network structure by applying economic theory to the analysis of complex network parameters. We found that the frequency of the price indices follows a normal distribution by counting the weighted degrees of the nodes, and we identified the price indices which have an important impact on the network's structure. We found out small groups in the weighted network by the methods of k-core and k-plex. We discovered structure holes in the network by calculating the hierarchy of the nodes. Finally, we found that the price indices weighted network has a small-world effect by calculating the shortest path. These results provide a scientific basis for macroeconomic control policies. PMID:23593399

A feature-based developmental model of the infant brain in structural MRI.

PubMed

Toews, Matthew; Wells, William M; Zöllei, Lilla

2012-01-01

In this paper, anatomical development is modeled as a collection of distinctive image patterns localized in space and time. A Bayesian posterior probability is defined over a random variable of subject age, conditioned on data in the form of scale-invariant image features. The model is automatically learned from a large set of images exhibiting significant variation, used to discover anatomical structure related to age and development, and fit to new images to predict age. The model is applied to a set of 230 infant structural MRIs of 92 subjects acquired at multiple sites over an age range of 8-590 days. Experiments demonstrate that the model can be used to identify age-related anatomical structure, and to predict the age of new subjects with an average error of 72 days.

Effects of achievement contexts on the meaning structure of emotion words.

PubMed

Gentsch, Kornelia; Loderer, Kristina; Soriano, Cristina; Fontaine, Johnny R J; Eid, Michael; Pekrun, Reinhard; Scherer, Klaus R

2018-03-01

Little is known about the impact of context on the meaning of emotion words. In the present study, we used a semantic profiling instrument (GRID) to investigate features representing five emotion components (appraisal, bodily reaction, expression, action tendencies, and feeling) of 11 emotion words in situational contexts involving success or failure. We compared these to the data from an earlier study in which participants evaluated the typicality of features out of context. Profile analyses identified features for which typicality changed as a function of context for all emotion words, except contentment, with appraisal features being most frequently affected. Those context effects occurred for both hypothesised basic and non-basic emotion words. Moreover, both data sets revealed a four-dimensional structure. The four dimensions were largely similar (valence, power, arousal, and novelty). The results suggest that context may not change the underlying dimensionality but affects facets of the meaning of emotion words.

Nakhla: a Martian Meteorite with Indigenous Organic Carbonaceous Features

NASA Technical Reports Server (NTRS)

McKay, D. S.; Gibson, E. K.; Thomas-Keprta, K. L.; Clemett, S. J.; Le, L.; Rahman, Z.; Wentworth, S. J.

2011-01-01

The Nakhla meteorite possesses discrete, well defined, structurally coherent morphologies of carbonaceous phases present within iddingsite alteration zones. Based upon both isotopic measurements and analysis of organic phases the presence of pre-terrestrial organics is now recognized. Within the microcrystalline layers of Nakhla s iddingsite, discrete clusters of salt crystals are present. These salts are predominantly halite (NaCl) with minor MgCl2 crystals. Some CaSO4, likely gypsum, appears to be partially intergrown with some of the halite. EDX mapping shows discrete C-rich features are interspersed among these crystals. A hollow semi-spherical bowl structure ( 3 m ) has been identified and analyzed after using a focused ion beam (FIB) to cut a transverse TEM thin section of the feature and the underlying iddingsite. TEM/EDX analysis reveals that the feature is primarily carbonaceous containing C with lesser amounts of Si, S, Ca, Cl, F, Na, and minor Mn and Fe; additionally a small peak consistent with N, which has been previously seen in Nakhla carbonaceous matter, is also present. Selected area electron diffraction (SAED) shows that this C-rich material is amorphous (lacking any long-range crystallographic order) and is not graphite or carbonate. Micro-Raman spectra acquired from the same surface from which the FIB section was extracted demonstrate a typical kerogen-like D and G band structure with a weak absorption peak at 1350 and a stronger peak at 1600/cm. The C-rich feature is intimately associated with both the surrounding halite and underlying iddingsite matrix. Both iddingsite and salts are interpreted as having formed as evaporate assemblages from progressive evaporation of water bodies on Mars. This assemblage, sans the carbonaceous moieties, closely resembles iddingsite alteration features previously described which were interpreted as indigenous Martian assemblages. These distinctive macromolecular carbonaceous structures in Nakhla may represent one of the sources of the high molecular weight organic material previously identified in Nakhla. While we do not speculate on the origin of these unique carbonaceous structures, we note that the significance of such observations is that it may allow us to construct a C-cycle for Mars based on the C chemistry of the Martian meteorites with obvious implications for astrobiology and the prebiotic evolution of Mars. In any case, our observations strongly suggest that organic C exists as micrometersize, discrete structures on Mars.

Progressive Fracture of Composite Structures

NASA Technical Reports Server (NTRS)

Minnetyan, Levon

2001-01-01

This report includes the results of a research in which the COmposite Durability STRuctural ANalysis (CODSTRAN) computational simulation capabilities were augmented and applied to various structures for demonstration of the new features and verification. The first chapter of this report provides an introduction to the computational simulation or virtual laboratory approach for the assessment of damage and fracture progression characteristics in composite structures. The second chapter outlines the details of the overall methodology used, including the failure criteria and the incremental/iterative loading procedure with the definitions of damage, fracture, and equilibrium states. The subsequent chapters each contain an augmented feature of the code and/or demonstration examples. All but one of the presented examples contains laminated composite structures with various fiber/matrix constituents. For each structure simulated, damage initiation and progression mechanisms are identified and the structural damage tolerance is quantified at various degradation stages. Many chapters contain the simulation of defective and defect free structures to evaluate the effects of existing defects on structural durability.

Structural and lithologic study of northern coast ranges and Sacramento Valley, California

NASA Technical Reports Server (NTRS)

Rich, E. I. (Principal Investigator)

1973-01-01

The author has identified the following significant results. The pattern of linear systems within the project area has been extended into the western foothill belt of the Sierra Nevada. The chief pattern of linear features in the western Sierran foothill belt trends about N. 10 - 15 deg W., but in the vicinity of the Feather River the trend of the features abruptly changes to about N. 50-60 deg W and appears to be contiguous across the Sacramento Valley with a similar system of linear features in the Coast Ranges. The linear features in the Modoc Plateau and Klamath Mt. areas appear unrelated to the systems detected in the Coast Ranges of Sierran foothill belt. Although the change in trend of the Sierran structural features has been previously suggested and the interrelationship of the Klamath Mt. region with the northern Sierra Nevadas has been postulated, the data obtained from the ERTS-1 imagery strengthens these notions and provides for the first time evidence of a direct connection of the structural trends within the alluviated part of the Sacramento Valley. In addition rocks of Pleistocene and Holocene age are offset by some of the linear features seen on ERTS-1 imagery and hence may record the latest episode of geologic deformation in north-central California.

EEG Sleep Stages Classification Based on Time Domain Features and Structural Graph Similarity.

PubMed

Diykh, Mohammed; Li, Yan; Wen, Peng

2016-11-01

The electroencephalogram (EEG) signals are commonly used in diagnosing and treating sleep disorders. Many existing methods for sleep stages classification mainly depend on the analysis of EEG signals in time or frequency domain to obtain a high classification accuracy. In this paper, the statistical features in time domain, the structural graph similarity and the K-means (SGSKM) are combined to identify six sleep stages using single channel EEG signals. Firstly, each EEG segment is partitioned into sub-segments. The size of a sub-segment is determined empirically. Secondly, statistical features are extracted, sorted into different sets of features and forwarded to the SGSKM to classify EEG sleep stages. We have also investigated the relationships between sleep stages and the time domain features of the EEG data used in this paper. The experimental results show that the proposed method yields better classification results than other four existing methods and the support vector machine (SVM) classifier. A 95.93% average classification accuracy is achieved by using the proposed method.

Flight State Identification of a Self-Sensing Wing via an Improved Feature Selection Method and Machine Learning Approaches.

PubMed

Chen, Xi; Kopsaftopoulos, Fotis; Wu, Qi; Ren, He; Chang, Fu-Kuo

2018-04-29

In this work, a data-driven approach for identifying the flight state of a self-sensing wing structure with an embedded multi-functional sensing network is proposed. The flight state is characterized by the structural vibration signals recorded from a series of wind tunnel experiments under varying angles of attack and airspeeds. A large feature pool is created by extracting potential features from the signals covering the time domain, the frequency domain as well as the information domain. Special emphasis is given to feature selection in which a novel filter method is developed based on the combination of a modified distance evaluation algorithm and a variance inflation factor. Machine learning algorithms are then employed to establish the mapping relationship from the feature space to the practical state space. Results from two case studies demonstrate the high identification accuracy and the effectiveness of the model complexity reduction via the proposed method, thus providing new perspectives of self-awareness towards the next generation of intelligent air vehicles.

The Rock Elm meteorite impact structure, Wisconsin: Geology and shock-metamorphic effects in quartz

USGS Publications Warehouse

French, B.M.; Cordua, W.S.; Plescia, J.B.

2004-01-01

The Rock Elm structure in southwest Wisconsin is an anomalous circular area of highly deformed rocks, ???6.5 km in diameter, located in a region of virtually horizontal undeformed sedimentary rocks. Shock-produced planar microstructures (PMs) have been identified in quartz grains in several lithologies associated with the structure: sandstones, quartzite pebbles, and breccia. Two distinct types of PMs are present: P1 features, which appear identical to planar fractures (PFs or cleavage), and P2 features, which are interpreted as possible incipient planar deformation features (PDFs). The latter are uniquely produced by the shock waves associated with meteorite impact events. Both types of PMs are oriented parallel to specific crystallographic planes in the quartz, most commonly to c(0001), ??112??2, and r/z101??1. The association of unusual, structurally deformed strata with distinct shock-produced microdeformation features in their quartz-bearing rocks establishes Rock Elm as a meteorite impact structure and supports the view that the presence of multiple parallel cleavages in quartz may be used independently as a criterion for meteorite impact. Preliminary paleontological studies indicate a minimum age of Middle Ordovician for the Rock Elm structure. A similar age estimate (450-400 Ma) is obtained independently by combining the results of studies of the general morphology of complex impact structures with estimated rates of sedimentation for the region. Such methods may be applicable to dating other old and deeply eroded impact structures formed in sedimentary target rocks.

PREvaIL, an integrative approach for inferring catalytic residues using sequence, structural, and network features in a machine-learning framework.

PubMed

Song, Jiangning; Li, Fuyi; Takemoto, Kazuhiro; Haffari, Gholamreza; Akutsu, Tatsuya; Chou, Kuo-Chen; Webb, Geoffrey I

2018-04-14

Determining the catalytic residues in an enzyme is critical to our understanding the relationship between protein sequence, structure, function, and enhancing our ability to design novel enzymes and their inhibitors. Although many enzymes have been sequenced, and their primary and tertiary structures determined, experimental methods for enzyme functional characterization lag behind. Because experimental methods used for identifying catalytic residues are resource- and labor-intensive, computational approaches have considerable value and are highly desirable for their ability to complement experimental studies in identifying catalytic residues and helping to bridge the sequence-structure-function gap. In this study, we describe a new computational method called PREvaIL for predicting enzyme catalytic residues. This method was developed by leveraging a comprehensive set of informative features extracted from multiple levels, including sequence, structure, and residue-contact network, in a random forest machine-learning framework. Extensive benchmarking experiments on eight different datasets based on 10-fold cross-validation and independent tests, as well as side-by-side performance comparisons with seven modern sequence- and structure-based methods, showed that PREvaIL achieved competitive predictive performance, with an area under the receiver operating characteristic curve and area under the precision-recall curve ranging from 0.896 to 0.973 and from 0.294 to 0.523, respectively. We demonstrated that this method was able to capture useful signals arising from different levels, leveraging such differential but useful types of features and allowing us to significantly improve the performance of catalytic residue prediction. We believe that this new method can be utilized as a valuable tool for both understanding the complex sequence-structure-function relationships of proteins and facilitating the characterization of novel enzymes lacking functional annotations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Mapping three-dimensional geological features from remotely-sensed images and digital elevation models

NASA Astrophysics Data System (ADS)

Morris, Kevin Peter

Accurate mapping of geological structures is important in numerous applications, ranging from mineral exploration through to hydrogeological modelling. Remotely sensed data can provide synoptic views of study areas enabling mapping of geological units within the area. Structural information may be derived from such data using standard manual photo-geologic interpretation techniques, although these are often inaccurate and incomplete. The aim of this thesis is, therefore, to compile a suite of automated and interactive computer-based analysis routines, designed to help a the user map geological structure. These are examined and integrated in the context of an expert system. The data used in this study include Digital Elevation Model (DEM) and Airborne Thematic Mapper images, both with a spatial resolution of 5m, for a 5 x 5 km area surrounding Llyn Cow lyd, Snowdonia, North Wales. The geology of this area comprises folded and faulted Ordo vician sediments intruded throughout by dolerite sills, providing a stringent test for the automated and semi-automated procedures. The DEM is used to highlight geomorphological features which may represent surface expressions of the sub-surface geology. The DEM is created from digitized contours, for which kriging is found to provide the best interpolation routine, based on a number of quantitative measures. Lambertian shading and the creation of slope and change of slope datasets are shown to provide the most successful enhancement of DEMs, in terms of highlighting a range of key geomorphological features. The digital image data are used to identify rock outcrops as well as lithologically controlled features in the land cover. To this end, a series of standard spectral enhancements of the images is examined. In this respect, the least correlated 3 band composite and a principal component composite are shown to give the best visual discrimination of geological and vegetation cover types. Automatic edge detection (followed by line thinning and extraction) and manual interpretation techniques are used to identify a set of 'geological primitives' (linear or arc features representing lithological boundaries) within these data. Inclusion of the DEM data provides the three-dimensional co-ordinates of these primitives enabling a least-squares fit to be employed to calculate dip and strike values, based, initially, on the assumption of a simple, linearly dipping structural model. A very large number of scene 'primitives' is identified using these procedures, only some of which have geological significance. Knowledge-based rules are therefore used to identify the relevant. For example, rules are developed to identify lake edges, forest boundaries, forest tracks, rock-vegetation boundaries, and areas of geomorphological interest. Confidence in the geological significance of some of the geological primitives is increased where they are found independently in both the DEM and remotely sensed data. The dip and strike values derived in this way are compared to information taken from the published geological map for this area, as well as measurements taken in the field. Many results are shown to correspond closely to those taken from the map and in the field, with an error of < 1°. These data and rules are incorporated into an expert system which, initially, produces a simple model of the geological structure. The system also provides a graphical user interface for manual control and interpretation, where necessary. Although the system currently only allows a relatively simple structural model (linearly dipping with faulting), in the future it will be possible to extend the system to model more complex features, such as anticlines, synclines, thrusts, nappes, and igneous intrusions.

Landscape determinants of fine-scale genetic structure of a small rodent in a heterogeneous landscape (Hluhluwe-iMfolozi Park, South Africa)

PubMed Central

Russo, Isa-Rita M.; Sole, Catherine L.; Barbato, Mario; von Bramann, Ullrich; Bruford, Michael W.

2016-01-01

Small mammals provide ecosystem services, acting, for example, as pollinators and seed dispersers. In addition, they are also disease reservoirs that can be detrimental to human health and they can also act as crop pests. Knowledge of their dispersal preferences is therefore useful for population management and landscape planning. Genetic data were used alongside landscape data to examine the influence of the landscape on the demographic connectedness of the Natal multimammate mouse (Mastomys natalensis) and to identify landscape characteristics that influence the genetic structure of this species across a spatially and temporally varying environment. The most significant landscape features shaping gene flow were aspect, vegetation cover, topographic complexity (TC) and rivers, with western facing slopes, topographic complexity and rivers restricting gene flow. In general, thicket vegetation was correlated with increased gene flow. Identifying features of the landscape that facilitate movement/dispersal in M. natalensis potentially has application for other small mammals in similar ecosystems. As the primary reservoir host of the zoonotic Lassa virus, a landscape genetics approach may have applications in determining areas of high disease risk to humans. Identifying these landscape features may also be important in crop management due to damage by rodent pests. PMID:27406468

Landscape determinants of fine-scale genetic structure of a small rodent in a heterogeneous landscape (Hluhluwe-iMfolozi Park, South Africa).

PubMed

Russo, Isa-Rita M; Sole, Catherine L; Barbato, Mario; von Bramann, Ullrich; Bruford, Michael W

2016-07-13

Small mammals provide ecosystem services, acting, for example, as pollinators and seed dispersers. In addition, they are also disease reservoirs that can be detrimental to human health and they can also act as crop pests. Knowledge of their dispersal preferences is therefore useful for population management and landscape planning. Genetic data were used alongside landscape data to examine the influence of the landscape on the demographic connectedness of the Natal multimammate mouse (Mastomys natalensis) and to identify landscape characteristics that influence the genetic structure of this species across a spatially and temporally varying environment. The most significant landscape features shaping gene flow were aspect, vegetation cover, topographic complexity (TC) and rivers, with western facing slopes, topographic complexity and rivers restricting gene flow. In general, thicket vegetation was correlated with increased gene flow. Identifying features of the landscape that facilitate movement/dispersal in M. natalensis potentially has application for other small mammals in similar ecosystems. As the primary reservoir host of the zoonotic Lassa virus, a landscape genetics approach may have applications in determining areas of high disease risk to humans. Identifying these landscape features may also be important in crop management due to damage by rodent pests.

Interprofessional teamwork and team interventions in chronic care: A systematic review.

PubMed

Körner, Mirjam; Bütof, Sarah; Müller, Christian; Zimmermann, Linda; Becker, Sonja; Bengel, Jürgen

2016-01-01

To identify key features of teamwork and interventions for enhancing interprofessional teamwork (IPT) in chronic care and to develop a framework for further research, we conducted a systematic literature review of IPT in chronic care for the years 2002-2014. Database searches yielded 3217 abstracts, 21 of which fulfilled inclusion criteria. We identified two more studies on the topic by scanning the reference lists of included articles, which resulted in a final total of 23 included studies. The key features identified in the articles (e.g., team member characteristics, common task, communication, cooperation, coordination, responsibility, participation, staff satisfaction, patient satisfaction, and efficiency) were structured in line with the input-process-output model, and evaluated interventions, such as tools, workshops, and changes in team structure, were added to the model. The most frequently evaluated team interventions were complex intervention programs. All but one of the 14 evaluation studies resulted in enhancement of teamwork and/or staff-related, patient-related, and organization-related outcome criteria. To date, there is no consensus about the main features of IPT and the most effective team interventions in chronic care. However, the findings may be used to standardize the implementation and evaluation of IPT and team interventions in practice and for further research.

Three Types of Flower Structures in a Divergent-Wrench Fault Zone

NASA Astrophysics Data System (ADS)

Huang, Lei; Liu, Chi-yang

2017-12-01

Flower structures are typical features of wrench fault zones. In conventional studies, two distinct kinds of flower structures have been identified based on differences in their internal structural architecture: (1) negative flower structures characterized by synforms and normal separations and (2) positive flower structures characterized by antiforms and reverse separations. In addition to negative and positive flower structures, in this study, a third kind of flower structure was identified in a divergent-wrench fault zone, a hybrid characterized by both antiforms and normal separations. Negative flower structures widely occur in divergent-wrench fault zones, and their presence indicates the combined effects of extensional and strike-slip motion. In contrast, positive and hybrid flower structures occur only in fault restraining bends and step overs. A hybrid flower structure can be considered as product of a kind of structural deformation typical of divergent-wrench zones; it is the result of the combined effects of extensional, compressional, and strike-slip strains under a locally appropriate compressional environment. The strain situation in it represents the transition stage that in between positive and negative flower structures. Kinematic and dynamic characteristics of the hybrid flower structures indicate the salient features of structural deformation in restraining bends and step overs along divergent-wrench faults, including the coexistence of three kinds of strains (i.e., compression, extension, and strike-slip) and synchronous presence of compressional (i.e., typical fault-bend fold) and extensional (normal faults) deformation in the same place. Hybrid flower structures are also favorable for the accumulation of hydrocarbons because of their special structural configuration in divergent-wrench fault zones.

Effect of Levee and Channel Structures on Long Lava Flow Emplacement: Martian Examples from THEMIS and MOLA Data

NASA Technical Reports Server (NTRS)

Peitersen, M. N.; Zimbelman, J. R.; Christensen, P. R.; Bare, C.

2003-01-01

Long lava flows (discrete flow units with lengths exceeding 50 km) are easily identified features found on many planetary surfaces. An ongoing investigation is being conducted into the origin of these flows. Here, we limit our attention to long lava flows which show evidence of channel-like structures.

24 CFR 1000.162 - How will a recipient know that non-dwelling structures assisted under the IHBG program meet the...

Code of Federal Regulations, 2010 CFR

2010-04-01

..., design, features, amenities, performance or other factors. The standards for such structures must be able to support the reasonableness and necessity for these factors and to clearly identify the affordable... change; (vi) Cultural relevance of design; (vii) Size and scope supported by population and need; (viii...

Visualizing spatial correlation: structural and electronic orders in iron-based superconductors on atomic scale

NASA Astrophysics Data System (ADS)

Maksov, Artem; Ziatdinov, Maxim; Li, Li; Sefat, Athena; Maksymovych, Petro; Kalinin, Sergei

Crystalline matter on the nanoscale level often exhibits strongly inhomogeneous structural and electronic orders, which have a profound effect on macroscopic properties. This may be caused by subtle interplay between chemical disorder, strain, magnetic, and structural order parameters. We present a novel approach based on combination of high resolution scanning tunneling microscopy/spectroscopy (STM/S) and deep data style analysis for automatic separation, extraction, and correlation of structural and electronic behavior which might lead us to uncovering the underlying sources of inhomogeneity in in iron-based family of superconductors (FeSe, BaFe2As2) . We identify STS spectral features using physically robust Bayesian linear unmixing, and show their direct relevance to the fundamental physical properties of the system, including electronic states associated with individual defects and impurities. We collect structural data from individual unit cells on the crystalline lattice, and calculate both global and local indicators of spatial correlation with electronic features, demonstrating, for the first time, a direct quantifiable connection between observed structural order parameters extracted from the STM data and electronic order parameters identified within the STS data. This research was sponsored by the Division of Materials Sciences and Engineering, Office of Science, Basic Energy Sciences, US DOE.

GATOR: Requirements capturing of telephony features

NASA Technical Reports Server (NTRS)

Dankel, Douglas D., II; Walker, Wayne; Schmalz, Mark

1992-01-01

We are developing a natural language-based, requirements gathering system called GATOR (for the GATherer Of Requirements). GATOR assists in the development of more accurate and complete specifications of new telephony features. GATOR interacts with a feature designer who describes a new feature, set of features, or capability to be implemented. The system aids this individual in the specification process by asking for clarifications when potential ambiguities are present, by identifying potential conflicts with other existing features, and by presenting its understanding of the feature to the designer. Through user interaction with a model of the existing telephony feature set, GATOR constructs a formal representation of the new, 'to be implemented' feature. Ultimately GATOR will produce a requirements document and will maintain an internal representation of this feature to aid in future design and specification. This paper consists of three sections that describe (1) the structure of GATOR, (2) POND, GATOR's internal knowledge representation language, and (3) current research issues.

Structural damage identification using damping: a compendium of uses and features

NASA Astrophysics Data System (ADS)

Cao, M. S.; Sha, G. G.; Gao, Y. F.; Ostachowicz, W.

2017-04-01

The vibration responses of structures under controlled or ambient excitation can be used to detect structural damage by correlating changes in structural dynamic properties extracted from responses with damage. Typical dynamic properties refer to modal parameters: natural frequencies, mode shapes, and damping. Among these parameters, natural frequencies and mode shapes have been investigated extensively for their use in damage characterization by associating damage with reduction in local stiffness of structures. In contrast, the use of damping as a dynamic property to represent structural damage has not been comprehensively elucidated, primarily due to the complexities of damping measurement and analysis. With advances in measurement technologies and analysis tools, the use of damping to identify damage is becoming a focus of increasing attention in the damage detection community. Recently, a number of studies have demonstrated that damping has greater sensitivity for characterizing damage than natural frequencies and mode shapes in various applications, but damping-based damage identification is still a research direction ‘in progress’ and is not yet well resolved. This situation calls for an overall survey of the state-of-the-art and the state-of-the-practice of using damping to detect structural damage. To this end, this study aims to provide a comprehensive survey of uses and features of applying damping in structural damage detection. First, we present various methods for damping estimation in different domains including the time domain, the frequency domain, and the time-frequency domain. Second, we investigate the features and applications of damping-based damage detection methods on the basis of two predominant infrastructure elements, reinforced concrete structures and fiber-reinforced composites. Third, we clarify the influential factors that can impair the capability of damping to characterize damage. Finally, we recommend future research directions for advancing damping-based damage detection. This work holds the promise of (a) helping researchers identify crucial components in damping-based damage detection theories, methods, and technologies, and (b) leading practitioners to better implement damping-based structural damage identification.

Regular Topographic Patterning of Karst Depressions Suggests Landscape Self-Organization

NASA Astrophysics Data System (ADS)

Quintero, C.; Cohen, M. J.

2017-12-01

Thousands of wetland depressions that are commonly host to cypress domes dot the sub-tropical limestone landscape of South Florida. The origin of these depression features has been the topic of debate. Here we build upon the work of previous surveyors of this landscape to analyze the morphology and spatial distribution of depressions on the Big Cypress landscape. We took advantage of the emergence and availability of high resolution Light Direction and Ranging (LiDAR) technology and ArcMap GIS software to analyze the structure and regularity of landscape features with methods unavailable to past surveyors. Six 2.25 km2 LiDAR plots within the preserve were selected for remote analysis and one depression feature within each plot was selected for more intensive sediment and water depth surveying. Depression features on the Big Cypress landscape were found to show strong evidence of regular spatial patterning. Periodicity, a feature of regularly patterned landscapes, is apparent in both Variograms and Radial Spectrum Analyses. Size class distributions of the identified features indicate constrained feature sizes while Average Nearest Neighbor analyses support the inference of dispersed features with non-random spacing. The presence of regular patterning on this landscape strongly implies biotic reinforcement of spatial structure by way of the scale dependent feedback. In characterizing the structure of this wetland landscape we add to the growing body of work dedicated to documenting how water, life and geology may interact to shape the natural landscapes we see today.

In Situ Identification of Nanoparticle Structural Information Using Optical Microscopy.

PubMed

Culver, Kayla S B; Liu, Tingting; Hryn, Alexander J; Fang, Ning; Odom, Teri W

2018-05-11

Diffraction-limited optical microscopy lacks the resolution to characterize directly nanoscale features of single nanoparticles. This paper describes how surprisingly rich structural features of small gold nanostars can be identified using differential interference contrast (DIC) microscopy. First, we established a library of structure-property relationships between nanoparticle shape and DIC optical image and then validated the correlation with electrodynamic simulations and electron microscopy. We found that DIC image patterns of single nanostars could be differentiated between 2D and 3D geometries. Also, DIC images could elucidate the symmetry properties and orientation of nanoparticles. Finally, we demonstrated how this wide-field optical technique can be used for in situ characterization of single nanoparticles rotating at a glass-water interface.

Identification Of Minangkabau Landscape Characters

NASA Astrophysics Data System (ADS)

Asrina, M.; Gunawan, A.; Aris, Munandar

2017-10-01

Minangkabau is one of cultures in indonesia which occupies landscape intact. Landscape of Minangkabau have a very close relationship with the culture of the people. Uniqueness of Minangkabau culture and landscape forming an inseparable characterunity. The landscape is necessarily identified to know the inherent landscape characters. The objective of this study was to identify the character of the Minangkabau landscape characterizes its uniqueness. The study was conducted by using descriptive method comprised literature review and field observasion. Observed the landscape characters comprised two main features, they were major and minor features. Indetification of the features was conducted in two original areas (darek) of the Minangkabau traditional society. The research results showed that major features or natural features of the landscape were predominantly landform, landcover, and hidrology. All luhak (districts) of Minangkabau showed similar main features such as hill, canyon, lake, valley, and forest. The existence of natural features such as hills, canyon and valleys characterizes the nature of minangkabau landscape. Minor features formed by Minangkabau cultural society were agricultural land and settlement. Rumah gadang (big house) is one of famous minor features characterizes the Minangkabau culture. In addition, several historical artefacts of building and others structure may strengthen uniqueness of the Minangkabau landscape character, such as The royal palace, inscription, and tunnels.

Optical coherence tomography angiography of normal skin and inflammatory dermatologic conditions.

PubMed

Deegan, Anthony J; Talebi-Liasi, Faezeh; Song, Shaozhen; Li, Yuandong; Xu, Jingjiang; Men, Shaojie; Shinohara, Michi M; Flowers, Mary E; Lee, Stephanie J; Wang, Ruikang K

2018-03-01

In clinical dermatology, the identification of subsurface vascular and structural features known to be associated with numerous cutaneous pathologies remains challenging without the use of invasive diagnostic tools. To present an advanced optical coherence tomography angiography (OCTA) method to directly visualize capillary-level vascular and structural features within skin in vivo. An advanced OCTA system with a 1310 nm wavelength was used to image the microvascular and structural features of various skin conditions. Subjects were enrolled and OCTA imaging was performed with a field of view of approximately 10 × 10 mm. Skin blood flow was identified using an optical microangiography (OMAG) algorithm. Depth-resolved microvascular networks and structural features were derived from segmented volume scans, representing tissue slabs of 0-132, 132-330, and 330-924 μm, measured from the surface of the skin. Subjects with both healthy and pathological conditions, such as benign skin lesions, psoriasis, chronic graft-versus-host-disease (cGvHD), and scleroderma, were OCTA scanned. Our OCTA results detailed variations in vascularization and local anatomical characteristics, for example, depth-dependent vascular, and structural alterations in psoriatic skin, alongside their resolve over time; vascular density changes and distribution irregularities, together with corresponding structural depositions in the skin of cGvHD patients; and vascular abnormalities in the nail folds of a patient with scleroderma. OCTA can image capillary blood flow and structural features within skin in vivo, which has the potential to provide new insights into the pathophysiology, as well as dynamic changes of skin diseases, valuable for diagnoses, and non-invasive monitoring of disease progression and treatment. Lasers Surg. Med. 50:183-193, 2018. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Profiling of the Tox21 Chemical Collection for Mitochondrial Function to Identify Compounds that Acutely Decrease Mitochondrial Membrane Potential

PubMed Central

Attene-Ramos, Matias S.; Huang, Ruili; Michael, Sam; Witt, Kristine L.; Richard, Ann; Tice, Raymond R.; Simeonov, Anton; Austin, Christopher P.

2014-01-01

Background: Mitochondrial dysfunction has been implicated in the pathogenesis of a variety of disorders including cancer, diabetes, and neurodegenerative and cardiovascular diseases. Understanding whether different environmental chemicals and druglike molecules impact mitochondrial function represents an initial step in predicting exposure-related toxicity and defining a possible role for such compounds in the onset of various diseases. Objectives: We sought to identify individual chemicals and general structural features associated with changes in mitochondrial membrane potential (MMP). Methods: We used a multiplexed [two end points in one screen; MMP and adenosine triphosphate (ATP) content] quantitative high throughput screening (qHTS) approach combined with informatics tools to screen the Tox21 library of 10,000 compounds (~ 8,300 unique chemicals) at 15 concentrations each in triplicate to identify chemicals and structural features that are associated with changes in MMP in HepG2 cells. Results: Approximately 11% of the compounds (913 unique compounds) decreased MMP after 1 hr of treatment without affecting cell viability (ATP content). In addition, 309 compounds decreased MMP over a concentration range that also produced measurable cytotoxicity [half maximal inhibitory concentration (IC50) in MMP assay/IC50 in viability assay ≤ 3; p < 0.05]. More than 11% of the structural clusters that constitute the Tox21 library (76 of 651 clusters) were significantly enriched for compounds that decreased the MMP. Conclusions: Our multiplexed qHTS approach allowed us to generate a robust and reliable data set to evaluate the ability of thousands of drugs and environmental compounds to decrease MMP. The use of structure-based clustering analysis allowed us to identify molecular features that are likely responsible for the observed activity. Citation: Attene-Ramos MS, Huang R, Michael S, Witt KL, Richard A, Tice RR, Simeonov A, Austin CP, Xia M. 2015. Profiling of the Tox21 chemical collection for mitochondrial function to identify compounds that acutely decrease mitochondrial membrane potential. Environ Health Perspect 123:49–56; http://dx.doi.org/10.1289/ehp.1408642 PMID:25302578

The sequence, structure and evolutionary features of HOTAIR in mammals

PubMed Central

2011-01-01

Background An increasing number of long noncoding RNAs (lncRNAs) have been identified recently. Different from all the others that function in cis to regulate local gene expression, the newly identified HOTAIR is located between HoxC11 and HoxC12 in the human genome and regulates HoxD expression in multiple tissues. Like the well-characterised lncRNA Xist, HOTAIR binds to polycomb proteins to methylate histones at multiple HoxD loci, but unlike Xist, many details of its structure and function, as well as the trans regulation, remain unclear. Moreover, HOTAIR is involved in the aberrant regulation of gene expression in cancer. Results To identify conserved domains in HOTAIR and study the phylogenetic distribution of this lncRNA, we searched the genomes of 10 mammalian and 3 non-mammalian vertebrates for matches to its 6 exons and the two conserved domains within the 1800 bp exon6 using Infernal. There was just one high-scoring hit for each mammal, but many low-scoring hits were found in both mammals and non-mammalian vertebrates. These hits and their flanking genes in four placental mammals and platypus were examined to determine whether HOTAIR contained elements shared by other lncRNAs. Several of the hits were within unknown transcripts or ncRNAs, many were within introns of, or antisense to, protein-coding genes, and conservation of the flanking genes was observed only between human and chimpanzee. Phylogenetic analysis revealed discrete evolutionary dynamics for orthologous sequences of HOTAIR exons. Exon1 at the 5' end and a domain in exon6 near the 3' end, which contain domains that bind to multiple proteins, have evolved faster in primates than in other mammals. Structures were predicted for exon1, two domains of exon6 and the full HOTAIR sequence. The sequence and structure of two fragments, in exon1 and the domain B of exon6 respectively, were identified to robustly occur in predicted structures of exon1, domain B of exon6 and the full HOTAIR in mammals. Conclusions HOTAIR exists in mammals, has poorly conserved sequences and considerably conserved structures, and has evolved faster than nearby HoxC genes. Exons of HOTAIR show distinct evolutionary features, and a 239 bp domain in the 1804 bp exon6 is especially conserved. These features, together with the absence of some exons and sequences in mouse, rat and kangaroo, suggest ab initio generation of HOTAIR in marsupials. Structure prediction identifies two fragments in the 5' end exon1 and the 3' end domain B of exon6, with sequence and structure invariably occurring in various predicted structures of exon1, the domain B of exon6 and the full HOTAIR. PMID:21496275

A deep learning framework for modeling structural features of RNA-binding protein targets

PubMed Central

Zhang, Sai; Zhou, Jingtian; Hu, Hailin; Gong, Haipeng; Chen, Ligong; Cheng, Chao; Zeng, Jianyang

2016-01-01

RNA-binding proteins (RBPs) play important roles in the post-transcriptional control of RNAs. Identifying RBP binding sites and characterizing RBP binding preferences are key steps toward understanding the basic mechanisms of the post-transcriptional gene regulation. Though numerous computational methods have been developed for modeling RBP binding preferences, discovering a complete structural representation of the RBP targets by integrating their available structural features in all three dimensions is still a challenging task. In this paper, we develop a general and flexible deep learning framework for modeling structural binding preferences and predicting binding sites of RBPs, which takes (predicted) RNA tertiary structural information into account for the first time. Our framework constructs a unified representation that characterizes the structural specificities of RBP targets in all three dimensions, which can be further used to predict novel candidate binding sites and discover potential binding motifs. Through testing on the real CLIP-seq datasets, we have demonstrated that our deep learning framework can automatically extract effective hidden structural features from the encoded raw sequence and structural profiles, and predict accurate RBP binding sites. In addition, we have conducted the first study to show that integrating the additional RNA tertiary structural features can improve the model performance in predicting RBP binding sites, especially for the polypyrimidine tract-binding protein (PTB), which also provides a new evidence to support the view that RBPs may own specific tertiary structural binding preferences. In particular, the tests on the internal ribosome entry site (IRES) segments yield satisfiable results with experimental support from the literature and further demonstrate the necessity of incorporating RNA tertiary structural information into the prediction model. The source code of our approach can be found in https://github.com/thucombio/deepnet-rbp. PMID:26467480

A Feature-based Developmental Model of the Infant Brain in Structural MRI

PubMed Central

Toews, Matthew; Wells, William M.; Zöllei, Lilla

2014-01-01

In this paper, anatomical development is modeled as a collection of distinctive image patterns localized in space and time. A Bayesian posterior probability is defined over a random variable of subject age, conditioned on data in the form of scale-invariant image features. The model is automatically learned from a large set of images exhibiting significant variation, used to discover anatomical structure related to age and development, and fit to new images to predict age. The model is applied to a set of 230 infant structural MRIs of 92 subjects acquired at multiple sites over an age range of 8-590 days. Experiments demonstrate that the model can be used to identify age-related anatomical structure, and to predict the age of new subjects with an average error of 72 days. PMID:23286050

Elements of the Chicxulub Impact Structure as revealed in SRTM and surface GPS topographic data

NASA Astrophysics Data System (ADS)

Kobrick, M.; Kinsland, G. L.; Sanchez, G.; Cardador, M. H.

2003-04-01

Pope et al have utilized elevations from the Petroleos Mexicanos (PEMEX) gravity data files to show that the main component of the surface expression of the Chicxu-lub Impact Structure is a roughly semi-circular, low-relief depression about 90 km in diameter. They also identified other topographic features and the elements of the buried impact which possibly led to the development of these features. Kinsland et al presented a connection between these topographic anomalies, small gravity anomalies and buried structure of the impact. Shaded relief images from recently acquired SRTM elevation data clearly show the circular depression of the crater and the moat/cenote ring. In addition we can readily identify Inner trough 1, Inner trough 2 and Outer trough as defined by Pope et al. The agreement between the topographic maps of Pope et al, Kinsland et al and SRTM data are remarkable considering that the distribution and types of data in the sets are so different. We also have ground topographic data collected with a special "autonomous differ-ential GPS" system during summer 2002. Profiles from these data generally agree with both the gravity data based topographic maps and profiles extracted from the SRTM data. Preliminary analyses of our new data, SRTM and GPS, have uncovered features not previously recognized: 1) as shown by the GPS data the moat/cenote ring consists of two distinct depressions separated by about 10 km...perhaps separate ring faults, 2) in the SRTM data over the southern part of the crater and on southward for perhaps 20 km beyond the moat/ cenote ring there exists a pattern, as yet unexplained, of roughly concentric topographic features whose center lies at about 21deg 40min N and 89deg 25min W, about 50km NNE of the moat/cenote ring center. The corroboration and better definition of the previously recognized topographic features yielded by the two new forms of data strengthens the cases for these fea-tures and for their relevance to the underlying collapsed crater structure.

Earth Observations taken by the Expedition 17 Crew

NASA Image and Video Library

2008-10-21

ISS017-E-020538 (21 Oct. 2008) --- Arkenu Craters 1 and 2 in Libya are featured in this image photographed by an Expedition 17 crewmember on the International Space Station. Geologists often study features on Earth, such as impact craters, to gain insight into processes that occur on other planets. On Earth, more than 150 impact craters have been identified on the continents, but only a few of these are classified as double impact craters. One such example, the Arkenu Craters in northern Africa, is shown in this image. Arkenu 1 and 2 are double impact structures located in eastern Libya (22.04 degrees north latitude and 23.45 degrees east longitude) in the Sahara desert, with diameters of approximately 6.8 kilometers and 10.3 kilometers, respectively. The craters are unusual in that they both exhibit concentric annular ridge structures (gray circles in the image indicate the position of the outermost visible ridges). In many terrestrial complex craters these features are highly eroded and no longer visible. While the circular structure of these features had been noted, the impact origin hypothesis was strengthened in December 2003 when a field team observed shatter cones -- conical-shaped features in rocks created by the high shock pressures generated during impact. Large outcrops of impact breccias -- a jumble of rock fragments generated at the impact site that are now cemented together into an identifiable rock layer -- were also observed by the field team. Two impactors, each approximately 500 meters in diameter, are thought to have created the craters. According to scientists, the age of the impact event has been dated as occurring less than 140 million years ago. While the presence of shatter cones and impact breccias is generally considered to be strong evidence for meteor impact, some scientists now question the interpretation of these features observed at the Arkenu structures and suggest that they were caused by erosive and volcanic processes. At present, both craters are being crossed by linear dunes extending northeast-southwest -- the superposition of the dunes across the annular ridges indicates that they are much younger than the craters.

Composition and structure of fresh ammonia clouds on Jupiter based on quantitative analysis of Galileo/NIMS and New Horizons/LEISA spectra

NASA Astrophysics Data System (ADS)

Sromovsky, L. A.; Fry, P. M.

2018-06-01

Ammonia gas has long been assumed to be the main source of condensables for the upper cloud layer on Jupiter, but distinctive spectral features associated with ammonia have been seen only rarely. Since both ammonia and NH4SH absorb in the 3 μm region, and widespread absorption in the 3 μm region was present (Sromovsky and Fry, 2010), identification of the 2 μm absorption feature of NH3 provided an opportunity to clearly establish its presence in Jovian clouds. Baines et al. (2002) succeeded in finding in Near Infrared Mapping Spectrometer (NIMS) observations one feature that had both 2 μm and 3 μm absorption, and many which were known to have absorption at 2.73 μm. They named these Spectrally Identifiable Ammonia Clouds (SIACs). They also argued that these were fresh ammonia clouds that would eventually succumb to some process that would obscure their absorption features. Detection of many more of the 2 μm features was later achieved by New Horizon's Linear Etalon Imaging Spectral Array (LEISA) instrument, which provided both the spatial and spectral resolution needed to identify these features. Here we report on the first quantitative modeling that uses NIMS spectra over a broad (1-5.2 μm) spectral range and LEISA spectra over a much narrower (1.25-2.5 μm) spectral range to constrain the cloud structure and composition of these rare cloud features and compare them to background clouds. We find that the absorption signature at 2 μm, which is well characterized in LEISA spectra, is relatively subtle and easily matched by model clouds containing spherical particles of ammonia ice with radii of 2-4 μm. The NIMS spectra, which cover both reflected sunlight as well as thermal emission regions are more difficult to model with cloud materials plausibly present in Jupiter's atmosphere. The best signal/noise spectra obtained from NIMS provide a relatively sparse sampling of the spectrum, which does not establish the detailed shape of the 3 μm absorption region. NIMS SIAC spectra with much denser spectral sampling are limited by much higher noise levels that degrade the features that are key to identifying cloud composition. The structure which best matches the wide range NIMS SIAC spectra contains two overlapping NH3 clouds with a bi-modal size distribution over an optically thick NH4SH cloud. The bi-modal distribution may be a result of modeling non-spherical, possibly fractal aggregate, particles with spheres.

Detection and analysis of morphotectonic features utilizing satellite remote sensing and GIS: An example in SW Jordan

NASA Astrophysics Data System (ADS)

Radaideh, Omar M. A.; Grasemann, Bernhard; Melichar, Rostislav; Mosar, Jon

2016-12-01

This study investigates the dominant orientations of morphological features and the relationship between these trends and the spatial orientation of tectonic structures in SW Jordan. Landsat 8 and hill-shaded images, constructed from 30 m-resolution ASTER-GDEM data, were used for automatically extracting and mapping geological lineaments. The ASTER-GDEM was further utilized to automatically identify and extract drainage network. Morphological features were analyzed by means of azimuth frequency and length density distributions. Tectonic controls on the land surface were evaluated using longitudinal profiles of many westerly flowing streams. The profiles were taken directly across the northerly trending faults within a strong topographic transition between the low-gradient uplands and the deeply incised mountain front on the east side of the Dead Sea Fault Zone. Streams of the area are widely divergent, and show numerous anomalies along their profiles when they transect faults and lineaments. Five types of drainage patterns were identified: dendritic, parallel, rectangular, trellis, and modified dendritic/trellis. Interpretation and analysis of the lineaments indicate the presence of four main lineament populations that trend E-W, N-S, NE-SW, and NW-SE. Azimuthal distribution analysis of both the measured structures and drainage channels shows similar trends, except for very few differences in the prevailing directions. The similarity in orientation of lineaments, drainage system, and subsurface structural trends highlights the degree of control exerted by underlying structure on the surface geomorphological features. Faults and lineaments serve as a preferential conduit for surface running waters. The extracted lineaments were divided into five populations based on the main age of host rocks outcropping in the study area to obtain information about the temporal evolution of the lineament trends through geologic time. A general consistency in lineament trends over the different lithological units was observed, most probably because repeated reactivation of tectonism along preexisting deep structural discontinuities which are apparently crustal weakness zones. The reactivation along such inherited discontinuities under the present-day stress field is the most probable explanation of the complicated pattern and style of present-day landscape features in SW Jordan.

Environmental and Water Quality Operational Studies. Environmental Features for Streambank Protection Projects.

DTIC Science & Technology

1984-11-01

Port Royal Road, Springfield, Virginia 22161. 19. KEY WORDS (Conltinue an, reverse olde It necessemy and Identify by block imbr) Bank protection (WES...20. AmT-RAcT (cothwe areyee &M ffneeeeiny ge Identify by block nmmber) This report provides guidance for incorporating environmental consid- erations...Environmental Effects ....................... 16 * PART IV: STRUCTURAL DESIGNS ..................... 24 4 Composite Revetment ........................ 249

Secondary structural entropy in RNA switch (Riboswitch) identification.

PubMed

Manzourolajdad, Amirhossein; Arnold, Jonathan

2015-04-28

RNA regulatory elements play a significant role in gene regulation. Riboswitches, a widespread group of regulatory RNAs, are vital components of many bacterial genomes. These regulatory elements generally function by forming a ligand-induced alternative fold that controls access to ribosome binding sites or other regulatory sites in RNA. Riboswitch-mediated mechanisms are ubiquitous across bacterial genomes. A typical class of riboswitch has its own unique structural and biological complexity, making de novo riboswitch identification a formidable task. Traditionally, riboswitches have been identified through comparative genomics based on sequence and structural homology. The limitations of structural-homology-based approaches, coupled with the assumption that there is a great diversity of undiscovered riboswitches, suggests the need for alternative methods for riboswitch identification, possibly based on features intrinsic to their structure. As of yet, no such reliable method has been proposed. We used structural entropy of riboswitch sequences as a measure of their secondary structural dynamics. Entropy values of a diverse set of riboswitches were compared to that of their mutants, their dinucleotide shuffles, and their reverse complement sequences under different stochastic context-free grammar folding models. Significance of our results was evaluated by comparison to other approaches, such as the base-pairing entropy and energy landscapes dynamics. Classifiers based on structural entropy optimized via sequence and structural features were devised as riboswitch identifiers and tested on Bacillus subtilis, Escherichia coli, and Synechococcus elongatus as an exploration of structural entropy based approaches. The unusually long untranslated region of the cotH in Bacillus subtilis, as well as upstream regions of certain genes, such as the sucC genes were associated with significant structural entropy values in genome-wide examinations. Various tests show that there is in fact a relationship between higher structural entropy and the potential for the RNA sequence to have alternative structures, within the limitations of our methodology. This relationship, though modest, is consistent across various tests. Understanding the behavior of structural entropy as a fairly new feature for RNA conformational dynamics, however, may require extensive exploratory investigation both across RNA sequences and folding models.

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

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

Dib, G.; Udpa, L.

2016-01-01

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

Using satellite imagery to identify and analyze tumuli on Earth and Mars

NASA Astrophysics Data System (ADS)

Diniega, Serina; Sangha, Simran; Browne, Brandon

2018-01-01

Tumuli are small, dome-like features that form when magmatic pressures build within a subsurface lava pathway, causing the overlying crust to bulge upwards. As the appearance of these features has been linked to lava flow structure (e.g., underlying lava flow tubes) and conditions, there is interest in identifying such features in satellite images so they can be used to expand our understanding of lava flows within regions difficult to access (such as on other planets). Here, we define a methodology for identifying (and measuring) tumuli within satellite imagery, and validate it by comparing our results with fieldwork results of terrestrial tumuli reported in the literature and with independent measurements we made within Amboy Field, CA. In addition, we present aggregated results from the application of our methodology to satellite images of six terrestrial fields and seven martian fields (with >2100 tumuli identified, per planet). Comparisons of tumuli morphometrics on Earth and Mars yield similarities in size and overall shape, which were surprising given the many differences in the environmental and planetary conditions within which these features have formed. Given our measurements, we identify constraints for tumulus formation models and drivers that would yield similar shapes and sizes on two different planets. Furthermore, we test a published hypothesis regarding the number of tumuli that form per a square kilometer, and find it unlikely that a diagnostic "tumuli density" value exists.

A Close Look At The Relationship Between WMAP (ILC) Small-Scale Features And Galactic HI Structure

NASA Astrophysics Data System (ADS)

Verschuur, Gerrit L.

2012-05-01

Galactic HI emission profiles surrounding two pairs of features located where large-scale filaments at very different velocities overlap were decomposed into Gaussian components. Families of components defined by similarity of center velocities and line widths were identified and found to be spatially related. Each of the two pairs of HI peaks straddle a high-frequency continuum source revealed in the WMAP survey data. It is suggested that where filamentary HI features are directly interacting high-frequency continuum radiation is being produced. The previously hypothesized mechanism for producing high-frequency continuum radiation involving free-free emission from electrons in the interstellar medium, in this case created where HI filaments interact to produce fractional ionizations of order 5 to 15%, fit the data very closely. The results confirm that WMAP data on small-scale structures believed to be cosmological in origin are in fact compromised by the presence of intervening galactic sources of interstellar electrons clumped on scales typical of interstellar HI structure.

Method and system for the diagnosis of disease using retinal image content and an archive of diagnosed human patient data

DOEpatents

Tobin, Kenneth W; Karnowski, Thomas P; Chaum, Edward

2013-08-06

A method for diagnosing diseases having retinal manifestations including retinal pathologies includes the steps of providing a CBIR system including an archive of stored digital retinal photography images and diagnosed patient data corresponding to the retinal photography images, the stored images each indexed in a CBIR database using a plurality of feature vectors, the feature vectors corresponding to distinct descriptive characteristics of the stored images. A query image of the retina of a patient is obtained. Using image processing, regions or structures in the query image are identified. The regions or structures are then described using the plurality of feature vectors. At least one relevant stored image from the archive based on similarity to the regions or structures is retrieved, and an eye disease or a disease having retinal manifestations in the patient is diagnosed based on the diagnosed patient data associated with the relevant stored image(s).

Features of Coping with Disease in Iranian Multiple Sclerosis Patients: a Qualitative Study.

PubMed

Dehghani, Ali; Dehghan Nayeri, Nahid; Ebadi, Abbas

2018-03-01

Introduction: Coping with disease is of the main components improving the quality of life in multiple sclerosis patients. Identifying the characteristics of this concept is based on the experiences of patients. Using qualitative research is essential to improve the quality of life. This study was conducted to explore the features of coping with the disease in patients with multiple sclerosis. Method: In this conventional content analysis study, eleven multiple sclerosis patients from Iran MS Society in Tehran (Iran) participated. Purposive sampling was used to select participants. Data were gathered using semi structured interviews. To analyze data, a conventional content analysis approach was used to identify meaning units and to make codes and categories. Results: Results showed that features of coping with disease in multiple sclerosis patients consists of (a) accepting the current situation, (b) maintenance and development of human interactions, (c) self-regulation and (d) self-efficacy. Each of these categories is composed of sub-categories and codes that showed the perception and experience of patients about the coping with disease. Conclusion: Accordingly, a unique set of features regarding features of coping with the disease were identified among the patients with multiple sclerosis. Therefore, working to ensure the emergence of, and subsequent reinforcement of these features in MS patients can be an important step in improving the adjustment and quality of their lives.

Quantifying site-specific physical heterogeneity within an estuarine seascape

USGS Publications Warehouse

Kennedy, Cristina G.; Mather, Martha E.; Smith, Joseph M.

2017-01-01

Quantifying physical heterogeneity is essential for meaningful ecological research and effective resource management. Spatial patterns of multiple, co-occurring physical features are rarely quantified across a seascape because of methodological challenges. Here, we identified approaches that measured total site-specific heterogeneity, an often overlooked aspect of estuarine ecosystems. Specifically, we examined 23 metrics that quantified four types of common physical features: (1) river and creek confluences, (2) bathymetric variation including underwater drop-offs, (3) land features such as islands/sandbars, and (4) major underwater channel networks. Our research at 40 sites throughout Plum Island Estuary (PIE) provided solutions to two problems. The first problem was that individual metrics that measured heterogeneity of a single physical feature showed different regional patterns. We solved this first problem by combining multiple metrics for a single feature using a within-physical feature cluster analysis. With this approach, we identified sites with four different types of confluences and three different types of underwater drop-offs. The second problem was that when multiple physical features co-occurred, new patterns of total site-specific heterogeneity were created across the seascape. This pattern of total heterogeneity has potential ecological relevance to structure-oriented predators. To address this second problem, we identified sites with similar types of total physical heterogeneity using an across-physical feature cluster analysis. Then, we calculated an additive heterogeneity index, which integrated all physical features at a site. Finally, we tested if site-specific additive heterogeneity index values differed for across-physical feature clusters. In PIE, the sites with the highest additive heterogeneity index values were clustered together and corresponded to sites where a fish predator, adult striped bass (Morone saxatilis), aggregated in a related acoustic tracking study. In summary, we have shown general approaches to quantifying site-specific heterogeneity.

Parenchymal texture analysis in digital mammography: robust texture feature identification and equivalence across devices.

PubMed

Keller, Brad M; Oustimov, Andrew; Wang, Yan; Chen, Jinbo; Acciavatti, Raymond J; Zheng, Yuanjie; Ray, Shonket; Gee, James C; Maidment, Andrew D A; Kontos, Despina

2015-04-01

An analytical framework is presented for evaluating the equivalence of parenchymal texture features across different full-field digital mammography (FFDM) systems using a physical breast phantom. Phantom images (FOR PROCESSING) are acquired from three FFDM systems using their automated exposure control setting. A panel of texture features, including gray-level histogram, co-occurrence, run length, and structural descriptors, are extracted. To identify features that are robust across imaging systems, a series of equivalence tests are performed on the feature distributions, in which the extent of their intersystem variation is compared to their intrasystem variation via the Hodges-Lehmann test statistic. Overall, histogram and structural features tend to be most robust across all systems, and certain features, such as edge enhancement, tend to be more robust to intergenerational differences between detectors of a single vendor than to intervendor differences. Texture features extracted from larger regions of interest (i.e., [Formula: see text]) and with a larger offset length (i.e., [Formula: see text]), when applicable, also appear to be more robust across imaging systems. This framework and observations from our experiments may benefit applications utilizing mammographic texture analysis on images acquired in multivendor settings, such as in multicenter studies of computer-aided detection and breast cancer risk assessment.

Accurate prediction of RNA-binding protein residues with two discriminative structural descriptors.

PubMed

Sun, Meijian; Wang, Xia; Zou, Chuanxin; He, Zenghui; Liu, Wei; Li, Honglin

2016-06-07

RNA-binding proteins participate in many important biological processes concerning RNA-mediated gene regulation, and several computational methods have been recently developed to predict the protein-RNA interactions of RNA-binding proteins. Newly developed discriminative descriptors will help to improve the prediction accuracy of these prediction methods and provide further meaningful information for researchers. In this work, we designed two structural features (residue electrostatic surface potential and triplet interface propensity) and according to the statistical and structural analysis of protein-RNA complexes, the two features were powerful for identifying RNA-binding protein residues. Using these two features and other excellent structure- and sequence-based features, a random forest classifier was constructed to predict RNA-binding residues. The area under the receiver operating characteristic curve (AUC) of five-fold cross-validation for our method on training set RBP195 was 0.900, and when applied to the test set RBP68, the prediction accuracy (ACC) was 0.868, and the F-score was 0.631. The good prediction performance of our method revealed that the two newly designed descriptors could be discriminative for inferring protein residues interacting with RNAs. To facilitate the use of our method, a web-server called RNAProSite, which implements the proposed method, was constructed and is freely available at http://lilab.ecust.edu.cn/NABind .

Atmospheric pressure chemical ionization studies of non-polar isomeric hydrocarbons using ion mobility spectrometry and mass spectrometry with different ionization techniques

NASA Technical Reports Server (NTRS)

Borsdorf, H.; Nazarov, E. G.; Eiceman, G. A.

2002-01-01

The ionization pathways were determined for sets of isomeric non-polar hydrocarbons (structural isomers, cis/trans isomers) using ion mobility spectrometry and mass spectrometry with different techniques of atmospheric pressure chemical ionization to assess the influence of structural features on ion formation. Depending on the structural features, different ions were observed using mass spectrometry. Unsaturated hydrocarbons formed mostly [M - 1]+ and [(M - 1)2H]+ ions while mainly [M - 3]+ and [(M - 3)H2O]+ ions were found for saturated cis/trans isomers using photoionization and 63Ni ionization. These ionization methods and corona discharge ionization were used for ion mobility measurements of these compounds. Different ions were detected for compounds with different structural features. 63Ni ionization and photoionization provide comparable ions for every set of isomers. The product ions formed can be clearly attributed to the structures identified. However, differences in relative abundance of product ions were found. Although corona discharge ionization permits the most sensitive detection of non-polar hydrocarbons, the spectra detected are complex and differ from those obtained with 63Ni ionization and photoionization. c. 2002 American Society for Mass Spectrometry.

Unique Structural Features and Sequence Motifs of Proline Utilization A (PutA)

PubMed Central

Singh, Ranjan K.; Tanner, John J.

2013-01-01

Proline utilization A proteins (PutAs) are bifunctional enzymes that catalyze the oxidation of proline to glutamate using spatially separated proline dehydrogenase and pyrroline-5-carboxylate dehydrogenase active sites. Here we use the crystal structure of the minimalist PutA from Bradyrhizobium japonicum (BjPutA) along with sequence analysis to identify unique structural features of PutAs. This analysis shows that PutAs have secondary structural elements and domains not found in the related monofunctional enzymes. Some of these extra features are predicted to be important for substrate channeling in BjPutA. Multiple sequence alignment analysis shows that some PutAs have a 17-residue conserved motif in the C-terminal 20–30 residues of the polypeptide chain. The BjPutA structure shows that this motif helps seal the internal substrate-channeling cavity from the bulk medium. Finally, it is shown that some PutAs have a 100–200 residue domain of unknown function in the C-terminus that is not found in minimalist PutAs. Remote homology detection suggests that this domain is homologous to the oligomerization beta-hairpin and Rossmann fold domain of BjPutA. PMID:22201760

Fragment-based virtual screening approach and molecular dynamics simulation studies for identification of BACE1 inhibitor leads.

PubMed

Manoharan, Prabu; Ghoshal, Nanda

2018-05-01

Traditional structure-based virtual screening method to identify drug-like small molecules for BACE1 is so far unsuccessful. Location of BACE1, poor Blood Brain Barrier permeability and P-glycoprotein (Pgp) susceptibility of the inhibitors make it even more difficult. Fragment-based drug design method is suitable for efficient optimization of initial hit molecules for target like BACE1. We have developed a fragment-based virtual screening approach to identify/optimize the fragment molecules as a starting point. This method combines the shape, electrostatic, and pharmacophoric features of known fragment molecules, bound to protein conjugate crystal structure, and aims to identify both chemically and energetically feasible small fragment ligands that bind to BACE1 active site. The two top-ranked fragment hits were subjected for a 53 ns MD simulation. Principle component analysis and free energy landscape analysis reveal that the new ligands show the characteristic features of established BACE1 inhibitors. The potent method employed in this study may serve for the development of potential lead molecules for BACE1-directed Alzheimer's disease therapeutics.

