Structural health monitoring of plates with surface features using guided ultrasonic waves

NASA Astrophysics Data System (ADS)

Fromme, P.

2009-03-01

Distributed array systems for guided ultrasonic waves offer an efficient way for the long-term monitoring of the structural integrity of large plate-like structures. The measurement concept involving baseline subtraction has been demonstrated under laboratory conditions. For the application to real technical structures it needs to be shown that the methodology works equally well in the presence of structural and surface features. Problems employing this structural health monitoring concept can occur due to the presence of additional changes in the signal reflected at undamaged parts of the structure. The influence of the signal processing parameters and transducer placement on the damage detection and localization accuracy is discussed. The use of permanently attached, distributed sensors for the A0 Lamb wave mode has been investigated. Results are presented using experimental data obtained from laboratory measurements and Finite Element simulated signals for a large steel plate with a welded stiffener.

Weighted Feature Significance: A Simple, Interpretable Model of Compound Toxicity Based on the Statistical Enrichment of Structural Features

PubMed Central

Huang, Ruili; Southall, Noel; Xia, Menghang; Cho, Ming-Hsuang; Jadhav, Ajit; Nguyen, Dac-Trung; Inglese, James; Tice, Raymond R.; Austin, Christopher P.

2009-01-01

In support of the U.S. Tox21 program, we have developed a simple and chemically intuitive model we call weighted feature significance (WFS) to predict the toxicological activity of compounds, based on the statistical enrichment of structural features in toxic compounds. We trained and tested the model on the following: (1) data from quantitative high–throughput screening cytotoxicity and caspase activation assays conducted at the National Institutes of Health Chemical Genomics Center, (2) data from Salmonella typhimurium reverse mutagenicity assays conducted by the U.S. National Toxicology Program, and (3) hepatotoxicity data published in the Registry of Toxic Effects of Chemical Substances. Enrichments of structural features in toxic compounds are evaluated for their statistical significance and compiled into a simple additive model of toxicity and then used to score new compounds for potential toxicity. The predictive power of the model for cytotoxicity was validated using an independent set of compounds from the U.S. Environmental Protection Agency tested also at the National Institutes of Health Chemical Genomics Center. We compared the performance of our WFS approach with classical classification methods such as Naive Bayesian clustering and support vector machines. In most test cases, WFS showed similar or slightly better predictive power, especially in the prediction of hepatotoxic compounds, where WFS appeared to have the best performance among the three methods. The new algorithm has the important advantages of simplicity, power, interpretability, and ease of implementation. PMID:19805409

The Purification of the Chlamydomonas reinhardtii chloroplast ClpP complex: additional subunits and structural features

PubMed Central

Derrien, Benoît; Majeran, Wojciech; Effantin, Grégory; Ebenezer, Joseph; Friso, Giulia; van Wijk, Klaas J.; Steven, Alasdair C.; Maurizi, Michael R.; Vallon, Olivier

2012-01-01

The ClpP peptidase is a major constituent of the proteolytic machinery of bacteria and organelles. The chloroplast ClpP complex is unusual, in that it associates a large number of subunits, one of which (ClpP1) is encoded in the chloroplast, the others in the nucleus. The complexity of these large hetero-oligomeric complexes has been a major difficulty in their overproduction and biochemical characterization. In this paper, we describe the purification of native chloroplast ClpP complex from the green alga Chlamydomonas reinhardtii, using a strain that carries the Strep-tag II at the C-terminus of the ClpP1 subunit. Similar to land plants, the algal complex comprises active and inactive subunits (3 ClpP and 5 ClpR, respectively). Evidence is presented that a sub-complex can be produced by dissociation, comprising ClpP1 and ClpR1, 2, 3 and 4, similar to the ClpR-ring described in land plants. Our Chlamydomonas ClpP preparation also contains two ClpT subunits, ClpT3 and ClpT4, which like the land plant ClpT1 and ClpT2 show 2 Clp-N domains. ClpTs are believed to function in substrate binding and/or assembly of the two heptameric rings. Phylogenetic analysis indicates that ClpT subunits have appeared independently in Chlorophycean algae, in land plants and in dispersed cyanobacterial genomes. Negative staining electron microscopy shows that the Chlamydomonas complex retains the barrel-like shape of homo-oligomeric ClpPs, with 4 additional peripheral masses that we speculate represent either the additional IS1 domain of ClpP1 (a feature unique to algae) or ClpTs or extensions of ClpR subunits PMID:22772861

GALT protein database: querying structural and functional features of GALT enzyme.

PubMed

d'Acierno, Antonio; Facchiano, Angelo; Marabotti, Anna

2014-09-01

Knowledge of the impact of variations on protein structure can enhance the comprehension of the mechanisms of genetic diseases related to that protein. Here, we present a new version of GALT Protein Database, a Web-accessible data repository for the storage and interrogation of structural effects of variations of the enzyme galactose-1-phosphate uridylyltransferase (GALT), the impairment of which leads to classic Galactosemia, a rare genetic disease. This new version of this database now contains the models of 201 missense variants of GALT enzyme, including heterozygous variants, and it allows users not only to retrieve information about the missense variations affecting this protein, but also to investigate their impact on substrate binding, intersubunit interactions, stability, and other structural features. In addition, it allows the interactive visualization of the models of variants collected into the database. We have developed additional tools to improve the use of the database by nonspecialized users. This Web-accessible database (http://bioinformatica.isa.cnr.it/GALT/GALT2.0) represents a model of tools potentially suitable for application to other proteins that are involved in human pathologies and that are subjected to genetic variations. © 2014 WILEY PERIODICALS, INC.

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.

Extracting physicochemical features to predict protein secondary structure.

PubMed

Huang, Yin-Fu; Chen, Shu-Ying

2013-01-01

We propose a protein secondary structure prediction method based on position-specific scoring matrix (PSSM) profiles and four physicochemical features including conformation parameters, net charges, hydrophobic, and side chain mass. First, the SVM with the optimal window size and the optimal parameters of the kernel function is found. Then, we train the SVM using the PSSM profiles generated from PSI-BLAST and the physicochemical features extracted from the CB513 data set. Finally, we use the filter to refine the predicted results from the trained SVM. For all the performance measures of our method, Q 3 reaches 79.52, SOV94 reaches 86.10, and SOV99 reaches 74.60; all the measures are higher than those of the SVMpsi method and the SVMfreq method. This validates that considering these physicochemical features in predicting protein secondary structure would exhibit better performances.

Extracting Physicochemical Features to Predict Protein Secondary Structure

PubMed Central

Chen, Shu-Ying

2013-01-01

We propose a protein secondary structure prediction method based on position-specific scoring matrix (PSSM) profiles and four physicochemical features including conformation parameters, net charges, hydrophobic, and side chain mass. First, the SVM with the optimal window size and the optimal parameters of the kernel function is found. Then, we train the SVM using the PSSM profiles generated from PSI-BLAST and the physicochemical features extracted from the CB513 data set. Finally, we use the filter to refine the predicted results from the trained SVM. For all the performance measures of our method, Q 3 reaches 79.52, SOV94 reaches 86.10, and SOV99 reaches 74.60; all the measures are higher than those of the SVMpsi method and the SVMfreq method. This validates that considering these physicochemical features in predicting protein secondary structure would exhibit better performances. PMID:23766688

Subsurface structures of buried features in the lunar Procellarum region

NASA Astrophysics Data System (ADS)

Wang, Wenrui; Heki, Kosuke

2017-07-01

The Gravity Recovery and Interior Laboratory (GRAIL) mission unraveled numbers of features showing strong gravity anomalies without prominent topographic signatures in the lunar Procellarum region. These features, located in different geologic units, are considered to have complex subsurface structures reflecting different evolution processes. By using the GRAIL level-1 data, we estimated the free-air and Bouguer gravity anomalies in several selected regions including such intriguing features. With the three-dimensional inversion technique, we recovered subsurface density structures in these regions.

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.

Diamond field emitter array cathodes and possibilities for employing additive manufacturing for dielectric laser accelerating structures

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

Simakov, Evgenya Ivanovna; Andrews, Heather Lynn; Herman, Matthew Joseph

2016-09-20

These are slides for a presentation at Stanford University. The outline is as follows: Motivation: customers for compact accelerators, LANL's technologies for laser acceleration, DFEA cathodes, and additive manufacturing of micron-size structures. Among the stated conclusions are the following: preliminary study identified DFEA cathodes as promising sources for DLAs--high beam current and small emittance; additive manufacturing with Nanoscribe Professional GT can produce structures with the right scale features for a DLA operating at micron wavelengths (fabrication tolerances need to be studied, DLAs require new materials). Future plans include DLA experiment with a beam produced by the DFEA cathode with fieldmore » emission, demonstration of photoemission from DFEAs, and new structures to print and test.« 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

Features and characterization needs of rubber composite structures

NASA Technical Reports Server (NTRS)

Tabaddor, Farhad

1989-01-01

Some of the major unique features of rubber composite structures are outlined. The features covered are those related to the material properties, but the analytical features are also briefly discussed. It is essential to recognize these features at the planning stage of any long-range analytical, experimental, or application program. The development of a general and comprehensive program which fully accounts for all the important characteristics of tires, under all the relevant modes of operation, may present a prohibitively expensive and impractical task at the near future. There is therefore a need to develop application methodologies which can utilize the less general models, beyond their theoretical limitations and yet with reasonable reliability, by proper mix of analytical, experimental, and testing activities.

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.

Structural features facilitating tumor cell targeting and internalization by bleomycin and its disaccharide.

PubMed

Yu, Zhiqiang; Paul, Rakesh; Bhattacharya, Chandrabali; Bozeman, Trevor C; Rishel, Michael J; Hecht, Sidney M

2015-05-19

We have shown previously that the bleomycin (BLM) carbohydrate moiety can recapitulate the tumor cell targeting effects of the entire BLM molecule, that BLM itself is modular in nature consisting of a DNA-cleaving aglycone which is delivered selectively to the interior of tumor cells by its carbohydrate moiety, and that there are disaccharides structurally related to the BLM disaccharide which are more efficient than the natural disaccharide at tumor cell targeting/uptake. Because BLM sugars can deliver molecular cargoes selectively to tumor cells, and thus potentially form the basis for a novel antitumor strategy, it seemed important to consider additional structural features capable of affecting the efficiency of tumor cell recognition and delivery. These included the effects of sugar polyvalency and net charge (at physiological pH) on tumor cell recognition, internalization, and trafficking. Since these parameters have been shown to affect cell surface recognition, internalization, and distribution in other contexts, this study has sought to define the effects of these structural features on tumor cell recognition by bleomycin and its disaccharide. We demonstrate that both can have a significant effect on tumor cell binding/internalization, and present data which suggests that the metal ions normally bound by bleomycin following clinical administration may significantly contribute to the efficiency of tumor cell uptake, in addition to their characterized function in DNA cleavage. A BLM disaccharide-Cy5** conjugate incorporating the positively charged dipeptide d-Lys-d-Lys was found to associate with both the mitochondria and the nuclear envelope of DU145 cells, suggesting possible cellular targets for BLM disaccharide-cytotoxin conjugates.

Nonlocal sparse model with adaptive structural clustering for feature extraction of aero-engine bearings

NASA Astrophysics Data System (ADS)

Zhang, Han; Chen, Xuefeng; Du, Zhaohui; Li, Xiang; Yan, Ruqiang

2016-04-01

Fault information of aero-engine bearings presents two particular phenomena, i.e., waveform distortion and impulsive feature frequency band dispersion, which leads to a challenging problem for current techniques of bearing fault diagnosis. Moreover, although many progresses of sparse representation theory have been made in feature extraction of fault information, the theory also confronts inevitable performance degradation due to the fact that relatively weak fault information has not sufficiently prominent and sparse representations. Therefore, a novel nonlocal sparse model (coined NLSM) and its algorithm framework has been proposed in this paper, which goes beyond simple sparsity by introducing more intrinsic structures of feature information. This work adequately exploits the underlying prior information that feature information exhibits nonlocal self-similarity through clustering similar signal fragments and stacking them together into groups. Within this framework, the prior information is transformed into a regularization term and a sparse optimization problem, which could be solved through block coordinate descent method (BCD), is formulated. Additionally, the adaptive structural clustering sparse dictionary learning technique, which utilizes k-Nearest-Neighbor (kNN) clustering and principal component analysis (PCA) learning, is adopted to further enable sufficient sparsity of feature information. Moreover, the selection rule of regularization parameter and computational complexity are described in detail. The performance of the proposed framework is evaluated through numerical experiment and its superiority with respect to the state-of-the-art method in the field is demonstrated through the vibration signals of experimental rig of aircraft engine bearings.

Voroprot: an interactive tool for the analysis and visualization of complex geometric features of protein structure.

PubMed

Olechnovic, Kliment; Margelevicius, Mindaugas; Venclovas, Ceslovas

2011-03-01

We present Voroprot, an interactive cross-platform software tool that provides a unique set of capabilities for exploring geometric features of protein structure. Voroprot allows the construction and visualization of the Apollonius diagram (also known as the additively weighted Voronoi diagram), the Apollonius graph, protein alpha shapes, interatomic contact surfaces, solvent accessible surfaces, pockets and cavities inside protein structure. Voroprot is available for Windows, Linux and Mac OS X operating systems and can be downloaded from http://www.ibt.lt/bioinformatics/voroprot/.

Comparative evaluation of Populus variants total sugar release and structural features following pretreatment and digestion by two distinct biological systems

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

Thomas, Vanessa A.; Kothari, Ninad; Bhagia, Samarthya

Populus natural variants have been shown to realize a broad range of sugar yields during saccharification, however, the structural features responsible for higher sugar release from natural variants are not clear. In addition, the sugar release patterns resulting from digestion with two distinct biological systems, fungal enzymes and Clostridium thermocellum, have yet to be evaluated and compared. This study evaluates the effect of structural features of three natural variant Populus lines, which includes the line BESC standard, with respect to the overall process of sugar release for two different biological systems.

Comparative evaluation of Populus variants total sugar release and structural features following pretreatment and digestion by two distinct biological systems

DOE PAGES

Thomas, Vanessa A.; Kothari, Ninad; Bhagia, Samarthya; ...

2017-11-30

Populus natural variants have been shown to realize a broad range of sugar yields during saccharification, however, the structural features responsible for higher sugar release from natural variants are not clear. In addition, the sugar release patterns resulting from digestion with two distinct biological systems, fungal enzymes and Clostridium thermocellum, have yet to be evaluated and compared. This study evaluates the effect of structural features of three natural variant Populus lines, which includes the line BESC standard, with respect to the overall process of sugar release for two different biological systems.

Structural Features Facilitating Tumor Cell Targeting and Internalization by Bleomycin and Its Disaccharide

PubMed Central

2016-01-01

We have shown previously that the bleomycin (BLM) carbohydrate moiety can recapitulate the tumor cell targeting effects of the entire BLM molecule, that BLM itself is modular in nature consisting of a DNA-cleaving aglycone which is delivered selectively to the interior of tumor cells by its carbohydrate moiety, and that there are disaccharides structurally related to the BLM disaccharide which are more efficient than the natural disaccharide at tumor cell targeting/uptake. Because BLM sugars can deliver molecular cargoes selectively to tumor cells, and thus potentially form the basis for a novel antitumor strategy, it seemed important to consider additional structural features capable of affecting the efficiency of tumor cell recognition and delivery. These included the effects of sugar polyvalency and net charge (at physiological pH) on tumor cell recognition, internalization, and trafficking. Since these parameters have been shown to affect cell surface recognition, internalization, and distribution in other contexts, this study has sought to define the effects of these structural features on tumor cell recognition by bleomycin and its disaccharide. We demonstrate that both can have a significant effect on tumor cell binding/internalization, and present data which suggests that the metal ions normally bound by bleomycin following clinical administration may significantly contribute to the efficiency of tumor cell uptake, in addition to their characterized function in DNA cleavage. A BLM disaccharide-Cy5** conjugate incorporating the positively charged dipeptide d-Lys-d-Lys was found to associate with both the mitochondria and the nuclear envelope of DU145 cells, suggesting possible cellular targets for BLM disaccharide–cytotoxin conjugates. PMID:25905565

Multi-channel MRI segmentation of eye structures and tumors using patient-specific features

PubMed Central

Ciller, Carlos; De Zanet, Sandro; Kamnitsas, Konstantinos; Maeder, Philippe; Glocker, Ben; Munier, Francis L.; Rueckert, Daniel; Thiran, Jean-Philippe

2017-01-01

Retinoblastoma and uveal melanoma are fast spreading eye tumors usually diagnosed by using 2D Fundus Image Photography (Fundus) and 2D Ultrasound (US). Diagnosis and treatment planning of such diseases often require additional complementary imaging to confirm the tumor extend via 3D Magnetic Resonance Imaging (MRI). In this context, having automatic segmentations to estimate the size and the distribution of the pathological tissue would be advantageous towards tumor characterization. Until now, the alternative has been the manual delineation of eye structures, a rather time consuming and error-prone task, to be conducted in multiple MRI sequences simultaneously. This situation, and the lack of tools for accurate eye MRI analysis, reduces the interest in MRI beyond the qualitative evaluation of the optic nerve invasion and the confirmation of recurrent malignancies below calcified tumors. In this manuscript, we propose a new framework for the automatic segmentation of eye structures and ocular tumors in multi-sequence MRI. Our key contribution is the introduction of a pathological eye model from which Eye Patient-Specific Features (EPSF) can be computed. These features combine intensity and shape information of pathological tissue while embedded in healthy structures of the eye. We assess our work on a dataset of pathological patient eyes by computing the Dice Similarity Coefficient (DSC) of the sclera, the cornea, the vitreous humor, the lens and the tumor. In addition, we quantitatively show the superior performance of our pathological eye model as compared to the segmentation obtained by using a healthy model (over 4% DSC) and demonstrate the relevance of our EPSF, which improve the final segmentation regardless of the classifier employed. PMID:28350816

The structure and rainfall features of Tropical Cyclone Rammasun (2002)

NASA Astrophysics Data System (ADS)

Ma, Leiming; Duan, Yihong; Zhu, Yongti

2004-12-01

Tropical Rainfall Measuring Mission (TRMM) data [TRMM Microwave Imager/Precipitation Radar/Visible and Infrared Scanner (TMI/PR/VIRS)] and a numerical model are used to investigate the structure and rainfall features of Tropical Cyclone (TC) Rammasun (2002). Based on the analysis of TRMM data, which are diagnosed together with NCEP/AVN [Aviation (global model)] analysis data, some typical features of TC structure and rainfall are preliminary discovered. Since the limitations of TRMM data are considered for their time resolution and coverage, the world observed by TRMM at several moments cannot be taken as the representation of the whole period of the TC lifecycle, therefore the picture should be reproduced by a numerical model of high quality. To better understand the structure and rainfall features of TC Rammasun, a numerical simulation is carried out with mesoscale model MM5 in which the validations have been made with the data of TRMM and NCEP/AVN analysis.

A spectral-structural bag-of-features scene classifier for very high spatial resolution remote sensing imagery

NASA Astrophysics Data System (ADS)

Zhao, Bei; Zhong, Yanfei; Zhang, Liangpei

2016-06-01

results show that the whole image as the scope of the pooling operator performs better than the scope generated by SP. In addition, SSBFC codes and pools the spectral and structural features separately to avoid mutual interruption between the spectral and structural features. The coding vectors of spectral and structural features are then concatenated into a final coding vector. Finally, SSBFC classifies the final coding vector by support vector machine (SVM) with a histogram intersection kernel (HIK). Compared with the latest scene classification methods, the experimental results with three VHSR datasets demonstrate that the proposed SSBFC performs better than the other classification methods for VHSR image scenes.

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

A neighboring structure reconstructed matching algorithm based on LARK features

NASA Astrophysics Data System (ADS)

Xue, Taobei; Han, Jing; Zhang, Yi; Bai, Lianfa

2015-11-01

Aimed at the low contrast ratio and high noise of infrared images, and the randomness and ambient occlusion of its objects, this paper presents a neighboring structure reconstructed matching (NSRM) algorithm based on LARK features. The neighboring structure relationships of local window are considered based on a non-negative linear reconstruction method to build a neighboring structure relationship matrix. Then the LARK feature matrix and the NSRM matrix are processed separately to get two different similarity images. By fusing and analyzing the two similarity images, those infrared objects are detected and marked by the non-maximum suppression. The NSRM approach is extended to detect infrared objects with incompact structure. High performance is demonstrated on infrared body set, indicating a lower false detecting rate than conventional methods in complex natural scenes.

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

Biobased extreme pressure additives: Structure-property considerations

USDA-ARS?s Scientific Manuscript database

Extreme pressure additives are widely used in lubricant formulations for engine oils, hydraulic fluids, gear oils, metalworking fluids, and many others. Extreme pressure additives contain selected elements such as sulfur, phosphorus, and halogens in their structures. These elements, under extreme tr...

Seeing Deep Structure from the Interactions of Surface Features

ERIC Educational Resources Information Center

Chi, Michelene T. H.; VanLehn, Kurt A.

2012-01-01

Transfer is typically thought of as requiring individuals to "see" what is the same in the deep structure between a new target problem and a previously encountered source problem, even though the surface features may be dissimilar. We propose that experts can "see" the deep structure by considering the first-order interactions…

3D additive manufactured 316L components microstructural features and changes induced by working life cycles

NASA Astrophysics Data System (ADS)

Pace, M. L.; Guarnaccio, A.; Dolce, P.; Mollica, D.; Parisi, G. P.; Lettino, A.; Medici, L.; Summa, V.; Ciancio, R.; Santagata, A.

2017-10-01

The ability of processing through laser beams different kinds of metallic powders for direct production of 3D components with complex geometries has been gaining an impressive and growing attention for specific industrial applications. The process which can be distinguished as Selective Laser Sintering or Selective Laser Melting is even considered, more generally, as Additive Manufacturing where layer by layer material is built by the interaction between a laser beam and a powder bed. The rapid heating of the powder due to the laser beam energy transfer process followed by a rapid cooling rate induces within the manufactured material a cellular structure with fine sub-grains, which are in the range of few hundreds of micrometers. These metastable structures, which are smaller than the grain size in conventionally manufactured 316L stainless steel components, can undertake towards a recrystallization process due to either heat or mechanical treatments. For instance, when sub-grain boundaries of the cells are enriched with Mo and higher concentration of dislocation, dynamical processes occur generating local residual stresses. In these circumstances the segregation of Mo in cell boundaries is out of thermodynamic equilibrium conditions so that microstructures and phases are metastable. In the range of 1100-1400 °C heat treatments a complete dissolution of Mo in the Fe matrix with a gradual disappearance of sub-microns cell is observed feeding the growth of larger austenitic sub-grains formation. It follows a higher degree of Mo dissolution in the material matrix and a decrease of dislocation's concentration (Saeidi et al., 2015) [1]. In the work here presented we point out which are the microstructural features of stainless steel 316L components realized by Additive Manufacturing. Furthermore, the occurrence of a microstructural evolution is presented after experiencing to fatigue of 80000 cycles some door joints obtained by this technique. A decrease of dislocation

Imposed, ordered dust structures and other plasma features in a strongly magnetized plasma

NASA Astrophysics Data System (ADS)

Thomas, Edward; Leblanc, Spencer; Lynch, Brian; Konopka, Uwe; Merlino, Robert; Rosenberg, Marlene

2015-11-01

The Magnetized Dusty Plasma Experiment (MDPX) device has been in operation for just over one year. In that time, the MDPX device has been operating using a uniform magnetic field configuration up to 3.0 Tesla and has successfully produced plasmas and dusty plasmas at high magnetic fields. In these experimental studies, we have made observations of a new type of imposed, ordered structure in a dusty plasma at magnetic fields above 1 T. These dusty plasma structures are shown to scale inversely with neutral pressure and are shown to reflect the spatial structure of a wire mesh placed in the plasma. Additionally, recent measurements have been made that give insights into the effective potential that establishes the ordered structures in the plasma. In this presentation, we report on details of the imposed, ordered dusty plasma structure as well as filamentary features that also appear in the plasma and modify the confinement of the dusty plasma. This work is supported with funding from the NSF and Department of Energy.

Feature Grouping and Selection Over an Undirected Graph.

PubMed

Yang, Sen; Yuan, Lei; Lai, Ying-Cheng; Shen, Xiaotong; Wonka, Peter; Ye, Jieping

2012-01-01

High-dimensional regression/classification continues to be an important and challenging problem, especially when features are highly correlated. Feature selection, combined with additional structure information on the features has been considered to be promising in promoting regression/classification performance. Graph-guided fused lasso (GFlasso) has recently been proposed to facilitate feature selection and graph structure exploitation, when features exhibit certain graph structures. However, the formulation in GFlasso relies on pairwise sample correlations to perform feature grouping, which could introduce additional estimation bias. In this paper, we propose three new feature grouping and selection methods to resolve this issue. The first method employs a convex function to penalize the pairwise l ∞ norm of connected regression/classification coefficients, achieving simultaneous feature grouping and selection. The second method improves the first one by utilizing a non-convex function to reduce the estimation bias. The third one is the extension of the second method using a truncated l 1 regularization to further reduce the estimation bias. The proposed methods combine feature grouping and feature selection to enhance estimation accuracy. We employ the alternating direction method of multipliers (ADMM) and difference of convex functions (DC) programming to solve the proposed formulations. Our experimental results on synthetic data and two real datasets demonstrate the effectiveness of the proposed methods.

Chinese wine classification system based on micrograph using combination of shape and structure features

NASA Astrophysics Data System (ADS)

Wan, Yi

2011-06-01

Chinese wines can be classification or graded by the micrographs. Micrographs of Chinese wines show floccules, stick and granule of variant shape and size. Different wines have variant microstructure and micrographs, we study the classification of Chinese wines based on the micrographs. Shape and structure of wines' particles in microstructure is the most important feature for recognition and classification of wines. So we introduce a feature extraction method which can describe the structure and region shape of micrograph efficiently. First, the micrographs are enhanced using total variation denoising, and segmented using a modified Otsu's method based on the Rayleigh Distribution. Then features are extracted using proposed method in the paper based on area, perimeter and traditional shape feature. Eight kinds total 26 features are selected. Finally, Chinese wine classification system based on micrograph using combination of shape and structure features and BP neural network have been presented. We compare the recognition results for different choices of features (traditional shape features or proposed features). The experimental results show that the better classification rate have been achieved using the combinational features proposed in this paper.

Inkjet Printing of Functional and Structural Materials: Fluid Property Requirements, Feature Stability, and Resolution

NASA Astrophysics Data System (ADS)

Derby, Brian

2010-08-01

Inkjet printing is viewed as a versatile manufacturing tool for applications in materials fabrication in addition to its traditional role in graphics output and marking. The unifying feature in all these applications is the dispensing and precise positioning of very small volumes of fluid (1-100 picoliters) on a substrate before transformation to a solid. The application of inkjet printing to the fabrication of structures for structural or functional materials applications requires an understanding as to how the physical processes that operate during inkjet printing interact with the properties of the fluid precursors used. Here we review the current state of understanding of the mechanisms of drop formation and how this defines the fluid properties that are required for a given liquid to be printable. The interactions between individual drops and the substrate as well as between adjacent drops are important in defining the resolution and accuracy of printed objects. Pattern resolution is limited by the extent to which a liquid drop spreads on a substrate and how spreading changes with the overlap of adjacent drops to form continuous features. There are clearly defined upper and lower bounds to the width of a printed continuous line, which can be defined in terms of materials and process variables. Finer-resolution features can be achieved through appropriate patterning and structuring of the substrate prior to printing, which is essential if polymeric semiconducting devices are to be fabricated. Low advancing and receding contact angles promote printed line stability but are also more prone to solute segregation or “coffee staining” on drying.

Mechanical features of the shuttle rotating service structure

NASA Technical Reports Server (NTRS)

Crump, J. M.

1985-01-01

With the development of the space shuttle launching facilities, it became mandatory to develop a shuttle rotating service structure to provide for the insertion and/or removal of payloads at the launch pads. The rotating service structure is a welded tubular steel space frame 189 feet high, 65 feet wide, and weighing 2100 tons. At the pivot column the structure is supported on a 30 inch diameter hemispherical bearing. At the opposite terminus the structure is supported on two truck assemblies each having eight 36 inch diameter double flanged wheels. The following features of the rotating service structure are discussed: (1) thermal expansion and contraction; (2) hurricane tie downs; (3) payload changeout room; (4) payload ground handling mechanism; (5) payload and orbiter access platforms; and (6) orbiter cargo bay access.

Structural MRI-based detection of Alzheimer's disease using feature ranking and classification error.

PubMed

Beheshti, Iman; Demirel, Hasan; Farokhian, Farnaz; Yang, Chunlan; Matsuda, Hiroshi

2016-12-01

This paper presents an automatic computer-aided diagnosis (CAD) system based on feature ranking for detection of Alzheimer's disease (AD) using structural magnetic resonance imaging (sMRI) data. The proposed CAD system is composed of four systematic stages. First, global and local differences in the gray matter (GM) of AD patients compared to the GM of healthy controls (HCs) are analyzed using a voxel-based morphometry technique. The aim is to identify significant local differences in the volume of GM as volumes of interests (VOIs). Second, the voxel intensity values of the VOIs are extracted as raw features. Third, the raw features are ranked using a seven-feature ranking method, namely, statistical dependency (SD), mutual information (MI), information gain (IG), Pearson's correlation coefficient (PCC), t-test score (TS), Fisher's criterion (FC), and the Gini index (GI). The features with higher scores are more discriminative. To determine the number of top features, the estimated classification error based on training set made up of the AD and HC groups is calculated, with the vector size that minimized this error selected as the top discriminative feature. Fourth, the classification is performed using a support vector machine (SVM). In addition, a data fusion approach among feature ranking methods is introduced to improve the classification performance. The proposed method is evaluated using a data-set from ADNI (130 AD and 130 HC) with 10-fold cross-validation. The classification accuracy of the proposed automatic system for the diagnosis of AD is up to 92.48% using the sMRI data. An automatic CAD system for the classification of AD based on feature-ranking method and classification errors is proposed. In this regard, seven-feature ranking methods (i.e., SD, MI, IG, PCC, TS, FC, and GI) are evaluated. The optimal size of top discriminative features is determined by the classification error estimation in the training phase. The experimental results indicate that

46 CFR 72.01-25 - Additional structural requirements.

Code of Federal Regulations, 2010 CFR

2010-10-01

... CONSTRUCTION AND ARRANGEMENT Hull Structure § 72.01-25 Additional structural requirements. (a) Vessels required.... The construction of the bulkheads shall be to the satisfaction of the Commandant. (2) Steps and... deck, such bulkhead or deck shall be made structurally watertight without the use of wood, cement, or...

Structured functional additive regression in reproducing kernel Hilbert spaces.

PubMed

Zhu, Hongxiao; Yao, Fang; Zhang, Hao Helen

2014-06-01

Functional additive models (FAMs) provide a flexible yet simple framework for regressions involving functional predictors. The utilization of data-driven basis in an additive rather than linear structure naturally extends the classical functional linear model. However, the critical issue of selecting nonlinear additive components has been less studied. In this work, we propose a new regularization framework for the structure estimation in the context of Reproducing Kernel Hilbert Spaces. The proposed approach takes advantage of the functional principal components which greatly facilitates the implementation and the theoretical analysis. The selection and estimation are achieved by penalized least squares using a penalty which encourages the sparse structure of the additive components. Theoretical properties such as the rate of convergence are investigated. The empirical performance is demonstrated through simulation studies and a real data application.

Effects of anodizing parameters and heat treatment on nanotopographical features, bioactivity, and cell culture response of additively manufactured porous titanium.

PubMed

Amin Yavari, S; Chai, Y C; Böttger, A J; Wauthle, R; Schrooten, J; Weinans, H; Zadpoor, A A

2015-06-01

Anodizing could be used for bio-functionalization of the surfaces of titanium alloys. In this study, we use anodizing for creating nanotubes on the surface of porous titanium alloy bone substitutes manufactured using selective laser melting. Different sets of anodizing parameters (voltage: 10 or 20V anodizing time: 30min to 3h) are used for anodizing porous titanium structures that were later heat treated at 500°C. The nanotopographical features are examined using electron microscopy while the bioactivity of anodized surfaces is measured using immersion tests in the simulated body fluid (SBF). Moreover, the effects of anodizing and heat treatment on the performance of one representative anodized porous titanium structures are evaluated using in vitro cell culture assays using human periosteum-derived cells (hPDCs). It has been shown that while anodizing with different anodizing parameters results in very different nanotopographical features, i.e. nanotubes in the range of 20 to 55nm, anodized surfaces have limited apatite-forming ability regardless of the applied anodizing parameters. The results of in vitro cell culture show that both anodizing, and thus generation of regular nanotopographical feature, and heat treatment improve the cell culture response of porous titanium. In particular, cell proliferation measured using metabolic activity and DNA content was improved for anodized and heat treated as well as for anodized but not heat-treated specimens. Heat treatment additionally improved the cell attachment of porous titanium surfaces and upregulated expression of osteogenic markers. Anodized but not heat-treated specimens showed some limited signs of upregulated expression of osteogenic markers. In conclusion, while varying the anodizing parameters creates different nanotube structure, it does not improve apatite-forming ability of porous titanium. However, both anodizing and heat treatment at 500°C improve the cell culture response of porous titanium

An integrated simulator of structure and anisotropic flow in gas diffusion layers with hydrophobic additives

NASA Astrophysics Data System (ADS)

Burganos, Vasilis N.; Skouras, Eugene D.; Kalarakis, Alexandros N.

2017-10-01

The lattice-Boltzmann (LB) method is used in this work to reproduce the controlled addition of binder and hydrophobicity-promoting agents, like polytetrafluoroethylene (PTFE), into gas diffusion layers (GDLs) and to predict flow permeabilities in the through- and in-plane directions. The present simulator manages to reproduce spreading of binder and hydrophobic additives, sequentially, into the neat fibrous layer using a two-phase flow model. Gas flow simulation is achieved by the same code, sidestepping the need for a post-processing flow code and avoiding the usual input/output and data interface problems that arise in other techniques. Compression effects on flow anisotropy of the impregnated GDL are also studied. The permeability predictions for different compression levels and for different binder or PTFE loadings are found to compare well with experimental data for commercial GDL products and with computational fluid dynamics (CFD) predictions. Alternatively, the PTFE-impregnated structure is reproduced from Scanning Electron Microscopy (SEM) images using an independent, purely geometrical approach. A comparison of the two approaches is made regarding their adequacy to reproduce correctly the main structural features of the GDL and to predict anisotropic flow permeabilities at different volume fractions of binder and hydrophobic additives.

An Eye-Tracking Study of Multiple Feature Value Category Structure Learning: The Role of Unique Features

PubMed Central

Liu, Zhiya; Song, Xiaohong; Seger, Carol A.

2015-01-01

We examined whether the degree to which a feature is uniquely characteristic of a category can affect categorization above and beyond the typicality of the feature. We developed a multiple feature value category structure with different dimensions within which feature uniqueness and typicality could be manipulated independently. Using eye tracking, we found that the highest attentional weighting (operationalized as number of fixations, mean fixation time, and the first fixation of the trial) was given to a dimension that included a feature that was both unique and highly typical of the category. Dimensions that included features that were highly typical but not unique, or were unique but not highly typical, received less attention. A dimension with neither a unique nor a highly typical feature received least attention. On the basis of these results we hypothesized that subjects categorized via a rule learning procedure in which they performed an ordered evaluation of dimensions, beginning with unique and strongly typical dimensions, and in which earlier dimensions received higher weighting in the decision. This hypothesis accounted for performance on transfer stimuli better than simple implementations of two other common theories of category learning, exemplar models and prototype models, in which all dimensions were evaluated in parallel and received equal weighting. PMID:26274332

An Eye-Tracking Study of Multiple Feature Value Category Structure Learning: The Role of Unique Features.

PubMed

Liu, Zhiya; Song, Xiaohong; Seger, Carol A

2015-01-01

We examined whether the degree to which a feature is uniquely characteristic of a category can affect categorization above and beyond the typicality of the feature. We developed a multiple feature value category structure with different dimensions within which feature uniqueness and typicality could be manipulated independently. Using eye tracking, we found that the highest attentional weighting (operationalized as number of fixations, mean fixation time, and the first fixation of the trial) was given to a dimension that included a feature that was both unique and highly typical of the category. Dimensions that included features that were highly typical but not unique, or were unique but not highly typical, received less attention. A dimension with neither a unique nor a highly typical feature received least attention. On the basis of these results we hypothesized that subjects categorized via a rule learning procedure in which they performed an ordered evaluation of dimensions, beginning with unique and strongly typical dimensions, and in which earlier dimensions received higher weighting in the decision. This hypothesis accounted for performance on transfer stimuli better than simple implementations of two other common theories of category learning, exemplar models and prototype models, in which all dimensions were evaluated in parallel and received equal weighting.

Longitudinal Validation of General and Specific Structural Features of Personality Pathology

PubMed Central

Wright, Aidan G.C.; Hopwood, Christopher J.; Skodol, Andrew E.; Morey, Leslie C.

2016-01-01

Theorists have long argued that personality disorder (PD) is best understood in terms of general impairments shared across the disorders as well as more specific instantiations of pathology. A model based on this theoretical structure was proposed as part of the DSM-5 revision process. However, only recently has this structure been subjected to formal quantitative evaluation, with little in the way of validation efforts via external correlates or prospective longitudinal prediction. We used the Collaborative Longitudinal Study of Personality Disorders dataset to: (1) estimate structural models that parse general from specific variance in personality disorder features, (2) examine patterns of growth in general and specific features over the course of 10 years, and (3) establish concurrent and dynamic longitudinal associations in PD features and a host of external validators including basic personality traits and psychosocial functioning scales. We found that general PD exhibited much lower absolute stability and was most strongly related to broad markers of psychosocial functioning, concurrently and longitudinally, whereas specific features had much higher mean stability and exhibited more circumscribed associations with functioning. However, both general and specific factors showed recognizable associations with normative and pathological traits. These results can inform efforts to refine the conceptualization and diagnosis of personality pathology. PMID:27819472

Structured functional additive regression in reproducing kernel Hilbert spaces

PubMed Central

Zhu, Hongxiao; Yao, Fang; Zhang, Hao Helen

2013-01-01

Summary Functional additive models (FAMs) provide a flexible yet simple framework for regressions involving functional predictors. The utilization of data-driven basis in an additive rather than linear structure naturally extends the classical functional linear model. However, the critical issue of selecting nonlinear additive components has been less studied. In this work, we propose a new regularization framework for the structure estimation in the context of Reproducing Kernel Hilbert Spaces. The proposed approach takes advantage of the functional principal components which greatly facilitates the implementation and the theoretical analysis. The selection and estimation are achieved by penalized least squares using a penalty which encourages the sparse structure of the additive components. Theoretical properties such as the rate of convergence are investigated. The empirical performance is demonstrated through simulation studies and a real data application. PMID:25013362

Targeted Structural Optimization with Additive Manufacturing of Metals

NASA Technical Reports Server (NTRS)

Burt, Adam; Hull, Patrick

2015-01-01

The recent advances in additive manufacturing (AM) of metals have now improved the state-of-the-art such that traditionally non-producible parts can be readily produced in a cost-effective way. Because of these advances in manufacturing technology, structural optimization techniques are well positioned to supplement and advance this new technology. The goal of this project is to develop a structural design, analysis, and optimization framework combined with AM to significantly light-weight the interior of metallic structures while maintaining the selected structural properties of the original solid. This is a new state-of-the-art capability to significantly reduce mass, while maintaining the structural integrity of the original design, something that can only be done with AM. In addition, this framework will couple the design, analysis, and fabrication process, meaning that what has been designed directly represents the produced part, thus closing the loop on the design cycle and removing human iteration between design and fabrication. This fundamental concept has applications from light-weighting launch vehicle components to in situ resource fabrication.

Influence of culture medium growth variables on Ganoderma lucidum exopolysaccharides structural features.

PubMed

Fraga, Irene; Coutinho, João; Bezerra, Rui M; Dias, Albino A; Marques, Guilhermina; Nunes, Fernando M

2014-10-13

In this work the effect of carbon and nitrogen levels and initial pH of the wheat extract culture medium of submerged culture of Ganoderma lucidum on the amount, purity and structural features of exopolysaccharides (EPS) were studied. A low peptone level (1.65 g L(-1)) favored mycelium biomass, EPS purity, but a higher supply of peptone (4.80 g L(-1)) is needed for maximum EPS production. The carbohydrate composition of the EPS and structural features also changed significantly according to the different growing conditions, being observed significant differences in the (1 → 3)/(1 → 4)-Glcp ratio and also on the branching degree of EPS. As the biological activities of EPS are highly dependent on the polysaccharide structural features, this variability can have implications on the EPS biological activities, but can also be used advantageously to produce tailor made polysaccharides with specific applications. Copyright © 2014 Elsevier Ltd. All rights reserved.

Additive Mixing and Conformal Coating of Noniridescent Structural Colors with Robust Mechanical Properties Fabricated by Atomization Deposition.

PubMed

Li, Qingsong; Zhang, Yafeng; Shi, Lei; Qiu, Huihui; Zhang, Suming; Qi, Ning; Hu, Jianchen; Yuan, Wei; Zhang, Xiaohua; Zhang, Ke-Qin

2018-04-24

Artificial structural colors based on short-range-ordered amorphous photonic structures (APSs) have attracted great scientific and industrial interest in recent years. However, the previously reported methods of self-assembling colloidal nanoparticles lack fine control of the APS coating and fixation on substrates and poorly realize three-dimensional (3D) conformal coatings for objects with irregular or highly curved surfaces. In this paper, atomization deposition of silica colloidal nanoparticles with poly(vinyl alcohol) as the additive is proposed to solve the above problems. By finely controlling the thicknesses of APS coatings, additive mixing of noniridescent structural colors is easily realized. Based on the intrinsic omnidirectional feature of atomization, a one-step 3D homogeneous conformal coating is also readily realized on various irregular or highly curved surfaces, including papers, resins, metal plates, ceramics, and flexible silk fabrics. The vivid coatings on silk fabrics by atomization deposition possess robust mechanical properties, which are confirmed by rubbing and laundering tests, showing great potential in developing an environmentally friendly coloring technique in the textile industry.

GFP-like proteins as ubiquitous metazoan superfamily: evolution of functional features and structural complexity.

PubMed

Shagin, Dmitry A; Barsova, Ekaterina V; Yanushevich, Yurii G; Fradkov, Arkady F; Lukyanov, Konstantin A; Labas, Yulii A; Semenova, Tatiana N; Ugalde, Juan A; Meyers, Ann; Nunez, Jose M; Widder, Edith A; Lukyanov, Sergey A; Matz, Mikhail V

2004-05-01

Homologs of the green fluorescent protein (GFP), including the recently described GFP-like domains of certain extracellular matrix proteins in Bilaterian organisms, are remarkably similar at the protein structure level, yet they often perform totally unrelated functions, thereby warranting recognition as a superfamily. Here we describe diverse GFP-like proteins from previously undersampled and completely new sources, including hydromedusae and planktonic Copepoda. In hydromedusae, yellow and nonfluorescent purple proteins were found in addition to greens. Notably, the new yellow protein seems to follow exactly the same structural solution to achieving the yellow color of fluorescence as YFP, an engineered yellow-emitting mutant variant of GFP. The addition of these new sequences made it possible to resolve deep-level phylogenetic relationships within the superfamily. Fluorescence (most likely green) must have already existed in the common ancestor of Cnidaria and Bilateria, and therefore GFP-like proteins may be responsible for fluorescence and/or coloration in virtually any animal. At least 15 color diversification events can be inferred following the maximum parsimony principle in Cnidaria. Origination of red fluorescence and nonfluorescent purple-blue colors on several independent occasions provides a remarkable example of convergent evolution of complex features at the molecular level.

The Wavelet Element Method. Part 2; Realization and Additional Features in 2D and 3D

NASA Technical Reports Server (NTRS)

Canuto, Claudio; Tabacco, Anita; Urban, Karsten

1998-01-01

The Wavelet Element Method (WEM) provides a construction of multiresolution systems and biorthogonal wavelets on fairly general domains. These are split into subdomains that are mapped to a single reference hypercube. Tensor products of scaling functions and wavelets defined on the unit interval are used on the reference domain. By introducing appropriate matching conditions across the interelement boundaries, a globally continuous biorthogonal wavelet basis on the general domain is obtained. This construction does not uniquely define the basis functions but rather leaves some freedom for fulfilling additional features. In this paper we detail the general construction principle of the WEM to the 1D, 2D and 3D cases. We address additional features such as symmetry, vanishing moments and minimal support of the wavelet functions in each particular dimension. The construction is illustrated by using biorthogonal spline wavelets on the interval.

Impact of the rate of the additive process of forming a heavy structure deforming in creep on the development of its technological stresses

NASA Astrophysics Data System (ADS)

Parshin, Dmitry A.

2018-05-01

The additive process of forming a semicircular arched structure by means of layer-by-layer addition of material to its inner surface is simulated. The impact of this process running mode on the development of the technological stresses fields in the structure being formed under the action of gravity under properties of the material creep and aging is examined. In the framework of the linear mechanics of accreted solids a mathematical model of the process under study is offered and numerical experiments are conducted. It is shown that the stress-strain state of the additively formed heavy objects decisively depends on their formation mode. Various practically important trends and features of this dependence are studied.

Friction Stir Additive Manufacturing: Route to High Structural Performance

NASA Astrophysics Data System (ADS)

Palanivel, S.; Sidhar, H.; Mishra, R. S.

2015-03-01

Aerospace and automotive industries provide the next big opportunities for additive manufacturing. Currently, the additive industry is confronted with four major challenges that have been identified in this article. These challenges need to be addressed for the additive technologies to march into new frontiers and create additional markets. Specific potential success in the transportation sectors is dependent on the ability to manufacture complicated structures with high performance. Most of the techniques used for metal-based additive manufacturing are fusion based because of their ability to fulfill the computer-aided design to component vision. Although these techniques aid in fabrication of complex shapes, achieving high structural performance is a key problem due to the liquid-solid phase transformation. In this article, friction stir additive manufacturing (FSAM) is shown as a potential solid-state process for attaining high-performance lightweight alloys for simpler geometrical applications. To illustrate FSAM as a high-performance route, manufactured builds of Mg-4Y-3Nd and AA5083 are shown as examples. In the Mg-based alloy, an average hardness of 120 HV was achieved in the built structure and was significantly higher than that of the base material (97 HV). Similarly for the Al-based alloy, compared with the base hardness of 88 HV, the average built hardness was 104 HV. A potential application of FSAM is illustrated by taking an example of a simple stiffener assembly.

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.

Grain Structure Control of Additively Manufactured Metallic Materials

PubMed Central

Faierson, Eric J.

2017-01-01

Grain structure control is challenging for metal additive manufacturing (AM). Grain structure optimization requires the control of grain morphology with grain size refinement, which can improve the mechanical properties of additive manufactured components. This work summarizes methods to promote fine equiaxed grains in both the additive manufacturing process and subsequent heat treatment. Influences of temperature gradient, solidification velocity and alloy composition on grain morphology are discussed. Equiaxed solidification is greatly promoted by introducing a high density of heterogeneous nucleation sites via powder rate control in the direct energy deposition (DED) technique or powder surface treatment for powder-bed techniques. Grain growth/coarsening during post-processing heat treatment can be restricted by presence of nano-scale oxide particles formed in-situ during AM. Grain refinement of martensitic steels can also be achieved by cyclic austenitizing in post-processing heat treatment. Evidently, new alloy powder design is another sustainable method enhancing the capability of AM for high-performance components with desirable microstructures.

Structural and Organisational Features of Sensorimotor Intelligence among Retarded Infants and Toddlers.

ERIC Educational Resources Information Center

Dunst, C. J.; And Others

1981-01-01

The structural features of sensorimotor intelligence were assessed among three groups of retarded infants and toddlers. Hierarchical cluster analysis (HCA) was performed on two measures of relationship (stage congruence and intercorrelations). The potential utility of HCA for studying Piaget's "structure d'ensemble" stage criteria is…

Fabrication of small-scale structures with non-planar features

DOEpatents

Burckel, David B.; Ten Eyck, Gregory A.

2015-11-19

The fabrication of small-scale structures is disclosed. A unit-cell of a small-scale structure with non-planar features is fabricated by forming a membrane on a suitable material. A pattern is formed in the membrane and a portion of the substrate underneath the membrane is removed to form a cavity. Resonators are then directionally deposited on the wall or sides of the cavity. The cavity may be rotated during deposition to form closed-loop resonators. The resonators may be non-planar. The unit-cells can be formed in a layer that includes an array of unit-cells.

One-step volumetric additive manufacturing of complex polymer structures

DOE PAGES

Shusteff, Maxim; Browar, Allison E. M.; Kelly, Brett E.; ...

2017-12-01

Two limitations of additive manufacturing methods that arise from layer-based fabrication are slow speed and geometric constraints (which include poor surface quality). Both limitations are overcome in the work reported here, introducing a new volumetric additive fabrication paradigm that produces photopolymer structures with complex non-periodic 3D geometries on a timescale of seconds. We implement this approach using holographic patterning of light fields, demonstrate the fabrication of a variety of structures, and study the properties of the light patterns and photosensitive resins required for this fabrication approach. The results indicate that lowabsorbing resins containing ~0.1% photoinitiator, illuminated at modest powers (~10-100more » mW) may be successfully used to build full structures in ~1-10 s.« less

One-step volumetric additive manufacturing of complex polymer structures

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

Shusteff, Maxim; Browar, Allison E. M.; Kelly, Brett E.

Two limitations of additive manufacturing methods that arise from layer-based fabrication are slow speed and geometric constraints (which include poor surface quality). Both limitations are overcome in the work reported here, introducing a new volumetric additive fabrication paradigm that produces photopolymer structures with complex non-periodic 3D geometries on a timescale of seconds. We implement this approach using holographic patterning of light fields, demonstrate the fabrication of a variety of structures, and study the properties of the light patterns and photosensitive resins required for this fabrication approach. The results indicate that lowabsorbing resins containing ~0.1% photoinitiator, illuminated at modest powers (~10-100more » mW) may be successfully used to build full structures in ~1-10 s.« less

One-step volumetric additive manufacturing of complex polymer structures

PubMed Central

Shusteff, Maxim; Browar, Allison E. M.; Kelly, Brett E.; Henriksson, Johannes; Weisgraber, Todd H.; Panas, Robert M.; Fang, Nicholas X.; Spadaccini, Christopher M.

2017-01-01

Two limitations of additive manufacturing methods that arise from layer-based fabrication are slow speed and geometric constraints (which include poor surface quality). Both limitations are overcome in the work reported here, introducing a new volumetric additive fabrication paradigm that produces photopolymer structures with complex nonperiodic three-dimensional geometries on a time scale of seconds. We implement this approach using holographic patterning of light fields, demonstrate the fabrication of a variety of structures, and study the properties of the light patterns and photosensitive resins required for this fabrication approach. The results indicate that low-absorbing resins containing ~0.1% photoinitiator, illuminated at modest powers (~10 to 100 mW), may be successfully used to build full structures in ~1 to 10 s. PMID:29230437

One-step volumetric additive manufacturing of complex polymer structures.

PubMed

Shusteff, Maxim; Browar, Allison E M; Kelly, Brett E; Henriksson, Johannes; Weisgraber, Todd H; Panas, Robert M; Fang, Nicholas X; Spadaccini, Christopher M

2017-12-01

Two limitations of additive manufacturing methods that arise from layer-based fabrication are slow speed and geometric constraints (which include poor surface quality). Both limitations are overcome in the work reported here, introducing a new volumetric additive fabrication paradigm that produces photopolymer structures with complex nonperiodic three-dimensional geometries on a time scale of seconds. We implement this approach using holographic patterning of light fields, demonstrate the fabrication of a variety of structures, and study the properties of the light patterns and photosensitive resins required for this fabrication approach. The results indicate that low-absorbing resins containing ~0.1% photoinitiator, illuminated at modest powers (~10 to 100 mW), may be successfully used to build full structures in ~1 to 10 s.

Evaluation of physical structural features on influencing enzymatic hydrolysis efficiency of micronized wood

Treesearch

Jinxue Jiang; Jinwu Wang; Xiao Zhang; Michael Wolcott

2016-01-01

Enzymatic hydrolysis of lignocellulosic biomass is highly dependent on the changes in structural features after pretreatment. Mechanical milling pretreatment is an effective approach to alter the physical structure of biomass and thus improve enzymatic hydrolysis. This study examined the influence of structural characteristics on the enzymatic hydrolysis of micronized...

The role of emotion in musical improvisation: an analysis of structural features.

PubMed

McPherson, Malinda J; Lopez-Gonzalez, Monica; Rankin, Summer K; Limb, Charles J

2014-01-01

One of the primary functions of music is to convey emotion, yet how music accomplishes this task remains unclear. For example, simple correlations between mode (major vs. minor) and emotion (happy vs. sad) do not adequately explain the enormous range, subtlety or complexity of musically induced emotions. In this study, we examined the structural features of unconstrained musical improvisations generated by jazz pianists in response to emotional cues. We hypothesized that musicians would not utilize any universal rules to convey emotions, but would instead combine heterogeneous musical elements together in order to depict positive and negative emotions. Our findings demonstrate a lack of simple correspondence between emotions and musical features of spontaneous musical improvisation. While improvisations in response to positive emotional cues were more likely to be in major keys, have faster tempos, faster key press velocities and more staccato notes when compared to negative improvisations, there was a wide distribution for each emotion with components that directly violated these primary associations. The finding that musicians often combine disparate features together in order to convey emotion during improvisation suggests that structural diversity may be an essential feature of the ability of music to express a wide range of emotion.

Friction-induced nano-structural evolution of graphene as a lubrication additive

NASA Astrophysics Data System (ADS)

Zhao, Jun; Mao, Junyuan; Li, Yingru; He, Yongyong; Luo, Jianbin

2018-03-01

Graphene has attracted enormous attention in the field of lubrication based on its excellent physical and chemical properties. Although many studies have obtained thermally or chemically- exfoliated graphene and investigated their wide and important application, few studies have reported their physical nano-structural evolution under friction. In this study, we investigated the lubrication properties of graphene additives with different layer numbers and interlayer spacing by exfoliating. The additives with a higher degrees of exfoliation changed to ordering under friction, and had better lubrication properties, while that with a lower degrees exhibited obvious structural defects and high friction. Therefore, the original degrees of exfoliation plays a key role in the structural evolution of graphene and superior lubrication can be achieved through the physical nano-structure changing to ordering, even graphitization. Furthermore, the ordered tribofilm on the frictional interfaces was parallel to the sliding direction, meaning the highly exfoliated graphene indeed reaching slippage between its layers, which wasn't experimentally discovered in previous studies. This work provides a new understanding of the relationship between friction-induced nano-structural evolution and lubrication properties of graphene as a lubrication additive, and has great potential for the structural design of graphene as a lubrication additive.

A Feature and Algorithm Selection Method for Improving the Prediction of Protein Structural Class.

PubMed

Ni, Qianwu; Chen, Lei

2017-01-01

Correct prediction of protein structural class is beneficial to investigation on protein functions, regulations and interactions. In recent years, several computational methods have been proposed in this regard. However, based on various features, it is still a great challenge to select proper classification algorithm and extract essential features to participate in classification. In this study, a feature and algorithm selection method was presented for improving the accuracy of protein structural class prediction. The amino acid compositions and physiochemical features were adopted to represent features and thirty-eight machine learning algorithms collected in Weka were employed. All features were first analyzed by a feature selection method, minimum redundancy maximum relevance (mRMR), producing a feature list. Then, several feature sets were constructed by adding features in the list one by one. For each feature set, thirtyeight algorithms were executed on a dataset, in which proteins were represented by features in the set. The predicted classes yielded by these algorithms and true class of each protein were collected to construct a dataset, which were analyzed by mRMR method, yielding an algorithm list. From the algorithm list, the algorithm was taken one by one to build an ensemble prediction model. Finally, we selected the ensemble prediction model with the best performance as the optimal ensemble prediction model. Experimental results indicate that the constructed model is much superior to models using single algorithm and other models that only adopt feature selection procedure or algorithm selection procedure. The feature selection procedure or algorithm selection procedure are really helpful for building an ensemble prediction model that can yield a better performance. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Therapeutic approaches against common structural features of toxic oligomers shared by multiple amyloidogenic proteins.

PubMed

Guerrero-Muñoz, Marcos J; Castillo-Carranza, Diana L; Kayed, Rakez

2014-04-15

Impaired proteostasis is one of the main features of all amyloid diseases, which are associated with the formation of insoluble aggregates from amyloidogenic proteins. The aggregation process can be caused by overproduction or poor clearance of these proteins. However, numerous reports suggest that amyloid oligomers are the most toxic species, rather than insoluble fibrillar material, in Alzheimer's, Parkinson's, and Prion diseases, among others. Although the exact protein that aggregates varies between amyloid disorders, they all share common structural features that can be used as therapeutic targets. In this review, we focus on therapeutic approaches against shared features of toxic oligomeric structures and future directions. Copyright © 2014 Elsevier Inc. All rights reserved.

Structural and compositional features of high-rise buildings: experimental design in Yekaterinburg

NASA Astrophysics Data System (ADS)

Yankovskaya, Yulia; Lobanov, Yuriy; Temnov, Vladimir

2018-03-01

The study looks at the specifics of high-rise development in Yekaterinburg. High-rise buildings are considered in the context of their historical development, structural features, compositional and imaginative design techniques. Experience of Yekaterinburg architects in experimental design is considered and analyzed. Main issues and prospects of high-rise development within the Yekaterinburg structure are studied. The most interesting and significant conceptual approaches to the structural and compositional arrangement of high-rise buildings are discussed.

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

PubMed

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

2011-09-01

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

Structural Mapping of Paterae and Mountains on Io: Implications for Crustal Stresses and Feature Evolution

NASA Astrophysics Data System (ADS)

Ahern, A.; Radebaugh, J.; Christiansen, E. H.; Harris, R. A.

2015-12-01

Paterae and mountains are some of the most distinguishing and well-distributed surface features on Io, and they reveal the role of tectonism in Io's crust. Paterae, similar to calderas, are volcano-tectonic collapse features that often have straight margins. Io's mountains are some of the highest in the solar system and contain linear features that reveal crustal stresses. Paterae and mountains are often found adjacent to one another, suggesting possible genetic relationships. We have produced twelve detailed regional structural maps from high-resolution images of relevant features, where available, as well as a global structural map from the Io Global Color Mosaic. The regional structural maps identify features such as fractures, lineations, folds, faults, and mass wasting scarps, which are then interpreted in the context of global and regional stress regimes. A total of 1048 structural lineations have been identified globally. Preliminary analyses of major thrust and normal fault orientations are dominantly 90° offset from each other, suggesting the maximum contractional stresses leading to large mountain formation are not a direct result of tidal extension. Rather, these results corroborate the model of volcanic loading of the crust and global shortening, leading to thrust faulting and uplift of coherent crustal blocks. Several paterae, such as Hi'iaka and Tohil, are found adjacent to mountains inside extensional basins where lava has migrated up normal faults to erupt onto patera floors. Over time, mass wasting and volcanic resurfacing can change mountains from young, steep, and angular peaks to older, gentler, and more rounded hills. Mass wasting scarps make up 53% of all features identified. The structural maps highlight the significant effect of mass wasting on Io's surface, the evolution of mountains through time, the role of tectonics in the formation of paterae, and the formation of mountains through global contraction due to volcanism.

The Role of Emotion in Musical Improvisation: An Analysis of Structural Features

PubMed Central

McPherson, Malinda J.; Lopez-Gonzalez, Monica; Rankin, Summer K.; Limb, Charles J.

2014-01-01

One of the primary functions of music is to convey emotion, yet how music accomplishes this task remains unclear. For example, simple correlations between mode (major vs. minor) and emotion (happy vs. sad) do not adequately explain the enormous range, subtlety or complexity of musically induced emotions. In this study, we examined the structural features of unconstrained musical improvisations generated by jazz pianists in response to emotional cues. We hypothesized that musicians would not utilize any universal rules to convey emotions, but would instead combine heterogeneous musical elements together in order to depict positive and negative emotions. Our findings demonstrate a lack of simple correspondence between emotions and musical features of spontaneous musical improvisation. While improvisations in response to positive emotional cues were more likely to be in major keys, have faster tempos, faster key press velocities and more staccato notes when compared to negative improvisations, there was a wide distribution for each emotion with components that directly violated these primary associations. The finding that musicians often combine disparate features together in order to convey emotion during improvisation suggests that structural diversity may be an essential feature of the ability of music to express a wide range of emotion. PMID:25144200

Multiclass Classification for the Differential Diagnosis on the ADHD Subtypes Using Recursive Feature Elimination and Hierarchical Extreme Learning Machine: Structural MRI Study

PubMed Central

Qureshi, Muhammad Naveed Iqbal; Min, Beomjun; Jo, Hang Joon; Lee, Boreom

2016-01-01

The classification of neuroimaging data for the diagnosis of certain brain diseases is one of the main research goals of the neuroscience and clinical communities. In this study, we performed multiclass classification using a hierarchical extreme learning machine (H-ELM) classifier. We compared the performance of this classifier with that of a support vector machine (SVM) and basic extreme learning machine (ELM) for cortical MRI data from attention deficit/hyperactivity disorder (ADHD) patients. We used 159 structural MRI images of children from the publicly available ADHD-200 MRI dataset. The data consisted of three types, namely, typically developing (TDC), ADHD-inattentive (ADHD-I), and ADHD-combined (ADHD-C). We carried out feature selection by using standard SVM-based recursive feature elimination (RFE-SVM) that enabled us to achieve good classification accuracy (60.78%). In this study, we found the RFE-SVM feature selection approach in combination with H-ELM to effectively enable the acquisition of high multiclass classification accuracy rates for structural neuroimaging data. In addition, we found that the most important features for classification were the surface area of the superior frontal lobe, and the cortical thickness, volume, and mean surface area of the whole cortex. PMID:27500640

Multiclass Classification for the Differential Diagnosis on the ADHD Subtypes Using Recursive Feature Elimination and Hierarchical Extreme Learning Machine: Structural MRI Study.

PubMed

Qureshi, Muhammad Naveed Iqbal; Min, Beomjun; Jo, Hang Joon; Lee, Boreom

2016-01-01

The classification of neuroimaging data for the diagnosis of certain brain diseases is one of the main research goals of the neuroscience and clinical communities. In this study, we performed multiclass classification using a hierarchical extreme learning machine (H-ELM) classifier. We compared the performance of this classifier with that of a support vector machine (SVM) and basic extreme learning machine (ELM) for cortical MRI data from attention deficit/hyperactivity disorder (ADHD) patients. We used 159 structural MRI images of children from the publicly available ADHD-200 MRI dataset. The data consisted of three types, namely, typically developing (TDC), ADHD-inattentive (ADHD-I), and ADHD-combined (ADHD-C). We carried out feature selection by using standard SVM-based recursive feature elimination (RFE-SVM) that enabled us to achieve good classification accuracy (60.78%). In this study, we found the RFE-SVM feature selection approach in combination with H-ELM to effectively enable the acquisition of high multiclass classification accuracy rates for structural neuroimaging data. In addition, we found that the most important features for classification were the surface area of the superior frontal lobe, and the cortical thickness, volume, and mean surface area of the whole cortex.

Structure and origin of Australian ring and dome features with reference to the search for asteroid impact events

NASA Astrophysics Data System (ADS)

Glikson, Andrew

2018-01-01

Ring, dome and crater features on the Australian continent and shelf include (A) 38 structures of confirmed or probable asteroid and meteorite impact origin and (B) numerous buried and exposed ring, dome and crater features of undefined origin. A large number of the latter include structural and geophysical elements consistent with impact structures, pending test by field investigations and/or drilling. This paper documents and briefly describes 43 ring and dome features with the aim of appraising their similarities and differences from those of impact structures. Discrimination between impact structures and igneous plugs, volcanic caldera and salt domes require field work and/or drilling. Where crater-like morphological patterns intersect pre-existing linear structural features and contain central morphological highs and unique thrust and fault patterns an impact connection needs to tested in the field. Hints of potential buried impact structures may be furnished by single or multi-ring TMI patterns, circular TMI quiet zones, corresponding gravity patterns, low velocity and non-reflective seismic zones.

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.

Critical Features of Fragment Libraries for Protein Structure Prediction

PubMed Central

dos Santos, Karina Baptista

2017-01-01

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

Critical Features of Fragment Libraries for Protein Structure Prediction.

PubMed

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

2017-01-01

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

Fabrication method for small-scale structures with non-planar features

DOEpatents

Burckel, David Bruce; Ten Eyck, Gregory A.

2016-09-20

The fabrication of small-scale structures is disclosed. A unit-cell of a small-scale structure with non-planar features is fabricated by forming a membrane on a suitable material. A pattern is formed in the membrane and a portion of the substrate underneath the membrane is removed to form a cavity. Resonators are then directionally deposited on the wall or sides of the cavity. The cavity may be rotated during deposition to form closed-loop resonators. The resonators may be non-planar. The unit-cells can be formed in a layer that includes an array of unit-cells.

Process Features in Writing: Internal Structure and Incremental Value over Product Features. Research Report. ETS RR-15-27

ERIC Educational Resources Information Center

Zhang, Mo; Deane, Paul

2015-01-01

In educational measurement contexts, essays have been evaluated and formative feedback has been given based on the end product. In this study, we used a large sample collected from middle school students in the United States to investigate the factor structure of the writing process features gathered from keystroke logs and the association of that…

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

Automated sub-cortical brain structure segmentation combining spatial and deep convolutional features.

PubMed

Kushibar, Kaisar; Valverde, Sergi; González-Villà, Sandra; Bernal, Jose; Cabezas, Mariano; Oliver, Arnau; Lladó, Xavier

2018-06-15

Sub-cortical brain structure segmentation in Magnetic Resonance Images (MRI) has attracted the interest of the research community for a long time as morphological changes in these structures are related to different neurodegenerative disorders. However, manual segmentation of these structures can be tedious and prone to variability, highlighting the need for robust automated segmentation methods. In this paper, we present a novel convolutional neural network based approach for accurate segmentation of the sub-cortical brain structures that combines both convolutional and prior spatial features for improving the segmentation accuracy. In order to increase the accuracy of the automated segmentation, we propose to train the network using a restricted sample selection to force the network to learn the most difficult parts of the structures. We evaluate the accuracy of the proposed method on the public MICCAI 2012 challenge and IBSR 18 datasets, comparing it with different traditional and deep learning state-of-the-art methods. On the MICCAI 2012 dataset, our method shows an excellent performance comparable to the best participant strategy on the challenge, while performing significantly better than state-of-the-art techniques such as FreeSurfer and FIRST. On the IBSR 18 dataset, our method also exhibits a significant increase in the performance with respect to not only FreeSurfer and FIRST, but also comparable or better results than other recent deep learning approaches. Moreover, our experiments show that both the addition of the spatial priors and the restricted sampling strategy have a significant effect on the accuracy of the proposed method. In order to encourage the reproducibility and the use of the proposed method, a public version of our approach is available to download for the neuroimaging community. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

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

Automatic feature learning using multichannel ROI based on deep structured algorithms for computerized lung cancer diagnosis.

PubMed

Sun, Wenqing; Zheng, Bin; Qian, Wei

2017-10-01

This study aimed to analyze the ability of extracting automatically generated features using deep structured algorithms in lung nodule CT image diagnosis, and compare its performance with traditional computer aided diagnosis (CADx) systems using hand-crafted features. All of the 1018 cases were acquired from Lung Image Database Consortium (LIDC) public lung cancer database. The nodules were segmented according to four radiologists' markings, and 13,668 samples were generated by rotating every slice of nodule images. Three multichannel ROI based deep structured algorithms were designed and implemented in this study: convolutional neural network (CNN), deep belief network (DBN), and stacked denoising autoencoder (SDAE). For the comparison purpose, we also implemented a CADx system using hand-crafted features including density features, texture features and morphological features. The performance of every scheme was evaluated by using a 10-fold cross-validation method and an assessment index of the area under the receiver operating characteristic curve (AUC). The observed highest area under the curve (AUC) was 0.899±0.018 achieved by CNN, which was significantly higher than traditional CADx with the AUC=0.848±0.026. The results from DBN was also slightly higher than CADx, while SDAE was slightly lower. By visualizing the automatic generated features, we found some meaningful detectors like curvy stroke detectors from deep structured schemes. The study results showed the deep structured algorithms with automatically generated features can achieve desirable performance in lung nodule diagnosis. With well-tuned parameters and large enough dataset, the deep learning algorithms can have better performance than current popular CADx. We believe the deep learning algorithms with similar data preprocessing procedure can be used in other medical image analysis areas as well. Copyright © 2017. Published by Elsevier Ltd.

What are the structural features that drive partitioning of proteins in aqueous two-phase systems?

PubMed

Wu, Zhonghua; Hu, Gang; Wang, Kui; Zaslavsky, Boris Yu; Kurgan, Lukasz; Uversky, Vladimir N

2017-01-01

Protein partitioning in aqueous two-phase systems (ATPSs) represents a convenient, inexpensive, and easy to scale-up protein separation technique. Since partition behavior of a protein dramatically depends on an ATPS composition, it would be highly beneficial to have reliable means for (even qualitative) prediction of partitioning of a target protein under different conditions. Our aim was to understand which structural features of proteins contribute to partitioning of a query protein in a given ATPS. We undertook a systematic empirical analysis of relations between 57 numerical structural descriptors derived from the corresponding amino acid sequences and crystal structures of 10 well-characterized proteins and the partition behavior of these proteins in 29 different ATPSs. This analysis revealed that just a few structural characteristics of proteins can accurately determine behavior of these proteins in a given ATPS. However, partition behavior of proteins in different ATPSs relies on different structural features. In other words, we could not find a unique set of protein structural features derived from their crystal structures that could be used for the description of the protein partition behavior of all proteins in all ATPSs analyzed in this study. We likely need to gain better insight into relationships between protein-solvent interactions and protein structure peculiarities, in particular given limitations of the used here crystal structures, to be able to construct a model that accurately predicts protein partition behavior across all ATPSs. Copyright © 2016 Elsevier B.V. All rights reserved.

Catalogue of the morphological features in the Spitzer Survey of Stellar Structure in Galaxies (S4G)

NASA Astrophysics Data System (ADS)

Herrera-Endoqui, M.; Díaz-García, S.; Laurikainen, E.; Salo, H.

2015-10-01

Context. A catalogue of the features for the complete Spitzer Survey of Stellar Structure in Galaxies (S4G), including 2352 nearby galaxies, is presented. The measurements are made using 3.6 μm images, largely tracing the old stellar population; at this wavelength the effects of dust are also minimal. The measured features are the sizes, ellipticities, and orientations of bars, rings, ringlenses, and lenses. Measured in a similar manner are also barlenses (lens-like structures embedded in the bars), which are not lenses in the usual sense, being rather the more face-on counterparts of the boxy/peanut structures in the edge-on view. In addition, pitch angles of spiral arm segments are measured for those galaxies where they can be reliably traced. More than one pitch angle may appear for a single galaxy. All measurements are made in a human-supervised manner so that attention is paid to each galaxy. Aims: We create a catalogue of morphological features in the complete S4G. Methods: We used isophotal analysis, unsharp masking, and fitting ellipses to measured structures. Results: We find that the sizes of the inner rings and lenses normalized to barlength correlate with the galaxy mass: the normalized sizes increase toward the less massive galaxies; it has been suggested that this is related to the larger dark matter content in the bar region in these systems. Bars in the low mass galaxies are also less concentrated, likely to be connected to the mass cut-off in the appearance of the nuclear rings and lenses. We also show observational evidence that barlenses indeed form part of the bar, and that a large fraction of the inner lenses in the non-barred galaxies could be former barlenses in which the thin outer bar component has dissolved. Full Tables 2 and 3 are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/582/A86

Analysis of Structural Features Contributing to Weak Affinities of Ubiquitin/Protein Interactions.