Local structural effects in Sr 3NiRhO 6 across magnetic transitions

DOE PAGES

Singh, Navneet; Khalid, S.; Bindu, R.

2016-04-06

Here, we investigate the temperature dependence of the structural parameters of quasi-one-dimensional Sr 3NiRhO 6 across the region of magnetic phase transitions using Ni K-edge and Sr K-edge x-ray absorption spectroscopy (XAS). The features in the x-ray absorption near-edge region are identified using multiple scattering calculations. The temperature-dependent extended x-ray absorption fine structure (EXAFS) studies show that the setting of the intra-chain super exchange interaction starts at ~200 K, which is well above the first transition temperature (45 K) revealed by magnetic susceptibility studies. The onset of the inter-chain super–super exchange interaction appears to be at ~125 K. Interestingly, themore » role played by direct exchange interaction between the Ni 3d and Rh 4d states in stabilising the magnetic interaction is less significant. The present results shed light on the generic features exhibited by isostructural compounds and may help in identifying the magnetic exchange pathways useful for understanding the unusual properties exhibited by such compounds.« less

Controllable Edge Feature Sharpening for Dental Applications

PubMed Central

2014-01-01

This paper presents a new approach to sharpen blurred edge features in scanned tooth preparation surfaces generated by structured-light scanners. It aims to efficiently enhance the edge features so that the embedded feature lines can be easily identified in dental CAD systems, and to avoid unnatural oversharpening geometry. We first separate the feature regions using graph-cut segmentation, which does not require a user-defined threshold. Then, we filter the face normal vectors to propagate the geometry from the smooth region to the feature region. In order to control the degree of the sharpness, we propose a feature distance measure which is based on normal tensor voting. Finally, the vertex positions are updated according to the modified face normal vectors. We have applied the approach to scanned tooth preparation models. The results show that the blurred edge features are enhanced without unnatural oversharpening geometry. PMID:24741376

Controllable edge feature sharpening for dental applications.

PubMed

Fan, Ran; Jin, Xiaogang

2014-01-01

This paper presents a new approach to sharpen blurred edge features in scanned tooth preparation surfaces generated by structured-light scanners. It aims to efficiently enhance the edge features so that the embedded feature lines can be easily identified in dental CAD systems, and to avoid unnatural oversharpening geometry. We first separate the feature regions using graph-cut segmentation, which does not require a user-defined threshold. Then, we filter the face normal vectors to propagate the geometry from the smooth region to the feature region. In order to control the degree of the sharpness, we propose a feature distance measure which is based on normal tensor voting. Finally, the vertex positions are updated according to the modified face normal vectors. We have applied the approach to scanned tooth preparation models. The results show that the blurred edge features are enhanced without unnatural oversharpening geometry.

EEG resolutions in detecting and decoding finger movements from spectral analysis

PubMed Central

Xiao, Ran; Ding, Lei

2015-01-01

Mu/beta rhythms are well-studied brain activities that originate from sensorimotor cortices. These rhythms reveal spectral changes in alpha and beta bands induced by movements of different body parts, e.g., hands and limbs, in electroencephalography (EEG) signals. However, less can be revealed in them about movements of different fine body parts that activate adjacent brain regions, such as individual fingers from one hand. Several studies have reported spatial and temporal couplings of rhythmic activities at different frequency bands, suggesting the existence of well-defined spectral structures across multiple frequency bands. In the present study, spectral principal component analysis (PCA) was applied on EEG data, obtained from a finger movement task, to identify cross-frequency spectral structures. Features from identified spectral structures were examined in their spatial patterns, cross-condition pattern changes, detection capability of finger movements from resting, and decoding performance of individual finger movements in comparison to classic mu/beta rhythms. These new features reveal some similar, but more different spatial and spectral patterns as compared with classic mu/beta rhythms. Decoding results further indicate that these new features (91%) can detect finger movements much better than classic mu/beta rhythms (75.6%). More importantly, these new features reveal discriminative information about movements of different fingers (fine body-part movements), which is not available in classic mu/beta rhythms. The capability in decoding fingers (and hand gestures in the future) from EEG will contribute significantly to the development of non-invasive BCI and neuroprosthesis with intuitive and flexible controls. PMID:26388720

Learning from patients: Identifying design features of medicines that cause medication use problems.

PubMed

Notenboom, Kim; Leufkens, Hubert Gm; Vromans, Herman; Bouvy, Marcel L

2017-01-30

Usability is a key factor in ensuring safe and efficacious use of medicines. However, several studies showed that people experience a variety of problems using their medicines. The purpose of this study was to identify design features of oral medicines that cause use problems among older patients in daily practice. A qualitative study with semi-structured interviews on the experiences of older people with the use of their medicines was performed (n=59). Information on practical problems, strategies to overcome these problems and the medicines' design features that caused these problems were collected. The practical problems and management strategies were categorised into 'use difficulties' and 'use errors'. A total of 158 use problems were identified, of which 45 were categorized as use difficulties and 113 as use error. Design features that contributed the most to the occurrence of use difficulties were the dimensions and surface texture of the dosage form (29.6% and 18.5%, respectively). Design features that contributed the most to the occurrence of use errors were the push-through force of blisters (22.1%) and tamper evident packaging (12.1%). These findings will help developers of medicinal products to proactively address potential usability issues with their medicines. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning

NASA Astrophysics Data System (ADS)

Fernandez Galarreta, J.; Kerle, N.; Gerke, M.

2015-06-01

Structural damage assessment is critical after disasters but remains a challenge. Many studies have explored the potential of remote sensing data, but limitations of vertical data persist. Oblique imagery has been identified as more useful, though the multi-angle imagery also adds a new dimension of complexity. This paper addresses damage assessment based on multi-perspective, overlapping, very high resolution oblique images obtained with unmanned aerial vehicles (UAVs). 3-D point-cloud assessment for the entire building is combined with detailed object-based image analysis (OBIA) of façades and roofs. This research focuses not on automatic damage assessment, but on creating a methodology that supports the often ambiguous classification of intermediate damage levels, aiming at producing comprehensive per-building damage scores. We identify completely damaged structures in the 3-D point cloud, and for all other cases provide the OBIA-based damage indicators to be used as auxiliary information by damage analysts. The results demonstrate the usability of the 3-D point-cloud data to identify major damage features. Also the UAV-derived and OBIA-processed oblique images are shown to be a suitable basis for the identification of detailed damage features on façades and roofs. Finally, we also demonstrate the possibility of aggregating the multi-perspective damage information at building level.

Electron and ion distribution functions in magnetopause reconnection

NASA Astrophysics Data System (ADS)

Wang, S.; Chen, L. J.; Bessho, N.; Hesse, M.; Kistler, L. M.; Torbert, R. B.; Mouikis, C.; Pollock, C. J.

2015-12-01

We investigate electron and ion velocity distribution functions in dayside magnetopause reconnection events observed by the Cluster and MMS spacecraft. The goal is to build a spatial map of electron and ion distribution features to enable the indication of the spacecraft location in the reconnection structure, and to understand plasma energization processes. Distribution functions, together with electromagnetic field structures, plasma densities, and bulk velocities, are organized and compared with particle-in-cell simulation results to indicate the proximities to the reconnection X-line. Anisotropic features in the distributions of magnetospheric- and magnetosheath- origin electrons at different locations in the reconnection inflow and exhaust are identified. In particular, parallel electron heating is observed in both the magnetosheath and magnetosphere inflow regions. Possible effects of the guide field strength, waves, and upstream density and temperature asymmetries on the distribution features will be discussed.

Fishermen Follow Fine-scaled Physical Ocean Features For Finance

NASA Astrophysics Data System (ADS)

Fuller, E.; Watson, J. R.; Samhouri, J.; Castruccio, F. S.

2016-12-01

The seascapes on which many millions of people make their living and secure food have complex and dynamic spatial features - the figurative hills and valleys - that control where and how people work at sea. Here, we quantify the physical mosaic of the surface ocean by identifying Lagrangian Coherent Structures for a whole seascape - the California Current - and assess their impact on the spatial distribution of fishing. We show that there is a mixed response: some fisheries track these physical features, and others avoid them. This spatial behavior maps to economic impacts: we find that tuna fishermen can expect to make three times more revenue per trip if fishing occurs on strong coherent structures. These results highlight a connection between the physical state of the oceans, the spatial patterns of human activity and ultimately the economic prosperity of coastal communities.

The evaluation of multi-structure, multi-atlas pelvic anatomy features in a prostate MR lymphography CAD system

NASA Astrophysics Data System (ADS)

Meijs, M.; Debats, O.; Huisman, H.

2015-03-01

In prostate cancer, the detection of metastatic lymph nodes indicates progression from localized disease to metastasized cancer. The detection of positive lymph nodes is, however, a complex and time consuming task for experienced radiologists. Assistance of a two-stage Computer-Aided Detection (CAD) system in MR Lymphography (MRL) is not yet feasible due to the large number of false positives in the first stage of the system. By introducing a multi-structure, multi-atlas segmentation, using an affine transformation followed by a B-spline transformation for registration, the organ location is given by a mean density probability map. The atlas segmentation is semi-automatically drawn with ITK-SNAP, using Active Contour Segmentation. Each anatomic structure is identified by a label number. Registration is performed using Elastix, using Mutual Information and an Adaptive Stochastic Gradient optimization. The dataset consists of the MRL scans of ten patients, with lymph nodes manually annotated in consensus by two expert readers. The feature map of the CAD system consists of the Multi-Atlas and various other features (e.g. Normalized Intensity and multi-scale Blobness). The voxel-based Gentleboost classifier is evaluated using ROC analysis with cross validation. We show in a set of 10 studies that adding multi-structure, multi-atlas anatomical structure likelihood features improves the quality of the lymph node voxel likelihood map. Multiple structure anatomy maps may thus make MRL CAD more feasible.

Discriminative analysis of schizophrenia using support vector machine and recursive feature elimination on structural MRI images.

PubMed

Lu, Xiaobing; Yang, Yongzhe; Wu, Fengchun; Gao, Minjian; Xu, Yong; Zhang, Yue; Yao, Yongcheng; Du, Xin; Li, Chengwei; Wu, Lei; Zhong, Xiaomei; Zhou, Yanling; Fan, Ni; Zheng, Yingjun; Xiong, Dongsheng; Peng, Hongjun; Escudero, Javier; Huang, Biao; Li, Xiaobo; Ning, Yuping; Wu, Kai

2016-07-01

Structural abnormalities in schizophrenia (SZ) patients have been well documented with structural magnetic resonance imaging (MRI) data using voxel-based morphometry (VBM) and region of interest (ROI) analyses. However, these analyses can only detect group-wise differences and thus, have a poor predictive value for individuals. In the present study, we applied a machine learning method that combined support vector machine (SVM) with recursive feature elimination (RFE) to discriminate SZ patients from normal controls (NCs) using their structural MRI data. We first employed both VBM and ROI analyses to compare gray matter volume (GMV) and white matter volume (WMV) between 41 SZ patients and 42 age- and sex-matched NCs. The method of SVM combined with RFE was used to discriminate SZ patients from NCs using significant between-group differences in both GMV and WMV as input features. We found that SZ patients showed GM and WM abnormalities in several brain structures primarily involved in the emotion, memory, and visual systems. An SVM with a RFE classifier using the significant structural abnormalities identified by the VBM analysis as input features achieved the best performance (an accuracy of 88.4%, a sensitivity of 91.9%, and a specificity of 84.4%) in the discriminative analyses of SZ patients. These results suggested that distinct neuroanatomical profiles associated with SZ patients might provide a potential biomarker for disease diagnosis, and machine-learning methods can reveal neurobiological mechanisms in psychiatric diseases.

Cemento-osseous dysplasia of the jaw bones: key radiographic features

PubMed Central

Alsufyani, NA; Lam, EWN

2011-01-01

Objective The purpose of this study is to assess possible diagnostic differences between general dentists (GPs) and oral and maxillofacial radiologists (RGs) in the identification of pathognomonic radiographic features of cemento-osseous dysplasia (COD) and its interpretation. Methods Using a systematic objective survey instrument, 3 RGs and 3 GPs reviewed 50 image sets of COD and similarly appearing entities (dense bone island, cementoblastoma, cemento-ossifying fibroma, fibrous dysplasia, complex odontoma and sclerosing osteitis). Participants were asked to identify the presence or absence of radiographic features and then to make an interpretation of the images. Results RGs identified a well-defined border (odds ratio (OR) 6.67, P < 0.05); radiolucent periphery (OR 8.28, P < 0.005); bilateral occurrence (OR 10.23, P < 0.01); mixed radiolucent/radiopaque internal structure (OR 10.53, P < 0.01); the absence of non-concentric bony expansion (OR 7.63, P < 0.05); and the association with anterior and posterior teeth (OR 4.43, P < 0.05) as key features of COD. Consequently, RGs were able to correctly interpret 79.3% of COD cases. In contrast, GPs identified the absence of root resorption (OR 4.52, P < 0.05) and the association with anterior and posterior teeth (OR 3.22, P = 0.005) as the only key features of COD and were able to correctly interpret 38.7% of COD cases. Conclusions There are statistically significant differences between RGs and GPs in the identification and interpretation of the radiographic features associated with COD (P < 0.001). We conclude that COD is radiographically discernable from other similarly appearing entities only if the characteristic radiographic features are correctly identified and then correctly interpreted. PMID:21346079

Cemento-osseous dysplasia of the jaw bones: key radiographic features.

PubMed

Alsufyani, N A; Lam, E W N

2011-03-01

The purpose of this study is to assess possible diagnostic differences between general dentists (GPs) and oral and maxillofacial radiologists (RGs) in the identification of pathognomonic radiographic features of cemento-osseous dysplasia (COD) and its interpretation. Using a systematic objective survey instrument, 3 RGs and 3 GPs reviewed 50 image sets of COD and similarly appearing entities (dense bone island, cementoblastoma, cemento-ossifying fibroma, fibrous dysplasia, complex odontoma and sclerosing osteitis). Participants were asked to identify the presence or absence of radiographic features and then to make an interpretation of the images. RGs identified a well-defined border (odds ratio (OR) 6.67, P < 0.05); radiolucent periphery (OR 8.28, P < 0.005); bilateral occurrence (OR 10.23, P < 0.01); mixed radiolucent/radiopaque internal structure (OR 10.53, P < 0.01); the absence of non-concentric bony expansion (OR 7.63, P < 0.05); and the association with anterior and posterior teeth (OR 4.43, P < 0.05) as key features of COD. Consequently, RGs were able to correctly interpret 79.3% of COD cases. In contrast, GPs identified the absence of root resorption (OR 4.52, P < 0.05) and the association with anterior and posterior teeth (OR 3.22, P = 0.005) as the only key features of COD and were able to correctly interpret 38.7% of COD cases. There are statistically significant differences between RGs and GPs in the identification and interpretation of the radiographic features associated with COD (P < 0.001). We conclude that COD is radiographically discernable from other similarly appearing entities only if the characteristic radiographic features are correctly identified and then correctly interpreted.

A Method for WD40 Repeat Detection and Secondary Structure Prediction

PubMed Central

Wang, Yang; Jiang, Fan; Zhuo, Zhu; Wu, Xian-Hui; Wu, Yun-Dong

2013-01-01

WD40-repeat proteins (WD40s), as one of the largest protein families in eukaryotes, play vital roles in assembling protein-protein/DNA/RNA complexes. WD40s fold into similar β-propeller structures despite diversified sequences. A program WDSP (WD40 repeat protein Structure Predictor) has been developed to accurately identify WD40 repeats and predict their secondary structures. The method is designed specifically for WD40 proteins by incorporating both local residue information and non-local family-specific structural features. It overcomes the problem of highly diversified protein sequences and variable loops. In addition, WDSP achieves a better prediction in identifying multiple WD40-domain proteins by taking the global combination of repeats into consideration. In secondary structure prediction, the average Q3 accuracy of WDSP in jack-knife test reaches 93.7%. A disease related protein LRRK2 was used as a representive example to demonstrate the structure prediction. PMID:23776530

Diagnosing pyogenic, brucella and tuberculous spondylitis using histopathology and MRI: A retrospective study.

PubMed

Li, Tao; Liu, Tao; Jiang, Zhensong; Cui, Xingang; Sun, Jianmin

2016-10-01

The present study examined the histopathological and magnetic resonance imaging (MRI) features of pyogenic, brucella and tuberculous spondylitis (PS, BS and TS, respectively). A total of 22 PS, 20 BS and 20 TS patients were included in the study. Histopathological examination was used to assess the lesion structure and composition, and the MRI observation identified the lesion location and signal features. The following histopathological and MRI features were identified significantly more in patients with PS than in patients with BS and TS: Predominant neutrophil infiltration, abnormal intervertebral disk signal, lesions on the ventral and lateral sides of the vertebral bodies, and thick and irregular abscess walls. The following histopathological and MRI features were identified significantly more in patients with BS than in patients with PS and TS: Predominant lymphocyte infiltration, new bone formation, epithelioid granuloma, lesions on the ventral sides of the vertebral bodies, no, or very mild, vertebral body deformation, no abnormal paraspinal soft tissue signal, no intraosseous or paraspinal abscesses, and thin and irregular abscess walls. The following histopathological and MRI features were identified significantly more in patients with TS than in patients with BS and PS: Sequestrum, Langerhans giant cells, caseous necrosis, lesions primarily in the thoracic region and on the lateral sides of the vertebral bodies, no obvious intervertebral disk damage, obvious vertebral body deformation, abnormal paraspinal soft tissue signal, intraosseous or paraspinal abscesses, and thin and smooth abscess walls. In conclusion, it can be suggested that these significant differences in histopathological and MRI features between the three different types of spondylitis may contribute towards the differential diagnosis of the diseases.

Flight State Identification of a Self-Sensing Wing via an Improved Feature Selection Method and Machine Learning Approaches

PubMed Central

Chen, Xi; Wu, Qi; Ren, He; Chang, Fu-Kuo

2018-01-01

In this work, a data-driven approach for identifying the flight state of a self-sensing wing structure with an embedded multi-functional sensing network is proposed. The flight state is characterized by the structural vibration signals recorded from a series of wind tunnel experiments under varying angles of attack and airspeeds. A large feature pool is created by extracting potential features from the signals covering the time domain, the frequency domain as well as the information domain. Special emphasis is given to feature selection in which a novel filter method is developed based on the combination of a modified distance evaluation algorithm and a variance inflation factor. Machine learning algorithms are then employed to establish the mapping relationship from the feature space to the practical state space. Results from two case studies demonstrate the high identification accuracy and the effectiveness of the model complexity reduction via the proposed method, thus providing new perspectives of self-awareness towards the next generation of intelligent air vehicles. PMID:29710832

The Beauty and Biology of Pollen.

ERIC Educational Resources Information Center

Clay-Poole, Scott T.; Slesnick, Irwin L.

1983-01-01

Describes: basic features of pollen grains (shapes, apertures, layering of wall, exine sculpturing); strategies for pollination (anemophily--wind transported, zoophily--animal transported); and the structures specialized for each process. Gives instructions for using scanning electron microscope photographs and for collecting, identifying, and…

Assessment of the Seattle Smart Traveler evaluation

DOT National Transportation Integrated Search

1999-09-01

The system was designed using a World Wide Web or Internet interface. Two of the unique features of the design were accommodating the desired travel times and identifying origins and destinations. A search structure was developed using a series of pu...

Automated retrieval of forest structure variables based on multi-scale texture analysis of VHR satellite imagery

NASA Astrophysics Data System (ADS)

Beguet, Benoit; Guyon, Dominique; Boukir, Samia; Chehata, Nesrine

2014-10-01

The main goal of this study is to design a method to describe the structure of forest stands from Very High Resolution satellite imagery, relying on some typical variables such as crown diameter, tree height, trunk diameter, tree density and tree spacing. The emphasis is placed on the automatization of the process of identification of the most relevant image features for the forest structure retrieval task, exploiting both spectral and spatial information. Our approach is based on linear regressions between the forest structure variables to be estimated and various spectral and Haralick's texture features. The main drawback of this well-known texture representation is the underlying parameters which are extremely difficult to set due to the spatial complexity of the forest structure. To tackle this major issue, an automated feature selection process is proposed which is based on statistical modeling, exploring a wide range of parameter values. It provides texture measures of diverse spatial parameters hence implicitly inducing a multi-scale texture analysis. A new feature selection technique, we called Random PRiF, is proposed. It relies on random sampling in feature space, carefully addresses the multicollinearity issue in multiple-linear regression while ensuring accurate prediction of forest variables. Our automated forest variable estimation scheme was tested on Quickbird and Pléiades panchromatic and multispectral images, acquired at different periods on the maritime pine stands of two sites in South-Western France. It outperforms two well-established variable subset selection techniques. It has been successfully applied to identify the best texture features in modeling the five considered forest structure variables. The RMSE of all predicted forest variables is improved by combining multispectral and panchromatic texture features, with various parameterizations, highlighting the potential of a multi-resolution approach for retrieving forest structure variables from VHR satellite images. Thus an average prediction error of ˜ 1.1 m is expected on crown diameter, ˜ 0.9 m on tree spacing, ˜ 3 m on height and ˜ 0.06 m on diameter at breast height.

Non-parametric adaptative JPEG fragments carving

NASA Astrophysics Data System (ADS)

Amrouche, Sabrina Cherifa; Salamani, Dalila

2018-04-01

The most challenging JPEG recovery tasks arise when the file header is missing. In this paper we propose to use a two layer machine learning model to restore headerless JPEG images. We first build a classifier able to identify the structural properties of the images/fragments and then use an AutoEncoder (AE) to learn the fragment features for the header prediction. We define a JPEG universal header and the remaining free image parameters (Height, Width) are predicted with a Gradient Boosting Classifier. Our approach resulted in 90% accuracy using the manually defined features and 78% accuracy using the AE features.

Label-free visualization of ultrastructural features of artificial synapses via cryo-EM.

PubMed

Gopalakrishnan, Gopakumar; Yam, Patricia T; Madwar, Carolin; Bostina, Mihnea; Rouiller, Isabelle; Colman, David R; Lennox, R Bruce

2011-12-21

The ultrastructural details of presynapses formed between artificial substrates of submicrometer silica beads and hippocampal neurons are visualized via cryo-electron microscopy (cryo-EM). The silica beads are derivatized by poly-d-lysine or lipid bilayers. Molecular features known to exist at presynapses are clearly present at these artificial synapses, as visualized by cryo-EM. Key synaptic features such as the membrane contact area at synaptic junctions, the presynaptic bouton containing presynaptic vesicles, as well as microtubular structures can be identified. This is the first report of the direct, label-free observation of ultrastructural details of artificial synapses.

Learning Microbial Community Structures with Supervised and Unsupervised Non-negative Matrix Factorization.

PubMed

Cai, Yun; Gu, Hong; Kenney, Toby

2017-08-31

Learning the structure of microbial communities is critical in understanding the different community structures and functions of microbes in distinct individuals. We view microbial communities as consisting of many subcommunities which are formed by certain groups of microbes functionally dependent on each other. The focus of this paper is on methods for extracting the subcommunities from the data, in particular Non-Negative Matrix Factorization (NMF). Our methods can be applied to both OTU data and functional metagenomic data. We apply the existing unsupervised NMF method and also develop a new supervised NMF method for extracting interpretable information from classification problems. The relevance of the subcommunities identified by NMF is demonstrated by their excellent performance for classification. Through three data examples, we demonstrate how to interpret the features identified by NMF to draw meaningful biological conclusions and discover hitherto unidentified patterns in the data. Comparing whole metagenomes of various mammals, (Muegge et al., Science 332:970-974, 2011), the biosynthesis of macrolides pathway is found in hindgut-fermenting herbivores, but not carnivores. This is consistent with results in veterinary science that macrolides should not be given to non-ruminant herbivores. For time series microbiome data from various body sites (Caporaso et al., Genome Biol 12:50, 2011), a shift in the microbial communities is identified for one individual. The shift occurs at around the same time in the tongue and gut microbiomes, indicating that the shift is a genuine biological trait, rather than an artefact of the method. For whole metagenome data from IBD patients and healthy controls (Qin et al., Nature 464:59-65, 2010), we identify differences in a number of pathways (some known, others new). NMF is a powerful tool for identifying the key features of microbial communities. These identified features can not only be used to perform difficult classification problems with a high degree of accuracy, they are also very interpretable and can lead to important biological insights into the structure of the communities. In addition, NMF is a dimension-reduction method (similar to PCA) in that it reduces the extremely complex microbial data into a low-dimensional representation, allowing a number of analyses to be performed more easily-for example, searching for temporal patterns in the microbiome. When we are interested in the differences between the structures of two groups of communities, supervised NMF provides a better way to do this, while retaining all the advantages of NMF-e.g. interpretability and a simple biological intuition.

Structural and sequence features of two residue turns in beta-hairpins.

PubMed

Madan, Bharat; Seo, Sung Yong; Lee, Sun-Gu

2014-09-01

Beta-turns in beta-hairpins have been implicated as important sites in protein folding. In particular, two residue β-turns, the most abundant connecting elements in beta-hairpins, have been a major target for engineering protein stability and folding. In this study, we attempted to investigate and update the structural and sequence properties of two residue turns in beta-hairpins with a large data set. For this, 3977 beta-turns were extracted from 2394 nonhomologous protein chains and analyzed. First, the distribution, dihedral angles and twists of two residue turn types were determined, and compared with previous data. The trend of turn type occurrence and most structural features of the turn types were similar to previous results, but for the first time Type II turns in beta-hairpins were identified. Second, sequence motifs for the turn types were devised based on amino acid positional potentials of two-residue turns, and their distributions were examined. From this study, we could identify code-like sequence motifs for the two residue beta-turn types. Finally, structural and sequence properties of beta-strands in the beta-hairpins were analyzed, which revealed that the beta-strands showed no specific sequence and structural patterns for turn types. The analytical results in this study are expected to be a reference in the engineering or design of beta-hairpin turn structures and sequences. © 2014 Wiley Periodicals, Inc.

Semantics and technologies in modern design of interior stairs

NASA Astrophysics Data System (ADS)

Kukhta, M.; Sokolov, A.; Pelevin, E.

2015-10-01

Use of metal in the design of interior stairs presents new features for shaping, and can be implemented using different technologies. The article discusses the features of design and production technologies of forged metal spiral staircase considering the image semantics based on the historical and cultural heritage. To achieve the objective was applied structural- semantic method (to identify the organization of structure and semantic features of the artistic image), engineering methods (to justify the construction of the object), anthropometry method and ergonomics (to provide usability), methods of comparative analysis (to reveale the features of the way the ladder in different periods of culture). According to the research results are as follows. Was revealed the semantics influence on the design of interior staircase that is based on the World Tree image. Also was suggested rational calculation of steps to ensure the required strength. And finally was presented technology, providing the realization of the artistic image. In the practical part of the work is presented version of forged staircase.

Assessment of metal ion concentration in water with structured feature selection.

PubMed

Naula, Pekka; Airola, Antti; Pihlasalo, Sari; Montoya Perez, Ileana; Salakoski, Tapio; Pahikkala, Tapio

2017-10-01

We propose a cost-effective system for the determination of metal ion concentration in water, addressing a central issue in water resources management. The system combines novel luminometric label array technology with a machine learning algorithm that selects a minimal number of array reagents (modulators) and liquid sample dilutions, such that enable accurate quantification. The algorithm is able to identify the optimal modulators and sample dilutions leading to cost reductions since less manual labour and resources are needed. Inferring the ion detector involves a unique type of a structured feature selection problem, which we formalize in this paper. We propose a novel Cartesian greedy forward feature selection algorithm for solving the problem. The novel algorithm was evaluated in the concentration assessment of five metal ions and the performance was compared to two known feature selection approaches. The results demonstrate that the proposed system can assist in lowering the costs with minimal loss in accuracy. Copyright © 2017 Elsevier Ltd. All rights reserved.

In silico modelling and molecular dynamics simulation studies of thiazolidine based PTP1B inhibitors.

PubMed

Mahapatra, Manoj Kumar; Bera, Krishnendu; Singh, Durg Vijay; Kumar, Rajnish; Kumar, Manoj

2018-04-01

Protein tyrosine phosphatase 1B (PTP1B) has been identified as a negative regulator of insulin and leptin signalling pathway; hence, it can be considered as a new therapeutic target of intervention for the treatment of type 2 diabetes. Inhibition of this molecular target takes care of both diabetes and obesity, i.e. diabestiy. In order to get more information on identification and optimization of lead, pharmacophore modelling, atom-based 3D QSAR, docking and molecular dynamics studies were carried out on a set of ligands containing thiazolidine scaffold. A six-point pharmacophore model consisting of three hydrogen bond acceptor (A), one negative ionic (N) and two aromatic rings (R) with discrete geometries as pharmacophoric features were developed for a predictive 3D QSAR model. The probable binding conformation of the ligands within the active site was studied through molecular docking. The molecular interactions and the structural features responsible for PTP1B inhibition and selectivity were further supplemented by molecular dynamics simulation study for a time scale of 30 ns. The present investigation has identified some of the indispensible structural features of thiazolidine analogues which can further be explored to optimize PTP1B inhibitors.

Using ancestry-informative markers to identify fine structure across 15 populations of European origin.

PubMed

Huckins, Laura M; Boraska, Vesna; Franklin, Christopher S; Floyd, James A B; Southam, Lorraine; Sullivan, Patrick F; Bulik, Cynthia M; Collier, David A; Tyler-Smith, Chris; Zeggini, Eleftheria; Tachmazidou, Ioanna

2014-10-01

The Wellcome Trust Case Control Consortium 3 anorexia nervosa genome-wide association scan includes 2907 cases from 15 different populations of European origin genotyped on the Illumina 670K chip. We compared methods for identifying population stratification, and suggest list of markers that may help to counter this problem. It is usual to identify population structure in such studies using only common variants with minor allele frequency (MAF) >5%; we find that this may result in highly informative SNPs being discarded, and suggest that instead all SNPs with MAF >1% may be used. We established informative axes of variation identified via principal component analysis and highlight important features of the genetic structure of diverse European-descent populations, some studied for the first time at this scale. Finally, we investigated the substructure within each of these 15 populations and identified SNPs that help capture hidden stratification. This work can provide information regarding the designing and interpretation of association results in the International Consortia.

Venusian arachnoids revisited

NASA Astrophysics Data System (ADS)

Kostama, V.-P.; Tormanen, T.

The Venusian volcano-tectonic structures have been subject to many classification and characterisation schemes. Several structure-types have been identified (e.g. coronae, novae, arachnoids, calderas, and corona-novae). Of these groups, the relationship of arachnoids and coronae has been complicated, and is a subject to much debate. Some previous works and studies have fused these two categories together, and even promoted the view of non-existence of arachnoids at times. However, based on the recognisable differences in morphology and other characteristics (e.g. size, topography, volcanism), they should be treated as a separate class of structures. In our first global study of the volcano-tectonic features, we found 96 arachnoids [1, 2]. During the reanalysis of the features as a by-product of another study, the arachnoid population was re-evalueted, and more importantly, the identification criteria was rechecked. The revised population increases the arachnoid number to 130 features. The work also produced many examples of features that can be considered as transitional forms between different morphological groups. [1] Kostama, V.-P., M. Aittola, LPSC XXXII, Abstract#1185, 2001a. [2] Kostama, V.-P., M. Aittola, The Catalogue of Venusian Arachnoids, Coronae and Novae, http://cc.oulu.fi/tati/JR/Venus/volcanotectonics/catalogue.html, 2001b.

The vanishing cryovolcanoes of Ceres

USGS Publications Warehouse

Sori, Michael M.; Byrne, Shane; Bland, Michael T.; Bramson, Ali; Ermakov, Anton; Hamilton, Christoper; Otto, Katharina; Ruesch, Ottaviano; Russell, Christopher

2017-01-01

Ahuna Mons is a 4 km tall mountain on Ceres interpreted as a geologically young cryovolcanic dome. Other possible cryovolcanic features are more ambiguous, implying that cryovolcanism is only a recent phenomenon or that other cryovolcanic structures have been modified beyond easy identification. We test the hypothesis that Cerean cryovolcanic domes viscously relax, precluding ancient domes from recognition. We use numerical models to predict flow velocities of Ahuna Mons to be 10–500 m/Myr, depending upon assumptions about ice content, rheology, grain size, and thermal parameters. Slower flow rates in this range are sufficiently fast to induce extensive relaxation of cryovolcanic structures over 108–109 years, but gradual enough for Ahuna Mons to remain identifiable today. Positive topographic features, including a tholus underlying Ahuna Mons, may represent relaxed cryovolcanic structures. A composition for Ahuna Mons of >40% ice explains the observed distribution of cryovolcanic structures because viscous relaxation renders old cryovolcanoes unrecognizable.

Diabetic Rethinopathy Screening by Bright Lesions Extraction from Fundus Images

NASA Astrophysics Data System (ADS)

Hanđsková, Veronika; Pavlovičova, Jarmila; Oravec, Miloš; Blaško, Radoslav

2013-09-01

Retinal images are nowadays widely used to diagnose many diseases, for example diabetic retinopathy. In our work, we propose the algorithm for the screening application, which identifies the patients with such severe diabetic complication as diabetic retinopathy is, in early phase. In the application we use the patient's fundus photography without any additional examination by an ophtalmologist. After this screening identification, other examination methods should be considered and the patient's follow-up by a doctor is necessary. Our application is composed of three principal modules including fundus image preprocessing, feature extraction and feature classification. Image preprocessing module has the role of luminance normalization, contrast enhancement and optical disk masking. Feature extraction module includes two stages: bright lesions candidates localization and candidates feature extraction. We selected 16 statistical and structural features. For feature classification, we use multilayer perceptron (MLP) with one hidden layer. We classify images into two classes. Feature classification efficiency is about 93 percent.

Extant fold-switching proteins are widespread.

PubMed

Porter, Lauren L; Looger, Loren L

2018-06-05

A central tenet of biology is that globular proteins have a unique 3D structure under physiological conditions. Recent work has challenged this notion by demonstrating that some proteins switch folds, a process that involves remodeling of secondary structure in response to a few mutations (evolved fold switchers) or cellular stimuli (extant fold switchers). To date, extant fold switchers have been viewed as rare byproducts of evolution, but their frequency has been neither quantified nor estimated. By systematically and exhaustively searching the Protein Data Bank (PDB), we found ∼100 extant fold-switching proteins. Furthermore, we gathered multiple lines of evidence suggesting that these proteins are widespread in nature. Based on these lines of evidence, we hypothesized that the frequency of extant fold-switching proteins may be underrepresented by the structures in the PDB. Thus, we sought to identify other putative extant fold switchers with only one solved conformation. To do this, we identified two characteristic features of our ∼100 extant fold-switching proteins, incorrect secondary structure predictions and likely independent folding cooperativity, and searched the PDB for other proteins with similar features. Reassuringly, this method identified dozens of other proteins in the literature with indication of a structural change but only one solved conformation in the PDB. Thus, we used it to estimate that 0.5-4% of PDB proteins switch folds. These results demonstrate that extant fold-switching proteins are likely more common than the PDB reflects, which has implications for cell biology, genomics, and human health. Copyright © 2018 the Author(s). Published by PNAS.

Consumers' Preferences for Electronic Nicotine Delivery System Product Features: A Structured Content Analysis.

PubMed

Kistler, Christine E; Crutchfield, Trisha M; Sutfin, Erin L; Ranney, Leah M; Berman, Micah L; Zarkin, Gary A; Goldstein, Adam O

2017-06-07

To inform potential governmental regulations, we aimed to develop a list of electronic nicotine delivery system (ENDS) product features important to U.S. consumers by age and gender. We employed qualitative data methods. Participants were eligible if they had used an ENDS at least once. Groups were selected by age and gender (young adult group aged 18-25, n = 11; middle-age group aged 26-64, n = 9; and women's group aged 26-64, n = 9). We conducted five individual older adult interviews (aged 68-80). Participants discussed important ENDS features. We conducted a structured content analysis of the group and interview responses. Of 34 participants, 68% were white and 56% were female. Participants mentioned 12 important ENDS features, including: (1) user experience; (2) social acceptability; (3) cost; (4) health risks/benefits; (5) ease of use; (6) flavors; (7) smoking cessation aid; (8) nicotine content; (9) modifiability; (10) ENDS regulation; (11) bridge between tobacco cigarettes; (12) collectability. The most frequently mentioned ENDS feature was modifiability for young adults, user experience for middle-age and older adults, and flavor for the women's group. This study identified multiple features important to ENDS consumers. Groups differed in how they viewed various features by age and gender. These results can inform ongoing regulatory efforts.

Consumers’ Preferences for Electronic Nicotine Delivery System Product Features: A Structured Content Analysis

PubMed Central

Kistler, Christine E.; Crutchfield, Trisha M.; Sutfin, Erin L.; Ranney, Leah M.; Berman, Micah L.; Zarkin, Gary A.; Goldstein, Adam O.

2017-01-01

To inform potential governmental regulations, we aimed to develop a list of electronic nicotine delivery system (ENDS) product features important to U.S. consumers by age and gender. We employed qualitative data methods. Participants were eligible if they had used an ENDS at least once. Groups were selected by age and gender (young adult group aged 18–25, n = 11; middle-age group aged 26–64, n = 9; and women’s group aged 26–64, n = 9). We conducted five individual older adult interviews (aged 68–80). Participants discussed important ENDS features. We conducted a structured content analysis of the group and interview responses. Of 34 participants, 68% were white and 56% were female. Participants mentioned 12 important ENDS features, including: (1) user experience; (2) social acceptability; (3) cost; (4) health risks/benefits; (5) ease of use; (6) flavors; (7) smoking cessation aid; (8) nicotine content; (9) modifiability; (10) ENDS regulation; (11) bridge between tobacco cigarettes; (12) collectability. The most frequently mentioned ENDS feature was modifiability for young adults, user experience for middle-age and older adults, and flavor for the women’s group. This study identified multiple features important to ENDS consumers. Groups differed in how they viewed various features by age and gender. These results can inform ongoing regulatory efforts. PMID:28590444

Bacterial chemoreceptors: high-performance signaling in networked arrays.

PubMed

Hazelbauer, Gerald L; Falke, Joseph J; Parkinson, John S

2008-01-01

Chemoreceptors are crucial components in the bacterial sensory systems that mediate chemotaxis. Chemotactic responses exhibit exquisite sensitivity, extensive dynamic range and precise adaptation. The mechanisms that mediate these high-performance functions involve not only actions of individual proteins but also interactions among clusters of components, localized in extensive patches of thousands of molecules. Recently, these patches have been imaged in native cells, important features of chemoreceptor structure and on-off switching have been identified, and new insights have been gained into the structural basis and functional consequences of higher order interactions among sensory components. These new data suggest multiple levels of molecular interactions, each of which contribute specific functional features and together create a sophisticated signaling device.

Bacterial chemoreceptors: high-performance signaling in networked arrays

PubMed Central

Hazelbauer, Gerald L.; Falke, Joseph J.; Parkinson, John S.

2010-01-01

Chemoreceptors are crucial components in the bacterial sensory systems that mediate chemotaxis. Chemotactic responses exhibit exquisite sensitivity, extensive dynamic range and precise adaptation. The mechanisms that mediate these high-performance functions involve not only actions of individual proteins but also interactions among clusters of components, localized in extensive patches of thousands of molecules. Recently, these patches have been imaged in native cells, important features of chemoreceptor structure and on–off switching have been identified, and new insights have been gained into the structural basis and functional consequences of higher order interactions among sensory components. These new data suggest multiple levels of molecular interactions, each of which contribute specific functional features and together create a sophisticated signaling device. PMID:18165013

Dynamic fiber Bragg gratings based health monitoring system of composite aerospace structures

NASA Astrophysics Data System (ADS)

Panopoulou, A.; Loutas, T.; Roulias, D.; Fransen, S.; Kostopoulos, V.

2011-09-01

The main purpose of the current work is to develop a new system for structural health monitoring of composite aerospace structures based on real-time dynamic measurements, in order to identify the structural state condition. Long-gauge Fibre Bragg Grating (FBG) optical sensors were used for monitoring the dynamic response of the composite structure. The algorithm that was developed for structural damage detection utilizes the collected dynamic response data, analyzes them in various ways and through an artificial neural network identifies the damage state and its location. Damage was simulated by slightly varying locally the mass of the structure (by adding a known mass) at different zones of the structure. Lumped masses in different locations upon the structure alter the eigen-frequencies in a way similar to actual damage. The structural dynamic behaviour has been numerically simulated and experimentally verified by means of modal testing on two different composite aerospace structures. Advanced digital signal processing techniques, e.g. the wavelet transform (WT), were used for the analysis of the dynamic response for feature extraction. WT's capability of separating the different frequency components in the time domain without loosing frequency information makes it a versatile tool for demanding signal processing applications. The use of WT is also suggested by the no-stationary nature of dynamic response signals and the opportunity of evaluating the temporal evolution of their frequency contents. Feature extraction is the first step of the procedure. The extracted features are effective indices of damage size and location. The classification step comprises of a feed-forward back propagation network, whose output determines the simulated damage location. Finally, dedicated training and validation activities were carried out by means of numerical simulations and experimental procedures. Experimental validation was performed initially on a flat stiffened panel, representing a section of a typical aeronautical structure, manufactured and tested in the lab and, as a second step, on a scaled up space oriented structure, which is a composite honeycomb plate, used as a deployment base for antenna arrays. An integrated FBG sensor network, based on the advantage of multiplexing, was mounted on both structures and different excitation positions and boundary conditions were used. The analysis of operational dynamic responses was employed to identify both the damage and its position. The system that was designed and tested initially on the thin composite panel, was successfully validated on the larger honeycomb structure. Numerical simulation of both structures was used as a support tool at all the steps of the work providing among others the location of the optical sensors used. The proposed work will be the base for the whole system qualification and validation on an antenna reflector in future work.

Structural Insights into the Transport Mechanism of the Human Sodium-dependent Lysophosphatidylcholine Transporter MFSD2A*♦

PubMed Central

Quek, Debra Q. Y.; Nguyen, Long N.; Fan, Hao; Silver, David L.

2016-01-01

Major facilitator superfamily domain containing 2A (MFSD2A) was recently characterized as a sodium-dependent lysophosphatidylcholine transporter expressed at the blood-brain barrier endothelium. It is the primary route for importation of docosohexaenoic acid and other long-chain fatty acids into fetal and adult brain and is essential for mouse and human brain growth and function. Remarkably, MFSD2A is the first identified major facilitator superfamily member that uniquely transports lipids, implying that MFSD2A harbors unique structural features and transport mechanism. Here, we present three three-dimensional structural models of human MFSD2A derived by homology modeling using MelB- and LacY-based crystal structures and refined by biochemical analysis. All models revealed 12 transmembrane helices and connecting loops and represented the partially outward-open, outward-partially occluded, and inward-open states of the transport cycle. In addition to a conserved sodium-binding site, three unique structural features were identified as follows: a phosphate headgroup binding site, a hydrophobic cleft to accommodate a hydrophobic hydrocarbon tail, and three sets of ionic locks that stabilize the outward-open conformation. Ligand docking studies and biochemical assays identified Lys-436 as a key residue for transport. It is seen forming a salt bridge with the negative charge on the phosphate headgroup. Importantly, MFSD2A transported structurally related acylcarnitines but not a lysolipid without a negative charge, demonstrating the necessity of a negatively charged headgroup interaction with Lys-436 for transport. These findings support a novel transport mechanism by which lysophosphatidylcholines are “flipped” within the transporter cavity by pivoting about Lys-436 leading to net transport from the outer to the inner leaflet of the plasma membrane. PMID:26945070

Persistence of urban organic aerosols composition: Decoding their structural complexity and seasonal variability.

PubMed

Matos, João T V; Duarte, Regina M B O; Lopes, Sónia P; Silva, Artur M S; Duarte, Armando C

2017-12-01

Organic Aerosols (OAs) are typically defined as highly complex matrices whose composition changes in time and space. Focusing on time vector, this work uses two-dimensional nuclear magnetic resonance (2D NMR) techniques to examine the structural features of water-soluble (WSOM) and alkaline-soluble organic matter (ASOM) sequentially extracted from fine atmospheric aerosols collected in an urban setting during cold and warm seasons. This study reveals molecular signatures not previously decoded in NMR-related studies of OAs as meaningful source markers. Although the ASOM is less hydrophilic and structurally diverse than its WSOM counterpart, both fractions feature a core with heteroatom-rich branched aliphatics from both primary (natural and anthropogenic) and secondary origin, aromatic secondary organics originated from anthropogenic aromatic precursors, as well as primary saccharides and amino sugar derivatives from biogenic emissions. These common structures represent those 2D NMR spectral signatures that are present in both seasons and can thus be seen as an "annual background" profile of the structural composition of OAs at the urban location. Lignin-derived structures, nitroaromatics, disaccharides, and anhydrosaccharides signatures were also identified in the WSOM samples only from periods identified as smoke impacted, which reflects the influence of biomass-burning sources. The NMR dataset on the H-C molecules backbone was also used to propose a semi-quantitative structural model of urban WSOM, which will aid efforts for more realistic studies relating the chemical properties of OAs with their atmospheric behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

Criterion for Identifying Vortices in High-Pressure Flows

NASA Technical Reports Server (NTRS)

Bellan, Josette; Okong'o, Nora

2007-01-01

A study of four previously published computational criteria for identifying vortices in high-pressure flows has led to the selection of one of them as the best. This development can be expected to contribute to understanding of high-pressure flows, which occur in diverse settings, including diesel, gas turbine, and rocket engines and the atmospheres of Jupiter and other large gaseous planets. Information on the atmospheres of gaseous planets consists mainly of visual and thermal images of the flows over the planets. Also, validation of recently proposed computational models of high-pressure flows entails comparison with measurements, which are mainly of visual nature. Heretofore, the interpretation of images of high-pressure flows to identify vortices has been based on experience with low-pressure flows. However, high-pressure flows have features distinct from those of low-pressure flows, particularly in regions of high pressure gradient magnitude caused by dynamic turbulent effects and by thermodynamic mixing of chemical species. Therefore, interpretations based on low-pressure behavior may lead to misidentification of vortices and other flow structures in high-pressure flows. The study reported here was performed in recognition of the need for one or more quantitative criteria for identifying coherent flow structures - especially vortices - from previously generated flow-field data, to complement or supersede the determination of flow structures by visual inspection of instantaneous fields or flow animations. The focus in the study was on correlating visible images of flow features with various quantities computed from flow-field data.

Correlation of HIV protease structure with Indinavir resistance: a data mining and neural networks approach

NASA Astrophysics Data System (ADS)

Draghici, Sorin; Cumberland, Lonnie T., Jr.; Kovari, Ladislau C.

2000-04-01

This paper presents some results of data mining HIV genotypic and structural data. Our aim is to try to relate structural features of HIV enzymes essential to its reproductive abilities to the drug resistance phenomenon. This paper concentrates on the HIV protease enzyme and Indinavir which is one of the FDA approved protease inhibitors. Our starting point was the current list of HIV mutations related to drug resistance. We used the fact that some molecular structures determined through high resolution X-ray crystallography were available for the protease-Indinavir complex. Starting with these structures and the known mutations, we modelled the mutant proteases and studied the pattern of atomic contacts between the protease and the drug. After suitable pre- processing, these patterns have been used as the input of our data mining process. We have used both supervised and unsupervised learning techniques with the aim of understanding the relationship between structural features at a molecular level and resistance to Indinavir. The supervised learning was aimed at predicting IC90 values for arbitrary mutants. The SOFM was aimed at identifying those structural features that are important for drug resistance and discovering a classifier based on such features. We have used validation and cross validation to test the generalization abilities of the learning paradigm we have designed. The straightforward supervised learning was able to learn very successfully but validation results are less than satisfactory. This is due to the insufficient number of patterns in the training set which in turn is due to the scarcity of the available data. The data mining using SOFM was very successful. We have managed to distinguish between resistant and non-resistant mutants using structural features. We have been able to divide all reported HIV mutants into several categories based on their 3- dimensional molecular structures and the pattern of contacts between the mutant protease and Indinavir. Our classifier shows reasonably good prediction performance being able to predict the drug resistance of previously unseen mutants with an accuracy of between 60% and 70%. We believe that this performance can be greatly improved once more data becomes available. The results presented here support the hypothesis that structural features of the molecular structure can be used in antiviral drug treatment selection and drug design.

Observations of fast-moving features in the debris disk of AU Mic on a three-year timescale: Confirmation and new discoveries

NASA Astrophysics Data System (ADS)

Boccaletti, A.; Sezestre, E.; Lagrange, A.-M.; Thébault, P.; Gratton, R.; Langlois, M.; Thalmann, C.; Janson, M.; Delorme, P.; Augereau, J.-C.; Schneider, G.; Milli, J.; Grady, C.; Debes, J.; Kral, Q.; Olofsson, J.; Carson, J.; Maire, A. L.; Henning, T.; Wisniewski, J.; Schlieder, J.; Dominik, C.; Desidera, S.; Ginski, C.; Hines, D.; Ménard, F.; Mouillet, D.; Pawellek, N.; Vigan, A.; Lagadec, E.; Avenhaus, H.; Beuzit, J.-L.; Biller, B.; Bonavita, M.; Bonnefoy, M.; Brandner, W.; Cantalloube, F.; Chauvin, G.; Cheetham, A.; Cudel, M.; Gry, C.; Daemgen, S.; Feldt, M.; Galicher, R.; Girard, J.; Hagelberg, J.; Janin-Potiron, P.; Kasper, M.; Coroller, H. Le; Mesa, D.; Peretti, S.; Perrot, C.; Samland, M.; Sissa, E.; Wildi, F.; Zurlo, A.; Rochat, S.; Stadler, E.; Gluck, L.; Origné, A.; Llored, M.; Baudoz, P.; Rousset, G.; Martinez, P.; Rigal, F.

2018-06-01

Context. The nearby and young M star AU Mic is surrounded by a debris disk in which we previously identified a series of large-scale arch-like structures that have never been seen before in any other debris disk and that move outward at high velocities. Aims: We initiated a monitoring program with the following objectives: (1) track the location of the structures and better constrain their projected speeds, (2) search for new features emerging closer in, and ultimately (3) understand the mechanism responsible for the motion and production of the disk features. Methods: AU Mic was observed at 11 different epochs between August 2014 and October 2017 with the IR camera and spectrograph of SPHERE. These high-contrast imaging data were processed with a variety of angular, spectral, and polarimetric differential imaging techniques to reveal the faintest structures in the disk. We measured the projected separations of the features in a systematic way for all epochs. We also applied the very same measurements to older observations from the Hubble Space Telescope (HST) with the visible cameras STIS and ACS. Results: The main outcomes of this work are (1) the recovery of the five southeastern broad arch-like structures we identified in our first study, and confirmation of their fast motion (projected speed in the range 4-12 km s-1); (2) the confirmation that the very first structures observed in 2004 with ACS are indeed connected to those observed later with STIS and now SPHERE; (3) the discovery of two new very compact structures at the northwest side of the disk (at 0.40'' and 0.55'' in May 2015) that move to the southeast at low speed; and (4) the identification of a new arch-like structure that might be emerging at the southeast side at about 0.4'' from the star (as of May 2016). Conclusions: Although the exquisite sensitivity of SPHERE allows one to follow the evolution not only of the projected separation, but also of the specific morphology of each individual feature, it remains difficult to distinguish between possible dynamical scenarios that may explain the observations. Understanding the exact origin of these features, the way they are generated, and their evolution over time is certainly a significant challenge in the context of planetary system formation around M stars. Based on data collected at the European Southern Observatory, Chile under programs 060.A-9249, 095.C-0298, 096.C-0625, 097.C-0865, 097.C-0813, 598.C-0359.A movie associated to Fig. 6 is available at http://https://www.aanda.org

Machine-learned cluster identification in high-dimensional data.

PubMed

Ultsch, Alfred; Lötsch, Jörn

2017-02-01

High-dimensional biomedical data are frequently clustered to identify subgroup structures pointing at distinct disease subtypes. It is crucial that the used cluster algorithm works correctly. However, by imposing a predefined shape on the clusters, classical algorithms occasionally suggest a cluster structure in homogenously distributed data or assign data points to incorrect clusters. We analyzed whether this can be avoided by using emergent self-organizing feature maps (ESOM). Data sets with different degrees of complexity were submitted to ESOM analysis with large numbers of neurons, using an interactive R-based bioinformatics tool. On top of the trained ESOM the distance structure in the high dimensional feature space was visualized in the form of a so-called U-matrix. Clustering results were compared with those provided by classical common cluster algorithms including single linkage, Ward and k-means. Ward clustering imposed cluster structures on cluster-less "golf ball", "cuboid" and "S-shaped" data sets that contained no structure at all (random data). Ward clustering also imposed structures on permuted real world data sets. By contrast, the ESOM/U-matrix approach correctly found that these data contain no cluster structure. However, ESOM/U-matrix was correct in identifying clusters in biomedical data truly containing subgroups. It was always correct in cluster structure identification in further canonical artificial data. Using intentionally simple data sets, it is shown that popular clustering algorithms typically used for biomedical data sets may fail to cluster data correctly, suggesting that they are also likely to perform erroneously on high dimensional biomedical data. The present analyses emphasized that generally established classical hierarchical clustering algorithms carry a considerable tendency to produce erroneous results. By contrast, unsupervised machine-learned analysis of cluster structures, applied using the ESOM/U-matrix method, is a viable, unbiased method to identify true clusters in the high-dimensional space of complex data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Machine learning for autonomous crystal structure identification.

PubMed

Reinhart, Wesley F; Long, Andrew W; Howard, Michael P; Ferguson, Andrew L; Panagiotopoulos, Athanassios Z

2017-07-21

We present a machine learning technique to discover and distinguish relevant ordered structures from molecular simulation snapshots or particle tracking data. Unlike other popular methods for structural identification, our technique requires no a priori description of the target structures. Instead, we use nonlinear manifold learning to infer structural relationships between particles according to the topology of their local environment. This graph-based approach yields unbiased structural information which allows us to quantify the crystalline character of particles near defects, grain boundaries, and interfaces. We demonstrate the method by classifying particles in a simulation of colloidal crystallization, and show that our method identifies structural features that are missed by standard techniques.

Atomic structures of corkscrew-forming segments of SOD1 reveal varied oligomer conformations.

PubMed

Sangwan, Smriti; Sawaya, Michael R; Murray, Kevin A; Hughes, Michael P; Eisenberg, David S

2018-02-17

The aggregation cascade of disease-related amyloidogenic proteins, terminating in insoluble amyloid fibrils, involves intermediate oligomeric states. The structural and biochemical details of these oligomers have been largely unknown. Here we report crystal structures of variants of the cytotoxic oligomer-forming segment residues 28-38 of the ALS-linked protein, SOD1. The crystal structures reveal three different architectures: corkscrew oligomeric structure, nontwisting curved sheet structure and a steric zipper proto-filament structure. Our work highlights the polymorphism of the segment 28-38 of SOD1 and identifies the molecular features of amyloidogenic entities. © 2018 The Protein Society.

Indel PDB: a database of structural insertions and deletions derived from sequence alignments of closely related proteins.

PubMed

Hsing, Michael; Cherkasov, Artem

2008-06-25

Insertions and deletions (indels) represent a common type of sequence variations, which are less studied and pose many important biological questions. Recent research has shown that the presence of sizable indels in protein sequences may be indicative of protein essentiality and their role in protein interaction networks. Examples of utilization of indels for structure-based drug design have also been recently demonstrated. Nonetheless many structural and functional characteristics of indels remain less researched or unknown. We have created a web-based resource, Indel PDB, representing a structural database of insertions/deletions identified from the sequence alignments of highly similar proteins found in the Protein Data Bank (PDB). Indel PDB utilized large amounts of available structural information to characterize 1-, 2- and 3-dimensional features of indel sites. Indel PDB contains 117,266 non-redundant indel sites extracted from 11,294 indel-containing proteins. Unlike loop databases, Indel PDB features more indel sequences with secondary structures including alpha-helices and beta-sheets in addition to loops. The insertion fragments have been characterized by their sequences, lengths, locations, secondary structure composition, solvent accessibility, protein domain association and three dimensional structures. By utilizing the data available in Indel PDB, we have studied and presented here several sequence and structural features of indels. We anticipate that Indel PDB will not only enable future functional studies of indels, but will also assist protein modeling efforts and identification of indel-directed drug binding sites.

Effects of contact network structure on epidemic transmission trees: implications for data required to estimate network structure.

PubMed

Carnegie, Nicole Bohme

2018-01-30

Understanding the dynamics of disease spread is key to developing effective interventions to control or prevent an epidemic. The structure of the network of contacts over which the disease spreads has been shown to have a strong influence on the outcome of the epidemic, but an open question remains as to whether it is possible to estimate contact network features from data collected in an epidemic. The approach taken in this paper is to examine the distributions of epidemic outcomes arising from epidemics on networks with particular structural features to assess whether that structure could be measured from epidemic data and what other constraints might be needed to make the problem identifiable. To this end, we vary the network size, mean degree, and transmissibility of the pathogen, as well as the network feature of interest: clustering, degree assortativity, or attribute-based preferential mixing. We record several standard measures of the size and spread of the epidemic, as well as measures that describe the shape of the transmission tree in order to ascertain whether there are detectable signals in the final data from the outbreak. The results suggest that there is potential to estimate contact network features from transmission trees or pure epidemic data, particularly for diseases with high transmissibility or for which the relevant contact network is of low mean degree. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Advances in the floral structural characterization of the major subclades of Malpighiales, one of the largest orders of flowering plants

PubMed Central

Endress, Peter K.; Davis, Charles C.; Matthews, Merran L.

2013-01-01

Background and Aims Malpighiales are one of the largest angiosperm orders and have undergone radical systematic restructuring based on molecular phylogenetic studies. The clade has been recalcitrant to molecular phylogenetic reconstruction, but has become much more resolved at the suprafamilial level. It now contains so many newly identified clades that there is an urgent need for comparative studies to understand their structure, biology and evolution. This is especially true because the order contains a disproportionally large diversity of rain forest species and includes numerous agriculturally important plants. This study is a first broad systematic step in this endeavour. It focuses on a comparative structural overview of the flowers across all recently identified suprafamilial clades of Malpighiales, and points towards areas that desperately need attention. Methods The phylogenetic comparative analysis of floral structure for the order is based on our previously published studies on four suprafamilial clades of Malpighiales, including also four related rosid orders (Celastrales, Crossosomatales, Cucurbitales, Oxalidales). In addition, the results are compiled from a survey of over 3000 publications on macrosystematics, floral structure and embryology across all orders of the core eudicots. Key Results Most new suprafamilial clades within Malpighiales are well supported by floral structural features. Inner morphological structures of the gynoecium (i.e. stigmatic lobes, inner shape of the locules, placentation, presence of obturators) and ovules (i.e. structure of the nucellus, thickness of the integuments, presence of vascular bundles in the integuments, presence of an endothelium in the inner integument) appear to be especially suitable for characterizing suprafamilial clades within Malpighiales. Conclusions Although the current phylogenetic reconstruction of Malpighiales is much improved compared with earlier versions, it is incomplete, and further focused phylogenetic and morphological studies are needed. Once all major subclades of Malpighiales are elucidated, more in-depth studies on promising structural features can be conducted. In addition, once the phylogenetic tree of Malpighiales, including closely related orders, is more fully resolved, character optimization studies will be possible to reconstruct evolution of structural and biological features within the order. PMID:23486341

MSSA de-noising of horizon time structure to improve the curvature attribute analysis

NASA Astrophysics Data System (ADS)

Tiwari, R. K.; Rekapalli, R.; Vedanti, N.