PubMed

Cohen, Ariel; Rosenthal, Eran; Shifman, Julia M

2017-11-10

Ubiquitin is a small protein that enables one of the most common post-translational modifications, where the whole ubiquitin molecule is attached to various target proteins, forming mono- or polyubiquitin conjugations. As a prototypical multispecific protein, ubiquitin interacts non-covalently with a variety of proteins in the cell, including ubiquitin-modifying enzymes and ubiquitin receptors that recognize signals from ubiquitin-conjugated substrates. To enable recognition of multiple targets and to support fast dissociation from the ubiquitin modifying enzymes, ubiquitin/protein interactions are characterized with low affinities, frequently in the higher μM and lower mM range. To determine how structure encodes low binding affinity of ubiquitin/protein complexes, we analyzed structures of more than a hundred such complexes compiled in the Ubiquitin Structural Relational Database. We calculated various structure-based features of ubiquitin/protein binding interfaces and compared them to the same features of general protein-protein interactions (PPIs) with various functions and generally higher affinities. Our analysis shows that ubiquitin/protein binding interfaces on average do not differ in size and shape complementarity from interfaces of higher-affinity PPIs. However, they contain fewer favorable hydrogen bonds and more unfavorable hydrophobic/charge interactions. We further analyzed how binding interfaces change upon affinity maturation of ubiquitin toward its target proteins. We demonstrate that while different features are improved in different experiments, the majority of the evolved complexes exhibit better shape complementarity and hydrogen bond pattern compared to wild-type complexes. Our analysis helps to understand how low-affinity PPIs have evolved and how they could be converted into high-affinity PPIs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Structural features of LC8-induced self-association of swallow.

PubMed

Kidane, Ariam I; Song, Yujuan; Nyarko, Afua; Hall, Justin; Hare, Michael; Löhr, Frank; Barbar, Elisar

2013-09-03

Cell functions depend on the collective activity of protein networks within which a few proteins, called hubs, participate in a large number of interactions. Dynein light chain LC8, first discovered as a subunit of the motor protein dynein, is considered to have a role broader than that of dynein, and its participation in diverse systems fits the description of a hub. Among its partners is Swallow with which LC8 is essential for proper localization of bicoid mRNA at the anterior cortex of Drosophila oocytes. Why LC8 is essential in this process is not clear, but emerging evidence suggests that LC8 functions by promoting self-association and/or structural organization of its diverse binding partners. This work addresses the energetics and structural features of LC8-induced Swallow self-association distant from LC8 binding. Mutational design based on a hypothetical helical wheel, intermonomer nuclear Overhauser effects assigned to residues expected at interface positions, and circular dichroism spectral characteristics indicate that the LC8-promoted dimer of Swallow is a coiled coil. Secondary chemical shifts and (15)N backbone relaxation identify the boundaries and distinguishing structural features of the coiled coil. Thermodynamic analysis of Swallow polypeptides designed to decouple self-association from LC8 binding reveals that the higher binding affinity of the engineered bivalent Swallow is of purely entropic origin and that the linker separating the coiled coil from the LC8 binding site remains disordered. We speculate that the LC8-promoted coiled coil is critical for bicoid mRNA localization because it favors structural organization of Swallow, which except for the central LC8-promoted coiled coil is primarily disordered.

Structural Features of LC8-Induced Self Association of Swallow†

PubMed Central

Kidane, Ariam I.; Song, Yujuan; Nyarko, Afua; Hall, Justin; Hare, Michael; Löhr, Frank; Barbar, Elisar

2013-01-01

Cell function depends on the collective activity of protein networks within which a few proteins, called hubs, participate in a large number of interactions. Dynein light chain LC8, first discovered as a subunit of the motor protein dynein, is considered to have a role broader than dynein and its participation in diverse systems fits the description of a hub. Among its partners is Swallow with which LC8 is essential for proper localization of bicoid mRNA at the anterior cortex of Drosophila oocytes. Why LC8 is essential in this process is not clear, but emerging evidence suggests that LC8 functions by promoting self-association and/or structural organization of its diverse binding partners. This work addresses the mechanistic and structural features of LC8-induced Swallow self-association distant from LC8 binding. Mutational design based on a hypothetical helical wheel, inter-monomer NOEs assigned to residues expected at interface positions and circular dichroism spectral characteristics indicate that the LC8-promoted dimer of Swallow is a coiled-coil. Secondary chemical shifts and 15N backbone relaxation identify the boundaries and distinguishing structural features of the coiled-coil. Thermodynamic analysis of Swallow polypeptides designed to decouple self-association from LC8 binding reveals that the higher binding affinity of the engineered bivalent Swallow is of purely entropic origin and that the linker separating the coiled-coil from the LC8 binding site remains disordered. We speculate that the LC8-promoted coiled-coil is critical for bicoid mRNA localization because it could induce structural organization of Swallow, which except for the central LC8-promoted coiled-coil is primarily disordered. PMID:23914803

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

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.

Local structure-based image decomposition for feature extraction with applications to face recognition.

PubMed

Qian, Jianjun; Yang, Jian; Xu, Yong

2013-09-01

This paper presents a robust but simple image feature extraction method, called image decomposition based on local structure (IDLS). It is assumed that in the local window of an image, the macro-pixel (patch) of the central pixel, and those of its neighbors, are locally linear. IDLS captures the local structural information by describing the relationship between the central macro-pixel and its neighbors. This relationship is represented with the linear representation coefficients determined using ridge regression. One image is actually decomposed into a series of sub-images (also called structure images) according to a local structure feature vector. All the structure images, after being down-sampled for dimensionality reduction, are concatenated into one super-vector. Fisher linear discriminant analysis is then used to provide a low-dimensional, compact, and discriminative representation for each super-vector. The proposed method is applied to face recognition and examined using our real-world face image database, NUST-RWFR, and five popular, publicly available, benchmark face image databases (AR, Extended Yale B, PIE, FERET, and LFW). Experimental results show the performance advantages of IDLS over state-of-the-art algorithms.

Development of Additive Construction Technologies for Application to Development of Lunar/Martian Surface Structures Using In-Situ Materials

NASA Technical Reports Server (NTRS)

Werkheiser, Niki J.; Fiske, Michael R.; Edmunson, Jennifer E.; Khoshnevis, Berokh

2015-01-01

For long-duration missions on other planetary bodies, the use of in situ materials will become increasingly critical. As human presence on these bodies expands, so must the breadth of the structures required to accommodate them including habitats, laboratories, berms, radiation shielding for natural radiation and surface reactors, garages, solar storm shelters, greenhouses, etc. Planetary surface structure manufacturing and assembly technologies that incorporate in situ resources provide options for autonomous, affordable, pre-positioned environments with radiation shielding features and protection from micrometeorites, exhaust plume debris, and other hazards. The ability to use in-situ materials to construct these structures will provide a benefit in the reduction of up-mass that would otherwise make long-term Moon or Mars structures cost prohibitive. The ability to fabricate structures in situ brings with it the ability to repair these structures, which allows for the self-sufficiency and sustainability necessary for long-duration habitation. Previously, under the auspices of the MSFC In-Situ Fabrication and Repair (ISFR) project and more recently, under the jointly-managed MSFC/KSC Additive Construction with Mobile Emplacement (ACME) project, the MSFC Surface Structures Group has been developing materials and construction technologies to support future planetary habitats with in-situ resources. One such additive construction technology is known as Contour Crafting. This paper presents the results to date of these efforts, including development of novel nozzle concepts for advanced layer deposition using this process. Conceived initially for rapid development of cementitious structures on Earth, it also lends itself exceptionally well to the automated fabrication of planetary surface structures using minimally processed regolith as aggregate, and binders developed from in situ materials as well. This process has been used successfully in the fabrication of

Structural features, kinetics and SAR study of radical scavenging and antioxidant activities of phenolic and anilinic compounds

PubMed Central

2013-01-01

Background Phenolic compounds are widely distributed in plant kingdom and constitute one of the most important classes of natural and synthetic antioxidants. In the present study fifty one natural and synthetic structurally variant phenolic, enolic and anilinic compounds were examined as antioxidants and radical scavengers against DPPH, hydroxyl and peroxyl radicals. The structural diversity of the used phenolic compounds includes monophenols with substituents frequently present in natural phenols e.g. alkyl, alkoxy, ester and carboxyl groups, besides many other electron donating and withdrawing groups, in addition to polyphenols with 1–3 hydroxyl groups and aminophenols. Some common groups e.g. alkyl, carboxyl, amino and second OH groups were incorporated in ortho, meta and para positions. Results SAR study indicates that the most important structural feature of phenolic compounds required to possess good antiradical and antioxidant activities is the presence of a second hydroxyl or an amino group in o- or p-position because of their strong electron donating effect in these positions and the formation of a stable quinone-like products upon two hydrogen-atom transfer process; otherwise, the presence of a number of alkoxy (in o or p-position) and /or alkyl groups (in o, m or p-position) should be present to stabilize the resulted phenoxyl radical and reach good activity. Anilines showed also similar structural feature requirements as phenols to achieve good activities, except o-diamines which gave low activity because of the high energy of the resulted 1,2-dimine product upon the 2H-transfer process. Enols with ene-1,2-diol structure undergo the same process and give good activity. Good correlations were obtained between DPPH inhibition and inhibition of both OH and peroxyl radicals. In addition, good correlations were obtained between DPPH inhibition and antioxidant activities in sunflower oil and liver homogenate systems. Conclusions In conclusion, the

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.

Structuring in Cement Systems with Introduction of Graphene Nano-Additives

NASA Astrophysics Data System (ADS)

Yanturina, R. A.; Trofimov, B. Ya; Ahmedjanov, R. M.

2017-11-01

At present, one of the most promising areas in the field of concrete research is the study of the effect of nano-additives for the production of highly effective concretes. Many authors have already obtained primary results which testify to the very effective role of nanoadditives based on carbon in modifying concrete. In this paper, the influence of a nano-additive of graphene on the phase composition and microstructure of the cement stone was studied. It has been found that, when a nano-additive of graphene is introduced, low-basic calcium hydrosilicates are mainly formed. This leads to an increase in the compressive strength of concrete. The results of the study of the microstructure of cement stone with nano-additive graphene showed that the high compressive strength of concrete modified with nano-additive graphene is explained by the cement stone dense structure. Thus, it was found that the nanoadditive of graphene contributes to the formation of a dense structure of cement stone, composed mainly of low-basic calcium hydrosilicates, and due to this, the physical and mechanical characteristics of concrete and its resistance to frost and other forms of aggression.

Features of Inner Structure of Placer Gold of the North-Eastern Part Siberian Platform

NASA Astrophysics Data System (ADS)

Gerasimov, Boris; Zhuravlev, Anatolii; Ivanov, Alexey

2017-12-01

Mineral and raw material base of placer and ore gold is based on prognosis evaluation, which allows to define promising areas regarding gold-bearing deposit prospecting. But there are some difficulties in gold primary source predicting and prospecting at the North-east Siberian platform, because the studied area is overlapped by thick cover of the Cenozoic deposits, where traditional methods of gold deposit prospecting are ineffective. In this connection, detailed study of typomorphic features of placer gold is important, because it contains key genetic information, necessary for development of mineralogical criteria of prognosis evaluation of ore gold content. Authors studied mineralogical-geochemical features of placer gold of the Anabar placer area for 15 years, with a view to identify indicators of gold, typical for different formation types of primary sources. This article presents results of these works. In placer regions, where primary sources of gold are not identified, there is need to study typomorphic features of placer gold, because it contains important genetic information, necessary for the development of mineralogical criteria of prognosis evaluation of ore gold content. Inner structures of gold from the Anabar placer region are studied, as one of the diagnostic typomorphic criteria as described in prominent method, developed by N.V. Petrovskaya [1980]. Etching of gold was carried out using reagent: HCl + HNO3 + FeCl3 × 6H2O + CrO3 +thioureat + water. Identified inner structures wer studied in details by means of scanning electron microscope JEOL JSM-6480LV. Two types of gold are identified according to the features of inner structure of placer gold of the Anabar region. First type - medium-high karat fine, well processed gold with significantly changed inner structure. This gold is allochthonous, which was redeposited many times from ancient intermediate reservoirs to younger deposits. Second type - low-medium karat, poorly rounded gold with

Assessing Diversity of DNA Structure-Related Sequence Features in Prokaryotic Genomes

PubMed Central

Huang, Yongjie; Mrázek, Jan

2014-01-01

Prokaryotic genomes are diverse in terms of their nucleotide and oligonucleotide composition as well as presence of various sequence features that can affect physical properties of the DNA molecule. We present a survey of local sequence patterns which have a potential to promote non-canonical DNA conformations (i.e. different from standard B-DNA double helix) and interpret the results in terms of relationships with organisms' habitats, phylogenetic classifications, and other characteristics. Our present work differs from earlier similar surveys not only by investigating a wider range of sequence patterns in a large number of genomes but also by using a more realistic null model to assess significant deviations. Our results show that simple sequence repeats and Z-DNA-promoting patterns are generally suppressed in prokaryotic genomes, whereas palindromes and inverted repeats are over-represented. Representation of patterns that promote Z-DNA and intrinsic DNA curvature increases with increasing optimal growth temperature (OGT), and decreases with increasing oxygen requirement. Additionally, representations of close direct repeats, palindromes and inverted repeats exhibit clear negative trends with increasing OGT. The observed relationships with environmental characteristics, particularly OGT, suggest possible evolutionary scenarios of structural adaptation of DNA to particular environmental niches. PMID:24408877

The Use of Additive Manufacturing for Fabrication of Multi-Function Small Satellite Structures

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

Horais, Brian J; Love, Lonnie J; Dehoff, Ryan R

2013-01-01

The use of small satellites in constellations is limited only by the growing functionality of smallsats themselves. Additive manufacturing provides exciting new design opportunities for development of multifunction CubeSat structures that integrate such functions as propulsion and thermal control into the satellite structures themselves. Manufacturing of these complex multifunction structures is now possible in lightweight, high strength, materials such as titanium by using existing electron beam melting additive manufacturing processes. However, the use of today's additive manufacturing capabilities is often cost-prohibitive for small companies due to the large capital investments required. To alleviate this impediment the U.S. Department of Energymore » has established a Manufacturing Demonstration Facility (MDF) at their Oak Ridge National Laboratory (ORNL) in Tennessee that provides industry access to a broad range of energy-efficient additive manufacturing equipment for collaborative use by both small and large organizations. This paper presents a notional CubeSat multifunction design that integrates the propulsion system into a three-unit (3U) CubeSat structure. The full-scale structure has been designed and fabricated at the ORNL MDF. The use of additive manufacturing for spacecraft fabrication is opening up many new possibilities in design and fabrication capabilities for what had previously been impossible structures to fabricate.« less

Biomechanical and Structural Features of CS2 Fimbriae of Enterotoxigenic Escherichia coli

PubMed Central

Mortezaei, Narges; Singh, Bhupender; Zakrisson, Johan; Bullitt, Esther; Andersson, Magnus

2015-01-01

Enterotoxigenic Escherichia coli (ETEC) are a major cause of diarrhea worldwide, and infection of children in under-developed countries often leads to high mortality rates. Isolated ETEC expresses a plethora of colonization factors (fimbriae/pili), of which CFA/I and CFA/II, which are assembled via the alternate chaperone pathway (ACP), are among the most common. Fimbriae are filamentous structures whose shafts are primarily composed of helically arranged single pilin-protein subunits, with a unique biomechanical ability to unwind and rewind. A sustained ETEC infection, under adverse conditions of dynamic shear forces, is primarily attributed to this biomechanical feature of ETEC fimbriae. Recent understanding about the role of fimbriae as virulence factors points to an evolutionary adaptation of their structural and biomechanical features. In this work, we investigated the biophysical properties of CS2 fimbriae from the CFA/II group. Homology modeling of its major structural subunit, CotA, reveals structural clues related to the niche in which they are expressed. Using optical-tweezers force spectroscopy, we found that CS2 fimbriae unwind at a constant force of 10 pN and have a corner velocity (i.e., the velocity at which the force required for unwinding rises exponentially with increased speed) of 1300 nm/s. The biophysical properties of CS2 fimbriae assessed in this work classify them into a low-force unwinding group of fimbriae together with the CFA/I and CS20 fimbriae expressed by ETEC strains. The three fimbriae are expressed by ETEC, colonize in similar gut environments, and exhibit similar biophysical features, but differ in their biogenesis. Our observation suggests that the environment has a strong impact on the biophysical characteristics of fimbriae expressed by ETEC. PMID:26153701

Incidental and context-responsive activation of structure- and function-based action features during object identification

PubMed Central

Lee, Chia-lin; Middleton, Erica; Mirman, Daniel; Kalénine, Solène; Buxbaum, Laurel J.

2012-01-01

Previous studies suggest that action representations are activated during object processing, even when task-irrelevant. In addition, there is evidence that lexical-semantic context may affect such activation during object processing. Finally, prior work from our laboratory and others indicates that function-based (“use”) and structure-based (“move”) action subtypes may differ in their activation characteristics. Most studies assessing such effects, however, have required manual object-relevant motor responses, thereby plausibly influencing the activation of action representations. The present work utilizes eyetracking and a Visual World Paradigm task without object-relevant actions to assess the time course of activation of action representations, as well as their responsiveness to lexical-semantic context. In two experiments, participants heard a target word and selected its referent from an array of four objects. Gaze fixations on non-target objects signal activation of features shared between targets and non-targets. The experiments assessed activation of structure-based (Experiment 1) or function-based (Experiment 2) distractors, using neutral sentences (“S/he saw the …”) or sentences with a relevant action verb (Experiment 1: “S/he picked up the……”; Experiment 2: “S/he used the….”). We observed task-irrelevant activations of action information in both experiments. In neutral contexts, structure-based activation was relatively faster-rising but more transient than function-based activation. Additionally, action verb contexts reliably modified patterns of activation in both Experiments. These data provide fine-grained information about the dynamics of activation of function-based and structure-based actions in neutral and action-relevant contexts, in support of the “Two Action System” model of object and action processing (e.g., Buxbaum & Kalénine, 2010). PMID:22390294

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.

Landscape Features Shape Genetic Structure in Threatened Northern Spotted Owls

USGS Publications Warehouse

Funk, W. Chris; Forsman, Eric D.; Mullins, Thomas D.; Haig, Susan M.

2008-01-01

Several recent studies have shown that landscape features can strongly affect spatial patterns of gene flow and genetic variation. Understanding landscape effects on genetic variation is important in conservation for defining management units and understanding movement patterns. The landscape may have little effect on gene flow, however, in highly mobile species such as birds. We tested for genetic breaks associated with landscape features in the northern spotted owl (Strix occidentalis caurina), a threatened subspecies associated with old forests in the U.S. Pacific Northwest and extreme southwestern Canada. We found little evidence for distinct genetic breaks in northern spotted owls using a large microsatellite dataset (352 individuals from across the subspecies' range genotyped at 10 loci). Nonetheless, dry low-elevation valleys and the Cascade and Olympic Mountains restrict gene flow, while the Oregon Coast Range facilitates it. The wide Columbia River is not a barrier to gene flow. In addition, inter-individual genetic distance and latitude were negatively related, likely reflecting northward colonization following Pleistocene glacial recession. Our study shows that landscape features may play an important role in shaping patterns of genetic variation in highly vagile taxa such as birds.

One-step synthesis and structural features of CdS/montmorillonite nanocomposites.

PubMed

Han, Zhaohui; Zhu, Huaiyong; Bulcock, Shaun R; Ringer, Simon P

2005-02-24

A novel synthesis method was introduced for the nanocomposites of cadmium sulfide and montmorillonite. This method features the combination of an ion exchange process and an in situ hydrothermal decomposition process of a complex precursor, which is simple in contrast to the conventional synthesis methods that comprise two separate steps for similar nanocomposite materials. Cadmium sulfide species in the composites exist in the forms of pillars and nanoparticles, the crystallized sulfide particles are in the hexagonal phase, and the sizes change when the amount of the complex for the synthesis is varied. Structural features of the nanocomposites are similar to those of the clay host but changed because of the introduction of the sulfide into the clay.

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.

Jackpot Structural Features: Rollover Effect and Goal-Gradient Effect in EGM Gambling.

PubMed

Li, En; Rockloff, Matthew J; Browne, Matthew; Donaldson, Phillip

2016-06-01

Relatively little research has been undertaken on the influence of jackpot structural features on electronic gaming machine (EGM) gambling behavior. This study considered two common features of EGM jackpots: progressive (i.e., the jackpot incrementally growing in value as players make additional bets), and deterministic (i.e., a guaranteed jackpot after a fixed number of bets, which is determined in advance and at random). Their joint influences on player betting behavior and the moderating role of jackpot size were investigated in a crossed-design experiment. Using real money, players gambled on a computer simulated EGM with real jackpot prizes of either $500 (i.e., small jackpot) or $25,000 (i.e., large jackpot). The results revealed three important findings. Firstly, players placed the largest bets (20.3 % higher than the average) on large jackpot EGMs that were represented to be deterministic and non-progressive. This finding was supportive of a hypothesized 'goal-gradient effect', whereby players might have felt subjectively close to an inevitable payoff for a high-value prize. Secondly, large jackpots that were non-deterministic and progressive also promoted high bet sizes (17.8 % higher than the average), resembling the 'rollover effect' demonstrated in lottery betting, whereby players might imagine that their large bets could be later recouped through a big win. Lastly, neither the hypothesized goal-gradient effect nor the rollover effect was evident among players betting on small jackpot machines. These findings suggest that certain high-value jackpot configurations may have intensifying effects on player behavior.

Design Optimization of Irregular Cellular Structure for Additive Manufacturing

NASA Astrophysics Data System (ADS)

Song, Guo-Hua; Jing, Shi-Kai; Zhao, Fang-Lei; Wang, Ye-Dong; Xing, Hao; Zhou, Jing-Tao

2017-09-01

Irregularcellular structurehas great potential to be considered in light-weight design field. However, the research on optimizing irregular cellular structures has not yet been reporteddue to the difficulties in their modeling technology. Based on the variable density topology optimization theory, an efficient method for optimizing the topology of irregular cellular structures fabricated through additive manufacturing processes is proposed. The proposed method utilizes tangent circles to automatically generate the main outline of irregular cellular structure. The topological layoutof each cellstructure is optimized using the relative density informationobtained from the proposed modified SIMP method. A mapping relationship between cell structure and relative densityelement is builtto determine the diameter of each cell structure. The results show that the irregular cellular structure can be optimized with the proposed method. The results of simulation and experimental test are similar for irregular cellular structure, which indicate that the maximum deformation value obtained using the modified Solid Isotropic Microstructures with Penalization (SIMP) approach is lower 5.4×10-5 mm than that using the SIMP approach under the same under the same external load. The proposed research provides the instruction to design the other irregular cellular structure.

Impedance-based structural health monitoring of additive manufactured structures with embedded piezoelectric wafers

NASA Astrophysics Data System (ADS)

Scheyer, Austin G.; Anton, Steven R.

2017-04-01

Embedding sensors within additive manufactured (AM) structures gives the ability to develop smart structures that are capable of monitoring the mechanical health of a system. AM provides an opportunity to embed sensors within a structure during the manufacturing process. One major limitation of AM technology is the ability to verify the geometric and material properties of fabricated structures. Over the past several years, the electromechanical impedance (EMI) method for structural health monitoring (SHM) has been proven to be an effective method for sensing damage in structurers. The EMI method utilizes the coupling between the electrical and mechanical properties of a piezoelectric transducer to detect a change in the dynamic response of a structure. A piezoelectric device, usually a lead zirconate titanate (PZT) ceramic wafer, is bonded to a structure and the electrical impedance is measured across as range of frequencies. A change in the electrical impedance is directly correlated to changes made to the mechanical condition of the structure. In this work, the EMI method is employed on piezoelectric transducers embedded inside AM parts to evaluate the feasibility of performing SHM on parts fabricated using additive manufacturing. The fused deposition modeling (FDM) method is used to print specimens for this feasibility study. The specimens are printed from polylactic acid (PLA) in the shape of a beam with an embedded monolithic piezoelectric ceramic disc. The specimen is mounted as a cantilever while impedance measurements are taken using an HP 4194A impedance analyzer. Both destructive and nondestructive damage is simulated in the specimens by adding an end mass and drilling a hole near the free end of the cantilever, respectively. The Root Mean Square Deviation (RMSD) method is utilized as a metric for quantifying damage to the system. In an effort to determine a threshold for RMSD, the values are calculated for the variation associated with taking multiple

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

Crystal structure of a lipoxygenase from Cyanothece sp. may reveal novel features for substrate acquisition[S

PubMed Central

Newie, Julia; Andreou, Alexandra; Neumann, Piotr; Einsle, Oliver; Feussner, Ivo; Ficner, Ralf

2016-01-01

In eukaryotes, oxidized PUFAs, so-called oxylipins, are vital signaling molecules. The first step in their biosynthesis may be catalyzed by a lipoxygenase (LOX), which forms hydroperoxides by introducing dioxygen into PUFAs. Here we characterized CspLOX1, a phylogenetically distant LOX family member from Cyanothece sp. PCC 8801 and determined its crystal structure. In addition to the classical two domains found in plant, animal, and coral LOXs, we identified an N-terminal helical extension, reminiscent of the long α-helical insertion in Pseudomonas aeruginosa LOX. In liposome flotation studies, this helical extension, rather than the β-barrel domain, was crucial for a membrane binding function. Additionally, CspLOX1 could oxygenate 1,2-diarachidonyl-sn-glycero-3-phosphocholine, suggesting that the enzyme may act directly on membranes and that fatty acids bind to the active site in a tail-first orientation. This binding mode is further supported by the fact that CspLOX1 catalyzed oxygenation at the n-10 position of both linoleic and arachidonic acid, resulting in 9R- and 11R-hydroperoxides, respectively. Together these results reveal unifying structural features of LOXs and their function. While the core of the active site is important for lipoxygenation and thus highly conserved, peripheral domains functioning in membrane and substrate binding are more variable. PMID:26667668

SU-E-QI-16: Reproducibility of Computed Tomography Quantitative Structural Features Using the FDA Thoracic Phantom Image Database

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

Budzevich, M; Grove, O; Balagurunathan, Y

Purpose: To assess the reproducibility of quantitative structural features using images from the computed tomography thoracic FDA phantom database under different scanning conditions. Methods: Development of quantitative image features to describe lesion shape and size, beyond conventional RECIST measures, is an evolving area of research in need of benchmarking standards. Gavrielides et al. (2010) scanned a FDA-developed thoracic phantom with nodules of various Hounsfield units (HU) values, shapes and sizes close to vascular structures using several scanners and varying scanning conditions/parameters; these images are in the public domain. We tested six structural features, namely, Convexity, Perimeter, Major Axis, Minor Axis,more » Extent Mean and Eccentricity, to characterize lung nodules. Convexity measures lesion irregularity referenced to a convex surface. Previously, we showed it to have prognostic value in lung adenocarcinoma. The above metrics and RECIST measures were evaluated on three spiculated (8mm/-300HU, 12mm/+30HU and 15mm/+30HU) and two non-spiculated (8mm/+100HU and 10mm/+100HU) nodules (from layout 2) imaged at three different mAs values: 25, 100 and 200 mAs; on a Phillips scanner (16-slice Mx8000-IDT; 3mm slice thickness). The nodules were segmented semi-automatically using a commercial software tool; the same HU range was used for all nodules. Results: Analysis showed convexity having the lowest maximum coefficient of variation (MCV): 1.1% and 0.6% for spiculated and non-spiculated nodules, respectively, much lower compared to RECIST Major and Minor axes whose MCV were 10.1% and 13.4% for spiculated, and 1.9% and 2.3% for non-spiculated nodules, respectively, across the various mAs. MCVs were consistently larger for speculated nodules. In general, the dependence of structural features on mAs (noise) was low. Conclusion: The FDA phantom CT database may be used for benchmarking of structural features for various scanners and scanning conditions

Additive-induced aggregate changes of two structurally similar dyes in aqueous solutions: A comparative photophysical study

NASA Astrophysics Data System (ADS)

Ghanadzadeh Gilani, A.; Poormohammadi-Ahandani, Z.; Kian, R.

2018-01-01

Absorption and emission spectral characteristics of the two structurally similar phenothiazine dyes, azure B and toluidine blue, in aqueous solutions of the two sets of molecular additives (ureas and monosaccharides) were studied as a function of the dye and additive concentrations. The absorption spectra of the dyes were also studied in pure tetramethylurea with an aprotic nature. The spectral data were analyzed using DECOM Program. The dimer structure of the interacting molecules in these dyes was discussed using the exciton model. The urea class of additives was found to act as water structure-breakers over the range of studied concentration. The carbohydrate additives were found to act as water structure-breakers at low concentrations. However, the water structure breaking process may be disfavored by the additive-additive interactions at higher concentrations. It can be concluded that at low additive concentrations, the main driving force for breaking the dye association is water-additive interaction, which disrupts the water hydrogen bonds induced by the additives. However, at the high additive concentrations, the different phenomena including additive-additive and additive-dye interactions can change the structure, strength, and aggregative properties of the dyes. Finally, the urea in water induces noticeably fluorescence quenching in emission spectra of both the dyes.

Additive-induced aggregate changes of two structurally similar dyes in aqueous solutions: A comparative photophysical study.

PubMed

Ghanadzadeh Gilani, A; Poormohammadi-Ahandani, Z; Kian, R

2018-01-15

Absorption and emission spectral characteristics of the two structurally similar phenothiazine dyes, azure B and toluidine blue, in aqueous solutions of the two sets of molecular additives (ureas and monosaccharides) were studied as a function of the dye and additive concentrations. The absorption spectra of the dyes were also studied in pure tetramethylurea with an aprotic nature. The spectral data were analyzed using DECOM Program. The dimer structure of the interacting molecules in these dyes was discussed using the exciton model. The urea class of additives was found to act as water structure-breakers over the range of studied concentration. The carbohydrate additives were found to act as water structure-breakers at low concentrations. However, the water structure breaking process may be disfavored by the additive-additive interactions at higher concentrations. It can be concluded that at low additive concentrations, the main driving force for breaking the dye association is water-additive interaction, which disrupts the water hydrogen bonds induced by the additives. However, at the high additive concentrations, the different phenomena including additive-additive and additive-dye interactions can change the structure, strength, and aggregative properties of the dyes. Finally, the urea in water induces noticeably fluorescence quenching in emission spectra of both the dyes. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantifying Wrinkle Features of Thin Membrane Structures

NASA Technical Reports Server (NTRS)

Jacobson, Mindy B.; Iwasa, Takashi; Naton, M. C.

2004-01-01

For future micro-systems utilizing membrane based structures, quantified predictions of wrinkling behavior in terms of amplitude, angle and wavelength are needed to optimize the efficiency and integrity of such structures, as well as their associated control systems. For numerical analyses performed in the past, limitations on the accuracy of membrane distortion simulations have often been related to the assumptions made. This work demonstrates that critical assumptions include: effects of gravity, supposed initial or boundary conditions, and the type of element used to model the membrane. In this work, a 0.2 m x 02 m membrane is treated as a structural material with non-negligible bending stiffness. Finite element modeling is used to simulate wrinkling behavior due to a constant applied in-plane shear load. Membrane thickness, gravity effects, and initial imperfections with respect to flatness were varied in numerous nonlinear analysis cases. Significant findings include notable variations in wrinkle modes for thickness in the range of 50 microns to 1000 microns, which also depend on the presence of an applied gravity field. However, it is revealed that relationships between overall strain energy density and thickness for cases with differing initial conditions are independent of assumed initial conditions. In addition, analysis results indicate that the relationship between wrinkle amplitude scale (W/t) and structural scale (L/t) is independent of the nonlinear relationship between thickness and stiffness.

Structural changes in gluten protein structure after addition of emulsifier. A Raman spectroscopy study

NASA Astrophysics Data System (ADS)

Ferrer, Evelina G.; Gómez, Analía V.; Añón, María C.; Puppo, María C.

2011-06-01

Food protein product, gluten protein, was chemically modified by varying levels of sodium stearoyl lactylate (SSL); and the extent of modifications (secondary and tertiary structures) of this protein was analyzed by using Raman spectroscopy. Analysis of the Amide I band showed an increase in its intensity mainly after the addition of the 0.25% of SSL to wheat flour to produced modified gluten protein, pointing the formation of a more ordered structure. Side chain vibrations also confirmed the observed changes.

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

Structural features of biomass in a hybrid MBBR reactor.

PubMed

Xiao, G Y; Ganczarczyk, J

2006-03-01

The structural features of biomass present in the hybrid MBBR (Moving Bed Biofilm Reactor) aeration tank were studied in two subsequent periods, which differed in hydraulic and substrate loads. The physical characteristics of attached-growth biomass, such as, biofilm thickness, density, porosity, inner and surface fractal dimensions, and those of suspended-growth biomass, such as, floc size distribution, density, porosity, inner and surface fractal dimensions, were investigated in each study period and then compared. The results indicated that biofilm always had a higher density, geometric porosity, and a larger boundary fractal dimension than flocs. Both types of biomass were found to exhibit at least two distinct Sierpinski fractal dimensions, indicating two major different pore space populations. With the increasing wastewater flow, both types of biomass were found to shift their structural properties to larger values, except porosity and surface roughness, which decreased. Floc density and biomass Sierpinski fractals were not affected much by the system loadings.

Comparative analyses of structural features and scaffold diversity for purchasable compound libraries.

PubMed

Shang, Jun; Sun, Huiyong; Liu, Hui; Chen, Fu; Tian, Sheng; Pan, Peichen; Li, Dan; Kong, Dexin; Hou, Tingjun

2017-04-21

Large purchasable screening libraries of small molecules afforded by commercial vendors are indispensable sources for virtual screening (VS). Selecting an optimal screening library for a specific VS campaign is quite important to improve the success rates and avoid wasting resources in later experimental phases. Analysis of the structural features and molecular diversity for different screening libraries can provide valuable information to the decision making process when selecting screening libraries for VS. In this study, the structural features and scaffold diversity of eleven purchasable screening libraries and Traditional Chinese Medicine Compound Database (TCMCD) were analyzed and compared. Their scaffold diversity represented by the Murcko frameworks and Level 1 scaffolds was characterized by the scaffold counts and cumulative scaffold frequency plots, and visualized by Tree Maps and SAR Maps. The analysis demonstrates that, based on the standardized subsets with similar molecular weight distributions, Chembridge, ChemicalBlock, Mucle, TCMCD and VitasM are more structurally diverse than the others. Compared with all purchasable screening libraries, TCMCD has the highest structural complexity indeed but more conservative molecular scaffolds. Moreover, we found that some representative scaffolds were important components of drug candidates against different drug targets, such as kinases and guanosine-binding protein coupled receptors, and therefore the molecules containing pharmacologically important scaffolds found in screening libraries might be potential inhibitors against the relevant targets. This study may provide valuable perspective on which purchasable compound libraries are better for you to screen. Graphical abstract Selecting diverse compound libraries with scaffold analyses.