2017-12-01

Although the seismic attributes are useful for identifying sub-surface structural features like faults, fractures, lineaments and sharp stratigraphy etc., the different kinds of noises arising from unknown physical sources during the data acquisition and processing creates acute problems in physical interpretation of complex crustal structures. Hence, we propose to study effect of noise on curvature attribute analysis of seismic time structure data. We propose here Multichannel Singular Spectrum Analysis (MSSA) de-noising algorithm as a pre filtering scheme to reduce effect of noise. To demonstrate the procedure, first, we compute the most positive and negative curvature on a synthetic time structure with surface features resembling anticlines, synclines and faults and then adding the known percentage of noise. We noticed that the curvatures estimated from the noisy data reveal considerable deviations from the curvature of pure synthetic data. This suggests that there is a strong impact of noise on the curvature estimates. Further, we have employed 2D median filter and MSSA methods to filter the noisy time structure and then computed the curvatures. The comparisons of curvatures estimated from de-noised data suggest that the results obtained from MSSA de-noised data match well with the curvatures of pure synthetic data. Finally, we present an example of real data analysis from Utsira Top (UT) horizon of Southern Viking Graben, Norway to identify the time-lapse changes in UT horizon after CO2 injection. We applied the MSSA de-noising algorithm on UT horizon time structure and amplitude data of pre and post CO2 injection. Our analyses suggest modest but clearly visible, structural changes in the UT horizon after CO2 injection at a few locations, which seem to be associated with the locations of change in seismic amplitudes. Thus, the results from both the synthetic and real field data suggest that the MSSA based de-noising algorithm is robust for filtering the horizon time structures for accurate curvature attributes analysis and better interpretation of structural changes in geological features. Key Words: Curvature attributes, MSSA, Seismic Horizon, 2D-median filter, Utsira Horizon.

Automated real-time search and analysis algorithms for a non-contact 3D profiling system

NASA Astrophysics Data System (ADS)

Haynes, Mark; Wu, Chih-Hang John; Beck, B. Terry; Peterman, Robert J.

2013-04-01

The purpose of this research is to develop a new means of identifying and extracting geometrical feature statistics from a non-contact precision-measurement 3D profilometer. Autonomous algorithms have been developed to search through large-scale Cartesian point clouds to identify and extract geometrical features. These algorithms are developed with the intent of providing real-time production quality control of cold-rolled steel wires. The steel wires in question are prestressing steel reinforcement wires for concrete members. The geometry of the wire is critical in the performance of the overall concrete structure. For this research a custom 3D non-contact profilometry system has been developed that utilizes laser displacement sensors for submicron resolution surface profiling. Optimizations in the control and sensory system allow for data points to be collected at up to an approximate 400,000 points per second. In order to achieve geometrical feature extraction and tolerancing with this large volume of data, the algorithms employed are optimized for parsing large data quantities. The methods used provide a unique means of maintaining high resolution data of the surface profiles while keeping algorithm running times within practical bounds for industrial application. By a combination of regional sampling, iterative search, spatial filtering, frequency filtering, spatial clustering, and template matching a robust feature identification method has been developed. These algorithms provide an autonomous means of verifying tolerances in geometrical features. The key method of identifying the features is through a combination of downhill simplex and geometrical feature templates. By performing downhill simplex through several procedural programming layers of different search and filtering techniques, very specific geometrical features can be identified within the point cloud and analyzed for proper tolerancing. Being able to perform this quality control in real time provides significant opportunities in cost savings in both equipment protection and waste minimization.

Iron-absorption band analysis for the discrimination of iron-rich zones

NASA Technical Reports Server (NTRS)

Rowan, L. C. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Study has concentrated on the two primary aspects of the project, structural analysis through evaluation of lineaments and circular features and spectral analyses through digital computer-processing techniques. Several previously unrecognized lineaments are mapped which may be the surface manifestations of major fault or fracture zones. Two of these, the Walker Lane and the Midas Trench lineament system, transect the predominantly NNE-NNW-trending moutain ranges for more than 500 km. Correlation of major lineaments with productive mining districts implies a genetic relationship, the 50 circular or elliptical features delineated suggest a related role for Tertiary volcanism. Color-ratio composites have been used to identify limonitic zones and to discriminate mafic and felsic rock by combing diazo color transparencies of three different ratios. EROS Data Center scene identification number for color composite in this report is ER 1 CC 500. Refinement of enhancement procedures for the ratio images is progressing. Fieldwork in coordination with both spectral and structural analyses is underway.

The Mysterious Bar of the Large Magellanic Cloud: What Is It?

NASA Astrophysics Data System (ADS)

Subramaniam, Annapurni; Subramanian, Smitha

2009-09-01

The bar of the Large Magellanic Cloud (LMC) is one of the prominent, but controversial, features regarding its location with respect to the disk of the LMC. In order to study the relative location of the bar with respect to the disk, we present the high-resolution map of the structure across the LMC. We used the reddening corrected mean magnitudes (I 0) of red clump (RC) stars from the OGLE III catalog to map the relative variation in distance (vertical structure) or variation in RC population across the LMC. The bar does not appear as an identifiable vertical feature in the map, as there is no difference in I 0 values between the bar and the disk regions. We conclude that the LMC bar is very much part of the disk (within 0.02 mag), located in the plane of the disk and not a separate component. We identify warps or variation in RC population with increase in radial distance.

Hit to lead account of the discovery of a new class of inhibitors of Pim kinases and crystallographic studies revealing an unusual kinase binding mode.

PubMed

Qian, Kevin; Wang, Lian; Cywin, Charles L; Farmer, Bennett T; Hickey, Eugene; Homon, Carol; Jakes, Scott; Kashem, Mohammed A; Lee, George; Leonard, Scott; Li, Jun; Magboo, Ronald; Mao, Wang; Pack, Edward; Peng, Charlene; Prokopowicz, Anthony; Welzel, Morgan; Wolak, John; Morwick, Tina

2009-04-09

A series of inhibitors of Pim-2 kinase identified by high-throughput screening is described. Details of the hit validation and lead generation process and structure-activity relationship (SAR) studies are presented. Disclosure of an unconventional binding mode for 1, as revealed by X-ray crystallography using the highly homologous Pim-1 protein, is also presented, and observed binding features are shown to correlate with the Pim-2 SAR. While highly selective within the kinase family, the series shows similar potency for both Pim-1 and Pim-2, which was expected on the basis of homology, but unusual in light of reports in the literature documenting a bias for Pim-1. A rationale for these observations based on Pim-1 and Pim-2 K(M(ATP)) values is suggested. Some interesting cross reactivity with casein kinase-2 was also identified, and structural features which may contribute to the association are discussed.

Towards the Improved Discovery and Design of Functional Peptides: Common Features of Diverse Classes Permit Generalized Prediction of Bioactivity

PubMed Central

Mooney, Catherine; Haslam, Niall J.; Pollastri, Gianluca; Shields, Denis C.

2012-01-01

The conventional wisdom is that certain classes of bioactive peptides have specific structural features that endow their particular functions. Accordingly, predictions of bioactivity have focused on particular subgroups, such as antimicrobial peptides. We hypothesized that bioactive peptides may share more general features, and assessed this by contrasting the predictive power of existing antimicrobial predictors as well as a novel general predictor, PeptideRanker, across different classes of peptides. We observed that existing antimicrobial predictors had reasonable predictive power to identify peptides of certain other classes i.e. toxin and venom peptides. We trained two general predictors of peptide bioactivity, one focused on short peptides (4–20 amino acids) and one focused on long peptides ( amino acids). These general predictors had performance that was typically as good as, or better than, that of specific predictors. We noted some striking differences in the features of short peptide and long peptide predictions, in particular, high scoring short peptides favour phenylalanine. This is consistent with the hypothesis that short and long peptides have different functional constraints, perhaps reflecting the difficulty for typical short peptides in supporting independent tertiary structure. We conclude that there are general shared features of bioactive peptides across different functional classes, indicating that computational prediction may accelerate the discovery of novel bioactive peptides and aid in the improved design of existing peptides, across many functional classes. An implementation of the predictive method, PeptideRanker, may be used to identify among a set of peptides those that may be more likely to be bioactive. PMID:23056189

A Review of the Structural Characteristics of Family Meals with Children in the United States12

PubMed Central

McCullough, Mary Beth; Robson, Shannon M; Stark, Lori J

2016-01-01

Family meals are associated with a range of positive outcomes among children and adolescents. There is inconsistency, however, in the way in which studies have defined and measured family meals. Therefore, a systematic review of the literature was conducted to determine how studies describe family meals with the use of structural characteristics. The current review focused on studies in the United States that included children ages 2–18 y. A total of 33 studies were identified that characterized family meals with the use of ≥1 of the following structural features: frequency or mean number of family meals per week, length of family meal, people present at meal, and where meals occurred. No study characterized family meals by using all 4 family meal features, whereas most studies (81%) characterized family meals by using frequency or mean number of meals per week. Findings not only provide an initial understanding of the structural features used to define family meals but also point to the importance of developing a more comprehensive, sensitive assessment that can accurately capture the complex and multidimensional nature of family meals. PMID:27422500

A Review of the Structural Characteristics of Family Meals with Children in the United States.

PubMed

McCullough, Mary Beth; Robson, Shannon M; Stark, Lori J

2016-07-01

Family meals are associated with a range of positive outcomes among children and adolescents. There is inconsistency, however, in the way in which studies have defined and measured family meals. Therefore, a systematic review of the literature was conducted to determine how studies describe family meals with the use of structural characteristics. The current review focused on studies in the United States that included children ages 2-18 y. A total of 33 studies were identified that characterized family meals with the use of ≥1 of the following structural features: frequency or mean number of family meals per week, length of family meal, people present at meal, and where meals occurred. No study characterized family meals by using all 4 family meal features, whereas most studies (81%) characterized family meals by using frequency or mean number of meals per week. Findings not only provide an initial understanding of the structural features used to define family meals but also point to the importance of developing a more comprehensive, sensitive assessment that can accurately capture the complex and multidimensional nature of family meals. © 2016 American Society for Nutrition.

Mariner 9 photographs of small-scale volcanic structures on Mars

NASA Technical Reports Server (NTRS)

Greeley, R.

1972-01-01

Surface features on the flanks of Martian shield volcanoes photographed by Mariner 9 are identified as lava flow channels, rift zones, and partly collapsed lava tubes by comparisons with similar structures on the flanks of Mauna Loa shield volcano, Hawaii. From these identifications, the composition of the Martian lava flows is interpreted to be basaltic, with viscosities ranging from those of fluid pahoehoe to more viscous aa.

Identification of Chemical Features Linked to Thyroperoxidase ...

EPA Pesticide Factsheets

Disruption of maternal serum thyroid hormone (TH) adversely affects fetal neurodevelopment. Therefore, assay development within the US EPA ToxCast program is ongoing to enable screening for chemicals that may disrupt TH, in support of the Endocrine Disruption Screening Program (EDSP21). The AUR-TPO assay was recently developed to screen >1,000 ToxCast chemicals for potential thyroperoxidase (TPO) inhibition activity. TPO is critical for TH synthesis and is a known target of thyroid-disrupting chemicals. The bioactivity results from the AUR-TPO assay were used to identify chemical substructures associated with in vitro TPO inhibition. Substructure profiles were generated for each chemical in the ToxCast test set using the publicly-available ToxPrint 2.0 chemotypes. Chemotypes enriched among the putative TPO inhibitors were identified using a cumulative hypergeometric probability (p < 0.01). Of the total 729 chemotypes evaluated, 31 were overrepresented among TPO inhibitors. Examination of those 31 chemotypes revealed four basic pharmacophores that accounted for 70% of the ToxCast chemicals active in the AUR-TPO assay: aromatic alcohols, aromatic amines, thiocarbonyls and phosphothioates. Chemico-structural analysis of AUR-TPO screening results enabled the identification of chemical features that likely drive TPO inhibition in the AUR-TPO assay. This highlights the potential to identify thyroid-disrupting chemicals in silico using structural alerts identified by

Characterization of the Cretaceous aquifer structure of the Meskala region of the Essaouira Basin, Morocco

USGS Publications Warehouse

Hanich, L.; Zouhri, L.; Dinger, J.

2011-01-01

The aquifer of early Cretaceous age in the Meskala region of the Essaouira Basin is defined by interpretation of geological drilling data of oil and hydrogeological wells, field measurement and analysis of in situ fracture orientations, and the application of a morphostructural method to identify lineaments. These analyzes are used to develop a stratigraphic-structural model of the aquifer delimited by fault zones of two principal orientations: NNE and WNW. These fault zones define fault blocks that range in area from 4 to 150km2. These blocks correspond either to elevated zones (horsts) or depressed zones (grabens). This structural setting with faults blocks of Meskala region is in accordance with the structure of the whole Essaouira Basin. Fault zones disrupt the continuity of the aquifer throughout the study area, create recharge and discharge zones, and create dip to the units from approximately 10?? to near vertical in various orientations. Fracture measurements and morphometric-lineament analyzes help to identify unmapped faults, and represent features important to groundwater hydraulics and water quality within fault blocks. The above geologic features will enable a better understanding of the behaviour and hydro-geo-chemical and hydrodynamics of groundwater in the Meskala aquifer. ?? 2010 Elsevier Ltd.

Knowledge-based fragment binding prediction.

PubMed

Tang, Grace W; Altman, Russ B

2014-04-01

Target-based drug discovery must assess many drug-like compounds for potential activity. Focusing on low-molecular-weight compounds (fragments) can dramatically reduce the chemical search space. However, approaches for determining protein-fragment interactions have limitations. Experimental assays are time-consuming, expensive, and not always applicable. At the same time, computational approaches using physics-based methods have limited accuracy. With increasing high-resolution structural data for protein-ligand complexes, there is now an opportunity for data-driven approaches to fragment binding prediction. We present FragFEATURE, a machine learning approach to predict small molecule fragments preferred by a target protein structure. We first create a knowledge base of protein structural environments annotated with the small molecule substructures they bind. These substructures have low-molecular weight and serve as a proxy for fragments. FragFEATURE then compares the structural environments within a target protein to those in the knowledge base to retrieve statistically preferred fragments. It merges information across diverse ligands with shared substructures to generate predictions. Our results demonstrate FragFEATURE's ability to rediscover fragments corresponding to the ligand bound with 74% precision and 82% recall on average. For many protein targets, it identifies high scoring fragments that are substructures of known inhibitors. FragFEATURE thus predicts fragments that can serve as inputs to fragment-based drug design or serve as refinement criteria for creating target-specific compound libraries for experimental or computational screening.

Knowledge-based Fragment Binding Prediction

PubMed Central

Tang, Grace W.; Altman, Russ B.

2014-01-01

Target-based drug discovery must assess many drug-like compounds for potential activity. Focusing on low-molecular-weight compounds (fragments) can dramatically reduce the chemical search space. However, approaches for determining protein-fragment interactions have limitations. Experimental assays are time-consuming, expensive, and not always applicable. At the same time, computational approaches using physics-based methods have limited accuracy. With increasing high-resolution structural data for protein-ligand complexes, there is now an opportunity for data-driven approaches to fragment binding prediction. We present FragFEATURE, a machine learning approach to predict small molecule fragments preferred by a target protein structure. We first create a knowledge base of protein structural environments annotated with the small molecule substructures they bind. These substructures have low-molecular weight and serve as a proxy for fragments. FragFEATURE then compares the structural environments within a target protein to those in the knowledge base to retrieve statistically preferred fragments. It merges information across diverse ligands with shared substructures to generate predictions. Our results demonstrate FragFEATURE's ability to rediscover fragments corresponding to the ligand bound with 74% precision and 82% recall on average. For many protein targets, it identifies high scoring fragments that are substructures of known inhibitors. FragFEATURE thus predicts fragments that can serve as inputs to fragment-based drug design or serve as refinement criteria for creating target-specific compound libraries for experimental or computational screening. PMID:24762971

Application of PALSAR-2 Remote Sensing Data for Landslide Hazard Mapping in Kelantan River Basin, Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Beiranvand Pour, Amin; Hashim, Mazlan

2016-06-01

Yearly, several landslides ensued during heavy monsoons rainfall in Kelantan river basin, peninsular Malaysia, which are obviously connected to geological structures and topographical features of the region. In this study, the recently launched Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) onboard the Advanced Land Observing Satellite-2 (ALOS-2), remote sensing data were used to map geological structural and topographical features in the Kelantan river basin for identification of high potential risk and susceptible zones for landslides. Adaptive Local Sigma filter was selected and applied to accomplish speckle reduction and preserving both edges and features in PALSAR-2 fine mode observation images. Different polarization images were integrated to enhance geological structures. Additionally, directional filters were applied to the PALSAR-2 Local Sigma resultant image for edge enhancement and detailed identification of linear features. Several faults, drainage patterns and lithological contact layers were identified at regional scale. In order to assess the results, fieldwork and GPS survey were conducted in the landslide affected zones in the Kelantan river basin. Results demonstrate the most of the landslides were associated with N-S, NNW-SSE and NE-SW trending faults, angulated drainage pattern and metamorphic and Quaternary units. Consequently, structural and topographical geology maps were produced for Kelantan river basin using PALSAR-2 data, which could be broadly applicable for landslide hazard mapping.

An evaluation of applicability of seismic refraction method in identifying shallow archaeological features A case study at archaeological site

NASA Astrophysics Data System (ADS)

Jahangardi, Morteza; Hafezi Moghaddas, Naser; Keivan Hosseini, Sayyed; Garazhian, Omran

2015-04-01

We applied the seismic refraction method at archaeological site, Tepe Damghani located in Sabzevar, NE of Iran, in order to determine the structures of archaeological interests. This pre-historical site has special conditions with respect to geographical location and geomorphological setting, so it is an urban archaeological site, and in recent years it has been used as an agricultural field. In spring and summer of 2012, the third season of archaeological excavation was carried out. Test trenches of excavations in this site revealed that cultural layers were often disturbed adversely due to human activities such as farming and road construction in recent years. Conditions of archaeological cultural layers in southern and eastern parts of Tepe are slightly better, for instance, in test trench 3×3 m²1S03, third test trench excavated in the southern part of Tepe, an adobe in situ architectural structure was discovered that likely belongs to cultural features of a complex with 5 graves. After conclusion of the third season of archaeological excavation, all of the test trenches were filled with the same soil of excavated test trenches. Seismic refraction method was applied with12 channels of P geophones in three lines with a geophone interval of 0.5 meter and a 1.5 meter distance between profiles on test trench 1S03. The goal of this operation was evaluation of applicability of seismic method in identification of archaeological features, especially adobe wall structures. Processing of seismic data was done with the seismic software, SiesImager. Results were presented in the form of seismic section for every profile, so that identification of adobe wall structures was achieved hardly. This could be due to that adobe wall had been built with the same materials of the natural surrounding earth. Thus, there is a low contrast and it has an inappropriate effect on seismic processing and identifying of archaeological features. Hence the result could be that application of the seismic method in order to determine the archaeological features, having the same conditions, is not affordable and efficient in comparison to GPR or magnetic methods which yield more desirable results.

Interface, information, interaction: a narrative review of design and functional requirements for clinical decision support.

PubMed

Miller, Kristen; Mosby, Danielle; Capan, Muge; Kowalski, Rebecca; Ratwani, Raj; Noaiseh, Yaman; Kraft, Rachel; Schwartz, Sanford; Weintraub, William S; Arnold, Ryan

2018-05-01

Provider acceptance and associated patient outcomes are widely discussed in the evaluation of clinical decision support systems (CDSSs), but critical design criteria for tools have generally been overlooked. The objective of this work is to inform electronic health record alert optimization and clinical practice workflow by identifying, compiling, and reporting design recommendations for CDSS to support the efficient, effective, and timely delivery of high-quality care. A narrative review was conducted from 2000 to 2016 in PubMed and The Journal of Human Factors and Ergonomics Society to identify papers that discussed/recommended design features of CDSSs that are associated with the success of these systems. Fourteen papers were included as meeting the criteria and were found to have a total of 42 unique recommendations; 11 were classified as interface features, 10 as information features, and 21 as interaction features. Features are defined and described, providing actionable guidance that can be applied to CDSS development and policy. To our knowledge, no reviews have been completed that discuss/recommend design features of CDSS at this scale, and thus we found that this was important for the body of literature. The recommendations identified in this narrative review will help to optimize design, organization, management, presentation, and utilization of information through presentation, content, and function. The designation of 3 categories (interface, information, and interaction) should be further evaluated to determine the critical importance of the categories. Future work will determine how to prioritize them with limited resources for designers and developers in order to maximize the clinical utility of CDSS. This review will expand the field of knowledge and provide a novel organization structure to identify key recommendations for CDSS.

Effect of Proximity of Features on the Damage Threshold During Submicron Additive Manufacturing Via Two-Photon Polymerization

DOE PAGES

Saha, Sourabh K.; Divin, Chuck; Cuadra, Jefferson A.; ...

2017-05-12

Two-photon polymerization (TPP) is a laser writing process that enables fabrication of millimeter scale three-dimensional (3D) structures with submicron features. In TPP, writing is achieved via nonlinear two-photon absorption that occurs at high laser intensities. Thus, it is essential to carefully select the incident power to prevent laser damage during polymerization. Currently, the feasible range of laser power is identified by writing small test patterns at varying power levels. Here in this paper, we demonstrate that the results of these tests cannot be generalized, because the damage threshold power depends on the proximity of features and reduces by as muchmore » as 47% for overlapping features. We have identified that this reduction occurs primarily due to an increase in the single-photon absorptivity of the resin after curing. We have captured the damage from proximity effects via X-ray 3D computed tomography (CT) images of a non-homogenous part that has varying feature density. Part damage manifests as internal spherical voids that arise due to boiling of the resist. We have empirically quantified this proximity effect by identifying the damage threshold power at different writing speeds and feature overlap spacings. In addition, we present a first-order analytical model that captures the scaling of this proximity effect. Based on this model and the experiments, we have identified that the proximity effect is more significant at high writing speeds; therefore, it adversely affects the scalability of manufacturing. The scaling laws and the empirical data generated here can be used to select the appropriate TPP writing parameters.« less

Effect of Proximity of Features on the Damage Threshold During Submicron Additive Manufacturing Via Two-Photon Polymerization

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

Saha, Sourabh K.; Divin, Chuck; Cuadra, Jefferson A.

Two-photon polymerization (TPP) is a laser writing process that enables fabrication of millimeter scale three-dimensional (3D) structures with submicron features. In TPP, writing is achieved via nonlinear two-photon absorption that occurs at high laser intensities. Thus, it is essential to carefully select the incident power to prevent laser damage during polymerization. Currently, the feasible range of laser power is identified by writing small test patterns at varying power levels. Here in this paper, we demonstrate that the results of these tests cannot be generalized, because the damage threshold power depends on the proximity of features and reduces by as muchmore » as 47% for overlapping features. We have identified that this reduction occurs primarily due to an increase in the single-photon absorptivity of the resin after curing. We have captured the damage from proximity effects via X-ray 3D computed tomography (CT) images of a non-homogenous part that has varying feature density. Part damage manifests as internal spherical voids that arise due to boiling of the resist. We have empirically quantified this proximity effect by identifying the damage threshold power at different writing speeds and feature overlap spacings. In addition, we present a first-order analytical model that captures the scaling of this proximity effect. Based on this model and the experiments, we have identified that the proximity effect is more significant at high writing speeds; therefore, it adversely affects the scalability of manufacturing. The scaling laws and the empirical data generated here can be used to select the appropriate TPP writing parameters.« less

Distributed acoustic cues for caller identity in macaque vocalization.

PubMed

Fukushima, Makoto; Doyle, Alex M; Mullarkey, Matthew P; Mishkin, Mortimer; Averbeck, Bruno B

2015-12-01

Individual primates can be identified by the sound of their voice. Macaques have demonstrated an ability to discern conspecific identity from a harmonically structured 'coo' call. Voice recognition presumably requires the integrated perception of multiple acoustic features. However, it is unclear how this is achieved, given considerable variability across utterances. Specifically, the extent to which information about caller identity is distributed across multiple features remains elusive. We examined these issues by recording and analysing a large sample of calls from eight macaques. Single acoustic features, including fundamental frequency, duration and Weiner entropy, were informative but unreliable for the statistical classification of caller identity. A combination of multiple features, however, allowed for highly accurate caller identification. A regularized classifier that learned to identify callers from the modulation power spectrum of calls found that specific regions of spectral-temporal modulation were informative for caller identification. These ranges are related to acoustic features such as the call's fundamental frequency and FM sweep direction. We further found that the low-frequency spectrotemporal modulation component contained an indexical cue of the caller body size. Thus, cues for caller identity are distributed across identifiable spectrotemporal components corresponding to laryngeal and supralaryngeal components of vocalizations, and the integration of those cues can enable highly reliable caller identification. Our results demonstrate a clear acoustic basis by which individual macaque vocalizations can be recognized.

Distributed acoustic cues for caller identity in macaque vocalization

PubMed Central

Doyle, Alex M.; Mullarkey, Matthew P.; Mishkin, Mortimer; Averbeck, Bruno B.

2015-01-01

Individual primates can be identified by the sound of their voice. Macaques have demonstrated an ability to discern conspecific identity from a harmonically structured ‘coo’ call. Voice recognition presumably requires the integrated perception of multiple acoustic features. However, it is unclear how this is achieved, given considerable variability across utterances. Specifically, the extent to which information about caller identity is distributed across multiple features remains elusive. We examined these issues by recording and analysing a large sample of calls from eight macaques. Single acoustic features, including fundamental frequency, duration and Weiner entropy, were informative but unreliable for the statistical classification of caller identity. A combination of multiple features, however, allowed for highly accurate caller identification. A regularized classifier that learned to identify callers from the modulation power spectrum of calls found that specific regions of spectral–temporal modulation were informative for caller identification. These ranges are related to acoustic features such as the call’s fundamental frequency and FM sweep direction. We further found that the low-frequency spectrotemporal modulation component contained an indexical cue of the caller body size. Thus, cues for caller identity are distributed across identifiable spectrotemporal components corresponding to laryngeal and supralaryngeal components of vocalizations, and the integration of those cues can enable highly reliable caller identification. Our results demonstrate a clear acoustic basis by which individual macaque vocalizations can be recognized. PMID:27019727

Hand Motion Classification Using a Multi-Channel Surface Electromyography Sensor

PubMed Central

Tang, Xueyan; Liu, Yunhui; Lv, Congyi; Sun, Dong

2012-01-01

The human hand has multiple degrees of freedom (DOF) for achieving high-dexterity motions. Identifying and replicating human hand motions are necessary to perform precise and delicate operations in many applications, such as haptic applications. Surface electromyography (sEMG) sensors are a low-cost method for identifying hand motions, in addition to the conventional methods that use data gloves and vision detection. The identification of multiple hand motions is challenging because the error rate typically increases significantly with the addition of more hand motions. Thus, the current study proposes two new methods for feature extraction to solve the problem above. The first method is the extraction of the energy ratio features in the time-domain, which are robust and invariant to motion forces and speeds for the same gesture. The second method is the extraction of the concordance correlation features that describe the relationship between every two channels of the multi-channel sEMG sensor system. The concordance correlation features of a multi-channel sEMG sensor system were shown to provide a vast amount of useful information for identification. Furthermore, a new cascaded-structure classifier is also proposed, in which 11 types of hand gestures can be identified accurately using the newly defined features. Experimental results show that the success rate for the identification of the 11 gestures is significantly high. PMID:22438703

Hand motion classification using a multi-channel surface electromyography sensor.

PubMed

Tang, Xueyan; Liu, Yunhui; Lv, Congyi; Sun, Dong

2012-01-01

The human hand has multiple degrees of freedom (DOF) for achieving high-dexterity motions. Identifying and replicating human hand motions are necessary to perform precise and delicate operations in many applications, such as haptic applications. Surface electromyography (sEMG) sensors are a low-cost method for identifying hand motions, in addition to the conventional methods that use data gloves and vision detection. The identification of multiple hand motions is challenging because the error rate typically increases significantly with the addition of more hand motions. Thus, the current study proposes two new methods for feature extraction to solve the problem above. The first method is the extraction of the energy ratio features in the time-domain, which are robust and invariant to motion forces and speeds for the same gesture. The second method is the extraction of the concordance correlation features that describe the relationship between every two channels of the multi-channel sEMG sensor system. The concordance correlation features of a multi-channel sEMG sensor system were shown to provide a vast amount of useful information for identification. Furthermore, a new cascaded-structure classifier is also proposed, in which 11 types of hand gestures can be identified accurately using the newly defined features. Experimental results show that the success rate for the identification of the 11 gestures is significantly high.

A novel approach to internal crown characterization for coniferous tree species classification

NASA Astrophysics Data System (ADS)

Harikumar, A.; Bovolo, F.; Bruzzone, L.

2016-10-01

The knowledge about individual trees in forest is highly beneficial in forest management. High density small foot- print multi-return airborne Light Detection and Ranging (LiDAR) data can provide a very accurate information about the structural properties of individual trees in forests. Every tree species has a unique set of crown structural characteristics that can be used for tree species classification. In this paper, we use both the internal and external crown structural information of a conifer tree crown, derived from a high density small foot-print multi-return LiDAR data acquisition for species classification. Considering the fact that branches are the major building blocks of a conifer tree crown, we obtain the internal crown structural information using a branch level analysis. The structure of each conifer branch is represented using clusters in the LiDAR point cloud. We propose the joint use of the k-means clustering and geometric shape fitting, on the LiDAR data projected onto a novel 3-dimensional space, to identify branch clusters. After mapping the identified clusters back to the original space, six internal geometric features are estimated using a branch-level analysis. The external crown characteristics are modeled by using six least correlated features based on cone fitting and convex hull. Species classification is performed using a sparse Support Vector Machines (sparse SVM) classifier.

Structural Associations of Symptomatic Knee Osteoarthritis

PubMed Central

Stoppiello, Laura A; Mapp, Paul I; Wilson, Deborah; Hill, Roger; Scammell, Brigitte E; Walsh, David A

2014-01-01

Objective Structural changes of osteoarthritis (OA) may occur in the absence of pain. In this study, we aimed to identify histopathologic features that are associated with symptomatic knee OA. Methods Medial tibial plateaus and synovium samples were obtained at the time of total knee replacement (TKR) surgery for OA (advanced OA group) or were obtained postmortem from subjects who had not sought medical attention for knee pain during the last year of life (non-OA control group). To identify features of OA, we compared the patients with advanced OA with the age-matched non-OA controls (n = 26 per group). To identify OA features associated with symptoms, we compared two additional groups of subjects who were matched for severity of chondropathy (n = 29 per group): patients undergoing TKR for symptomatic OA (symptomatic chondropathy group) and postmortem subjects with similar severity of chondropathy who were asymptomatic during the last year of life (asymptomatic chondropathy group). The histologic features of the samples were graded, and immunoreactivities for macrophages (CD68) and nerve growth factor (NGF) in the synovium were quantified. The cellular localization of synovial NGF was determined by double immunofluorescence analysis. Results Advanced OA cases displayed more severe changes in the synovium (synovitis, increased synovial NGF, and CD68-immunoreactive macrophages) and cartilage (loss of cartilage surface integrity, loss of proteoglycan, tidemark breaching, and alterations in chondrocyte morphology) than did the non-OA controls. Synovial NGF was localized predominantly to fibroblasts and to some macrophages. The symptomatic chondropathy group displayed greater levels of synovitis, synovial NGF, and loss of cartilage integrity, in addition to alterations in chondrocyte morphology, than did the asymptomatic chondropathy group (P < 0.05 for each comparison). Conclusion Synovitis, increased synovial NGF, alterations in chondrocyte morphology, and loss of cartilage integrity are features of knee OA that may be associated with symptoms. PMID:25049144

Structures of Pseudomonas aeruginosa β-ketoacyl-(acyl-carrier-protein) synthase II (FabF) and a C164Q mutant provide templates for antibacterial drug discovery and identify a buried potassium ion and a ligand-binding site that is an artefact of the crystal form

PubMed Central

Baum, Bernhard; Lecker, Laura S. M.; Zoltner, Martin; Jaenicke, Elmar; Schnell, Robert; Hunter, William N.; Brenk, Ruth

2015-01-01

Bacterial infections remain a serious health concern, in particular causing life-threatening infections of hospitalized and immunocompromised patients. The situation is exacerbated by the rise in antibacterial drug resistance, and new treatments are urgently sought. In this endeavour, accurate structures of molecular targets can support early-stage drug discovery. Here, crystal structures, in three distinct forms, of recombinant Pseudomonas aeruginosa β-ketoacyl-(acyl-carrier-protein) synthase II (FabF) are presented. This enzyme, which is involved in fatty-acid biosynthesis, has been validated by genetic and chemical means as an antibiotic target in Gram-positive bacteria and represents a potential target in Gram-negative bacteria. The structures of apo FabF, of a C164Q mutant in which the binding site is altered to resemble the substrate-bound state and of a complex with 3-(benzoylamino)-2-hydroxybenzoic acid are reported. This compound mimics aspects of a known natural product inhibitor, platensimycin, and surprisingly was observed binding outside the active site, interacting with a symmetry-related molecule. An unusual feature is a completely buried potassium-binding site that was identified in all three structures. Comparisons suggest that this may represent a conserved structural feature of FabF relevant to fold stability. The new structures provide templates for structure-based ligand design and, together with the protocols and reagents, may underpin a target-based drug-discovery project for urgently needed antibacterials. PMID:26249693

Prediction of interface residue based on the features of residue interaction network.

PubMed

Jiao, Xiong; Ranganathan, Shoba

2017-11-07

Protein-protein interaction plays a crucial role in the cellular biological processes. Interface prediction can improve our understanding of the molecular mechanisms of the related processes and functions. In this work, we propose a classification method to recognize the interface residue based on the features of a weighted residue interaction network. The random forest algorithm is used for the prediction and 16 network parameters and the B-factor are acting as the element of the input feature vector. Compared with other similar work, the method is feasible and effective. The relative importance of these features also be analyzed to identify the key feature for the prediction. Some biological meaning of the important feature is explained. The results of this work can be used for the related work about the structure-function relationship analysis via a residue interaction network model. Copyright © 2017 Elsevier Ltd. All rights reserved.

Geologic evidence of hotspot activity of Venus - Predictions for Magellan

NASA Technical Reports Server (NTRS)

Stofan, Ellen R.; Saunders, R. Stephen

1990-01-01

A number of distinctive types of geologic features have been identified on Venus that are interpreted to be related to thermal plumes including domal rises, coronae, and major composite shield volcanoes. The basic characteristics of these features as well as their distribution are documented. The three types of features have related morphologies and are interpreted to represent a continuum of features formed by mantle plumes at scales from 100s to over 1000 km. The Artemis structure, located in Aphrodite Terra, is proposed to be a large corona. If crustal spreading processes are operating on Venus, hotspot features should form chains on the surface as seen in terrestrial ocean basins. On the basis of current data on hotspot-related feature distribution on Venus, no clear evidence exists for hotspot chains. The complete distribution of hotspot features in Magellan data will be used to understand better the relationship between interior processes and surface features, as well as to provide a test for the crustal spreading hypothesis.

MMDB: Entrez’s 3D-structure database

PubMed Central

Wang, Yanli; Anderson, John B.; Chen, Jie; Geer, Lewis Y.; He, Siqian; Hurwitz, David I.; Liebert, Cynthia A.; Madej, Thomas; Marchler, Gabriele H.; Marchler-Bauer, Aron; Panchenko, Anna R.; Shoemaker, Benjamin A.; Song, James S.; Thiessen, Paul A.; Yamashita, Roxanne A.; Bryant, Stephen H.

2002-01-01

Three-dimensional structures are now known within many protein families and it is quite likely, in searching a sequence database, that one will encounter a homolog with known structure. The goal of Entrez’s 3D-structure database is to make this information, and the functional annotation it can provide, easily accessible to molecular biologists. To this end Entrez’s search engine provides three powerful features. (i) Sequence and structure neighbors; one may select all sequences similar to one of interest, for example, and link to any known 3D structures. (ii) Links between databases; one may search by term matching in MEDLINE, for example, and link to 3D structures reported in these articles. (iii) Sequence and structure visualization; identifying a homolog with known structure, one may view molecular-graphic and alignment displays, to infer approximate 3D structure. In this article we focus on two features of Entrez’s Molecular Modeling Database (MMDB) not described previously: links from individual biopolymer chains within 3D structures to a systematic taxonomy of organisms represented in molecular databases, and links from individual chains (and compact 3D domains within them) to structure neighbors, other chains (and 3D domains) with similar 3D structure. MMDB may be accessed at http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=Structure. PMID:11752307

Diffeomorphic functional brain surface alignment: Functional demons.

PubMed

Nenning, Karl-Heinz; Liu, Hesheng; Ghosh, Satrajit S; Sabuncu, Mert R; Schwartz, Ernst; Langs, Georg

2017-08-01

Aligning brain structures across individuals is a central prerequisite for comparative neuroimaging studies. Typically, registration approaches assume a strong association between the features used for alignment, such as macro-anatomy, and the variable observed, such as functional activation or connectivity. Here, we propose to use the structure of intrinsic resting state fMRI signal correlation patterns as a basis for alignment of the cortex in functional studies. Rather than assuming the spatial correspondence of functional structures between subjects, we have identified locations with similar connectivity profiles across subjects. We mapped functional connectivity relationships within the brain into an embedding space, and aligned the resulting maps of multiple subjects. We then performed a diffeomorphic alignment of the cortical surfaces, driven by the corresponding features in the joint embedding space. Results show that functional alignment based on resting state fMRI identifies functionally homologous regions across individuals with higher accuracy than alignment based on the spatial correspondence of anatomy. Further, functional alignment enables measurement of the strength of the anatomo-functional link across the cortex, and reveals the uneven distribution of this link. Stronger anatomo-functional dissociation was found in higher association areas compared to primary sensory- and motor areas. Functional alignment based on resting state features improves group analysis of task based functional MRI data, increasing statistical power and improving the delineation of task-specific core regions. Finally, a comparison of the anatomo-functional dissociation between cohorts is demonstrated with a group of left and right handed subjects. Copyright © 2017 Elsevier Inc. All rights reserved.

Change of the image of the city in process of using traffic infrastructure

NASA Astrophysics Data System (ADS)

Alihodžić, Rifat; Vasiljević Tomić, Dragana; Iablonskii, Leonid

2017-10-01

Unique urban image cannot be experienced without moving within its structure. This paper deals with phenomenology considering changes of images of the city and influential factors closely related to it. Infrastructure gives basic structural scheme of every city, so its planning requires a high level proficiency. Some changes in these images can be observed during longer period of time. Sometimes it includes rapid changes of temporal layers, generated by building new urban elements on the exact same place where the old ones existed; while lighter change during the time passing is a regular occurrence. Creating completely new urban frames, caused by expanding the city, represents its dynamical variant. Topography is a significant factor, giving distinctive feature to the urbanity. This paper considers factors identified as generators of the change of the urban image, based on research so far. The structural elements are considered with the utmost attention. The importance of the city landmark, monumental complexes not possessing these features but having the importance in image of the city stability (as well as the inhabitants’ memory) are crucial elements of identifying its picture. Another significant factor is related to individual personal experience. However, there are also certain factors of significance features, but not considered within this paper. One such factor is change in coloring, being the special topic itself. The purpose of this work is to indicate that urban planning requires special attention in order to keep continuous nature of the urban image for the city to preserve its visual identity.

Structured Post-IQ Domain Governs Selectivity of Myosin X for Fascin-Actin Bundles*

PubMed Central

Nagy, Stanislav; Rock, Ronald S.

2010-01-01

Without guidance cues, cytoskeletal motors would traffic components to the wrong destination with disastrous consequences for the cell. Recently, we identified a motor protein, myosin X, that identifies bundled actin filaments for transport. These bundles direct myosin X to a unique destination, the tips of cellular filopodia. Because the structural and kinetic features that drive bundle selection are unknown, we employed a domain-swapping approach with the nonselective myosin V to identify the selectivity module of myosin X. We found a surprising role of the myosin X tail region (post-IQ) in supporting long runs on bundles. Moreover, the myosin X head is adapted for initiating processive runs on bundles. We found that the tail is structured and biases the orientation of the two myosin X heads because a targeted insertion that introduces flexibility in the tail abolishes selectivity. Together, these results suggest how myosin motors may manage to read cellular addresses. PMID:20538587

Setting an Agenda for a Person-Centered Approach to Personality Development.

ERIC Educational Resources Information Center

Robins, Richard W.; Tracy, Jessica L.

2003-01-01

Describes features and benefits of the person-centered approach to studying personality, identifies unanswered questions, and suggests research directions. Benefits noted include focus on intraindividual structure, descriptive efficiency, use of types as moderator variables, predictive validity, and conceptual clarity and intuitive appeal.…

Stories in Conversation.

ERIC Educational Resources Information Center

Hofer, Roberta Senner

Although conversational stories within one individual's corpus share the same structure, they have features that set them apart from one another. Based on the stories' general characteristics and the way they function in ongoing talk, they can be identified as: (1) durable personal experience narratives (PENs), which are often repeated during the…

EARLY-TYPE GALAXIES WITH TIDAL DEBRIS AND THEIR SCALING RELATIONS IN THE SPITZER SURVEY OF STELLAR STRUCTURE IN GALAXIES (S{sup 4}G)

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

Kim, Taehyun; Sheth, Kartik; Munoz-Mateos, Juan-Carlos

2012-07-01

Tidal debris around galaxies can yield important clues on their evolution. We have identified tidal debris in 11 early-type galaxies (T {<=} 0) from a sample of 65 early types drawn from the Spitzer Survey of Stellar Structure in Galaxies (S{sup 4}G). The tidal debris includes features such as shells, ripples, and tidal tails. A variety of techniques, including two-dimensional decomposition of galactic structures, were used to quantify the residual tidal features. The tidal debris contributes {approx}3%-10% to the total 3.6 {mu}m luminosity of the host galaxy. Structural parameters of the galaxies were estimated using two-dimensional profile fitting. We investigatemore » the locations of galaxies with tidal debris in the fundamental plane and Kormendy relation. We find that galaxies with tidal debris lie within the scatter of early-type galaxies without tidal features. Assuming that the tidal debris is indicative of recent gravitational interaction or merger, this suggests that these galaxies have either undergone minor merging events so that the overall structural properties of the galaxies are not significantly altered, or they have undergone a major merging events but already have experienced sufficient relaxation and phase mixing so that their structural properties become similar to those of the non-interacting early-type galaxies.« less

Phosphatization Associated Features of Ferromanganese Crusts at Lemkein Seamount, Marshall Islands

NASA Astrophysics Data System (ADS)

Choi, J.; Lee, I.; Park, B. K.; Kim, J.

2014-12-01

Old layers of ferromanganese crusts, especially in the Pacific Ocean, have been affected by phosphatization. Ferromanganese crusts on Lemkein seamount in Marshall Islands also are phosphatized (3.3 to 4.2 wt % of P concentration). Furthermore, they have characteristic features that are different from other ferromanganese crusts. These features occur near the phosphorite, which were thought to fill the pore spaces of ferromanganese crusts. Inside the features, ferromanganese crusts are botryoidally precipitated from the round-boundary. The features of the phosphatized lower crusts of Lemkein seamount are observed using microscope and SEM. Elemental compositions of the selected samples were analyzed by SEM-EDS. Based on the observation and analysis of samples, three characteristic structures are identified: (1) phosphate-filled circles, (2) tongue-shaped framboidal crust, and (3) massive framboidal crust. The phosphate-filled circles are mostly composed of phosphorite, and they include trace fossils such as foraminifera. Phosphatized ferromanganese crusts exist at the boundary of this structure. The tongue-shaped crust is connected with the lips downward, and ferromanganese crusts inside the tongue show distinct growth rim. The massive framboidal crust is located below the tongue. Ferromanganese crusts in the massive framboidal crust are enveloped by phosphate, and some of the crusts are phosphatized. Around the structures, Mn oxide phase is concentrated as a shape of corona on BSE image. All of the structures are in the phosphatized crusts that show columnar growth of ferromanganese crusts and have sub-parallel lamination. These observation and chemical analysis of the ferromanganese crusts can provide a clue of diagenetic processes during the formation of ferromanganese crusts.

An ensemble-of-classifiers based approach for early diagnosis of Alzheimer's disease: classification using structural features of brain images.

PubMed

Farhan, Saima; Fahiem, Muhammad Abuzar; Tauseef, Huma

2014-01-01

Structural brain imaging is playing a vital role in identification of changes that occur in brain associated with Alzheimer's disease. This paper proposes an automated image processing based approach for the identification of AD from MRI of the brain. The proposed approach is novel in a sense that it has higher specificity/accuracy values despite the use of smaller feature set as compared to existing approaches. Moreover, the proposed approach is capable of identifying AD patients in early stages. The dataset selected consists of 85 age and gender matched individuals from OASIS database. The features selected are volume of GM, WM, and CSF and size of hippocampus. Three different classification models (SVM, MLP, and J48) are used for identification of patients and controls. In addition, an ensemble of classifiers, based on majority voting, is adopted to overcome the error caused by an independent base classifier. Ten-fold cross validation strategy is applied for the evaluation of our scheme. Moreover, to evaluate the performance of proposed approach, individual features and combination of features are fed to individual classifiers and ensemble based classifier. Using size of left hippocampus as feature, the accuracy achieved with ensemble of classifiers is 93.75%, with 100% specificity and 87.5% sensitivity.

Accurate predictions of population-level changes in sequence and structural properties of HIV-1 Env using a volatility-controlled diffusion model

PubMed Central

DeLeon, Orlando; Hodis, Hagit; O’Malley, Yunxia; Johnson, Jacklyn; Salimi, Hamid; Zhai, Yinjie; Winter, Elizabeth; Remec, Claire; Eichelberger, Noah; Van Cleave, Brandon; Puliadi, Ramya; Harrington, Robert D.; Stapleton, Jack T.; Haim, Hillel

2017-01-01

The envelope glycoproteins (Envs) of HIV-1 continuously evolve in the host by random mutations and recombination events. The resulting diversity of Env variants circulating in the population and their continuing diversification process limit the efficacy of AIDS vaccines. We examined the historic changes in Env sequence and structural features (measured by integrity of epitopes on the Env trimer) in a geographically defined population in the United States. As expected, many Env features were relatively conserved during the 1980s. From this state, some features diversified whereas others remained conserved across the years. We sought to identify “clues” to predict the observed historic diversification patterns. Comparison of viruses that cocirculate in patients at any given time revealed that each feature of Env (sequence or structural) exists at a defined level of variance. The in-host variance of each feature is highly conserved among individuals but can vary between different HIV-1 clades. We designate this property “volatility” and apply it to model evolution of features as a linear diffusion process that progresses with increasing genetic distance. Volatilities of different features are highly correlated with their divergence in longitudinally monitored patients. Volatilities of features also correlate highly with their population-level diversification. Using volatility indices measured from a small number of patient samples, we accurately predict the population diversity that developed for each feature over the course of 30 years. Amino acid variants that evolved at key antigenic sites are also predicted well. Therefore, small “fluctuations” in feature values measured in isolated patient samples accurately describe their potential for population-level diversification. These tools will likely contribute to the design of population-targeted AIDS vaccines by effectively capturing the diversity of currently circulating strains and addressing properties of variants expected to appear in the future. PMID:28384158

The expanding universe of thiolated gold nanoclusters and beyond.

PubMed

Jiang, De-en

2013-08-21

Thiolated gold nanoclusters form a universe of their own. Researchers in this field are constantly pushing the boundary of this universe by identifying new compositions and in a few "lucky" cases, solving their structures. Such solved structures, even if there are only few, provide important hints for predicting the many identified compositions that are yet to be crystallized or structure determined. Structure prediction is the most pressing issue for a computational chemist in this field. The success of the density functional theory method in gauging the energetic ordering of isomers for thiolated gold clusters has been truly remarkable, but to predict the most stable structure for a given composition remains a great challenge. In this feature article from a computational chemist's point of view, the author shows how one understands and predicts structures for thiolated gold nanoclusters based on his old and new results. To further entertain the reader, the author also offers several "imaginative" structures, claims, and challenges for this field.

TFBSshape: a motif database for DNA shape features of transcription factor binding sites.

PubMed

Yang, Lin; Zhou, Tianyin; Dror, Iris; Mathelier, Anthony; Wasserman, Wyeth W; Gordân, Raluca; Rohs, Remo

2014-01-01

Transcription factor binding sites (TFBSs) are most commonly characterized by the nucleotide preferences at each position of the DNA target. Whereas these sequence motifs are quite accurate descriptions of DNA binding specificities of transcription factors (TFs), proteins recognize DNA as a three-dimensional object. DNA structural features refine the description of TF binding specificities and provide mechanistic insights into protein-DNA recognition. Existing motif databases contain extensive nucleotide sequences identified in binding experiments based on their selection by a TF. To utilize DNA shape information when analysing the DNA binding specificities of TFs, we developed a new tool, the TFBSshape database (available at http://rohslab.cmb.usc.edu/TFBSshape/), for calculating DNA structural features from nucleotide sequences provided by motif databases. The TFBSshape database can be used to generate heat maps and quantitative data for DNA structural features (i.e., minor groove width, roll, propeller twist and helix twist) for 739 TF datasets from 23 different species derived from the motif databases JASPAR and UniPROBE. As demonstrated for the basic helix-loop-helix and homeodomain TF families, our TFBSshape database can be used to compare, qualitatively and quantitatively, the DNA binding specificities of closely related TFs and, thus, uncover differential DNA binding specificities that are not apparent from nucleotide sequence alone.

TFBSshape: a motif database for DNA shape features of transcription factor binding sites

PubMed Central

Yang, Lin; Zhou, Tianyin; Dror, Iris; Mathelier, Anthony; Wasserman, Wyeth W.; Gordân, Raluca; Rohs, Remo

2014-01-01

Transcription factor binding sites (TFBSs) are most commonly characterized by the nucleotide preferences at each position of the DNA target. Whereas these sequence motifs are quite accurate descriptions of DNA binding specificities of transcription factors (TFs), proteins recognize DNA as a three-dimensional object. DNA structural features refine the description of TF binding specificities and provide mechanistic insights into protein–DNA recognition. Existing motif databases contain extensive nucleotide sequences identified in binding experiments based on their selection by a TF. To utilize DNA shape information when analysing the DNA binding specificities of TFs, we developed a new tool, the TFBSshape database (available at http://rohslab.cmb.usc.edu/TFBSshape/), for calculating DNA structural features from nucleotide sequences provided by motif databases. The TFBSshape database can be used to generate heat maps and quantitative data for DNA structural features (i.e., minor groove width, roll, propeller twist and helix twist) for 739 TF datasets from 23 different species derived from the motif databases JASPAR and UniPROBE. As demonstrated for the basic helix-loop-helix and homeodomain TF families, our TFBSshape database can be used to compare, qualitatively and quantitatively, the DNA binding specificities of closely related TFs and, thus, uncover differential DNA binding specificities that are not apparent from nucleotide sequence alone. PMID:24214955

Clinical anatomy of the elbow and shoulder.

PubMed

Villaseñor-Ovies, Pablo; Vargas, Angélica; Chiapas-Gasca, Karla; Canoso, Juan J; Hernández-Díaz, Cristina; Saavedra, Miguel Ángel; Navarro-Zarza, José Eduardo; Kalish, Robert A

The elbow patients herein discussed feature common soft tissue conditions such as tennis elbow, golfers' elbow and olecranon bursitis. Relevant anatomical structures for these conditions can easily be identified and demonstrated by cross examination by instructors and participants. Patients usually present rotator cuff tendinopathy, frozen shoulder, axillary neuropathy and suprascapular neuropathy. The structures involved in tendinopathy and frozen shoulder can be easily identified and demonstrated under normal conditions. The axillary and the suprascapular nerves have surface landmarks but cannot be palpated. In neuropathy however, physical findings in both neuropathies are pathognomonic and will be discussed. Copyright © 2012 Elsevier España, S.L. All rights reserved.

A 2-year study of Gram stain competency assessment in 40 clinical laboratories.

PubMed

Goodyear, Nancy; Kim, Sara; Reeves, Mary; Astion, Michael L

2006-01-01

We used a computer-based competency assessment tool for Gram stain interpretation to assess the performance of 278 laboratory staff from 40 laboratories on 40 multiple-choice questions. We report test reliability, mean scores, median, item difficulty, discrimination, and analysis of the highest- and lowest-scoring questions. The questions were reliable (KR-20 coefficient, 0.80). Overall mean score was 88% (range, 63%-98%). When categorized by cell type, the means were host cells, 93%; other cells (eg, yeast), 92%; gram-positive, 90%; and gram-negative, 88%. When categorized by type of interpretation, the means were other (eg, underdecolorization), 92%; identify by structure (eg, bacterial morphologic features), 91%; and identify by name (eg, genus and species), 87%. Of the 6 highest-scoring questions (mean scores, > or = 99%) 5 were identify by structure and 1 was identify by name. Of the 6 lowest-scoring questions (mean scores, < 75%) 5 were gram-negative and 1 was host cells. By type of interpretation, 2 were identify by structure and 4 were identify by name. Computer-based Gram stain competency assessment examinations are reliable. Our analysis helps laboratories identify areas for continuing education in Gram stain interpretation and will direct future revisions of the tests.

Gstruct: a system for extracting schemas from GML documents

NASA Astrophysics Data System (ADS)

Chen, Hui; Zhu, Fubao; Guan, Jihong; Zhou, Shuigeng

2008-10-01

Geography Markup Language (GML) becomes the de facto standard for geographic information representation on the internet. GML schema provides a way to define the structure, content, and semantic of GML documents. It contains useful structural information of GML documents and plays an important role in storing, querying and analyzing GML data. However, GML schema is not mandatory, and it is common that a GML document contains no schema. In this paper, we present Gstruct, a tool for GML schema extraction. Gstruct finds the features in the input GML documents, identifies geometry datatypes as well as simple datatypes, then integrates all these features and eliminates improper components to output the optimal schema. Experiments demonstrate that Gstruct is effective in extracting semantically meaningful schemas from GML documents.

Exploration and discovery in Yellowstone Lake: Results from high-resolution sonar imaging, seismic reflection profiling, and submersible studies

USGS Publications Warehouse

Morgan, L.A.; Shanks, Wayne C.; Lovalvo, D.A.; Johnson, S.Y.; Stephenson, W.J.; Pierce, K.L.; Harlan, S.S.; Finn, C.A.; Lee, G.; Webring, M.; Schulze, B.; Duhn, J.; Sweeney, R.; Balistrieri, L.

2003-01-01

Discoveries from multi-beam sonar mapping and seismic reflection surveys of the northern, central, and West Thumb basins of Yellowstone Lake provide new insight into the extent of post-collapse volcanism and active hydrothermal processes occurring in a large lake environment above a large magma chamber. Yellowstone Lake has an irregular bottom covered with dozens of features directly related to hydrothermal, tectonic, volcanic, and sedimentary processes. Detailed bathymetric, seismic reflection, and magnetic evidence reveals that rhyolitic lava flows underlie much of Yellowstone Lake and exert fundamental control on lake bathymetry and localization of hydrothermal activity. Many previously unknown features have been identified and include over 250 hydrothermal vents, several very large (>500 m diameter) hydrothermal explosion craters, many small hydrothermal vent craters (???1-200 m diameter), domed lacustrine sediments related to hydrothermal activity, elongate fissures cutting post-glacial sediments, siliceous hydrothermal spire structures, sublacustrine landslide deposits, submerged former shorelines, and a recently active graben. Sampling and observations with a submersible remotely operated vehicle confirm and extend our understanding of the identified features. Faults, fissures, hydrothermally inflated domal structures, hydrothermal explosion craters, and sublacustrine landslides constitute potentially significant geologic hazards. Toxic elements derived from hydrothermal processes also may significantly affect the Yellowstone ecosystem. Published by Elsevier Science B.V.

Diagnostic Analyzer for Gearboxes (DAG): User's Guide. Version 3.1 for Microsoft Windows 3.1

NASA Technical Reports Server (NTRS)

Jammu, Vinay B.; Kourosh, Danai

1997-01-01

This documentation describes the Diagnostic Analyzer for Gearboxes (DAG) software for performing fault diagnosis of gearboxes. First, the user would construct a graphical representation of the gearbox using the gear, bearing, shaft, and sensor tools contained in the DAG software. Next, a set of vibration features obtained by processing the vibration signals recorded from the gearbox using a signal analyzer is required. Given this information, the DAG software uses an unsupervised neural network referred to as the Fault Detection Network (FDN) to identify the occurrence of faults, and a pattern classifier called Single Category-Based Classifier (SCBC) for abnormality scaling of individual vibration features. The abnormality-scaled vibration features are then used as inputs to a Structure-Based Connectionist Network (SBCN) for identifying faults in gearbox subsystems and components. The weights of the SBCN represent its diagnostic knowledge and are derived from the structure of the gearbox graphically presented in DAG. The outputs of SBCN are fault possibility values between 0 and 1 for individual subsystems and components in the gearbox with a 1 representing a definite fault and a 0 representing normality. This manual describes the steps involved in creating the diagnostic gearbox model, along with the options and analysis tools of the DAG software.

The impact of jackpots on EGM gambling behavior: a review.

PubMed

Rockloff, Matthew J; Hing, Nerilee

2013-12-01

This paper reviews literature on how jackpots influence Electronic Gaming Machine (EGM) gambling behaviour. Most of the available evidence addresses the motivational effect of the mere presence of EGM jackpots on play, as actual wins are relatively rare for individual gamblers. The review identifies a distinction between rational, biased and irrational motivations that attract people to EGM jackpots. The evidence suggests that EGM jackpots should generate additional consumption on EGMs above machines that do not have such lottery-like features. Rational motivations are likely to lead to consumer surplus, whereas biased and irrational motivations are likely to contribute to excessive consumption. Moreover, there is evidence that excessive gambling consumption is strongly associated with gambling-related harm. Future research should identify how the structural features of different types of jackpots; such as progressive, deterministic, hidden, mystery, linked and wide-area jackpots; may differentially appeal to rational, biased and irrational gambling motivations. Jackpots are common feature of EGM games, and therefore it is important to have a better understanding of how jackpot features influence play on the machines.

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

The Identification of Hail Storms in the Early Stage Using Time Series Analysis

NASA Astrophysics Data System (ADS)

Wang, Ping; Shi, Jinyu; Hou, Jinyi; Hu, Yan

2018-01-01

This study investigates the characteristics of hail storms and cumulonimbus storms in China from 2005 to 2016. Ten features are proposed to identify storm cells that can produce hail, especially in the early stage of hail formation. These features describe hail storms based on three factors: the height and thickness of the cell core, the radar echo intensity, and the overhang structure and the horizontal reflectivity gradient. The 10 features are transformed into two-dimensional comprehensive features by principal component analysis (PCA). The two comprehensive features are named the volume measurement comprehensive feature (VMCF) and the height-gradient comprehensive feature (HGCF). Through an analysis of 49 hail cases and 35 heavy rainfall cases with S-band radar data, the time series exhibit a distinct increase in VMCF or HGCF values in the early stage of a hail storm. However, the VMCF and HGCF values of heavy rainfall events remain relatively stable throughout the storm life cycle. An experiment involving real-storm events, including 31 hail cases and 33 heavy rainfall cases, indicated that the probability of detection of hail storms was 93.33% and the false alarm ratio was 15.66%. In the cases that could be successfully identified as hail storms, 80.00% were detected within 18 min of reaching a hail storm reflectivity of 40 dBZ.

Effect of ion-beam treatment on structure and fracture resistance of 12Cr1MoV steel under static, cyclic and dynamic loading

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

Panin, S. V., E-mail: svp@ispms.tsc.ru; Vlasov, I. V., E-mail: good0@yandex.ru; Sergeev, V. P., E-mail: retc@ispms.tsc.ru

2015-10-27

Features of the structure and properties modification of 12Cr1MoV steel subjected to irradiation by zirconium ion beam have been investigated with the use of optical and electron microscopy as well as microhardness measurement. It has been shown that upon treatment the structure modification occurred across the entire cross-section of specimens with the thickness of 1 mm. Changes in the mechanical properties of these specimens under static, cyclic and impact loading are interpreted in terms of identified structure changes.

Covariance of dynamic strain responses for structural damage detection

NASA Astrophysics Data System (ADS)

Li, X. Y.; Wang, L. X.; Law, S. S.; Nie, Z. H.

2017-10-01

A new approach to address the practical problems with condition evaluation/damage detection of structures is proposed based on the distinct features of a new damage index. The covariance of strain response function (CoS) is a function of modal parameters of the structure. A local stiffness reduction in structure would cause monotonous increase in the CoS. Its sensitivity matrix with respect to local damages of structure is negative and narrow-banded. The damage extent can be estimated with an approximation to the sensitivity matrix to decouple the identification equations. The CoS sensitivity can be calibrated in practice from two previous states of measurements to estimate approximately the damage extent of a structure. A seven-storey plane frame structure is numerically studied to illustrate the features of the CoS index and the proposed method. A steel circular arch in the laboratory is tested. Natural frequencies changed due to damage in the arch and the damage occurrence can be judged. However, the proposed CoS method can identify not only damage happening but also location, even damage extent without need of an analytical model. It is promising for structural condition evaluation of selected components.

Improve the prediction of RNA-binding residues using structural neighbours.

PubMed

Li, Quan; Cao, Zanxia; Liu, Haiyan

2010-03-01

The interactions between RNA-binding proteins (RBPs) with RNA play key roles in managing some of the cell's basic functions. The identification and prediction of RNA binding sites is important for understanding the RNA-binding mechanism. Computational approaches are being developed to predict RNA-binding residues based on the sequence- or structure-derived features. To achieve higher prediction accuracy, improvements on current prediction methods are necessary. We identified that the structural neighbors of RNA-binding and non-RNA-binding residues have different amino acid compositions. Combining this structure-derived feature with evolutionary (PSSM) and other structural information (secondary structure and solvent accessibility) significantly improves the predictions over existing methods. Using a multiple linear regression approach and 6-fold cross validation, our best model can achieve an overall correct rate of 87.8% and MCC of 0.47, with a specificity of 93.4%, correctly predict 52.4% of the RNA-binding residues for a dataset containing 107 non-homologous RNA-binding proteins. Compared with existing methods, including the amino acid compositions of structure neighbors lead to clearly improvement. A web server was developed for predicting RNA binding residues in a protein sequence (or structure),which is available at http://mcgill.3322.org/RNA/.

Loss of integrity and atrophy in cingulate structural covariance networks in Parkinson's disease.

PubMed

de Schipper, Laura J; van der Grond, Jeroen; Marinus, Johan; Henselmans, Johanna M L; van Hilten, Jacobus J

2017-01-01

In Parkinson's disease (PD), the relation between cortical brain atrophy on MRI and clinical progression is not straightforward. Determination of changes in structural covariance networks - patterns of covariance in grey matter density - has shown to be a valuable technique to detect subtle grey matter variations. We evaluated how structural network integrity in PD is related to clinical data. 3 Tesla MRI was performed in 159 PD patients. We used nine standardized structural covariance networks identified in 370 healthy subjects as a template in the analysis of the PD data. Clinical assessment comprised motor features (Movement Disorder Society-Unified Parkinson's Disease Rating Scale; MDS-UPDRS motor scale) and predominantly non-dopaminergic features (SEverity of Non-dopaminergic Symptoms in Parkinson's Disease; SENS-PD scale: postural instability and gait difficulty, psychotic symptoms, excessive daytime sleepiness, autonomic dysfunction, cognitive impairment and depressive symptoms). Voxel-based analyses were performed within networks significantly associated with PD. The anterior and posterior cingulate network showed decreased integrity, associated with the SENS-PD score, p = 0.001 (β = - 0.265, η p 2  = 0.070) and p = 0.001 (β = - 0.264, η p 2  = 0.074), respectively. Of the components of the SENS-PD score, cognitive impairment and excessive daytime sleepiness were associated with atrophy within both networks. We identified loss of integrity and atrophy in the anterior and posterior cingulate networks in PD patients. Abnormalities of both networks were associated with predominantly non-dopaminergic features, specifically cognition and excessive daytime sleepiness. Our findings suggest that (components of) the cingulate networks display a specific vulnerability to the pathobiology of PD and may operate as interfaces between networks involved in cognition and alertness.

Noscapinoids with anti-cancer activity against human acute lymphoblastic leukemia cells (CEM): a three dimensional chemical space pharmacophore modeling and electronic feature analysis.

PubMed

Naik, Pradeep K; Santoshi, Seneha; Joshi, Harish C

2012-01-01

We have identified a new class of microtubule-binding compounds-noscapinoids-that alter microtubule dynamics at stoichiometric concentrations without affecting tubulin polymer mass. Noscapinoids show great promise as chemotherapeutic agents for the treatment of human cancers. To investigate the structural determinants of noscapinoids responsible for anti-cancer activity, we tested 36 structurally diverse noscapinoids in human acute lymphoblastic leukemia cells (CEM). The IC(50) values of these noscapinoids vary from 1.2 to 56.0 μM. Pharmacophore models of anti-cancer activity were generated that identify two hydrogen bond acceptors, two aromatic rings, two hydrophobic groups, and one positively charged group as essential structural features. Additionally, an atom-based quantitative structure-activity relationship (QSAR) model was developed that gave a statistically satisfying result (R(2) = 0.912, Q(2) = 0.908, Pearson R = 0.951) and effectively predicts the anti-cancer activity of training and test set compounds. The pharmacophore model presented here is well supported by electronic property analysis using density functional theory at B3LYP/3-21*G level. Molecular electrostatic potential, particularly localization of negative potential near oxygen atoms of the dimethoxy isobenzofuranone ring of active compounds, matched the hydrogen bond acceptor feature of the generated pharmacophore. Our results further reveal that all active compounds have smaller lowest unoccupied molecular orbital (LUMO) energies concentrated over the dimethoxy isobenzofuranone ring, azido group, and nitro group, which is indicative of the electron acceptor capacity of the compounds. Results obtained from this study will be useful in the efficient design and development of more active noscapinoids.

HUMAN GLYCERALDEHYDE 3-PHOSPHATE DEHYDROGENASE-2 (GAPD2) GENE IS EXPRESSED SPECIFICALLY IN SPERMATOGENIC CELLS

EPA Science Inventory

Although the process of glycolysis is highly conserved in eukaryotes, several glycolytic enzymes have unique structural or functional features in spermatogenic cells. We previously identified and characterized the mouse complementary DNA (cDNA) and a gene for 1 of these enzymes, ...

Assessing Quality in Home Visiting Programs

ERIC Educational Resources Information Center

Korfmacher, Jon; Laszewski, Audrey; Sparr, Mariel; Hammel, Jennifer

2013-01-01

Defining quality and designing a quality assessment measure for home visitation programs is a complex and multifaceted undertaking. This article summarizes the process used to create the Home Visitation Program Quality Rating Tool (HVPQRT) and identifies next steps for its development. The HVPQRT measures both structural and dynamic features of…

Research on Higher Education: A U.S. Perspective.

ERIC Educational Resources Information Center

Toombs, William

Characteristics of U.S. higher education are identified, along with the structural features that influence the nature of research, specific research topics, and the locations of research activities. This information was obtained from several sources, including the Educational Resources Information Center database for the years 1981 and 1982, the…

Near infrared detection of ammonium minerals.

USGS Publications Warehouse

Krohn, M.D.; Altaner, S.P.

1987-01-01

Diagnostic near-infrared spectral features have been identified for minerals with ammonium (NH4+) bound in the crystal structure. Near-infrared detection of NH4-bearing minerals may provide useful information for prospecting for certain ore deposits and may provide a better understanding of the nitrogen cycle within geologic environments.-from Authors

Methods for Monitoring the Detection of Multi-Temporal Land Use Change Through the Classification of Urban Areas

NASA Astrophysics Data System (ADS)

Alhaddad, B. I.; Burns, M. C.; Roca, J.

2011-08-01

Urban areas are complicated due to the mix of man-made features and natural features. A higher level of structural information plays an important role in land cover/use classification of urban areas. Additional spatial indicators have to be extracted based on structural analysis in order to understand and identify spatial patterns or the spatial organization of features, especially for man-made feature. It's very difficult to extract such spatial patterns by using only classification approaches. Clusters of urban patterns which are integral parts of other uses may be difficult to identify. A lot of public resources have been directed towards seeking to develop a standardized classification system and to provide as much compatibility as possible to ensure the widespread use of such categorized data obtained from remote sensor sources. In this paper different methods applied to understand the change in the land use areas by understanding and monitoring the change in urban areas and as its hard to apply those methods to classification results for high elements quantities, dusts and scratches (Roca and Alhaddad, 2005). This paper focuses on a methodology developed based relation between urban elements and how to join this elements in zones or clusters have commune behaviours such as form, pattern, size. The main objective is to convert urban class category in to various structure densities depend on conjunction of pixel and shortest distance between them, Delaunay triangulation has been widely used in spatial analysis and spatial modelling. To identify these different zones, a spatial density-based clustering technique was adopted. In highly urban zones, the spatial density of the pixels is high, while in sparsely areas the density of points is much lower. Once the groups of pixels are identified, the calculation of the boundaries of the areas containing each group of pixels defines the new regions indicate the different contains inside such as high or low urban areas. Multi-temporal datasets from 1986, 1995 and 2004 used to urban region centroid to be our reference in this study which allow us to follow the urban movement, increase and decrease by the time. Kernel Density function used to Calculates urban magnitude, Voronoi algorithm is proposed for deriving explicit boundaries between objects units. To test the approach, we selected a site in a suburban area in Barcelona Municipality, the Spain.

Features of primary health care teams associated with successful quality improvement of diabetes care: a qualitative study.

PubMed

Stevenson, K; Baker, R; Farooqi, A; Sorrie, R; Khunti, K

2001-02-01

In quality improvement activities such as audit, some general practices succeed in improving care and some do not. With audit of care likely to be one of the major tools in clinical governance, it would be helpful to establish what features of primary health care teams are associated with successful audit in general practice. The aim of the present study was to identify those features of primary health care teams that were associated with successful quality improvement during systematic audit of diabetes care. Semi-structured tape-recorded interviews were carried out with lead GPs and practice nurses in 18 general practices in Leicestershire that had the opportunity to improve their care and had completed two data collections in a multipractice audit of diabetes care. The interviewees were asked to describe their practice's approach to audit and the transcripts were coded for common features and judged for strength of feeling by blinded independent raters. Features common to practices that had, and those that had not, managed to improve diabetes care were identified. Six features were identified reliably in the transcripts by blinded independent raters. Four were significantly associated with the successful improvement of care. Success was more likely in teams in which: the GP or nurse felt personally involved in the audit; they perceived their teamwork as good; they had recognized the need for systematic plans to address obstacles to quality improvement; and their teams had a positive attitude to continued monitoring of care. A positive attitude to audit and a personal interest in the disease were not associated with improvement in care. Success in improving diabetes care is associated with certain organizational features of primary health care teams. Experimental studies are required to determine whether the development of teamwork enables practice teams to identify and overcome systematically the obstacles to improved quality of patient care that face them.

Landscape genetics and the spatial distribution of chronic wasting disease

USGS Publications Warehouse

Blanchong, Julie A.; Samuel, M.D.; Scribner, K.T.; Weckworth, B.V.; Langenberg, J.A.; Filcek, K.B.

2008-01-01

Predicting the spread of wildlife disease is critical for identifying populations at risk, targeting surveillance and designing proactive management programmes. We used a landscape genetics approach to identify landscape features that influenced gene flow and the distribution of chronic wasting disease (CWD) in Wisconsin white-tailed deer. CWD prevalence was negatively correlated with genetic differentiation of study area deer from deer in the area of disease origin (core-area). Genetic differentiation was greatest, and CWD prevalence lowest, in areas separated from the core-area by the Wisconsin River, indicating that this river reduced deer gene flow and probably disease spread. Features of the landscape that influence host dispersal and spatial patterns of disease can be identified based on host spatial genetic structure. Landscape genetics may be used to predict high-risk populations based on their genetic connection to infected populations and to target disease surveillance, control and preventative activities. ?? 2007 The Royal Society.

Identifying and Synchronizing Health Information Technology (HIT) Events from FDA Medical Device Reports.

PubMed

Kang, Hong; Wang, Frank; Zhou, Sicheng; Miao, Qi; Gong, Yang

2017-01-01

Health information technology (HIT) events, a subtype of patient safety events, pose a major threat and barrier toward a safer healthcare system. It is crucial to gain a better understanding of the nature of the errors and adverse events caused by current HIT systems. The scarcity of HIT event-exclusive databases and event reporting systems indicates the challenge of identifying the HIT events from existing resources. FDA Manufacturer and User Facility Device Experience (MAUDE) database is a potential resource for HIT events. However, the low proportion and the rapid evolvement of HIT-related events present challenges for distinguishing them from other equipment failures and hazards. We proposed a strategy to identify and synchronize HIT events from MAUDE by using a filter based on structured features and classifiers based on unstructured features. The strategy will help us develop and grow an HIT event-exclusive database, keeping pace with updates to MAUDE toward shared learning.

The effect of alkaline pretreatment methods on cellulose structure and accessibility

DOE PAGES

Bali, Garima; Meng, Xianzhi; Deneff, Jacob I.; ...

2014-11-24

The effects of different alkaline pretreatments on cellulose structural features and accessibility are compared and correlated with the enzymatic hydrolysis of Populus. The pretreatments are shown to modify polysaccharides and lignin content to enhance the accessibility for cellulase enzymes. The highest increase in the cellulose accessibility was observed in dilute sodium hydroxide, followed by methods using ammonia soaking and lime (Ca(OH) 2). The biggest increase of cellulose accessibility occurs during the first 10 min of pretreatment, with further increases at a slower rate as severity increases. Low temperature ammonia soaking at longer residence times dissolved a major portion of hemicellulosemore » and exhibited higher cellulose accessibility than high temperature soaking. Moreover, the most significant reduction of degree of polymerization (DP) occurred for dilute sodium hydroxide (NaOH) and ammonia pretreated Populus samples. The study thus identifies important cellulose structural features and relevant parameters related to biomass recalcitrance.« less

Complete fold annotation of the human proteome using a novel structural feature space.

PubMed

Middleton, Sarah A; Illuminati, Joseph; Kim, Junhyong

2017-04-13

Recognition of protein structural fold is the starting point for many structure prediction tools and protein function inference. Fold prediction is computationally demanding and recognizing novel folds is difficult such that the majority of proteins have not been annotated for fold classification. Here we describe a new machine learning approach using a novel feature space that can be used for accurate recognition of all 1,221 currently known folds and inference of unknown novel folds. We show that our method achieves better than 94% accuracy even when many folds have only one training example. We demonstrate the utility of this method by predicting the folds of 34,330 human protein domains and showing that these predictions can yield useful insights into potential biological function, such as prediction of RNA-binding ability. Our method can be applied to de novo fold prediction of entire proteomes and identify candidate novel fold families.

Complete fold annotation of the human proteome using a novel structural feature space

PubMed Central

Middleton, Sarah A.; Illuminati, Joseph; Kim, Junhyong

2017-01-01

Recognition of protein structural fold is the starting point for many structure prediction tools and protein function inference. Fold prediction is computationally demanding and recognizing novel folds is difficult such that the majority of proteins have not been annotated for fold classification. Here we describe a new machine learning approach using a novel feature space that can be used for accurate recognition of all 1,221 currently known folds and inference of unknown novel folds. We show that our method achieves better than 94% accuracy even when many folds have only one training example. We demonstrate the utility of this method by predicting the folds of 34,330 human protein domains and showing that these predictions can yield useful insights into potential biological function, such as prediction of RNA-binding ability. Our method can be applied to de novo fold prediction of entire proteomes and identify candidate novel fold families. PMID:28406174

In Silico Analysis of the Structural and Biochemical Features of the NMD Factor UPF1 in Ustilago maydis.

PubMed

Martínez-Montiel, Nancy; Morales-Lara, Laura; Hernández-Pérez, Julio M; Martínez-Contreras, Rebeca D

2016-01-01

The molecular mechanisms regulating the accuracy of gene expression are still not fully understood. Among these mechanisms, Nonsense-mediated Decay (NMD) is a quality control process that detects post-transcriptionally abnormal transcripts and leads them to degradation. The UPF1 protein lays at the heart of NMD as shown by several structural and functional features reported for this factor mainly for Homo sapiens and Saccharomyces cerevisiae. This process is highly conserved in eukaryotes but functional diversity can be observed in various species. Ustilago maydis is a basidiomycete and the best-known smut, which has become a model to study molecular and cellular eukaryotic mechanisms. In this study, we performed in silico analysis to investigate the structural and biochemical properties of the putative UPF1 homolog in Ustilago maydis. The putative homolog for UPF1 was recognized in the annotated genome for the basidiomycete, exhibiting 66% identity with its human counterpart at the protein level. The known structural and functional domains characteristic of UPF1 homologs were also found. Based on the crystal structures available for UPF1, we constructed different three-dimensional models for umUPF1 in order to analyze the secondary and tertiary structural features of this factor. Using these models, we studied the spatial arrangement of umUPF1 and its capability to interact with UPF2. Moreover, we identified the critical amino acids that mediate the interaction of umUPF1 with UPF2, ATP, RNA and with UPF1 itself. Mutating these amino acids in silico showed an important effect over the native structure. Finally, we performed molecular dynamic simulations for UPF1 proteins from H. sapiens and U. maydis and the results obtained show a similar behavior and physicochemical properties for the protein in both organisms. Overall, our results indicate that the putative UPF1 identified in U. maydis shows a very similar sequence, structural organization, mechanical stability, physicochemical properties and spatial organization in comparison to the NMD factor depicted for Homo sapiens. These observations strongly support the notion that human and fungal UPF1 could perform equivalent biological activities.

Automatic Identification of Critical Follow-Up Recommendation Sentences in Radiology Reports

PubMed Central

Yetisgen-Yildiz, Meliha; Gunn, Martin L.; Xia, Fei; Payne, Thomas H.

2011-01-01

Communication of follow-up recommendations when abnormalities are identified on imaging studies is prone to error. When recommendations are not systematically identified and promptly communicated to referrers, poor patient outcomes can result. Using information technology can improve communication and improve patient safety. In this paper, we describe a text processing approach that uses natural language processing (NLP) and supervised text classification methods to automatically identify critical recommendation sentences in radiology reports. To increase the classification performance we enhanced the simple unigram token representation approach with lexical, semantic, knowledge-base, and structural features. We tested different combinations of those features with the Maximum Entropy (MaxEnt) classification algorithm. Classifiers were trained and tested with a gold standard corpus annotated by a domain expert. We applied 5-fold cross validation and our best performing classifier achieved 95.60% precision, 79.82% recall, 87.0% F-score, and 99.59% classification accuracy in identifying the critical recommendation sentences in radiology reports. PMID:22195225

Automatic identification of critical follow-up recommendation sentences in radiology reports.

PubMed

Yetisgen-Yildiz, Meliha; Gunn, Martin L; Xia, Fei; Payne, Thomas H

2011-01-01

Communication of follow-up recommendations when abnormalities are identified on imaging studies is prone to error. When recommendations are not systematically identified and promptly communicated to referrers, poor patient outcomes can result. Using information technology can improve communication and improve patient safety. In this paper, we describe a text processing approach that uses natural language processing (NLP) and supervised text classification methods to automatically identify critical recommendation sentences in radiology reports. To increase the classification performance we enhanced the simple unigram token representation approach with lexical, semantic, knowledge-base, and structural features. We tested different combinations of those features with the Maximum Entropy (MaxEnt) classification algorithm. Classifiers were trained and tested with a gold standard corpus annotated by a domain expert. We applied 5-fold cross validation and our best performing classifier achieved 95.60% precision, 79.82% recall, 87.0% F-score, and 99.59% classification accuracy in identifying the critical recommendation sentences in radiology reports.

Study of the electronic structure of electron accepting cyano-films: TCNQversusTCNE.

PubMed

Capitán, Maria J; Álvarez, Jesús; Navio, Cristina

2018-04-18

In this article, we perform systematic research on the electronic structure of two closely related organic electron acceptor molecules (TCNQ and TCNE), which are of technological interest due to their outstanding electronic properties. These studies have been performed from the experimental point of view by the use electron spectroscopies (XPS and UPS) and supported theoretically by the use of ab-initio DFT calculations. The cross-check between both molecules allows us to identify the characteristic electronic features of each part of the molecules and their contribution to the final electronic structure. We can describe the nature of the band gap of these materials, and we relate this with the appearance of the shake-up features in the core level spectra. A band bending and energy gap reduction of the aforementioned electronic structure in contact with a metal surface are seen in the experimental results as well in the theoretical calculations. This behavior implies that the TCNQ thin film accepts electrons from the metal substrate becoming a Schottky n-junction.

Structural and mechanical features of the order-disorder transition in experimental hard-sphere packings

NASA Astrophysics Data System (ADS)

Hanifpour, M.; Francois, N.; Robins, V.; Kingston, A.; Vaez Allaei, S. M.; Saadatfar, M.

2015-06-01

Here we present an experimental and numerical investigation on the grain-scale geometrical and mechanical properties of partially crystallized structures made of macroscopic frictional grains. Crystallization is inevitable in arrangements of monosized hard spheres with packing densities exceeding Bernal's limiting density ϕBernal≈0.64 . We study packings of monosized hard spheres whose density spans over a wide range (0.59 <ϕ <0.72 ) . These experiments harness x-ray computed tomography, three-dimensional image analysis, and numerical simulations to access precisely the geometry and the 3D structure of internal forces within the sphere packings. We show that clear geometrical transitions coincide with modifications of the mechanical backbone of the packing both at the grain and global scale. Notably, two transitions are identified at ϕBernal≈0.64 and ϕc≈0.68 . These results provide insights on how geometrical and mechanical features at the grain scale conspire to yield partially crystallized structures that are mechanically stable.

Borrowed Capital as Risk Factor for Large Construction Companies in Russia

NASA Astrophysics Data System (ADS)

Guzikova, L.; Plotnikova, E.; Zubareva, M.

2017-11-01

The paper investigates the features of the formation of the capital structure of large construction companies from the standpoint of the financial risks and opportunities for companies’ development. The authors compare the opportunities and risks linked with the use of the own and borrowed capital, analyze the capital structure of large Russian construction companies, identify factors affecting the capital structure and determining the ratio of own and borrowed sources of financing. In the paper the hypothesis is considered that companies use larger volumes of borrowed capital by means of their assets increase.

Integrating epigenomic data and 3D genomic structure with a new measure of chromatin assortativity.

PubMed

Pancaldi, Vera; Carrillo-de-Santa-Pau, Enrique; Javierre, Biola Maria; Juan, David; Fraser, Peter; Spivakov, Mikhail; Valencia, Alfonso; Rico, Daniel

2016-07-08

Network analysis is a powerful way of modeling chromatin interactions. Assortativity is a network property used in social sciences to identify factors affecting how people establish social ties. We propose a new approach, using chromatin assortativity, to integrate the epigenomic landscape of a specific cell type with its chromatin interaction network and thus investigate which proteins or chromatin marks mediate genomic contacts. We use high-resolution promoter capture Hi-C and Hi-Cap data as well as ChIA-PET data from mouse embryonic stem cells to investigate promoter-centered chromatin interaction networks and calculate the presence of specific epigenomic features in the chromatin fragments constituting the nodes of the network. We estimate the association of these features with the topology of four chromatin interaction networks and identify features localized in connected areas of the network. Polycomb group proteins and associated histone marks are the features with the highest chromatin assortativity in promoter-centered networks. We then ask which features distinguish contacts amongst promoters from contacts between promoters and other genomic elements. We observe higher chromatin assortativity of the actively elongating form of RNA polymerase 2 (RNAPII) compared with inactive forms only in interactions between promoters and other elements. Contacts among promoters and between promoters and other elements have different characteristic epigenomic features. We identify a possible role for the elongating form of RNAPII in mediating interactions among promoters, enhancers, and transcribed gene bodies. Our approach facilitates the study of multiple genome-wide epigenomic profiles, considering network topology and allowing the comparison of chromatin interaction networks.

Prediction of redox-sensitive cysteines using sequential distance and other sequence-based features.

PubMed

Sun, Ming-An; Zhang, Qing; Wang, Yejun; Ge, Wei; Guo, Dianjing

2016-08-24

Reactive oxygen species can modify the structure and function of proteins and may also act as important signaling molecules in various cellular processes. Cysteine thiol groups of proteins are particularly susceptible to oxidation. Meanwhile, their reversible oxidation is of critical roles for redox regulation and signaling. Recently, several computational tools have been developed for predicting redox-sensitive cysteines; however, those methods either only focus on catalytic redox-sensitive cysteines in thiol oxidoreductases, or heavily depend on protein structural data, thus cannot be widely used. In this study, we analyzed various sequence-based features potentially related to cysteine redox-sensitivity, and identified three types of features for efficient computational prediction of redox-sensitive cysteines. These features are: sequential distance to the nearby cysteines, PSSM profile and predicted secondary structure of flanking residues. After further feature selection using SVM-RFE, we developed Redox-Sensitive Cysteine Predictor (RSCP), a SVM based classifier for redox-sensitive cysteine prediction using primary sequence only. Using 10-fold cross-validation on RSC758 dataset, the accuracy, sensitivity, specificity, MCC and AUC were estimated as 0.679, 0.602, 0.756, 0.362 and 0.727, respectively. When evaluated using 10-fold cross-validation with BALOSCTdb dataset which has structure information, the model achieved performance comparable to current structure-based method. Further validation using an independent dataset indicates it is robust and of relatively better accuracy for predicting redox-sensitive cysteines from non-enzyme proteins. In this study, we developed a sequence-based classifier for predicting redox-sensitive cysteines. The major advantage of this method is that it does not rely on protein structure data, which ensures more extensive application compared to other current implementations. Accurate prediction of redox-sensitive cysteines not only enhances our understanding about the redox sensitivity of cysteine, it may also complement the proteomics approach and facilitate further experimental investigation of important redox-sensitive cysteines.

Feature-oriented regional modeling and simulations in the Gulf of Maine and Georges Bank

NASA Astrophysics Data System (ADS)

Gangopadhyay, Avijit; Robinson, Allan R.; Haley, Patrick J.; Leslie, Wayne G.; Lozano, Carlos J.; Bisagni, James J.; Yu, Zhitao

2003-03-01

The multiscale synoptic circulation system in the Gulf of Maine and Georges Bank (GOMGB) region is presented using a feature-oriented approach. Prevalent synoptic circulation structures, or 'features', are identified from previous observational studies. These features include the buoyancy-driven Maine Coastal Current, the Georges Bank anticyclonic frontal circulation system, the basin-scale cyclonic gyres (Jordan, Georges and Wilkinson), the deep inflow through the Northeast Channel (NEC), the shallow outflow via the Great South Channel (GSC), and the shelf-slope front (SSF). Their synoptic water-mass ( T- S) structures are characterized and parameterized in a generalized formulation to develop temperature-salinity feature models. A synoptic initialization scheme for feature-oriented regional modeling and simulation (FORMS) of the circulation in the coastal-to-deep region of the GOMGB system is then developed. First, the temperature and salinity feature-model profiles are placed on a regional circulation template and then objectively analyzed with appropriate background climatology in the coastal region. Furthermore, these fields are melded with adjacent deep-ocean regional circulation (Gulf Stream Meander and Ring region) along and across the SSF. These initialization fields are then used for dynamical simulations via the primitive equation model. Simulation results are analyzed to calibrate the multiparameter feature-oriented modeling system. Experimental short-term synoptic simulations are presented for multiple resolutions in different regions with and without atmospheric forcing. The presented 'generic and portable' methodology demonstrates the potential of applying similar FORMS in many other regions of the Global Coastal Ocean.

Analysis of spike-wave discharges in rats using discrete wavelet transform.

PubMed

Ubeyli, Elif Derya; Ilbay, Gül; Sahin, Deniz; Ateş, Nurbay

2009-03-01

A feature is a distinctive or characteristic measurement, transform, structural component extracted from a segment of a pattern. Features are used to represent patterns with the goal of minimizing the loss of important information. The discrete wavelet transform (DWT) as a feature extraction method was used in representing the spike-wave discharges (SWDs) records of Wistar Albino Glaxo/Rijswijk (WAG/Rij) rats. The SWD records of WAG/Rij rats were decomposed into time-frequency representations using the DWT and the statistical features were calculated to depict their distribution. The obtained wavelet coefficients were used to identify characteristics of the signal that were not apparent from the original time domain signal. The present study demonstrates that the wavelet coefficients are useful in determining the dynamics in the time-frequency domain of SWD records.

Structural Similarities and Differences between Two Functionally Distinct SecA Proteins, Mycobacterium tuberculosis SecA1 and SecA2

PubMed Central

Swanson, Stephanie; Ioerger, Thomas R.; Rigel, Nathan W.; Miller, Brittany K.; Braunstein, Miriam

2015-01-01

ABSTRACT While SecA is the ATPase component of the major bacterial secretory (Sec) system, mycobacteria and some Gram-positive pathogens have a second paralog, SecA2. In bacteria with two SecA paralogs, each SecA is functionally distinct, and they cannot compensate for one another. Compared to SecA1, SecA2 exports a distinct and smaller set of substrates, some of which have roles in virulence. In the mycobacterial system, some SecA2-dependent substrates lack a signal peptide, while others contain a signal peptide but possess features in the mature protein that necessitate a role for SecA2 in their export. It is unclear how SecA2 functions in protein export, and one open question is whether SecA2 works with the canonical SecYEG channel to export proteins. In this study, we report the structure of Mycobacterium tuberculosis SecA2 (MtbSecA2), which is the first structure of any SecA2 protein. A high level of structural similarity is observed between SecA2 and SecA1. The major structural difference is the absence of the helical wing domain, which is likely to play a role in how MtbSecA2 recognizes its unique substrates. Importantly, structural features critical to the interaction between SecA1 and SecYEG are preserved in SecA2. Furthermore, suppressor mutations of a dominant-negative secA2 mutant map to the surface of SecA2 and help identify functional regions of SecA2 that may promote interactions with SecYEG or the translocating polypeptide substrate. These results support a model in which the mycobacterial SecA2 works with SecYEG. IMPORTANCE SecA2 is a paralog of SecA1, which is the ATPase of the canonical bacterial Sec secretion system. SecA2 has a nonredundant function with SecA1, and SecA2 exports a distinct and smaller set of substrates than SecA1. This work reports the crystal structure of SecA2 of Mycobacterium tuberculosis (the first SecA2 structure reported for any organism). Many of the structural features of SecA1 are conserved in the SecA2 structure, including putative contacts with the SecYEG channel. Several structural differences are also identified that could relate to the unique function and selectivity of SecA2. Suppressor mutations of a secA2 mutant map to the surface of SecA2 and help identify functional regions of SecA2 that may promote interactions with SecYEG. PMID:26668263

Structural and functional adaptations of the mammalian nuclear envelope to meet the meiotic requirements.

PubMed

Link, Jana; Jahn, Daniel; Alsheimer, Manfred

2015-01-01

Numerous studies in the past years provided definite evidence that the nuclear envelope is much more than just a simple barrier. It rather constitutes a multifunctional platform combining structural and dynamic features to fulfill many fundamental functions such as chromatin organization, regulation of transcription, signaling, but also structural duties like maintaining general nuclear architecture and shape. One additional and, without doubt, highly impressive aspect is the recently identified key function of selected nuclear envelope components in driving meiotic chromosome dynamics, which in turn is essential for accurate recombination and segregation of the homologous chromosomes. Here, we summarize the recent work identifying new key players in meiotic telomere attachment and movement and discuss the latest advances in our understanding of the actual function of the meiotic nuclear envelope.

Classifying Structures in the ISM with Machine Learning Techniques

NASA Astrophysics Data System (ADS)

Beaumont, Christopher; Goodman, A. A.; Williams, J. P.

2011-01-01

The processes which govern molecular cloud evolution and star formation often sculpt structures in the ISM: filaments, pillars, shells, outflows, etc. Because of their morphological complexity, these objects are often identified manually. Manual classification has several disadvantages; the process is subjective, not easily reproducible, and does not scale well to handle increasingly large datasets. We have explored to what extent machine learning algorithms can be trained to autonomously identify specific morphological features in molecular cloud datasets. We show that the Support Vector Machine algorithm can successfully locate filaments and outflows blended with other emission structures. When the objects of interest are morphologically distinct from the surrounding emission, this autonomous classification achieves >90% accuracy. We have developed a set of IDL-based tools to apply this technique to other datasets.

Immediate effects of EVA midsole resilience and upper shoe structure on running biomechanics: a machine learning approach

PubMed Central

Gavião Neto, Wilson P.; Roveri, Maria Isabel; Oliveira, Wagner R.

2017-01-01

Background Resilience of midsole material and the upper structure of the shoe are conceptual characteristics that can interfere in running biomechanics patterns. Artificial intelligence techniques can capture features from the entire waveform, adding new perspective for biomechanical analysis. This study tested the influence of shoe midsole resilience and upper structure on running kinematics and kinetics of non-professional runners by using feature selection, information gain, and artificial neural network analysis. Methods Twenty-seven experienced male runners (63 ± 44 km/week run) ran in four-shoe design that combined two resilience-cushioning materials (low and high) and two uppers (minimalist and structured). Kinematic data was acquired by six infrared cameras at 300 Hz, and ground reaction forces were acquired by two force plates at 1,200 Hz. We conducted a Machine Learning analysis to identify features from the complete kinematic and kinetic time series and from 42 discrete variables that had better discriminate the four shoes studied. For that analysis, we built an input data matrix of dimensions 1,080 (10 trials × 4 shoes × 27 subjects) × 1,254 (3 joints × 3 planes of movement × 101 data points + 3 vectors forces × 101 data points + 42 discrete calculated kinetic and kinematic features). Results The applied feature selection by information gain and artificial neural networks successfully differentiated the two resilience materials using 200(16%) biomechanical variables with an accuracy of 84.8% by detecting alterations of running biomechanics, and the two upper structures with an accuracy of 93.9%. Discussion The discrimination of midsole resilience resulted in lower accuracy levels than did the discrimination of the shoe uppers. In both cases, the ground reaction forces were among the 25 most relevant features. The resilience of the cushioning material caused significant effects on initial heel impact, while the effects of different uppers were distributed along the stance phase of running. Biomechanical changes due to shoe midsole resilience seemed to be subject-dependent, while those due to upper structure seemed to be subject-independent. PMID:28265506

Immediate effects of EVA midsole resilience and upper shoe structure on running biomechanics: a machine learning approach.

PubMed

Onodera, Andrea N; Gavião Neto, Wilson P; Roveri, Maria Isabel; Oliveira, Wagner R; Sacco, Isabel Cn

2017-01-01

Resilience of midsole material and the upper structure of the shoe are conceptual characteristics that can interfere in running biomechanics patterns. Artificial intelligence techniques can capture features from the entire waveform, adding new perspective for biomechanical analysis. This study tested the influence of shoe midsole resilience and upper structure on running kinematics and kinetics of non-professional runners by using feature selection, information gain, and artificial neural network analysis. Twenty-seven experienced male runners (63 ± 44 km/week run) ran in four-shoe design that combined two resilience-cushioning materials (low and high) and two uppers (minimalist and structured). Kinematic data was acquired by six infrared cameras at 300 Hz, and ground reaction forces were acquired by two force plates at 1,200 Hz. We conducted a Machine Learning analysis to identify features from the complete kinematic and kinetic time series and from 42 discrete variables that had better discriminate the four shoes studied. For that analysis, we built an input data matrix of dimensions 1,080 (10 trials × 4 shoes × 27 subjects) × 1,254 (3 joints × 3 planes of movement × 101 data points + 3 vectors forces × 101 data points + 42 discrete calculated kinetic and kinematic features). The applied feature selection by information gain and artificial neural networks successfully differentiated the two resilience materials using 200(16%) biomechanical variables with an accuracy of 84.8% by detecting alterations of running biomechanics, and the two upper structures with an accuracy of 93.9%. The discrimination of midsole resilience resulted in lower accuracy levels than did the discrimination of the shoe uppers. In both cases, the ground reaction forces were among the 25 most relevant features. The resilience of the cushioning material caused significant effects on initial heel impact, while the effects of different uppers were distributed along the stance phase of running. Biomechanical changes due to shoe midsole resilience seemed to be subject-dependent, while those due to upper structure seemed to be subject-independent.

Spiders: water-driven erosive structures in the southern hemisphere of Mars.

PubMed

Prieto-Ballesteros, Olga; Fernández-Remolar, David C; Rodríguez-Manfredi, José Antonio; Selsis, Franck; Manrubia, Susanna C

2006-08-01

Recent data from space missions reveal that there are ongoing climatic changes and erosive processes that continuously modify surface features of Mars. We have investigated the seasonal dynamics of a number of morphological features located at Inca City, a representative area at high southern latitude that has undergone seasonal processes. By integrating visual information from the Mars Orbiter Camera on board the Mars Global Surveyor and climatic cycles from a Mars' General Circulation Model, and considering the recently reported evidence for the presence of water-ice and aqueous precipitates on Mars, we propose that a number of the erosive features identified in Inca City, among them spiders, result from the seasonal melting of aqueous salty solutions.

Role of artesian groundwater in forming Martian permafrost features

NASA Technical Reports Server (NTRS)

Howard, Alan D.

1991-01-01

Various landforms possibly related to formation (growth), movement, or decay of ground ice have been identified on Mars, including fretted terrain (ft) and associated lobate debris aprons (lda), the chaotic terrain, concentric crater fills (ccf), polygonal ground, softened terrain, small domes that are possibly pingos, and curvilinear (fingerprint) features (cuf). Glaciers may also have been present. Some of these may involve ice derived from artesian groundwater. Topical areas of discussion are: Mars groundwater and the location of permafrost features; the ft, lda, ccf, and cuf; role of artesian groundwater in formation of fretted terrain, lobate debris blankets, and concentric crater fills; sources of glacial ice; and pingos and other pseudovolcanic structures.

Spatial Relationships of Auroral Particle Acceleration Relative to High Latitude Plasma Boundaries

NASA Technical Reports Server (NTRS)

Ghielmetti, Arthur G.

1997-01-01

This final report describes the activities under NASA contract to Lockheed Missiles and Space Company. It covers the period from 10-1-94 to 12-31-97. The objective of this investigation is to identify and characterize the spatial relationships of auroral particle acceleration features relative to the characteristic transition features in the surrounding polar ionospheric plasmas. Due to the reduced funding level approved for this contract, the original scope of the proposed work was readjusted with the focus placed on examining spatial relationships with respect to particle structures.

Application of multispectral photography to mineral and land resources of South Carolina

NASA Technical Reports Server (NTRS)

Olson, N. K. (Principal Investigator)

1975-01-01

The author has identified the following significant results. Good results were obtained from using Skylab photography in conjunction with LANDSAT imagery for visual interpretation of various geologic features, particularly lineaments. It was concluded that visual interpretation alone of Skylab photographs was quite limited, and much of this was because of the low contrast, heavily vegetated terrain in southeastern United States. Lineaments of major structural features are detectable but subtle. An intimate knowledge of the geologic field relationships is needed before a meaningful analysis is feasible using current satellite photography alone.

Lagrangian motion, coherent structures, and lines of persistent material strain.

PubMed

Samelson, R M

2013-01-01

Lagrangian motion in geophysical fluids may be strongly influenced by coherent structures that support distinct regimes in a given flow. The problems of identifying and demarcating Lagrangian regime boundaries associated with dynamical coherent structures in a given velocity field can be studied using approaches originally developed in the context of the abstract geometric theory of ordinary differential equations. An essential insight is that when coherent structures exist in a flow, Lagrangian regime boundaries may often be indicated as material curves on which the Lagrangian-mean principal-axis strain is large. This insight is the foundation of many numerical techniques for identifying such features in complex observed or numerically simulated ocean flows. The basic theoretical ideas are illustrated with a simple, kinematic traveling-wave model. The corresponding numerical algorithms for identifying candidate Lagrangian regime boundaries and lines of principal Lagrangian strain (also called Lagrangian coherent structures) are divided into parcel and bundle schemes; the latter include the finite-time and finite-size Lyapunov exponent/Lagrangian strain (FTLE/FTLS and FSLE/FSLS) metrics. Some aspects and results of oceanographic studies based on these approaches are reviewed, and the results are discussed in the context of oceanographic observations of dynamical coherent structures.

Synthesis temperature effect on the structural features and optical absorption of Zn(1-x)Co(x)Al2O4 oxides.

PubMed

Gaudon, M; Apheceixborde, A; Ménétrier, M; Le Nestour, A; Demourgues, A

2009-10-05

Zinc/cobalt aluminates with spinel-type structure were prepared by a polymeric route, leading to a pure phase with controlled grain size. The prepared pigments were characterized by powder X-ray diffraction Rietveld analyses in order to determine structural features, scanning electron microscopy for morphological investigation, helium pycnometry and (27)Al MAS NMR in order to highlight the occurrence of defects inside the structure, and UV-visible-near-IR spectroscopy to identify electronic transitions responsible for the compounds' color. The green-blue coloration of these pigments is known to be dependent on the sample thermal history. Here, for the first time, the Zn(1-x)Co(x)Al(2)O(4) color is newly interpreted. The pigment is green once synthesized at low temperature (i.e., with diminution of the pigment grain size); this variation was attributed to the appearance of a new absorption band located at about 500 nm, linked to a complex network feature involving Co ions in octahedral sites as well as oxygen and cationic vacancies. Hence, this work shows the possibility of easily getting a nonstoichiometric network with an abnormal cationic distribution from "chimie douce" processes with moderate synthesis temperature, and so various colorations for the same composition.

Structural Features of a Picornavirus Polymerase Involved in the Polyadenylation of Viral RNA

PubMed Central

Kempf, Brian J.; Kelly, Michelle M.; Springer, Courtney L.; Peersen, Olve B.

2013-01-01

Picornaviruses have 3′ polyadenylated RNA genomes, but the mechanisms by which these genomes are polyadenylated during viral replication remain obscure. Based on prior studies, we proposed a model wherein the poliovirus RNA-dependent RNA polymerase (3Dpol) uses a reiterative transcription mechanism while replicating the poly(A) and poly(U) portions of viral RNA templates. To further test this model, we examined whether mutations in 3Dpol influenced the polyadenylation of virion RNA. We identified nine alanine substitution mutations in 3Dpol that resulted in shorter or longer 3′ poly(A) tails in virion RNA. These mutations could disrupt structural features of 3Dpol required for the recruitment of a cellular poly(A) polymerase; however, the structural orientation of these residues suggests a direct role of 3Dpol in the polyadenylation of RNA genomes. Reaction mixtures containing purified 3Dpol and a template RNA with a defined poly(U) sequence provided data consistent with a template-dependent reiterative transcription mechanism for polyadenylation. The phylogenetically conserved structural features of 3Dpol involved in the polyadenylation of virion RNA include a thumb domain alpha helix that is positioned in the minor groove of the double-stranded RNA product and lysine and arginine residues that interact with the phosphates of both the RNA template and product strands. PMID:23468507

Structure of the Triatoma virus capsid

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

Squires, Gaëlle; Pous, Joan; Agirre, Jon

The crystallographic structure of TrV shows specific morphological and functional features that clearly distinguish it from the type species of the Cripavirus genus, CrPV. The members of the Dicistroviridae family are non-enveloped positive-sense single-stranded RNA (+ssRNA) viruses pathogenic to beneficial arthropods as well as insect pests of medical importance. Triatoma virus (TrV), a member of this family, infects several species of triatomine insects (popularly named kissing bugs), which are vectors for human trypanosomiasis, more commonly known as Chagas disease. The potential use of dicistroviruses as biological control agents has drawn considerable attention in the past decade, and several viruses ofmore » this family have been identified, with their targets covering honey bees, aphids and field crickets, among others. Here, the crystal structure of the TrV capsid at 2.5 Å resolution is reported, showing that as expected it is very similar to that of Cricket paralysis virus (CrPV). Nevertheless, a number of distinguishing structural features support the introduction of a new genus (Triatovirus; type species TrV) under the Dicistroviridae family. The most striking differences are the absence of icosahedrally ordered VP4 within the infectious particle and the presence of prominent projections that surround the fivefold axis. Furthermore, the structure identifies a second putative autoproteolytic DDF motif in protein VP3, in addition to the conserved one in VP1 which is believed to be responsible for VP0 cleavage during capsid maturation. The potential meaning of these new findings is discussed.« less

The prediction of airborne and structure-borne noise potential for a tire

NASA Astrophysics Data System (ADS)

Sakamoto, Nicholas Y.

Tire/pavement interaction noise is a major component of both exterior pass-by noise and vehicle interior noise. The current testing methods for ranking tires from loud to quiet require expensive equipment, multiple tires, and/or long experimental set-up and run times. If a laboratory based off-vehicle test could be used to identify the airborne and structure-borne potential of a tire from its dynamic characteristics, a relative ranking of a large group of tires could be performed at relatively modest expense. This would provide a smaller sample set of tires for follow-up testing and thus save expense for automobile OEMs. The focus of this research was identifying key noise features from a tire/pavement experiment. These results were compared against a stationary tire test in which the natural response of the tire to a forced input was measured. Since speed was identified as having some effect on the noise, an input function was also developed to allow the tires to be ranked at an appropriate speed. A relative noise model was used on a second sample set of tires to verify if the ranking could be used against interior vehicle measurements. While overall level analysis of the specified spectrum had mixed success, important noise generating features were identified, and the methods used could be improved to develop a standard off-vehicle test to predict a tire's noise potential.

Seismically-induced soft-sediment deformation structures associated with the Magallanes-Fagnano Fault System (Isla Grande de Tierra del Fuego, Argentina)

NASA Astrophysics Data System (ADS)

Onorato, M. Romina; Perucca, Laura; Coronato, Andrea; Rabassa, Jorge; López, Ramiro

2016-10-01

In this paper, evidence of paleoearthquake-induced soft-sediment deformation structures associated with the Magallanes-Fagnano Fault System in the Isla Grande de Tierra del Fuego, southern Argentina, has been identified. Well-preserved soft-sediment deformation structures were found in a Holocene sequence of the Udaeta pond. These structures were analyzed in terms of their geometrical characteristics, deformation mechanism, driving force system and possible trigger agent. They were also grouped in different morphological types: sand dykes, convolute lamination, load structures and faulted soft-sediment deformation features. Udaeta, a small pond in Argentina Tierra del Fuego, is considered a Quaternary pull-apart basin related to the Magallanes-Fagnano Fault System. The recognition of these seismically-induced features is an essential tool for paleoseismic studies. Since the three main urban centers in the Tierra del Fuego province of Argentina (Ushuaia, Río Grande and Tolhuin) have undergone an explosive growth in recent years, the results of this study will hopefully contribute to future analyses of the seismic risk of the region.

Application of Functional Use Predictions to Aid in Structure ...

EPA Pesticide Factsheets

Humans are potentially exposed to thousands of anthropogenic chemicals in commerce. Recent work has shown that the bulk of this exposure may occur in near-field indoor environments (e.g., home, school, work, etc.). Advances in suspect screening analyses (SSA) now allow an improved understanding of the chemicals present in these environments. However, due to the nature of suspect screening techniques, investigators are often left with chemical formula predictions, with the possibility of many chemical structures matching to each formula. Here, newly developed quantitative structure-use relationship (QSUR) models are used to identify potential exposure sources for candidate structures. Previously, a suspect screening workflow was introduced and applied to house dust samples collected from the U.S. Department of Housing and Urban Development’s American Healthy Homes Survey (AHHS) [Rager, et al., Env. Int. 88 (2016)]. This workflow utilized the US EPA’s Distributed Structure-Searchable Toxicity (DSSTox) Database to link identified molecular features to molecular formulas, and ultimately chemical structures. Multiple QSUR models were applied to support the evaluation of candidate structures. These QSURs predict the likelihood of a chemical having a functional use commonly associated with consumer products having near-field use. For 3,228 structures identified as possible chemicals in AHHS house dust samples, we were able to obtain the required descriptors to appl

Development of lower Triassic wrinkle structures: implications for the search for life on other planets.

PubMed

Mata, Scott A; Bottjer, David J

2009-11-01

Wrinkle structures are microbially mediated sedimentary structures that are a common feature of Proterozoic and earliest Phanerozoic siliciclastic seafloors on Earth and occur only rarely in post-Cambrian strata. These macroscopic microbially induced sedimentary structures are readily identifiable at the outcrop scale, and their recognition on other planetary bodies by landed missions may suggest the presence of past microbial life. Wrinkle structures of the Lower Triassic (Spathian) Virgin Limestone Member of the Moenkopi Formation in the western United States record an occurrence of widespread microbialite formation in the wake of the end-Permian mass extinction, the largest biotic crisis of the Phanerozoic. Wrinkle structures occur on proximal sandy tempestites deposited within the offshore transition. Storm layers appear to have been rapidly colonized by microbial mats and were subsequently buried by mud during fair-weather conditions. Wrinkle structures exhibit flat-topped crests and sinuous troughs, with associated mica grains oriented parallel to bedding, suggestive of trapping and binding activity. Although Lower Triassic wrinkle structures postdate the widespread occurrence of these features during the Proterozoic and Cambrian, they exhibit many of the same characteristics and environmental trends, which suggests a conservation of microbial formational and preservational processes in subtidal siliciclastic settings on Earth from the Precambrian into the Phanerozoic. In the search for extraterrestrial life, it may be these conservative characteristics that prove to be the most useful and robust for recognizing microbial features on other planetary bodies, and may add to an ever-growing foundation of knowledge for directing future explorations aimed at seeking out macroscopic microbial signatures.

Identification of DNA primase inhibitors via a combined fragment-based and virtual screening

NASA Astrophysics Data System (ADS)

Ilic, Stefan; Akabayov, Sabine R.; Arthanari, Haribabu; Wagner, Gerhard; Richardson, Charles C.; Akabayov, Barak

2016-11-01

The structural differences between bacterial and human primases render the former an excellent target for drug design. Here we describe a technique for selecting small molecule inhibitors of the activity of T7 DNA primase, an ideal model for bacterial primases due to their common structural and functional features. Using NMR screening, fragment molecules that bind T7 primase were identified and then exploited in virtual filtration to select larger molecules from the ZINC database. The molecules were docked to the primase active site using the available primase crystal structure and ranked based on their predicted binding energies to identify the best candidates for functional and structural investigations. Biochemical assays revealed that some of the molecules inhibit T7 primase-dependent DNA replication. The binding mechanism was delineated via NMR spectroscopy. Our approach, which combines fragment based and virtual screening, is rapid and cost effective and can be applied to other targets.

Dynamics of feature categorization.

PubMed

Martí, Daniel; Rinzel, John

2013-01-01

In visual and auditory scenes, we are able to identify shared features among sensory objects and group them according to their similarity. This grouping is preattentive and fast and is thought of as an elementary form of categorization by which objects sharing similar features are clustered in some abstract perceptual space. It is unclear what neuronal mechanisms underlie this fast categorization. Here we propose a neuromechanistic model of fast feature categorization based on the framework of continuous attractor networks. The mechanism for category formation does not rely on learning and is based on biologically plausible assumptions, for example, the existence of populations of neurons tuned to feature values, feature-specific interactions, and subthreshold-evoked responses upon the presentation of single objects. When the network is presented with a sequence of stimuli characterized by some feature, the network sums the evoked responses and provides a running estimate of the distribution of features in the input stream. If the distribution of features is structured into different components or peaks (i.e., is multimodal), recurrent excitation amplifies the response of activated neurons, and categories are singled out as emerging localized patterns of elevated neuronal activity (bumps), centered at the centroid of each cluster. The emergence of bump states through sequential, subthreshold activation and the dependence on input statistics is a novel application of attractor networks. We show that the extraction and representation of multiple categories are facilitated by the rich attractor structure of the network, which can sustain multiple stable activity patterns for a robust range of connectivity parameters compatible with cortical physiology.

A daily global mesoscale ocean eddy dataset from satellite altimetry.

PubMed

Faghmous, James H; Frenger, Ivy; Yao, Yuanshun; Warmka, Robert; Lindell, Aron; Kumar, Vipin

2015-01-01

Mesoscale ocean eddies are ubiquitous coherent rotating structures of water with radial scales on the order of 100 kilometers. Eddies play a key role in the transport and mixing of momentum and tracers across the World Ocean. We present a global daily mesoscale ocean eddy dataset that contains ~45 million mesoscale features and 3.3 million eddy trajectories that persist at least two days as identified in the AVISO dataset over a period of 1993-2014. This dataset, along with the open-source eddy identification software, extract eddies with any parameters (minimum size, lifetime, etc.), to study global eddy properties and dynamics, and to empirically estimate the impact eddies have on mass or heat transport. Furthermore, our open-source software may be used to identify mesoscale features in model simulations and compare them to observed features. Finally, this dataset can be used to study the interaction between mesoscale ocean eddies and other components of the Earth System.

A daily global mesoscale ocean eddy dataset from satellite altimetry

PubMed Central

Faghmous, James H.; Frenger, Ivy; Yao, Yuanshun; Warmka, Robert; Lindell, Aron; Kumar, Vipin

2015-01-01

Mesoscale ocean eddies are ubiquitous coherent rotating structures of water with radial scales on the order of 100 kilometers. Eddies play a key role in the transport and mixing of momentum and tracers across the World Ocean. We present a global daily mesoscale ocean eddy dataset that contains ~45 million mesoscale features and 3.3 million eddy trajectories that persist at least two days as identified in the AVISO dataset over a period of 1993–2014. This dataset, along with the open-source eddy identification software, extract eddies with any parameters (minimum size, lifetime, etc.), to study global eddy properties and dynamics, and to empirically estimate the impact eddies have on mass or heat transport. Furthermore, our open-source software may be used to identify mesoscale features in model simulations and compare them to observed features. Finally, this dataset can be used to study the interaction between mesoscale ocean eddies and other components of the Earth System. PMID:26097744

Territory and nest site selection patterns by Grasshopper Sparrows in southeastern Arizona

USGS Publications Warehouse

Ruth, Janet M.; Skagen, Susan K.

2017-01-01

Grassland bird populations are showing some of the greatest rates of decline of any North American birds, prompting measures to protect and improve important habitat. We assessed how vegetation structure and composition, habitat features often targeted for management, affected territory and nest site selection by Grasshopper Sparrows (Ammodramus savannarum ammolegus) in southeastern Arizona. To identify features important to males establishing territories, we compared vegetation characteristics of known territories and random samples on 2 sites over 5 years. We examined habitat selection patterns of females by comparing characteristics of nest sites with territories over 3 years. Males selected territories in areas of sparser vegetation structure and more tall shrubs (>2 m) than random plots on the site with low shrub densities. Males did not select territories based on the proportion of exotic grasses. Females generally located nest sites in areas with lower small shrub (1–2 m tall) densities than territories overall when possible and preferentially selected native grasses for nest construction. Whether habitat selection was apparent depended upon the range of vegetation structure that was available. We identified an upper threshold above which grass structure seemed to be too high and dense for Grasshopper Sparrows. Our results suggest that some management that reduces vegetative structure may benefit this species in desert grasslands at the nest and territory scale. However, we did not assess initial male habitat selection at a broader landscape scale where their selection patterns may be different and could be influenced by vegetation density and structure outside the range of values sampled in this study.

Limited Documentation and Treatment Quality of Glycemic Inpatient Care in Relation to Structural Deficits of Heterogeneous Insulin Charts at a Large University Hospital.

PubMed

Kopanz, Julia; Lichtenegger, Katharina M; Sendlhofer, Gerald; Semlitsch, Barbara; Cuder, Gerald; Pak, Andreas; Pieber, Thomas R; Tax, Christa; Brunner, Gernot; Plank, Johannes

2018-02-09

Insulin charts represent a key component in the inpatient glycemic management process. The aim was to evaluate the quality of structure, documentation, and treatment of diabetic inpatient care to design a new standardized insulin chart for a large university hospital setting. Historically grown blank insulin charts in use at 39 general wards were collected and evaluated for quality structure features. Documentation and treatment quality were evaluated in a consecutive snapshot audit of filled-in charts. The primary end point was the percentage of charts with any medication error. Overall, 20 different blank insulin charts with variable designs and significant structural deficits were identified. A medication error occurred in 55% of the 102 audited filled-in insulin charts, consisting of prescription and management errors in 48% and 16%, respectively. Charts of insulin-treated patients had more medication errors relative to patients treated with oral medication (P < 0.01). Chart design did support neither clinical authorization of individual insulin prescription (10%), nor insulin administration confirmed by nurses' signature (25%), nor treatment of hypoglycemia (0%), which resulted in a reduced documentation and treatment quality in clinical practice 7%, 30%, 25%, respectively. A multitude of charts with variable design characteristics and structural deficits were in use across the inpatient wards. More than half of the inpatients had a chart displaying a medication error. Lack of structure quality features of the charts had an impact on documentation and treatment quality. Based on identified deficits and international standards, a new insulin chart was developed to overcome these quality hurdles.

Identification of Amnestic Mild Cognitive Impairment Using Multi-Modal Brain Features: A Combined Structural MRI and Diffusion Tensor Imaging Study.

PubMed

Xie, Yunyan; Cui, Zaixu; Zhang, Zhongmin; Sun, Yu; Sheng, Can; Li, Kuncheng; Gong, Gaolang; Han, Ying; Jia, Jianping

2015-01-01

Identifying amnestic mild cognitive impairment (aMCI) is of great clinical importance because aMCI is a putative prodromal stage of Alzheimer's disease. The present study aimed to explore the feasibility of accurately identifying aMCI with a magnetic resonance imaging (MRI) biomarker. We integrated measures of both gray matter (GM) abnormalities derived from structural MRI and white matter (WM) alterations acquired from diffusion tensor imaging at the voxel level across the entire brain. In particular, multi-modal brain features, including GM volume, WM fractional anisotropy, and mean diffusivity, were extracted from a relatively large sample of 64 Han Chinese aMCI patients and 64 matched controls. Then, support vector machine classifiers for GM volume, FA, and MD were fused to distinguish the aMCI patients from the controls. The fused classifier was evaluated with the leave-one-out and the 10-fold cross-validations, and the classifier had an accuracy of 83.59% and an area under the curve of 0.862. The most discriminative regions of GM were mainly located in the medial temporal lobe, temporal lobe, precuneus, cingulate gyrus, parietal lobe, and frontal lobe, whereas the most discriminative regions of WM were mainly located in the corpus callosum, cingulum, corona radiata, frontal lobe, and parietal lobe. Our findings suggest that aMCI is characterized by a distributed pattern of GM abnormalities and WM alterations that represent discriminative power and reflect relevant pathological changes in the brain, and these changes further highlight the advantage of multi-modal feature integration for identifying aMCI.