Synthesis and characterization of high-surface-area millimeter-sized silica beads with hierarchical multi-modal pore structure by the addition of agar

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

Han, Yosep; Choi, Junhyun; Tong, Meiping, E-mail: tongmeiping@iee.pku.edu.cn

2014-04-01

Millimeter-sized spherical silica foams (SSFs) with hierarchical multi-modal pore structure featuring high specific surface area and ordered mesoporous frameworks were successfully prepared using aqueous agar addition, foaming and drop-in-oil processes. The pore-related properties of the prepared spherical silica (SSs) and SSFs were systematically characterized by field emission-scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM), small-angle X-ray diffraction (SAXRD), Hg intrusion porosimetry, and N{sub 2} adsorption–desorption isotherm measurements. Improvements in the BET surface area and total pore volume were observed at 504 m{sup 2} g{sup −1} and 5.45 cm{sup 3} g{sup −1}, respectively, after an agar addition and foaming process. Despitemore » the increase in the BET surface area, the mesopore wall thickness and the pore size of the mesopores generated from the block copolymer with agar addition were unchanged based on the SAXRD, TEM, and BJH methods. The SSFs prepared in the present study were confirmed to have improved BET surface area and micropore volume through the agar loading, and to exhibit interconnected 3-dimensional network macropore structure leading to the enhancement of total porosity and BET surface area via the foaming process. - Highlights: • Millimeter-sized spherical silica foams (SSFs) are successfully prepared. • SSFs exhibit high BET surface area and ordered hierarchical pore structure. • Agar addition improves BET surface area and micropore volume of SSFs. • Foaming process generates interconnected 3-D network macropore structure of SSFs.« less

[Morphometric features of the structure of the central nucleus of the amygdala in men and women].

PubMed

Antyukhov, A D

2015-01-01

To identify the interhemispheric asymmetry in the structure of the central nucleus of the amygdala in men and women. Morphometric features of the structure of neurons of the central nucleus amygdala complex were studied in histological sections of the brain of 6 men and 6 women (24 hemispheres), aged 19 to 55 years, with no lifetime diagnosis of mental or neurological disease. The value of the profile fields of neurons of the central nucleus amygdala complex in the left and right hemispheres of the brain were investigated. In women, the average value of neurons in the left hemisphere was somewhat greater than in the right hemisphere, while in men this value was greater in the right hemisphere. The interhemispheric morphometric differences were not significant regardless of gender. In addition, the quantity of relevant fields of neurons in the central nucleus of the amygdala in women was significantly larger than that of men in both hemispheres. The authors attempted to associate the results obtained in the study with emotional perception in men and women.

Feature engineering for MEDLINE citation categorization with MeSH.

PubMed

Jimeno Yepes, Antonio Jose; Plaza, Laura; Carrillo-de-Albornoz, Jorge; Mork, James G; Aronson, Alan R

2015-04-08

Research in biomedical text categorization has mostly used the bag-of-words representation. Other more sophisticated representations of text based on syntactic, semantic and argumentative properties have been less studied. In this paper, we evaluate the impact of different text representations of biomedical texts as features for reproducing the MeSH annotations of some of the most frequent MeSH headings. In addition to unigrams and bigrams, these features include noun phrases, citation meta-data, citation structure, and semantic annotation of the citations. Traditional features like unigrams and bigrams exhibit strong performance compared to other feature sets. Little or no improvement is obtained when using meta-data or citation structure. Noun phrases are too sparse and thus have lower performance compared to more traditional features. Conceptual annotation of the texts by MetaMap shows similar performance compared to unigrams, but adding concepts from the UMLS taxonomy does not improve the performance of using only mapped concepts. The combination of all the features performs largely better than any individual feature set considered. In addition, this combination improves the performance of a state-of-the-art MeSH indexer. Concerning the machine learning algorithms, we find that those that are more resilient to class imbalance largely obtain better performance. We conclude that even though traditional features such as unigrams and bigrams have strong performance compared to other features, it is possible to combine them to effectively improve the performance of the bag-of-words representation. We have also found that the combination of the learning algorithm and feature sets has an influence in the overall performance of the system. Moreover, using learning algorithms resilient to class imbalance largely improves performance. However, when using a large set of features, consideration needs to be taken with algorithms due to the risk of over-fitting. Specific

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.

Local Feature Selection for Data Classification.

PubMed

Armanfard, Narges; Reilly, James P; Komeili, Majid

2016-06-01

Typical feature selection methods choose an optimal global feature subset that is applied over all regions of the sample space. In contrast, in this paper we propose a novel localized feature selection (LFS) approach whereby each region of the sample space is associated with its own distinct optimized feature set, which may vary both in membership and size across the sample space. This allows the feature set to optimally adapt to local variations in the sample space. An associated method for measuring the similarities of a query datum to each of the respective classes is also proposed. The proposed method makes no assumptions about the underlying structure of the samples; hence the method is insensitive to the distribution of the data over the sample space. The method is efficiently formulated as a linear programming optimization problem. Furthermore, we demonstrate the method is robust against the over-fitting problem. Experimental results on eleven synthetic and real-world data sets demonstrate the viability of the formulation and the effectiveness of the proposed algorithm. In addition we show several examples where localized feature selection produces better results than a global feature selection method.

Large-scale oscillation of structure-related DNA sequence features in human chromosome 21

NASA Astrophysics Data System (ADS)

Li, Wentian; Miramontes, Pedro

2006-08-01

Human chromosome 21 is the only chromosome in the human genome that exhibits oscillation of the (G+C) content of a cycle length of hundreds kilobases (kb) ( 500kb near the right telomere). We aim at establishing the existence of a similar periodicity in structure-related sequence features in order to relate this (G+C)% oscillation to other biological phenomena. The following quantities are shown to oscillate with the same 500kb periodicity in human chromosome 21: binding energy calculated by two sets of dinucleotide-based thermodynamic parameters, AA/TT and AAA/TTT bi- and tri-nucleotide density, 5'-TA-3' dinucleotide density, and signal for 10- or 11-base periodicity of AA/TT or AAA/TTT. These intrinsic quantities are related to structural features of the double helix of DNA molecules, such as base-pair binding, untwisting or unwinding, stiffness, and a putative tendency for nucleosome formation.

Realistic Free-Spins Features Increase Preference for Slot Machines.

PubMed

Taylor, Lorance F; Macaskill, Anne C; Hunt, Maree J

2017-06-01

Despite increasing research into how the structural characteristics of slot machines influence gambling behaviour there have been no experimental investigations into the effect of free-spins bonus features-a structural characteristic that is commonly central to the design of slot machines. This series of three experiments investigated the free-spins feature using slot machine simulations to determine whether participants allocate more wagers to a machine with free spins, and, which components of free-spins features drive this preference. In each experiment, participants were exposed to two computer-simulated slot machines-one with a free-spins feature or similar bonus feature and one without. Participants then completed a testing phase where they could freely switch between the two machines. In Experiment 1, participants did not prefer the machine with a simple free-spins feature. In Experiment 2 the free-spins feature incorporated additional elements such as sounds, animations, and an increased win frequency; participants preferred to gamble on this machine. The Experiment 3 "bonus feature" machine resembled the free spins machine in Experiment 2 except spins were not free; participants showed a clear preference for this machine also. These findings indicate that (1) free-spins features have a major influence over machine choice and (2) the "freeness" of the free-spins bonus features is not an important driver of preference, contrary to self-report and interview research with gamblers.

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.

nRC: non-coding RNA Classifier based on structural features.

PubMed

Fiannaca, Antonino; La Rosa, Massimo; La Paglia, Laura; Rizzo, Riccardo; Urso, Alfonso

2017-01-01

Non-coding RNA (ncRNA) are small non-coding sequences involved in gene expression regulation of many biological processes and diseases. The recent discovery of a large set of different ncRNAs with biologically relevant roles has opened the way to develop methods able to discriminate between the different ncRNA classes. Moreover, the lack of knowledge about the complete mechanisms in regulative processes, together with the development of high-throughput technologies, has required the help of bioinformatics tools in addressing biologists and clinicians with a deeper comprehension of the functional roles of ncRNAs. In this work, we introduce a new ncRNA classification tool, nRC (non-coding RNA Classifier). Our approach is based on features extraction from the ncRNA secondary structure together with a supervised classification algorithm implementing a deep learning architecture based on convolutional neural networks. We tested our approach for the classification of 13 different ncRNA classes. We obtained classification scores, using the most common statistical measures. In particular, we reach an accuracy and sensitivity score of about 74%. The proposed method outperforms other similar classification methods based on secondary structure features and machine learning algorithms, including the RNAcon tool that, to date, is the reference classifier. nRC tool is freely available as a docker image at https://hub.docker.com/r/tblab/nrc/. The source code of nRC tool is also available at https://github.com/IcarPA-TBlab/nrc.

The sequence, structure and evolutionary features of HOTAIR in mammals

PubMed Central

2011-01-01

. 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

Quantification of Lignin and Its Structural Features in Plant Biomass Using 13C Lignin as Internal Standard for Pyrolysis-GC-SIM-MS.

PubMed

van Erven, Gijs; de Visser, Ries; Merkx, Donny W H; Strolenberg, Willem; de Gijsel, Peter; Gruppen, Harry; Kabel, Mirjam A

2017-10-17

Understanding the mechanisms underlying plant biomass recalcitrance at the molecular level can only be achieved by accurate analyses of both the content and structural features of the molecules involved. Current quantification of lignin is, however, majorly based on unspecific gravimetric analysis after sulfuric acid hydrolysis. Hence, our research aimed at specific lignin quantification with concurrent characterization of its structural features. Hereto, for the first time, a polymeric 13 C lignin was used as internal standard (IS) for lignin quantification via analytical pyrolysis coupled to gas chromatography with mass-spectrometric detection in selected ion monitoring mode (py-GC-SIM-MS). In addition, relative response factors (RRFs) for the various pyrolysis products obtained were determined and applied. First, 12 C and 13 C lignin were isolated from nonlabeled and uniformly 13 C labeled wheat straw, respectively, and characterized by heteronuclear single quantum coherence (HSQC), nuclear magnetic resonance (NMR), and py-GC/MS. The two lignin isolates were found to have identical structures. Second, 13 C-IS based lignin quantification by py-GC-SIM-MS was validated in reconstituted biomass model systems with known contents of the 12 C lignin analogue and was shown to be extremely accurate (>99.9%, R 2 > 0.999) and precise (RSD < 1.5%). Third, 13 C-IS based lignin quantification was applied to four common poaceous biomass sources (wheat straw, barley straw, corn stover, and sugar cane bagasse), and lignin contents were in good agreement with the total gravimetrically determined lignin contents. Our robust method proves to be a promising alternative for the high-throughput quantification of lignin in milled biomass samples directly and simultaneously provides a direct insight into the structural features of lignin.

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

Evaluation of Waveform Structure Features on Time Domain Target Recognition under Cross Polarization

NASA Astrophysics Data System (ADS)

Selver, M. A.; Seçmen, M.; Zoral, E. Y.

2016-08-01

Classification of aircraft targets from scattered electromagnetic waves is a challenging application, which suffers from aspect angle dependency. In order to eliminate the adverse effects of aspect angle, various strategies were developed including the techniques that rely on extraction of several features and design of suitable classification systems to process them. Recently, a hierarchical method, which uses features that take advantage of waveform structure of the scattered signals, is introduced and shown to have effective results. However, this approach has been applied to the special cases that consider only a single planar component of electric field that cause no-cross polarization at the observation point. In this study, two small scale aircraft models, Boeing-747 and DC-10, are selected as the targets and various polarizations are used to analyse the cross-polarization effects on system performance of the aforementioned method. The results reveal the advantages and the shortcomings of using waveform structures in time-domain target identification.

Texture feature extraction based on a uniformity estimation method for local brightness and structure in chest CT images.

PubMed

Peng, Shao-Hu; Kim, Deok-Hwan; Lee, Seok-Lyong; Lim, Myung-Kwan

2010-01-01

Texture feature is one of most important feature analysis methods in the computer-aided diagnosis (CAD) systems for disease diagnosis. In this paper, we propose a Uniformity Estimation Method (UEM) for local brightness and structure to detect the pathological change in the chest CT images. Based on the characteristics of the chest CT images, we extract texture features by proposing an extension of rotation invariant LBP (ELBP(riu4)) and the gradient orientation difference so as to represent a uniform pattern of the brightness and structure in the image. The utilization of the ELBP(riu4) and the gradient orientation difference allows us to extract rotation invariant texture features in multiple directions. Beyond this, we propose to employ the integral image technique to speed up the texture feature computation of the spatial gray level dependent method (SGLDM). Copyright © 2010 Elsevier Ltd. All rights reserved.

Some volcanic and structural features of Mare Serenitatis. [as determined by low angle lighting in Apollo 17 photography

NASA Technical Reports Server (NTRS)

Bryan, W. B.; Adams, M.

1973-01-01

Relationships between volcanic and structural features along the southern edge of Mare Serenitatis as determined from low angle lighting in Apollo 17 photographs are discussed. Observational summaries are given of: (1) contact relations between the dark border material and the central mare fill, (2) a late stage lava flow with associated cinder cones, and (3) certain structural features related to the development of the mare basin and its associated volcanic landforms. A chronologic summary is given of volcanic and structural events believed to be critical to understanding the development of Mare Serenitatis.

Additive-manufactured sandwich lattice structures: A numerical and experimental investigation

NASA Astrophysics Data System (ADS)

Fergani, Omar; Tronvoll, Sigmund; Brøtan, Vegard; Welo, Torgeir; Sørby, Knut

2017-10-01

The utilization of additive-manufactured lattice structures in engineered products is becoming more and more common as the competitiveness of AM as a production technology has increased during the past several years. Lattice structures may enable important weight reductions as well as open opportunities to build products with customized functional properties, thanks to the flexibility of AM for producing complex geometrical configurations. One of the most critical aspects related to taking AM into new application areas—such as safety critical products—is currently the limited understanding of the mechanical behavior of sandwich-based lattice structure mechanical under static and dynamic loading. In this study, we evaluate manufacturability of lattice structures and the impact of AM processing parameters on the structural behavior of this type of sandwich structures. For this purpose, we conducted static compression testing for a variety of geometry and manufacturing parameters. Further, the study discusses a numerical model capable of predicting the behavior of different lattice structure. A reasonably good correlation between the experimental and numerical results was observed.

Automated discrimination of dementia spectrum disorders using extreme learning machine and structural T1 MRI features.

PubMed

Jongin Kim; Boreom Lee

2017-07-01

The classification of neuroimaging data for the diagnosis of Alzheimer's Disease (AD) is one of the main research goals of the neuroscience and clinical fields. In this study, we performed extreme learning machine (ELM) classifier to discriminate the AD, mild cognitive impairment (MCI) from normal control (NC). We compared the performance of ELM with that of a linear kernel support vector machine (SVM) for 718 structural MRI images from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The data consisted of normal control, MCI converter (MCI-C), MCI non-converter (MCI-NC), and AD. We employed SVM-based recursive feature elimination (RFE-SVM) algorithm to find the optimal subset of features. In this study, we found that the RFE-SVM feature selection approach in combination with ELM shows the superior classification accuracy to that of linear kernel SVM for structural T1 MRI data.

Design, construction and operation features of high-rise structures

NASA Astrophysics Data System (ADS)

Mylnik, Alexey; Mylnik, Vladimir; Zubeeva, Elena; Mukhamedzhanova, Olga

2018-03-01

The article considers design, construction and operation features of high-rise facilities. The analysis of various situations, that come from improper designing, construction and operation of unique facilities, is carried out. The integrated approach is suggested, when the problems of choosing acceptable constructional solutions related to the functional purpose, architectural solutions, methods of manufacturing and installation, operating conditions for unique buildings and structures are being tackled. A number of main causes for the emergency destruction of objects under construction and operation is considered. A number of measures are proposed on the basis of factor classification in order to efficiently prevent the situations, when various negative options of design loads and emergency impacts occur.

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

Additive Manufacturing of Aerospace Alloys for Aircraft Structures

DTIC Science & Technology

2006-05-01

power and traverse speed on microstructure, porosity , and build height in laser-deposited Ti- 6Al - 4V ”, Scripta Mater., Vol. 43, pp. 299-305, 2000. [10...laser additive manufacturing) process to produce Ti- 6Al - 4V structures. Many similar processes are under development elsewhere, including electron-beam...wattage CO2 laser and a powder feed system to deposit wide, thick beads (~ 0.5” x 0.15”) of Ti- 6Al - 4V onto a substrate. The primary LAMSM deposition

Quantitative Susceptibility Mapping using Structural Feature based Collaborative Reconstruction (SFCR) in the Human Brain

PubMed Central

Cai, Congbo; Chen, Zhong; van Zijl, Peter C.M.

2017-01-01

The reconstruction of MR quantitative susceptibility mapping (QSM) from local phase measurements is an ill posed inverse problem and different regularization strategies incorporating a priori information extracted from magnitude and phase images have been proposed. However, the anatomy observed in magnitude and phase images does not always coincide spatially with that in susceptibility maps, which could give erroneous estimation in the reconstructed susceptibility map. In this paper, we develop a structural feature based collaborative reconstruction (SFCR) method for QSM including both magnitude and susceptibility based information. The SFCR algorithm is composed of two consecutive steps corresponding to complementary reconstruction models, each with a structural feature based l1 norm constraint and a voxel fidelity based l2 norm constraint, which allows both the structure edges and tiny features to be recovered, whereas the noise and artifacts could be reduced. In the M-step, the initial susceptibility map is reconstructed by employing a k-space based compressed sensing model incorporating magnitude prior. In the S-step, the susceptibility map is fitted in spatial domain using weighted constraints derived from the initial susceptibility map from the M-step. Simulations and in vivo human experiments at 7T MRI show that the SFCR method provides high quality susceptibility maps with improved RMSE and MSSIM. Finally, the susceptibility values of deep gray matter are analyzed in multiple head positions, with the supine position most approximate to the gold standard COSMOS result. PMID:27019480

New features in the structure of the classical Kuiper Belt

NASA Astrophysics Data System (ADS)

Gladman, Brett; Bannister, Michele T.; Alexandersen, Mike; Chen, Ying-Tung; Gwyn, Stephen; Kavelaars, J. J.; Petit, Jean-Marc; Volk, Kathryn; OSSOS Collaboration

2016-10-01

We report fascinating new dynamical structures emerging from a higher precision view of the classical Kuiper belt (the plentiful non-resonant orbits with semimajor axes in roughly the a=35-60 au range). The classical Kuiper Belt divides into multiple sub-populations: an 'inner' classical belt (a small group of non-resonant objects with a<39.4 au where the 3:2 resonance is located), an abundant 'main' classical belt (between the 3:2 and the 2:1 at a=47.4 au), and a difficult to study outer classical belt beyond the 2:1. We examine the dynamical structure, as precisely revealed in the detections from OSSOS (the Outer Solar System Origin's Survey); the data set is of superb quality in terms of orbital element and numbers of detections (Kavelaars et al, this meeting).The previous CFEPS survey showed that the main classical belt requires a complex dynamical substructure that goes beyond a simple 'hot versus cold' division based primarily on orbital inclination; the 'cold' inclination component requires two sub-components in the semimajor axis and perihelion distance q space (Petit et al 2011). CFEPS modelled this as a 'stirred' component present at all a=40-47 AU semimajor axes, with a dense superposed 'kernel' near a=44 AU at low eccentricity; the first OSSOS data release remained consistent with this (Bannister et al 2016). As with the main asteroid belt, as statistics and orbital quality improve we see additional significant substructure emerging in the classical belt's orbital distribution.OSSOS continues to add evidence that the cold stirred component extends smoothly beyond the 2:1 (Bannister et al 2016). Unexpectedly, the data also reveal the clear existence of a paucity of orbits just beyond the outer edge of the kernel; there are significantly fewer TNOs in the narrow semimajor axis band from a=44.5-45.0 AU. This may be related to the kernel population's creation, or it may be an independent feature created by planet migration as resonances moved in the

High Fidelity Additive Manufacturing of Optically Transparent Glass Structures

NASA Astrophysics Data System (ADS)

Inamura, Chikara

Glass has been an integral part of human civilization with expressions across scales and disciplines: from the microscope to the telescope, from fiber optics to mobile interface, and from the petri dish to a building envelope. Such a diverse range of applications is enabled by the inherent material properties including mechanical strength, optical transparency and chemical inertness. Additive manufacturing provides opportunities for integrating the unique properties of glass to engineer novel structures that are functionary graded through precise spatiotemporal deposition of molten glass. This talk presents the Mediated Matter Group's latest development of a novel additive manufacturing platform, and related processes, for 3D Printing optically transparent glass for architectural scale applications.

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.

Computer ranking of the sequence of appearance of 73 features of the brain and related structures in staged human embryos during the sixth week of development.

PubMed

O'Rahilly, R; Müller, F; Hutchins, G M; Moore, G W

1987-09-01

The sequence of events in the development of the brain in human embryos, already published for stages 8-15, is here continued for stages 16 and 17. With the aid of a computerized bubble-sort algorithm, 71 individual embryos were ranked in ascending order of the features present. Whereas these numbered 100 in the previous study, the increasing structural complexity gave 27 new features in the two stages now under investigation. The chief characteristics of stage 16 (approximately 37 postovulatory days) are protruding basal nuclei, the caudal olfactory elevation (olfactory tubercle), the tectobulbar tracts, and ascending fibers to the cerebellum. The main features of stage 17 (approximately 41 postovulatory days) are the cortical nucleus of the amygdaloid body, an intermediate layer in the tectum mesencephali, the posterior commissure, and the habenulo-interpeduncular tract. In addition, a typical feature at stage 17 is the crescentic shape of the lens cavity.

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

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.

Features of Cross-Correlation Analysis in a Data-Driven Approach for Structural Damage Assessment

PubMed Central

Camacho Navarro, Jhonatan; Ruiz, Magda; Villamizar, Rodolfo; Mujica, Luis

2018-01-01

This work discusses the advantage of using cross-correlation analysis in a data-driven approach based on principal component analysis (PCA) and piezodiagnostics to obtain successful diagnosis of events in structural health monitoring (SHM). In this sense, the identification of noisy data and outliers, as well as the management of data cleansing stages can be facilitated through the implementation of a preprocessing stage based on cross-correlation functions. Additionally, this work evidences an improvement in damage detection when the cross-correlation is included as part of the whole damage assessment approach. The proposed methodology is validated by processing data measurements from piezoelectric devices (PZT), which are used in a piezodiagnostics approach based on PCA and baseline modeling. Thus, the influence of cross-correlation analysis used in the preprocessing stage is evaluated for damage detection by means of statistical plots and self-organizing maps. Three laboratory specimens were used as test structures in order to demonstrate the validity of the methodology: (i) a carbon steel pipe section with leak and mass damage types, (ii) an aircraft wing specimen, and (iii) a blade of a commercial aircraft turbine, where damages are specified as mass-added. As the main concluding remark, the suitability of cross-correlation features combined with a PCA-based piezodiagnostic approach in order to achieve a more robust damage assessment algorithm is verified for SHM tasks. PMID:29762505

Features of Cross-Correlation Analysis in a Data-Driven Approach for Structural Damage Assessment.

PubMed

Camacho Navarro, Jhonatan; Ruiz, Magda; Villamizar, Rodolfo; Mujica, Luis; Quiroga, Jabid

2018-05-15

This work discusses the advantage of using cross-correlation analysis in a data-driven approach based on principal component analysis (PCA) and piezodiagnostics to obtain successful diagnosis of events in structural health monitoring (SHM). In this sense, the identification of noisy data and outliers, as well as the management of data cleansing stages can be facilitated through the implementation of a preprocessing stage based on cross-correlation functions. Additionally, this work evidences an improvement in damage detection when the cross-correlation is included as part of the whole damage assessment approach. The proposed methodology is validated by processing data measurements from piezoelectric devices (PZT), which are used in a piezodiagnostics approach based on PCA and baseline modeling. Thus, the influence of cross-correlation analysis used in the preprocessing stage is evaluated for damage detection by means of statistical plots and self-organizing maps. Three laboratory specimens were used as test structures in order to demonstrate the validity of the methodology: (i) a carbon steel pipe section with leak and mass damage types, (ii) an aircraft wing specimen, and (iii) a blade of a commercial aircraft turbine, where damages are specified as mass-added. As the main concluding remark, the suitability of cross-correlation features combined with a PCA-based piezodiagnostic approach in order to achieve a more robust damage assessment algorithm is verified for SHM tasks.

Quantification of Lignin and Its Structural Features in Plant Biomass Using 13C Lignin as Internal Standard for Pyrolysis-GC-SIM-MS

PubMed Central

2017-01-01

Understanding the mechanisms underlying plant biomass recalcitrance at the molecular level can only be achieved by accurate analyses of both the content and structural features of the molecules involved. Current quantification of lignin is, however, majorly based on unspecific gravimetric analysis after sulfuric acid hydrolysis. Hence, our research aimed at specific lignin quantification with concurrent characterization of its structural features. Hereto, for the first time, a polymeric 13C lignin was used as internal standard (IS) for lignin quantification via analytical pyrolysis coupled to gas chromatography with mass-spectrometric detection in selected ion monitoring mode (py-GC-SIM-MS). In addition, relative response factors (RRFs) for the various pyrolysis products obtained were determined and applied. First, 12C and 13C lignin were isolated from nonlabeled and uniformly 13C labeled wheat straw, respectively, and characterized by heteronuclear single quantum coherence (HSQC), nuclear magnetic resonance (NMR), and py-GC/MS. The two lignin isolates were found to have identical structures. Second, 13C-IS based lignin quantification by py-GC-SIM-MS was validated in reconstituted biomass model systems with known contents of the 12C lignin analogue and was shown to be extremely accurate (>99.9%, R2 > 0.999) and precise (RSD < 1.5%). Third, 13C-IS based lignin quantification was applied to four common poaceous biomass sources (wheat straw, barley straw, corn stover, and sugar cane bagasse), and lignin contents were in good agreement with the total gravimetrically determined lignin contents. Our robust method proves to be a promising alternative for the high-throughput quantification of lignin in milled biomass samples directly and simultaneously provides a direct insight into the structural features of lignin. PMID:28926698

Robust Classification and Segmentation of Planar and Linear Features for Construction Site Progress Monitoring and Structural Dimension Compliance Control

NASA Astrophysics Data System (ADS)

Maalek, R.; Lichti, D. D.; Ruwanpura, J.

2015-08-01

The application of terrestrial laser scanners (TLSs) on construction sites for automating construction progress monitoring and controlling structural dimension compliance is growing markedly. However, current research in construction management relies on the planned building information model (BIM) to assign the accumulated point clouds to their corresponding structural elements, which may not be reliable in cases where the dimensions of the as-built structure differ from those of the planned model and/or the planned model is not available with sufficient detail. In addition outliers exist in construction site datasets due to data artefacts caused by moving objects, occlusions and dust. In order to overcome the aforementioned limitations, a novel method for robust classification and segmentation of planar and linear features is proposed to reduce the effects of outliers present in the LiDAR data collected from construction sites. First, coplanar and collinear points are classified through a robust principal components analysis procedure. The classified points are then grouped using a robust clustering method. A method is also proposed to robustly extract the points belonging to the flat-slab floors and/or ceilings without performing the aforementioned stages in order to preserve computational efficiency. The applicability of the proposed method is investigated in two scenarios, namely, a laboratory with 30 million points and an actual construction site with over 150 million points. The results obtained by the two experiments validate the suitability of the proposed method for robust segmentation of planar and linear features in contaminated datasets, such as those collected from construction sites.

Analysis of variability in additive manufactured open cell porous structures.

PubMed

Evans, Sam; Jones, Eric; Fox, Pete; Sutcliffe, Chris

2017-06-01

In this article, a novel method of analysing build consistency of additively manufactured open cell porous structures is presented. Conventionally, methods such as micro computed tomography or scanning electron microscopy imaging have been applied to the measurement of geometric properties of porous material; however, high costs and low speeds make them unsuitable for analysing high volumes of components. Recent advances in the image-based analysis of open cell structures have opened up the possibility of qualifying variation in manufacturing of porous material. Here, a photogrammetric method of measurement, employing image analysis to extract values for geometric properties, is used to investigate the variation between identically designed porous samples measuring changes in material thickness and pore size, both intra- and inter-build. Following the measurement of 125 samples, intra-build material thickness showed variation of ±12%, and pore size ±4% of the mean measured values across five builds. Inter-build material thickness and pore size showed mean ranges higher than those of intra-build, ±16% and ±6% of the mean material thickness and pore size, respectively. Acquired measurements created baseline variation values and demonstrated techniques suitable for tracking build deviation and inspecting additively manufactured porous structures to indicate unwanted process fluctuations.

Guiding exploration in conformational feature space with Lipschitz underestimation for ab-initio protein structure prediction.

PubMed

Hao, Xiaohu; Zhang, Guijun; Zhou, Xiaogen

2018-04-01

Computing conformations which are essential to associate structural and functional information with gene sequences, is challenging due to the high dimensionality and rugged energy surface of the protein conformational space. Consequently, the dimension of the protein conformational space should be reduced to a proper level, and an effective exploring algorithm should be proposed. In this paper, a plug-in method for guiding exploration in conformational feature space with Lipschitz underestimation (LUE) for ab-initio protein structure prediction is proposed. The conformational space is converted into ultrafast shape recognition (USR) feature space firstly. Based on the USR feature space, the conformational space can be further converted into Underestimation space according to Lipschitz estimation theory for guiding exploration. As a consequence of the use of underestimation model, the tight lower bound estimate information can be used for exploration guidance, the invalid sampling areas can be eliminated in advance, and the number of energy function evaluations can be reduced. The proposed method provides a novel technique to solve the exploring problem of protein conformational space. LUE is applied to differential evolution (DE) algorithm, and metropolis Monte Carlo(MMC) algorithm which is available in the Rosetta; When LUE is applied to DE and MMC, it will be screened by the underestimation method prior to energy calculation and selection. Further, LUE is compared with DE and MMC by testing on 15 small-to-medium structurally diverse proteins. Test results show that near-native protein structures with higher accuracy can be obtained more rapidly and efficiently with the use of LUE. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

Orientale and Caloris. [lunar basins with similar structural features

NASA Technical Reports Server (NTRS)

Mccauley, J. F.

1977-01-01

Based on revised stratigraphy, structural interpretation, explosion-crater data, and a genetic model for Orientale, it is suggested that Orientale and Caloris have much in common. It is noted that: (1) although the basin fill in Caloris is different from that seen in Orientale, the materials between the most prominent scarp and the weakly-developed outer scarp may be degraded equivalents of the massifs and knobs associated with the Montes Rook, (2) the Montes Rook and the main Caloris scarp have similar stratigraphic and structural features, (3) the lineated ejecta derived from shallower horizons are found near and beyond the weakly-developed outer Caloris scarp which is the counterpart of the Orientale scarp, (4) a well developed field of secondary craters is observed beyond 1 basin diameter at Caloris, (5) the observed textural differences between the material around the main Caloris scarp and the lineated material beyond suggest that Mercury is layered and that Caloris crater excavated coherent materials from one or more of these layers at depth, and (6) the difference in spacing between the Caloris rings is not related to internal layering effects.

Structural and phylogenetic analysis of Rhodobacter capsulatus NifF: uncovering general features of nitrogen-fixation (nif)-flavodoxins.

PubMed

Pérez-Dorado, Inmaculada; Bortolotti, Ana; Cortez, Néstor; Hermoso, Juan A

2013-01-09

Analysis of the crystal structure of NifF from Rhodobacter capsulatus and its homologues reported so far reflects the existence of unique structural features in nif flavodoxins: a leucine at the re face of the isoalloxazine, an eight-residue insertion at the C-terminus of the 50's loop and a remarkable difference in the electrostatic potential surface with respect to non-nif flavodoxins. A phylogenetic study on 64 sequences from 52 bacterial species revealed four clusters, including different functional prototypes, correlating the previously defined as "short-chain" with the firmicutes flavodoxins and the "long-chain" with gram-negative species. The comparison of Rhodobacter NifF structure with other bacterial flavodoxin prototypes discloses the concurrence of specific features of these functional electron donors to nitrogenase.

Additive manufacturing of biologically-inspired materials.

PubMed

Studart, André R

2016-01-21

Additive manufacturing (AM) technologies offer an attractive pathway towards the fabrication of functional materials featuring complex heterogeneous architectures inspired by biological systems. In this paper, recent research on the use of AM approaches to program the local chemical composition, structure and properties of biologically-inspired materials is reviewed. A variety of structural motifs found in biological composites have been successfully emulated in synthetic systems using inkjet-based, direct-writing, stereolithography and slip casting technologies. The replication in synthetic systems of design principles underlying such structural motifs has enabled the fabrication of lightweight cellular materials, strong and tough composites, soft robots and autonomously shaping structures with unprecedented properties and functionalities. Pushing the current limits of AM technologies in future research should bring us closer to the manufacturing capabilities of living organisms, opening the way for the digital fabrication of advanced materials with superior performance, lower environmental impact and new functionalities.

Characterization and Comparison of the Structural Features, Immune-Modulatory and Anti-Avian Influenza Virus Activities Conferred by Three Algal Sulfated Polysaccharides

PubMed Central

Song, Lin; Chen, Xiaolin; Liu, Xiaodong; Zhang, Fubo; Hu, Linfeng; Yue, Yang; Li, Kecheng; Li, Pengcheng

2015-01-01

Three marine macroalgae, i.e., Grateloupia filicina, Ulva pertusa and Sargassum qingdaoense, were selected as the deputies of Rhodophyta, Chlorophyta and Ochrophyta for comparative analysis of the molecular structures and biological activities of sulfated polysaccharides (SP). The ratio of water-soluble polysaccharides, the monosaccharide composition and the sulfated contents of three extracted SPs were determined, and their structures were characterized by Fourier transformation infrared spectroscopy. In addition, biological activity analysis showed that all three SPs had immune-modulatory activity both in vitro and in vivo, and SPs from S. qingdaoense had the best effect. Further bioassays showed that three SPs could not only enhance the immunity level stimulated by inactivated avian influenza virus (AIV) in vivo but also significantly inhibited the activity of activated AIV (H9N2 subtype) in vitro. G. filicina SP exhibited the strongest anti-AIV activity. These results revealed the variations in structural features and bioactivities among three SPs and indicated the potential adjuvants for immune-enhancement and anti-AIV. PMID:26729137

Boosting structured additive quantile regression for longitudinal childhood obesity data.

PubMed

Fenske, Nora; Fahrmeir, Ludwig; Hothorn, Torsten; Rzehak, Peter; Höhle, Michael

2013-07-25

Childhood obesity and the investigation of its risk factors has become an important public health issue. Our work is based on and motivated by a German longitudinal study including 2,226 children with up to ten measurements on their body mass index (BMI) and risk factors from birth to the age of 10 years. We introduce boosting of structured additive quantile regression as a novel distribution-free approach for longitudinal quantile regression. The quantile-specific predictors of our model include conventional linear population effects, smooth nonlinear functional effects, varying-coefficient terms, and individual-specific effects, such as intercepts and slopes. Estimation is based on boosting, a computer intensive inference method for highly complex models. We propose a component-wise functional gradient descent boosting algorithm that allows for penalized estimation of the large variety of different effects, particularly leading to individual-specific effects shrunken toward zero. This concept allows us to flexibly estimate the nonlinear age curves of upper quantiles of the BMI distribution, both on population and on individual-specific level, adjusted for further risk factors and to detect age-varying effects of categorical risk factors. Our model approach can be regarded as the quantile regression analog of Gaussian additive mixed models (or structured additive mean regression models), and we compare both model classes with respect to our obesity data.

Features and Historical Aspects of the Philippines Educational System

ERIC Educational Resources Information Center

Musa, Sajid; Ziatdinov, Rushan

2012-01-01

This article deals with the features of the Philippine educational system. Additionally, brief and concise information will be given on how the educational system came into existence, the organization and the structure of the system itself. This paper also tackles the obstacles and problems observed in the past and up to the present, and gives…

Innovations in individual feature history management - The significance of feature-based temporal model

USGS Publications Warehouse

Choi, J.; Seong, J.C.; Kim, B.; Usery, E.L.