Identification of deep magnetized structures in the tectonically active Chlef area (Algeria) from aeromagnetic data using wavelet and ridgelet transforms

NASA Astrophysics Data System (ADS)

Boukerbout, H.; Abtout, A.; Gibert, D.; Henry, B.; Bouyahiaoui, B.; Derder, M. E. M.

2018-07-01

The Chlef region constitutes a key area to study neotectonics structures and their geodynamical context. Aeromagnetic data analyzed using different processing methods (shaded relief technique, computation of vertical gradient, upward continuation, use of the continuous wavelet transform and ridgelet transform), allow establishing a structural image of emerging and deep structures both onshore and offshore. Magnetic anomalies, over the Mediterranean Sea, the Chlef basin and the Ouarsenis Mounts, are well-correlated with the known geological structures. Long and short wavelength anomalies have been distinguished. The short wavelength anomalies are associated with the volcanic rocks on the coast from Chenoua to El Marsa and with the basement in the Boukadir zone in the sedimentary Chlef basin. The long wavelength anomalies to the South are associated mainly with deep E-W structures, limiting the Chlef basin. To the North, similar structures have been identified in the Mediterranean Sea. The compilation of the identified magnetic features leads to geometrical shape corroborating the structure in blocks of the Chlef basin.

Structural and spectroscopic features of proton hydrates in the crystalline state. Solid-state DFT study on HCl and triflic acid hydrates

NASA Astrophysics Data System (ADS)

Vener, M. V.; Chernyshov, I. Yu.; Rykounov, A. A.; Filarowski, A.

2018-01-01

Crystalline HCl and CF3SO3H hydrates serve as excellent model systems for protonated water and perfluorosulphonic acid membranes, respectively. They contain characteristic H3O+, H5О+2, H7О+3 and H3O+(H2O)3 (the Eigen cation) structures. The properties of these cations in the crystalline hydrates of strong monobasic acids are studied by solid-state density function theory (DFT). Simultaneous consideration of the HCl and CF3SO3H hydrates reveals the impact of the size of a counter ion and the crystalline environment on the structure and infrared active bands of the simplest proton hydrates. The H7O+3 structure is very sensitive to the size of the counter ion and symmetry of the local environment. This makes it virtually impossible to identify the specific features of H7O+3 in molecular crystals. The H3O+ ion can be treated as the Eigen-like cation in the crystalline state. Structural, infrared and electron-density features of H5О+2 and the Eigen cation are virtually insensitive to the size of the counter ion and the symmetry of the local crystalline environment. These cations can be considered as the simplest stable proton hydrates in the condensed phase. Finally, the influence of the Grimme correction on the structure and harmonic frequencies of the molecular crystals with short (strong) intermolecular O-H···O bonds is discussed.

Key structural features of nonsteroidal ligands for binding and activation of the androgen receptor.

PubMed

Yin, Donghua; He, Yali; Perera, Minoli A; Hong, Seoung Soo; Marhefka, Craig; Stourman, Nina; Kirkovsky, Leonid; Miller, Duane D; Dalton, James T

2003-01-01

The purposes of the present studies were to examine the androgen receptor (AR) binding ability and in vitro functional activity of multiple series of nonsteroidal compounds derived from known antiandrogen pharmacophores and to investigate the structure-activity relationships (SARs) of these nonsteroidal compounds. The AR binding properties of sixty-five nonsteroidal compounds were assessed by a radioligand competitive binding assay with the use of cytosolic AR prepared from rat prostates. The AR agonist and antagonist activities of high-affinity ligands were determined by the ability of the ligand to regulate AR-mediated transcriptional activation in cultured CV-1 cells, using a cotransfection assay. Nonsteroidal compounds with diverse structural features demonstrated a wide range of binding affinity for the AR. Ten compounds, mainly from the bicalutamide-related series, showed a binding affinity superior to the structural pharmacophore from which they were derived. Several SARs regarding nonsteroidal AR binding were revealed from the binding data, including stereoisomeric conformation, steric effect, and electronic effect. The functional activity of high-affinity ligands ranged from antagonist to full agonist for the AR. Several structural features were found to be determinative of agonist and antagonist activities. The nonsteroidal AR agonists identified from the present studies provided a pool of candidates for further development of selective androgen receptor modulators (SARMs) for androgen therapy. Also, these studies uncovered or confirmed numerous important SARs governing AR binding and functional properties by nonsteroidal molecules, which would be valuable in the future structural optimization of SARMs.

Reliability and validity of the Symptoms of Depression Questionnaire (SDQ)

PubMed Central

Pedrelli, Paola; Blais, Mark A.; Alpert, Jonathan E.; Shelton, Richard C.; Walker, Rosemary S. W.; Fava, Maurizio

2015-01-01

Current measures for major depressive disorder focus primarily on the assessment of depressive symptoms, while often omitting other common features. However, the presence of comorbid features in the anxiety spectrum influences outcome and may effect treatment. More comprehensive measures of depression are needed that include the assessment of symptoms in the anxiety–depression spectrum. This study examines the reliability and validity of the Symptoms of Depression Questionnaire (SDQ), which assesses irritability, anger attacks, and anxiety symptoms together with the commonly considered symptoms of depression. Analysis of the factor structure of the SDQ identified 5 subscales, including one in the anxiety–depression spectrum, with adequate internal consistency and concurrent validity. The SDQ may be a valuable new tool to better characterize depression and identify and administer more targeted interventions. PMID:25275853

Identifying Risk and Promoting Resilience in Infants and Toddlers with Fetal Alcohol Spectrum Disorders

ERIC Educational Resources Information Center

Shah, Prachi; Milgrom, Tedi; Munzer, Tiffany; Hoyme, H. Eugene

2015-01-01

Fetal alcohol spectrum disorders (FASDs) is an umbrella term that describes a variety of conditions characterized by a pattern of atypical facial features, growth restriction, structural physical abnormalities, and brain dysfunction resulting from prenatal alcohol exposure. Studies suggest that the prevalence of FASDs ranges between 2-5% (of the…

Applications of Location Similarity Measures and Conceptual Spaces to Event Coreference and Classification

ERIC Educational Resources Information Center

McConky, Katie Theresa

2013-01-01

This work covers topics in event coreference and event classification from spoken conversation. Event coreference is the process of identifying descriptions of the same event across sentences, documents, or structured databases. Existing event coreference work focuses on sentence similarity models or feature based similarity models requiring slot…

Modeling and Measuring the Structure of Professional Vision in Preservice Teachers

ERIC Educational Resources Information Center

Seidel, Tina; Stürmer, Kathleen

2014-01-01

Professional vision has been identified as an important element of teacher expertise that can be developed in teacher education. It describes the use of knowledge to notice and interpret significant features of classroom situations. Three aspects of professional vision have been described by qualitative research: describe, explain, and predict…

Distribution and Features of the Six Classes of Peroxiredoxins

PubMed Central

Poole, Leslie B.; Nelson, Kimberly J.

2016-01-01

Peroxiredoxins are cysteine-dependent peroxide reductases that group into 6 different, structurally discernable classes. In 2011, our research team reported the application of a bioinformatic approach called active site profiling to extract active site-proximal sequence segments from the 29 distinct, structurally-characterized peroxiredoxins available at the time. These extracted sequences were then used to create unique profiles for the six groups which were subsequently used to search GenBank(nr), allowing identification of ∼3500 peroxiredoxin sequences and their respective subgroups. Summarized in this minireview are the features and phylogenetic distributions of each of these peroxiredoxin subgroups; an example is also provided illustrating the use of the web accessible, searchable database known as PREX to identify subfamily-specific peroxiredoxin sequences for the organism Vitis vinifera (grape). PMID:26810075

Inhomogeneous kinetic effects related to intermittent magnetic discontinuities

NASA Astrophysics Data System (ADS)

Greco, A.; Valentini, F.; Servidio, S.; Matthaeus, W. H.

2012-12-01

A connection between kinetic processes and two-dimensional intermittent plasma turbulence is observed using direct numerical simulations of a hybrid Vlasov-Maxwell model, in which the Vlasov equation is solved for protons, while the electrons are described as a massless fluid. During the development of turbulence, the proton distribution functions depart from the typical configuration of local thermodynamic equilibrium, displaying statistically significant non-Maxwellian features. In particular, temperature anisotropy and distortions are concentrated near coherent structures, generated as the result of the turbulent cascade, such as current sheets, which are nonuniformly distributed in space. Here, the partial variance of increments (PVI) method has been employed to identify high magnetic stress regions within a two-dimensional turbulent pattern. A quantitative association between non-Maxwellian features and coherent structures is established.

Analysis of ERTS imagery of Wyoming and its application to evaluation of Wyoming's natural resources

NASA Technical Reports Server (NTRS)

Houston, R. S. (Principal Investigator); Marrs, R. W.

1972-01-01

The author has identified the following significant results. The Wyoming ERTS investigation has been hindered only slightly by incomplete ERTS data sets and lack of coverage. Efforts to map cultural development, vegetation distributions, and various geomorphologic features are underway. Tectonic analysis of the Rock Springs area has isolated two linear features that may be very significant with regard to the regional structure of central Wyoming. Studies of the fracture systems of the Wind River Mountains are being completed. The fracture map, constructed from ERTS-1 interpretations, contains a great deal of structural information which was previously unavailable. Mapping of the Precambrian metasedimentary and metavolcanic terrain of the Granite Mountains is nearing completion, and interpretation of ERTS supporting aircraft data has revealed deposits of iron formation.

Second harmonic generation microscopy differentiates collagen type I and type III in COPD

NASA Astrophysics Data System (ADS)

Suzuki, Masaru; Kayra, Damian; Elliott, W. Mark; Hogg, James C.; Abraham, Thomas

2012-03-01

The structural remodeling of extracellular matrix proteins in peripheral lung region is an important feature in chronic obstructive pulmonary disease (COPD). Multiphoton microscopy is capable of inducing specific second harmonic generation (SHG) signal from non-centrosymmetric structural proteins such as fibrillar collagens. In this study, SHG microscopy was used to examine structural remodeling of the fibrillar collagens in human lungs undergoing emphysematous destruction (n=2). The SHG signals originating from these diseased lung thin sections from base to apex (n=16) were captured simultaneously in both forward and backward directions. We found that the SHG images detected in the forward direction showed well-developed and well-structured thick collagen fibers while the SHG images detected in the backward direction showed striking different morphological features which included the diffused pattern of forward detected structures plus other forms of collagen structures. Comparison of these images with the wellestablished immunohistochemical staining indicated that the structures detected in the forward direction are primarily the thick collagen type I fibers and the structures identified in the backward direction are diffusive structures of forward detected collagen type I plus collagen type III. In conclusion, we here demonstrate the feasibility of SHG microscopy in differentiating fibrillar collagen subtypes and understanding their remodeling in diseased lung tissues.

Sequential structural damage diagnosis algorithm using a change point detection method

NASA Astrophysics Data System (ADS)

Noh, H.; Rajagopal, R.; Kiremidjian, A. S.

2013-11-01

This paper introduces a damage diagnosis algorithm for civil structures that uses a sequential change point detection method. The general change point detection method uses the known pre- and post-damage feature distributions to perform a sequential hypothesis test. In practice, however, the post-damage distribution is unlikely to be known a priori, unless we are looking for a known specific type of damage. Therefore, we introduce an additional algorithm that estimates and updates this distribution as data are collected using the maximum likelihood and the Bayesian methods. We also applied an approximate method to reduce the computation load and memory requirement associated with the estimation. The algorithm is validated using a set of experimental data collected from a four-story steel special moment-resisting frame and multiple sets of simulated data. Various features of different dimensions have been explored, and the algorithm was able to identify damage, particularly when it uses multidimensional damage sensitive features and lower false alarm rates, with a known post-damage feature distribution. For unknown feature distribution cases, the post-damage distribution was consistently estimated and the detection delays were only a few time steps longer than the delays from the general method that assumes we know the post-damage feature distribution. We confirmed that the Bayesian method is particularly efficient in declaring damage with minimal memory requirement, but the maximum likelihood method provides an insightful heuristic approach.

Segmentation and texture analysis of structural biomarkers using neighborhood-clustering-based level set in MRI of the schizophrenic brain.

PubMed

Latha, Manohar; Kavitha, Ganesan

2018-02-03

Schizophrenia (SZ) is a psychiatric disorder that especially affects individuals during their adolescence. There is a need to study the subanatomical regions of SZ brain on magnetic resonance images (MRI) based on morphometry. In this work, an attempt was made to analyze alterations in structure and texture patterns in images of the SZ brain using the level-set method and Laws texture features. T1-weighted MRI of the brain from Center of Biomedical Research Excellence (COBRE) database were considered for analysis. Segmentation was carried out using the level-set method. Geometrical and Laws texture features were extracted from the segmented brain stem, corpus callosum, cerebellum, and ventricle regions to analyze pattern changes in SZ. The level-set method segmented multiple brain regions, with higher similarity and correlation values compared with an optimized method. The geometric features obtained from regions of the corpus callosum and ventricle showed significant variation (p < 0.00001) between normal and SZ brain. Laws texture feature identified a heterogeneous appearance in the brain stem, corpus callosum and ventricular regions, and features from the brain stem were correlated with Positive and Negative Syndrome Scale (PANSS) score (p < 0.005). A framework of geometric and Laws texture features obtained from brain subregions can be used as a supplement for diagnosis of psychiatric disorders.

Quantitative verification of thin-film polyvinylidene fluoride (PVDF) transducer array performance up to 60 °C

NASA Astrophysics Data System (ADS)

Hakoda, Christopher; Ren, Baiyang; Lissenden, Cliff J.; Rose, Joseph L.

2017-02-01

Thin-film PVDF (polyvinylidene fluoride) transducers are appealing as low cost, light weight, durable, and flexible sensors for structural health monitoring applications in aircraft structures. However, due to the relatively low Curie temperature of PVDF, there is a concern that it's performance will drop below acceptable levels during elevated-temperature operating conditions. To verify acceptable performance in these environmental operating conditions, temperature history data were collected between 23-60 °C. The effect of temperature on the thin-film PVDF was investigated and a temperature-independent damage feature was assessed. The temperature dependence of the signal's peak amplitude was investigated in both the time domain and the spectral domain to get two damage features. It was found that the measurement of the incident guided wave by the thin-film PVDF transducer had a temperature dependence that varied with frequency. A third damage feature, the mode ratio, was also calculated in the spectral domain with the goal of defining a damage feature that is temperature independent. A comparison of how well these damage features performed when used to identify a notch in an aluminum plate was made using receiver operating characteristic curves and their respective area under the curve values. This result demonstrated that a temperature-independent damage feature can be calculated, to some degree, by using a mode ratio between two modes of similar temperature dependence.

Investigation of progressive failure robustness and alternate load paths for damage tolerant structures

NASA Astrophysics Data System (ADS)

Marhadi, Kun Saptohartyadi

Structural optimization for damage tolerance under various unforeseen damage scenarios is computationally challenging. It couples non-linear progressive failure analysis with sampling-based stochastic analysis of random damage. The goal of this research was to understand the relationship between alternate load paths available in a structure and its damage tolerance, and to use this information to develop computationally efficient methods for designing damage tolerant structures. Progressive failure of a redundant truss structure subjected to small random variability was investigated to identify features that correlate with robustness and predictability of the structure's progressive failure. The identified features were used to develop numerical surrogate measures that permit computationally efficient deterministic optimization to achieve robustness and predictability of progressive failure. Analysis of damage tolerance on designs with robust progressive failure indicated that robustness and predictability of progressive failure do not guarantee damage tolerance. Damage tolerance requires a structure to redistribute its load to alternate load paths. In order to investigate the load distribution characteristics that lead to damage tolerance in structures, designs with varying degrees of damage tolerance were generated using brute force stochastic optimization. A method based on principal component analysis was used to describe load distributions (alternate load paths) in the structures. Results indicate that a structure that can develop alternate paths is not necessarily damage tolerant. The alternate load paths must have a required minimum load capability. Robustness analysis of damage tolerant optimum designs indicates that designs are tailored to specified damage. A design Optimized under one damage specification can be sensitive to other damages not considered. Effectiveness of existing load path definitions and characterizations were investigated for continuum structures. A load path definition using a relative compliance change measure (U* field) was demonstrated to be the most useful measure of load path. This measure provides quantitative information on load path trajectories and qualitative information on the effectiveness of the load path. The use of the U* description of load paths in optimizing structures for effective load paths was investigated.

Feature-opinion pair identification of product reviews in Chinese: a domain ontology modeling method

NASA Astrophysics Data System (ADS)

Yin, Pei; Wang, Hongwei; Guo, Kaiqiang

2013-03-01

With the emergence of the new economy based on social media, a great amount of consumer feedback on particular products are conveyed through wide-spreading product online reviews, making opinion mining a growing interest for both academia and industry. According to the characteristic mode of expression in Chinese, this research proposes an ontology-based linguistic model to identify the basic appraisal expression in Chinese product reviews-"feature-opinion pair (FOP)." The product-oriented domain ontology is constructed automatically at first, then algorithms to identify FOP are designed by mapping product features and opinions to the conceptual space of the domain ontology, and finally comparative experiments are conducted to evaluate the model. Experimental results indicate that the performance of the proposed approach in this paper is efficient in obtaining a more accurate result compared to the state-of-art algorithms. Furthermore, through identifying and analyzing FOPs, the unstructured product reviews are converted into structured and machine-sensible expression, which provides valuable information for business application. This paper contributes to the related research in opinion mining by developing a solid foundation for further sentiment analysis at a fine-grained level and proposing a general way for automatic ontology construction.

Geological analysis and evaluation of ERTS-A imagery for the state of New Mexico

NASA Technical Reports Server (NTRS)

Kottlowski, F. E. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Coverage of approximately one-third of the test site had been received by January 31, 1973 and all of the images received were MSS products. Images recorded during the first two months of the ERTS-1 mission were of poor quality, owing largely to high ground reflectance. Later images were of better quality and MSS bands 5 and 7 have proven to be particularly useful. Features noted during visual inspection of 9 1/2 x 9 1/2 prints include major structural forms, vegetation patterns, drainage patterns, and outcrops of geologic formations having marked color contrasts. The Border Hills Structural Zone and the Y-O Structural Zone are prominently reflected in coverage of the Pecos Valley. A study of available maps and remote sensing material covering the Deming-Columbus area indicated that the limit of detection and the resolution of MSS products are not as good as those of aerial photographs, geologic maps, and manned satellite photographs. The limit of detection of high contrast features on MSS prints is approximately 1000 feet or 300 meters for linear features and about 18 acres for roughly circular areas.

Magnetoconductance signatures of subband structure in semiconductor nanowires

NASA Astrophysics Data System (ADS)

Holloway, Gregory; Haapamaki, Chris; Lapierre, Ray; Baugh, Jonathan

2015-03-01

Understanding the subband structure due to radial confinement in semiconductor nanowires can benefit technologies ranging from optical sensors to quantum information processing. An axial magnetic field couples to the orbital angular momentum, giving rise to non-trivial features in electronic transport as a function of magnetic field. Previous reports focused on conduction electrons confined to a thin shell near the nanowire surface, which lead to flux-periodic energies and conductance oscillations. Here, we calculate the eigenstates for more general radial potentials with moderate to low surface band bending such that electrons are distributed more uniformly across the nanowire cross-section. It is found that the energy spectrum becomes aperiodic in both gate voltage and magnetic field as the radial potential becomes flatter. The behavior of an energy level is dictated by its angular momentum, and this allows, in principle, each state to be identified based on its dependence on magnetic field and the chemical potential. We experimentally investigate a short-channel InAs nanowire FET in search of conductance features that reveal this subband structure. A quantitative measure for assigning conductance features to specific transverse states is introduced and applied to this device.

Improving link prediction in complex networks by adaptively exploiting multiple structural features of networks

NASA Astrophysics Data System (ADS)

Ma, Chuang; Bao, Zhong-Kui; Zhang, Hai-Feng

2017-10-01

So far, many network-structure-based link prediction methods have been proposed. However, these methods only highlight one or two structural features of networks, and then use the methods to predict missing links in different networks. The performances of these existing methods are not always satisfied in all cases since each network has its unique underlying structural features. In this paper, by analyzing different real networks, we find that the structural features of different networks are remarkably different. In particular, even in the same network, their inner structural features are utterly different. Therefore, more structural features should be considered. However, owing to the remarkably different structural features, the contributions of different features are hard to be given in advance. Inspired by these facts, an adaptive fusion model regarding link prediction is proposed to incorporate multiple structural features. In the model, a logistic function combing multiple structural features is defined, then the weight of each feature in the logistic function is adaptively determined by exploiting the known structure information. Last, we use the "learnt" logistic function to predict the connection probabilities of missing links. According to our experimental results, we find that the performance of our adaptive fusion model is better than many similarity indices.

Unsupervised segmentation of lungs from chest radiographs

NASA Astrophysics Data System (ADS)

Ghosh, Payel; Antani, Sameer K.; Long, L. Rodney; Thoma, George R.

2012-03-01

This paper describes our preliminary investigations for deriving and characterizing coarse-level textural regions present in the lung field on chest radiographs using unsupervised grow-cut (UGC), a cellular automaton based unsupervised segmentation technique. The segmentation has been performed on a publicly available data set of chest radiographs. The algorithm is useful for this application because it automatically converges to a natural segmentation of the image from random seed points using low-level image features such as pixel intensity values and texture features. Our goal is to develop a portable screening system for early detection of lung diseases for use in remote areas in developing countries. This involves developing automated algorithms for screening x-rays as normal/abnormal with a high degree of sensitivity, and identifying lung disease patterns on chest x-rays. Automatically deriving and quantitatively characterizing abnormal regions present in the lung field is the first step toward this goal. Therefore, region-based features such as geometrical and pixel-value measurements were derived from the segmented lung fields. In the future, feature selection and classification will be performed to identify pathological conditions such as pulmonary tuberculosis on chest radiographs. Shape-based features will also be incorporated to account for occlusions of the lung field and by other anatomical structures such as the heart and diaphragm.

The Widespread Prevalence and Functional Significance of Silk-Like Structural Proteins in Metazoan Biological Materials

PubMed Central

McDougall, Carmel; Woodcroft, Ben J.

2016-01-01

In nature, numerous mechanisms have evolved by which organisms fabricate biological structures with an impressive array of physical characteristics. Some examples of metazoan biological materials include the highly elastic byssal threads by which bivalves attach themselves to rocks, biomineralized structures that form the skeletons of various animals, and spider silks that are renowned for their exceptional strength and elasticity. The remarkable properties of silks, which are perhaps the best studied biological materials, are the result of the highly repetitive, modular, and biased amino acid composition of the proteins that compose them. Interestingly, similar levels of modularity/repetitiveness and similar bias in amino acid compositions have been reported in proteins that are components of structural materials in other organisms, however the exact nature and extent of this similarity, and its functional and evolutionary relevance, is unknown. Here, we investigate this similarity and use sequence features common to silks and other known structural proteins to develop a bioinformatics-based method to identify similar proteins from large-scale transcriptome and whole-genome datasets. We show that a large number of proteins identified using this method have roles in biological material formation throughout the animal kingdom. Despite the similarity in sequence characteristics, most of the silk-like structural proteins (SLSPs) identified in this study appear to have evolved independently and are restricted to a particular animal lineage. Although the exact function of many of these SLSPs is unknown, the apparent independent evolution of proteins with similar sequence characteristics in divergent lineages suggests that these features are important for the assembly of biological materials. The identification of these characteristics enable the generation of testable hypotheses regarding the mechanisms by which these proteins assemble and direct the construction of biological materials with diverse morphologies. The SilkSlider predictor software developed here is available at https://github.com/wwood/SilkSlider. PMID:27415783

Prospecting Biotechnologically-Relevant Monooxygenases from Cold Sediment Metagenomes: An In Silico Approach

DOE PAGES

Musumeci, Matias A.; Lozada, Mariana; Rial, Daniela V.; ...

2017-04-09

The goal of this work was to identify sequences encoding monooxygenase biocatalysts with novel features by in silico mining an assembled metagenomic dataset of polar and subpolar marine sediments. The targeted enzyme sequences were Baeyer-Villiger and bacterial cytochrome P450 monooxygenases (CYP153). These enzymes have wide-ranging applications, from the synthesis of steroids, antibiotics, mycotoxins and pheromones to the synthesis of monomers for polymerization and anticancer precursors, due to their extraordinary enantio-, regio-, and chemo- selectivity that are valuable features for organic synthesis. Phylogenetic analyses were used to select the most divergent sequences affiliated to these enzyme families among the 264 putativemore » monooxygenases recovered from the ~14 million protein-coding sequences in the assembled metagenome dataset. Three-dimensional structure modeling and docking analysis suggested features useful in biotechnological applications in five metagenomic sequences, such as wide substrate range, novel substrate specificity or regioselectivity. Further analysis revealed structural features associated with psychrophilic enzymes, such as broader substrate accessibility, larger catalytic pockets or low domain interactions, suggesting that they could be applied in biooxidations at room or low temperatures, saving costs inherent to energy consumption. As a result, this work allowed the identification of putative enzyme candidates with promising features from metagenomes, providing a suitable starting point for further developments.« less

Prospecting Biotechnologically-Relevant Monooxygenases from Cold Sediment Metagenomes: An In Silico Approach

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

Musumeci, Matias A.; Lozada, Mariana; Rial, Daniela V.

The goal of this work was to identify sequences encoding monooxygenase biocatalysts with novel features by in silico mining an assembled metagenomic dataset of polar and subpolar marine sediments. The targeted enzyme sequences were Baeyer-Villiger and bacterial cytochrome P450 monooxygenases (CYP153). These enzymes have wide-ranging applications, from the synthesis of steroids, antibiotics, mycotoxins and pheromones to the synthesis of monomers for polymerization and anticancer precursors, due to their extraordinary enantio-, regio-, and chemo- selectivity that are valuable features for organic synthesis. Phylogenetic analyses were used to select the most divergent sequences affiliated to these enzyme families among the 264 putativemore » monooxygenases recovered from the ~14 million protein-coding sequences in the assembled metagenome dataset. Three-dimensional structure modeling and docking analysis suggested features useful in biotechnological applications in five metagenomic sequences, such as wide substrate range, novel substrate specificity or regioselectivity. Further analysis revealed structural features associated with psychrophilic enzymes, such as broader substrate accessibility, larger catalytic pockets or low domain interactions, suggesting that they could be applied in biooxidations at room or low temperatures, saving costs inherent to energy consumption. As a result, this work allowed the identification of putative enzyme candidates with promising features from metagenomes, providing a suitable starting point for further developments.« less

Prospecting Biotechnologically-Relevant Monooxygenases from Cold Sediment Metagenomes: An In Silico Approach.

PubMed

Musumeci, Matías A; Lozada, Mariana; Rial, Daniela V; Mac Cormack, Walter P; Jansson, Janet K; Sjöling, Sara; Carroll, JoLynn; Dionisi, Hebe M

2017-04-09

The goal of this work was to identify sequences encoding monooxygenase biocatalysts with novel features by in silico mining an assembled metagenomic dataset of polar and subpolar marine sediments. The targeted enzyme sequences were Baeyer-Villiger and bacterial cytochrome P450 monooxygenases (CYP153). These enzymes have wide-ranging applications, from the synthesis of steroids, antibiotics, mycotoxins and pheromones to the synthesis of monomers for polymerization and anticancer precursors, due to their extraordinary enantio-, regio-, and chemo- selectivity that are valuable features for organic synthesis. Phylogenetic analyses were used to select the most divergent sequences affiliated to these enzyme families among the 264 putative monooxygenases recovered from the ~14 million protein-coding sequences in the assembled metagenome dataset. Three-dimensional structure modeling and docking analysis suggested features useful in biotechnological applications in five metagenomic sequences, such as wide substrate range, novel substrate specificity or regioselectivity. Further analysis revealed structural features associated with psychrophilic enzymes, such as broader substrate accessibility, larger catalytic pockets or low domain interactions, suggesting that they could be applied in biooxidations at room or low temperatures, saving costs inherent to energy consumption. This work allowed the identification of putative enzyme candidates with promising features from metagenomes, providing a suitable starting point for further developments.

Prospecting Biotechnologically-Relevant Monooxygenases from Cold Sediment Metagenomes: An In Silico Approach

PubMed Central

Musumeci, Matías A.; Lozada, Mariana; Rial, Daniela V.; Mac Cormack, Walter P.; Jansson, Janet K.; Sjöling, Sara; Carroll, JoLynn; Dionisi, Hebe M.

2017-01-01

The goal of this work was to identify sequences encoding monooxygenase biocatalysts with novel features by in silico mining an assembled metagenomic dataset of polar and subpolar marine sediments. The targeted enzyme sequences were Baeyer–Villiger and bacterial cytochrome P450 monooxygenases (CYP153). These enzymes have wide-ranging applications, from the synthesis of steroids, antibiotics, mycotoxins and pheromones to the synthesis of monomers for polymerization and anticancer precursors, due to their extraordinary enantio-, regio-, and chemo- selectivity that are valuable features for organic synthesis. Phylogenetic analyses were used to select the most divergent sequences affiliated to these enzyme families among the 264 putative monooxygenases recovered from the ~14 million protein-coding sequences in the assembled metagenome dataset. Three-dimensional structure modeling and docking analysis suggested features useful in biotechnological applications in five metagenomic sequences, such as wide substrate range, novel substrate specificity or regioselectivity. Further analysis revealed structural features associated with psychrophilic enzymes, such as broader substrate accessibility, larger catalytic pockets or low domain interactions, suggesting that they could be applied in biooxidations at room or low temperatures, saving costs inherent to energy consumption. This work allowed the identification of putative enzyme candidates with promising features from metagenomes, providing a suitable starting point for further developments. PMID:28397770

Identification of the chemical constituents of Chinese medicine Yi-Xin-Shu capsule by molecular feature orientated precursor ion selection and tandem mass spectrometry structure elucidation.

PubMed

Wang, Hong-ping; Chen, Chang; Liu, Yan; Yang, Hong-Jun; Wu, Hong-Wei; Xiao, Hong-Bin

2015-11-01

The incomplete identification of the chemical components of traditional Chinese medicinal formula has been one of the bottlenecks in the modernization of traditional Chinese medicine. Tandem mass spectrometry has been widely used for the identification of chemical substances. Current automatic tandem mass spectrometry acquisition, where precursor ions were selected according to their signal intensity, encounters a drawback in chemical substances identification when samples contain many overlapping signals. Compounds in minor or trace amounts could not be identified because most tandem mass spectrometry information was lost. Herein, a molecular feature orientated precursor ion selection and tandem mass spectrometry structure elucidation method for complex Chinese medicine chemical constituent analysis was developed. The precursor ions were selected according to their two-dimensional characteristics of retention times and mass-to-charge ratio ranges from herbal compounds, so that all precursor ions from herbal compounds were included and more minor chemical constituents in Chinese medicine were identified. Compared to the conventional automatic tandem mass spectrometry setups, the approach is novel and can overcome the drawback for chemical substances identification. As an example, 276 compounds from the Chinese Medicine of Yi-Xin-Shu capsule were identified. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Profiling of the Tox21 Chemical Collection for Mitochondrial ...

EPA Pesticide Factsheets

Mitochondrial dysfunction has been implicated in the pathogenesis of a variety of disorders including cancer, diabetes, and neurodegenerative and cardiovascular diseases. Understanding how different environmental chemicals and drug-like molecules impact mitochondrial function represents an initial step in predicting exposure-related toxic effects and defining a possible role for such compounds in the onset of various diseases. OBJECTIVES: To identify individual chemicals and general structural features associated with the disruption of mitochondrial membrane potential (MMP). METHODS: We used a multiplexed quantitative high throughput screening (qHTS) approach combined with informatics tools to screen the Tox21 10,000 compound library (~8300 unique chemicals) at 15 concentrations in triplicate to identify chemicals and structural features that are associated with changes in MMP in HepG2 cells. RESULTS: In the primary screening, approximately 11% of the compounds (913 unique compounds) decreased the MMP after 1 h of treatment without affecting cell viability. Additionally, 309 compounds decreased MMP over a concentration range that also produced measurable cytotoxicity [half maximal inhibitory concentration (IC50) in MMP assay/IC50 in viability assay) ≤ 3, p<0.05]. Over 11% of the structural clusters that constitute the Tox21 library (76 of 651 clusters) were significantly enriched for compounds that decreased the MMP. CONCLUSIONS: Our multiplexed qHTS approach

Celluloid devils: a research study of male nurses in feature films.

PubMed

Stanley, David

2012-11-01

To report a study of how male nurses are portrayed in feature films. It was hypothesized that male nurses are frequently portrayed negatively or stereotypically in the film media, potentially having a negative impact on male nurse recruitment and the public's perception of male nurses. An interpretive, qualitative methodology guided by insights into hegemonic masculinity and structured around a set of collective case studies (films) was used to examine the portrayal of male nurses in feature films made in the Western world from 1900 to 2007. Over 36,000 feature film synopses were reviewed (via CINAHL, ProQuest and relevant movie-specific literature) for the keyword 'nurse' and 'nursing' with an additional search for films from 1900 to 2010 for the word 'male nurse'. Identified films were labelled as 'cases' and analysed collectively to determine key attributes related to men in nursing and explore them for the emergence of concepts and themes related to the image of male nurses in films. A total of 13 relevant cases (feature films) were identified with 12 being made in the USA. Most films portrayed male nurses negatively and in ways opposed to hegemonic masculinity, as effeminate, homosexual, homicidal, corrupt or incompetent. Few film images of male nurses show them in traditional masculine roles or as clinically competent or self-confident professionals.   Feature films predominantly portray male nurses negatively. Given the popularity of feature films, there may be negative effects on recruitment and on the public's perception of male nurses. © 2012 Blackwell Publishing Ltd.

Recognition of emotions using multimodal physiological signals and an ensemble deep learning model.

PubMed

Yin, Zhong; Zhao, Mengyuan; Wang, Yongxiong; Yang, Jingdong; Zhang, Jianhua

2017-03-01

Using deep-learning methodologies to analyze multimodal physiological signals becomes increasingly attractive for recognizing human emotions. However, the conventional deep emotion classifiers may suffer from the drawback of the lack of the expertise for determining model structure and the oversimplification of combining multimodal feature abstractions. In this study, a multiple-fusion-layer based ensemble classifier of stacked autoencoder (MESAE) is proposed for recognizing emotions, in which the deep structure is identified based on a physiological-data-driven approach. Each SAE consists of three hidden layers to filter the unwanted noise in the physiological features and derives the stable feature representations. An additional deep model is used to achieve the SAE ensembles. The physiological features are split into several subsets according to different feature extraction approaches with each subset separately encoded by a SAE. The derived SAE abstractions are combined according to the physiological modality to create six sets of encodings, which are then fed to a three-layer, adjacent-graph-based network for feature fusion. The fused features are used to recognize binary arousal or valence states. DEAP multimodal database was employed to validate the performance of the MESAE. By comparing with the best existing emotion classifier, the mean of classification rate and F-score improves by 5.26%. The superiority of the MESAE against the state-of-the-art shallow and deep emotion classifiers has been demonstrated under different sizes of the available physiological instances. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A Hierarchical Feature and Sample Selection Framework and Its Application for Alzheimer’s Disease Diagnosis

NASA Astrophysics Data System (ADS)

An, Le; Adeli, Ehsan; Liu, Mingxia; Zhang, Jun; Lee, Seong-Whan; Shen, Dinggang

2017-03-01

Classification is one of the most important tasks in machine learning. Due to feature redundancy or outliers in samples, using all available data for training a classifier may be suboptimal. For example, the Alzheimer’s disease (AD) is correlated with certain brain regions or single nucleotide polymorphisms (SNPs), and identification of relevant features is critical for computer-aided diagnosis. Many existing methods first select features from structural magnetic resonance imaging (MRI) or SNPs and then use those features to build the classifier. However, with the presence of many redundant features, the most discriminative features are difficult to be identified in a single step. Thus, we formulate a hierarchical feature and sample selection framework to gradually select informative features and discard ambiguous samples in multiple steps for improved classifier learning. To positively guide the data manifold preservation process, we utilize both labeled and unlabeled data during training, making our method semi-supervised. For validation, we conduct experiments on AD diagnosis by selecting mutually informative features from both MRI and SNP, and using the most discriminative samples for training. The superior classification results demonstrate the effectiveness of our approach, as compared with the rivals.

Coordination of Leaf Photosynthesis, Transpiration, and Structural Traits in Rice and Wild Relatives (Genus Oryza)1[W][OA

PubMed Central

Giuliani, Rita; Koteyeva, Nuria; Voznesenskaya, Elena; Evans, Marc A.; Cousins, Asaph B.; Edwards, Gerald E.

2013-01-01

The genus Oryza, which includes rice (Oryza sativa and Oryza glaberrima) and wild relatives, is a useful genus to study leaf properties in order to identify structural features that control CO2 access to chloroplasts, photosynthesis, water use efficiency, and drought tolerance. Traits, 26 structural and 17 functional, associated with photosynthesis and transpiration were quantified on 24 accessions (representatives of 17 species and eight genomes). Hypotheses of associations within, and between, structure, photosynthesis, and transpiration were tested. Two main clusters of positively interrelated leaf traits were identified: in the first cluster were structural features, leaf thickness (Thickleaf), mesophyll (M) cell surface area exposed to intercellular air space per unit of leaf surface area (Smes), and M cell size; a second group included functional traits, net photosynthetic rate, transpiration rate, M conductance to CO2 diffusion (gm), stomatal conductance to gas diffusion (gs), and the gm/gs ratio. While net photosynthetic rate was positively correlated with gm, neither was significantly linked with any individual structural traits. The results suggest that changes in gm depend on covariations of multiple leaf (Smes) and M cell (including cell wall thickness) structural traits. There was an inverse relationship between Thickleaf and transpiration rate and a significant positive association between Thickleaf and leaf transpiration efficiency. Interestingly, high gm together with high gm/gs and a low Smes/gm ratio (M resistance to CO2 diffusion per unit of cell surface area exposed to intercellular air space) appear to be ideal for supporting leaf photosynthesis while preserving water; in addition, thick M cell walls may be beneficial for plant drought tolerance. PMID:23669746

Coordination of Leaf Photosynthesis, Transpiration, and Structural Traits in Rice and Wild Relatives (Genus Oryza).

PubMed

Giuliani, Rita; Koteyeva, Nuria; Voznesenskaya, Elena; Evans, Marc A; Cousins, Asaph B; Edwards, Gerald E

2013-07-01

The genus Oryza, which includes rice (Oryza sativa and Oryza glaberrima) and wild relatives, is a useful genus to study leaf properties in order to identify structural features that control CO(2) access to chloroplasts, photosynthesis, water use efficiency, and drought tolerance. Traits, 26 structural and 17 functional, associated with photosynthesis and transpiration were quantified on 24 accessions (representatives of 17 species and eight genomes). Hypotheses of associations within, and between, structure, photosynthesis, and transpiration were tested. Two main clusters of positively interrelated leaf traits were identified: in the first cluster were structural features, leaf thickness (Thick(leaf)), mesophyll (M) cell surface area exposed to intercellular air space per unit of leaf surface area (S(mes)), and M cell size; a second group included functional traits, net photosynthetic rate, transpiration rate, M conductance to CO(2) diffusion (g(m)), stomatal conductance to gas diffusion (g(s)), and the g(m)/g(s) ratio.While net photosynthetic rate was positively correlated with gm, neither was significantly linked with any individual structural traits. The results suggest that changes in gm depend on covariations of multiple leaf (S(mes)) and M cell (including cell wall thickness) structural traits. There was an inverse relationship between Thick(leaf) and transpiration rate and a significant positive association between Thick(leaf) and leaf transpiration efficiency. Interestingly, high g(m) together with high g(m)/g(s) and a low S(mes)/g(m) ratio (M resistance to CO(2) diffusion per unit of cell surface area exposed to intercellular air space) appear to be ideal for supporting leaf photosynthesis while preserving water; in addition, thick M cell walls may be beneficial for plant drought tolerance.

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

PubMed

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

2013-01-01

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. 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. 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). 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. This confirms that structural brain traits contribute to individual performance in BCI use.

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

Demersal fish assemblages on seamounts and other rugged features in the northeastern Caribbean

NASA Astrophysics Data System (ADS)

Quattrini, Andrea M.; Demopoulos, Amanda W. J.; Singer, Randal; Roa-Varon, Adela; Chaytor, Jason D.

2017-05-01

Recent investigations of demersal fish communities in deepwater (>50 m) habitats have considerably increased our knowledge of the factors that influence the assemblage structure of fishes across mesophotic to deep-sea depths. While different habitat types influence deepwater fish distribution, whether different types of rugged seafloor features provide functionally equivalent habitat for fishes is poorly understood. In the northeastern Caribbean, different types of rugged features (e.g., seamounts, banks, canyons) punctuate insular margins, and thus create a remarkable setting in which to compare demersal fish communities across various features. Concurrently, several water masses are vertically layered in the water column, creating strong stratification layers corresponding to specific abiotic conditions. In this study, we examined differences among fish assemblages across different features (e.g., seamount, canyon, bank/ridge) and water masses at depths ranging from 98 to 4060 m in the northeastern Caribbean. We conducted 26 remotely operated vehicle dives across 18 sites, identifying 156 species of which 42% of had not been previously recorded from particular depths or localities in the region. While rarefaction curves indicated fewer species at seamounts than at other features in the NE Caribbean, assemblage structure was similar among the different types of features. Thus, similar to seamount studies in other regions, seamounts in the Anegada Passage do not harbor distinct communities from other types of rugged features. Species assemblages, however, differed among depths, with zonation generally corresponding to water mass boundaries in the region. High species turnover occurred at depths <1200 m, and may be driven by changes in water mass characteristics including temperature (4.8-24.4 °C) and dissolved oxygen (2.2-9.5 mg per l). Our study suggests the importance of water masses in influencing community structure of benthic fauna, while considerably adding to the knowledge of mesophotic and deep-sea fish biogeography.

Demersal fish assemblages on seamounts and other rugged features in the northeastern Caribbean

USGS Publications Warehouse

Quattrini, Andrea M.; Demopoulos, Amanda W. J.; Singer, Randal; Roa-Varon, Adela; Chaytor, Jason D.

2017-01-01

Recent investigations of demersal fish communities in deepwater (>50 m) habitats have considerably increased our knowledge of the factors that influence the assemblage structure of fishes across mesophotic to deep-sea depths. While different habitat types influence deepwater fish distribution, whether different types of rugged seafloor features provide functionally equivalent habitat for fishes is poorly understood. In the northeastern Caribbean, different types of rugged features (e.g., seamounts, banks, canyons) punctuate insular margins, and thus create a remarkable setting in which to compare demersal fish communities across various features. Concurrently, several water masses are vertically layered in the water column, creating strong stratification layers corresponding to specific abiotic conditions. In this study, we examined differences among fish assemblages across different features (e.g., seamount, canyon, bank/ridge) and water masses at depths ranging from 98 to 4060 m in the northeastern Caribbean. We conducted 26 remotely operated vehicle dives across 18 sites, identifying 156 species of which 42% of had not been previously recorded from particular depths or localities in the region. While rarefaction curves indicated fewer species at seamounts than at other features in the NE Caribbean, assemblage structure was similar among the different types of features. Thus, similar to seamount studies in other regions, seamounts in the Anegada Passage do not harbor distinct communities from other types of rugged features. Species assemblages, however, differed among depths, with zonation generally corresponding to water mass boundaries in the region. High species turnover occurred at depths <1200 m, and may be driven by changes in water mass characteristics including temperature (4.8–24.4 °C) and dissolved oxygen (2.2–9.5 mg per l). Our study suggests the importance of water masses in influencing community structure of benthic fauna, while considerably adding to the knowledge of mesophotic and deep-sea fish biogeography.

Applications of CPL mask technology for sub-65nm gate imaging

NASA Astrophysics Data System (ADS)

Litt, Lloyd C.; Conley, Will; Wu, Wei; Peters, Richie; Parker, Colita; Cobb, Jonathan; Kasprowicz, Bryan S.; van den Broeke, Doug; Park, J. C.; Karur-Shanmugam, Ramkumar

2005-05-01

The requirements for critical dimension control on gate layer for high performance products are increasingly demanding. Phase shift techniques provide aerial image enhancement, which can translate into improved process window performance and greater critical dimension (CD) control if properly applied. Unfortunately, the application of hard shifter technology to production requires significant effort in layout and optical proximity correction (OPC) application. Chromeless Phase Lithography (CPL) has several advantages over complementary phase mask (c:PSM) such as use of a single mask, and lack of phase placement 'coloring' conflicts and phase imbalance issues. CPL does have implementation issues that must be resolved before it can be used in full-scale production. CPL mask designs can be approached by separating features into three zones based on several parameters, including size relative to the lithographic resolution of the stepper lens, wavelength, and illumination conditions defined. Features are placed into buckets for different treatment zones. Zone 1 features are constructed with 100% transmission phase shifted structures and Zone 3 features are chrome (binary) structures. Features that fall into Zone 2, which are too wide to be defined using the 100% transmission of pure CPL (i.e. have negative mask error factor, MEEF) are the most troublesome and can be approached in several ways. The authors have investigated the application of zebra structures of various sizes to product type layouts. Previous work to investigate CPL using test structures set the groundwork for the more difficult task of applying CPL rules to actual random logic design layouts, which include many zone transitions. Mask making limitations have been identified that play a role in the zebra sizing that can be applied to Zone 2 features. The elimination of Zone 2 regions was also investigated in an effort to simplify the application of CPL and improve manufacturability of reticle through data enhancements.

Linking spatially distributed biogeochemical data with a two-host life-cycle pathogen:A model of whirling disease dynamics in salmonid fishes in the Intermountain West

NASA Astrophysics Data System (ADS)

Fytilis, N.; Lamb, R.; Stevens, L.; Morrissey, L. A.; Kerans, B.; Rizzo, D. M.

2010-12-01

Fish diseases are often caused by waterborne parasites, making them ideal systems for modeling the non-linear relationships between biogeochemical features and disease dynamics. Myxobolus cerebralis, the causative agent of whirling disease, has been a major contributor to the loss of wild rainbow trout populations in numerous streams within the Intermountain West (Colorado, Idaho, Montana, Utah, Wyoming). The parasite alternates between an invertebrate and vertebrate host, being transmitted between the sediment feeding worm T.Tubifex and salmonid fishes. A greater understanding of the linkage between biological stream integrity, geomorphic features, water quality parameters and whirling disease risk is needed to improve current management techniques. Biodiversity and abundance of the worm communities are influenced by biogeochemical features and linked to disease severity in fish. We collected and identified ~700 worms from eight sites using molecular genetic probes and a taxonomic key. Additionally, ~1700 worms were identified using only a taxonomic key. Our work examines the links between worm community structure and biogeochemical features. We use a modified Self-Organizing-Map (SOM), which is a non-parametric clustering method based on an artificial neural network (ANN). Clustering methods are particularly attractive for exploratory data analyses because they do not require either the target number of groupings or the data structure be specified at the outset. ANN clustering methods have been shown to be more robust and to account for more data variability than traditional methods when applied to clustering geo-hydrochemical and microbiological datasets. The SOM highlights spatial variation of worm community structure between sites; and is used in tandem with expert knowledge (Lamb and Kerans) of local worm communities and a Madison River, MT physiochemical dataset (GIS-derived layers, water quality parameters). We iteratively clustered the physiochemical data and then compared the resulting groups to site-specific worm community structures. The SOM mined patterns from this highly dimensional data and produced 2-D visualizations of the data clusters. This process, in concert with iterative feedback with stream ecologists, led to the adaptation of new nonlinear relations and suggests new subsets of input parameters that guide the next round of SOM simulations, expand the pool of concepts, hone existing hypotheses, generate new hypotheses, and so on. The methodologies developed here helped mine the relationship between dominant biogeochemical features and the distribution of an alternative host of a vertebrate disease. This collaboration between modelers, field ecologists and geneticists will prove useful in guiding future data gathering and modeling efforts. (i.e., identifying missing data gaps and sampling frequency), and will enable more effective, high-volume hypothesis generation that, in turn, will better guide complex experimental designs providing integrated understanding of disease dynamics.

Data for Known Geothermal Resource Areas (KGRA) and Identified Hydrothermal Resource Areas (IHRA) in Southern Idaho and Southeastern Oregon

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

Neupane, Ghanashyam; McLing, Travis; Mattson, Earl

The presented database includes water chemistry data and structural rating values for various geothermal features used for performing principal component (PC) and cluster analyses work to identify promising KGRAs and IHRAs in southern Idaho and southeastern Oregon. A brief note on various KGRAs/IHRAs is also included herewith. Results of PC and cluster analyses are presented as a separate paper (Lindsey et al., 2017) that is, as of the time of this submission, in 'revision' status.

Geologic Mapping of Vesta

NASA Technical Reports Server (NTRS)

Yingst, R. A.; Mest, S. C.; Berman, D. C.; Garry, W. B.; Williams, D. A.; Buczkowski, D.; Jaumann, R.; Pieters, C. M.; De Sanctis, M. C.; Frigeri, A.;

The Visible Human Project: From Body to Bits.

PubMed

Ackerman, Michael J

2017-01-01

Atlases of anatomy have long been a mainstay for visualizing and identifying features of the human body [1]. Many are constructed of idealized illustrations rendered so that structures are presented as three-dimensional (3-D) pictures. Others have employed photographs of actual dissections. Still others are composed of collections of artist renderings of organs or areas of interest. All rely on a basically two-dimensional (2-D) graphic display to depict and allow for a better understanding of a complicated 3-D structure.

iEzy-Drug: A Web Server for Identifying the Interaction between Enzymes and Drugs in Cellular Networking

PubMed Central

Min, Jian-Liang; Chou, Kuo-Chen

2013-01-01

With the features of extremely high selectivity and efficiency in catalyzing almost all the chemical reactions in cells, enzymes play vitally important roles for the life of an organism and hence have become frequent targets for drug design. An essential step in developing drugs by targeting enzymes is to identify drug-enzyme interactions in cells. It is both time-consuming and costly to do this purely by means of experimental techniques alone. Although some computational methods were developed in this regard based on the knowledge of the three-dimensional structure of enzyme, unfortunately their usage is quite limited because three-dimensional structures of many enzymes are still unknown. Here, we reported a sequence-based predictor, called “iEzy-Drug,” in which each drug compound was formulated by a molecular fingerprint with 258 feature components, each enzyme by the Chou's pseudo amino acid composition generated via incorporating sequential evolution information and physicochemical features derived from its sequence, and the prediction engine was operated by the fuzzy K-nearest neighbor algorithm. The overall success rate achieved by iEzy-Drug via rigorous cross-validations was about 91%. Moreover, to maximize the convenience for the majority of experimental scientists, a user-friendly web server was established, by which users can easily obtain their desired results. PMID:24371828

A systematic approach to prioritize drug targets using machine learning, a molecular descriptor-based classification model, and high-throughput screening of plant derived molecules: a case study in oral cancer.

PubMed

Randhawa, Vinay; Kumar Singh, Anil; Acharya, Vishal

2015-12-01

Systems-biology inspired identification of drug targets and machine learning-based screening of small molecules which modulate their activity have the potential to revolutionize modern drug discovery by complementing conventional methods. To utilize the effectiveness of such pipelines, we first analyzed the dysregulated gene pairs between control and tumor samples and then implemented an ensemble-based feature selection approach to prioritize targets in oral squamous cell carcinoma (OSCC) for therapeutic exploration. Based on the structural information of known inhibitors of CXCR4-one of the best targets identified in this study-a feature selection was implemented for the identification of optimal structural features (molecular descriptor) based on which a classification model was generated. Furthermore, the CXCR4-centered descriptor-based classification model was finally utilized to screen a repository of plant derived small-molecules to obtain potential inhibitors. The application of our methodology may assist effective selection of the best targets which may have previously been overlooked, that in turn will lead to the development of new oral cancer medications. The small molecules identified in this study can be ideal candidates for trials as potential novel anti-oral cancer agents. Importantly, distinct steps of this whole study may provide reference for the analysis of other complex human diseases.

Towards automated processing of clinical Finnish: sublanguage analysis and a rule-based parser.

PubMed

Laippala, Veronika; Ginter, Filip; Pyysalo, Sampo; Salakoski, Tapio

2009-12-01

In this paper, we present steps taken towards more efficient automated processing of clinical Finnish, focusing on daily nursing notes in a Finnish Intensive Care Unit (ICU). First, we analyze ICU Finnish as a sublanguage, identifying its specific features facilitating, for example, the development of a specialized syntactic analyser. The identified features include frequent omission of finite verbs, limitations in allowed syntactic structures, and domain-specific vocabulary. Second, we develop a formal grammar and a parser for ICU Finnish, thus providing better tools for the development of further applications in the clinical domain. The grammar is implemented in the LKB system in a typed feature structure formalism. The lexicon is automatically generated based on the output of the FinTWOL morphological analyzer adapted to the clinical domain. As an additional experiment, we study the effect of using Finnish constraint grammar to reduce the size of the lexicon. The parser construction thus makes efficient use of existing resources for Finnish. The grammar currently covers 76.6% of ICU Finnish sentences, producing highly accurate best-parse analyzes with F-score of 91.1%. We find that building a parser for the highly specialized domain sublanguage is not only feasible, but also surprisingly efficient, given an existing morphological analyzer with broad vocabulary coverage. The resulting parser enables a deeper analysis of the text than was previously possible.

Recurrence time statistics: versatile tools for genomic DNA sequence analysis.

PubMed

Cao, Yinhe; Tung, Wen-Wen; Gao, J B

2004-01-01

With the completion of the human and a few model organisms' genomes, and the genomes of many other organisms waiting to be sequenced, it has become increasingly important to develop faster computational tools which are capable of easily identifying the structures and extracting features from DNA sequences. One of the more important structures in a DNA sequence is repeat-related. Often they have to be masked before protein coding regions along a DNA sequence are to be identified or redundant expressed sequence tags (ESTs) are to be sequenced. Here we report a novel recurrence time based method for sequence analysis. The method can conveniently study all kinds of periodicity and exhaustively find all repeat-related features from a genomic DNA sequence. An efficient codon index is also derived from the recurrence time statistics, which has the salient features of being largely species-independent and working well on very short sequences. Efficient codon indices are key elements of successful gene finding algorithms, and are particularly useful for determining whether a suspected EST belongs to a coding or non-coding region. We illustrate the power of the method by studying the genomes of E. coli, the yeast S. cervisivae, the nematode worm C. elegans, and the human, Homo sapiens. Computationally, our method is very efficient. It allows us to carry out analysis of genomes on the whole genomic scale by a PC.

Exploration and discovery in Yellowstone Lake: results from high-resolution sonar imaging, seismic reflection profiling, and submersible studies

NASA Astrophysics Data System (ADS)

Morgan, L. A.; Shanks, W. C.; Lovalvo, D. A.; Johnson, S. Y.; Stephenson, W. J.; Pierce, K. L.; Harlan, S. S.; Finn, C. A.; Lee, G.; Webring, M.; Schulze, B.; Dühn, J.; Sweeney, R.; Balistrieri, L.

2003-04-01

'No portion of the American continent is perhaps so rich in wonders as the Yellow Stone' (F.V. Hayden, September 2, 1874) Discoveries from multi-beam sonar mapping and seismic reflection surveys of the northern, central, and West Thumb basins of Yellowstone Lake provide new insight into the extent of post-collapse volcanism and active hydrothermal processes occurring in a large lake environment above a large magma chamber. Yellowstone Lake has an irregular bottom covered with dozens of features directly related to hydrothermal, tectonic, volcanic, and sedimentary processes. Detailed bathymetric, seismic reflection, and magnetic evidence reveals that rhyolitic lava flows underlie much of Yellowstone Lake and exert fundamental control on lake bathymetry and localization of hydrothermal activity. Many previously unknown features have been identified and include over 250 hydrothermal vents, several very large (>500 m diameter) hydrothermal explosion craters, many small hydrothermal vent craters (˜1-200 m diameter), domed lacustrine sediments related to hydrothermal activity, elongate fissures cutting post-glacial sediments, siliceous hydrothermal spire structures, sublacustrine landslide deposits, submerged former shorelines, and a recently active graben. Sampling and observations with a submersible remotely operated vehicle confirm and extend our understanding of the identified features. Faults, fissures, hydrothermally inflated domal structures, hydrothermal explosion craters, and sublacustrine landslides constitute potentially significant geologic hazards. Toxic elements derived from hydrothermal processes also may significantly affect the Yellowstone ecosystem.

Discriminative prediction of mammalian enhancers from DNA sequence

PubMed Central

Lee, Dongwon; Karchin, Rachel; Beer, Michael A.

2011-01-01

Accurately predicting regulatory sequences and enhancers in entire genomes is an important but difficult problem, especially in large vertebrate genomes. With the advent of ChIP-seq technology, experimental detection of genome-wide EP300/CREBBP bound regions provides a powerful platform to develop predictive tools for regulatory sequences and to study their sequence properties. Here, we develop a support vector machine (SVM) framework which can accurately identify EP300-bound enhancers using only genomic sequence and an unbiased set of general sequence features. Moreover, we find that the predictive sequence features identified by the SVM classifier reveal biologically relevant sequence elements enriched in the enhancers, but we also identify other features that are significantly depleted in enhancers. The predictive sequence features are evolutionarily conserved and spatially clustered, providing further support of their functional significance. Although our SVM is trained on experimental data, we also predict novel enhancers and show that these putative enhancers are significantly enriched in both ChIP-seq signal and DNase I hypersensitivity signal in the mouse brain and are located near relevant genes. Finally, we present results of comparisons between other EP300/CREBBP data sets using our SVM and uncover sequence elements enriched and/or depleted in the different classes of enhancers. Many of these sequence features play a role in specifying tissue-specific or developmental-stage-specific enhancer activity, but our results indicate that some features operate in a general or tissue-independent manner. In addition to providing a high confidence list of enhancer targets for subsequent experimental investigation, these results contribute to our understanding of the general sequence structure of vertebrate enhancers. PMID:21875935

BDA: A novel method for identifying defects in body-centered cubic crystals.

PubMed

Möller, Johannes J; Bitzek, Erik

2016-01-01

The accurate and fast identification of crystallographic defects plays a key role for the analysis of atomistic simulation output data. For face-centered cubic (fcc) metals, most existing structure analysis tools allow for the direct distinction of common defects, such as stacking faults or certain low-index surfaces. For body-centered cubic (bcc) metals, on the other hand, a robust way to identify such defects is currently not easily available. We therefore introduce a new method for analyzing atomistic configurations of bcc metals, the BCC Defect Analysis (BDA). It uses existing structure analysis algorithms and combines their results to uniquely distinguish between typical defects in bcc metals. In essence, the BDA method offers the following features:•Identification of typical defect structures in bcc metals.•Reduction of erroneously identified defects by iterative comparison to the defects in the atom's neighborhood.•Availability as ready-to-use Python script for the widespread visualization tool OVITO [http://ovito.org].

Line drawing extraction from gray level images by feature integration

NASA Astrophysics Data System (ADS)

Yoo, Hoi J.; Crevier, Daniel; Lepage, Richard; Myler, Harley R.