2008-01-01

A feature relies on three dimensions (space, theme, and time) for its representation. Even though spatiotemporal models have been proposed, they have principally focused on the spatial changes of a feature. In this paper, a feature-based temporal model is proposed to represent the changes of both space and theme independently. The proposed model modifies the ISO's temporal schema and adds new explicit temporal relationship structure that stores temporal topological relationship with the ISO's temporal primitives of a feature in order to keep track feature history. The explicit temporal relationship can enhance query performance on feature history by removing topological comparison during query process. Further, a prototype system has been developed to test a proposed feature-based temporal model by querying land parcel history in Athens, Georgia. The result of temporal query on individual feature history shows the efficiency of the explicit temporal relationship structure. ?? Springer Science+Business Media, LLC 2007.

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

Association between MRI structural features and cognitive measures in pediatric multiple sclerosis

NASA Astrophysics Data System (ADS)

Amoroso, N.; Bellotti, R.; Fanizzi, A.; Lombardi, A.; Monaco, A.; Liguori, M.; Margari, L.; Simone, M.; Viterbo, R. G.; Tangaro, S.

2017-09-01

Multiple sclerosis (MS) is an inflammatory and demyelinating disease associated with neurodegenerative processes that lead to brain structural changes. The disease affects mostly young adults, but 3-5% of cases has a pediatric onset (POMS). Magnetic Resonance Imaging (MRI) is generally used for diagnosis and follow-up in MS patients, however the most common MRI measures (e.g. new or enlarging T2-weighted lesions, T1-weighted gadolinium- enhancing lesions) have often failed as surrogate markers of MS disability and progression. MS is clinically heterogenous with symptoms that can include both physical changes (such as visual loss or walking difficulties) and cognitive impairment. 30-50% of POMS experience prominent cognitive dysfunction. In order to investigate the association between cognitive measures and brain morphometry, in this work we present a fully automated pipeline for processing and analyzing MRI brain scans. Relevant anatomical structures are segmented with FreeSurfer; besides, statistical features are computed. Thus, we describe the data referred to 12 patients with early POMS (mean age at MRI: 15.5 +/- 2.7 years) with a set of 181 structural features. The major cognitive abilities measured are verbal and visuo-spatial learning, expressive language and complex attention. Data was collected at the Department of Basic Sciences, Neurosciences and Sense Organs, University of Bari, and exploring different abilities like the verbal and visuo-spatial learning, expressive language and complex attention. Different regression models and parameter configurations are explored to assess the robustness of the results, in particular Generalized Linear Models, Bayes Regression, Random Forests, Support Vector Regression and Artificial Neural Networks are discussed.

Structural features of the San Andreas fault at Tejon Pass, California

NASA Astrophysics Data System (ADS)

Dewers, T. A.; Reches, Z.; Brune, J. N.

2002-12-01

We mapped a 2 km belt along the San Andreas fault (SAF) in the Tejon Pass area where road cuts provide fresh exposures of the fault zone and surrounding rocks. Our 1:2,000 structural mapping is focused on analysis of faulting processes and is complementary to regional mapping at 1:12,000 scale by Ramirez (M.Sc., UC Santa Barbara, 1984). The dominant rock units are the Hungry Valley Formation of Pliocene age (clastic sediments) exposed south of the SAF, and the Tejon Lookout granite (Cretaceous) and Neenach Volcanic Formation exposed north of it. Ramirez (1983) deduced ~220 km of post-Miocene lateral slip. The local trend of the SAF is about N60W and it includes at least three main, subparallel segments that form a 200 m wide zone. The traces of the segments are quasi-linear, discontinuous, and they are stepped with respect to each other, forming at least five small pull-aparts and sag ponds in the mapping area. The three segments were not active semi-contemporaneously and the southern segment is apparently the oldest. The largest pull-apart, 60-70 m wide, displays young (Quaternary?) silt and shale layers. We found two rock bodies that are suspected as fault-rocks. One is a 1-2 m thick sheet-like body that separates the Tejon Lookout granite from young (Recent?) clastic rocks. In the field, it appears as a gouge zone composed of poorly cemented, dark clay size grains; however, the microstructure of this rock does not reveal clear shear features. The second body is the 80-120 m wide zone of Tejon Lookout granite that extends for less than 1 km along the SAF in the mapped area. It is characterized by three structural features: (1) pulverization into friable, granular material by multitude of grain-crossing fractures; (2) abundance of dip-slip small faults that are gently dipping toward and away from the SAF; and (3) striking lack of evidence for shear parallel to the SAF. The relationships between these features and the large right-lateral shear along the SAF are

Discrimination Enhancement with Transient Feature Analysis of a Graphene Chemical Sensor.

PubMed

Nallon, Eric C; Schnee, Vincent P; Bright, Collin J; Polcha, Michael P; Li, Qiliang

2016-01-19

A graphene chemical sensor is subjected to a set of structurally and chemically similar hydrocarbon compounds consisting of toluene, o-xylene, p-xylene, and mesitylene. The fractional change in resistance of the sensor upon exposure to these compounds exhibits a similar response magnitude among compounds, whereas large variation is observed within repetitions for each compound, causing a response overlap. Therefore, traditional features depending on maximum response change will cause confusion during further discrimination and classification analysis. More robust features that are less sensitive to concentration, sampling, and drift variability would provide higher quality information. In this work, we have explored the advantage of using transient-based exponential fitting coefficients to enhance the discrimination of similar compounds. The advantages of such feature analysis to discriminate each compound is evaluated using principle component analysis (PCA). In addition, machine learning-based classification algorithms were used to compare the prediction accuracies when using fitting coefficients as features. The additional features greatly enhanced the discrimination between compounds while performing PCA and also improved the prediction accuracy by 34% when using linear discrimination analysis.

A review of the performance and structural considerations of paraffin wax hybrid rocket fuels with additives

NASA Astrophysics Data System (ADS)

Veale, Kirsty; Adali, Sarp; Pitot, Jean; Brooks, Michael

2017-12-01

Paraffin wax as a hybrid rocket fuel has not been comprehensively characterised, especially regarding the structural feasibility of the material in launch applications. Preliminary structural testing has shown paraffin wax to be a brittle, low strength material, and at risk of failure under launch loading conditions. Structural enhancing additives have been identified, but their effect on motor performance has not always been considered, nor has any standard method of testing been identified between research institutes. A review of existing regression rate measurement techniques on paraffin wax based fuels and the results obtained with various additives are collated and discussed in this paper. The review includes 2D slab motors that enable visualisation of liquefying fuel droplet entrainment and the effect of an increased viscosity on the droplet entrainment mechanism, which can occur with the addition of structural enhancing polymers. An increased viscosity has been shown to reduce the regression rate of liquefying fuels. Viscosity increasing additives that have been tested include EVA and LDPE. Both these additives increase the structural properties of paraffin wax, where the elongation and UTS are improved. Other additives, such as metal hydrides, aluminium and boron generally offer improvements on the regression rate. However, very little consideration has been given to the structural effects these additives have on the wax grain. A 40% aluminised grain, for example, offers a slight increase in the UTS but reduces the elongation of paraffin wax. Geometrically accurate lab-scale motors have also been used to determine the regression rate properties of various additives in paraffin wax. A concise review of all available regression rate testing techniques and results on paraffin wax based hybrid propellants, as well as existing structural testing data, is presented in this paper.

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.

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.

Understanding Reflectance Anisotropy: Surface-structure signatures and bulk-related features

NASA Astrophysics Data System (ADS)

Gero Schmidt, W.

2000-03-01

Reflectance anisotropy spectroscopy (RAS) is becoming an increasingly important tool for in situ control of semiconductor processing with real-time feedback. The understanding and interpretation of the measured spectra, however, has been hampered by relatively slow theoretical progress. Using a massively parallel real-space multigrid technique [1] and ab initio pseudopotentials we calculated the optical spectra of a variety of III-V(001) growth structures and stepped Si(111):H surfaces. Our results agree well with experiment, notably with respect to the stoichiometric changes induced by different surface preparations. We identify two distinct sources for the optical anisotropy: (i) highly structure-dependent features are caused by transitions involving electronic surface states, and (ii) derivative-like oscillations or peaks at the bulk critical point energies arise from transitions between surface-modified bulk wave functions. The latter are nearly independent from the actual surface structure. The agreement between the calculated and measured spectra is further improved by applying quasi-particle corrections obtained from numerically efficient, simplified GW calculations [2]. The combination of converged first-principles calculations with an approximate treatment of many-particle effects allows the reliable identification of ``surface-structure fingerprints'' in the optical spectra, paving the way for the exploitation of their rich technological potential. [1ex] [1] EL Briggs, DJ Sullivan, J Bernholc, Phys. Rev. B 54, 14362 (1996). [2] F Bechstedt, R Del Sole, G Cappellini, L Reining, Solid State Commun. 84, 765 (1992).

Estimating standard errors in feature network models.

PubMed

Frank, Laurence E; Heiser, Willem J

2007-05-01

Feature network models are graphical structures that represent proximity data in a discrete space while using the same formalism that is the basis of least squares methods employed in multidimensional scaling. Existing methods to derive a network model from empirical data only give the best-fitting network and yield no standard errors for the parameter estimates. The additivity properties of networks make it possible to consider the model as a univariate (multiple) linear regression problem with positivity restrictions on the parameters. In the present study, both theoretical and empirical standard errors are obtained for the constrained regression parameters of a network model with known features. The performance of both types of standard error is evaluated using Monte Carlo techniques.

Linking structural features from mitochondrial and bacterial F-type ATP synthases to their distinct mechanisms of ATPase inhibition.

PubMed

Krah, Alexander

2015-10-01

ATP synthases are molecular motors, which synthesize ATP, the ubiquitous energy source in all living cells. They use an electrochemical gradient to drive a rotation in the membrane embedded Fo domain, namely the c-ring, causing a conformational change in the soluble F1 domain which leads to the catalytic event. In the opposite fashion, they can also hydrolyse ATP to maintain the ion gradient across the membrane. To prevent wasteful ATP hydrolysis, bacteria and mammals have developed peculiar mechanistic features in addition to a common one, namely MgADP inhibition. Here I discuss the distinct ATPase inhibition mechanism in mitochondrial (IF1) and bacterial (subunits ε and ζ) F-type ATP synthases, based on available structural, biophysical and biochemical data. Copyright © 2015 Elsevier Ltd. All rights reserved.

Structural and ultrastructural features of the agouti tongue (Dasyprocta aguti Linnaeus, 1766)

PubMed Central

Ciena, Adriano Polican; Bolina, Cristina de Sousa; de Almeida, Sonia Regina Yokomizo; Rici, Rose Eli Grassi; de Oliveira, Moacir Franco; da da Silva, Marcelo Cavenaghi Pereira; Miglino, Maria Angélica; Watanabe, Ii-sei

2013-01-01

The agouti (Dasyprocta aguti Linnaeus, 1766) is a wild rodent belonging to the family Dasyproctidae that is found throughout Brazil and feeds on fruits and seeds. The aim of the present study was to describe the following features of the tongue of agouti: its morphological structures, the three-dimensional characteristics of the lingual papillae surface, the connective tissue cores (CTCs) and the epithelial cell ultrastructure. Four types of papillae were observed on the dorsal surface of the tongue with a triangular shape: filiform, fungiform, foliate and vallate. Filiform papillae were distributed throughout the tongue surface, and removal of the epithelial surface revealed conical CTCs and multifilaments. Fungiform papillae were observed in the rostral and middle regions, whereas foliate papillae developed in pairs on the lateral margin of the caudal region. Removal of the epithelium in these regions revealed CTCs with parallel laminar conformation. Vallate papillae were arranged in a V-shape in the caudal region, and their CTCs ranged in shape from elongate to ovoid. The ultrastructural components of the dorsal epithelium were the basal, spinous, granular and keratinised layers. A broad area with cytoplasmic projections was identified in the interface region between the lamina propria and the basal layer. Flattened cells with intermediate filaments were observed in the transitional region between spinous and granular layers. The keratinised layer was composed of superimposed epithelial cells where desmosomes and cell-surface microridges were observed. These structural features, including the three-dimensional aspects of the lingual papillae, the CTCs and the epithelial ultrastructure, indicate that when compared with other animals, particularly other rodent species, the morphological features of the tongue of agouti are relatively well developed, especially regarding foliate and vallate papillae. PMID:23701183

Structure of ternary additive hard-sphere fluid mixtures.

PubMed

Malijevský, Alexander; Malijevský, Anatol; Yuste, Santos B; Santos, Andrés; López de Haro, Mariano

2002-12-01

Monte Carlo simulations on the structural properties of ternary fluid mixtures of additive hard spheres are reported. The results are compared with those obtained from a recent analytical approximation [S. B. Yuste, A. Santos, and M. López de Haro, J. Chem. Phys. 108, 3683 (1998)] to the radial distribution functions of hard-sphere mixtures and with the results derived from the solution of the Ornstein-Zernike integral equation with both the Martynov-Sarkisov and the Percus-Yevick closures. Very good agreement between the results of the first two approaches and simulation is observed, with a noticeable improvement over the Percus-Yevick predictions especially near contact.

Structural and superconducting features of Tl-1223 prepared at ambient pressure

DOE PAGES

Shipra, Fnu; Idrobo Tapia, Juan Carlos; Sefat, Athena Safa

2015-09-25

This study provides an account of the bulk preparation of TlBa 2Ca 2Cu 3O 9-δ (Tl-1223) superconductor at ambient pressure, and the Tc features under thermal-annealing conditions. The ‘as-prepared’ Tl-1223 (Tc =106 K) presents a significantly higher T c = 125 K after annealing the polycrystalline material in either flowing Ar+4% H 2, or N 2 gases. In order to understand the fundamental reasons for a particular Tc, we refined the average bulk structures using powder X-ray diffraction data. Although Ar+4%H2 annealed Tl- 1223 shows an increased ‘c’ lattice parameter, it shrinks by 0.03% (approximately unchanged) upon N2 anneal. Duemore » to such indeterminate conclusions on the average structural changes, local structures were investigated at using aberration-corrected scanning-transmission electron microscopy technique. Similar compositional changes in the atomic arrangements of both annealed-samples of Tl-1223 were detected in which the plane containing Ca atomic layer gives a non-uniform contrast, due to substitution of some heavier Tl. In this report, extensive bulk properties are summarized through temperature-dependent resistivity, and shielding and Meissner fractions of magnetic susceptibility results; the bulk and local structures are investigated to correlate to properties.« less

PSSP-RFE: accurate prediction of protein structural class by recursive feature extraction from PSI-BLAST profile, physical-chemical property and functional annotations.

PubMed

Li, Liqi; Cui, Xiang; Yu, Sanjiu; Zhang, Yuan; Luo, Zhong; Yang, Hua; Zhou, Yue; Zheng, Xiaoqi

2014-01-01

Protein structure prediction is critical to functional annotation of the massively accumulated biological sequences, which prompts an imperative need for the development of high-throughput technologies. As a first and key step in protein structure prediction, protein structural class prediction becomes an increasingly challenging task. Amongst most homological-based approaches, the accuracies of protein structural class prediction are sufficiently high for high similarity datasets, but still far from being satisfactory for low similarity datasets, i.e., below 40% in pairwise sequence similarity. Therefore, we present a novel method for accurate and reliable protein structural class prediction for both high and low similarity datasets. This method is based on Support Vector Machine (SVM) in conjunction with integrated features from position-specific score matrix (PSSM), PROFEAT and Gene Ontology (GO). A feature selection approach, SVM-RFE, is also used to rank the integrated feature vectors through recursively removing the feature with the lowest ranking score. The definitive top features selected by SVM-RFE are input into the SVM engines to predict the structural class of a query protein. To validate our method, jackknife tests were applied to seven widely used benchmark datasets, reaching overall accuracies between 84.61% and 99.79%, which are significantly higher than those achieved by state-of-the-art tools. These results suggest that our method could serve as an accurate and cost-effective alternative to existing methods in protein structural classification, especially for low similarity datasets.

Hemipteran Mitochondrial Genomes: Features, Structures and Implications for Phylogeny

PubMed Central

Wang, Yuan; Chen, Jing; Jiang, Li-Yun; Qiao, Ge-Xia

2015-01-01

The study of Hemipteran mitochondrial genomes (mitogenomes) began with the Chagas disease vector, Triatoma dimidiata, in 2001. At present, 90 complete Hemipteran mitogenomes have been sequenced and annotated. This review examines the history of Hemipteran mitogenomes research and summarizes the main features of them including genome organization, nucleotide composition, protein-coding genes, tRNAs and rRNAs, and non-coding regions. Special attention is given to the comparative analysis of repeat regions. Gene rearrangements are an additional data type for a few families, and most mitogenomes are arranged in the same order to the proposed ancestral insect. We also discuss and provide insights on the phylogenetic analyses of a variety of taxonomic levels. This review is expected to further expand our understanding of research in this field and serve as a valuable reference resource. PMID:26039239

Structure and properties of parts produced by electron-beam additive manufacturing

NASA Astrophysics Data System (ADS)

Klimenov, Vasilii; Klopotov, Anatolii; Fedorov, Vasilii; Abzaev, Yurii; Batranin, Andrey; Kurgan, Kirill; Kairalapov, Daniyar

2017-12-01

The paper deals with the study of structure, microstructure, composition and microhardness of a tube processed by electron-beam additive manufacturing using optical and scanning electron microscopy. The structure and macrodefects of a tube made of Grade2 titanium alloy is studied using the X-ray computed tomography. The principles of layer-by-layer assembly and boundaries after powder sintering are set out in this paper. It is found that the titanium alloy has two phases. Future work will involve methods to improve properties of created parts.

A Novel Method Using Abstract Convex Underestimation in Ab-Initio Protein Structure Prediction for Guiding Search in Conformational Feature Space.

PubMed

Hao, Xiao-Hu; Zhang, Gui-Jun; Zhou, Xiao-Gen; Yu, Xu-Feng

2016-01-01

To address the searching problem of protein conformational space in ab-initio protein structure prediction, a novel method using abstract convex underestimation (ACUE) based on the framework of evolutionary algorithm was proposed. Computing such conformations, essential to associate structural and functional information with gene sequences, is challenging due to the high-dimensionality and rugged energy surface of the protein conformational space. As a consequence, the dimension of protein conformational space should be reduced to a proper level. In this paper, the high-dimensionality original conformational space was converted into feature space whose dimension is considerably reduced by feature extraction technique. And, the underestimate space could be constructed according to abstract convex theory. Thus, the entropy effect caused by searching in the high-dimensionality conformational space could be avoided through such conversion. The tight lower bound estimate information was obtained to guide the searching direction, and the invalid searching area in which the global optimal solution is not located could be eliminated in advance. Moreover, instead of expensively calculating the energy of conformations in the original conformational space, the estimate value is employed to judge if the conformation is worth exploring to reduce the evaluation time, thereby making computational cost lower and the searching process more efficient. Additionally, fragment assembly and the Monte Carlo method are combined to generate a series of metastable conformations by sampling in the conformational space. The proposed method provides a novel technique to solve the searching problem of protein conformational space. Twenty small-to-medium structurally diverse proteins were tested, and the proposed ACUE method was compared with It Fix, HEA, Rosetta and the developed method LEDE without underestimate information. Test results show that the ACUE method can more rapidly and more

Effect of hydrogen peroxide pretreatment on the structural features and the enzymatic hydrolysis of rice straw.

PubMed

Wei, C J; Cheng, C Y

1985-10-01

Assessment was made to evaluate the effect of hydrogen peroxide pretreatment on the change of the structural features and the enzymatic hydrolysis of rice straw. Changes in the lignin content, weight loss, accessibility for Cadoxen, water holding capacity, and crystallinity of straw were measured during pretreatment to express the modification of the lignocellulosic structure of straw. The rates and the extents of enzymatic hydrolysis, cellulase adsorption, and cellobiose accumulation in the initial stage of hydrolysis were determined to study the pretreatment effect on hydrolysis. Pretreatment at 60 degrees C for 5 h in a solution with 1% (w/w) H(2)O(2) and NaOH resulted in 60% delignification, 40% weight loss, a fivefold increase in the accessibility for Cadoxen, an one times increase in the water-holding capacity, and only a slight decrease in crystallinity as compared with that of the untreated straw. Improvement on the pretreatment effect could be made by increasing the initial alkalinity and the pretreatment temperature of hydrogen peroxide solution. A saturated improvement on the structural features was found when the weight ratio of hydrogen peroxide to straw was above 0.25 g H(2)O(2)/g straw in an alkaline H(2)O(2) solution with 1% (w/w) NaOH at 32 degrees C. The initial rates and extents of hydrolysis, cellulase adsorption, and cellobiose accumulation in hydrolysis were enhanced in accordance with the improved structural features of straw pretreated. A four times increase in the extent of the enzymatic hydrolysis of straw for 24 h was attributed to the alkaline hydrogen peroxide pretreatment.

Hybrid Residual Flexibility/Mass-Additive Method for Structural Dynamic Testing

NASA Technical Reports Server (NTRS)

Tinker, M. L.

2003-01-01

A large fixture was designed and constructed for modal vibration testing of International Space Station elements. This fixed-base test fixture, which weighs thousands of pounds and is anchored to a massive concrete floor, initially utilized spherical bearings and pendulum mechanisms to simulate Shuttle orbiter boundary constraints for launch of the hardware. Many difficulties were encountered during a checkout test of the common module prototype structure, mainly due to undesirable friction and excessive clearances in the test-article-to-fixture interface bearings. Measured mode shapes and frequencies were not representative of orbiter-constrained modes due to the friction and clearance effects in the bearings. As a result, a major redesign effort for the interface mechanisms was undertaken. The total cost of the fixture design, construction and checkout, and redesign was over $2 million. Because of the problems experienced with fixed-base testing, alternative free-suspension methods were studied, including the residual flexibility and mass-additive approaches. Free-suspension structural dynamics test methods utilize soft elastic bungee cords and overhead frame suspension systems that are less complex and much less expensive than fixed-base systems. The cost of free-suspension fixturing is on the order of tens of thousands of dollars as opposed to millions, for large fixed-base fixturing. In addition, free-suspension test configurations are portable, allowing modal tests to be done at sites without modal test facilities. For example, a mass-additive modal test of the ASTRO-1 Shuttle payload was done at the Kennedy Space Center launch site. In this Technical Memorandum, the mass-additive and residual flexibility test methods are described in detail. A discussion of a hybrid approach that combines the best characteristics of each method follows and is the focus of the study.

A combination of feature extraction methods with an ensemble of different classifiers for protein structural class prediction problem.

PubMed

Dehzangi, Abdollah; Paliwal, Kuldip; Sharma, Alok; Dehzangi, Omid; Sattar, Abdul

2013-01-01

Better understanding of structural class of a given protein reveals important information about its overall folding type and its domain. It can also be directly used to provide critical information on general tertiary structure of a protein which has a profound impact on protein function determination and drug design. Despite tremendous enhancements made by pattern recognition-based approaches to solve this problem, it still remains as an unsolved issue for bioinformatics that demands more attention and exploration. In this study, we propose a novel feature extraction model that incorporates physicochemical and evolutionary-based information simultaneously. We also propose overlapped segmented distribution and autocorrelation-based feature extraction methods to provide more local and global discriminatory information. The proposed feature extraction methods are explored for 15 most promising attributes that are selected from a wide range of physicochemical-based attributes. Finally, by applying an ensemble of different classifiers namely, Adaboost.M1, LogitBoost, naive Bayes, multilayer perceptron (MLP), and support vector machine (SVM) we show enhancement of the protein structural class prediction accuracy for four popular benchmarks.

Generic Features of Tertiary Chromatin Structure as Detected in Natural Chromosomes

PubMed Central

Müller, Waltraud G.; Rieder, Dietmar; Kreth, Gregor; Cremer, Christoph; Trajanoski, Zlatko; McNally, James G.

2004-01-01

Knowledge of tertiary chromatin structure in mammalian interphase chromosomes is largely derived from artificial tandem arrays. In these model systems, light microscope images reveal fibers or beaded fibers after high-density targeting of transactivators to insertional domains spanning several megabases. These images of fibers have lent support to chromonema fiber models of tertiary structure. To assess the relevance of these studies to natural mammalian chromatin, we identified two different ∼400-kb regions on human chromosomes 6 and 22 and then examined light microscope images of interphase tertiary chromatin structure when the regions were transcriptionally active and inactive. When transcriptionally active, these natural chromosomal regions elongated, yielding images characterized by a series of adjacent puncta or “beads”, referred to hereafter as beaded images. These elongated structures required transcription for their maintenance. Thus, despite marked differences in the density and the mode of transactivation, the natural and artificial systems showed similarities, suggesting that beaded images are generic features of transcriptionally active tertiary chromatin. We show here, however, that these images do not necessarily favor chromonema fiber models but can also be explained by a radial-loop model or even a simple nucleosome affinity, random-chain model. Thus, light microscope images of tertiary structure cannot distinguish among competing models, although they do impose key constraints: chromatin must be clustered to yield beaded images and then packaged within each cluster to enable decondensation into adjacent clusters. PMID:15485905

Spectral-domain Optical Coherence Tomography in Manifest Glaucoma: Its Additive Role in Structural Diagnosis.

PubMed

Kim, Ko Eun; Oh, Sohee; Jeoung, Jin Wook; Suh, Min Hee; Seo, Je Hyun; Kim, Martha; Park, Ki Ho; Kim, Dong Myung; Kim, Seok Hwan

2016-11-01

To investigate the additive role of spectral-domain optical coherence tomography (SDOCT) in the structural diagnosis in glaucoma. Reliability and validity analysis. Structural examinations from 109 eyes of 109 healthy individuals and 151 eyes of 151 glaucoma patients with different severities were included. Four structural-diagnostic examination sets were prepared using stereo-optic disc photography (SDP), red-free retinal nerve fiber layer photography (RNFLP), and SDOCT: (1) SDP (S), (2) SDP and SDOCT (SO), (3) SDP and RNFLP (SR), and (4) SDP, RNFLP, and SDOCT (SRO). Five glaucoma specialists were instructed to classify subjects as normal or glaucoma using each of the 4 diagnostic sets in the order S, SO, SR, and SRO, with a 1-month interval. The interobserver agreement was evaluated using kappa (κ) statistics. The additive effect of SDOCT on the diagnostic performance of the specialists was evaluated using the generalized estimating equation. Five glaucoma specialists showed an excellent level of interobserver agreement on the diagnostic assessments based on the 4 sets. In the comparison of the collective diagnostic performance of the specialists, addition of SDOCT to SDP showed an approximately 2-fold significant increase in the diagnostic accuracy. Adding SDOCT to SDP significantly enhanced the specialists' structural-diagnostic ability with respect to the moderate glaucoma, though not mild or advanced glaucoma. SDOCT significantly enhanced the diagnostic accuracy of the glaucoma specialists' performance, showing its additive diagnostic value in judging glaucomatous structural damage, especially in the moderate stage of glaucoma. Copyright © 2016 Elsevier Inc. All rights reserved.

Embedding Carbon Fibre Structures in Metal Matrixes for Additive Manufacturing

NASA Astrophysics Data System (ADS)

Frostevarg, Jan; Robertson, Stephanie; Benavides, Vicente; Soldatov, Alexander

It is possible to reinforce structures and components using carbon fibres for applications in electronics and medicine, but most commonly used in reinforcing resin fibre composites for personal protection equipment and light weight constructions. Carbon fibres act as stress redistributors while having increased electrical and thermal conductivities. These properties could also be utilized in metal matrixes, if the fibres are properly fused to the metal and the structure remains intact. Another recently developed high potential carbon structure, carbon nanotube- (CNT) yarns, has similar but even greater mechanical properties than common carbon fibres. Via laser cladding, these reinforcing materials could be used in a plethora of applications, either locally (or globally) as surface treatments or as structural reinforcements using multi-layer laser cladding (additive manufacturing). The challenges of embedding carbon fibres or CNT-yarns in a CuAl mixture and SnPb solder wire using lasers are here investigated using high speed imaging and SEM. It is revealed that the carbon fibres have very high buoyancy in the molten metal and quickly degrades when irradiated by the laser. Wetting of the fibres is shown to be improved by a Tungsten coating and embedding of the structures after processing are evaluated using SEM and Raman spectroscopy.

Semantic data association for planar features in outdoor 6D-SLAM using lidar

NASA Astrophysics Data System (ADS)

Ulas, C.; Temeltas, H.

2013-05-01

Simultaneous Localization and Mapping (SLAM) is a fundamental problem of the autonomous systems in GPS (Global Navigation System) denied environments. The traditional probabilistic SLAM methods uses point features as landmarks and hold all the feature positions in their state vector in addition to the robot pose. The bottleneck of the point-feature based SLAM methods is the data association problem, which are mostly based on a statistical measure. The data association performance is very critical for a robust SLAM method since all the filtering strategies are applied after a known correspondence. For point-features, two different but very close landmarks in the same scene might be confused while giving the correspondence decision when their positions and error covariance matrix are solely taking into account. Instead of using the point features, planar features can be considered as an alternative landmark model in the SLAM problem to be able to provide a more consistent data association. Planes contain rich information for the solution of the data association problem and can be distinguished easily with respect to point features. In addition, planar maps are very compact since an environment has only very limited number of planar structures. The planar features does not have to be large structures like building wall or roofs; the small plane segments can also be used as landmarks like billboards, traffic posts and some part of the bridges in urban areas. In this paper, a probabilistic plane-feature extraction method from 3DLiDAR data and the data association based on the extracted semantic information of the planar features is introduced. The experimental results show that the semantic data association provides very satisfactory result in outdoor 6D-SLAM.

Tuning structure and mobility of solvation shells surrounding tracer additives.

PubMed

Carmer, James; Jain, Avni; Bollinger, Jonathan A; van Swol, Frank; Truskett, Thomas M

2015-03-28

Molecular dynamics simulations and a stochastic Fokker-Planck equation based approach are used to illuminate how position-dependent solvent mobility near one or more tracer particle(s) is affected when tracer-solvent interactions are rationally modified to affect corresponding solvation structure. For tracers in a dense hard-sphere fluid, we compare two types of tracer-solvent interactions: (1) a hard-sphere-like interaction, and (2) a soft repulsion extending beyond the hard core designed via statistical mechanical theory to enhance tracer mobility at infinite dilution by suppressing coordination-shell structure [Carmer et al., Soft Matter 8, 4083-4089 (2012)]. For the latter case, we show that the mobility of surrounding solvent particles is also increased by addition of the soft repulsive interaction, which helps to rationalize the mechanism underlying the tracer's enhanced diffusivity. However, if multiple tracer surfaces are in closer proximity (as at higher tracer concentrations), similar interactions that disrupt local solvation structure instead suppress the position-dependent solvent dynamics.

Asymmetric Michael Addition Mediated by Chiral Ionic Liquids.

PubMed

Suzuki, Yumiko

2018-06-01

Chiral ionic liquids with a focus on their applications in asymmetric Michael additions and related reactions were reviewed. The examples were classified on the basis of the mode of asymmetric induction (e.g., external induction/non-covalent interaction or internal induction/covalent bond formation), the roles in reactions (as a solvent or catalyst), and their structural features (e.g., imidazolium-based chiral cations, other chiral oniums; proline derivatives). Most of the reactions with high chiral induction are Michael addition of ketones or aldehydes to chalcones or nitrostyrenes where proline-derived chiral ionic liquids catalyze the reaction through enamine/ iminium formation. Many reports demonstrate the recyclability of ionic liquid-tagged pyrrolidines.

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…

The association between patella alta and the prevalence and worsening of structural features of patellofemoral joint osteoarthritis: The Multicenter Osteoarthritis Study

PubMed Central

Stefanik, J.J.; Zhu, Y.; Zumwalt, A.C.; Gross, K.D.; Clancy, M.; Lynch, J. A.; Frey Law, L.A.; Lewis, C.E.; Roemer, F.W.; Powers, C.M.; Guermazi, A.; Felson, D.T.

2010-01-01

Objective To examine the relationship between patella alta and the prevalence and worsening at follow-up of structural features of patellofemoral joint (PFJ) osteoarthritis (OA) on MRI. Methods The Multicenter Osteoarthritis (MOST) Study is a cohort study of persons aged 50-79 years with or at risk for knee OA. Patella alta was measured using the Insall-Salvati ratio (ISR) on the baseline lateral radiograph and cartilage damage, bone marrow lesions (BMLs), and subchondral bone attrition (SBA) were graded on MRI at baseline and at 30 months follow-up in the PFJ. We examined the association of the ISR with the prevalence and worsening of cartilage damage, BMLs, and SBA in the PFJ using logistic regression. Results 907 knees were studied (mean age 62, BMI 30, ISR 1.10), 63% from female subjects. Compared with knees in the lowest ISR quartile at baseline, those in the highest had 2.4 (95% CI 1.7, 3.3), 2.9 (2.0, 4.3), and 3.5 (2.3, 5.5) times the odds of having lateral PFJ cartilage damage, BMLs, and SBA respectively, and 1.5 (95% CI 1.1, 2.0), 1.3 (0.9, 1.8), and 2.2 (1.4, 3.4) times the odds of having medial PFJ cartilage damage, BMLs, and SBA respectively. Similarly, those with high ISRs were also at risk for worsening of cartilage damage and BMLs over time than those with low ISRs. Conclusion A high ISR, indicative of patella alta, is associated with structural features of OA in the PFJ. Additionally, the same knees have increased risk of worsening of these same features over time. PMID:20506169

The development of real-time stability supports visual working memory performance: Young children's feature binding can be improved through perceptual structure.

PubMed

Simmering, Vanessa R; Wood, Chelsey M

2017-08-01

Working memory is a basic cognitive process that predicts higher-level skills. A central question in theories of working memory development is the generality of the mechanisms proposed to explain improvements in performance. Prior theories have been closely tied to particular tasks and/or age groups, limiting their generalizability. The cognitive dynamics theory of visual working memory development has been proposed to overcome this limitation. From this perspective, developmental improvements arise through the coordination of cognitive processes to meet demands of different behavioral tasks. This notion is described as real-time stability, and can be probed through experiments that assess how changing task demands impact children's performance. The current studies test this account by probing visual working memory for colors and shapes in a change detection task that compares detection of changes to new features versus swaps in color-shape binding. In Experiment 1, 3- to 4-year-old children showed impairments specific to binding swaps, as predicted by decreased real-time stability early in development; 5- to 6-year-old children showed a slight advantage on binding swaps, but 7- to 8-year-old children and adults showed no difference across trial types. Experiment 2 tested the proposed explanation of young children's binding impairment through added perceptual structure, which supported the stability and precision of feature localization in memory-a process key to detecting binding swaps. This additional structure improved young children's binding swap detection, but not new-feature detection or adults' performance. These results provide further evidence for the cognitive dynamics and real-time stability explanation of visual working memory development. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Numerical Simulation of Flow Features and Energy Exchange Physics in Near-Wall Region with Fluid-Structure Interaction

NASA Astrophysics Data System (ADS)

Zhang, Lixiang; Wang, Wenquan; Guo, Yakun

Large eddy simulation is used to explore flow features and energy exchange physics between turbulent flow and structure vibration in the near-wall region with fluid-structure interaction (FSI). The statistical turbulence characteristics in the near-wall region of a vibrating wall, such as the skin frictional coefficient, velocity, pressure, vortices, and the coherent structures have been studied for an aerofoil blade passage of a true three-dimensional hydroturbine. The results show that (i) FSI greatly strengthens the turbulence in the inner region of y+ < 25; and (ii) the energy exchange mechanism between the flow and the vibration depends strongly on the vibration-induced vorticity in the inner region. The structural vibration provokes a frequent action between the low- and high-speed streaks to balance the energy deficit caused by the vibration. The velocity profile in the inner layer near the vibrating wall has a significant distinctness, and the viscosity effect of the fluid in the inner region decreases due to the vibration. The flow features in the inner layer are altered by a suitable wall vibration.