1994-10-01

We describe procedures that extract line drawings from digitized gray level images, without use of domain knowledge, by modeling preattentive and perceptual organization functions of the human visual system. First, edge points are identified by standard low-level processing, based on the Canny edge operator. Edge points are then linked into single-pixel thick straight- line segments and circular arcs: this operation serves to both filter out isolated and highly irregular segments, and to lump the remaining points into a smaller number of structures for manipulation by later stages of processing. The next stages consist in linking the segments into a set of closed boundaries, which is the system's definition of a line drawing. According to the principles of Gestalt psychology, closure allows us to organize the world by filling in the gaps in a visual stimulation so as to perceive whole objects instead of disjoint parts. To achieve such closure, the system selects particular features or combinations of features by methods akin to those of preattentive processing in humans: features include gaps, pairs of straight or curved parallel lines, L- and T-junctions, pairs of symmetrical lines, and the orientation and length of single lines. These preattentive features are grouped into higher-level structures according to the principles of proximity, similarity, closure, symmetry, and feature conjunction. Achieving closure may require supplying missing segments linking contour concavities. Choices are made between competing structures on the basis of their overall compliance with the principles of closure and symmetry. Results include clean line drawings of curvilinear manufactured objects. The procedures described are part of a system called VITREO (viewpoint-independent 3-D recognition and extraction of objects).

Examination of the relationship between host worm community structure on transmission of the parasite, Myxobolus cerebralis by developing taxon-specific probes for multiplex qPCR to identify worm taxa in stream communities

NASA Astrophysics Data System (ADS)

Fytilis, N.; Lamb, R.; Kerans, B.; Stevens, L.; Rizzo, D. M.

2011-12-01

Fish diseases are often caused by waterborne parasites, making them ideal systems for modeling the non-linear relationships between disease dynamics, stream dwelling oligochaete communities and geochemical features. Myxobolus cerebralis, the causative agent of whirling disease in salmonid fishes, has been a major contributor to the loss of wild rainbow trout populations in numerous streams within the Intermountain West. The parasite alternates between an invertebrate and vertebrate host, being transmitted between the sediment feeding worm Tubifex tubifex (T.tubifex) and salmonid fishes. Worm community biodiversity and abundance are influenced by biogeochemical features and have been linked to disease severity in fish. The worm (T.tubifex) lives in communities with 3-4 other types of worms in stream sediments. Unfortunately, taxonomic identification of oligochaetes is largely dependent on morphological characteristics of sexually mature adults. We have collected and identified ~700 worms from eight sites using molecular genetic probes and a taxonomic key. Additionally, ~1700 worms were identified using only molecular genetic probes. To facilitate distinguishing among tubificids, we developed two multiplex molecular genetic probe-based quantitative polymerase reaction (qPCR) assays to assess tubificid communities in the study area. Similar qPCR techniques specific for M.cerebralis used to determine if individual worms were infected with the parasite. We show how simple Bayesian analysis of the qPCR data can predict the worm community structure and reveal relationships between biodiversity of host communities and host-parasite dynamics. To our knowledge, this is the first study that combines molecular data of both the host and the parasite to examine the effects of host community structure on the transmission of a parasite. Our work can be extended to examine the links between worm community structure and biogeochemical features using molecular genetics and Bayesian statistics to assist in identifying new nonlinear relationships and suggest new subsets of input parameters. Future work includes the development of a new complex systems tool capable of assimilating biological DNA sequence data and biogeochemical features using artificial neural networks and Bayesian analysis. The methodologies developed here helped mine the relationships between biodiversity of host communities and host-parasite dynamics. The results from our study will be useful to managers and researchers for assessing the risk of whirling disease in drainages where tubificid community composition data are needed. This collaboration between modelers, field ecologists and geneticists will prove useful in modeling efforts and will enable more effective, high-volume hypothesis generation. The ability to characterize areas of high whirling disease risk is essential for improving our understanding of the dynamics of M.cerebralis such that appropriate management strategies can be implemented.

Stratigraphic and structural configuration of the Navajo (Jurassic) through Ouray (Mississippian-Devonian) formations in the vicinity of Davis and Lavender Canyons, southeastern Utah

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

McCleary, J.R.; Romie, J.E.

1986-04-01

This study developed a three-dimensional computer model of stratigraphic and structural relationships within a 3497-km/sup 2/ (1350-mi/sup 2/) study area centered on the proposed site for a high-level nuclear waste repository in southeastern Utah. The model consists of a sequence of internally reconciled isopach and structure contour maps horizontally registered and stored in stratigraphic order. This model can be used to display cross sections, perspective block diagrams, or fence diagrams at any orientation; estimate depth of formation contacts and thicknesses for any new stratigraphic or hydrologic boreholes; facilitate ground-water modeling studies; and evaluate the structural and stratigraphic evolution of themore » study area. This study also includes limited evaluations of aquifer continuity in the Elephant Canyon and Honaker Trail Formations, and of salt dissolution and flowage features as interpreted from geophysical logs. The study identified a long history of movement in the fault system in the north-central part of the study area and a major salt flowage feature in the northeastern part. It describes the Elephant Canyon Formation aquifer as laterally limited, the Honaker Trail Formation aquifer as fairly continuous over the area, and Beef Basin in the southern part of the area as a probable dissolution feature. It also concludes that the Shay-Bridger Jack-Salt Creek Graben system is apparently a vertically continuous feature between the basement and ground surface. No stratigraphic or structural discontinuities were detected in the vicinity of Davis Canyon that appear to be detrimental to the siting of a waste repository.« less

An expert botanical feature extraction technique based on phenetic features for identifying plant species.

PubMed

Kolivand, Hoshang; Fern, Bong Mei; Rahim, Mohd Shafry Mohd; Sulong, Ghazali; Baker, Thar; Tully, David

2018-01-01

In this paper, we present a new method to recognise the leaf type and identify plant species using phenetic parts of the leaf; lobes, apex and base detection. Most of the research in this area focuses on the popular features such as the shape, colour, vein, and texture, which consumes large amounts of computational processing and are not efficient, especially in the Acer database with a high complexity structure of the leaves. This paper is focused on phenetic parts of the leaf which increases accuracy. Detecting the local maxima and local minima are done based on Centroid Contour Distance for Every Boundary Point, using north and south region to recognise the apex and base. Digital morphology is used to measure the leaf shape and the leaf margin. Centroid Contour Gradient is presented to extract the curvature of leaf apex and base. We analyse 32 leaf images of tropical plants and evaluated with two different datasets, Flavia, and Acer. The best accuracy obtained is 94.76% and 82.6% respectively. Experimental results show the effectiveness of the proposed technique without considering the commonly used features with high computational cost.

An expert botanical feature extraction technique based on phenetic features for identifying plant species

PubMed Central

Fern, Bong Mei; Rahim, Mohd Shafry Mohd; Sulong, Ghazali; Baker, Thar; Tully, David

2018-01-01

In this paper, we present a new method to recognise the leaf type and identify plant species using phenetic parts of the leaf; lobes, apex and base detection. Most of the research in this area focuses on the popular features such as the shape, colour, vein, and texture, which consumes large amounts of computational processing and are not efficient, especially in the Acer database with a high complexity structure of the leaves. This paper is focused on phenetic parts of the leaf which increases accuracy. Detecting the local maxima and local minima are done based on Centroid Contour Distance for Every Boundary Point, using north and south region to recognise the apex and base. Digital morphology is used to measure the leaf shape and the leaf margin. Centroid Contour Gradient is presented to extract the curvature of leaf apex and base. We analyse 32 leaf images of tropical plants and evaluated with two different datasets, Flavia, and Acer. The best accuracy obtained is 94.76% and 82.6% respectively. Experimental results show the effectiveness of the proposed technique without considering the commonly used features with high computational cost. PMID:29420568

The Diagnostic Dilemma of Pathological Appearance and Performance Enhancing Drug Use

PubMed Central

Hildebrandt, Tom; Lai, Justine K.; Langenbucher, James W.; Schneider, Melanie; Yehuda, Rachel; Pfaff, Donald W.

2010-01-01

Appearance and performance enhancing drug (APED) use includes the use of a range of pharmacologically distinct substances and concurrent investment in outward appearance or achievement, dietary control, and frequent exercise. A number of existing reviews and conceptual papers have defined pathological forms of APED use within the APED class of anabolic-androgenic steroids (AASs) and using the framework of AAS dependence. We review published data on APED use including human studies of AAS users and identified three defining phenomenological features associated with increased health risk and pathology. These features included (1) polypharmacy or the concurrent use of several pharmacologically distinct substances used to change outward appearance or increase likelihood of personal achievement; (2) significant body image disturbance; (3) rigid practices and preoccupations with diet and exercise. Investigations into the latent structure of APED use suggest these features cluster together in a homogenous group of APED users who have the highest health risk and most psychopathology. These features are discussed in the context of AAS dependence and problems with defining classic tolerance-withdrawal symptoms among APED users. Suggestions for a resolution and outline for future research needed to determine the best system for identifying and diagnosing pathological APED use are discussed. PMID:21115306

Radiological features for the approach in trans-sphenoidal pituitary surgery.

PubMed

Twigg, Victoria; Carr, Simon D; Balakumar, Ramkishan; Sinha, Saurabh; Mirza, Showkat

2017-08-01

In order to perform trans-sphenoidal endoscopic pituitary surgery safely and efficiently it is important to identify anatomical and pituitary disease features on the pre-operative CT and MRI scans; thereby minimising the risk to surrounding structures and optimising outcomes. We aim to create a checklist to streamline pre-operative planning. We retrospectively reviewed pre-operative CT and MRI scans of 100 adults undergoing trans-sphenoidal endoscopic pituitary surgery. Radiological findings and their incidence included deviated nasal septum (62%), concha bullosa (32%), bony dehiscence of the carotid arteries (18%), sphenoid septation overlying the internal carotid artery (24% at the sella) and low lying CSF (32%). The mean distance of the sphenoid ostium to the skull base was 10 mm (range 2.7-17.6 mm). We also describe the 'teddy bear' sign which when present on an axial CT indicates the carotid arteries will be identifiable intra-operatively. There are significant variations in the anatomical and pituitary disease features between patients. We describe a number of features on pre-operative scans and have devised a checklist including a new 'teddy bear' sign to aid the surgeon in the anatomical assessment of patients undergoing trans-sphenoidal pituitary surgery.

Quantitative radiomic profiling of glioblastoma represents transcriptomic expression.

PubMed

Kong, Doo-Sik; Kim, Junhyung; Ryu, Gyuha; You, Hye-Jin; Sung, Joon Kyung; Han, Yong Hee; Shin, Hye-Mi; Lee, In-Hee; Kim, Sung-Tae; Park, Chul-Kee; Choi, Seung Hong; Choi, Jeong Won; Seol, Ho Jun; Lee, Jung-Il; Nam, Do-Hyun

2018-01-19

Quantitative imaging biomarkers have increasingly emerged in the field of research utilizing available imaging modalities. We aimed to identify good surrogate radiomic features that can represent genetic changes of tumors, thereby establishing noninvasive means for predicting treatment outcome. From May 2012 to June 2014, we retrospectively identified 65 patients with treatment-naïve glioblastoma with available clinical information from the Samsung Medical Center data registry. Preoperative MR imaging data were obtained for all 65 patients with primary glioblastoma. A total of 82 imaging features including first-order statistics, volume, and size features, were semi-automatically extracted from structural and physiologic images such as apparent diffusion coefficient and perfusion images. Using commercially available software, NordicICE, we performed quantitative imaging analysis and collected the dataset composed of radiophenotypic parameters. Unsupervised clustering methods revealed that the radiophenotypic dataset was composed of three clusters. Each cluster represented a distinct molecular classification of glioblastoma; classical type, proneural and neural types, and mesenchymal type. These clusters also reflected differential clinical outcomes. We found that extracted imaging signatures does not represent copy number variation and somatic mutation. Quantitative radiomic features provide a potential evidence to predict molecular phenotype and treatment outcome. Radiomic profiles represents transcriptomic phenotypes more well.

An interdisciplinary analysis of multispectral satellite data for selected cover types in the Colorado mountains, using automatic data processing techniques

NASA Technical Reports Server (NTRS)

Hoffer, R. M. (Principal Investigator)

1974-01-01

The author has identified the following significant results. In the San Juan Mountains there exists a group of structural and topographic features which suggest a common origin. The relative positions of the San Juan Depression with the Silverton and Lake City Calderas indicate they are possibly on the edge of a large circular feature. Comparison with the 1:250,000 scale Durango Geologic Map reveals a series of radial and arcuate faults concentric with the major circular feature. Such a fracture pattern implies that the circular feature may represent the extent of a major domal uplift in the area. The uplift was very likely due to the sub-crustal emplacement of the parent magma of the San Juan volcanics and intrusives. The broad doming led to the formation of a zone of tensional ring fractures which acted as conduits of release for the magma and the eventual development of the various calderas. The ring fracturing was probably incomplete with hinging occurring in the southern and southwestern portions of the dome accounting for the lack of development of caldera structures in that portion of the area.

Aspects of the structure of film expression and anthropological paradigm of films reception in Croatian cinema and TV distribution.

PubMed

Svilicić, Niksa

2012-09-01

This research paper deals with one part of a comprehensive study called "Causality of narratological-semiotic aspects of the structure of film expression and paradigms of reception of Croatian feature film". It is conceived as a response to the hypothesis that the expression of narrative-semiotic terms correlate with the reception of the Croatian feature film audience and all them leads into a broader holistic i.e. anthropological context.The basic idea of scientific research is to analyze the complete feature productions since Croatian independence 1991 to date, presented at the National Film Festival (film festival in Pula), identify, define and isolate positive social narrative-semiotic stereotypes, which can then serve as a paradigm of better ratings and increase of the currently very low rating of domestic films in Croatian cinemas, as well as TV distribution. In other words, the paper will be analyzed and processed by a range of different effects based on narrative-semiotic, set design and mise-en-scène motives, used in the Croatian feature films since independence to date, that we assume to positively influence the mood of the viewer, and thus increase the rating of the film.

Geologic map of the Metis Mons quadrangle (V–6), Venus

USGS Publications Warehouse

Dohm, James M.; Tanaka, Kenneth L.; Skinner, James A.

2011-01-01

The Metis Mons quadrangle (V–6) in the northern hemisphere of Venus (lat 50° to 75° N., long 240° to 300° E.) includes a variety of coronae, large volcanoes, ridge and fracture (structure) belts, tesserae, impact craters, and other volcanic and structural features distributed within a plains setting, affording study of their detailed age relations and evolutionary development. Coronae in particular have magmatic, tectonic, and topographic signatures that indicate complex evolutionary histories. Previously, the geology of the map region has been described either in general or narrowly focused investigations. Based on Venera radar mapping, a 1:15,000,000-scale geologic map of part of the northern hemisphere of Venus included the V–6 map region and identified larger features such as tesserae, smooth and hummocky plains materials, ridge belts, coronae, volcanoes, and impact craters but proposed little relative-age information. Global-scale mapping from Magellan data identified similar features and also determined their mean global ages with crater counts. However, the density of craters on Venus is too low for meaningful relative-age determinations at local to regional scales. Several of the coronae in the map area have been described using Venera data (Stofan and Head, 1990), while Crumpler and others (1992) compiled detailed identification and description of volcanic and tectonic features from Magellan data. The main purpose of this map is to reconstruct the geologic history of the Metis Mons quadrangle at a level of detail commensurate with a scale of 1:5,000,000 using Magellan data. We interpret four partly overlapping stages of geologic activity, which collectively resulted in the formation of tesserae, coronae (oriented along structure belts), plains materials of varying ages, and four large volcanic constructs. Scattered impact craters, small shields and pancake-shaped domes, and isolated flows superpose the tectonically deformed materials and appear to be the most youthful materials in the map region.

A Target-Less Vision-Based Displacement Sensor Based on Image Convex Hull Optimization for Measuring the Dynamic Response of Building Structures.

PubMed

Choi, Insub; Kim, JunHee; Kim, Donghyun

2016-12-08

Existing vision-based displacement sensors (VDSs) extract displacement data through changes in the movement of a target that is identified within the image using natural or artificial structure markers. A target-less vision-based displacement sensor (hereafter called "TVDS") is proposed. It can extract displacement data without targets, which then serve as feature points in the image of the structure. The TVDS can extract and track the feature points without the target in the image through image convex hull optimization, which is done to adjust the threshold values and to optimize them so that they can have the same convex hull in every image frame and so that the center of the convex hull is the feature point. In addition, the pixel coordinates of the feature point can be converted to physical coordinates through a scaling factor map calculated based on the distance, angle, and focal length between the camera and target. The accuracy of the proposed scaling factor map was verified through an experiment in which the diameter of a circular marker was estimated. A white-noise excitation test was conducted, and the reliability of the displacement data obtained from the TVDS was analyzed by comparing the displacement data of the structure measured with a laser displacement sensor (LDS). The dynamic characteristics of the structure, such as the mode shape and natural frequency, were extracted using the obtained displacement data, and were compared with the numerical analysis results. TVDS yielded highly reliable displacement data and highly accurate dynamic characteristics, such as the natural frequency and mode shape of the structure. As the proposed TVDS can easily extract the displacement data even without artificial or natural markers, it has the advantage of extracting displacement data from any portion of the structure in the image.

A review of reagents for fluorescence microscopy of cellular compartments and structures, part I: BacMam labeling and reagents for vesicular structures.

PubMed

Dolman, Nick J; Kilgore, Jason A; Davidson, Michael W

2013-07-01

Fluorescent labeling of vesicular structures in cultured cells, particularly for live cells, can be challenging for a number of reasons. The first challenge is to identify a reagent that will be specific enough where some structures have a number of potential reagents and others very few options. The emergence of BacMam constructs has allowed more easy-to-use choices. Presented here is a discussion of BacMam constructs as well as a review of commercially-available reagents for labeling vesicular structures in cells, including endosomes, peroxisomes, lysosomes, and autophagosomes, complete with a featured reagent for each structure, recommended protocol, troubleshooting guide, and example image. © 2013 by John Wiley & Sons, Inc.

Integrated feature extraction and selection for neuroimage classification

NASA Astrophysics Data System (ADS)

Fan, Yong; Shen, Dinggang

2009-02-01

Feature extraction and selection are of great importance in neuroimage classification for identifying informative features and reducing feature dimensionality, which are generally implemented as two separate steps. This paper presents an integrated feature extraction and selection algorithm with two iterative steps: constrained subspace learning based feature extraction and support vector machine (SVM) based feature selection. The subspace learning based feature extraction focuses on the brain regions with higher possibility of being affected by the disease under study, while the possibility of brain regions being affected by disease is estimated by the SVM based feature selection, in conjunction with SVM classification. This algorithm can not only take into account the inter-correlation among different brain regions, but also overcome the limitation of traditional subspace learning based feature extraction methods. To achieve robust performance and optimal selection of parameters involved in feature extraction, selection, and classification, a bootstrapping strategy is used to generate multiple versions of training and testing sets for parameter optimization, according to the classification performance measured by the area under the ROC (receiver operating characteristic) curve. The integrated feature extraction and selection method is applied to a structural MR image based Alzheimer's disease (AD) study with 98 non-demented and 100 demented subjects. Cross-validation results indicate that the proposed algorithm can improve performance of the traditional subspace learning based classification.

Nonlocal atlas-guided multi-channel forest learning for human brain labeling

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

Ma, Guangkai; Gao, Yaozong; Wu, Guorong

Purpose: It is important for many quantitative brain studies to label meaningful anatomical regions in MR brain images. However, due to high complexity of brain structures and ambiguous boundaries between different anatomical regions, the anatomical labeling of MR brain images is still quite a challenging task. In many existing label fusion methods, appearance information is widely used. However, since local anatomy in the human brain is often complex, the appearance information alone is limited in characterizing each image point, especially for identifying the same anatomical structure across different subjects. Recent progress in computer vision suggests that the context features canmore » be very useful in identifying an object from a complex scene. In light of this, the authors propose a novel learning-based label fusion method by using both low-level appearance features (computed from the target image) and high-level context features (computed from warped atlases or tentative labeling maps of the target image). Methods: In particular, the authors employ a multi-channel random forest to learn the nonlinear relationship between these hybrid features and target labels (i.e., corresponding to certain anatomical structures). Specifically, at each of the iterations, the random forest will output tentative labeling maps of the target image, from which the authors compute spatial label context features and then use in combination with original appearance features of the target image to refine the labeling. Moreover, to accommodate the high inter-subject variations, the authors further extend their learning-based label fusion to a multi-atlas scenario, i.e., they train a random forest for each atlas and then obtain the final labeling result according to the consensus of results from all atlases. Results: The authors have comprehensively evaluated their method on both public LONI-LBPA40 and IXI datasets. To quantitatively evaluate the labeling accuracy, the authors use the dice similarity coefficient to measure the overlap degree. Their method achieves average overlaps of 82.56% on 54 regions of interest (ROIs) and 79.78% on 80 ROIs, respectively, which significantly outperform the baseline method (random forests), with the average overlaps of 72.48% on 54 ROIs and 72.09% on 80 ROIs, respectively. Conclusions: The proposed methods have achieved the highest labeling accuracy, compared to several state-of-the-art methods in the literature.« less

Nonlocal atlas-guided multi-channel forest learning for human brain labeling

PubMed Central

Ma, Guangkai; Gao, Yaozong; Wu, Guorong; Wu, Ligang; Shen, Dinggang

2016-01-01

Purpose: It is important for many quantitative brain studies to label meaningful anatomical regions in MR brain images. However, due to high complexity of brain structures and ambiguous boundaries between different anatomical regions, the anatomical labeling of MR brain images is still quite a challenging task. In many existing label fusion methods, appearance information is widely used. However, since local anatomy in the human brain is often complex, the appearance information alone is limited in characterizing each image point, especially for identifying the same anatomical structure across different subjects. Recent progress in computer vision suggests that the context features can be very useful in identifying an object from a complex scene. In light of this, the authors propose a novel learning-based label fusion method by using both low-level appearance features (computed from the target image) and high-level context features (computed from warped atlases or tentative labeling maps of the target image). Methods: In particular, the authors employ a multi-channel random forest to learn the nonlinear relationship between these hybrid features and target labels (i.e., corresponding to certain anatomical structures). Specifically, at each of the iterations, the random forest will output tentative labeling maps of the target image, from which the authors compute spatial label context features and then use in combination with original appearance features of the target image to refine the labeling. Moreover, to accommodate the high inter-subject variations, the authors further extend their learning-based label fusion to a multi-atlas scenario, i.e., they train a random forest for each atlas and then obtain the final labeling result according to the consensus of results from all atlases. Results: The authors have comprehensively evaluated their method on both public LONI_LBPA40 and IXI datasets. To quantitatively evaluate the labeling accuracy, the authors use the dice similarity coefficient to measure the overlap degree. Their method achieves average overlaps of 82.56% on 54 regions of interest (ROIs) and 79.78% on 80 ROIs, respectively, which significantly outperform the baseline method (random forests), with the average overlaps of 72.48% on 54 ROIs and 72.09% on 80 ROIs, respectively. Conclusions: The proposed methods have achieved the highest labeling accuracy, compared to several state-of-the-art methods in the literature. PMID:26843260

Does my face FIT?: a face image task reveals structure and distortions of facial feature representation.

PubMed

Fuentes, Christina T; Runa, Catarina; Blanco, Xenxo Alvarez; Orvalho, Verónica; Haggard, Patrick

2013-01-01

Despite extensive research on face perception, few studies have investigated individuals' knowledge about the physical features of their own face. In this study, 50 participants indicated the location of key features of their own face, relative to an anchor point corresponding to the tip of the nose, and the results were compared to the true location of the same individual's features from a standardised photograph. Horizontal and vertical errors were analysed separately. An overall bias to underestimate vertical distances revealed a distorted face representation, with reduced face height. Factor analyses were used to identify separable subconfigurations of facial features with correlated localisation errors. Independent representations of upper and lower facial features emerged from the data pattern. The major source of variation across individuals was in representation of face shape, with a spectrum from tall/thin to short/wide representation. Visual identification of one's own face is excellent, and facial features are routinely used for establishing personal identity. However, our results show that spatial knowledge of one's own face is remarkably poor, suggesting that face representation may not contribute strongly to self-awareness.

Mediterranean scrubland and elevation drive gene flow of a Mediterranean carnivore, the Egyptian mongoose Herpestes ichneumon (Herpestidae)

Treesearch

Tania Barros; Samuel A. Cushman; Joao Carvalho; Carlos Fonseca

2016-01-01

Identifying the environmental features affecting gene flow across a species range is of extreme importance for conservation planning. We investigated the genetic structure of the Egyptian mongoose (Herpestes ichneumon) in Western Iberian Peninsula by analyzing the correlations between genetic distances and landscape resistance models. We evaluated several...

Structure and Strategies in Children's Educational Television: The Roles of Program Type and Learning Strategies in Children's Learning

ERIC Educational Resources Information Center

Linebarger, Deborah L.; Piotrowski, Jessica Taylor

2010-01-01

Educational TV has been consistently linked to children's learning. In this research, educational TV characteristics were identified, coded, and tested for their influence on children's program-specific comprehension and vocabulary outcomes. Study 1 details a content analysis of TV features including a program's macrostructure (i.e., narrative or…

Educational Experiences and Needs of Higher Education Students with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Cai, Ru Ying; Richdale, Amanda L.

2016-01-01

Little research directly examines the needs of post-secondary students with ASD. The experiences and support needs of 23 students with ASD enrolled in two universities and four colleges, and 15 family members were explored in 15 semi-structured focus groups. Thematic analysis identified five themes: core ASD features, co-morbid conditions,…

Teacher Collaborative Learning through the Lesson Study: Identifying Pathways for Instructional Success in a Singapore High School

ERIC Educational Resources Information Center

Lawrence, Christine Anne; Chong, Wan Har

2010-01-01

Research shows teacher collaborative learning to be a powerful vehicle to mobilise teacher instructional change and pedagogical practices, and to improve student achievement. For such undertakings to have positive impact, understanding the visible features of collaborative structures may not be sufficient to ensure sustainable practice. Instead,…

Focus on the Family: New Images of Parents and Children in the 1980's.

ERIC Educational Resources Information Center

Bane, Mary Jo; And Others

The present and future of the American family are discussed in a collection of four papers. The first paper, by Mary Jo Bane, identifies trends in demographic and structural features of families, including fertility rates, marriage trends, divorce rates, household headship rates, and the proportion of women in the labor force. Societies' changing…

Identifying Affordances of 3D Printed Tangible Models for Understanding Core Biological Concepts

ERIC Educational Resources Information Center

Davenport, Jodi L.; Silberglitt, Matt; Boxerman, Jonathan; Olson, Arthur

2014-01-01

3D models derived from actual molecular structures have the potential to transform student learning in biology. We share findings related to our research questions: 1) what types of interactions with a protein folding kit promote specific learning objectives?, and 2) what features of the instructional environment (e.g., peer interactions, teacher…

Road map to adaptive optimal control. [jet engine control

NASA Technical Reports Server (NTRS)

Boyer, R.

1980-01-01

A building block control structure leading toward adaptive, optimal control for jet engines is developed. This approach simplifies the addition of new features and allows for easier checkout of the control by providing a baseline system for comparison. Also, it is possible to eliminate certain features that do not have payoff by being selective in the addition of new building blocks to be added to the baseline system. The minimum risk approach specifically addresses the need for active identification of the plant to be controlled in real time and real time optimization of the control for the identified plant.

Large scale prop-fan structural design study. Volume 1: Initial concepts

NASA Technical Reports Server (NTRS)

Billman, L. C.; Gruska, C. J.; Ladden, R. M.; Leishman, D. K.; Turnberg, J. E.

1988-01-01

In recent years, considerable attention has been directed toward improving aircraft fuel consumption. Studies have shown that the inherent efficiency advantage that turboprop propulsion systems have demonstrated at lower cruise speeds may now be extended to the higher speeds of today's turbofan and turbojet-powered aircraft. To achieve this goal, new propeller designs will require features such as thin, high speed airfoils and aerodynamic sweep, features currently found only in wing designs for high speed aircraft. This is Volume 1 of a 2 volume study to establish structural concepts for such advanced propeller blades, to define their structural properties, to identify any new design, analysis, or fabrication techniques which were required, and to determine the structural tradeoffs involved with several blade shapes selected primarily on the basis of aero/acoustic design considerations. The feasibility of fabricating and testing dynamically scaled models of these blades for aeroelastic testing was also established. The preliminary design of a blade suitable for flight use in a testbed advanced turboprop was conducted and is described in Volume 2.

Structural features of phosphate accumulations in the Gantour basin - Morocco : Application of GIS

NASA Astrophysics Data System (ADS)

Mohamed, Laadraoui; El Hassane, Boumaggard; Essaid, Jourani

2010-05-01

The Moroccan Atlantic margin raises a lot of interest because of its potential resources in phosphates. It also holds in its Mesetien part one of the largest phosphatic deposit in the world. The authors present the results of their researches on structural environments of the phosphatic sedimentary sequences in the Gantour deposit in western Morocco. These investigations are mainly based on field data, data recorded from work done by the OCP (Office Chérifien des Phosphates) group, the interpretation of industrial seismic profiles and the application of GIS. Our aim are devoted to the apprehension of the geometry and the cinematic of these basins which are contemporaneous to the Central Atlantic Rifting, as well as the determination of the list of factors liable to the genesis of these phosphatic basins. Other data of field observations (cartography, study of structural features,...) permit to identify the general structure of the prospect. Sedimentation of phosphated deposits is strained by the presence of two wrench faulting systems oriented N20¬40E, N80¬120E and N140¬160E.

Large scale prop-fan structural design study. Volume 2: Preliminary design of SR-7

NASA Technical Reports Server (NTRS)

Billman, L. C.; Gruska, C. J.; Ladden, R. M.; Leishman, D. K.; Turnberg, J. E.

1988-01-01

In recent years, considerable attention has been directed toward improving aircraft fuel consumption. Studies have shown that the inherent efficiency advantage that turboprop propulsion systems have demonstrated at lower cruise speeds may now be extended to the higher speeds of today's turbofan and turbojet-powered aircraft. To achieve this goal, new propeller designs will require features such as thin, high speed airfoils and aerodynamic sweep, features currently found only in wing designs for high speed aircraft. This is Volume 2 of a 2 volume study to establish structural concepts for such advanced propeller blades, to define their structural properties, to identify any new design, analysis, or fabrication techniques which were required, and to determine the structural tradeoffs involved with several blade shapes selected primarily on the basis of aero/acoustic design considerations. The feasibility of fabricating and testing dynamically scaled models of these blades for aeroelastic testing was also established. The preliminary design of a blade suitable for flight use in a testbed advanced turboprop was conducted and is described.

Identification of DNA-Binding Proteins Using Structural, Electrostatic and Evolutionary Features

PubMed Central

Nimrod, Guy; Szilágyi, András; Leslie, Christina; Ben-Tal, Nir

2009-01-01

Summary DNA binding proteins (DBPs) often take part in various crucial processes of the cell's life cycle. Therefore, the identification and characterization of these proteins are of great importance. We present here a random forests classifier for identifying DBPs among proteins with known three-dimensional structures. First, clusters of evolutionarily conserved regions (patches) on the protein's surface are detected using the PatchFinder algorithm; previous studies showed that these regions are typically the proteins' functionally important regions. Next, we train a classifier using features like the electrostatic potential, cluster-based amino acid conservation patterns and the secondary structure content of the patches, as well as features of the whole protein including its dipole moment. Using 10-fold cross validation on a dataset of 138 DNA-binding proteins and 110 proteins which do not bind DNA, the classifier achieved a sensitivity and a specificity of 0.90, which is overall better than the performance of previously published methods. Furthermore, when we tested 5 different methods on 11 new DBPs which did not appear in the original dataset, only our method annotated all correctly. The resulting classifier was applied to a collection of 757 proteins of known structure and unknown function. Of these proteins, 218 were predicted to bind DNA, and we anticipate that some of them interact with DNA using new structural motifs. The use of complementary computational tools supports the notion that at least some of them do bind DNA. PMID:19233205

Identification of DNA-binding proteins using structural, electrostatic and evolutionary features.

PubMed

Nimrod, Guy; Szilágyi, András; Leslie, Christina; Ben-Tal, Nir

2009-04-10

DNA-binding proteins (DBPs) participate in various crucial processes in the life-cycle of the cells, and the identification and characterization of these proteins is of great importance. We present here a random forests classifier for identifying DBPs among proteins with known 3D structures. First, clusters of evolutionarily conserved regions (patches) on the surface of proteins were detected using the PatchFinder algorithm; earlier studies showed that these regions are typically the functionally important regions of proteins. Next, we trained a classifier using features like the electrostatic potential, cluster-based amino acid conservation patterns and the secondary structure content of the patches, as well as features of the whole protein, including its dipole moment. Using 10-fold cross-validation on a dataset of 138 DBPs and 110 proteins that do not bind DNA, the classifier achieved a sensitivity and a specificity of 0.90, which is overall better than the performance of published methods. Furthermore, when we tested five different methods on 11 new DBPs that did not appear in the original dataset, only our method annotated all correctly. The resulting classifier was applied to a collection of 757 proteins of known structure and unknown function. Of these proteins, 218 were predicted to bind DNA, and we anticipate that some of them interact with DNA using new structural motifs. The use of complementary computational tools supports the notion that at least some of them do bind DNA.

PDB2Graph: A toolbox for identifying critical amino acids map in proteins based on graph theory.

PubMed

Niknam, Niloofar; Khakzad, Hamed; Arab, Seyed Shahriar; Naderi-Manesh, Hossein

2016-05-01

The integrative and cooperative nature of protein structure involves the assessment of topological and global features of constituent parts. Network concept takes complete advantage of both of these properties in the analysis concomitantly. High compatibility to structural concepts or physicochemical properties in addition to exploiting a remarkable simplification in the system has made network an ideal tool to explore biological systems. There are numerous examples in which different protein structural and functional characteristics have been clarified by the network approach. Here, we present an interactive and user-friendly Matlab-based toolbox, PDB2Graph, devoted to protein structure network construction, visualization, and analysis. Moreover, PDB2Graph is an appropriate tool for identifying critical nodes involved in protein structural robustness and function based on centrality indices. It maps critical amino acids in protein networks and can greatly aid structural biologists in selecting proper amino acid candidates for manipulating protein structures in a more reasonable and rational manner. To introduce the capability and efficiency of PDB2Graph in detail, the structural modification of Calmodulin through allosteric binding of Ca(2+) is considered. In addition, a mutational analysis for three well-identified model proteins including Phage T4 lysozyme, Barnase and Ribonuclease HI, was performed to inspect the influence of mutating important central residues on protein activity. Copyright © 2016 Elsevier Ltd. All rights reserved.

Pharmacophore modeling and virtual screening to identify potential RET kinase inhibitors.

PubMed

Shih, Kuei-Chung; Shiau, Chung-Wai; Chen, Ting-Shou; Ko, Ching-Huai; Lin, Chih-Lung; Lin, Chun-Yuan; Hwang, Chrong-Shiong; Tang, Chuan-Yi; Chen, Wan-Ru; Huang, Jui-Wen

2011-08-01

Chemical features based 3D pharmacophore model for REarranged during Transfection (RET) tyrosine kinase were developed by using a training set of 26 structurally diverse known RET inhibitors. The best pharmacophore hypothesis, which identified inhibitors with an associated correlation coefficient of 0.90 between their experimental and estimated anti-RET values, contained one hydrogen-bond acceptor, one hydrogen-bond donor, one hydrophobic, and one ring aromatic features. The model was further validated by a testing set, Fischer's randomization test, and goodness of hit (GH) test. We applied this pharmacophore model to screen NCI database for potential RET inhibitors. The hits were docked to RET with GOLD and CDOCKER after filtering by Lipinski's rules. Ultimately, 24 molecules were selected as potential RET inhibitors for further investigation. Copyright © 2011 Elsevier Ltd. All rights reserved.

The Precise and Efficient Identification of Medical Order Forms Using Shape Trees

NASA Astrophysics Data System (ADS)

Henker, Uwe; Petersohn, Uwe; Ultsch, Alfred

A powerful and flexible technique to identify, classify and process documents using images from a scanning process is presented. The types of documents can be described to the system as a set of differentiating features in a case base using shape trees. The features are filtered and abstracted from an extremely reduced scanner image of the document. Classification rules are stored with the cases to enable precise recognition and further mark reading and Optical Character Recognition (OCR) process. The method is implemented in a system which actually processes the majority of requests for medical lab procedures in Germany. A large practical experiment with data from practitioners was performed. An average of 97% of the forms were correctly identified; none were identified incorrectly. This meets the quality requirements for most medical applications. The modular description of the recognition process allows for a flexible adaptation of future changes to the form and content of the document’s structures.

A Novel Characterization of Amalgamated Networks in Natural Systems

PubMed Central

Barranca, Victor J.; Zhou, Douglas; Cai, David

2015-01-01

Densely-connected networks are prominent among natural systems, exhibiting structural characteristics often optimized for biological function. To reveal such features in highly-connected networks, we introduce a new network characterization determined by a decomposition of network-connectivity into low-rank and sparse components. Based on these components, we discover a new class of networks we define as amalgamated networks, which exhibit large functional groups and dense connectivity. Analyzing recent experimental findings on cerebral cortex, food-web, and gene regulatory networks, we establish the unique importance of amalgamated networks in fostering biologically advantageous properties, including rapid communication among nodes, structural stability under attacks, and separation of network activity into distinct functional modules. We further observe that our network characterization is scalable with network size and connectivity, thereby identifying robust features significant to diverse physical systems, which are typically undetectable by conventional characterizations of connectivity. We expect that studying the amalgamation properties of biological networks may offer new insights into understanding their structure-function relationships. PMID:26035066

Complete fold annotation of the human proteome using a novel structural feature space

DOE PAGES

Middleton, Sarah A.; Illuminati, Joseph; Kim, Junhyong

2017-04-13

Recognition of protein structural fold is the starting point for many structure prediction tools and protein function inference. Fold prediction is computationally demanding and recognizing novel folds is difficult such that the majority of proteins have not been annotated for fold classification. Here we describe a new machine learning approach using a novel feature space that can be used for accurate recognition of all 1,221 currently known folds and inference of unknown novel folds. We show that our method achieves better than 94% accuracy even when many folds have only one training example. We demonstrate the utility of this methodmore » by predicting the folds of 34,330 human protein domains and showing that these predictions can yield useful insights into potential biological function, such as prediction of RNA-binding ability. Finally, our method can be applied to de novo fold prediction of entire proteomes and identify candidate novel fold families.« less

3D fluid-structure modelling and vibration analysis for fault diagnosis of Francis turbine using multiple ANN and multiple ANFIS

NASA Astrophysics Data System (ADS)

Saeed, R. A.; Galybin, A. N.; Popov, V.

2013-01-01

This paper discusses condition monitoring and fault diagnosis in Francis turbine based on integration of numerical modelling with several different artificial intelligence (AI) techniques. In this study, a numerical approach for fluid-structure (turbine runner) analysis is presented. The results of numerical analysis provide frequency response functions (FRFs) data sets along x-, y- and z-directions under different operating load and different position and size of faults in the structure. To extract features and reduce the dimensionality of the obtained FRF data, the principal component analysis (PCA) has been applied. Subsequently, the extracted features are formulated and fed into multiple artificial neural networks (ANN) and multiple adaptive neuro-fuzzy inference systems (ANFIS) in order to identify the size and position of the damage in the runner and estimate the turbine operating conditions. The results demonstrated the effectiveness of this approach and provide satisfactory accuracy even when the input data are corrupted with certain level of noise.

Regulatory effects of cotranscriptional RNA structure formation and transitions.

PubMed

Liu, Sheng-Rui; Hu, Chun-Gen; Zhang, Jin-Zhi

2016-09-01

RNAs, which play significant roles in many fundamental biological processes of life, fold into sophisticated and precise structures. RNA folding is a dynamic and intricate process, which conformation transition of coding and noncoding RNAs form the primary elements of genetic regulation. The cellular environment contains various intrinsic and extrinsic factors that potentially affect RNA folding in vivo, and experimental and theoretical evidence increasingly indicates that the highly flexible features of the RNA structure are affected by these factors, which include the flanking sequence context, physiochemical conditions, cis RNA-RNA interactions, and RNA interactions with other molecules. Furthermore, distinct RNA structures have been identified that govern almost all steps of biological processes in cells, including transcriptional activation and termination, transcriptional mutagenesis, 5'-capping, splicing, 3'-polyadenylation, mRNA export and localization, and translation. Here, we briefly summarize the dynamic and complex features of RNA folding along with a wide variety of intrinsic and extrinsic factors that affect RNA folding. We then provide several examples to elaborate RNA structure-mediated regulation at the transcriptional and posttranscriptional levels. Finally, we illustrate the regulatory roles of RNA structure and discuss advances pertaining to RNA structure in plants. WIREs RNA 2016, 7:562-574. doi: 10.1002/wrna.1350 For further resources related to this article, please visit the WIREs website. © 2016 Wiley Periodicals, Inc.

A multimodal image sensor system for identifying water stress in grapevines

NASA Astrophysics Data System (ADS)

Zhao, Yong; Zhang, Qin; Li, Minzan; Shao, Yongni; Zhou, Jianfeng; Sun, Hong

2012-11-01

Water stress is one of the most common limitations of fruit growth. Water is the most limiting resource for crop growth. In grapevines, as well as in other fruit crops, fruit quality benefits from a certain level of water deficit which facilitates to balance vegetative and reproductive growth and the flow of carbohydrates to reproductive structures. A multi-modal sensor system was designed to measure the reflectance signature of grape plant surfaces and identify different water stress levels in this paper. The multi-modal sensor system was equipped with one 3CCD camera (three channels in R, G, and IR). The multi-modal sensor can capture and analyze grape canopy from its reflectance features, and identify the different water stress levels. This research aims at solving the aforementioned problems. The core technology of this multi-modal sensor system could further be used as a decision support system that combines multi-modal sensory data to improve plant stress detection and identify the causes of stress. The images were taken by multi-modal sensor which could output images in spectral bands of near-infrared, green and red channel. Based on the analysis of the acquired images, color features based on color space and reflectance features based on image process method were calculated. The results showed that these parameters had the potential as water stress indicators. More experiments and analysis are needed to validate the conclusion.

Photogeological analysis of Europan tectonic features

NASA Technical Reports Server (NTRS)

Tufts, B. R.

1993-01-01

Preliminary photogeological analyses of the Pelorus Linea and Sidon Flexus regions of Europa were conducted to explore the proposal by Schenk that lateral motion of crustal blocks has occurred in a 'rift zone' including possible strike-slip, tension fracturing, and geometric plate rotation about an Euler pole. These analyses revealed features interpreted as tensional structures and block rotation in a strike-slip regime consistent with the Schenk hypotheses and implied the presence of at least two stages of crustal deformation consistent with a chronology developed by Lucchitta. Confirmation of regional scale Euler pole rotation was ambiguous, however. Up to 80 kilometers of possible extension was identified in the rift zone; to accommodate this, 'cryosubduction' is speculatively proposed as a mechanism for recycling Europan 'ice lithosphere'. The cumulative width of wedge-shaped bands included in the rift zone was measured and plotted versus distance from the inferred rotation pole. Three sharp decreases in the total width were noted. These occur roughly where certain triple bands cross the rift zone suggesting that the bands are structural features that predate and influence the zone. While the curve hints at one or more sinusoidal relationships consistent with rotation geometry, given the low photographic resolution and the preliminary nature of this examination the question of whether the observations represent coherent regional rotation modified by crosscutting structures or instead imply independent local rotations separated by these structures is unanswered by this analysis.

A systematic approach to identify therapeutic effects of natural products based on human metabolite information.

PubMed

Noh, Kyungrin; Yoo, Sunyong; Lee, Doheon

2018-06-13

Natural products have been widely investigated in the drug development field. Their traditional use cases as medicinal agents and their resemblance of our endogenous compounds show the possibility of new drug development. Many researchers have focused on identifying therapeutic effects of natural products, yet the resemblance of natural products and human metabolites has been rarely touched. We propose a novel method which predicts therapeutic effects of natural products based on their similarity with human metabolites. In this study, we compare the structure, target and phenotype similarities between natural products and human metabolites to capture molecular and phenotypic properties of both compounds. With the generated similarity features, we train support vector machine model to identify similar natural product and human metabolite pairs. The known functions of human metabolites are then mapped to the paired natural products to predict their therapeutic effects. With our selected three feature sets, structure, target and phenotype similarities, our trained model successfully paired similar natural products and human metabolites. When applied to the natural product derived drugs, we could successfully identify their indications with high specificity and sensitivity. We further validated the found therapeutic effects of natural products with the literature evidence. These results suggest that our model can match natural products to similar human metabolites and provide possible therapeutic effects of natural products. By utilizing the similar human metabolite information, we expect to find new indications of natural products which could not be covered by previous in silico methods.

Cross-sectional anatomy, computed tomography and magnetic resonance imaging of the head of common dolphin (Delphinus delphis) and striped dolphin (Stenella coeruleoalba).

PubMed

Alonso-Farré, J M; Gonzalo-Orden, M; Barreiro-Vázquez, J D; Barreiro-Lois, A; André, M; Morell, M; Llarena-Reino, M; Monreal-Pawlowsky, T; Degollada, E

2015-02-01

Computed tomography (CT) and low-field magnetic resonance imaging (MRI) were used to scan seven by-caught dolphin cadavers, belonging to two species: four common dolphins (Delphinus delphis) and three striped dolphins (Stenella coeruleoalba). CT and MRI were obtained with the animals in ventral recumbency. After the imaging procedures, six dolphins were frozen at -20°C and sliced in the same position they were examined. Not only CT and MRI scans, but also cross sections of the heads were obtained in three body planes: transverse (slices of 1 cm thickness) in three dolphins, sagittal (5 cm thickness) in two dolphins and dorsal (5 cm thickness) in two dolphins. Relevant anatomical structures were identified and labelled on each cross section, obtaining a comprehensive bi-dimensional topographical anatomy guide of the main features of the common and the striped dolphin head. Furthermore, the anatomical cross sections were compared with their corresponding CT and MRI images, allowing an imaging identification of most of the anatomical features. CT scans produced an excellent definition of the bony and air-filled structures, while MRI allowed us to successfully identify most of the soft tissue structures in the dolphin's head. This paper provides a detailed anatomical description of the head structures of common and striped dolphins and compares anatomical cross sections with CT and MRI scans, becoming a reference guide for the interpretation of imaging studies. © 2014 Blackwell Verlag GmbH.

Mutations Abrogating VP35 Interaction with Double-Stranded RNA Render Ebola Virus Avirulent in Guinea Pigs

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

Prins, Kathleen C.; Delpeut, Sebastien; Leung, Daisy W.

2010-10-11

Ebola virus (EBOV) protein VP35 is a double-stranded RNA (dsRNA) binding inhibitor of host interferon (IFN)-{alpha}/{beta} responses that also functions as a viral polymerase cofactor. Recent structural studies identified key features, including a central basic patch, required for VP35 dsRNA binding activity. To address the functional significance of these VP35 structural features for EBOV replication and pathogenesis, two point mutations, K319A/R322A, that abrogate VP35 dsRNA binding activity and severely impair its suppression of IFN-{alpha}/{beta} production were identified. Solution nuclear magnetic resonance (NMR) spectroscopy and X-ray crystallography reveal minimal structural perturbations in the K319A/R322A VP35 double mutant and suggest that lossmore » of basic charge leads to altered function. Recombinant EBOVs encoding the mutant VP35 exhibit, relative to wild-type VP35 viruses, minimal growth attenuation in IFN-defective Vero cells but severe impairment in IFN-competent cells. In guinea pigs, the VP35 mutant virus revealed a complete loss of virulence. Strikingly, the VP35 mutant virus effectively immunized animals against subsequent wild-type EBOV challenge. These in vivo studies, using recombinant EBOV viruses, combined with the accompanying biochemical and structural analyses directly correlate VP35 dsRNA binding and IFN inhibition functions with viral pathogenesis. Moreover, these studies provide a framework for the development of antivirals targeting this critical EBOV virulence factor.« less

Learning and Improving in Quality Improvement Collaboratives: Which Collaborative Features Do Participants Value Most?

PubMed Central

Nembhard, Ingrid M

2009-01-01

Objective To understand participants' views on the relative helpfulness of various features of collaboratives, why each feature was helpful and which features the most successful participants viewed as most central to their success. Data Sources Primary data collected from 53 teams in four 2004–2005 Institute for Healthcare Improvement (IHI) Breakthrough Series collaboratives; secondary data from IHI and demographic sources. Study Design Cross-sectional analyses were conducted to assess participants' views of 12 features, and the relationship between their views and performance improvement. Data Collection Methods Participants' views on features were obtained via self-administered surveys and semi-structured telephone interviews. Performance improvement data were obtained from IHI and demographic data from secondary sources. Principal Findings Participants viewed six features as most helpful for advancing their improvement efforts overall and knowledge acquisition in particular: collaborative faculty, solicitation of their staff's ideas, change package, Plan-Do-Study-Act cycles, Learning Session interactions, and collaborative extranet. These features also provided participants with motivation, social support, and project management skills. Features enabling interorganizational learning were rated higher by teams whose organizations improved significantly than by other teams. Conclusions Findings identify features of collaborative design and implementation that participants view as most helpful and highlight the importance of interorganizational features, at least for those organizations that most improve. PMID:19040423

A systemic approach to occupational and environmental health.

PubMed

Spitzer, Skip

2005-01-01

As the corporate role in occupational and public health receives increased scrutiny, it is essential to recognize that it is not sufficient to identify specific acts of malfeasance or influence, or even to campaign to address them. A more comprehensive and systemic framework for understanding the role of corporations requires consideration of corporate power and its effects as endemic features of national socioeconomic systems and the rapidly integrating global order. The underlying social structures that produce social and environmental problems, and undermine reform, make systemic change necessary. Identifying this "structure of harm" provides important implications for researchers, policymakers, activists, and others trying to address environmental and social problems, particularly with regard to integrating efforts to address immediate impacts with those for longer-term, systemic change.

Electron Microscopy and Analytical X-ray Characterization of Compositional and Nanoscale Structural Changes in Fossil Bone

NASA Astrophysics Data System (ADS)

Boatman, Elizabeth Marie

The nanoscale structure of compact bone contains several features that are direct indicators of bulk tissue mechanical properties. Fossil bone tissues represent unique opportunities to understand the compact bone structure/property relationships from a deep time perspective, offering a possible array of new insights into bone diseases, biomimicry of composite materials, and basic knowledge of bioapatite composition and nanoscale bone structure. To date, most work with fossil bone has employed microscale techniques and has counter-indicated the survival of bioapatite and other nanoscale structural features. The obvious disconnect between the use of microscale techniques and the discernment of nanoscale structure has prompted this work. The goal of this study was to characterize the nanoscale constituents of fossil compact bone by applying a suite of diffraction, microscopy, and spectrometry techniques, representing the highest levels of spatial and energy resolution available today, and capable of complementary structural and compositional characterization from the micro- to the nanoscale. Fossil dinosaur and crocodile long bone specimens, as well as modern ratite and crocodile femurs, were acquired from the UC Museum of Paleontology. Preserved physiological features of significance were documented with scanning electron microscopy back-scattered imaging. Electron microprobe wavelength-dispersive X-ray spectroscopy (WDS) revealed fossil bone compositions enriched in fluorine with a complementary loss of oxygen. X-ray diffraction analyses demonstrated that all specimens were composed of apatite. Transmission electron microscopy (TEM) imaging revealed preserved nanocrystallinity in the fossil bones and electron diffraction studies further identified these nanocrystallites as apatite. Tomographic analyses of nanoscale elements imaged by TEM and small angle X-ray scattering were performed, with the results of each analysis further indicating that nanoscale structure is highly conserved in these four fossil specimens. Finally, the results of this study indicate that bioapatite can be preserved in even the most ancient vertebrate specimens, further supporting the idea that fossilization is a preservational process. This work also underlines the importance of using appropriately selected characterization and analytical techniques for the study of fossil bone, especially from the perspective of spatial resolution and the scale of the bone structural features in question.

Cracks in the palisade cuticle of soybean seed coats correlate with their permeability to water.

PubMed

Ma, Fengshan; Cholewa, Ewa; Mohamed, Tasneem; Peterson, Carol A; Gijzen, Mark

2004-08-01

Soybean (Glycine max) is among the many legumes that are well known for 'hardseededness'. This feature can be beneficial for long-term seed survival, but is undesirable for the food processing industry. There is substantial disagreement concerning the mechanisms and related structures that control the permeability properties of soybean seed coats. In this work, the structural component that controls water entry into the seed is identified. Six soybean cultivars were tested for their seed coat permeabilities to water. To identify the structural feature(s) that may contribute to the determination of these permeabilities, fluorescent tracer dyes, and light and electron microscopic techniques were used. The cultivar 'Tachanagaha' has the most permeable seed coat, 'OX 951' the least permeable seed coat, and the permeabilities of the rest ('Harovinton', 'Williams', 'Clark L 67-3469', and 'Harosoy 63') are intermediate. All seeds have surface deposits, depressions, a light line, and a cuticle about 0.2 microm thick overlaying the palisade layer. In permeable cultivars the cuticle tends to break, whereas in impermeable seeds of 'OX 951' it remains intact. In the case of permeable seed coats, the majority of the cracks are from 1 to 5 micro m wide and from 20 to 200 micro m long, and occur more frequently on the dorsal side than in other regions of the seed coat, a position that correlates with the site of initial water uptake. The cuticle of the palisade layer is the key factor that determines the permeability property of a soybean seed coat. The cuticle of a permeable seed coat is mechanically weak and develops small cracks through which water can pass. The cuticle of an impermeable seed coat is mechanically strong and does not crack under normal circumstances.

An in-silico method for identifying aggregation rate enhancer and mitigator mutations in proteins.

PubMed

Rawat, Puneet; Kumar, Sandeep; Michael Gromiha, M

2018-06-24

Newly synthesized polypeptides must pass stringent quality controls in cells to ensure appropriate folding and function. However, mutations, environmental stresses and aging can reduce efficiencies of these controls, leading to accumulation of protein aggregates, amyloid fibrils and plaques. In-vitro experiments have shown that even single amino acid substitutions can drastically enhance or mitigate protein aggregation kinetics. In this work, we have collected a dataset of 220 unique mutations in 25 proteins and classified them as enhancers or mitigators on the basis of their effect on protein aggregation rate. The data were analyzed via machine learning to identify features capable of distinguishing between aggregation rate enhancers and mitigators. Our initial Support Vector Machine (SVM) model separated such mutations with an overall accuracy of 69%. When local secondary structures at the mutation sites were considered, the accuracies further improved by 13-15%. The machine-learnt features are distinct for each secondary structure class at mutation sites. Protein stability and flexibility changes are important features for mutations in α-helices. β-strand propensity, polarity and charge become important when mutations occur in β-strands and ability to form secondary structure, helical tendency and aggregation propensity are important for mutations lying in coils. These results have been incorporated into a sequence-based algorithm (available at http://www.iitm.ac.in/bioinfo/aggrerate-disc/) capable of predicting whether a mutation will enhance or mitigate a protein's aggregation rate. This algorithm will find several applications towards understanding protein aggregation in human diseases, enable in-silico optimization of biopharmaceuticals and enzymes for improved biophysical attributes and de novo design of bio-nanomaterials. Copyright © 2018. Published by Elsevier B.V.

New geomorphic data on the active Taiwan orogen: A multisource approach

NASA Technical Reports Server (NTRS)

Deffontaines, B.; Lee, J.-C.; Angelier, J.; Carvalho, J.; Rudant, J.-P.

1994-01-01

A multisource and multiscale approach of Taiwan morphotectonics combines different complementary geomorphic analyses based on a new elevation model (DEM), side-looking airborne radar (SLAR), and satellite (SPOT) imagery, aerial photographs, and control from independent field data. This analysis enables us not only to present an integrated geomorphic description of the Taiwan orogen but also to highlight some new geodynamic aspects. Well-known, major geological structures such as the Longitudinal Valley, Lishan, Pingtung, and the Foothills fault zones are of course clearly recognized, but numerous, previously unrecognized structures appear distributed within different regions of Taiwan. For instance, transfer fault zones within the Western Foothills and the Central Range are identified based on analyses of lineaments and general morphology. In many cases, the existence of geomorphic features identified in general images is supported by the results of geological field analyses carried out independently. In turn, the field analyses of structures and mechanisms at some sites provide a key for interpreting similar geomorphic featues in other areas. Examples are the conjugate pattern of strike-slip faults within the Central Range and the oblique fold-and-thrust pattern of the Coastal Range. Furthermore, neotectonic and morphological analyses (drainage and erosional surfaces) has been combined in order to obtain a more comprehensive description and interpretation of neotectonic features in Taiwan, such as for the Longitudinal Valley Fault. Next, at a more general scale, numerical processing of digital elevation models, resulting in average topography, summit level or base level maps, allows identification of major features related to the dynamics of uplift and erosion and estimates of erosion balance. Finally, a preliminary morphotectonic sketch map of Taiwan, combining information from all the sources listed above, is presented.

Method for detecting damage in carbon-fibre reinforced plastic-steel structures based on eddy current pulsed thermography

NASA Astrophysics Data System (ADS)

Li, Xuan; Liu, Zhiping; Jiang, Xiaoli; Lodewijks, Gabrol

2018-01-01

Eddy current pulsed thermography (ECPT) is well established for non-destructive testing of electrical conductive materials, featuring the advantages of contactless, intuitive detecting and efficient heating. The concept of divergence characterization of the damage rate of carbon fibre-reinforced plastic (CFRP)-steel structures can be extended to ECPT thermal pattern characterization. It was found in this study that the use of ECPT technology on CFRP-steel structures generated a sizeable amount of valuable information for comprehensive material diagnostics. The relationship between divergence and transient thermal patterns can be identified and analysed by deploying mathematical models to analyse the information about fibre texture-like orientations, gaps and undulations in these multi-layered materials. The developed algorithm enabled the removal of information about fibre texture and the extraction of damage features. The model of the CFRP-glue-steel structures with damage was established using COMSOL Multiphysics® software, and quantitative non-destructive damage evaluation from the ECPT image areas was derived. The results of this proposed method illustrate that damaged areas are highly affected by available information about fibre texture. This proposed work can be applied for detection of impact induced damage and quantitative evaluation of CFRP structures.

Undefined freeform surfaces having deterministic structure: issues of their characterization for functionality and manufacture

NASA Astrophysics Data System (ADS)

Whitehouse, David J.

2016-09-01

There is an increasing use of surfaces which have structure, an increase in the use of freeform surfaces, and most importantly an increase in the number of surfaces having both characteristics. These can be called multi-function surfaces, where more than one function is helped by the geometrical features: the structure can help one, the freeform another. Alternatively, they can be complementary to optimize a single function, but in all cases both geometries are involved. This paper examines some of the problems posed by having such disparate geometries on one surface; in particular, the methods of characterization needed to help understand the functionality and also to some extent their manufacture. This involves investigating ways of expressing how local and global geometric features of undefined freeform surfaces might influence function and how surface structure on top of or in series with the freeform affects the nature of the characterization. Some methods have been found of identifying possible strategies for tackling the characterization problem, based in part on the principles of least action and on the way that nature has solved the marriage of flexible freeform geometry and structure on surfaces.

Detection and localization of damage using empirical mode decomposition and multilevel support vector machine

NASA Astrophysics Data System (ADS)

Dushyanth, N. D.; Suma, M. N.; Latte, Mrityanjaya V.

2016-03-01

Damage in the structure may raise a significant amount of maintenance cost and serious safety problems. Hence detection of the damage at its early stage is of prime importance. The main contribution pursued in this investigation is to propose a generic optimal methodology to improve the accuracy of positioning of the flaw in a structure. This novel approach involves a two-step process. The first step essentially aims at extracting the damage-sensitive features from the received signal, and these extracted features are often termed the damage index or damage indices, serving as an indicator to know whether the damage is present or not. In particular, a multilevel SVM (support vector machine) plays a vital role in the distinction of faulty and healthy structures. Formerly, when a structure is unveiled as a damaged structure, in the subsequent step, the position of the damage is identified using Hilbert-Huang transform. The proposed algorithm has been evaluated in both simulation and experimental tests on a 6061 aluminum plate with dimensions 300 mm × 300 mm × 5 mm which accordingly yield considerable improvement in the accuracy of estimating the position of the flaw.

Chimaeric sounds reveal dichotomies in auditory perception

PubMed Central

Smith, Zachary M.; Delgutte, Bertrand; Oxenham, Andrew J.

2008-01-01

By Fourier's theorem1, signals can be decomposed into a sum of sinusoids of different frequencies. This is especially relevant for hearing, because the inner ear performs a form of mechanical Fourier transform by mapping frequencies along the length of the cochlear partition. An alternative signal decomposition, originated by Hilbert2, is to factor a signal into the product of a slowly varying envelope and a rapidly varying fine time structure. Neurons in the auditory brainstem3–6 sensitive to these features have been found in mammalian physiological studies. To investigate the relative perceptual importance of envelope and fine structure, we synthesized stimuli that we call ‘auditory chimaeras’, which have the envelope of one sound and the fine structure of another. Here we show that the envelope is most important for speech reception, and the fine structure is most important for pitch perception and sound localization. When the two features are in conflict, the sound of speech is heard at a location determined by the fine structure, but the words are identified according to the envelope. This finding reveals a possible acoustic basis for the hypothesized ‘what’ and ‘where’ pathways in the auditory cortex7–10. PMID:11882898

Substrate-bound Crystal Structures Reveal Features Unique to Mycobacterium tuberculosis N-Acetyl-glucosamine 1-Phosphate Uridyltransferase and a Catalytic Mechanism for Acetyl Transfer

PubMed Central

Jagtap, Pravin Kumar Ankush; Soni, Vijay; Vithani, Neha; Jhingan, Gagan Deep; Bais, Vaibhav Singh; Nandicoori, Vinay Kumar; Prakash, Balaji

2012-01-01

N-Acetyl-glucosamine-1-phosphate uridyltransferase (GlmU), a bifunctional enzyme involved in bacterial cell wall synthesis is exclusive to prokaryotes. GlmU, now recognized as a promising target to develop new antibacterial drugs, catalyzes two key reactions: acetyl transfer and uridyl transfer at two independent domains. Hitherto, we identified GlmU from Mycobacterium tuberculosis (GlmUMtb) to be unique in possessing a 30-residue extension at the C terminus. Here, we present the crystal structures of GlmUMtb in complex with substrates/products bound at the acetyltransferase active site. Analysis of these and mutational data, allow us to infer a catalytic mechanism operative in GlmUMtb. In this SN2 reaction, His-374 and Asn-397 act as catalytic residues by enhancing the nucleophilicity of the attacking amino group of glucosamine 1-phosphate. Ser-416 and Trp-460 provide important interactions for substrate binding. A short helix at the C-terminal extension uniquely found in mycobacterial GlmU provides the highly conserved Trp-460 for substrate binding. Importantly, the structures reveal an uncommon mode of acetyl-CoA binding in GlmUMtb; we term this the U conformation, which is distinct from the L conformation seen in the available non-mycobacterial GlmU structures. Residues, likely determining U/L conformation, were identified, and their importance was evaluated. In addition, we identified that the primary site for PknB-mediated phosphorylation is Thr-418, near the acetyltransferase active site. Down-regulation of acetyltransferase activity upon Thr-418 phosphorylation is rationalized by the structures presented here. Overall, this work provides an insight into substrate recognition, catalytic mechanism for acetyl transfer, and features unique to GlmUMtb, which may be exploited for the development of inhibitors specific to GlmU. PMID:22969087

Edge enhancement and noise suppression for infrared image based on feature analysis

NASA Astrophysics Data System (ADS)

Jiang, Meng

2018-06-01

Infrared images are often suffering from background noise, blurred edges, few details and low signal-to-noise ratios. To improve infrared image quality, it is essential to suppress noise and enhance edges simultaneously. To realize it in this paper, we propose a novel algorithm based on feature analysis in shearlet domain. Firstly, as one of multi-scale geometric analysis (MGA), we introduce the theory and superiority of shearlet transform. Secondly, after analyzing the defects of traditional thresholding technique to suppress noise, we propose a novel feature extraction distinguishing image structures from noise well and use it to improve the traditional thresholding technique. Thirdly, with computing the correlations between neighboring shearlet coefficients, the feature attribute maps identifying the weak detail and strong edges are completed to improve the generalized unsharped masking (GUM). At last, experiment results with infrared images captured in different scenes demonstrate that the proposed algorithm suppresses noise efficiently and enhances image edges adaptively.

Automatic identification of abstract online groups

DOEpatents

Engel, David W; Gregory, Michelle L; Bell, Eric B; Cowell, Andrew J; Piatt, Andrew W

2014-04-15

Online abstract groups, in which members aren't explicitly connected, can be automatically identified by computer-implemented methods. The methods involve harvesting records from social media and extracting content-based and structure-based features from each record. Each record includes a social-media posting and is associated with one or more entities. Each feature is stored on a data storage device and includes a computer-readable representation of an attribute of one or more records. The methods further involve grouping records into record groups according to the features of each record. Further still the methods involve calculating an n-dimensional surface representing each record group and defining an outlier as a record having feature-based distances measured from every n-dimensional surface that exceed a threshold value. Each of the n-dimensional surfaces is described by a footprint that characterizes the respective record group as an online abstract group.

Subcutaneous soft tissue sarcoma with rhabdoid features in a dog.

PubMed

Sayama, Ayako; Okado, Keiko; Imaoka, Masako; Yokouchi, Yusuke; Jindo, Toshimasa; Takasaki, Wataru

2014-07-01

A nine-year-old male beagle dog had a white spherical mass in the subcutis of the left lumbar region. Microscopically, spindle to oval cells diffusely proliferated in the fibrous and myxoid stroma. Many neoplastic cells showed rhabdoid features or vacuolated cytoplasm. Immunohistochemically, the neoplastic cells were positive for vimentin and S100 and partly positive for neuron-specific enolase and glial fibrillary acidic protein but were negative for von Willebrand factor, desmin and α-smooth muscle actin. Ultrastructurally, the neoplastic cells had abundant cytoplasmic processes and desmosome-like structures. Cytoplasmic inclusions of rhabdoid-featured cells in HE sections were composed of aggregates of intermediate filaments, and cytoplasmic vacuoles were identified as an invagination of cytoplasm. Although malignant peripheral nerve sheath tumor was suggested according to these results, the present case was diagnosed as a soft tissue sarcoma with rhabdoid features due to a lack of identification of the basal lamina under electron microscopy.

Subcutaneous Soft Tissue Sarcoma with Rhabdoid Features in a Dog

PubMed Central

Sayama, Ayako; Okado, Keiko; Imaoka, Masako; Yokouchi, Yusuke; Jindo, Toshimasa; Takasaki, Wataru

2014-01-01

A nine-year-old male beagle dog had a white spherical mass in the subcutis of the left lumbar region. Microscopically, spindle to oval cells diffusely proliferated in the fibrous and myxoid stroma. Many neoplastic cells showed rhabdoid features or vacuolated cytoplasm. Immunohistochemically, the neoplastic cells were positive for vimentin and S100 and partly positive for neuron-specific enolase and glial fibrillary acidic protein but were negative for von Willebrand factor, desmin and α-smooth muscle actin. Ultrastructurally, the neoplastic cells had abundant cytoplasmic processes and desmosome-like structures. Cytoplasmic inclusions of rhabdoid-featured cells in HE sections were composed of aggregates of intermediate filaments, and cytoplasmic vacuoles were identified as an invagination of cytoplasm. Although malignant peripheral nerve sheath tumor was suggested according to these results, the present case was diagnosed as a soft tissue sarcoma with rhabdoid features due to a lack of identification of the basal lamina under electron microscopy. PMID:25352714

Structural properties of prokaryotic promoter regions correlate with functional features.

PubMed

Meysman, Pieter; Collado-Vides, Julio; Morett, Enrique; Viola, Roberto; Engelen, Kristof; Laukens, Kris

2014-01-01

The structural properties of the DNA molecule are known to play a critical role in transcription. In this paper, the structural profiles of promoter regions were studied within the context of their diversity and their function for eleven prokaryotic species; Escherichia coli, Klebsiella pneumoniae, Salmonella Typhimurium, Pseudomonas auroginosa, Geobacter sulfurreducens Helicobacter pylori, Chlamydophila pneumoniae, Synechocystis sp., Synechoccocus elongates, Bacillus anthracis, and the archaea Sulfolobus solfataricus. The main anchor point for these promoter regions were transcription start sites identified through high-throughput experiments or collected within large curated databases. Prokaryotic promoter regions were found to be less stable and less flexible than the genomic mean across all studied species. However, direct comparison between species revealed differences in their structural profiles that can not solely be explained by the difference in genomic GC content. In addition, comparison with functional data revealed that there are patterns in the promoter structural profiles that can be linked to specific functional loci, such as sigma factor regulation or transcription factor binding. Interestingly, a novel structural element clearly visible near the transcription start site was found in genes associated with essential cellular functions and growth in several species. Our analyses reveals the great diversity in promoter structural profiles both between and within prokaryotic species. We observed relationships between structural diversity and functional features that are interesting prospects for further research to yet uncharacterized functional loci defined by DNA structural properties.

Structures of Pseudomonas aeruginosa β-ketoacyl-(acyl-carrier-protein) synthase II (FabF) and a C164Q mutant provide templates for antibacterial drug discovery and identify a buried potassium ion and a ligand-binding site that is an artefact of the crystal form

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

Baum, Bernhard; Lecker, Laura S. M.; Zoltner, Martin

Three crystal structures of recombinant P. aeruginosa FabF are reported: the apoenzyme, an active-site mutant and a complex with a fragment of a natural product inhibitor. The characterization provides reagents and new information to support antibacterial drug discovery. Bacterial infections remain a serious health concern, in particular causing life-threatening infections of hospitalized and immunocompromised patients. The situation is exacerbated by the rise in antibacterial drug resistance, and new treatments are urgently sought. In this endeavour, accurate structures of molecular targets can support early-stage drug discovery. Here, crystal structures, in three distinct forms, of recombinant Pseudomonas aeruginosa β-ketoacyl-(acyl-carrier-protein) synthase II (FabF)more » are presented. This enzyme, which is involved in fatty-acid biosynthesis, has been validated by genetic and chemical means as an antibiotic target in Gram-positive bacteria and represents a potential target in Gram-negative bacteria. The structures of apo FabF, of a C164Q mutant in which the binding site is altered to resemble the substrate-bound state and of a complex with 3-(benzoylamino)-2-hydroxybenzoic acid are reported. This compound mimics aspects of a known natural product inhibitor, platensimycin, and surprisingly was observed binding outside the active site, interacting with a symmetry-related molecule. An unusual feature is a completely buried potassium-binding site that was identified in all three structures. Comparisons suggest that this may represent a conserved structural feature of FabF relevant to fold stability. The new structures provide templates for structure-based ligand design and, together with the protocols and reagents, may underpin a target-based drug-discovery project for urgently needed antibacterials.« less

Identification of F impurities in F-doped ZnO by synchrotron X-ray absorption near edge structures

NASA Astrophysics Data System (ADS)

Na-Phattalung, Sutassana; Limpijumnong, Sukit; Min, Chul-Hee; Cho, Deok-Yong; Lee, Seung-Ran; Char, Kookrin; Yu, Jaejun

2018-04-01

Synchrotron X-ray absorption near edge structure (XANES) measurements of F K-edge in conjunction with first-principles calculations are used to identify the local structure of the fluorine (F) atom in F-doped ZnO. The ZnO film was grown by pulsed laser deposition with an Nd:YAG laser, and an oxyfluoridation method was used to introduce F ions into the ZnO films. The measured XANES spectrum of the sample was compared against the first-principles XANES calculations based on various models for local atomic structures surrounding F atoms. The observed spectral features are attributed to ZnF2 and FO defects in wurtzite bulk ZnO.

The geometrical structure of quantum theory as a natural generalization of information geometry

NASA Astrophysics Data System (ADS)

Reginatto, Marcel

2015-01-01

Quantum mechanics has a rich geometrical structure which allows for a geometrical formulation of the theory. This formalism was introduced by Kibble and later developed by a number of other authors. The usual approach has been to start from the standard description of quantum mechanics and identify the relevant geometrical features that can be used for the reformulation of the theory. Here this procedure is inverted: the geometrical structure of quantum theory is derived from information geometry, a geometrical structure that may be considered more fundamental, and the Hilbert space of the standard formulation of quantum mechanics is constructed using geometrical quantities. This suggests that quantum theory has its roots in information geometry.

Lithium halide monolayers: Structural, electronic and optical properties by first principles study

NASA Astrophysics Data System (ADS)

Safari, Mandana; Maskaneh, Pegah; Moghadam, Atousa Dashti; Jalilian, Jaafar

2016-09-01

Using first principle study, we investigate the structural, electronic and optical properties of lithium halide monolayers (LiF, LiCl, LiBr). In contrast to graphene and other graphene-like structures that form hexagonal rings in plane, these compounds can form and stabilize in cubic shape interestingly. The type of band structure in these insulators is identified as indirect type and ionic nature of their bonds are illustrated as well. The optical properties demonstrate extremely transparent feature for them as a result of wide band gap in the visible range; also their electron transitions are indicated for achieving a better vision on the absorption mechanism in these kinds of monolayers.

iSS-PseDNC: identifying splicing sites using pseudo dinucleotide composition.

PubMed

Chen, Wei; Feng, Peng-Mian; Lin, Hao; Chou, Kuo-Chen

2014-01-01

In eukaryotic genes, exons are generally interrupted by introns. Accurately removing introns and joining exons together are essential processes in eukaryotic gene expression. With the avalanche of genome sequences generated in the postgenomic age, it is highly desired to develop automated methods for rapid and effective detection of splice sites that play important roles in gene structure annotation and even in RNA splicing. Although a series of computational methods were proposed for splice site identification, most of them neglected the intrinsic local structural properties. In the present study, a predictor called "iSS-PseDNC" was developed for identifying splice sites. In the new predictor, the sequences were formulated by a novel feature-vector called "pseudo dinucleotide composition" (PseDNC) into which six DNA local structural properties were incorporated. It was observed by the rigorous cross-validation tests on two benchmark datasets that the overall success rates achieved by iSS-PseDNC in identifying splice donor site and splice acceptor site were 85.45% and 87.73%, respectively. It is anticipated that iSS-PseDNC may become a useful tool for identifying splice sites and that the six DNA local structural properties described in this paper may provide novel insights for in-depth investigations into the mechanism of RNA splicing.

Evaluation of normal findings using a detailed and focused technique for transcutaneous abdominal ultrasonography in the horse

PubMed Central

2014-01-01

Background Ultrasonography is an important diagnostic tool in the investigation of abdominal disease in the horse. Several factors may affect the ability to image different structures within the abdomen. The aim of the study was to describe the repeatability of identification of abdominal structures in normal horses using a detailed ultrasonographic examination technique and using a focused, limited preparation technique. Methods A detailed abdominal ultrasound examination was performed in five normal horses, repeated on five occasions (total of 25 examinations). The abdomen was divided into ten different imaging sites, and structures identified in each site were recorded. Five imaging sites were then selected for a single focused ultrasound examination in 20 normal horses. Limited patient preparation was performed. Structures were recorded as ‘identified’ if ultrasonographic features could be distinguished. The location of organs and their frequency of identification were recorded. Data from both phases were analysed to determine repeatability of identification of structures in each examination (irrespective of imaging site), and for each imaging site. Results Caecum, colon, spleen, liver and right kidney were repeatably identified using the detailed technique, and had defined locations. Large colon and right kidney were identified in 100% of examinations with both techniques. Liver, spleen, caecum, duodenum and other small intestine were identified more frequently with the detailed examination. Small intestine was most frequently identified in the ventral abdomen, its identification varied markedly within and between horses, and required repeated examinations in some horses. Left kidney could not be identified in every horse using either technique. Sacculated colon was identified in all ventral sites, and was infrequently identified in dorsal sites. Conclusions Caecum, sacculated large intestine, spleen, liver and right kidney were consistently identified with both techniques. There were some normal variations which should be considered when interpreting ultrasonographic findings in clinical cases: left kidney was not always identified, sacculated colon was occasionally identified in dorsal flank sites. Multiple imaging sites and repeated examinations may be required to identify small intestine. A focused examination identified most key structures, but has some limitations compared to a detailed examination. PMID:25238559

Effective Moment Feature Vectors for Protein Domain Structures

PubMed Central

Shi, Jian-Yu; Yiu, Siu-Ming; Zhang, Yan-Ning; Chin, Francis Yuk-Lun

2013-01-01

Imaging processing techniques have been shown to be useful in studying protein domain structures. The idea is to represent the pairwise distances of any two residues of the structure in a 2D distance matrix (DM). Features and/or submatrices are extracted from this DM to represent a domain. Existing approaches, however, may involve a large number of features (100–400) or complicated mathematical operations. Finding fewer but more effective features is always desirable. In this paper, based on some key observations on DMs, we are able to decompose a DM image into four basic binary images, each representing the structural characteristics of a fundamental secondary structure element (SSE) or a motif in the domain. Using the concept of moments in image processing, we further derive 45 structural features based on the four binary images. Together with 4 features extracted from the basic images, we represent the structure of a domain using 49 features. We show that our feature vectors can represent domain structures effectively in terms of the following. (1) We show a higher accuracy for domain classification. (2) We show a clear and consistent distribution of domains using our proposed structural vector space. (3) We are able to cluster the domains according to our moment features and demonstrate a relationship between structural variation and functional diversity. PMID:24391828

Optical diagnostics of turbulent mixing in explosively-driven shock tube

NASA Astrophysics Data System (ADS)

Anderson, James; Hargather, Michael

2016-11-01

Explosively-driven shock tube experiments were performed to investigate the turbulent mixing of explosive product gases and ambient air. A small detonator initiated Al / I2O5 thermite, which produced a shock wave and expanding product gases. Schlieren and imaging spectroscopy were applied simultaneously along a common optical path to identify correlations between turbulent structures and spatially-resolved absorbance. The schlieren imaging identifies flow features including shock waves and turbulent structures while the imaging spectroscopy identifies regions of iodine gas presence in the product gases. Pressure transducers located before and after the optical diagnostic section measure time-resolved pressure. Shock speed is measured from tracking the leading edge of the shockwave in the schlieren images and from the pressure transducers. The turbulent mixing characteristics were determined using digital image processing. Results show changes in shock speed, product gas propagation, and species concentrations for varied explosive charge mass. Funded by DTRA Grant HDTRA1-14-1-0070.

Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction

DOE PAGES

Boiteau, Rene M.; Hoyt, David W.; Nicora, Carrie D.; ...

2018-01-17

Here, we introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS 2), and NMR in a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS 2 approach is well suited for discovery ofmore » new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.« less

The Impact of parasitic loss on solar cells with plasmonic nano-textured rear reflectors.

PubMed

Disney, Claire E R; Pillai, Supriya; Green, Martin A

2017-10-09

Significant photocurrent enhancement has been demonstrated using plasmonic light-trapping structures comprising nanostructured metallic features at the rear of the cell. These structures have conversely been identified as suffering heightened parasitic absorption into the metal at certain resonant wavelengths severely mitigating benefits of light trapping. In this study, we undertook simulations exploring the relationship between enhanced absorption into the solar cell, and parasitic losses in the metal. These simulations reveal that resonant wavelengths associated with high parasitic losses in the metal could also be associated with high absorption enhancement in the solar cell. We identify mechanisms linking these parasitic losses and absorption enhancements, but found that by ensuring correct design, the light trapping structures will have a positive impact on the overall solar cell performance. Our results clearly show that the large angle scattering provided by the plasmonic nanostructures is the reason for the enhanced absorption observed in the solar cells.

Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction

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

Boiteau, Rene M.; Hoyt, David W.; Nicora, Carrie D.

Here, we introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS 2), and NMR in a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS 2 approach is well suited for discovery ofmore » new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.« less

Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction

PubMed Central

Hoyt, David W.; Nicora, Carrie D.; Kinmonth-Schultz, Hannah A.; Ward, Joy K.

2018-01-01

We introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS2), and NMR into a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter out the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture, and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS2 approach is well suited to the discovery of new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases. PMID:29342073

Molecular Dynamics Simulations and Structural Analysis of Giardia duodenalis 14-3-3 Protein-Protein Interactions.

PubMed

Cau, Ylenia; Fiorillo, Annarita; Mori, Mattia; Ilari, Andrea; Botta, Maurizo; Lalle, Marco

2015-12-28

Giardiasis is a gastrointestinal diarrheal illness caused by the protozoan parasite Giardia duodenalis, which affects annually over 200 million people worldwide. The limited antigiardial drug arsenal and the emergence of clinical cases refractory to standard treatments dictate the need for new chemotherapeutics. The 14-3-3 family of regulatory proteins, extensively involved in protein-protein interactions (PPIs) with pSer/pThr clients, represents a highly promising target. Despite homology with human counterparts, the single 14-3-3 of G. duodenalis (g14-3-3) is characterized by a constitutive phosphorylation in a region critical for target binding, thus affecting the function and the conformation of g14-3-3/clients interaction. However, to approach the design of specific small molecule modulators of g14-3-3 PPIs, structural elucidations are required. Here, we present a detailed computational and crystallographic study exploring the implications of g14-3-3 phosphorylation on protein structure and target binding. Self-Guided Langevin Dynamics and classical molecular dynamics simulations show that phosphorylation affects locally and globally g14-3-3 conformation, inducing a structural rearrangement more suitable for target binding. Profitable features for g14-3-3/clients interaction were highlighted using a hydrophobicity-based descriptor to characterize g14-3-3 client peptides. Finally, the X-ray structure of g14-3-3 in complex with a mode-1 prototype phosphopeptide was solved and combined with structure-based simulations to identify molecular features relevant for clients binding to g14-3-3. The data presented herein provide a further and structural understanding of g14-3-3 features and set the basis for drug design studies.

Multiple conformations of the cytidine repressor DNA-binding domain coalesce to one upon recognition of a specific DNA surface.

PubMed

Moody, Colleen L; Tretyachenko-Ladokhina, Vira; Laue, Thomas M; Senear, Donald F; Cocco, Melanie J

2011-08-09

The cytidine repressor (CytR) is a member of the LacR family of bacterial repressors with distinct functional features. The Escherichia coli CytR regulon comprises nine operons whose palindromic operators vary in both sequence and, most significantly, spacing between the recognition half-sites. This suggests a strong likelihood that protein folding would be coupled to DNA binding as a mechanism to accommodate the variety of different operator architectures to which CytR is targeted. Such coupling is a common feature of sequence-specific DNA-binding proteins, including the LacR family repressors; however, there are no significant structural rearrangements upon DNA binding within the three-helix DNA-binding domains (DBDs) studied to date. We used nuclear magnetic resonance (NMR) spectroscopy to characterize the CytR DBD free in solution and to determine the high-resolution structure of a CytR DBD monomer bound specifically to one DNA half-site of the uridine phosphorylase (udp) operator. We find that the free DBD populates multiple distinct conformations distinguished by up to four sets of NMR peaks per residue. This structural heterogeneity is previously unknown in the LacR family. These stable structures coalesce into a single, more stable udp-bound form that features a three-helix bundle containing a canonical helix-turn-helix motif. However, this structure differs from all other LacR family members whose structures are known with regard to the packing of the helices and consequently their relative orientations. Aspects of CytR activity are unique among repressors; we identify here structural properties that are also distinct and that might underlie the different functional properties. © 2011 American Chemical Society

Challenging the state-of-the-art in protein structure prediction: Highlights of experimental target structures for the 10th Critical Assessment of Techniques for Protein Structure Prediction Experiment CASP10

PubMed Central

Kryshtafovych, Andriy; Moult, John; Bales, Patrick; Bazan, J. Fernando; Biasini, Marco; Burgin, Alex; Chen, Chen; Cochran, Frank V.; Craig, Timothy K.; Das, Rhiju; Fass, Deborah; Garcia-Doval, Carmela; Herzberg, Osnat; Lorimer, Donald; Luecke, Hartmut; Ma, Xiaolei; Nelson, Daniel C.; van Raaij, Mark J.; Rohwer, Forest; Segall, Anca; Seguritan, Victor; Zeth, Kornelius; Schwede, Torsten

2014-01-01

For the last two decades, CASP has assessed the state of the art in techniques for protein structure prediction and identified areas which required further development. CASP would not have been possible without the prediction targets provided by the experimental structural biology community. In the latest experiment, CASP10, over 100 structures were suggested as prediction targets, some of which appeared to be extraordinarily difficult for modeling. In this paper, authors of some of the most challenging targets discuss which specific scientific question motivated the experimental structure determination of the target protein, which structural features were especially interesting from a structural or functional perspective, and to what extent these features were correctly reproduced in the predictions submitted to CASP10. Specifically, the following targets will be presented: the acid-gated urea channel, a difficult to predict trans-membrane protein from the important human pathogen Helicobacter pylori; the structure of human interleukin IL-34, a recently discovered helical cytokine; the structure of a functionally uncharacterized enzyme OrfY from Thermoproteus tenax formed by a gene duplication and a novel fold; an ORFan domain of mimivirus sulfhydryl oxidase R596; the fibre protein gp17 from bacteriophage T7; the Bacteriophage CBA-120 tailspike protein; a virus coat protein from metagenomic samples of the marine environment; and finally an unprecedented class of structure prediction targets based on engineered disulfide-rich small proteins. PMID:24318984

Identification of dual-tropic HIV-1 using evolved neural networks.

PubMed

Fogel, Gary B; Lamers, Susanna L; Liu, Enoch S; Salemi, Marco; McGrath, Michael S

2015-11-01

Blocking the binding of the envelope HIV-1 protein to immune cells is a popular concept for development of anti-HIV therapeutics. R5 HIV-1 binds CCR5, X4 HIV-1 binds CXCR4, and dual-tropic HIV-1 can bind either coreceptor for cellular entry. R5 viruses are associated with early infection and over time can evolve to X4 viruses that are associated with immune failure. Dual-tropic HIV-1 is less studied; however, it represents functional antigenic intermediates during the transition of R5 to X4 viruses. Viral tropism is linked partly to the HIV-1 envelope V3 domain, where the amino acid sequence helps dictate the receptor a particular virus will target; however, using V3 sequence information to identify dual-tropic HIV-1 isolates has remained difficult. Our goal in this study was to elucidate features of dual-tropic HIV-1 isolates that assist in the biological understanding of dual-tropism and develop an approach for their detection. Over 1559 HIV-1 subtype B sequences with known tropisms were analyzed. Each sequence was represented by 73 structural, biochemical and regional features. These features were provided to an evolved neural network classifier and evaluated using balanced and unbalanced data sets. The study resolved R5X4 viruses from R5 with an accuracy of 81.8% and from X4 with an accuracy of 78.8%. The approach also identified a set of V3 features (hydrophobicity, structural and polarity) that are associated with tropism transitions. The ability to distinguish R5X4 isolates will improve computational tropism decisions for R5 vs. X4 and assist in HIV-1 research and drug development efforts. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Continental slope morphology in northern Gulf of Mexico mapped with long-range (GLORIA) side-scan data

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

McGregor, B.A.; Garrison, L.E.; Kenyon, N.H.

1985-02-01

GLORIA II long-range side-scan data provide a mosaic of the continental slope in the northern Gulf of Mexico, seaward of the Texas-Louisiana coast. A swath as wide as 30 km and a 10% overlap of the data between parallel track lines provide a continuous picture of the complex slope morphology, which is largely controlled by salt deformation. Morphologic features range from piercement structures approximately 2 km in diameter to basins as much as 30 km across. The GLORIA data delineate the East Breaks submarine slide, where surface lineations are suggestive of deformation features. High-resolution 10 kHz seismic-reflection profiles indicate thatmore » the very irregular surface on the slide has a relief of 10 m. The 3 types of intraslope basins (blocked canyon, interdomal, and collapse) described by A.H. Bouma can be identified on the GLORIA data. The walls of Gyre basin, an example of a blocked canyon, have what are interpreted to be gullies, which are commonly associated with submarine canyons. Another basin downslope has similar gully-like features on the walls, which suggest that it may have been part of the original canyon system. Although many canyon-like features direct the movement of sediment downslope, the present data show that all conduits end in closed basins. No system of basins can be shown to transport sediment across the entire slope between the Mississippi Canyon and the East Breaks slide. Small-scale slumps, which can be identified on the flanks of some of the diapiric structures, also contribute sediments to basins such as Gyre basin.« less

A persistent homology approach to collective behavior in insect swarms

NASA Astrophysics Data System (ADS)

Sinhuber, Michael; Ouellette, Nicholas T.

Various animals from birds and fish to insects tend to form aggregates, displaying self-organized collective swarming behavior. Due to their frequent occurrence in nature and their implications for engineered, collective systems, these systems have been investigated and modeled thoroughly for decades. Common approaches range from modeling them with coupled differential equations on the individual level up to continuum approaches. We present an alternative, topology-based approach for describing swarming behavior at the macroscale rather than the microscale. We study laboratory swarms of Chironomus riparius, a flying, non-biting midge. To obtain the time-resolved three-dimensional trajectories of individual insects, we use a multi-camera stereoimaging and particle-tracking setup. To investigate the swarming behavior in a topological sense, we employ a persistent homology approach to identify persisting structures and features in the insect swarm that elude a direct, ensemble-averaging approach. We are able to identify features of sub-clusters in the swarm that show behavior distinct from that of the remaining swarm members. The coexistence of sub-swarms with different features resembles some non-biological systems such as active colloids or even thermodynamic systems.

Understanding the differences in molecular conformation of carbohydrate and protein in endosperm tissues of grains with different biodegradation kinetics using advanced synchrotron technology

NASA Astrophysics Data System (ADS)

Yu, P.; Block, H. C.; Doiron, K.

2009-01-01

Conventional "wet" chemical analyses rely heavily on the use of harsh chemicals and derivatization, thereby altering native seed structures leaving them unable to detect any original inherent structures within an intact tissue sample. A synchrotron is a giant particle accelerator that turns electrons into light (million times brighter than sunlight) which can be used to study the structure of materials at the molecular level. Synchrotron radiation-based Fourier transform IR microspectroscopy (SR-FTIRM) has been developed as a rapid, direct, non-destructive and bioanalytical technique. This technique, taking advantage of the brightness of synchrotron light and a small effective source size, is capable of exploring the molecular chemistry within the microstructures of a biological tissue without the destruction of inherent structures at ultraspatial resolutions within cellular dimensions. This is in contrast to traditional 'wet' chemical methods, which, during processing for analysis, often result in the destruction of the intrinsic structures of feeds. To date there has been very little application of this technique to the study of plant seed tissue in relation to nutrient utilization. The objective of this study was to use novel synchrotron radiation-based technology (SR-FTIRM) to identify the differences in the molecular chemistry and conformation of carbohydrate and protein in various plant seed endosperms within intact tissues at cellular and subcellular level from grains with different biodegradation kinetics. Barley grain (cv. Harrington) with a high rate (31.3%/h) and extent (78%), corn grain (cv. Pioneer) with a low rate (9.6%/h) and extent of (57%), and wheat grain (cv. AC Barrie) with an intermediate rate (23%/h) and extent (72%) of ruminal DM degradation were selected for evaluation. SR-FTIRM evaluations were performed at the National Synchrotron Light Source at the Brookhaven National Laboratory (Brookhaven, NY). The molecular structure spectral analysis involved the fingerprint regions of ca. 1720-1485 cm -1 (attributed to protein amide I C dbnd O and C sbnd N stretching; amide II N sbnd H bending and C sbnd N stretching), ca. 1650-950 cm -1 (non-structural CHO starch in endosperms), and ca. 1185-800 cm -1 (attributed to total CHO C sbnd O stretching vibrations) together with agglomerative hierarchical cluster and principal component analyses. Analyses involving the protein amide I features consistently identified differences between all three grains. Other analyses involving carbohydrate features were able to differentiate between wheat and barley but failed however to differentiate between wheat and corn. These results suggest that SR-FTIRM plus the multivariate analyses can be used to identify spectral features associated with the molecular structure of endosperm from grains with different biodegradation kinetics, especially in relation to protein structure. The Novel synchrotron radiation-based bioanalytical technique provides a new approach for plant seed structural molecular studies at ultraspatial resolution and within intact tissue in relation to nutrient availability.

K2 ZnSn3 Se8 : A Non-Centrosymmetric Zinc Selenidostannate(IV) Featuring Interesting Covalently Bonded [ZnSn3 Se8 ]2- Layer and Exhibiting Intriguing Second Harmonic Generation Activity.

PubMed

Zhou, Molin; Jiang, Xingxing; Yang, Yi; Guo, Yangwu; Lin, Zheshuai; Yao, JJiyong; Wu, Yicheng

2017-06-19

Non-centrosymmetric zinc selenidostannate(IV) K 2 ZnSn 3 Se 8 was synthesized. It features interesting covalently bonded [ZnSn 3 Se 8 ] 2- layers with K + cations filling in the interlayer voids. The phonon spectrum was calculated to clarify its structural stability. Based on the X-ray diffraction data along with the Raman spectrum, the major bonding features of the title compound were identified. According to the UV/vis-NIR spectroscopy, K 2 ZnSn 3 Se 8 possesses a typical direct band gap of 2.10 eV, which is in good agreement with the band structure calculations. Moreover, our experimental measurements and detailed theoretical calculations reveal that K 2 ZnSn 3 Se 8 is a new phase-matchable nonlinear optical material with a powder second harmonic generation (SHG) signal about 0.6 times of that of AgGaS 2 . © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Illumination-invariant and deformation-tolerant inner knuckle print recognition using portable devices.

PubMed

Xu, Xuemiao; Jin, Qiang; Zhou, Le; Qin, Jing; Wong, Tien-Tsin; Han, Guoqiang

2015-02-12

We propose a novel biometric recognition method that identifies the inner knuckle print (IKP). It is robust enough to confront uncontrolled lighting conditions, pose variations and low imaging quality. Such robustness is crucial for its application on portable devices equipped with consumer-level cameras. We achieve this robustness by two means. First, we propose a novel feature extraction scheme that highlights the salient structure and suppresses incorrect and/or unwanted features. The extracted IKP features retain simple geometry and morphology and reduce the interference of illumination. Second, to counteract the deformation induced by different hand orientations, we propose a novel structure-context descriptor based on local statistics. To our best knowledge, we are the first to simultaneously consider the illumination invariance and deformation tolerance for appearance-based low-resolution hand biometrics. Settings in previous works are more restrictive. They made strong assumptions either about the illumination condition or the restrictive hand orientation. Extensive experiments demonstrate that our method outperforms the state-of-the-art methods in terms of recognition accuracy, especially under uncontrolled lighting conditions and the flexible hand orientation requirement.

Illumination-Invariant and Deformation-Tolerant Inner Knuckle Print Recognition Using Portable Devices

PubMed Central

Xu, Xuemiao; Jin, Qiang; Zhou, Le; Qin, Jing; Wong, Tien-Tsin; Han, Guoqiang

2015-01-01

We propose a novel biometric recognition method that identifies the inner knuckle print (IKP). It is robust enough to confront uncontrolled lighting conditions, pose variations and low imaging quality. Such robustness is crucial for its application on portable devices equipped with consumer-level cameras. We achieve this robustness by two means. First, we propose a novel feature extraction scheme that highlights the salient structure and suppresses incorrect and/or unwanted features. The extracted IKP features retain simple geometry and morphology and reduce the interference of illumination. Second, to counteract the deformation induced by different hand orientations, we propose a novel structure-context descriptor based on local statistics. To our best knowledge, we are the first to simultaneously consider the illumination invariance and deformation tolerance for appearance-based low-resolution hand biometrics. Settings in previous works are more restrictive. They made strong assumptions either about the illumination condition or the restrictive hand orientation. Extensive experiments demonstrate that our method outperforms the state-of-the-art methods in terms of recognition accuracy, especially under uncontrolled lighting conditions and the flexible hand orientation requirement. PMID:25686317

A fast algorithm for identifying friends-of-friends halos

NASA Astrophysics Data System (ADS)

Feng, Y.; Modi, C.

2017-07-01

We describe a simple and fast algorithm for identifying friends-of-friends features and prove its correctness. The algorithm avoids unnecessary expensive neighbor queries, uses minimal memory overhead, and rejects slowdown in high over-density regions. We define our algorithm formally based on pair enumeration, a problem that has been heavily studied in fast 2-point correlation codes and our reference implementation employs a dual KD-tree correlation function code. We construct features in a hierarchical tree structure, and use a splay operation to reduce the average cost of identifying the root of a feature from O [ log L ] to O [ 1 ] (L is the size of a feature) without additional memory costs. This reduces the overall time complexity of merging trees from O [ L log L ] to O [ L ] , reducing the number of operations per splay by orders of magnitude. We next introduce a pruning operation that skips merge operations between two fully self-connected KD-tree nodes. This improves the robustness of the algorithm, reducing the number of merge operations in high density peaks from O [δ2 ] to O [ δ ] . We show that for cosmological data set the algorithm eliminates more than half of merge operations for typically used linking lengths b ∼ 0 . 2 (relative to mean separation). Furthermore, our algorithm is extremely simple and easy to implement on top of an existing pair enumeration code, reusing the optimization effort that has been invested in fast correlation function codes.

Gas hydrate and spatial venting variations in the continental margin offshore Southwestern Taiwan

NASA Astrophysics Data System (ADS)

Lin, S.; Lim, Y.; Hsieh, W.; Yang, T.; Wang, Y.

2006-12-01

Strong BSR, high methane contents and rapid sulfate reduction were found in the continental margin sediments offshore southwestern Taiwan. In order to identify the venting phenomena and its relationship with gas hydrate, this research investigate sea floor vent features using WHOI?|s Towcam system as well as piston core in the study region. A total of 10 dives were conducted on board the r/v OR-1. Pore water sulfate, dissolved sulfide, methane, chloride, del O18 ratio, sediment organic carbon, carbonate content and carbonate del C13 ratio, pyrite-S were measured Large spatial variations were found based on pictures obtained from Towcam system and piston cores. Active venting features include bacteria mat, live dense bivalve patches, gas plume, temperature and salinity fluctuations, rapid sulfate reduction and high concentrations of methane in sediments. In addition, vent chimney, pockmark and large authigenic carbonate buildup were also observed in the active venting area. In contrast, in some areas without active venting features, scatter dead chimney, semi- buried carbonate structures, and dead bivalves were found. Total sulfate depletion was found at depth as shallow as 1 meter below sediment water interface in area near active vent whereas almost no sulfate depletion was observed in areas without any vent feature. Stages of carbonate build up existed, with initial phase dominated by small tube, chimney, and later with massive carbonate structures protruding the sea floor. The appearances of massive carbonate buildup structures seemed to indicate the end stage of gas hydrate venting phenomena.

A distance constrained synaptic plasticity model of C. elegans neuronal network

NASA Astrophysics Data System (ADS)

Badhwar, Rahul; Bagler, Ganesh

2017-03-01

Brain research has been driven by enquiry for principles of brain structure organization and its control mechanisms. The neuronal wiring map of C. elegans, the only complete connectome available till date, presents an incredible opportunity to learn basic governing principles that drive structure and function of its neuronal architecture. Despite its apparently simple nervous system, C. elegans is known to possess complex functions. The nervous system forms an important underlying framework which specifies phenotypic features associated to sensation, movement, conditioning and memory. In this study, with the help of graph theoretical models, we investigated the C. elegans neuronal network to identify network features that are critical for its control. The 'driver neurons' are associated with important biological functions such as reproduction, signalling processes and anatomical structural development. We created 1D and 2D network models of C. elegans neuronal system to probe the role of features that confer controllability and small world nature. The simple 1D ring model is critically poised for the number of feed forward motifs, neuronal clustering and characteristic path-length in response to synaptic rewiring, indicating optimal rewiring. Using empirically observed distance constraint in the neuronal network as a guiding principle, we created a distance constrained synaptic plasticity model that simultaneously explains small world nature, saturation of feed forward motifs as well as observed number of driver neurons. The distance constrained model suggests optimum long distance synaptic connections as a key feature specifying control of the network.

Interpretation of aeromagnetic data in the Jameson Land Basin, central East Greenland: Structures and related mineralized systems

NASA Astrophysics Data System (ADS)

Brethes, Anaïs; Guarnieri, Pierpaolo; Rasmussen, Thorkild Maack; Bauer, Tobias Erich

2018-01-01

This paper provides a detailed interpretation of several aeromagnetic datasets over the Jameson Land Basin in central East Greenland. The interpretation is based on texture and lineament analysis of magnetic data and derivatives of these, in combination with geological field observations. Numerous faults and Cenozoic intrusions were identified and a chronological interpretation of the events responsible for the magnetic features is proposed built on crosscutting relationships and correlated with absolute ages. Lineaments identified in enhanced magnetic data are compared with structures controlling the mineralized systems occurring in the area and form the basis for the interpretations presented in this paper. Several structures associated with base metal mineralization systems that were known at a local scale are here delineated at a larger scale; allowing the identification of areas displaying favorable geological settings for mineralization. This study demonstrates the usefulness of high-resolution airborne magnetic data for detailed structural interpretation and mineral exploration in geological contexts such as the Jameson Land Basin.

POOL server: machine learning application for functional site prediction in proteins.

PubMed

Somarowthu, Srinivas; Ondrechen, Mary Jo

2012-08-01

We present an automated web server for partial order optimum likelihood (POOL), a machine learning application that combines computed electrostatic and geometric information for high-performance prediction of catalytic residues from 3D structures. Input features consist of THEMATICS electrostatics data and pocket information from ConCavity. THEMATICS measures deviation from typical, sigmoidal titration behavior to identify functionally important residues and ConCavity identifies binding pockets by analyzing the surface geometry of protein structures. Both THEMATICS and ConCavity (structure only) do not require the query protein to have any sequence or structure similarity to other proteins. Hence, POOL is applicable to proteins with novel folds and engineered proteins. As an additional option for cases where sequence homologues are available, users can include evolutionary information from INTREPID for enhanced accuracy in site prediction. The web site is free and open to all users with no login requirements at http://www.pool.neu.edu. m.ondrechen@neu.edu Supplementary data are available at Bioinformatics online.

Sequence and structural analyses of nuclear export signals in the NESdb database

PubMed Central

Xu, Darui; Farmer, Alicia; Collett, Garen; Grishin, Nick V.; Chook, Yuh Min

2012-01-01

We compiled >200 nuclear export signal (NES)–containing CRM1 cargoes in a database named NESdb. We analyzed the sequences and three-dimensional structures of natural, experimentally identified NESs and of false-positive NESs that were generated from the database in order to identify properties that might distinguish the two groups of sequences. Analyses of amino acid frequencies, sequence logos, and agreement with existing NES consensus sequences revealed strong preferences for the Φ1-X3-Φ2-X2-Φ3-X-Φ4 pattern and for negatively charged amino acids in the nonhydrophobic positions of experimentally identified NESs but not of false positives. Strong preferences against certain hydrophobic amino acids in the hydrophobic positions were also revealed. These findings led to a new and more precise NES consensus. More important, three-dimensional structures are now available for 68 NESs within 56 different cargo proteins. Analyses of these structures showed that experimentally identified NESs are more likely than the false positives to adopt α-helical conformations that transition to loops at their C-termini and more likely to be surface accessible within their protein domains or be present in disordered or unobserved parts of the structures. Such distinguishing features for real NESs might be useful in future NES prediction efforts. Finally, we also tested CRM1-binding of 40 NESs that were found in the 56 structures. We found that 16 of the NES peptides did not bind CRM1, hence illustrating how NESs are easily misidentified. PMID:22833565

Quantitative Wood Anatomy-Practical Guidelines.

PubMed

von Arx, Georg; Crivellaro, Alan; Prendin, Angela L; Čufar, Katarina; Carrer, Marco

2016-01-01

Quantitative wood anatomy analyzes the variability of xylem anatomical features in trees, shrubs, and herbaceous species to address research questions related to plant functioning, growth, and environment. Among the more frequently considered anatomical features are lumen dimensions and wall thickness of conducting cells, fibers, and several ray properties. The structural properties of each xylem anatomical feature are mostly fixed once they are formed, and define to a large extent its functionality, including transport and storage of water, nutrients, sugars, and hormones, and providing mechanical support. The anatomical features can often be localized within an annual growth ring, which allows to establish intra-annual past and present structure-function relationships and its sensitivity to environmental variability. However, there are many methodological challenges to handle when aiming at producing (large) data sets of xylem anatomical data. Here we describe the different steps from wood sample collection to xylem anatomical data, provide guidance and identify pitfalls, and present different image-analysis tools for the quantification of anatomical features, in particular conducting cells. We show that each data production step from sample collection in the field, microslide preparation in the lab, image capturing through an optical microscope and image analysis with specific tools can readily introduce measurement errors between 5 and 30% and more, whereby the magnitude usually increases the smaller the anatomical features. Such measurement errors-if not avoided or corrected-may make it impossible to extract meaningful xylem anatomical data in light of the rather small range of variability in many anatomical features as observed, for example, within time series of individual plants. Following a rigid protocol and quality control as proposed in this paper is thus mandatory to use quantitative data of xylem anatomical features as a powerful source for many research topics.

Quantitative Wood Anatomy—Practical Guidelines

PubMed Central

von Arx, Georg; Crivellaro, Alan; Prendin, Angela L.; Čufar, Katarina; Carrer, Marco

2016-01-01

Quantitative wood anatomy analyzes the variability of xylem anatomical features in trees, shrubs, and herbaceous species to address research questions related to plant functioning, growth, and environment. Among the more frequently considered anatomical features are lumen dimensions and wall thickness of conducting cells, fibers, and several ray properties. The structural properties of each xylem anatomical feature are mostly fixed once they are formed, and define to a large extent its functionality, including transport and storage of water, nutrients, sugars, and hormones, and providing mechanical support. The anatomical features can often be localized within an annual growth ring, which allows to establish intra-annual past and present structure-function relationships and its sensitivity to environmental variability. However, there are many methodological challenges to handle when aiming at producing (large) data sets of xylem anatomical data. Here we describe the different steps from wood sample collection to xylem anatomical data, provide guidance and identify pitfalls, and present different image-analysis tools for the quantification of anatomical features, in particular conducting cells. We show that each data production step from sample collection in the field, microslide preparation in the lab, image capturing through an optical microscope and image analysis with specific tools can readily introduce measurement errors between 5 and 30% and more, whereby the magnitude usually increases the smaller the anatomical features. Such measurement errors—if not avoided or corrected—may make it impossible to extract meaningful xylem anatomical data in light of the rather small range of variability in many anatomical features as observed, for example, within time series of individual plants. Following a rigid protocol and quality control as proposed in this paper is thus mandatory to use quantitative data of xylem anatomical features as a powerful source for many research topics. PMID:27375641

Non-rigid registration of 3D ultrasound for neurosurgery using automatic feature detection and matching.

PubMed

Machado, Inês; Toews, Matthew; Luo, Jie; Unadkat, Prashin; Essayed, Walid; George, Elizabeth; Teodoro, Pedro; Carvalho, Herculano; Martins, Jorge; Golland, Polina; Pieper, Steve; Frisken, Sarah; Golby, Alexandra; Wells, William

2018-06-04

The brain undergoes significant structural change over the course of neurosurgery, including highly nonlinear deformation and resection. It can be informative to recover the spatial mapping between structures identified in preoperative surgical planning and the intraoperative state of the brain. We present a novel feature-based method for achieving robust, fully automatic deformable registration of intraoperative neurosurgical ultrasound images. A sparse set of local image feature correspondences is first estimated between ultrasound image pairs, after which rigid, affine and thin-plate spline models are used to estimate dense mappings throughout the image. Correspondences are derived from 3D features, distinctive generic image patterns that are automatically extracted from 3D ultrasound images and characterized in terms of their geometry (i.e., location, scale, and orientation) and a descriptor of local image appearance. Feature correspondences between ultrasound images are achieved based on a nearest-neighbor descriptor matching and probabilistic voting model similar to the Hough transform. Experiments demonstrate our method on intraoperative ultrasound images acquired before and after opening of the dura mater, during resection and after resection in nine clinical cases. A total of 1620 automatically extracted 3D feature correspondences were manually validated by eleven experts and used to guide the registration. Then, using manually labeled corresponding landmarks in the pre- and post-resection ultrasound images, we show that our feature-based registration reduces the mean target registration error from an initial value of 3.3 to 1.5 mm. This result demonstrates that the 3D features promise to offer a robust and accurate solution for 3D ultrasound registration and to correct for brain shift in image-guided neurosurgery.

Discriminant Features and Temporal Structure of Nonmanuals in American Sign Language

PubMed Central

Benitez-Quiroz, C. Fabian; Gökgöz, Kadir; Wilbur, Ronnie B.; Martinez, Aleix M.

2014-01-01

To fully define the grammar of American Sign Language (ASL), a linguistic model of its nonmanuals needs to be constructed. While significant progress has been made to understand the features defining ASL manuals, after years of research, much still needs to be done to uncover the discriminant nonmanual components. The major barrier to achieving this goal is the difficulty in correlating facial features and linguistic features, especially since these correlations may be temporally defined. For example, a facial feature (e.g., head moves down) occurring at the end of the movement of another facial feature (e.g., brows moves up), may specify a Hypothetical conditional, but only if this time relationship is maintained. In other instances, the single occurrence of a movement (e.g., brows move up) can be indicative of the same grammatical construction. In the present paper, we introduce a linguistic–computational approach to efficiently carry out this analysis. First, a linguistic model of the face is used to manually annotate a very large set of 2,347 videos of ASL nonmanuals (including tens of thousands of frames). Second, a computational approach is used to determine which features of the linguistic model are more informative of the grammatical rules under study. We used the proposed approach to study five types of sentences – Hypothetical conditionals, Yes/no questions, Wh-questions, Wh-questions postposed, and Assertions – plus their polarities – positive and negative. Our results verify several components of the standard model of ASL nonmanuals and, most importantly, identify several previously unreported features and their temporal relationship. Notably, our results uncovered a complex interaction between head position and mouth shape. These findings define some temporal structures of ASL nonmanuals not previously detected by other approaches. PMID:24516528

Structural insights into species-specific features of the ribosome from the pathogen Staphylococcus aureus

PubMed Central

Eyal, Zohar; Matzov, Donna; Krupkin, Miri; Wekselman, Itai; Paukner, Susanne; Zimmerman, Ella; Rozenberg, Haim; Bashan, Anat; Yonath, Ada

2015-01-01

The emergence of bacterial multidrug resistance to antibiotics threatens to cause regression to the preantibiotic era. Here we present the crystal structure of the large ribosomal subunit from Staphylococcus aureus, a versatile Gram-positive aggressive pathogen, and its complexes with the known antibiotics linezolid and telithromycin, as well as with a new, highly potent pleuromutilin derivative, BC-3205. These crystal structures shed light on specific structural motifs of the S. aureus ribosome and the binding modes of the aforementioned antibiotics. Moreover, by analyzing the ribosome structure and comparing it with those of nonpathogenic bacterial models, we identified some unique internal and peripheral structural motifs that may be potential candidates for improving known antibiotics and for use in the design of selective antibiotic drugs against S. aureus. PMID:26464510

Revealing mesoscopic structural universality with diffusion.

PubMed

Novikov, Dmitry S; Jensen, Jens H; Helpern, Joseph A; Fieremans, Els

2014-04-08

Measuring molecular diffusion is widely used for characterizing materials and living organisms noninvasively. This characterization relies on relations between macroscopic diffusion metrics and structure at the mesoscopic scale commensurate with the diffusion length. Establishing such relations remains a fundamental challenge, hindering progress in materials science, porous media, and biomedical imaging. Here we show that the dynamical exponent in the time dependence of the diffusion coefficient distinguishes between the universality classes of the mesoscopic structural complexity. Our approach enables the interpretation of diffusion measurements by objectively selecting and modeling the most relevant structural features. As an example, the specific values of the dynamical exponent allow us to identify the relevant mesoscopic structure affecting MRI-measured water diffusion in muscles and in brain, and to elucidate the structural changes behind the decrease of diffusion coefficient in ischemic stroke.

Integrative topological analysis of mass spectrometry data reveals molecular features with clinical relevance in esophageal squamous cell carcinoma

PubMed Central

Gao, She-Gan; Liu, Rui-Min; Zhao, Yun-Gang; Wang, Pei; Ward, Douglas G.; Wang, Guang-Chao; Guo, Xiang-Qian; Gu, Juan; Niu, Wan-Bin; Zhang, Tian; Martin, Ashley; Guo, Zhi-Peng; Feng, Xiao-Shan; Qi, Yi-Jun; Ma, Yuan-Fang

2016-01-01

Combining MS-based proteomic data with network and topological features of such network would identify more clinically relevant molecules and meaningfully expand the repertoire of proteins derived from MS analysis. The integrative topological indexes representing 95.96% information of seven individual topological measures of node proteins were calculated within a protein-protein interaction (PPI) network, built using 244 differentially expressed proteins (DEPs) identified by iTRAQ 2D-LC-MS/MS. Compared with DEPs, differentially expressed genes (DEGs) and comprehensive features (CFs), structurally dominant nodes (SDNs) based on integrative topological index distribution produced comparable classification performance in three different clinical settings using five independent gene expression data sets. The signature molecules of SDN-based classifier for distinction of early from late clinical TNM stages were enriched in biological traits of protein synthesis, intracellular localization and ribosome biogenesis, which suggests that ribosome biogenesis represents a promising therapeutic target for treating ESCC. In addition, ITGB1 expression selected exclusively by integrative topological measures correlated with clinical stages and prognosis, which was further validated with two independent cohorts of ESCC samples. Thus the integrative topological analysis of PPI networks proposed in this study provides an alternative approach to identify potential biomarkers and therapeutic targets from MS/MS data with functional insights in ESCC. PMID:26898710

Automated classification of mouse pup isolation syllables: from cluster analysis to an Excel-based "mouse pup syllable classification calculator".

PubMed

Grimsley, Jasmine M S; Gadziola, Marie A; Wenstrup, Jeffrey J

2012-01-01

Mouse pups vocalize at high rates when they are cold or isolated from the nest. The proportions of each syllable type produced carry information about disease state and are being used as behavioral markers for the internal state of animals. Manual classifications of these vocalizations identified 10 syllable types based on their spectro-temporal features. However, manual classification of mouse syllables is time consuming and vulnerable to experimenter bias. This study uses an automated cluster analysis to identify acoustically distinct syllable types produced by CBA/CaJ mouse pups, and then compares the results to prior manual classification methods. The cluster analysis identified two syllable types, based on their frequency bands, that have continuous frequency-time structure, and two syllable types featuring abrupt frequency transitions. Although cluster analysis computed fewer syllable types than manual classification, the clusters represented well the probability distributions of the acoustic features within syllables. These probability distributions indicate that some of the manually classified syllable types are not statistically distinct. The characteristics of the four classified clusters were used to generate a Microsoft Excel-based mouse syllable classifier that rapidly categorizes syllables, with over a 90% match, into the syllable types determined by cluster analysis.

ERTS-1 imagery use in reconnaissance prospecting: Evaluation of commercial utility of ERTS-1 imagery in structural reconnaissance for minerals and petroleum

NASA Technical Reports Server (NTRS)

Saunders, D. F.; Thomas, G. E. (Principal Investigator); Kinsman, F. E.; Beatty, D. F.

1973-01-01

The author has identified the following significant results. This study was performed to investigate applications of ERTS-1 imagery in commercial reconnaissance for mineral and hydrocarbon resources. ERTS-1 imagery collected over five areas in North America (Montana; Colorado; New Mexico-West Texas; Superior Province, Canada; and North Slope, Alaska) has been analyzed for data content including linears, lineaments, and curvilinear anomalies. Locations of these features were mapped and compared with known locations of mineral and hydrocarbon accumulations. Results were analyzed in the context of a simple-shear, block-coupling model. Data analyses have resulted in detection of new lineaments, some of which may be continental in extent, detection of many curvilinear patterns not generally seen on aerial photos, strong evidence of continental regmatic fracture patterns, and realization that geological features can be explained in terms of a simple-shear, block-coupling model. The conculsions are that ERTS-1 imagery is of great value in photogeologic/geomorphic interpretations of regional features, and the simple-shear, block-coupling model provides a means of relating data from ERTS imagery to structures that have controlled emplacement of ore deposits and hydrocarbon accumulations, thus providing a basis for a new approach for reconnaissance for mineral, uranium, gas, and oil deposits and structures.

Malignant lymphoma simulating lymph node toxoplasmosis.

PubMed

Miettinen, M; Franssila, K

1982-03-01

On histological examination of 667 cases originally suspected of lymph node toxoplasmosis, 12 cases were diagnosed as malignant lymphoma and 15 cases as atypical hyperplasia (AH), suspicious of malignant lymphoma. All 12 malignant cases were of Hodgkin's disease: eight of the lymphocyte predominant nodular type, two of lymphocyte predominant diffuse type, and two of the nodular sclerosis type. In all cases, the lymph nodes contained small groups of epithelioid cells which were virtually indistinguishable from those seen in toxoplasmosis. In the differential diagnosis between lymph node toxoplasmosis and malignant lymphoma, the following features were found helpful. In toxoplasmosis the general structure is preserved and germinal centres are frequent, while in malignant lymphoma and in AH the general structure is destroyed. However, in some cases of toxoplasmosis germinal centres may be difficult to identify because their margins are indistinct due to clusters of epithelioid cells. Also, in some types of Hodgkin's disease and in some cases of AH with epithelioid cells, the general structure of the lymph node may be partially preserved. The occurrence of epithelioid cells within germinal centres seems to be a specific feature for toxoplasmosis; it was never seen in malignant lymphoma nor in AH. The occurrence of strands of monocytoid cells (unreife Sinushistiocytose) though a fairly typical feature of toxoplasmosis, was also occasionally seen in Hodgkin's disease or AH.

The Acquisition of Problem-Solving Skills in Mathematics: How Animations Can Aid Understanding of Structural Problem Features and Solution Procedures

ERIC Educational Resources Information Center

Scheiter, Katharina; Gerjets, Peter; Schuh, Julia

2010-01-01

In this paper the augmentation of worked examples with animations for teaching problem-solving skills in mathematics is advocated as an effective instructional method. First, in a cognitive task analysis different knowledge prerequisites are identified for solving mathematical word problems. Second, it is argued that so called hybrid animations…

"Structures beneath the Skin": How School Leaders Use Their Power and Authority To Create Institutional Opportunities for Developing Positive Interethnic Communities.

ERIC Educational Resources Information Center

Norte, Edmundo

1999-01-01

Explores key features of processes school leaders employ to create positive interethnic school communities, identifying five elements for effective intervention and applying an analytical model to each to provide a schema for framing elements of central importance. Addresses how school leaders use their power and authority and how they determine…

Towards Implicational Scales for Use in Chicano English Composition. Papers in Southwest English 1: Research Techniques and Prospects.