Feature Inference and the Causal Structure of Categories

ERIC Educational Resources Information Center

Rehder, B.; Burnett, R.C.

2005-01-01

The purpose of this article was to establish how theoretical category knowledge-specifically, knowledge of the causal relations that link the features of categories-supports the ability to infer the presence of unobserved features. Our experiments were designed to test proposals that causal knowledge is represented psychologically as Bayesian…

Optimal design of high damping force engine mount featuring MR valve structure with both annular and radial flow paths

NASA Astrophysics Data System (ADS)

Nguyen, Q. H.; Choi, S. B.; Lee, Y. S.; Han, M. S.

2013-11-01

This paper focuses on the optimal design of a compact and high damping force engine mount featuring magnetorheological fluid (MRF). In the mount, a MR valve structure with both annular and radial flows is employed to generate a high damping force. First, the configuration and working principle of the proposed MR mount is introduced. The MRF flows in the mount are then analyzed and the governing equations of the MR mount are derived based on the Bingham plastic behavior of the MRF. An optimal design of the MR mount is then performed to find the optimal structure of the MR valve to generate a maximum damping force with certain design constraints. In addition, the gap size of MRF ducts is empirically chosen considering the ‘lockup’ problem of the mount at high frequency. Performance of the optimized MR mount is then evaluated based on finite element analysis and discussions on performance results of the optimized MR mount are given. The effectiveness of the proposed MR engine mount is demonstrated via computer simulation by presenting damping force and power consumption.

Studies on sintering additives for hydroxyapatite, and controlled porosity structures of calcium aluminates and polypropylene-tricalcium phosphate for bone graft applications

NASA Astrophysics Data System (ADS)

Kalita, Samar Jyoti

Tissue engineering has made a significant contribution in developing new biomaterials that can restore the structural features and physiological functions of natural tissues. Various materials, such as metals, ceramics, polymers and composites have been developed for their use in hard tissue engineering applications. Part A of this thesis describes my research on HAp ceramics. HAp, a bioactive ceramic, is known for its osteoconductivity, but shows poor mechanical performance. This program aimed at improving mechanical performance of synthetic HAp by introducing small quantities of various sintering additives. A range of oxide-based sintering additives were selected and prepared. Dense compacts were prepared using a uniaxial press with an average green density of 1.6 g/cc. Results showed that some of these sintering additives improved densification, hardness and compression strength of synthetic HAp compared to the pure composition. A maximum bulk density of 3.06 g/cc was achieved for 2.5 wt% addition of MgO. A Microhardness of 4.9 GPa (505 HV) was measured for 2.5 wt% addition of BaO, and the highest compression strength (220MPa) was reported for 2.5 wt% addition of CaO. Cytotoxicity and cell proliferation studies with a modified human osteoblast (HOB) cell-line (OPC1) proved most of these materials non-toxic and biocompatible. Microscopic observation revealed that bone cells were attached and grew well on most of these ceramic matrices. Part B describes my work on development of controlled porosity polypropylene-tricalcium phosphate composite scaffolds via the fused deposition modeling (FDM) process. Hg-porosimetry was performed to determine pore size and their distribution. Uniaxial compression testing performed on samples with 36 vol% porosity and pore size of 160 mum showed the best compressive strength of 12.7 MPa. Part C includes my research on development of "3-D honeycomb" porous calcium aluminate structures via the indirect FDM process. Samples of 29% and

Automated identification of protein-ligand interaction features using Inductive Logic Programming: a hexose binding case study.

PubMed

A Santos, Jose C; Nassif, Houssam; Page, David; Muggleton, Stephen H; E Sternberg, Michael J

2012-07-11

There is a need for automated methods to learn general features of the interactions of a ligand class with its diverse set of protein receptors. An appropriate machine learning approach is Inductive Logic Programming (ILP), which automatically generates comprehensible rules in addition to prediction. The development of ILP systems which can learn rules of the complexity required for studies on protein structure remains a challenge. In this work we use a new ILP system, ProGolem, and demonstrate its performance on learning features of hexose-protein interactions. The rules induced by ProGolem detect interactions mediated by aromatics and by planar-polar residues, in addition to less common features such as the aromatic sandwich. The rules also reveal a previously unreported dependency for residues cys and leu. They also specify interactions involving aromatic and hydrogen bonding residues. This paper shows that Inductive Logic Programming implemented in ProGolem can derive rules giving structural features of protein/ligand interactions. Several of these rules are consistent with descriptions in the literature. In addition to confirming literature results, ProGolem's model has a 10-fold cross-validated predictive accuracy that is superior, at the 95% confidence level, to another ILP system previously used to study protein/hexose interactions and is comparable with state-of-the-art statistical learners.

Diamond field emitter array cathodes and possibilities of employing additive manufacturing for dielectric laser accelerating structures

NASA Astrophysics Data System (ADS)

Simakov, Evgenya I.; Andrews, Heather L.; Herman, Matthew J.; Hubbard, Kevin M.; Weis, Eric

2017-03-01

Demonstration of a stand-alone practical dielectric laser accelerator (DLA) requires innovation in two major critical components: high-current ultra-low-emittance cathodes and efficient laser accelerator structures. LANL develops two technologies that in our opinion are applicable to the novel DLA architectures: diamond field emitter array (DFEA) cathodes and additive manufacturing of photonic band-gap (PBG) structures. This paper discusses the results of testing of DFEA cathodes in the field-emission regime and the possibilities for their operation in the photoemission regime, and compares their emission characteristics to the specific needs of DLAs. We also describe recent advances in additive manufacturing of dielectric woodpile structures using a Nanoscribe direct laser-writing device capable of maskless lithography and additive manufacturing, and the development of novel infrared dielectric materials compatible with additive manufacturing.

New Nomenclatures for Heat Treatments of Additively Manufactured Titanium Alloys

NASA Astrophysics Data System (ADS)

Baker, Andrew H.; Collins, Peter C.; Williams, James C.

2017-07-01

The heat-treatment designations and microstructure nomenclatures for many structural metallic alloys were established for traditional metals processing, such as casting, hot rolling or forging. These terms do not necessarily apply for additively manufactured (i.e., three-dimensionally printed or "3D printed") metallic structures. The heat-treatment terminology for titanium alloys generally implies the heat-treatment temperatures and their sequence relative to a thermomechanical processing step (e.g., forging, rolling). These designations include: β-processing, α + β-processing, β-annealing, duplex annealing and mill annealing. Owing to the absence of a thermomechanical processing step, these traditional designations can pose a problem when titanium alloys are first produced via additive manufacturing, and then heat-treated. This communication proposes new nomenclatures for heat treatments of additively manufactured titanium alloys, and uses the distinct microstructural features to provide a correlation between traditional nomenclature and the proposed nomenclature.

Structural Color for Additive Manufacturing: 3D-Printed Photonic Crystals from Block Copolymers.

PubMed

Boyle, Bret M; French, Tracy A; Pearson, Ryan M; McCarthy, Blaine G; Miyake, Garret M

2017-03-28

The incorporation of structural color into 3D printed parts is reported, presenting an alternative to the need for pigments or dyes for colored parts produced through additive manufacturing. Thermoplastic build materials composed of dendritic block copolymers were designed, synthesized, and used to additively manufacture plastic parts exhibiting structural color. The reflection properties of the photonic crystals arise from the periodic nanostructure formed through block copolymer self-assembly during polymer processing. The wavelength of reflected light could be tuned across the visible spectrum by synthetically controlling the block copolymer molecular weight and manufacture parts that reflected violet, green, or orange light with the capacity to serve as selective optical filters and light guides.

Role of strongly interacting additives in tuning the structure and properties of polymer systems

NASA Astrophysics Data System (ADS)

Daga, Vikram Kumar

Block copolymer (BCP) nanocomposites are an important class of hybrid materials in which the BCP guides the spatial location and the periodic assembly of the additives. High loadings of well-dispersed nanofillers are generally important for many applications including mechanical reinforcing of polymers. In particular the composites shown in this work might find use as etch masks in nanolithography, or for enabling various phase selective reactions for new materials development. This work explores the use of hydrogen bonding interactions between various additives (such as homopolymers and non-polymeric additives) and small, disordered BCPs to cause the formation of well-ordered morphologies with small domains. A detailed study of the organization of homopolymer chains and the evolution of structure during the process of ordering is performed. The results demonstrate that by tuning the selective interaction of the additive with the incorporating phase of the BCP, composites with significantly high loadings of additives can be formed while maintaining order in the BCP morphology. The possibility of high and selective loading of additives in one of the phases of the ordered BCP composite opens new avenues due to high degree of functionalization and the proximity of the additives within the incorporating phase. This aspect is utilized in one case for the formation of a network structure between adjoining additive cores to derive mesoporous inorganic materials with their structures templated by the BCP. The concept of additive-driven assembly is extended to formulate BCPadditive blends with an ability to undergo photo-induced ordering. Underlying this strategy is the ability to transition a weakly interacting additive to its strongly interacting form. This strategy provides an on-demand, non-intrusive route for formation of well-ordered nanostructures in arbitrarily defined regions of an otherwise disordered material. The second area explored in this dissertation deals

Additive Manufacturing of Metal Structures at the Micrometer Scale.

PubMed

Hirt, Luca; Reiser, Alain; Spolenak, Ralph; Zambelli, Tomaso

2017-05-01

Currently, the focus of additive manufacturing (AM) is shifting from simple prototyping to actual production. One driving factor of this process is the ability of AM to build geometries that are not accessible by subtractive fabrication techniques. While these techniques often call for a geometry that is easiest to manufacture, AM enables the geometry required for best performance to be built by freeing the design process from restrictions imposed by traditional machining. At the micrometer scale, the design limitations of standard fabrication techniques are even more severe. Microscale AM thus holds great potential, as confirmed by the rapid success of commercial micro-stereolithography tools as an enabling technology for a broad range of scientific applications. For metals, however, there is still no established AM solution at small scales. To tackle the limited resolution of standard metal AM methods (a few tens of micrometers at best), various new techniques aimed at the micrometer scale and below are presently under development. Here, we review these recent efforts. Specifically, we feature the techniques of direct ink writing, electrohydrodynamic printing, laser-assisted electrophoretic deposition, laser-induced forward transfer, local electroplating methods, laser-induced photoreduction and focused electron or ion beam induced deposition. Although these methods have proven to facilitate the AM of metals with feature sizes in the range of 0.1-10 µm, they are still in a prototype stage and their potential is not fully explored yet. For instance, comprehensive studies of material availability and material properties are often lacking, yet compulsory for actual applications. We address these items while critically discussing and comparing the potential of current microscale metal AM techniques. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Structural features, substrate specificity, kinetic properties of insect α-amylase and specificity of plant α-amylase inhibitors.

PubMed

Kaur, Rimaljeet; Kaur, Narinder; Gupta, Anil Kumar

2014-11-01

α-Amylase is an important digestive enzyme required for the optimal growth and development of insects. Several insect α-amylases had been purified and their physical and chemical properties were characterized. Insect α-amylases of different orders display variability in structure, properties and substrate specificity. Such diverse properties of amylases could be due to different feeding habits and gut environment of insects. In this review, structural features and properties of several insect α-amylases were compared. This could be helpful in exploring the diversity in characteristics of α-amylase between the members of the same class (insecta). Properties like pH optima are reflected in enzyme structural features. In plants, α-amylase inhibitors (α-AIs) occur as part of natural defense mechanisms against pests by interfering in their digestion process and thus could also provide access to new pest management strategies. AIs are quite specific in their action; therefore, these could be employed according to their effectiveness against target amylases. Potential of transgenics with α-AIs has also been discussed for insect resistance and controlling infestation. The differences in structural features of insect α-amylases provided reasons for their efficient functioning at different pH and the specificity towards various substrates. Various proteinaceous and non-proteinaceous inhibitors discussed could be helpful in controlling pest infestation. In depth detailed studies are required on proteinaceous α-AI-α-amylase interaction at different pH's as well as the insect proteinase action on these inhibitors before selecting the α-AI for making transgenics resistant to particular insect. Copyright © 2014 Elsevier Inc. All rights reserved.

JCE Feature Columns

NASA Astrophysics Data System (ADS)

Holmes, Jon L.

1999-05-01

The Features area of JCE Online is now readily accessible through a single click from our home page. In the Features area each column is linked to its own home page. These column home pages also have links to them from the online Journal Table of Contents pages or from any article published as part of that feature column. Using these links you can easily find abstracts of additional articles that are related by topic. Of course, JCE Online+ subscribers are then just one click away from the entire article. Finding related articles is easy because each feature column "site" contains links to the online abstracts of all the articles that have appeared in the column. In addition, you can find the mission statement for the column and the email link to the column editor that I mentioned above. At the discretion of its editor, a feature column site may contain additional resources. As an example, the Chemical Information Instructor column edited by Arleen Somerville will have a periodically updated bibliography of resources for teaching and using chemical information. Due to the increase in the number of these resources available on the WWW, it only makes sense to publish this information online so that you can get to these resources with a simple click of the mouse. We expect that there will soon be additional information and resources at several other feature column sites. Following in the footsteps of the Chemical Information Instructor, up-to-date bibliographies and links to related online resources can be made available. We hope to extend the online component of our feature columns with moderated online discussion forums. If you have a suggestion for an online resource you would like to see included, let the feature editor or JCE Online (jceonline@chem.wisc.edu) know about it. JCE Internet Features JCE Internet also has several feature columns: Chemical Education Resource Shelf, Conceptual Questions and Challenge Problems, Equipment Buyers Guide, Hal's Picks, Mathcad

Atomic Structure of GRK5 Reveals Distinct Structural Features Novel for G Protein-coupled Receptor Kinases.

PubMed

Komolov, Konstantin E; Bhardwaj, Anshul; Benovic, Jeffrey L

2015-08-21

G protein-coupled receptor kinases (GRKs) are members of the protein kinase A, G, and C families (AGC) and play a central role in mediating G protein-coupled receptor phosphorylation and desensitization. One member of the family, GRK5, has been implicated in several human pathologies, including heart failure, hypertension, cancer, diabetes, and Alzheimer disease. To gain mechanistic insight into GRK5 function, we determined a crystal structure of full-length human GRK5 at 1.8 Å resolution. GRK5 in complex with the ATP analog 5'-adenylyl β,γ-imidodiphosphate or the nucleoside sangivamycin crystallized as a monomer. The C-terminal tail (C-tail) of AGC kinase domains is a highly conserved feature that is divided into three segments as follows: the C-lobe tether, the active-site tether (AST), and the N-lobe tether (NLT). This domain is fully resolved in GRK5 and reveals novel interactions with the nucleotide and N-lobe. Similar to other AGC kinases, the GRK5 AST is an integral part of the nucleotide-binding pocket, a feature not observed in other GRKs. The AST also mediates contact between the kinase N- and C-lobes facilitating closure of the kinase domain. The GRK5 NLT is largely displaced from its previously observed position in other GRKs. Moreover, although the autophosphorylation sites in the NLT are >20 Å away from the catalytic cleft, they are capable of rapid cis-autophosphorylation suggesting high mobility of this region. In summary, we provide a snapshot of GRK5 in a partially closed state, where structural elements of the kinase domain C-tail are aligned to form novel interactions to the nucleotide and N-lobe not previously observed in other GRKs. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Tuning structure and mobility of solvation shells surrounding tracer additives

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

Carmer, James; Jain, Avni; Bollinger, Jonathan A.

2015-03-28

Molecular dynamics simulations and a stochastic Fokker-Planck equation based approach are used to illuminate how position-dependent solvent mobility near one or more tracer particle(s) is affected when tracer-solvent interactions are rationally modified to affect corresponding solvation structure. For tracers in a dense hard-sphere fluid, we compare two types of tracer-solvent interactions: (1) a hard-sphere-like interaction, and (2) a soft repulsion extending beyond the hard core designed via statistical mechanical theory to enhance tracer mobility at infinite dilution by suppressing coordination-shell structure [Carmer et al., Soft Matter 8, 4083–4089 (2012)]. For the latter case, we show that the mobility of surroundingmore » solvent particles is also increased by addition of the soft repulsive interaction, which helps to rationalize the mechanism underlying the tracer’s enhanced diffusivity. However, if multiple tracer surfaces are in closer proximity (as at higher tracer concentrations), similar interactions that disrupt local solvation structure instead suppress the position-dependent solvent dynamics.« less

Morphologic features of basal cell carcinoma using the en-face mode in frequency domain optical coherence tomography.

PubMed

von Braunmühl, T; Hartmann, D; Tietze, J K; Cekovic, D; Kunte, C; Ruzicka, T; Berking, C; Sattler, E C

2016-11-01

Optical coherence tomography (OCT) has become a valuable non-invasive tool in the in vivo diagnosis of non-melanoma skin cancer, especially of basal cell carcinoma (BCC). Due to an updated software-supported algorithm, a new en-face mode - similar to the horizontal en-face mode in high-definition OCT and reflectance confocal microscopy - surface-parallel imaging is possible which, in combination with the established slice mode of frequency domain (FD-)OCT, may offer additional information in the diagnosis of BCC. To define characteristic morphologic features of BCC using the new en-face mode in addition to the conventional cross-sectional imaging mode for three-dimensional imaging of BCC in FD-OCT. A total of 33 BCC were examined preoperatively by imaging in en-face mode as well as cross-sectional mode in FD-OCT. Characteristic features were evaluated and correlated with histopathology findings. Features established in the cross-sectional imaging mode as well as additional features were present in the en-face mode of FD-OCT: lobulated structures (100%), dark peritumoral rim (75%), bright peritumoral stroma (96%), branching vessels (90%), compressed fibrous bundles between lobulated nests ('star shaped') (78%), and intranodular small bright dots (51%). These features were also evaluated according to the histopathological subtype. In the en-face mode, the lobulated structures with compressed fibrous bundles of the BCC were more distinct than in the slice mode. FD-OCT with a new depiction for horizontal and vertical imaging modes offers additional information in the diagnosis of BCC, especially in nodular BCC, and enhances the possibility of the evaluation of morphologic tumour features. © 2016 European Academy of Dermatology and Venereology.

Effects of Spatial and Feature Attention on Disparity-Rendered Structure-From-Motion Stimuli in the Human Visual Cortex

PubMed Central

Ip, Ifan Betina; Bridge, Holly; Parker, Andrew J.

2014-01-01

An important advance in the study of visual attention has been the identification of a non-spatial component of attention that enhances the response to similar features or objects across the visual field. Here we test whether this non-spatial component can co-select individual features that are perceptually bound into a coherent object. We combined human psychophysics and functional magnetic resonance imaging (fMRI) to demonstrate the ability to co-select individual features from perceptually coherent objects. Our study used binocular disparity and visual motion to define disparity structure-from-motion (dSFM) stimuli. Although the spatial attention system induced strong modulations of the fMRI response in visual regions, the non-spatial system’s ability to co-select features of the dSFM stimulus was less pronounced and variable across subjects. Our results demonstrate that feature and global feature attention effects are variable across participants, suggesting that the feature attention system may be limited in its ability to automatically select features within the attended object. Careful comparison of the task design suggests that even minor differences in the perceptual task may be critical in revealing the presence of global feature attention. PMID:24936974

Identification of DNA-Binding Proteins Using Mixed Feature Representation Methods.

PubMed

Qu, Kaiyang; Han, Ke; Wu, Song; Wang, Guohua; Wei, Leyi

2017-09-22

DNA-binding proteins play vital roles in cellular processes, such as DNA packaging, replication, transcription, regulation, and other DNA-associated activities. The current main prediction method is based on machine learning, and its accuracy mainly depends on the features extraction method. Therefore, using an efficient feature representation method is important to enhance the classification accuracy. However, existing feature representation methods cannot efficiently distinguish DNA-binding proteins from non-DNA-binding proteins. In this paper, a multi-feature representation method, which combines three feature representation methods, namely, K-Skip-N-Grams, Information theory, and Sequential and structural features (SSF), is used to represent the protein sequences and improve feature representation ability. In addition, the classifier is a support vector machine. The mixed-feature representation method is evaluated using 10-fold cross-validation and a test set. Feature vectors, which are obtained from a combination of three feature extractions, show the best performance in 10-fold cross-validation both under non-dimensional reduction and dimensional reduction by max-relevance-max-distance. Moreover, the reduced mixed feature method performs better than the non-reduced mixed feature technique. The feature vectors, which are a combination of SSF and K-Skip-N-Grams, show the best performance in the test set. Among these methods, mixed features exhibit superiority over the single features.

Asymmetric Michael Addition Mediated by Chiral Ionic Liquids

PubMed Central

Suzuki, Yumiko

2018-01-01

Chiral ionic liquids with a focus on their applications in asymmetric Michael additions and related reactions were reviewed. The examples were classified on the basis of the mode of asymmetric induction (e.g., external induction/non-covalent interaction or internal induction/covalent bond formation), the roles in reactions (as a solvent or catalyst), and their structural features (e.g., imidazolium-based chiral cations, other chiral oniums; proline derivatives). Most of the reactions with high chiral induction are Michael addition of ketones or aldehydes to chalcones or nitrostyrenes where proline-derived chiral ionic liquids catalyze the reaction through enamine/ iminium formation. Many reports demonstrate the recyclability of ionic liquid-tagged pyrrolidines. PMID:29861702

A Comparison of Supervised Machine Learning Algorithms and Feature Vectors for MS Lesion Segmentation Using Multimodal Structural MRI

PubMed Central

Sweeney, Elizabeth M.; Vogelstein, Joshua T.; Cuzzocreo, Jennifer L.; Calabresi, Peter A.; Reich, Daniel S.; Crainiceanu, Ciprian M.; Shinohara, Russell T.

2014-01-01

Machine learning is a popular method for mining and analyzing large collections of medical data. We focus on a particular problem from medical research, supervised multiple sclerosis (MS) lesion segmentation in structural magnetic resonance imaging (MRI). We examine the extent to which the choice of machine learning or classification algorithm and feature extraction function impacts the performance of lesion segmentation methods. As quantitative measures derived from structural MRI are important clinical tools for research into the pathophysiology and natural history of MS, the development of automated lesion segmentation methods is an active research field. Yet, little is known about what drives performance of these methods. We evaluate the performance of automated MS lesion segmentation methods, which consist of a supervised classification algorithm composed with a feature extraction function. These feature extraction functions act on the observed T1-weighted (T1-w), T2-weighted (T2-w) and fluid-attenuated inversion recovery (FLAIR) MRI voxel intensities. Each MRI study has a manual lesion segmentation that we use to train and validate the supervised classification algorithms. Our main finding is that the differences in predictive performance are due more to differences in the feature vectors, rather than the machine learning or classification algorithms. Features that incorporate information from neighboring voxels in the brain were found to increase performance substantially. For lesion segmentation, we conclude that it is better to use simple, interpretable, and fast algorithms, such as logistic regression, linear discriminant analysis, and quadratic discriminant analysis, and to develop the features to improve performance. PMID:24781953

A comparison of supervised machine learning algorithms and feature vectors for MS lesion segmentation using multimodal structural MRI.

PubMed

Sweeney, Elizabeth M; Vogelstein, Joshua T; Cuzzocreo, Jennifer L; Calabresi, Peter A; Reich, Daniel S; Crainiceanu, Ciprian M; Shinohara, Russell T

2014-01-01

Machine learning is a popular method for mining and analyzing large collections of medical data. We focus on a particular problem from medical research, supervised multiple sclerosis (MS) lesion segmentation in structural magnetic resonance imaging (MRI). We examine the extent to which the choice of machine learning or classification algorithm and feature extraction function impacts the performance of lesion segmentation methods. As quantitative measures derived from structural MRI are important clinical tools for research into the pathophysiology and natural history of MS, the development of automated lesion segmentation methods is an active research field. Yet, little is known about what drives performance of these methods. We evaluate the performance of automated MS lesion segmentation methods, which consist of a supervised classification algorithm composed with a feature extraction function. These feature extraction functions act on the observed T1-weighted (T1-w), T2-weighted (T2-w) and fluid-attenuated inversion recovery (FLAIR) MRI voxel intensities. Each MRI study has a manual lesion segmentation that we use to train and validate the supervised classification algorithms. Our main finding is that the differences in predictive performance are due more to differences in the feature vectors, rather than the machine learning or classification algorithms. Features that incorporate information from neighboring voxels in the brain were found to increase performance substantially. For lesion segmentation, we conclude that it is better to use simple, interpretable, and fast algorithms, such as logistic regression, linear discriminant analysis, and quadratic discriminant analysis, and to develop the features to improve performance.

The Function of Embryonic Stem Cell-expressed RAS (E-RAS), a Unique RAS Family Member, Correlates with Its Additional Motifs and Its Structural Properties.

PubMed

Nakhaei-Rad, Saeideh; Nakhaeizadeh, Hossein; Kordes, Claus; Cirstea, Ion C; Schmick, Malte; Dvorsky, Radovan; Bastiaens, Philippe I H; Häussinger, Dieter; Ahmadian, Mohammad Reza

2015-06-19

E-RAS is a member of the RAS family specifically expressed in embryonic stem cells, gastric tumors, and hepatic stellate cells. Unlike classical RAS isoforms (H-, N-, and K-RAS4B), E-RAS has, in addition to striking and remarkable sequence deviations, an extended 38-amino acid-long unique N-terminal region with still unknown functions. We investigated the molecular mechanism of E-RAS regulation and function with respect to its sequence and structural features. We found that N-terminal extension of E-RAS is important for E-RAS signaling activity. E-RAS protein most remarkably revealed a different mode of effector interaction as compared with H-RAS, which correlates with deviations in the effector-binding site of E-RAS. Of all these residues, tryptophan 79 (arginine 41 in H-RAS), in the interswitch region, modulates the effector selectivity of RAS proteins from H-RAS to E-RAS features. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Structural features of soluble cereal arabinoxylan fibers associated with a slow rate of in vitro fermentation by human fecal microbiota.

PubMed

Rumpagaporn, Pinthip; Reuhs, Brad L; Kaur, Amandeep; Patterson, John A; Keshavarzian, Ali; Hamaker, Bruce R

2015-10-05

Most soluble dietary fibers ferment rapidly in the proximal colon, potentially causing discomfort and poor tolerability. Alkali-extracted arabinoxylan isolates from corn, wheat, rice and sorghum brans were prepared, through hydrolysis (except sorghum) and ethanol fractionation, to have a broad range of initial fermentation rates, and their linkage patterns were determined to understand structural aspects related to slow fermentation rate. They were all highly branched polymers with degree of substitution greater than 64%. There was no relationship of molecular mass, arabinose:xylose ratio, or degree of substitution to fermentation rate patterns. Slow fermenting wheat and corn arabinoxylans had much higher amount of terminal xylose in branches than fast fermenting rice and sorghum arabinoxylans. The slowest fermenting wheat arabinoxylan additionally contained a complex trisaccharide side chain with two arabinoses linked at the O-2 and O-3 positions of an arabinose that is O-2 linked to the xylan backbone. Structural features were proposed for tolerable slowly fermentable arabinoxylan with possible beneficial fermentation function into the distal colon. Copyright © 2015 Elsevier Ltd. All rights reserved.

Structure Property Studies for Additively Manufactured Parts

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

Milenski, Helen M; Schmalzer, Andrew Michael; Kelly, Daniel

2015-08-17

Since the invention of modern Additive Manufacturing (AM) processes engineers and designers have worked hard to capitalize on the unique building capabilities that AM allows. By being able to customize the interior fill of parts it is now possible to design components with a controlled density and customized internal structure. The creation of new polymers and polymer composites allow for even greater control over the mechanical properties of AM parts. One of the key reasons to explore AM, is to bring about a new paradigm in part design, where materials can be strategically optimized in a way that conventional subtractivemore » methods cannot achieve. The two processes investigated in my research were the Fused Deposition Modeling (FDM) process and the Direct Ink Write (DIW) process. The objectives of the research were to determine the impact of in-fill density and morphology on the mechanical properties of FDM parts, and to determine if DIW printed samples could be produced where the filament diameter was varied while the overall density remained constant.« less

Supplementary Microstructural Features Induced During Laser Surface Melting of Thermally Sprayed Inconel 625 Coatings

NASA Astrophysics Data System (ADS)

Ahmed, Nauman; Voisey, K. T.; McCartney, D. G.

2014-02-01

Laser surface melting of thermally sprayed coatings has the potential to enhance their corrosion properties by incorporating favorable microstructural changes. Besides homogenizing the as-sprayed structure, laser melting may induce certain microstructural modifications (i.e., supplementary features) in addition to those that directly improve the corrosion performance. Such features, being a direct result of the laser treatment process, are described in this paper which is part of a broader study in which high velocity oxy-fuel sprayed Inconel 625 coatings on mild-steel substrates were treated with a diode laser and the modified microstructure characterized using optical and scanning electron microscopy and x-ray diffraction. The laser treated coating features several different zones, including a region with a microstructure in which there is a continuous columnar dendritic structure through a network of retained oxide stringers.

Effect of mineral additives on structure and properties of concrete for pavements

NASA Astrophysics Data System (ADS)

Sobol, Khrystyna; Markiv, Taras; Hunyak, Oleksii

2017-12-01

Concrete pavements is an attractive alternative to asphalt pavements because of its lower cost and higher durability. Major contribution to sustainable development can be made by partial replacement of cement in concrete pavement with supplementary cementitious materials of different nature and origin. In this paper, the effect of natural zeolite and perlite additives in complex with chemical admixtures on the structure and properties of concrete for pavement was studied. Compressive and flexural strength test was used to study the mechanical behavior of designed concrete under load. Generally, the compressive strength of both control concrete and concrete containing mineral additives levels at the later ages of hardening. The microstructure analysis of concrete with mineral additives of different nature activity showed the formation of additional amount of hydration products such as tobermorite type calcium hydrosilicate which provide self-reinforcement of hardening concrete system.

iPHLoc-ES: Identification of bacteriophage protein locations using evolutionary and structural features.

PubMed

Shatabda, Swakkhar; Saha, Sanjay; Sharma, Alok; Dehzangi, Abdollah

2017-12-21

Bacteriophage proteins are viruses that can significantly impact on the functioning of bacteria and can be used in phage based therapy. The functioning of Bacteriophage in the host bacteria depends on its location in those host cells. It is very important to know the subcellular location of the phage proteins in a host cell in order to understand their working mechanism. In this paper, we propose iPHLoc-ES, a prediction method for subcellular localization of bacteriophage proteins. We aim to solve two problems: discriminating between host located and non-host located phage proteins and discriminating between the locations of host located protein in a host cell (membrane or cytoplasm). To do this, we extract sets of evolutionary and structural features of phage protein and employ Support Vector Machine (SVM) as our classifier. We also use recursive feature elimination (RFE) to reduce the number of features for effective prediction. On standard dataset using standard evaluation criteria, our method significantly outperforms the state-of-the-art predictor. iPHLoc-ES is readily available to use as a standalone tool from: https://github.com/swakkhar/iPHLoc-ES/ and as a web application from: http://brl.uiu.ac.bd/iPHLoc-ES/. Copyright © 2017 Elsevier Ltd. All rights reserved.

Generation of the first structure-based pharmacophore model containing a selective "zinc binding group" feature to identify potential glyoxalase-1 inhibitors.

PubMed

Al-Balas, Qosay; Hassan, Mohammad; Al-Oudat, Buthina; Alzoubi, Hassan; Mhaidat, Nizar; Almaaytah, Ammar

2012-11-22

Within this study, a unique 3D structure-based pharmacophore model of the enzyme glyoxalase-1 (Glo-1) has been revealed. Glo-1 is considered a zinc metalloenzyme in which the inhibitor binding with zinc atom at the active site is crucial. To our knowledge, this is the first pharmacophore model that has a selective feature for a "zinc binding group" which has been customized within the structure-based pharmacophore model of Glo-1 to extract ligands that possess functional groups able to bind zinc atom solely from database screening. In addition, an extensive 2D similarity search using three diverse similarity techniques (Tanimoto, Dice, Cosine) has been performed over the commercially available "Zinc Clean Drug-Like Database" that contains around 10 million compounds to help find suitable inhibitors for this enzyme based on known inhibitors from the literature. The resultant hits were mapped over the structure based pharmacophore and the successful hits were further docked using three docking programs with different pose fitting and scoring techniques (GOLD, LibDock, CDOCKER). Nine candidates were suggested to be novel Glo-1 inhibitors containing the "zinc binding group" with the highest consensus scoring from docking.

Automated identification of protein-ligand interaction features using Inductive Logic Programming: a hexose binding case study

PubMed Central

2012-01-01

Background There is a need for automated methods to learn general features of the interactions of a ligand class with its diverse set of protein receptors. An appropriate machine learning approach is Inductive Logic Programming (ILP), which automatically generates comprehensible rules in addition to prediction. The development of ILP systems which can learn rules of the complexity required for studies on protein structure remains a challenge. In this work we use a new ILP system, ProGolem, and demonstrate its performance on learning features of hexose-protein interactions. Results The rules induced by ProGolem detect interactions mediated by aromatics and by planar-polar residues, in addition to less common features such as the aromatic sandwich. The rules also reveal a previously unreported dependency for residues cys and leu. They also specify interactions involving aromatic and hydrogen bonding residues. This paper shows that Inductive Logic Programming implemented in ProGolem can derive rules giving structural features of protein/ligand interactions. Several of these rules are consistent with descriptions in the literature. Conclusions In addition to confirming literature results, ProGolem’s model has a 10-fold cross-validated predictive accuracy that is superior, at the 95% confidence level, to another ILP system previously used to study protein/hexose interactions and is comparable with state-of-the-art statistical learners. PMID:22783946

Structural features of northern Tarim basin: Implications for regional tectonics and petroleum traps

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

Dong Jia; Juafu Lu; Dongsheng Cai

1998-01-01

The rhombus-shaped Tarim basin in northwestern China is controlled mainly by two left-lateral strike-slip systems: the northeast-trending Altun fault zone along its southeastern side and the northeast-trending Aheqi fault zone along its northwestern side. In this paper, we discuss the northern Tarim basin`s structural features, which include three main tectonic units: the Kalpin uplift, the Kuqa depression, and the North Tarim uplift along the northern margin of the Tarim basin. Structural mapping in the Kalpin uplift shows that a series of imbricated thrust sheets have been overprinted by strike-slip faulting. The amount of strike-slip displacement is estimated to be 148more » km by restoration of strike-slip structures in the uplift. The Kuqa depression is a Mesozoic-Cenozoic foredeep depression with well-developed flat-ramp structures and fault-related folds. The Baicheng basin, a Quaternary pull-apart basin, developed at the center of the Kuqa depression. Subsurface structures in the North Tarim uplift can be divided into the Mesozoic-Cenozoic and the Paleozoic lithotectonic sequences in seismic profiles. The Paleozoic litho-tectonic sequence exhibits the interference of earlier left-lateral and later right-lateral strike-slip structures. Many normal faults in the Mesozoic-Cenozoic litho-tectonic sequence form the negative flower structures in the North Tarim uplift; these structures commonly directly overlie the positive flower structures in the Paleozoic litho-tectonic sequence. The interference regions of the northwest-trending and northeast-trending folds in the Paleozoic tectonic sequence have been identified to have the best trap structures. Our structural analysis indicates that the Tarim basin is a transpressional foreland basin rejuvenated during the Cenozoic.« less

Feature Inference Learning and Eyetracking

ERIC Educational Resources Information Center

Rehder, Bob; Colner, Robert M.; Hoffman, Aaron B.

2009-01-01

Besides traditional supervised classification learning, people can learn categories by inferring the missing features of category members. It has been proposed that feature inference learning promotes learning a category's internal structure (e.g., its typical features and interfeature correlations) whereas classification promotes the learning of…

Structural and functional features of lysine acetylation of plant and animal tubulins.