ERIC Educational Resources Information Center

Hoffer, Bates

Dialect analysis should follow the procedure for analysis of a new language: collection of a corpus of words, stories, and sentences and identifying structural features of phonology, morphology, syntax, and lexicon. Contrastive analysis between standard English and the native language is used and the ethnic dialect of English is described and…

Modelling high data rate communication network access protocol

NASA Technical Reports Server (NTRS)

Khanna, S.; Foudriat, E. C.; Paterra, Frank; Maly, Kurt J.; Overstreet, C. Michael

1990-01-01

Modeling of high data rate communication systems is different from the low data rate systems. Three simulations were built during the development phase of Carrier Sensed Multiple Access/Ring Network (CSMA/RN) modeling. The first was a model using SIMCRIPT based upon the determination and processing of each event at each node. The second simulation was developed in C based upon isolating the distinct object that can be identified as the ring, the message, the node, and the set of critical events. The third model further identified the basic network functionality by creating a single object, the node which includes the set of critical events which occur at the node. The ring structure is implicit in the node structure. This model was also built in C. Each model is discussed and their features compared. It should be stated that the language used was mainly selected by the model developer because of his past familiarity. Further the models were not built with the intent to compare either structure or language but because the complexity of the problem and initial results contained obvious errors, so alternative models were built to isolate, determine, and correct programming and modeling errors. The CSMA/RN protocol is discussed in sufficient detail to understand modeling complexities. Each model is described along with its features and problems. The models are compared and concluding observations and remarks are presented.

The development of a core syllabus for the teaching of head and neck anatomy to medical students.

PubMed

Tubbs, R Shane; Sorenson, Edward P; Sharma, Amit; Benninger, Brion; Norton, Neil; Loukas, Marios; Moxham, Bernard J

2014-04-01

The study of human anatomy has traditionally served as a fundamental component in the basic science education of medical students, yet there exists a remarkable lack of firm guidance on essential features that must be included in a gross anatomy course, which would constitute a "Core Syllabus" of absolutely mandatory structures and related clinical pathologies. While universal agreement on the details of a core syllabus is elusive, there is a general consensus that a core syllabus aims to identify the minimum level of knowledge expected of recently qualified medical graduates in order to carry out clinical procedures safely and effectively, while avoiding overloading students with unnecessary facts that have less immediate application to their future careers as clinicians. This paper aims to identify consensus standards of essential features of Head and Neck anatomy via a Delphi Panel consisting of anatomists and clinicians who evaluated syllabus content structures (greater than 1,000) as "essential", "important", "acceptable", or "not required." The goal is to provide guidance for program/course directors who intend to provide the optimal balance between establishing a comprehensive list of clinically relevant essential structures and an overwhelming litany, which would otherwise overburden trainees in their initial years of medical school with superficial rote learning, which potentially dilutes the key and enduring fundamental lessons that prepare students for training in any medical field. Copyright © 2014 Wiley Periodicals, Inc.

Micromechanical Characterization of Polysilicon Films through On-Chip Tests

PubMed Central

Mirzazadeh, Ramin; Eftekhar Azam, Saeed; Mariani, Stefano

2016-01-01

When the dimensions of polycrystalline structures become comparable to the average grain size, some reliability issues can be reported for the moving parts of inertial microelectromechanical systems (MEMS). Not only the overall behavior of the device turns out to be affected by a large scattering, but also the sensitivity to imperfections gets enhanced. In this work, through on-chip tests, we experimentally investigate the behavior of thin polysilicon samples using standard electrostatic actuation/sensing. The discrepancy between the target and actual responses of each sample has then been exploited to identify: (i) the overall stiffness of the film and, according to standard continuum elasticity, a morphology-based value of its Young’s modulus; (ii) the relevant over-etch induced by the fabrication process. To properly account for the aforementioned stochastic features at the micro-scale, the identification procedure has been based on particle filtering. A simple analytical reduced-order model of the moving structure has been also developed to account for the nonlinearities in the electrical field, up to pull-in. Results are reported for a set of ten film samples of constant slenderness, and the effects of different actuation mechanisms on the identified micromechanical features are thoroughly discussed. PMID:27483268

Micromechanical Characterization of Polysilicon Films through On-Chip Tests.

PubMed

Mirzazadeh, Ramin; Eftekhar Azam, Saeed; Mariani, Stefano

2016-07-28

When the dimensions of polycrystalline structures become comparable to the average grain size, some reliability issues can be reported for the moving parts of inertial microelectromechanical systems (MEMS). Not only the overall behavior of the device turns out to be affected by a large scattering, but also the sensitivity to imperfections gets enhanced. In this work, through on-chip tests, we experimentally investigate the behavior of thin polysilicon samples using standard electrostatic actuation/sensing. The discrepancy between the target and actual responses of each sample has then been exploited to identify: (i) the overall stiffness of the film and, according to standard continuum elasticity, a morphology-based value of its Young's modulus; (ii) the relevant over-etch induced by the fabrication process. To properly account for the aforementioned stochastic features at the micro-scale, the identification procedure has been based on particle filtering. A simple analytical reduced-order model of the moving structure has been also developed to account for the nonlinearities in the electrical field, up to pull-in. Results are reported for a set of ten film samples of constant slenderness, and the effects of different actuation mechanisms on the identified micromechanical features are thoroughly discussed.

Observational Tests of the Mars Ocean Hypothesis: Selected MOC and MOLA Results

NASA Technical Reports Server (NTRS)

Parker, T. J.; Banerdt, W. B.

1999-01-01

We have begun a detailed analysis of the evidence for and topography of features identified as potential shorelines that have been im-aged by the Mars Orbiter Camera (MOC) during the Aerobraking Hiatus and Science Phasing Orbit periods of the Mars Global Surveyor (MGS) mission. MOC images, comparable in resolution to high-altitude terrestrial aerial photographs, are particularly well suited to address the morphological expressions of these features at scales comparable to known shore morphologies on Earth. Particularly useful are examples of detailed relationships between potential shore features, such as erosional (and depositional) terraces have been cut into "familiar" pre-existing structures and topography in a fashion that points to a shoreline interpretation as the most likely mechanism for their formation. Additional information is contained in the original extended abstract.

Thematic mapper studies of Andean volcanoes

NASA Technical Reports Server (NTRS)

Francis, P. W.

1986-01-01

The primary objective was to identify all the active volcanoes in the Andean region of Bolivia. Morphological features of the Tata Sabaya volcano, Bolivia, were studied with the thematic mapper. Details include marginal levees on lava and pyroclastic flows, and summit crater structure. Valley glacier moraine deposits, not easily identified on the multispectral band scanner, were also unambiguous, and provide useful marker horizons on large volcanic edifices which were built up in preglacial times but which were active subsequently. With such high resolution imagery, it is not only possible to identify potentially active volcanoes, but also to use standard photogeological interpretation to outline the history of individual volcanoes.

A lack of Birbeck granules in Langerhans cells is associated with a naturally occurring point mutation in the human Langerin gene.

PubMed

Verdijk, Pauline; Dijkman, Remco; Plasmeijer, Elsemieke I; Mulder, Aat A; Zoutman, Willem H; Mieke Mommaas, A; Tensen, Cornelis P

2005-04-01

A heterozygous mutation in the Langerin gene corresponding to position 837 in the Langerin mRNA was identified in a person deficient in Birbeck granules (BG). This mutation results in an amino acid replacement of tryptophan by arginine at position 264 in the carbohydrate recognition domain of the Langerine protein. Expression of mutated Langerin in human fibroblasts induces tubular-like structures that are negative for BG-specific antibodies and do not resemble the characteristic structural features of BG.

Raman Spectral Signatures as Conformational Probes of Biomolecules

NASA Astrophysics Data System (ADS)

Golan, Amir; Mayorkas, Nitzan; Rosenwaks, Salman; Bar, Ilana

2009-06-01

A first application of ionization-loss stimulated Raman spectroscopy (ILSRS) for monitoring the spectral features of four conformers of a gas phase neurotransmitter (2-phenylethylamine) is reported. The Raman spectra of the conformers show bands that uniquely identify the conformational structure of the molecule and are well matched by density functional theory calculations. The measurement of spectral signatures by ILSRS in an extended spectral range, with a relatively convenient laser source, is extremely important, allowing enhanced accessibility to intra- and inter-molecular forces, which are significant in biological structure and activity.

Raman Spectral Signatures as Conformational Probes of Biomolecules

NASA Astrophysics Data System (ADS)

Bar, Ilana; Golan, Amir; Mayorkas, Nitzan; Rosenwaks, Salman

2009-03-01

A first application of ionization-loss stimulated Raman spectroscopy (ILSRS) monitoring the spectral features of four conformers of a gas phase neurotransmitter (2-phenylethylamine) is reported. The Raman spectra of the conformers show bands that uniquely identify the conformational structure of the molecule and are well matched by density functional theory calculations. The measurement of spectral signatures by ILSRS in an extended spectral range, with a relatively convenient laser source, is extremely important, allowing enhanced accessibility to intra- and inter-molecular forces, which are significant in biological structure and activity.

Raman spectral signatures as conformational probes of gas phase flexible molecules

NASA Astrophysics Data System (ADS)

Golan, Amir; Mayorkas, Nitzan; Rosenwaks, Salman; Bar, Ilana

2009-07-01

A novel application of ionization-loss stimulated Raman spectroscopy (ILSRS) for monitoring the spectral features of four conformers of a gas phase flexible molecule is reported. The Raman spectral signatures of four conformers of 2-phenylethylamine are well matched by the results of density functional theory calculations, showing bands uniquely identifying the structures. The measurement of spectral signatures by ILSRS in an extended spectral range, with a conventional laser source, is instrumental in facilitating the unraveling of intra- and intermolecular interactions that are significant in biological structure and activity.

The structure and energetics of midlatitude disturbances accompanying cold-air outbreaks over East Asia

NASA Technical Reports Server (NTRS)

Lau, N.-C.; Lau, K.-M.

1984-01-01

The evolution of extratropical transient waves as they propagate eastward from the Eurasian land mass toward the Pacific during selected cold surge events in the winter Monsoon Experiment (MONEX) is studied. The outstanding cold surge episodes during MONEX are first identified, and the salient synoptic features related to these events are described using composite streamline charts. The structure of rapidly varying disturbances accompanying the cold surges and the associated energetics are examined, and the behavior of those fluctuations over relatively longer time scales is addressed.

Carbonate Biogenic Structures in Storrs Lake, Bahamas

NASA Technical Reports Server (NTRS)

Byrne, Monica; Morris, Penny A.; Wentworth, Susan J.; Brigmon, Robin L.; McKay, David S.

2001-01-01

Storr's Lake, an inland hypersaline lake on San Salvador Island, Bahamas, contains calcium carbonate-rich lithified mats of filamentous microorganisms, diatoms, associated photosynthetic and chemotrophic bacteria, and trapped sediment. In addition, 16S rRNA analysis indicates the presence of five sulfur-reducing genera of bacteria. These microbes are potential modern-day analogs to some ancient stromatolitic structures. The goals of this study are to identify unique compositional and biogenic features, possibly correlating some of these with some of the sulfate-reducing bacteria. Additional information is contained in the original extended abstract.

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

PubMed Central

2012-01-01

Background Nucleosome distribution along chromatin dictates genomic DNA accessibility and thus profoundly influences gene expression. However, the underlying mechanism of nucleosome formation remains elusive. Here, taking a structural perspective, we systematically explored nucleosome formation potential of genomic sequences and the effect on chromatin organization and gene expression in S. cerevisiae. Results We analyzed twelve structural features related to flexibility, curvature and energy of DNA sequences. The results showed that some structural features such as DNA denaturation, DNA-bending stiffness, Stacking energy, Z-DNA, Propeller twist and free energy, were highly correlated with in vitro and in vivo nucleosome occupancy. Specifically, they can be classified into two classes, one positively and the other negatively correlated with nucleosome occupancy. These two kinds of structural features facilitated nucleosome binding in centromere regions and repressed nucleosome formation in the promoter regions of protein-coding genes to mediate transcriptional regulation. Based on these analyses, we integrated all twelve structural features in a model to predict more accurately nucleosome occupancy in vivo than the existing methods that mainly depend on sequence compositional features. Furthermore, we developed a novel approach, named DLaNe, that located nucleosomes by detecting peaks of structural profiles, and built a meta predictor to integrate information from different structural features. As a comparison, we also constructed a hidden Markov model (HMM) to locate nucleosomes based on the profiles of these structural features. The result showed that the meta DLaNe and HMM-based method performed better than the existing methods, demonstrating the power of these structural features in predicting nucleosome positions. Conclusions Our analysis revealed that DNA structures significantly contribute to nucleosome organization and influence chromatin structure and gene expression regulation. The results indicated that our proposed methods are effective in predicting nucleosome occupancy and positions and that these structural features are highly predictive of nucleosome organization. The implementation of our DLaNe method based on structural features is available online. PMID:22449207

Analysis of laser produced plasmas of gold in the 1-7 nm region

NASA Astrophysics Data System (ADS)

Li, Bowen; Higashiguchi, Takeshi; Otsuka, Takamitsu; Yugami, Noboru; Dunne, Padraig; Kilbane, Deirdre; Sokell, Emma; O'Sullivan, Gerry

2014-04-01

Extreme ultraviolet (EUV) spectra from gold laser produced plasmas were recorded in the 1-7 nm region using two Nd:YAG lasers with pulse lengths of 150 ps and 10 ns, respectively, operating at a range of power densities. The maximum focused peak power density was 9.5 × 1013 W cm-2 for the former and 5.3 × 1012 W cm-2 for the latter. Two intense quasicontinuous intensity bands resulting from n = 4-n = 4 and n = 4-n = 5 unresolved transition arrays dominate the 4-5.5 and 1.5-3.6 nm regions of both spectra. Comparison with atomic structure calculations performed with the Cowan suite of atomic structure codes as well as consideration of previous experimental and theoretical results aided identification of the most prominent features in the spectra. For the ns spectrum, the highest ion stage that could be identified from the n = 4-n = 5 arrays was Au28+ while for the ps plasma the presence of significantly higher stages was deduced and lines due to 4d104f-4d94f2 transitions in Ag-like Au32+ give rise to the strongest observed features within the n = 4-n = 4 array while in the n = 4-n = 5 array it was possible to identify a number of previously unidentified spectral features as resulting from 4f-5g transitions in the spectra of Au XX to Au XXXIII.

Ionospheric response to 17 March 2013 geomagnetic storm identified by data assimilation result

NASA Astrophysics Data System (ADS)

Yue, Xinan; Zhao, Biqiang; Hu, Lianhuan; She, Chengli

2017-04-01

Based on slant total electron content (TEC) observations made by 10 satellites and 450 ground IGS GNSS stations, we constructed a 4-D ionospheric electron density reanalysis during the March 17, 2013 geomagnetic storm. Four main large-scale ionospheric disturbances are identified from reanalysis: (1) The positive storm during the initial phase; (2) The SED (storm enhanced density) structure in both northern and southern hemisphere; (3) The large positive storm in main phase; (4) The significant negative storm in middle and low latitude during recovery phase. We then run the NCAR-TIEGCM model with Heelis electric potential empirical model as polar input. The TIEGCM can reproduce 3 of 4 large-scale structures (except SED) very well. We then further analyzed the altitudinal variations of these large-scale disturbances and found several interesting things, such as the altitude variation of SED, the rotation of positive/negative storm phase with local time. Those structures could not be identified clearly by traditional used data sources, which either has no global coverage or no vertical resolution. The drivers such as neutral wind/density and electric field from TIEGCM simulations are also analyzed to self-consistently explain the identified disturbance features.

General Platform for Systematic Quantitative Evaluation of Small-Molecule Permeability in Bacteria

PubMed Central

2015-01-01

The chemical features that impact small-molecule permeability across bacterial membranes are poorly understood, and the resulting lack of tools to predict permeability presents a major obstacle to the discovery and development of novel antibiotics. Antibacterials are known to have vastly different structural and physicochemical properties compared to nonantiinfective drugs, as illustrated herein by principal component analysis (PCA). To understand how these properties influence bacterial permeability, we have developed a systematic approach to evaluate the penetration of diverse compounds into bacteria with distinct cellular envelopes. Intracellular compound accumulation is quantitated using LC-MS/MS, then PCA and Pearson pairwise correlations are used to identify structural and physicochemical parameters that correlate with accumulation. An initial study using 10 sulfonyladenosines in Escherichia coli, Bacillus subtilis, and Mycobacterium smegmatis has identified nonobvious correlations between chemical structure and permeability that differ among the various bacteria. Effects of cotreatment with efflux pump inhibitors were also investigated. This sets the stage for use of this platform in larger prospective analyses of diverse chemotypes to identify global relationships between chemical structure and bacterial permeability that would enable the development of predictive tools to accelerate antibiotic drug discovery. PMID:25198656

Feature-to-Feature Inference Under Conditions of Cue Restriction and Dimensional Correlation.

PubMed

Lancaster, Matthew E; Homa, Donald

2017-01-01

The present study explored feature-to-feature and label-to-feature inference in a category task for different category structures. In the correlated condition, each of the 4 dimensions comprising the category was positively correlated to each other and to the category label. In the uncorrelated condition, no correlation existed between the 4 dimensions comprising the category, although the dimension to category label correlation matched that of the correlated condition. After learning, participants made inference judgments of a missing feature, given 1, 2, or 3 feature cues; on half the trials, the category label was also included as a cue. The results showed superior inference of features following training on the correlated structure, with accurate inference when only a single feature was presented. In contrast, a single-feature cue resulted in chance levels of inference for the uncorrelated structure. Feature inference systematically improved with number of cues after training on the correlated structure. Surprisingly, a similar outcome was obtained for the uncorrelated structure, an outcome that must have reflected mediation via the category label. A descriptive model is briefly introduced to explain the results, with a suggestion that this paradigm might be profitably extended to hierarchical structures where the levels of feature-to-feature inference might vary with the depth of the hierarchy.

Archaeogeophysical investigations of early Caddo settlement patterning at the Crenshaw site (3MI6)

NASA Astrophysics Data System (ADS)

Samuelsen, John R.

The Teran map, made during Don Domingo Teran de los Rios' expedition for New Spain, shows a Caddo settlement in 1691 with a vacant mound center and many small farmsteads dispersed across the countryside along both banks of the Red River. This map, combined with the 19th Century photographs taken by William Soule, provides a testable model for the settlement pattern of the Caddo people called the Teran-Soule model. This model states that large numbers of people besides a small caretaker population did not inhabit the mound centers, supporting a vacant mound center hypothesis. Recent studies have begun to challenge this hypothesis, using archaeogeophysical techniques to find structures near Middle to Late Caddo mounds. An archaeogeophysical survey of the Crenshaw site along the Great Bend of the Red River was conducted to determine if structures could be found there. Is the settlement pattern at this early Caddo site, occupied between A.D. 700 and 1400, consistent with the late historic model of a vacant mound center? Is there evidence that both Caddo and Fourche Maline occupations existed in horizontally distinct components? The 3.2 hectare survey identified more than 100 possible structures, of which more than 50 are probably structures associated with the Fourche Maline or early Caddo occupations of the site. Several structures were found in linear patterns, including an oval series of possible structures measuring 90 x 85 m in diameter. While cultural affiliation was not determined for most of these features, some can be attributed to Caddo origin based on architectural attributes, such as extended entranceways. This suggests that Crenshaw was not literally vacant, but the presence of extended entranceways suggests that some of the identified features were special use structures, which does not conflict with the vacant mound center hypothesis. However, the large number of possible structures present with unknown cultural affiliations provides ample opportunities for testing the model.

Novel chromatin texture features for the classification of pap smears

NASA Astrophysics Data System (ADS)

Bejnordi, Babak E.; Moshavegh, Ramin; Sujathan, K.; Malm, Patrik; Bengtsson, Ewert; Mehnert, Andrew

2013-03-01

This paper presents a set of novel structural texture features for quantifying nuclear chromatin patterns in cells on a conventional Pap smear. The features are derived from an initial segmentation of the chromatin into bloblike texture primitives. The results of a comprehensive feature selection experiment, including the set of proposed structural texture features and a range of different cytology features drawn from the literature, show that two of the four top ranking features are structural texture features. They also show that a combination of structural and conventional features yields a classification performance of 0.954±0.019 (AUC±SE) for the discrimination of normal (NILM) and abnormal (LSIL and HSIL) slides. The results of a second classification experiment, using only normal-appearing cells from both normal and abnormal slides, demonstrates that a single structural texture feature measuring chromatin margination yields a classification performance of 0.815±0.019. Overall the results demonstrate the efficacy of the proposed structural approach and that it is possible to detect malignancy associated changes (MACs) in Papanicoloau stain.

Mediastinal lymph node detection and station mapping on chest CT using spatial priors and random forest

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

Liu, Jiamin; Hoffman, Joanne; Zhao, Jocelyn

2016-07-15

Purpose: To develop an automated system for mediastinal lymph node detection and station mapping for chest CT. Methods: The contextual organs, trachea, lungs, and spine are first automatically identified to locate the region of interest (ROI) (mediastinum). The authors employ shape features derived from Hessian analysis, local object scale, and circular transformation that are computed per voxel in the ROI. Eight more anatomical structures are simultaneously segmented by multiatlas label fusion. Spatial priors are defined as the relative multidimensional distance vectors corresponding to each structure. Intensity, shape, and spatial prior features are integrated and parsed by a random forest classifiermore » for lymph node detection. The detected candidates are then segmented by the following curve evolution process. Texture features are computed on the segmented lymph nodes and a support vector machine committee is used for final classification. For lymph node station labeling, based on the segmentation results of the above anatomical structures, the textual definitions of mediastinal lymph node map according to the International Association for the Study of Lung Cancer are converted into patient-specific color-coded CT image, where the lymph node station can be automatically assigned for each detected node. Results: The chest CT volumes from 70 patients with 316 enlarged mediastinal lymph nodes are used for validation. For lymph node detection, their system achieves 88% sensitivity at eight false positives per patient. For lymph node station labeling, 84.5% of lymph nodes are correctly assigned to their stations. Conclusions: Multiple-channel shape, intensity, and spatial prior features aggregated by a random forest classifier improve mediastinal lymph node detection on chest CT. Using the location information of segmented anatomic structures from the multiatlas formulation enables accurate identification of lymph node stations.« less

Divergent personality structures of brown (Sapajus apella) and white-faced capuchins (Cebus capucinus).

PubMed

Robinson, Lauren M; Morton, F Blake; Gartner, Marieke C; Widness, Jane; Paukner, Annika; Essler, Jennifer L; Brosnan, Sarah F; Weiss, Alexander

2016-11-01

One way to gain insights into personality evolution is by comparing the personality structures of related species. We compared the personality structure of 240 wild white-faced capuchin monkeys to the personality structure of 100 captive brown capuchin monkeys. An ancillary goal was to test the degree to which different personality questionnaires yielded similar personality dimensions. Both species were rated on a common set of 26 antonym pairs. The brown capuchin monkeys were also rated on the 54-item Hominoid Personality Questionnaire. Our cross-species comparisons revealed 3 personality dimensions-Assertiveness, Openness, and Neuroticism-shared by brown and white-faced capuchins, suggesting that these dimensions were present in the common ancestor of these species. Our comparison of the dimensions derived from the antonym pairs and the Hominoid Personality Questionnaire revealed that three common dimensions were identified by both questionnaires. In addition, the dimension Attentiveness was only identified using the Hominoid Personality Questionnaire. These results indicate that major features of capuchin personality are conserved and that the structure of some traits, such as those related to focus, persistence, and attention, diverged. Further work is needed to identify the evolutionary bases that led to the conservation of some dimensions but not others. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Spectral feature extraction of EEG signals and pattern recognition during mental tasks of 2-D cursor movements for BCI using SVM and ANN.

PubMed

Bascil, M Serdar; Tesneli, Ahmet Y; Temurtas, Feyzullah

2016-09-01

Brain computer interface (BCI) is a new communication way between man and machine. It identifies mental task patterns stored in electroencephalogram (EEG). So, it extracts brain electrical activities recorded by EEG and transforms them machine control commands. The main goal of BCI is to make available assistive environmental devices for paralyzed people such as computers and makes their life easier. This study deals with feature extraction and mental task pattern recognition on 2-D cursor control from EEG as offline analysis approach. The hemispherical power density changes are computed and compared on alpha-beta frequency bands with only mental imagination of cursor movements. First of all, power spectral density (PSD) features of EEG signals are extracted and high dimensional data reduced by principle component analysis (PCA) and independent component analysis (ICA) which are statistical algorithms. In the last stage, all features are classified with two types of support vector machine (SVM) which are linear and least squares (LS-SVM) and three different artificial neural network (ANN) structures which are learning vector quantization (LVQ), multilayer neural network (MLNN) and probabilistic neural network (PNN) and mental task patterns are successfully identified via k-fold cross validation technique.

Statistical universals reveal the structures and functions of human music.

PubMed

Savage, Patrick E; Brown, Steven; Sakai, Emi; Currie, Thomas E

2015-07-21

Music has been called "the universal language of mankind." Although contemporary theories of music evolution often invoke various musical universals, the existence of such universals has been disputed for decades and has never been empirically demonstrated. Here we combine a music-classification scheme with statistical analyses, including phylogenetic comparative methods, to examine a well-sampled global set of 304 music recordings. Our analyses reveal no absolute universals but strong support for many statistical universals that are consistent across all nine geographic regions sampled. These universals include 18 musical features that are common individually as well as a network of 10 features that are commonly associated with one another. They span not only features related to pitch and rhythm that are often cited as putative universals but also rarely cited domains including performance style and social context. These cross-cultural structural regularities of human music may relate to roles in facilitating group coordination and cohesion, as exemplified by the universal tendency to sing, play percussion instruments, and dance to simple, repetitive music in groups. Our findings highlight the need for scientists studying music evolution to expand the range of musical cultures and musical features under consideration. The statistical universals we identified represent important candidates for future investigation.

Statistical universals reveal the structures and functions of human music

PubMed Central

Savage, Patrick E.; Brown, Steven; Sakai, Emi; Currie, Thomas E.

2015-01-01

Music has been called “the universal language of mankind.” Although contemporary theories of music evolution often invoke various musical universals, the existence of such universals has been disputed for decades and has never been empirically demonstrated. Here we combine a music-classification scheme with statistical analyses, including phylogenetic comparative methods, to examine a well-sampled global set of 304 music recordings. Our analyses reveal no absolute universals but strong support for many statistical universals that are consistent across all nine geographic regions sampled. These universals include 18 musical features that are common individually as well as a network of 10 features that are commonly associated with one another. They span not only features related to pitch and rhythm that are often cited as putative universals but also rarely cited domains including performance style and social context. These cross-cultural structural regularities of human music may relate to roles in facilitating group coordination and cohesion, as exemplified by the universal tendency to sing, play percussion instruments, and dance to simple, repetitive music in groups. Our findings highlight the need for scientists studying music evolution to expand the range of musical cultures and musical features under consideration. The statistical universals we identified represent important candidates for future investigation. PMID:26124105

Thermal characterization of QSH crashes in RFX-mod

NASA Astrophysics Data System (ADS)

Fassina, Alessandro; Gobbin, Marco; Franz, Paolo; Marrelli, Lionello; Ruzzon, Alberto

2012-10-01

QSH (Quasi Single Helicity) states have gained a growing interest in RFP research since they show improved confinement and transport features with respect to standard discharges. However, ITBs associated with QSH states can be obtained only in a transient way, and in general with a shorter lifetime with respect to that of the QSH phase [1]. In this work the analysis has essentially the purpose of confirming, with TS data, the Te dynamics seen with the double filter, multichord SXR spectrometer in [1]: TS data allow a better spatial definition of temperature profile and a more reliable description of plasma edge. Te profile features in rising and crashing phases are determined via ensemble averaging, possible precursors of thermal crashes are identified, while q(r) behavior is studied identifying the thermal structures associated with rational surfaces. [4pt] [1] Ruzzon et al, 39th EPS Conference, P2.023

Digital image processing of Seabeam bathymetric data for structural studies of seamounts near the East Pacific Rise

NASA Technical Reports Server (NTRS)

Edwards, M. H.; Arvidson, R. E.; Guinness, E. A.

1984-01-01

The problem of displaying information on the seafloor morphology is attacked by utilizing digital image processing techniques to generate images for Seabeam data covering three young seamounts on the eastern flank of the East Pacific Rise. Errors in locations between crossing tracks are corrected by interactively identifying features and translating tracks relative to a control track. Spatial interpolation techniques using moving averages are used to interpolate between gridded depth values to produce images in shaded relief and color-coded forms. The digitally processed images clarify the structural control on seamount growth and clearly show the lateral extent of volcanic materials, including the distribution and fault control of subsidiary volcanic constructional features. The image presentations also clearly show artifacts related to both residual navigational errors and to depth or location differences that depend on ship heading relative to slope orientation in regions with steep slopes.

Nonlinear dimensionality reduction of CT histogram based feature space for predicting recurrence-free survival in non-small-cell lung cancer

NASA Astrophysics Data System (ADS)

Kawata, Y.; Niki, N.; Ohmatsu, H.; Aokage, K.; Kusumoto, M.; Tsuchida, T.; Eguchi, K.; Kaneko, M.

2015-03-01

Advantages of CT scanners with high resolution have allowed the improved detection of lung cancers. In the recent release of positive results from the National Lung Screening Trial (NLST) in the US showing that CT screening does in fact have a positive impact on the reduction of lung cancer related mortality. While this study does show the efficacy of CT based screening, physicians often face the problems of deciding appropriate management strategies for maximizing patient survival and for preserving lung function. Several key manifold-learning approaches efficiently reveal intrinsic low-dimensional structures latent in high-dimensional data spaces. This study was performed to investigate whether the dimensionality reduction can identify embedded structures from the CT histogram feature of non-small-cell lung cancer (NSCLC) space to improve the performance in predicting the likelihood of RFS for patients with NSCLC.

Impact Crater in Coastal Patagonia

NASA Technical Reports Server (NTRS)

D'Antoni, Hector L; Lasta, Carlos A.; Condon, Estelle (Technical Monitor)

2000-01-01

Impact craters are geological structures attributed to the impact of a meteoroid on the Earth's (or other planet's) surface (Koeberl and Sharpton. 1999). The inner planets of the solar system as well as other bodies such as our moon show extensive meteoroid impacts (Gallant 1964, French 1998). Because of its size and gravity, we may assume that the Earth has been heavily bombarded but weathering and erosion have erased or masked most of these features. In the 1920's, a meteor crater (Mark 1987) was identified in Arizona and to this first finding the identification of a large number of impact structures on Earth followed (Hodge 1994). Shock metamorphic effects are associated with meteorite impact craters. Due to extremely high pressures, shatter cones are produced as well as planar features in quartz and feldspar grains, diaplectic glass and high-pressure mineral phases such as stishovite (French 1998).

Optimal Design of Experiments by Combining Coarse and Fine Measurements

NASA Astrophysics Data System (ADS)

Lee, Alpha A.; Brenner, Michael P.; Colwell, Lucy J.

2017-11-01

In many contexts, it is extremely costly to perform enough high-quality experimental measurements to accurately parametrize a predictive quantitative model. However, it is often much easier to carry out large numbers of experiments that indicate whether each sample is above or below a given threshold. Can many such categorical or "coarse" measurements be combined with a much smaller number of high-resolution or "fine" measurements to yield accurate models? Here, we demonstrate an intuitive strategy, inspired by statistical physics, wherein the coarse measurements are used to identify the salient features of the data, while the fine measurements determine the relative importance of these features. A linear model is inferred from the fine measurements, augmented by a quadratic term that captures the correlation structure of the coarse data. We illustrate our strategy by considering the problems of predicting the antimalarial potency and aqueous solubility of small organic molecules from their 2D molecular structure.

Topographic Map of Chryse Planitia with Location of Possible Buried Basin

NASA Technical Reports Server (NTRS)

2005-01-01

This topographic map, based on data from the Mars Orbiter Laser Altimeter, shows the ground track of the 1,892nd and the 1,903rd orbits of Mars Express and the arc structures detected by that orbiter's Mars Advanced Radar for Subsurface and Ionospheric Sounding (MARSIS). The arc structures are interpreted to be part of a buried impact basin about 250 kilometers (155 miles) in diameter.

The topographic relief represented in the image is 1 kilometer (0.6 mile), from low (purple) to high (red). The projected arcs are shown in red for orbit 1892 and white for orbit 1903. There is no obvious feature in the surface topography that corresponds to the buried feature identified with MARSIS data.

NASA and the Italian Space Agency jointly funded the MARSIS instrument on the European Space Agency's Mars Express orbiter. The Mars Orbiter Laser Altimeter is an instrument on NASA's Mars Global Surveyor orbiter.

High-resolution angle-resolved photoemission study of electronic structure and charge-density wave formation in HoTe3

NASA Astrophysics Data System (ADS)

Liu, Guodong; Wang, Chenlu; Zhang, Yan; Hu, Bingfeng; Mou, Daixiang; Yu, Li; Zhao, Lin; Zhou, Xingjiang; Wang, Nanlin; Chen, Chuangtian; Xu, Zuyan

We performed high-resolution angle-resolved photoemission spectroscopy (ARPES) measurement on high quality crystal of HoTe3, an intriguing quasi-two-dimensional rare-earth-element tritelluride charge-density-wave (CDW) compound. The main features of the electronic structure in this compound are established by employing a quasi-CW laser (7eV) and a helium discharging lamp (21.22 eV) as excitation light sources. It reveals many bands back folded according to the CDW periodicity and two incommensurate CDW gaps created by perpendicular Fermi surface (FS) nesting vectors. A large gap is found to open in well nested regions of the Fermi surface sheets, whereas other Fermi surface sections with poor nesting remain ungapped. In particular, some peculiar features are identified by using our ultra-high resolution and bulk sensitive laser-ARPES.

Development of purely structure-based pharmacophores for the topoisomerase I-DNA-ligand binding pocket

NASA Astrophysics Data System (ADS)

Drwal, Malgorzata N.; Agama, Keli; Pommier, Yves; Griffith, Renate

2013-12-01

Purely structure-based pharmacophores (SBPs) are an alternative method to ligand-based approaches and have the advantage of describing the entire interaction capability of a binding pocket. Here, we present the development of SBPs for topoisomerase I, an anticancer target with an unusual ligand binding pocket consisting of protein and DNA atoms. Different approaches to cluster and select pharmacophore features are investigated, including hierarchical clustering and energy calculations. In addition, the performance of SBPs is evaluated retrospectively and compared to the performance of ligand- and complex-based pharmacophores. SBPs emerge as a valid method in virtual screening and a complementary approach to ligand-focussed methods. The study further reveals that the choice of pharmacophore feature clustering and selection methods has a large impact on the virtual screening hit lists. A prospective application of the SBPs in virtual screening reveals that they can be used successfully to identify novel topoisomerase inhibitors.

Rate and Gain Limitations of MSGC's and MGC's Combined with GEM and other Preamplification Structures

NASA Technical Reports Server (NTRS)

Fonte, P.; Peskov, V.; Ramsey, B. D.

1998-01-01

We have studied the rate and gain limits of diamond-coated Microstrip Gas Counters (MSGC's) and Micro-Gap Counters (MGC's) when combined with various preamplification structures: Gas Electron Multiplier (GEM), Parallel-Plate Avalanche Chamber (PPAC) or a MICROMEGAS-type structure. Measurements were done both with X rays and alpha particles with various detector geometries and in different gas mixtures at pressures from 0.05 to 10 atm. The results obtained varied significantly with detector design, gas mixture and pressure, but some general features can be identified. We found that in all cases, bare MSGC'S, MGC'S, PPAC's and MICROMEGAS, the maximum achievable gain drops with rate. The addition of preamplification structures significantly increases the gain of MSGC's and MGC'S, but this gain is still rate dependent. There would seem to be a general rate-dependent effect governing the usable gain of all these detectors. We speculate on possible mechanisms for this effect, and identify a safe, spark-free, operation zone for each system (detector + preamplification structure) in the rate-gain coordinate plane.

Recognition of the geologic framework of porphyry deposits on ERTS-1 imagery

NASA Technical Reports Server (NTRS)

Wilson, J. C. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Photointerpretation methods have been most successfully applied in the less vegetated test sites where several previously unknown geologic features have been recognized and known ones extended. Northwest mid-Tertiary faults in the ELY, Nevada area are observed to offset north-trending ranges and abruptly terminate older Mesozoic structures. In the Ray, Arizona area the observed patterns of fault and fracture systems appear to be related to the locations of known porphyry copper deposits. In the Tanacross, Alaska area a number of regional circular features observed may represent near surface intrusions and, therefore, permissive environments for copper porphyries.

Identification of symptom and functional domains that fibromyalgia patients would like to see improved: a cluster analysis.

PubMed

Bennett, Robert M; Russell, Jon; Cappelleri, Joseph C; Bushmakin, Andrew G; Zlateva, Gergana; Sadosky, Alesia

2010-06-28

The purpose of this study was to determine whether some of the clinical features of fibromyalgia (FM) that patients would like to see improved aggregate into definable clusters. Seven hundred and eighty-eight patients with clinically confirmed FM and baseline pain > or =40 mm on a 100 mm visual analogue scale ranked 5 FM clinical features that the subjects would most like to see improved after treatment (one for each priority quintile) from a list of 20 developed during focus groups. For each subject, clinical features were transformed into vectors with rankings assigned values 1-5 (lowest to highest ranking). Logistic analysis was used to create a distance matrix and hierarchical cluster analysis was applied to identify cluster structure. The frequency of cluster selection was determined, and cluster importance was ranked using cluster scores derived from rankings of the clinical features. Multidimensional scaling was used to visualize and conceptualize cluster relationships. Six clinical features clusters were identified and named based on their key characteristics. In order of selection frequency, the clusters were Pain (90%; 4 clinical features), Fatigue (89%; 4 clinical features), Domestic (42%; 4 clinical features), Impairment (29%; 3 functions), Affective (21%; 3 clinical features), and Social (9%; 2 functional). The "Pain Cluster" was ranked of greatest importance by 54% of subjects, followed by Fatigue, which was given the highest ranking by 28% of subjects. Multidimensional scaling mapped these clusters to two dimensions: Status (bounded by Physical and Emotional domains), and Setting (bounded by Individual and Group interactions). Common clinical features of FM could be grouped into 6 clusters (Pain, Fatigue, Domestic, Impairment, Affective, and Social) based on patient perception of relevance to treatment. Furthermore, these 6 clusters could be charted in the 2 dimensions of Status and Setting, thus providing a unique perspective for interpretation of FM symptomatology.

The metabotropic glutamate receptors: structure, activation mechanism and pharmacology.

PubMed

Pin, Jean-Philippe; Acher, Francine

2002-06-01

The metabotropic glutamate receptors are G-protein coupled receptors (GPCR) involved in the regulation of many synapses, including most glutamatergic fast excitatory synapses. Eight subtypes have been identified that can be classified into three groups. The molecular characterization of these receptors revealed proteins much more complex than any other GPCRs. They are composed of a Venus Flytrap (VFT) module where glutamate binds, connected to a heptahelical domain responsible for G-protein coupling. Recent data including the structure of the VFT module determined with and without glutamate, indicate that these receptors function as dimers. Moreover a number of intracellular proteins can regulate their targeting and transduction mechanism. Such structural features of mGlu receptors offer multiple possibilities for synthetic compounds to modulate their activity. In addition to agonists and competitive antagonists acting at the glutamate binding site, a number of non-competitive antagonists with inverse agonist activity, and positive allosteric modulators have been discovered. These later compounds share specific properties that make them good candidates for therapeutic applications. First, their non-amino acid structure makes them pass more easily the blood brain barrier. Second, they are much more selective than any other compound identified so far, being the first subtype selective molecules. Third, for the negative modulators, their non competitive mechanism of action makes them relatively unaffected by high concentrations of glutamate that may be present in disease states (e.g. stroke, epilepsy, neuropathic pain, etc.). Fourth, like the benzodiazepines acting at the GABA(A) receptors, the positive modulators offer a new way to increase the activity of these receptors in vivo, with a low risk of inducing their desensitization. The present review article focuses on the specific structural features of these receptors and highlights the various possibilities these offer for drug development.

Structural and evolutionary adaptation of rhoptry kinases and pseudokinases, a family of coccidian virulence factors

PubMed Central

2013-01-01

Background The widespread protozoan parasite Toxoplasma gondii interferes with host cell functions by exporting the contents of a unique apical organelle, the rhoptry. Among the mix of secreted proteins are an expanded, lineage-specific family of protein kinases termed rhoptry kinases (ROPKs), several of which have been shown to be key virulence factors, including the pseudokinase ROP5. The extent and details of the diversification of this protein family are poorly understood. Results In this study, we comprehensively catalogued the ROPK family in the genomes of Toxoplasma gondii, Neospora caninum and Eimeria tenella, as well as portions of the unfinished genome of Sarcocystis neurona, and classified the identified genes into 42 distinct subfamilies. We systematically compared the rhoptry kinase protein sequences and structures to each other and to the broader superfamily of eukaryotic protein kinases to study the patterns of diversification and neofunctionalization in the ROPK family and its subfamilies. We identified three ROPK sub-clades of particular interest: those bearing a structurally conserved N-terminal extension to the kinase domain (NTE), an E. tenella-specific expansion, and a basal cluster including ROP35 and BPK1 that we term ROPKL. Structural analysis in light of the solved structures ROP2, ROP5, ROP8 and in comparison to typical eukaryotic protein kinases revealed ROPK-specific conservation patterns in two key regions of the kinase domain, surrounding a ROPK-conserved insert in the kinase hinge region and a disulfide bridge in the kinase substrate-binding lobe. We also examined conservation patterns specific to the NTE-bearing clade. We discuss the possible functional consequences of each. Conclusions Our work sheds light on several important but previously unrecognized features shared among rhoptry kinases, as well as the essential differences between active and degenerate protein kinases. We identify the most distinctive ROPK-specific features conserved across both active kinases and pseudokinases, and discuss these in terms of sequence motifs, evolutionary context, structural impact and potential functional relevance. By characterizing the proteins that enable these parasites to invade the host cell and co-opt its signaling mechanisms, we provide guidance on potential therapeutic targets for the diseases caused by coccidian parasites. PMID:23742205

Soft-sediment deformation structures in Cambrian Series 2 tidal deposits (NW Estonia): implications for identifying endogenic triggering mechanisms in ancient sedimentary record

NASA Astrophysics Data System (ADS)

Põldsaar, Kairi

2015-04-01

Soft-sediment deformation structures (SSDS) are documented in several horizons within silt- and sandstones of the Cambrian Series 2 (Dominopolian Stage) Tiskre Formation, and some in the below-deposited argillaceous deposits of the Lükati Formation (northern part of the Baltoscandian Palaeobasin, NW Estonia). The aim of this study was to map, describe, and analyze these deformation features, discuss their deformation mechanism and possible triggers. Load structures (simple load casts, pillows, flame structures, convoluted lamination) with varying shapes and sizes occur in the Tiskre Fm in sedimentary interfaces within medium-bedded peritidal rhythmites (siltstone-argillaceous material) as well as within up to 3 m thick slightly seaward inclined stacked sandstone sequences. Homogenized beds, dish-and-pillar structures, and severely deformed bedding are also found within these stacked units and within a large tidal runoff channel infill. Autoclastic breccias and water-escape channels are rare and occur only in small-scale -- always related to thin, horizontal tidal laminae. Profound sedimentary dykes, sand volcanoes, and thrust faults, which are often related to earthquake triggered soft sediment deformation, were not observed within the studied intervals. Deformation horizon or horizons with large flat-topped pillows often with elongated morphologies occur at or near the boundary between the Tiskre and Lükati formations. Deformation mechanisms identified in this study for the various deformation types are gravitationally unstable reversed density gradient (especially in case of load features that are related to profound sedimentary interfaces) and lateral shear stress due to sediment current drag (in case of deformation structures that not related to loading at any apparent sedimentary interface). Synsedimentary liquefaction was identified as the primary driving force in most of the observed deformation horizons. Clay thixotropy may have contributed in the formation of large sandstone pillows within the Tiskre-Lükati boundary interval at some localities. It is discussed here that the formation of the observed SSDS is genetically related to the restless dynamics of the storm-influenced open marine tidal depositional environment. The most obvious causes of deformation were rapid-deposition, shear and slumping caused by tidal surges, and storm-wave loading.

Predicting and analyzing DNA-binding domains using a systematic approach to identifying a set of informative physicochemical and biochemical properties

PubMed Central

2011-01-01

Background Existing methods of predicting DNA-binding proteins used valuable features of physicochemical properties to design support vector machine (SVM) based classifiers. Generally, selection of physicochemical properties and determination of their corresponding feature vectors rely mainly on known properties of binding mechanism and experience of designers. However, there exists a troublesome problem for designers that some different physicochemical properties have similar vectors of representing 20 amino acids and some closely related physicochemical properties have dissimilar vectors. Results This study proposes a systematic approach (named Auto-IDPCPs) to automatically identify a set of physicochemical and biochemical properties in the AAindex database to design SVM-based classifiers for predicting and analyzing DNA-binding domains/proteins. Auto-IDPCPs consists of 1) clustering 531 amino acid indices in AAindex into 20 clusters using a fuzzy c-means algorithm, 2) utilizing an efficient genetic algorithm based optimization method IBCGA to select an informative feature set of size m to represent sequences, and 3) analyzing the selected features to identify related physicochemical properties which may affect the binding mechanism of DNA-binding domains/proteins. The proposed Auto-IDPCPs identified m=22 features of properties belonging to five clusters for predicting DNA-binding domains with a five-fold cross-validation accuracy of 87.12%, which is promising compared with the accuracy of 86.62% of the existing method PSSM-400. For predicting DNA-binding sequences, the accuracy of 75.50% was obtained using m=28 features, where PSSM-400 has an accuracy of 74.22%. Auto-IDPCPs and PSSM-400 have accuracies of 80.73% and 82.81%, respectively, applied to an independent test data set of DNA-binding domains. Some typical physicochemical properties discovered are hydrophobicity, secondary structure, charge, solvent accessibility, polarity, flexibility, normalized Van Der Waals volume, pK (pK-C, pK-N, pK-COOH and pK-a(RCOOH)), etc. Conclusions The proposed approach Auto-IDPCPs would help designers to investigate informative physicochemical and biochemical properties by considering both prediction accuracy and analysis of binding mechanism simultaneously. The approach Auto-IDPCPs can be also applicable to predict and analyze other protein functions from sequences. PMID:21342579

Insertion and deletion polymorphisms of the ancient AluS family in the human genome.

PubMed

Kryatova, Maria S; Steranka, Jared P; Burns, Kathleen H; Payer, Lindsay M

2017-01-01

Polymorphic Alu elements account for 17% of structural variants in the human genome. The majority of these belong to the youngest AluY subfamilies, and most structural variant discovery efforts have focused on identifying Alu polymorphisms from these currently retrotranspositionally active subfamilies. In this report we analyze polymorphisms from the evolutionarily older AluS subfamily, whose peak activity was tens of millions of years ago. We annotate the AluS polymorphisms, assess their likely mechanism of origin, and evaluate their contribution to structural variation in the human genome. Of 52 previously reported polymorphic AluS elements ascertained for this study, 48 were confirmed to belong to the AluS subfamily using high stringency subfamily classification criteria. Of these, the majority (77%, 37/48) appear to be deletion polymorphisms. Two polymorphic AluS elements (4%) have features of non-classical Alu insertions and one polymorphic AluS element (2%) likely inserted by a mechanism involving internal priming. Seven AluS polymorphisms (15%) appear to have arisen by the classical target-primed reverse transcription (TPRT) retrotransposition mechanism. These seven TPRT products are 3' intact with 3' poly-A tails, and are flanked by target site duplications; L1 ORF2p endonuclease cleavage sites were also observed, providing additional evidence that these are L1 ORF2p endonuclease-mediated TPRT insertions. Further sequence analysis showed strong conservation of both the RNA polymerase III promoter and SRP9/14 binding sites, important for mediating transcription and interaction with retrotransposition machinery, respectively. This conservation of functional features implies that some of these are fairly recent insertions since they have not diverged significantly from their respective retrotranspositionally competent source elements. Of the polymorphic AluS elements evaluated in this report, 15% (7/48) have features consistent with TPRT-mediated insertion, thus suggesting that some AluS elements have been more active recently than previously thought, or that fixation of AluS insertion alleles remains incomplete. These data expand the potential significance of polymorphic AluS elements in contributing to structural variation in the human genome. Future discovery efforts focusing on polymorphic AluS elements are likely to identify more such polymorphisms, and approaches tailored to identify deletion alleles may be warranted.

Sequential projection pursuit for optimised vibration-based damage detection in an experimental wind turbine blade

NASA Astrophysics Data System (ADS)

Hoell, Simon; Omenzetter, Piotr

2018-02-01

To advance the concept of smart structures in large systems, such as wind turbines (WTs), it is desirable to be able to detect structural damage early while using minimal instrumentation. Data-driven vibration-based damage detection methods can be competitive in that respect because global vibrational responses encompass the entire structure. Multivariate damage sensitive features (DSFs) extracted from acceleration responses enable to detect changes in a structure via statistical methods. However, even though such DSFs contain information about the structural state, they may not be optimised for the damage detection task. This paper addresses the shortcoming by exploring a DSF projection technique specialised for statistical structural damage detection. High dimensional initial DSFs are projected onto a low-dimensional space for improved damage detection performance and simultaneous computational burden reduction. The technique is based on sequential projection pursuit where the projection vectors are optimised one by one using an advanced evolutionary strategy. The approach is applied to laboratory experiments with a small-scale WT blade under wind-like excitations. Autocorrelation function coefficients calculated from acceleration signals are employed as DSFs. The optimal numbers of projection vectors are identified with the help of a fast forward selection procedure. To benchmark the proposed method, selections of original DSFs as well as principal component analysis scores from these features are additionally investigated. The optimised DSFs are tested for damage detection on previously unseen data from the healthy state and a wide range of damage scenarios. It is demonstrated that using selected subsets of the initial and transformed DSFs improves damage detectability compared to the full set of features. Furthermore, superior results can be achieved by projecting autocorrelation coefficients onto just a single optimised projection vector.

Structural and Practical Identifiability Issues of Immuno-Epidemiological Vector-Host Models with Application to Rift Valley Fever.

PubMed

Tuncer, Necibe; Gulbudak, Hayriye; Cannataro, Vincent L; Martcheva, Maia

2016-09-01

In this article, we discuss the structural and practical identifiability of a nested immuno-epidemiological model of arbovirus diseases, where host-vector transmission rate, host recovery, and disease-induced death rates are governed by the within-host immune system. We incorporate the newest ideas and the most up-to-date features of numerical methods to fit multi-scale models to multi-scale data. For an immunological model, we use Rift Valley Fever Virus (RVFV) time-series data obtained from livestock under laboratory experiments, and for an epidemiological model we incorporate a human compartment to the nested model and use the number of human RVFV cases reported by the CDC during the 2006-2007 Kenya outbreak. We show that the immunological model is not structurally identifiable for the measurements of time-series viremia concentrations in the host. Thus, we study the non-dimensionalized and scaled versions of the immunological model and prove that both are structurally globally identifiable. After fixing estimated parameter values for the immunological model derived from the scaled model, we develop a numerical method to fit observable RVFV epidemiological data to the nested model for the remaining parameter values of the multi-scale system. For the given (CDC) data set, Monte Carlo simulations indicate that only three parameters of the epidemiological model are practically identifiable when the immune model parameters are fixed. Alternatively, we fit the multi-scale data to the multi-scale model simultaneously. Monte Carlo simulations for the simultaneous fitting suggest that the parameters of the immunological model and the parameters of the immuno-epidemiological model are practically identifiable. We suggest that analytic approaches for studying the structural identifiability of nested models are a necessity, so that identifiable parameter combinations can be derived to reparameterize the nested model to obtain an identifiable one. This is a crucial step in developing multi-scale models which explain multi-scale data.

Observations, theoretical ideas and modeling of turbulent flows: Past, present and future

NASA Technical Reports Server (NTRS)

Chapman, G. T.; Tobak, M.

1985-01-01

Turbulence was analyzed in a historical context featuring the interactions between observations, theoretical ideas, and modeling within three successive movements. These are identified as predominantly statistical, structural and deterministic. The statistical movement is criticized for its failure to deal with the structural elements observed in turbulent flows. The structural movement is criticized for its failure to embody observed structural elements within a formal theory. The deterministic movement is described as having the potential of overcoming these deficiencies by allowing structural elements to exhibit chaotic behavior that is nevertheless embodied within a theory. Four major ideas of this movement are described: bifurcation theory, strange attractors, fractals, and the renormalization group. A framework for the future study of turbulent flows is proposed, based on the premises of the deterministic movement.

AutoSite: an automated approach for pseudo-ligands prediction—from ligand-binding sites identification to predicting key ligand atoms

PubMed Central

Ravindranath, Pradeep Anand; Sanner, Michel F.

2016-01-01

Motivation: The identification of ligand-binding sites from a protein structure facilitates computational drug design and optimization, and protein function assignment. We introduce AutoSite: an efficient software tool for identifying ligand-binding sites and predicting pseudo ligand corresponding to each binding site identified. Binding sites are reported as clusters of 3D points called fills in which every point is labelled as hydrophobic or as hydrogen bond donor or acceptor. From these fills AutoSite derives feature points: a set of putative positions of hydrophobic-, and hydrogen-bond forming ligand atoms. Results: We show that AutoSite identifies ligand-binding sites with higher accuracy than other leading methods, and produces fills that better matches the ligand shape and properties, than the fills obtained with a software program with similar capabilities, AutoLigand. In addition, we demonstrate that for the Astex Diverse Set, the feature points identify 79% of hydrophobic ligand atoms, and 81% and 62% of the hydrogen acceptor and donor hydrogen ligand atoms interacting with the receptor, and predict 81.2% of water molecules mediating interactions between ligand and receptor. Finally, we illustrate potential uses of the predicted feature points in the context of lead optimization in drug discovery projects. Availability and Implementation: http://adfr.scripps.edu/AutoDockFR/autosite.html Contact: sanner@scripps.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27354702

Ultra-Widefield Steering-Based SD-OCT Imaging of the Retinal Periphery

PubMed Central

Choudhry, Netan; Golding, John; Manry, Matthew W.; Rao, Rajesh C.

2016-01-01

Objective To describe the spectral-domain optical coherence tomography (SD-OCT) features of peripheral retinal findings using an ultra-widefield (UWF) steering technique to image the retinal periphery. Design Observational study. Participants 68 patients (68 eyes) with 19 peripheral retinal features. Main Outcome Measures SD-OCT-based structural features. Methods Nineteen peripheral retinal features including: vortex vein, congenital hypertrophy of the retinal pigment epithelium (CHRPE), pars plana, ora serrata pearl, typical cystoid degeneration (TCD), cystic retinal tuft, meridional fold, lattice and cobblestone degeneration, retinal hole, retinal tear, rhegmatogenous retinal detachment (RRD), typical degenerative senile retinoschisis, peripheral laser coagulation scars, ora tooth, cryopexy scars (retinal tear and treated retinoblastoma scar), bone spicules, white without pressure, and peripheral drusen were identified by peripheral clinical examination. Near infrared (NIR) scanning laser ophthalmoscopy (SLO) images and SD-OCT of these entities were registered to UWF color photographs. Results SD-OCT resolved structural features of all peripheral findings. Dilated hyporeflective tubular structures within the choroid were observed in the vortex vein. Loss of retinal lamination, neural retinal attenuation, RPE loss or hypertrophy were seen in several entities including CHRPE, ora serrata pearl, TCD, cystic retinal tuft, meridional fold, lattice and cobblestone degenerations. Hyporeflective intraretinal spaces, indicating cystoid or schitic fluid, were seen in ora serrata pearl, ora tooth, TCD, cystic retinal tuft, meridional fold, retinal hole, and typical degenerative senile retinoschisis. The vitreoretinal interface, which often consisted of lamellae-like structures of the condensed cortical vitreous near or adherent to the neural retina, appeared clearly in most peripheral findings, confirming its association with many low-risk and vision-threatening pathologies such as lattice degeneration, meridional folds, retinal breaks, and RRDs. Conclusions UWF steering technique-based SD-OCT imaging of the retinal periphery is feasible with current commercially available devices, and provides detailed anatomical information of the peripheral retina, including benign and pathological entities, not previously imaged. This imaging technique may deepen our structural understanding of these entities, their potentially associated macular and systemic pathologies, and may influence decision-making in clinical practice, particularly in areas with teleretinal capabilities but poor access to retinal specialists. PMID:26992837

Aromatic Structure in Simulates Titan Aerosol

NASA Technical Reports Server (NTRS)

Trainer, Melissa G.; Loeffler, M. J.; Anderson, C. M.; Hudson, R. L.; Samuelson, R. E.; Moore, M. A.

2011-01-01

Observations of Titan by the Cassini Composite Infrared Spectrometer (CIRS) between 560 and 20 per centimeter (approximately 18 to 500 micrometers) have been used to infer the vertical variations of Titan's ice abundances, as well as those of the aerosol from the surface to an altitude of 300 km [1]. The aerosol has a broad emission feature centered approximately at 140 per centimeter (71 micrometers). As seen in Figure 1, this feature cannot be reproduced using currently available optical constants from laboratory-generated Titan aerosol analogs [2]. The far-IR is uniquely qualified for investigating low-energy vibrational motions within the lattice structures of COITIDlex aerosol. The feature observed by CIRS is broad, and does not likely arise from individual molecules, but rather is representative of the skeletal movements of macromolecules. Since Cassini's arrival at Titan, benzene (C6H6) has been detected in the atmosphere at ppm levels as well as ions that may be polycyclic aromatic hydrocarbons (PAHs) [3]. We speculate that the feature may be a blended composite that can be identified with low-energy vibrations of two-dimensional lattice structures of large molecules, such as PAHs or nitrogenated aromatics. Such structures do not dominate the composition of analog materials generated from CH4 and N2 irradiation. We are performing studies forming aerosol analog via UV irradiation of aromatic precursors - specifically C6H6 - to understand how the unique chemical architecture of the products will influence the observable aerosol characteristics. The optical and chemical properties of the aromatic analog will be compared to those formed from CH4/N2 mixtures, with a focus on the as-yet unidentified far-IR absorbance feature. Preliminary results indicate that the photochemically-formed aromatic aerosol has distinct chemical composition, and may incorporate nitrogen either into the ring structure or adjoined chemical groups. These compositional differences are demonstrated in the aerosol mass spectra shown in Figure 2. The aromatic aerosol also demonstrates strong chemical reactivity when exposed to laboratory air, indicating substantial stored chemical potential. Oxidatoin and solubility studies wil be presented and implicatoins for prebiotic chemistry o nTitan will be discussed.

Processing of hierarchical syntactic structure in music.

PubMed

Koelsch, Stefan; Rohrmeier, Martin; Torrecuso, Renzo; Jentschke, Sebastian

2013-09-17

Hierarchical structure with nested nonlocal dependencies is a key feature of human language and can be identified theoretically in most pieces of tonal music. However, previous studies have argued against the perception of such structures in music. Here, we show processing of nonlocal dependencies in music. We presented chorales by J. S. Bach and modified versions in which the hierarchical structure was rendered irregular whereas the local structure was kept intact. Brain electric responses differed between regular and irregular hierarchical structures, in both musicians and nonmusicians. This finding indicates that, when listening to music, humans apply cognitive processes that are capable of dealing with long-distance dependencies resulting from hierarchically organized syntactic structures. Our results reveal that a brain mechanism fundamental for syntactic processing is engaged during the perception of music, indicating that processing of hierarchical structure with nested nonlocal dependencies is not just a key component of human language, but a multidomain capacity of human cognition.