PubMed

Rayevsky, Alexey V; Sharifi, Mohsen; Samofalova, Dariya A; Karpov, Pavel A; Blume, Yaroslav B

2017-10-10

The study of the genome and the proteome of different species and representatives of distinct kingdoms, especially detection of proteome via wide-scaled analyses has various challenges and pitfalls. Attempts to combine all available information together and isolate some common features for determination of the pathway and their mechanism of action generally have a highly complicated nature. However, microtubule (MT) monomers are highly conserved protein structures, and microtubules are structurally conserved from Homo sapiens to Arabidopsis thaliana. The interaction of MT elements with microtubule-associated proteins and post-translational modifiers is fully dependent on protein interfaces, and almost all MT modifications are well described except acetylation. Crystallography and interactome data using different approaches were combined to identify conserved proteins important in acetylation of microtubules. Application of computational methods and comparative analysis of binding modes generated a robust predictive model of acetylation of the ϵ-amino group of Lys40 in α-tubulins. In turn, the model discarded some probable mechanisms of interaction between elements of interest. Reconstruction of unresolved protein structures was carried out with modeling by homology to the existing crystal structure (PDBID: 1Z2B) from B. taurus using Swiss-model server, followed by a molecular dynamics simulation. Docking of the human tubulin fragment with Lys40 into the active site of α-tubulin acetyltransferase, reproduces the binding mode of peptidomimetic from X-ray structure (PDBID: 4PK3). © 2017 International Federation for Cell Biology.

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.

Structures composing protein domains.

PubMed

Kubrycht, Jaroslav; Sigler, Karel; Souček, Pavel; Hudeček, Jiří

2013-08-01

This review summarizes available data concerning intradomain structures (IS) such as functionally important amino acid residues, short linear motifs, conserved or disordered regions, peptide repeats, broadly occurring secondary structures or folds, etc. IS form structural features (units or elements) necessary for interactions with proteins or non-peptidic ligands, enzyme reactions and some structural properties of proteins. These features have often been related to a single structural level (e.g. primary structure) mostly requiring certain structural context of other levels (e.g. secondary structures or supersecondary folds) as follows also from some examples reported or demonstrated here. In addition, we deal with some functionally important dynamic properties of IS (e.g. flexibility and different forms of accessibility), and more special dynamic changes of IS during enzyme reactions and allosteric regulation. Selected notes concern also some experimental methods, still more necessary tools of bioinformatic processing and clinically interesting relationships. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Feature-based Morphometry

PubMed Central

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

2013-01-01

This paper presents feature-based morphometry (FBM), a new, fully data-driven technique for identifying group-related differences in volumetric imagery. In contrast to most morphometry methods which assume one-to-one correspondence between all subjects, FBM models images as a collage of distinct, localized image features which may not be present in all subjects. FBM thus explicitly accounts for the case where the same anatomical tissue cannot be reliably identified in all subjects due to disease or anatomical variability. A probabilistic model describes features in terms of their appearance, geometry, and relationship to sub-groups of a population, and is automatically learned from a set of subject images and group labels. Features identified indicate group-related anatomical structure that can potentially be used as disease biomarkers or as a basis for computer-aided diagnosis. Scale-invariant image features are used, which reflect generic, salient patterns in the image. 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 obtains an equal error classification rate of 0.78 on new subjects. PMID:20426102

On the use of attractor dimension as a feature in structural health monitoring

USGS Publications Warehouse

Nichols, J.M.; Virgin, L.N.; Todd, M.D.; Nichols, J.D.

2003-01-01

Recent works in the vibration-based structural health monitoring community have emphasised the use of correlation dimension as a discriminating statistic in seperating a damaged from undamaged response. This paper explores the utility of attractor dimension as a 'feature' and offers some comparisons between different metrics reflecting dimension. This focus is on evaluating the performance of two different measures of dimension as damage indicators in a structural health monitoring context. Results indicate that the correlation dimension is probably a poor choice of statistic for the purpose of signal discrimination. Other measures of dimension may be used for the same purposes with a higher degree of statistical reliability. The question of competing methodologies is placed in a hypothesis testing framework and answered with experimental data taken from a cantilivered beam.

Features of structure-phase transformations and segregation processes under irradiation of austenitic and ferritic-martensitic steels

NASA Astrophysics Data System (ADS)

Neklyudov, I. M.; Voyevodin, V. N.

1994-09-01

The difference between crystal lattices of austenitic and ferritic steels leads to distinctive features in mechanisms of physical-mechanical change. This paper presents the results of investigations of dislocation structure and phase evolution, and segregation phenomena in austenitic and ferritic-martensitic steels and alloys during irradiation with heavy ions in the ESUVI and UTI accelerators and by neutrons in fast reactors BOR-60 and BN-600. The influence of different factors (including different alloying elements) on processes of structure-phase transformation was studied.

Control-group feature normalization for multivariate pattern analysis of structural MRI data using the support vector machine.

PubMed

Linn, Kristin A; Gaonkar, Bilwaj; Satterthwaite, Theodore D; Doshi, Jimit; Davatzikos, Christos; Shinohara, Russell T

2016-05-15

Normalization of feature vector values is a common practice in machine learning. Generally, each feature value is standardized to the unit hypercube or by normalizing to zero mean and unit variance. Classification decisions based on support vector machines (SVMs) or by other methods are sensitive to the specific normalization used on the features. In the context of multivariate pattern analysis using neuroimaging data, standardization effectively up- and down-weights features based on their individual variability. Since the standard approach uses the entire data set to guide the normalization, it utilizes the total variability of these features. This total variation is inevitably dependent on the amount of marginal separation between groups. Thus, such a normalization may attenuate the separability of the data in high dimensional space. In this work we propose an alternate approach that uses an estimate of the control-group standard deviation to normalize features before training. We study our proposed approach in the context of group classification using structural MRI data. We show that control-based normalization leads to better reproducibility of estimated multivariate disease patterns and improves the classifier performance in many cases. Copyright © 2016 Elsevier Inc. All rights reserved.

Deterministic object tracking using Gaussian ringlet and directional edge features

NASA Astrophysics Data System (ADS)

Krieger, Evan W.; Sidike, Paheding; Aspiras, Theus; Asari, Vijayan K.

2017-10-01

Challenges currently existing for intensity-based histogram feature tracking methods in wide area motion imagery (WAMI) data include object structural information distortions, background variations, and object scale change. These issues are caused by different pavement or ground types and from changing the sensor or altitude. All of these challenges need to be overcome in order to have a robust object tracker, while attaining a computation time appropriate for real-time processing. To achieve this, we present a novel method, Directional Ringlet Intensity Feature Transform (DRIFT), which employs Kirsch kernel filtering for edge features and a ringlet feature mapping for rotational invariance. The method also includes an automatic scale change component to obtain accurate object boundaries and improvements for lowering computation times. We evaluated the DRIFT algorithm on two challenging WAMI datasets, namely Columbus Large Image Format (CLIF) and Large Area Image Recorder (LAIR), to evaluate its robustness and efficiency. Additional evaluations on general tracking video sequences are performed using the Visual Tracker Benchmark and Visual Object Tracking 2014 databases to demonstrate the algorithms ability with additional challenges in long complex sequences including scale change. Experimental results show that the proposed approach yields competitive results compared to state-of-the-art object tracking methods on the testing datasets.

Iterative feature refinement for accurate undersampled MR image reconstruction

NASA Astrophysics Data System (ADS)

Wang, Shanshan; Liu, Jianbo; Liu, Qiegen; Ying, Leslie; Liu, Xin; Zheng, Hairong; Liang, Dong

2016-05-01

Accelerating MR scan is of great significance for clinical, research and advanced applications, and one main effort to achieve this is the utilization of compressed sensing (CS) theory. Nevertheless, the existing CSMRI approaches still have limitations such as fine structure loss or high computational complexity. This paper proposes a novel iterative feature refinement (IFR) module for accurate MR image reconstruction from undersampled K-space data. Integrating IFR with CSMRI which is equipped with fixed transforms, we develop an IFR-CS method to restore meaningful structures and details that are originally discarded without introducing too much additional complexity. Specifically, the proposed IFR-CS is realized with three iterative steps, namely sparsity-promoting denoising, feature refinement and Tikhonov regularization. Experimental results on both simulated and in vivo MR datasets have shown that the proposed module has a strong capability to capture image details, and that IFR-CS is comparable and even superior to other state-of-the-art reconstruction approaches.

Analysis of nanopore arrangement and structural features of anodic alumina layers formed by two-step anodizing in oxalic acid using the dedicated executable software

NASA Astrophysics Data System (ADS)

Zaraska, Leszek; Stępniowski, Wojciech J.; Sulka, Grzegorz D.; Ciepiela, Eryk; Jaskuła, Marian

2014-02-01

Anodic porous alumina layers were fabricated by a two-step self-organized anodization in 0.3 M oxalic acid under various anodizing potentials ranging from 30 to 60 V at two different temperatures (10 and 17 ∘C). The effect of anodizing conditions on structural features and pore arrangement of AAO was investigated in detail by using the dedicated executable publication combined with ImageJ software. With increasing anodizing potential, a linear increase of the average pore diameter, interpore distance, wall thickness and barrier layer thickness, as well as a decrease of the pore density, were observed. In addition, the higher pore diameter and porosity values were obtained for samples anodized at the elevated temperature, independently of the anodizing potential. A degree of pore order was investigated on the basis of Delaunay triangulations (defect maps) and calculation of pair distribution or angle distribution functions (PDF or ADF), respectively. All methods confirmed that in order to obtain nanoporous alumina with the best, hexagonal pore arrangement, the potential of 40 V should be applied during anodization. It was confirmed that the dedicated executable publication can be used to a fast and complex analysis of nanopore arrangement and structural features of nanoporous oxide layers.

Students' Demand for Smartphones: Structural Relationships of Product Features, Brand Name, Product Price and Social Infuence

ERIC Educational Resources Information Center

Suki, Norazah Mohd

2013-01-01

Purpose: The study aims to examine structural relationships of product features, brand name, product price and social influence with demand for Smartphones among Malaysian students'. Design/methodology/approach: Data collected from 320 valid pre-screened university students studying at the pubic higher learning institution in Federal Territory of…

UbSRD: The Ubiquitin Structural Relational Database.

PubMed

Harrison, Joseph S; Jacobs, Tim M; Houlihan, Kevin; Van Doorslaer, Koenraad; Kuhlman, Brian

2016-02-22

The structurally defined ubiquitin-like homology fold (UBL) can engage in several unique protein-protein interactions and many of these complexes have been characterized with high-resolution techniques. Using Rosetta's structural classification tools, we have created the Ubiquitin Structural Relational Database (UbSRD), an SQL database of features for all 509 UBL-containing structures in the PDB, allowing users to browse these structures by protein-protein interaction and providing a platform for quantitative analysis of structural features. We used UbSRD to define the recognition features of ubiquitin (UBQ) and SUMO observed in the PDB and the orientation of the UBQ tail while interacting with certain types of proteins. While some of the interaction surfaces on UBQ and SUMO overlap, each molecule has distinct features that aid in molecular discrimination. Additionally, we find that the UBQ tail is malleable and can adopt a variety of conformations upon binding. UbSRD is accessible as an online resource at rosettadesign.med.unc.edu/ubsrd. Copyright © 2015 Elsevier Ltd. All rights reserved.

Predicting disulfide connectivity from protein sequence using multiple sequence feature vectors and secondary structure.

PubMed

Song, Jiangning; Yuan, Zheng; Tan, Hao; Huber, Thomas; Burrage, Kevin

2007-12-01

Disulfide bonds are primary covalent crosslinks between two cysteine residues in proteins that play critical roles in stabilizing the protein structures and are commonly found in extracy-toplasmatic or secreted proteins. In protein folding prediction, the localization of disulfide bonds can greatly reduce the search in conformational space. Therefore, there is a great need to develop computational methods capable of accurately predicting disulfide connectivity patterns in proteins that could have potentially important applications. We have developed a novel method to predict disulfide connectivity patterns from protein primary sequence, using a support vector regression (SVR) approach based on multiple sequence feature vectors and predicted secondary structure by the PSIPRED program. The results indicate that our method could achieve a prediction accuracy of 74.4% and 77.9%, respectively, when averaged on proteins with two to five disulfide bridges using 4-fold cross-validation, measured on the protein and cysteine pair on a well-defined non-homologous dataset. We assessed the effects of different sequence encoding schemes on the prediction performance of disulfide connectivity. It has been shown that the sequence encoding scheme based on multiple sequence feature vectors coupled with predicted secondary structure can significantly improve the prediction accuracy, thus enabling our method to outperform most of other currently available predictors. Our work provides a complementary approach to the current algorithms that should be useful in computationally assigning disulfide connectivity patterns and helps in the annotation of protein sequences generated by large-scale whole-genome projects. The prediction web server and Supplementary Material are accessible at http://foo.maths.uq.edu.au/~huber/disulfide

Ten-Structure as Strategy of Addition 1-20 by Involving Spatial Structuring Ability for First Grade Students

ERIC Educational Resources Information Center

Salmah, Ummy; Putri, Ratu Ilma Indra; Somakim

2015-01-01

The aim of this study is to design learning activities that can support students to develop strategies for the addition of number 1 to 20 in the first grade by involving students' spatial structuring ability. This study was conducted in Indonesia by involving 27 students. In this paper, one of three activities is discussed namely ten-box activity.…

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

PubMed Central

2011-01-01

Background Systematic mutagenesis studies have shown that only a few interface residues termed hot spots contribute significantly to the binding free energy of protein-protein interactions. Therefore, hot spots prediction becomes increasingly important for well understanding the essence of proteins interactions and helping narrow down the search space for drug design. Currently many computational methods have been developed by proposing different features. However comparative assessment of these features and furthermore effective and accurate methods are still in pressing need. Results In this study, we first comprehensively collect the features to discriminate hot spots and non-hot spots and analyze their distributions. We find that hot spots have lower relASA and larger relative change in ASA, suggesting hot spots tend to be protected from bulk solvent. In addition, hot spots have more contacts including hydrogen bonds, salt bridges, and atomic contacts, which favor complexes formation. Interestingly, we find that conservation score and sequence entropy are not significantly different between hot spots and non-hot spots in Ab+ dataset (all complexes). While in Ab- dataset (antigen-antibody complexes are excluded), there are significant differences in two features between hot pots and non-hot spots. Secondly, we explore the predictive ability for each feature and the combinations of features by support vector machines (SVMs). The results indicate that sequence-based feature outperforms other combinations of features with reasonable accuracy, with a precision of 0.69, a recall of 0.68, an F1 score of 0.68, and an AUC of 0.68 on independent test set. Compared with other machine learning methods and two energy-based approaches, our approach achieves the best performance. Moreover, we demonstrate the applicability of our method to predict hot spots of two protein complexes. Conclusion Experimental results show that support vector machine classifiers are quite

Image segmentation using association rule features.

PubMed

Rushing, John A; Ranganath, Heggere; Hinke, Thomas H; Graves, Sara J

2002-01-01

A new type of texture feature based on association rules is described. Association rules have been used in applications such as market basket analysis to capture relationships present among items in large data sets. It is shown that association rules can be adapted to capture frequently occurring local structures in images. The frequency of occurrence of these structures can be used to characterize texture. Methods for segmentation of textured images based on association rule features are described. Simulation results using images consisting of man made and natural textures show that association rule features perform well compared to other widely used texture features. Association rule features are used to detect cumulus cloud fields in GOES satellite images and are found to achieve higher accuracy than other statistical texture features for this problem.

Addition of electrophilic lipids to actin alters filament structure

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

Gayarre, Javier; Sanchez, David; Sanchez-Gomez, Francisco J.

2006-11-03

Pathophysiological processes associated with oxidative stress lead to the generation of reactive lipid species. Among them, lipids bearing unsaturated aldehyde or ketone moieties can form covalent adducts with cysteine residues and modulate protein function. Through proteomic techniques we have identified actin as a target for the addition of biotinylated analogs of the cyclopentenone prostaglandins 15-deoxy-{delta}{sup 12,14}-PGJ{sub 2} (15d-PGJ{sub 2}) and PGA{sub 1} in NIH-3T3 fibroblasts. This modification could take place in vitro and mapped to the protein C-terminal end. Other electrophilic lipids, like the isoprostane 8-iso-PGA{sub 1} and 4-hydroxy-2-nonenal, also bound to actin. The C-terminal region of actin is importantmore » for monomer-monomer interactions and polymerization. Electron microscopy showed that actin treated with 15d-PGJ{sub 2} or 4-hydroxy-2-nonenal formed filaments which were less abundant and displayed shorter length and altered structure. Streptavidin-gold staining allowed mapping of biotinylated 15d-PGJ{sub 2} at sites of filament disruption. These results shed light on the structural implications of actin modification by lipid electrophiles.« less

Additive Manufacturing of Biomedical Constructs with Biomimetic Structural Organizations

PubMed Central

Li, Xiao; He, Jiankang; Zhang, Weijie; Jiang, Nan; Li, Dichen

2016-01-01

Additive manufacturing (AM), sometimes called three-dimensional (3D) printing, has attracted a lot of research interest and is presenting unprecedented opportunities in biomedical fields, because this technology enables the fabrication of biomedical constructs with great freedom and in high precision. An important strategy in AM of biomedical constructs is to mimic the structural organizations of natural biological organisms. This can be done by directly depositing cells and biomaterials, depositing biomaterial structures before seeding cells, or fabricating molds before casting biomaterials and cells. This review organizes the research advances of AM-based biomimetic biomedical constructs into three major directions: 3D constructs that mimic tubular and branched networks of vasculatures; 3D constructs that contains gradient interfaces between different tissues; and 3D constructs that have different cells positioned to create multicellular systems. Other recent advances are also highlighted, regarding the applications of AM for organs-on-chips, AM-based micro/nanostructures, and functional nanomaterials. Under this theme, multiple aspects of AM including imaging/characterization, material selection, design, and printing techniques are discussed. The outlook at the end of this review points out several possible research directions for the future. PMID:28774030

Additive Manufacturing of Biomedical Constructs with Biomimetic Structural Organizations.

PubMed

Li, Xiao; He, Jiankang; Zhang, Weijie; Jiang, Nan; Li, Dichen

2016-11-09

Additive manufacturing (AM), sometimes called three-dimensional (3D) printing, has attracted a lot of research interest and is presenting unprecedented opportunities in biomedical fields, because this technology enables the fabrication of biomedical constructs with great freedom and in high precision. An important strategy in AM of biomedical constructs is to mimic the structural organizations of natural biological organisms. This can be done by directly depositing cells and biomaterials, depositing biomaterial structures before seeding cells, or fabricating molds before casting biomaterials and cells. This review organizes the research advances of AM-based biomimetic biomedical constructs into three major directions: 3D constructs that mimic tubular and branched networks of vasculatures; 3D constructs that contains gradient interfaces between different tissues; and 3D constructs that have different cells positioned to create multicellular systems. Other recent advances are also highlighted, regarding the applications of AM for organs-on-chips, AM-based micro/nanostructures, and functional nanomaterials. Under this theme, multiple aspects of AM including imaging/characterization, material selection, design, and printing techniques are discussed. The outlook at the end of this review points out several possible research directions for the future.

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.

UV absorption investigation of ferromagnetically filled ultra-thick carbon onions, carriers of the 217.5 nm Interstellar Absorption Feature

NASA Astrophysics Data System (ADS)

Boi, Filippo S.; Zhang, Xiaotian; Ivaturi, Sameera; Liu, Qianyang; Wen, Jiqiu; Wang, Shanling

2017-12-01

Carbon nano-onions (CNOs) are fullerene-like structures which consist of quasi-spherical closed carbon shells. These structures have become a subject of great interest thanks to their characteristic absorption feature of interstellar origin (at 217.5 nm, 4.6 μm-1). An additional extinction peak at 3.8 μm-1 has also been reported and attributed to absorption by graphitic residues between the as-grown CNOs. Here, we report the ultraviolet absorption properties of ultra-thick CNOs filled with FePt3 crystals, which also exhibit two main absorption peaks—features located at 4.58 μm-1 and 3.44 μm-1. The presence of this additional feature is surprising and is attributed to nonmagnetic graphite flakes produced as a by-product in the pyrolysis experiment (as confirmed by magnetic separation methods). Instead, the feature at 4.58 μm-1 is associated with the π-plasmonic resonance of the CNOs structures. The FePt3 filled CNOs were fabricated in situ by an advanced one-step fast process consisting in the direct sublimation and pyrolysis of two molecular precursors, namely, ferrocene and dichloro-cyclooctadiene-platinum in a chemical vapour deposition system. The morphological, structural, and magnetic properties of the as-grown filled CNOs were characterized by a means of scanning and transmission electron microscopy, X-ray diffraction, and magnetometry.

Contrasted structuring effects of mesoscale features on the seabird community in the Mozambique Channel

NASA Astrophysics Data System (ADS)

Jaquemet, S.; Ternon, J. F.; Kaehler, S.; Thiebot, J. B.; Dyer, B.; Bemanaja, E.; Marteau, C.; Le Corre, M.

2014-02-01

of mescoscale features in structuring the tropical seabird community in the Mozambique Channel, in addition to segregating tropical and non-tropical species. The mechanisms underlying the segregation of tropical seabirds seem to partially differ from that of other tropical regions, and this may be a consequence of the strong local mesoscale activity, affecting prey size and availability schemes. Beyond characterising the foraging habitats of the seabird community of the Mozambique Channel, this study highlights the importance of this region as a hot spot for seabirds; especially the southern part, where several endangered sub-Antarctic species over-winter.

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.

Distributed cable sensors with memory feature for post-disaster damage assessment

NASA Astrophysics Data System (ADS)

Chen, Genda; McDaniel, Ryan D.; Pommerenke, David J.; Sun, Shishuang

2005-05-01

A new design of distributed crack sensors is presented for the condition assessment of reinforced concrete (RC) structures during and immediately after an earthquake event. This study is mainly focused on the performance of cable sensors under dynamic loading, particularly their ability to memorize the crack history of an RC member. This unique memory feature enables the post-earthquake condition assessment of structural members such as RC columns, in which the earthquake-induced cracks are closed immediately after an earthquake event due to gravity loads and they are visually undetectable. Factors affecting the onset of the memory feature were investigated experimentally with small-scale RC beams under cyclic loading. Test results indicated that both crack width and the number of loading cycles were instrumental in the onset of the memory feature of cable sensors. Practical issues related to dynamic acquisition with the sensors were discussed. The sensors were proven to be fatigue resistant from the shake table tests of RC columns. They continued to show useful signal after the columns can no longer support additional loads.

Faxing Structures to the Moon: Freeform Additive Construction System (FACS)

NASA Technical Reports Server (NTRS)

Howe, A. Scott; Wilcox, Brian; McQuin, Christopher; Townsend, Julie; Rieber, Richard; Barmatz, Martin; Leichty, John

2013-01-01

Using the highly articulated All-Terrain Hex-Limbed Extra-Terrestrial Explorer (ATHLETE) robotic mobility system as a precision positioning tool, a variety of print head technologies can be used to 3D print large-scale in-situ structures on planetary surfaces such as the moon or Mars. In effect, in the same way CAD models can be printed in a 3D printer, large-scale structures such as walls, vaults, domes, berms, paving, trench walls, and other insitu derived elements can be FAXed to the planetary surface and built in advance of the arrival of crews, supplementing equipment and materials brought from earth. This paper discusses the ATHLETE system as a mobility / positioning platform, and presents several options for large-scale additive print head technologies, including tunable microwave "sinterator" approaches and in-situ concrete deposition. The paper also discusses potential applications, such as sintered-in-place habitat shells, radiation shielding, road paving, modular bricks, and prefabricated construction components.

New Features in the Lipid A Structure of Brucella suis and Brucella abortus Lipopolysaccharide

NASA Astrophysics Data System (ADS)

Casabuono, Adriana C.; Czibener, Cecilia; Del Giudice, Mariela G.; Valguarnera, Ezequiel; Ugalde, Juan E.; Couto, Alicia S.

2017-12-01

Brucellaceae are Gram-negative bacteria that cause brucellosis, one of the most distributed worldwide zoonosis, transmitted to humans by contact with either infected animals or their products. The lipopolysaccharide exposed on the cell surface has been intensively studied and is considered a major virulence factor of Brucella. In the last years, structural studies allowed the determination of new structures in the core oligosaccharide and the O-antigen of this lipopolysaccharide. In this work, we have reinvestigated the lipid A structure isolated from B. suis and B. abortus lipopolysaccharides. A detailed study by MALDI-TOF mass spectrometry in the positive and negative ion modes of the lipid A moieties purified from both species was performed. Interestingly, a new feature was detected: the presence of a pyrophosphorylethanolamine residue substituting the backbone. LID-MS/MS analysis of some of the detected ions allowed assurance that the Lipid A structure composed by the diGlcN3N disaccharide, mainly hexa-acylated and penta-acylated, bearing one phosphate and one pyrophosphorylethanolamine residue. [Figure not available: see fulltext.

New Features in the Lipid A Structure of Brucella suis and Brucella abortus Lipopolysaccharide.

PubMed

Casabuono, Adriana C; Czibener, Cecilia; Del Giudice, Mariela G; Valguarnera, Ezequiel; Ugalde, Juan E; Couto, Alicia S

2017-12-01

Brucellaceae are Gram-negative bacteria that cause brucellosis, one of the most distributed worldwide zoonosis, transmitted to humans by contact with either infected animals or their products. The lipopolysaccharide exposed on the cell surface has been intensively studied and is considered a major virulence factor of Brucella. In the last years, structural studies allowed the determination of new structures in the core oligosaccharide and the O-antigen of this lipopolysaccharide. In this work, we have reinvestigated the lipid A structure isolated from B. suis and B. abortus lipopolysaccharides. A detailed study by MALDI-TOF mass spectrometry in the positive and negative ion modes of the lipid A moieties purified from both species was performed. Interestingly, a new feature was detected: the presence of a pyrophosphorylethanolamine residue substituting the backbone. LID-MS/MS analysis of some of the detected ions allowed assurance that the Lipid A structure composed by the diGlcN3N disaccharide, mainly hexa-acylated and penta-acylated, bearing one phosphate and one pyrophosphorylethanolamine residue. Graphical abstract ᅟ.

Process-Structure Linkages Using a Data Science Approach: Application to Simulated Additive Manufacturing Data

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

Popova, Evdokia; Rodgers, Theron M.; Gong, Xinyi

A novel data science workflow is developed and demonstrated to extract process-structure linkages (i.e., reduced-order model) for microstructure evolution problems when the final microstructure depends on (simulation or experimental) processing parameters. Our workflow consists of four main steps: data pre-processing, microstructure quantification, dimensionality reduction, and extraction/validation of process-structure linkages. These methods that can be employed within each step vary based on the type and amount of available data. In this paper, this data-driven workflow is applied to a set of synthetic additive manufacturing microstructures obtained using the Potts-kinetic Monte Carlo (kMC) approach. Additive manufacturing techniques inherently produce complex microstructures thatmore » can vary significantly with processing conditions. Using the developed workflow, a low-dimensional data-driven model was established to correlate process parameters with the predicted final microstructure. In addition, the modular workflows developed and presented in this work facilitate easy dissemination and curation by the broader community.« less

Process-Structure Linkages Using a Data Science Approach: Application to Simulated Additive Manufacturing Data

DOE PAGES

Popova, Evdokia; Rodgers, Theron M.; Gong, Xinyi; ...

2017-03-13

A novel data science workflow is developed and demonstrated to extract process-structure linkages (i.e., reduced-order model) for microstructure evolution problems when the final microstructure depends on (simulation or experimental) processing parameters. Our workflow consists of four main steps: data pre-processing, microstructure quantification, dimensionality reduction, and extraction/validation of process-structure linkages. These methods that can be employed within each step vary based on the type and amount of available data. In this paper, this data-driven workflow is applied to a set of synthetic additive manufacturing microstructures obtained using the Potts-kinetic Monte Carlo (kMC) approach. Additive manufacturing techniques inherently produce complex microstructures thatmore » can vary significantly with processing conditions. Using the developed workflow, a low-dimensional data-driven model was established to correlate process parameters with the predicted final microstructure. In addition, the modular workflows developed and presented in this work facilitate easy dissemination and curation by the broader community.« less

In vivo XCT bone characterization of lattice structured implants fabricated by additive manufacturing.

PubMed

Obaton, A-F; Fain, J; Djemaï, M; Meinel, D; Léonard, F; Mahé, E; Lécuelle, B; Fouchet, J-J; Bruno, G

2017-08-01

Several cylindrical specimens and dental implants, presenting diagonal lattice structures with different cell sizes (600, 900 and 1200 μm) were additively manufactured by selective laser melting process. Then they were implanted for two months in a sheep. After removal, they were studied by Archimedes' method as well as X-ray computed tomography in order to assess the penetration of bone into the lattice. We observed that the additive manufactured parts were geometrically conformed to the theoretical specifications. However, several particles were left adhering to the surface of the lattice, thereby partly or entirely obstructing the cells. Nevertheless, bone penetration was clearly visible. We conclude that the 900 μm lattice cell size is more favourable to bone penetration than the 1200 μm lattice cell size, as the bone penetration is 84% for 900 μm against 54% for 1200 μm cell structures. The lower bone penetration value for the 1200 μm lattice cell could possibly be attributed to the short residence time in the sheep. Our results lead to the conclusion that lattice implants additively manufactured by selective laser melting enable better bone integration.

A feature refinement approach for statistical interior CT reconstruction

NASA Astrophysics Data System (ADS)

Hu, Zhanli; Zhang, Yunwan; Liu, Jianbo; Ma, Jianhua; Zheng, Hairong; Liang, Dong

2016-07-01

Interior tomography is clinically desired to reduce the radiation dose rendered to patients. In this work, a new statistical interior tomography approach for computed tomography is proposed. The developed design focuses on taking into account the statistical nature of local projection data and recovering fine structures which are lost in the conventional total-variation (TV)—minimization reconstruction. The proposed method falls within the compressed sensing framework of TV minimization, which only assumes that the interior ROI is piecewise constant or polynomial and does not need any additional prior knowledge. To integrate the statistical distribution property of projection data, the objective function is built under the criteria of penalized weighed least-square (PWLS-TV). In the implementation of the proposed method, the interior projection extrapolation based FBP reconstruction is first used as the initial guess to mitigate truncation artifacts and also provide an extended field-of-view. Moreover, an interior feature refinement step, as an important processing operation is performed after each iteration of PWLS-TV to recover the desired structure information which is lost during the TV minimization. Here, a feature descriptor is specifically designed and employed to distinguish structure from noise and noise-like artifacts. A modified steepest descent algorithm is adopted to minimize the associated objective function. The proposed method is applied to both digital phantom and in vivo Micro-CT datasets, and compared to FBP, ART-TV and PWLS-TV. The reconstruction results demonstrate that the proposed method performs better than other conventional methods in suppressing noise, reducing truncated and streak artifacts, and preserving features. The proposed approach demonstrates its potential usefulness for feature preservation of interior tomography under truncated projection measurements.

A feature refinement approach for statistical interior CT reconstruction.

PubMed

Hu, Zhanli; Zhang, Yunwan; Liu, Jianbo; Ma, Jianhua; Zheng, Hairong; Liang, Dong

2016-07-21

Interior tomography is clinically desired to reduce the radiation dose rendered to patients. In this work, a new statistical interior tomography approach for computed tomography is proposed. The developed design focuses on taking into account the statistical nature of local projection data and recovering fine structures which are lost in the conventional total-variation (TV)-minimization reconstruction. The proposed method falls within the compressed sensing framework of TV minimization, which only assumes that the interior ROI is piecewise constant or polynomial and does not need any additional prior knowledge. To integrate the statistical distribution property of projection data, the objective function is built under the criteria of penalized weighed least-square (PWLS-TV). In the implementation of the proposed method, the interior projection extrapolation based FBP reconstruction is first used as the initial guess to mitigate truncation artifacts and also provide an extended field-of-view. Moreover, an interior feature refinement step, as an important processing operation is performed after each iteration of PWLS-TV to recover the desired structure information which is lost during the TV minimization. Here, a feature descriptor is specifically designed and employed to distinguish structure from noise and noise-like artifacts. A modified steepest descent algorithm is adopted to minimize the associated objective function. The proposed method is applied to both digital phantom and in vivo Micro-CT datasets, and compared to FBP, ART-TV and PWLS-TV. The reconstruction results demonstrate that the proposed method performs better than other conventional methods in suppressing noise, reducing truncated and streak artifacts, and preserving features. The proposed approach demonstrates its potential usefulness for feature preservation of interior tomography under truncated projection measurements.

Influence of major structural features of tocopherols and tocotrienols on their omega-oxidation by tocopherol-omega-hydroxylase.

PubMed

Sontag, Timothy J; Parker, Robert S

2007-05-01

Human cytochrome P450 4F2 (CYP4F2) catalyzes the initial omega-hydroxylation reaction in the metabolism of tocopherols and tocotrienols to carboxychromanols and is, to date, the only enzyme shown to metabolize vitamin E. The objective of this study was to characterize this activity, particularly the influence of key features of tocochromanol substrate structure. The influence of the number and positions of methyl groups on the chromanol ring, and of stereochemistry and saturation of the side chain, were explored using HepG2 cultures and microsomal reaction systems. Human liver microsomes and microsomes selectively expressing recombinant human CYP4F2 exhibited substrate activity patterns similar to those of HepG2 cells. Although activity was strongly associated with substrate accumulation by cells or microsomes, substantial differences in specific activities between substrates remained under conditions of similar microsomal membrane substrate concentration. Methylation at C5 of the chromanol ring was associated with markedly low activity. Tocotrienols exhibited much higher Vmax values than their tocopherol counterparts. Side chain stereochemistry had no effect on omega-hydroxylation of alpha-tocopherol (alpha-TOH) by any system. Kinetic analysis of microsomal CYP4F2 activity revealed Michaelis-Menten kinetics for alpha-TOH but allosteric cooperativity for other vitamers, especially tocotrienols. Additionally, alpha-TOH was a positive effector of omega-hydroxylation of other vitamers. These results indicate that CYP4F2-mediated tocopherol-omega-hydroxylation is a central feature underlying the different biological half-lives, and therefore biopotencies, of the tocopherols and tocotrienols.

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

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

PubMed Central

Yachdav, Guy; Kloppmann, Edda; Kajan, Laszlo; Hecht, Maximilian; Goldberg, Tatyana; Hamp, Tobias; Hönigschmid, Peter; Schafferhans, Andrea; Roos, Manfred; Bernhofer, Michael; Richter, Lothar; Ashkenazy, Haim; Punta, Marco; Schlessinger, Avner; Bromberg, Yana; Schneider, Reinhard; Vriend, Gerrit; Sander, Chris; Ben-Tal, Nir; Rost, Burkhard

2014-01-01

PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with a protein sequence it returns: multiple sequence alignments, predicted aspects of structure (secondary structure, solvent accessibility, transmembrane helices (TMSEG) and strands, coiled-coil regions, disulfide bonds and disordered regions) and function. The service incorporates analysis methods for the identification of functional regions (ConSurf), homology-based inference of Gene Ontology terms (metastudent), comprehensive subcellular localization prediction (LocTree3), protein–protein binding sites (ISIS2), protein–polynucleotide binding sites (SomeNA) and predictions of the effect of point mutations (non-synonymous SNPs) on protein function (SNAP2). Our goal has always been to develop a system optimized to meet the demands of experimentalists not highly experienced in bioinformatics. To this end, the PredictProtein results are presented as both text and a series of intuitive, interactive and visually appealing figures. The web server and sources are available at http://ppopen.rostlab.org. PMID:24799431

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.

Changes in quantitative 3D shape features of the optic nerve head associated with age

NASA Astrophysics Data System (ADS)

Christopher, Mark; Tang, Li; Fingert, John H.; Scheetz, Todd E.; Abramoff, Michael D.

2013-02-01

Optic nerve head (ONH) structure is an important biological feature of the eye used by clinicians to diagnose and monitor progression of diseases such as glaucoma. ONH structure is commonly examined using stereo fundus imaging or optical coherence tomography. Stereo fundus imaging provides stereo views of the ONH that retain 3D information useful for characterizing structure. In order to quantify 3D ONH structure, we applied a stereo correspondence algorithm to a set of stereo fundus images. Using these quantitative 3D ONH structure measurements, eigen structures were derived using principal component analysis from stereo images of 565 subjects from the Ocular Hypertension Treatment Study (OHTS). To evaluate the usefulness of the eigen structures, we explored associations with the demographic variables age, gender, and race. Using regression analysis, the eigen structures were found to have significant (p < 0.05) associations with both age and race after Bonferroni correction. In addition, classifiers were constructed to predict the demographic variables based solely on the eigen structures. These classifiers achieved an area under receiver operating characteristic curve of 0.62 in predicting a binary age variable, 0.52 in predicting gender, and 0.67 in predicting race. The use of objective, quantitative features or eigen structures can reveal hidden relationships between ONH structure and demographics. The use of these features could similarly allow specific aspects of ONH structure to be isolated and associated with the diagnosis of glaucoma, disease progression and outcomes, and genetic factors.

Structural health monitoring for ship structures

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

Farrar, Charles; Park, Gyuhae; Angel, Marian

2009-01-01

Currently the Office of Naval Research is supporting the development of structural health monitoring (SHM) technology for U.S. Navy ship structures. This application is particularly challenging because of the physical size of these structures, the widely varying and often extreme operational and environmental conditions associated with these ships missions, lack of data from known damage conditions, limited sensing that was not designed specifically for SHM, and the management of the vast amounts of data that can be collected during a mission. This paper will first define a statistical pattern recognition paradigm for SHM by describing the four steps of (1)more » Operational Evaluation, (2) Data Acquisition, (3) Feature Extraction, and (4) Statistical Classification of Features as they apply to ship structures. Note that inherent in the last three steps of this process are additional tasks of data cleansing, compression, normalization and fusion. The presentation will discuss ship structure SHM challenges in the context of applying various SHM approaches to sea trials data measured on an aluminum multi-hull high-speed ship, the HSV-2 Swift. To conclude, the paper will discuss several outstanding issues that need to be addressed before SHM can make the transition from a research topic to actual field applications on ship structures and suggest approaches for addressing these issues.« less

Features and machine learning classification of connected speech samples from patients with autopsy proven Alzheimer's disease with and without additional vascular pathology.

PubMed

Rentoumi, Vassiliki; Raoufian, Ladan; Ahmed, Samrah; de Jager, Celeste A; Garrard, Peter

2014-01-01

Mixed vascular and Alzheimer-type dementia and pure Alzheimer's disease are both associated with changes in spoken language. These changes have, however, seldom been subjected to systematic comparison. In the present study, we analyzed language samples obtained during the course of a longitudinal clinical study from patients in whom one or other pathology was verified at post mortem. The aims of the study were twofold: first, to confirm the presence of differences in language produced by members of the two groups using quantitative methods of evaluation; and secondly to ascertain the most informative sources of variation between the groups. We adopted a computational approach to evaluate digitized transcripts of connected speech along a range of language-related dimensions. We then used machine learning text classification to assign the samples to one of the two pathological groups on the basis of these features. The classifiers' accuracies were tested using simple lexical features, syntactic features, and more complex statistical and information theory characteristics. Maximum accuracy was achieved when word occurrences and frequencies alone were used. Features based on syntactic and lexical complexity yielded lower discrimination scores, but all combinations of features showed significantly better performance than a baseline condition in which every transcript was assigned randomly to one of the two classes. The classification results illustrate the word content specific differences in the spoken language of the two groups. In addition, those with mixed pathology were found to exhibit a marked reduction in lexical variation and complexity compared to their pure AD counterparts.

Recent Progress in Biomimetic Additive Manufacturing Technology: From Materials to Functional Structures.

PubMed

Yang, Yang; Song, Xuan; Li, Xiangjia; Chen, Zeyu; Zhou, Chi; Zhou, Qifa; Chen, Yong

2018-06-19

Nature has developed high-performance materials and structures over millions of years of evolution and provides valuable sources of inspiration for the design of next-generation structural materials, given the variety of excellent mechanical, hydrodynamic, optical, and electrical properties. Biomimicry, by learning from nature's concepts and design principles, is driving a paradigm shift in modern materials science and technology. However, the complicated structural architectures in nature far exceed the capability of traditional design and fabrication technologies, which hinders the progress of biomimetic study and its usage in engineering systems. Additive manufacturing (three-dimensional (3D) printing) has created new opportunities for manipulating and mimicking the intrinsically multiscale, multimaterial, and multifunctional structures in nature. Here, an overview of recent developments in 3D printing of biomimetic reinforced mechanics, shape changing, and hydrodynamic structures, as well as optical and electrical devices is provided. The inspirations are from various creatures such as nacre, lobster claw, pine cone, flowers, octopus, butterfly wing, fly eye, etc., and various 3D-printing technologies are discussed. Future opportunities for the development of biomimetic 3D-printing technology to fabricate next-generation functional materials and structures in mechanical, electrical, optical, and biomedical engineering are also outlined. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

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.

Simulation of metal additive manufacturing microstructures using kinetic Monte Carlo

DOE PAGES

Rodgers, Theron M.; Madison, Jonathan D.; Tikare, Veena

2017-04-19

Additive manufacturing (AM) is of tremendous interest given its ability to realize complex, non-traditional geometries in engineered structural materials. But, microstructures generated from AM processes can be equally, if not more, complex than their conventionally processed counterparts. While some microstructural features observed in AM may also occur in more traditional solidification processes, the introduction of spatially and temporally mobile heat sources can result in significant microstructural heterogeneity. While grain size and shape in metal AM structures are understood to be highly dependent on both local and global temperature profiles, the exact form of this relation is not well understood. Wemore » implement an idealized molten zone and temperature-dependent grain boundary mobility in a kinetic Monte Carlo model to predict three-dimensional grain structure in additively manufactured metals. In order to demonstrate the flexibility of the model, synthetic microstructures are generated under conditions mimicking relatively diverse experimental results present in the literature. Simulated microstructures are then qualitatively and quantitatively compared to their experimental complements and are shown to be in good agreement.« less

Structural Mass Saving Potential of a 5-MW Direct-Drive Generator Designed for Additive Manufacturing

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

Sethuraman, Latha; Fingersh, Lee J; Dykes, Katherine L

As wind turbine blade diameters and tower height increase to capture more energy in the wind, higher structural loads results in more structural support material increasing the cost of scaling. Weight reductions in the generator transfer to overall cost savings of the system. Additive manufacturing facilitates a design-for-functionality approach, thereby removing traditional manufacturing constraints and labor costs. The most feasible additive manufacturing technology identified for large, direct-drive generators in this study is powder-binder jetting of a sand cast mold. A parametric finite element analysis optimization study is performed, optimizing for mass and deformation. Also, topology optimization is employed for eachmore » parameter-optimized design.The optimized U-beam spoked web design results in a 24 percent reduction in structural mass of the rotor and 60 percent reduction in radial deflection.« less

Perspectives for Practice: A New JOSPT Feature to Facilitate Translation of Research Into Practice.

PubMed

Abbott, J Haxby

2016-03-01

In this month's issue, we introduce a new feature, Perspectives for Practice, which aims to interpret new research in the context of established best practice. This 2-page feature is designed to offer clinicians insight into the state of the art: what was known before, what research was done before, what new evidence the present study found, and how we should interpret this new evidence in light of what was known before. The second page of the Perspectives for Practice will provide additional material useful for teaching and discussion. The structure and content of these features will undergo continued development in response to reader feedback, which we welcome.

Adaptive cellular structures and devices with internal features for enhanced structural performance

NASA Astrophysics Data System (ADS)

Pontecorvo, Michael Eugene

and force inputs are contrasted in relation to these metrics. The key innovation to the early structural elements presented here is the combination of the VMT with the pin-jointed hexagonal cell. Chapter 3 explores several prototypes of repeatable structural elements for simultaneous load-carrying capability and energy dissipation that are based on this innovation. The final demonstration prototype presented in this chapter is a column-like element that is based on a hexagonal cell containing two horizontal springs and one vertical damper. The unit is enclosed by a pair of buckling plates that serve to give the prototype a high initial stiffness and load carrying capability. The prototype is tested in both displacement and force input and its behavior is compared to simulation. Chapter 4 builds on the conceptual designs of Chapter 3 with the introduction of a plate-like element, that contains two compact VMTs connected by a horizontally oriented damper. Pre-loaded springs are used in the prototype to perform the same load carrying function as the buckling plates in the column-like prototype with increased predictability. The plate-like prototype is studied under impact to demonstrate its effectiveness as a protective layer. It is shown to reduce peak impact loads transmitted to the base of the device by over 60%. In most cases, the prototype compares well with a conventional protective rubber layer, and in cases of extreme impact loads, it exceeds the performance of the rubber layer. In addition to impact testing, the prototype is also experimentally tested under harmonic displacement input, and is simulated under both harmonic displacement and force input. The experiments illustrate that while the VMT parameters of a single layer can be optimized to a particular harmonic load amplitude, having two layers with softer and stiffer VMTs allows the system to show good energy dissipation characteristics at different harmonic load amplitude levels. Chapter 5 examines using

Additive Technology: Update on Current Materials and Applications in Dentistry.

PubMed

Barazanchi, Abdullah; Li, Kai Chun; Al-Amleh, Basil; Lyons, Karl; Waddell, J Neil

2017-02-01

Additive manufacturing or 3D printing is becoming an alternative to subtractive manufacturing or milling in the area of computer-aided manufacturing. Research on material for use in additive manufacturing is ongoing, and a wide variety of materials are being used or developed for use in dentistry. Some materials, however, such as cobalt chromium, still lack sufficient research to allow definite conclusions about the suitability of their use in clinical dental practice. Despite this, due to the wide variety of machines that use additive manufacturing, there is much more flexibility in the build material and geometry when building structures compared with subtractive manufacturing. Overall additive manufacturing produces little material waste and is energy efficient when compared to subtractive manufacturing, due to passivity and the additive layering nature of the build process. Such features make the technique suitable to be used with fabricating structures out of hard to handle materials such as cobalt chromium. The main limitations of this technology include the appearance of steps due to layering of material and difficulty in fabricating certain material generally used in dentistry for use in 3D printing such as ceramics. The current pace of technological development, however, promises exciting possibilities. © 2016 by the American College of Prosthodontists.

Weak conservation of structural features in the interfaces of homologous transient protein–protein complexes

PubMed Central

Sudha, Govindarajan; Singh, Prashant; Swapna, Lakshmipuram S; Srinivasan, Narayanaswamy

2015-01-01

Residue types at the interface of protein–protein complexes (PPCs) are known to be reasonably well conserved. However, we show, using a dataset of known 3-D structures of homologous transient PPCs, that the 3-D location of interfacial residues and their interaction patterns are only moderately and poorly conserved, respectively. Another surprising observation is that a residue at the interface that is conserved is not necessarily in the interface in the homolog. Such differences in homologous complexes are manifested by substitution of the residues that are spatially proximal to the conserved residue and structural differences at the interfaces as well as differences in spatial orientations of the interacting proteins. Conservation of interface location and the interaction pattern at the core of the interfaces is higher than at the periphery of the interface patch. Extents of variability of various structural features reported here for homologous transient PPCs are higher than the variation in homologous permanent homomers. Our findings suggest that straightforward extrapolation of interfacial nature and inter-residue interaction patterns from template to target could lead to serious errors in the modeled complex structure. Understanding the evolution of interfaces provides insights to improve comparative modeling of PPC structures. PMID:26311309

iFeature: a python package and web server for features extraction and selection from protein and peptide sequences.

PubMed

Chen, Zhen; Zhao, Pei; Li, Fuyi; Leier, André; Marquez-Lago, Tatiana T; Wang, Yanan; Webb, Geoffrey I; Smith, A Ian; Daly, Roger J; Chou, Kuo-Chen; Song, Jiangning

2018-03-08

Structural and physiochemical descriptors extracted from sequence data have been widely used to represent sequences and predict structural, functional, expression and interaction profiles of proteins and peptides as well as DNAs/RNAs. Here, we present iFeature, a versatile Python-based toolkit for generating various numerical feature representation schemes for both protein and peptide sequences. iFeature is capable of calculating and extracting a comprehensive spectrum of 18 major sequence encoding schemes that encompass 53 different types of feature descriptors. It also allows users to extract specific amino acid properties from the AAindex database. Furthermore, iFeature integrates 12 different types of commonly used feature clustering, selection, and dimensionality reduction algorithms, greatly facilitating training, analysis, and benchmarking of machine-learning models. The functionality of iFeature is made freely available via an online web server and a stand-alone toolkit. http://iFeature.erc.monash.edu/; https://github.com/Superzchen/iFeature/. jiangning.song@monash.edu; kcchou@gordonlifescience.org; roger.daly@monash.edu. Supplementary data are available at Bioinformatics online.

Towards improved NDE and SHM methodologies incorporating nonlinear structural features

NASA Astrophysics Data System (ADS)

Chillara, Vamshi Krishna

Ultrasound is widely employed in Nondestructive Evaluation (NDE) and Structural Health Monitoring (SHM) applications to detect and characterize damage/defects in materials. In particular, ultrasonic guided waves are considered a foremost candidate for in-situ monitoring applications. Conventional ultrasonic techniques rely on changes/discontinuities in linear elastic material properties, namely the Young's modulus and shear modulus to detect damage. On the other hand, nonlinear ultrasonic techniques that rely on micro-scale nonlinear material/structural behavior are proven to be sensitive to damage induced microstructural changes that precede macro-scale damage and are hence capable of early damage detection. The goal of this thesis is to investigate the capabilities of nonlinear guided waves --- a fusion of nonlinear ultrasonic techniques with the guided wave methodologies for early damage detection. To that end, the thesis focuses on two important aspects of the problem: 1. Wavemechanics - deals with ultrasonic guided wave propagation in nonlinear waveguides; 2. Micromechanics - deals with correlating ultrasonic response with micro-scale nonlinear material behavior. For the development of efficient NDE and SHM methodologies that incorporate nonlinear structural features, a detailed understanding of the above aspects is indispensable. In this thesis, the wavemechanics aspect of the problem is dealt with from both theoretical and numerical standpoints. A generalized theoretical framework is developed to study higher harmonic guided waves in plates. This was employed to study second harmonic guided waves in pipes using a large-radius asymptotic approximation. Second harmonic guided waves in plates are studied from a numerical standpoint. Theoretical predictions are validated and some key aspects of higher harmonic generation in waveguides are outlined. Finally, second harmonic guided waves in plates with inhomogeneous and localized nonlinearities are studied and

The Structure of Neurexin 1[alpha] Reveals Features Promoting a Role as Synaptic Organizer

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

Chen, Fang; Venugopal, Vandavasi; Murray, Beverly

{alpha}-Neurexins are essential synaptic adhesion molecules implicated in autism spectrum disorder and schizophrenia. The {alpha}-neurexin extracellular domain consists of six LNS domains interspersed by three EGF-like repeats and interacts with many different proteins in the synaptic cleft. To understand how {alpha}-neurexins might function as synaptic organizers, we solved the structure of the neurexin 1{alpha} extracellular domain (n1{alpha}) to 2.65 {angstrom}. The L-shaped molecule can be divided into a flexible repeat I (LNS1-EGF-A-LNS2), a rigid horseshoe-shaped repeat II (LNS3-EGF-B-LNS4) with structural similarity to so-called reelin repeats, and an extended repeat III (LNS5-EGF-B-LNS6) with controlled flexibility. A 2.95 {angstrom} structure of n1{alpha}more » carrying splice insert SS3 in LNS4 reveals that SS3 protrudes as a loop and does not alter the rigid arrangement of repeat II. The global architecture imposed by conserved structural features enables {alpha}-neurexins to recruit and organize proteins in distinct and variable ways, influenced by splicing, thereby promoting synaptic function.« less

The performance improvement of automatic classification among obstructive lung diseases on the basis of the features of shape analysis, in addition to texture analysis at HRCT

NASA Astrophysics Data System (ADS)

Lee, Youngjoo; Kim, Namkug; Seo, Joon Beom; Lee, JuneGoo; Kang, Suk Ho

2007-03-01

In this paper, we proposed novel shape features to improve classification performance of differentiating obstructive lung diseases, based on HRCT (High Resolution Computerized Tomography) images. The images were selected from HRCT images, obtained from 82 subjects. For each image, two experienced radiologists selected rectangular ROIs with various sizes (16x16, 32x32, and 64x64 pixels), representing each disease or normal lung parenchyma. Besides thirteen textural features, we employed additional seven shape features; cluster shape features, and Top-hat transform features. To evaluate the contribution of shape features for differentiation of obstructive lung diseases, several experiments were conducted with two different types of classifiers and various ROI sizes. For automated classification, the Bayesian classifier and support vector machine (SVM) were implemented. To assess the performance and cross-validation of the system, 5-folding method was used. In comparison to employing only textural features, adding shape features yields significant enhancement of overall sensitivity(5.9, 5.4, 4.4% in the Bayesian and 9.0, 7.3, 5.3% in the SVM), in the order of ROI size 16x16, 32x32, 64x64 pixels, respectively (t-test, p<0.01). Moreover, this enhancement was largely due to the improvement on class-specific sensitivity of mild centrilobular emphysema and bronchiolitis obliterans which are most hard to differentiate for radiologists. According to these experimental results, adding shape features to conventional texture features is much useful to improve classification performance of obstructive lung diseases in both Bayesian and SVM classifiers.

Structural and morphological changes in supramolecular-structured polymer electrolyte membrane fuel cell on addition of phosphoric acid

NASA Astrophysics Data System (ADS)

Hendrana, S.; Pryliana, R. F.; Natanael, C. L.; Rahayu, I.

2018-03-01

Phosphoric acid is one agents used in membrane fuel cell to modify ionic conductivity. Therefore, its distribution in membrane is a key parameter to gain expected conductivity. Efforts have been made to distribute phosphoric acid in a supramolecular-structured membrane prepared with a matrix. To achieve even distribution across bulk of the membrane, the inclusion of the polyacid is carried out under pressurized chamber. Image of scanning electron microscopy (SEM) shows better phosphoric acid distribution for one prepared in pressurized state. It also leads in better performing in ionic conductivity. Moreover, data from differential scanning calorimetry (DSC) indicate that the addition of phosphoric acid is prominent in the change of membrane structure, while morphological changes are captured in SEM images.

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

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

Synchrotron x-ray microdiffraction reveals intrinsic structural features of amyloid deposits in situ.

PubMed

Briki, Fatma; Vérine, Jérôme; Doucet, Jean; Bénas, Philippe; Fayard, Barbara; Delpech, Marc; Grateau, Gilles; Riès-Kautt, Madeleine

2011-07-20

Amyloidoses are increasingly recognized as a major public health concern in Western countries. All amyloidoses share common morphological, structural, and tinctorial properties. These consist of staining by specific dyes, a fibrillar aspect in electron microscopy and a typical cross-β folding in x-ray diffraction patterns. Most studies that aim at deciphering the amyloid structure rely on fibers generated in vitro or extracted from tissues using protocols that may modify their intrinsic structure. Therefore, the fine details of the in situ architecture of the deposits remain unknown. Here, we present to our knowledge the first data obtained on ex vivo human renal tissue sections using x-ray microdiffraction. The typical cross-β features from fixed paraffin-embedded samples are similar to those formed in vitro or extracted from tissues. Moreover, the fiber orientation maps obtained across glomerular sections reveal an intrinsic texture that is correlated with the glomerulus morphology. These results are of the highest importance to understanding the formation of amyloid deposits and are thus expected to trigger new incentives for tissue investigation. Moreover, the access to intrinsic structural parameters such as fiber size and orientation using synchrotron x-ray microdiffraction, could provide valuable information concerning in situ mechanisms and deposit formation with potential benefits for diagnostic and therapeutic purposes. Copyright © 2011 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Novel Features for Brain-Computer Interfaces

PubMed Central

Woon, W. L.; Cichocki, A.

2007-01-01

While conventional approaches of BCI feature extraction are based on the power spectrum, we have tried using nonlinear features for classifying BCI data. In this paper, we report our test results and findings, which indicate that the proposed method is a potentially useful addition to current feature extraction techniques. PMID:18364991

Structural features of the exocellular polysaccharides of Mycobacterium tuberculosis.

PubMed Central

Lemassu, A; Daffé, M

1994-01-01

The cell envelope which surrounds pathogenic mycobacteria is postulated to be a defence barrier against phagocytic cells and its outermost constituents have a tendency to accumulate in the culture medium. The present work demonstrates that the exocellular material of Mycobacterium tuberculosis contains large amounts of polysaccharides with only traces, if any at all, of lipids. Three types of polysaccharides were purified by anion-exchange and gel-filtration chromatography; all were found to be neutral compounds devoid of acyl substituents. They consisted of D-glucan, D-arabino-D-mannan and D-mannan, which were eluted from gel-filtration columns in positions corresponding to molecular masses of 123, 13 and 4 kDa respectively. Their predominant structural features were determined by the characterization of the per-O-methyl derivatives of enzymic, acetolysis and Smith-degradation products and by 1H- and 13C-n.m.r. spectroscopy of the purified polysaccharides, using mono- and two-dimensional homonuclear chemical-shift correlated spectroscopy and two-dimensional heteronuclear (1H/13C) spectroscopy. The glucan which represented up to 90% of the polysaccharides was composed of repeating units of five or six-->4-alpha-D-Glcp-1--> residues and a -->4-alpha-D-Glcp substituted at position 6 with an alpha-D-Glcp, indicating a glycogen-like highly branched structure not related to the so-called polysaccharide-II previously identified in tuberculin. The arabinomannan consisted of a mannan segment composed of a -->6-alpha-D-Man-1--> core substituted at some positions 2 with an alpha-D-Manp. The arabinan termini of the arabinomannan were found to be extensively capped with mannosyl residues. The possibility that these polysaccharides contribute to the persistence of the tubercle bacillus in the macrophage by molecular mimicry is discussed. PMID:8297342

Structural features of the exocellular polysaccharides of Mycobacterium tuberculosis.

PubMed

Lemassu, A; Daffé, M

1994-01-15

The cell envelope which surrounds pathogenic mycobacteria is postulated to be a defence barrier against phagocytic cells and its outermost constituents have a tendency to accumulate in the culture medium. The present work demonstrates that the exocellular material of Mycobacterium tuberculosis contains large amounts of polysaccharides with only traces, if any at all, of lipids. Three types of polysaccharides were purified by anion-exchange and gel-filtration chromatography; all were found to be neutral compounds devoid of acyl substituents. They consisted of D-glucan, D-arabino-D-mannan and D-mannan, which were eluted from gel-filtration columns in positions corresponding to molecular masses of 123, 13 and 4 kDa respectively. Their predominant structural features were determined by the characterization of the per-O-methyl derivatives of enzymic, acetolysis and Smith-degradation products and by 1H- and 13C-n.m.r. spectroscopy of the purified polysaccharides, using mono- and two-dimensional homonuclear chemical-shift correlated spectroscopy and two-dimensional heteronuclear (1H/13C) spectroscopy. The glucan which represented up to 90% of the polysaccharides was composed of repeating units of five or six-->4-alpha-D-Glcp-1--> residues and a -->4-alpha-D-Glcp substituted at position 6 with an alpha-D-Glcp, indicating a glycogen-like highly branched structure not related to the so-called polysaccharide-II previously identified in tuberculin. The arabinomannan consisted of a mannan segment composed of a -->6-alpha-D-Man-1--> core substituted at some positions 2 with an alpha-D-Manp. The arabinan termini of the arabinomannan were found to be extensively capped with mannosyl residues. The possibility that these polysaccharides contribute to the persistence of the tubercle bacillus in the macrophage by molecular mimicry is discussed.

Linguistic Features and Schematic Textual Structure in Look-Good Advertisements in the Indian Print Media in English

ERIC Educational Resources Information Center

Singh, Sukhdev; Bedi, Navkiran Kaur

2013-01-01

Every text has a communicative purpose that it performs by dividing itself into generic stages. These stages are assigned specific goals and have differing linguistic structures. This paper makes an attempt to investigate whether there is a definable co-relation between linguistic features and stages in the genre of look-good advertisements. It…

Chinese character recognition based on Gabor feature extraction and CNN

NASA Astrophysics Data System (ADS)

Xiong, Yudian; Lu, Tongwei; Jiang, Yongyuan

2018-03-01

As an important application in the field of text line recognition and office automation, Chinese character recognition has become an important subject of pattern recognition. However, due to the large number of Chinese characters and the complexity of its structure, there is a great difficulty in the Chinese character recognition. In order to solve this problem, this paper proposes a method of printed Chinese character recognition based on Gabor feature extraction and Convolution Neural Network(CNN). The main steps are preprocessing, feature extraction, training classification. First, the gray-scale Chinese character image is binarized and normalized to reduce the redundancy of the image data. Second, each image is convoluted with Gabor filter with different orientations, and the feature map of the eight orientations of Chinese characters is extracted. Third, the feature map through Gabor filters and the original image are convoluted with learning kernels, and the results of the convolution is the input of pooling layer. Finally, the feature vector is used to classify and recognition. In addition, the generalization capacity of the network is improved by Dropout technology. The experimental results show that this method can effectively extract the characteristics of Chinese characters and recognize Chinese characters.

Method to assess the temporal persistence of potential biometric features: Application to oculomotor, gait, face and brain structure databases

PubMed Central

Nixon, Mark S.; Komogortsev, Oleg V.

2017-01-01

We introduce the intraclass correlation coefficient (ICC) to the biometric community as an index of the temporal persistence, or stability, of a single biometric feature. It requires, as input, a feature on an interval or ratio scale, and which is reasonably normally distributed, and it can only be calculated if each subject is tested on 2 or more occasions. For a biometric system, with multiple features available for selection, the ICC can be used to measure the relative stability of each feature. We show, for 14 distinct data sets (1 synthetic, 8 eye-movement-related, 2 gait-related, and 2 face-recognition-related, and one brain-structure-related), that selecting the most stable features, based on the ICC, resulted in the best biometric performance generally. Analyses based on using only the most stable features produced superior Rank-1-Identification Rate (Rank-1-IR) performance in 12 of 14 databases (p = 0.0065, one-tailed), when compared to other sets of features, including the set of all features. For Equal Error Rate (EER), using a subset of only high-ICC features also produced superior performance in 12 of 14 databases (p = 0. 0065, one-tailed). In general, then, for our databases, prescreening potential biometric features, and choosing only highly reliable features yields better performance than choosing lower ICC features or than choosing all features combined. We also determined that, as the ICC of a group of features increases, the median of the genuine similarity score distribution increases and the spread of this distribution decreases. There was no statistically significant similar relationships for the impostor distributions. We believe that the ICC will find many uses in biometric research. In case of the eye movement-driven biometrics, the use of reliable features, as measured by ICC, allowed to us achieve the authentication performance with EER = 2.01%, which was not possible before. PMID:28575030

Method to assess the temporal persistence of potential biometric features: Application to oculomotor, gait, face and brain structure databases.

PubMed

Friedman, Lee; Nixon, Mark S; Komogortsev, Oleg V

2017-01-01

We introduce the intraclass correlation coefficient (ICC) to the biometric community as an index of the temporal persistence, or stability, of a single biometric feature. It requires, as input, a feature on an interval or ratio scale, and which is reasonably normally distributed, and it can only be calculated if each subject is tested on 2 or more occasions. For a biometric system, with multiple features available for selection, the ICC can be used to measure the relative stability of each feature. We show, for 14 distinct data sets (1 synthetic, 8 eye-movement-related, 2 gait-related, and 2 face-recognition-related, and one brain-structure-related), that selecting the most stable features, based on the ICC, resulted in the best biometric performance generally. Analyses based on using only the most stable features produced superior Rank-1-Identification Rate (Rank-1-IR) performance in 12 of 14 databases (p = 0.0065, one-tailed), when compared to other sets of features, including the set of all features. For Equal Error Rate (EER), using a subset of only high-ICC features also produced superior performance in 12 of 14 databases (p = 0. 0065, one-tailed). In general, then, for our databases, prescreening potential biometric features, and choosing only highly reliable features yields better performance than choosing lower ICC features or than choosing all features combined. We also determined that, as the ICC of a group of features increases, the median of the genuine similarity score distribution increases and the spread of this distribution decreases. There was no statistically significant similar relationships for the impostor distributions. We believe that the ICC will find many uses in biometric research. In case of the eye movement-driven biometrics, the use of reliable features, as measured by ICC, allowed to us achieve the authentication performance with EER = 2.01%, which was not possible before.

Non-iridescent Transmissive Structural Color Filter Featuring Highly Efficient Transmission and High Excitation Purity

PubMed Central

Shrestha, Vivek Raj; Lee, Sang-Shin; Kim, Eun-Soo; Choi, Duk-Yong

2014-01-01

Nanostructure based color filtering has been considered an attractive replacement for current colorant pigmentation in the display technologies, in view of its increased efficiencies, ease of fabrication and eco-friendliness. For such structural filtering, iridescence relevant to its angular dependency, which poses a detrimental barrier to the practical development of high performance display and sensing devices, should be mitigated. We report on a non-iridescent transmissive structural color filter, fabricated in a large area of 76.2 × 25.4 mm2, taking advantage of a stack of three etalon resonators in dielectric films based on a high-index cavity in amorphous silicon. The proposed filter features a high transmission above 80%, a high excitation purity of 0.93 and non-iridescence over a range of 160°, exhibiting no significant change in the center wavelength, dominant wavelength and excitation purity, which implies no change in hue and saturation of the output color. The proposed structure may find its potential applications to large-scale display and imaging sensor systems. PMID:24815530

Resolving Transition Metal Chemical Space: Feature Selection for Machine Learning and Structure-Property Relationships.

PubMed

Janet, Jon Paul; Kulik, Heather J

2017-11-22

Machine learning (ML) of quantum mechanical properties shows promise for accelerating chemical discovery. For transition metal chemistry where accurate calculations are computationally costly and available training data sets are small, the molecular representation becomes a critical ingredient in ML model predictive accuracy. We introduce a series of revised autocorrelation functions (RACs) that encode relationships of the heuristic atomic properties (e.g., size, connectivity, and electronegativity) on a molecular graph. We alter the starting point, scope, and nature of the quantities evaluated in standard ACs to make these RACs amenable to inorganic chemistry. On an organic molecule set, we first demonstrate superior standard AC performance to other presently available topological descriptors for ML model training, with mean unsigned errors (MUEs) for atomization energies on set-aside test molecules as low as 6 kcal/mol. For inorganic chemistry, our RACs yield 1 kcal/mol ML MUEs on set-aside test molecules in spin-state splitting in comparison to 15-20× higher errors for feature sets that encode whole-molecule structural information. Systematic feature selection methods including univariate filtering, recursive feature elimination, and direct optimization (e.g., random forest and LASSO) are compared. Random-forest- or LASSO-selected subsets 4-5× smaller than the full RAC set produce sub- to 1 kcal/mol spin-splitting MUEs, with good transferability to metal-ligand bond length prediction (0.004-5 Å MUE) and redox potential on a smaller data set (0.2-0.3 eV MUE). Evaluation of feature selection results across property sets reveals the relative importance of local, electronic descriptors (e.g., electronegativity, atomic number) in spin-splitting and distal, steric effects in redox potential and bond lengths.

A Multi-Scale, Multi-Physics Optimization Framework for Additively Manufactured Structural Components

NASA Astrophysics Data System (ADS)

El-Wardany, Tahany; Lynch, Mathew; Gu, Wenjiong; Hsu, Arthur; Klecka, Michael; Nardi, Aaron; Viens, Daniel

This paper proposes an optimization framework enabling the integration of multi-scale / multi-physics simulation codes to perform structural optimization design for additively manufactured components. Cold spray was selected as the additive manufacturing (AM) process and its constraints were identified and included in the optimization scheme. The developed framework first utilizes topology optimization to maximize stiffness for conceptual design. The subsequent step applies shape optimization to refine the design for stress-life fatigue. The component weight was reduced by 20% while stresses were reduced by 75% and the rigidity was improved by 37%. The framework and analysis codes were implemented using Altair software as well as an in-house loading code. The optimized design was subsequently produced by the cold spray process.

Influence of calcium addition and stirring on the cellular structure and foaming behavior of molten zinc

NASA Astrophysics Data System (ADS)

Hossein Elahi, S.; Arabi Jeshvaghani, R.; Shahverdi, H. R.

2015-05-01

In this paper, the influence of calcium addition and melt stirring on the structure and foaming behavior of molten zinc was investigated. In this regard, zinc foam was produced by Alporas method (in which foam alloy melts and titanium hydride is used as a blowing agent). Optical microscopy and scanning electron microscopy were used to investigate the phase distribution and structure in the foams. Results showed that addition of calcium increased foamability and foam efficiency of the molten zinc. In contrast, stirring had no significant effect on the foaming behavior of the melt. Microstructural examinations indicated that improving the foaming behavior of molten zinc was attributed to the formation of CaZn13 intermetallic phase and ZnO particles in the foam structure, which increased viscosity and reduced drainage rate.

Effect of processing on structural features of anodic aluminum oxides

NASA Astrophysics Data System (ADS)

Erdogan, Pembe; Birol, Yucel

2012-09-01

Morphological features of the anodic aluminum oxide (AAO) templates fabricated by electrochemical oxidation under different processing conditions were investigated. The selection of the polishing parameters does not appear to be critical as long as the aluminum substrate is polished adequately prior to the anodization process. AAO layers with a highly ordered pore distribution are obtained after anodizing in 0.6 M oxalic acid at 20 °C under 40 V for 5 minutes suggesting that the desired pore features are attained once an oxide layer develops on the surface. While the pore features are not affected much, the thickness of the AAO template increases with increasing anodization treatment time. Pore features are better and the AAO growth rate is higher at 20 °C than at 5 °C; higher under 45 V than under 40 V; higher with 0.6 M than with 0.3 M oxalic acid.

Application of alkyne-TCNQ addition reaction to polymerization.

PubMed

Washino, Yusuke; Michinobu, Tsuyoshi

2011-04-19

The polymerization using a high-yielding addition reaction between electron-rich alkynes and 7,7,8,8-tetracyanoquinodimethane (TCNQ) derivatives is described. The bifunctional monomer containing two TCNQ moieties and the counter comonomer bearing two dialkylaniline (DAA)-substituted alkynes are reacted in 1,2-dichloroethane under mild heating conditions. At the high monomer concentrations, high molecular weight linear polymers are obtained, while the reaction at the low monomer concentrations produces a significant amount of the cyclic compounds. A clear relationship between the monomer concentration and the cyclic compound amount is demonstrated. The obtained polymers feature a sufficient thermal stability with the decomposition temperature exceeding 300  °C as well as strong charge-transfer (CT) bands and redox activities ascribed to the produced donor-acceptor moieties. These features are also used to optimize the polymerization conditions and to estimate the chemical structures. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Characterization of Effect of Support Structures in Laser Additive Manufacturing of Stainless Steel

NASA Astrophysics Data System (ADS)

Järvinen, Jukka-Pekka; Matilainen, Ville; Li, Xiaoyun; Piili, Heidi; Salminen, Antti; Mäkelä, Ismo; Nyrhilä, Olli

Laser additive manufacturing (LAM) of stainless steel is a layer wisetechnology for fabricating 3D parts from metal powder via selectively melting powder with laser beam. Support structures play a significant role in LAM process as they help to remove heat away from the process and on the other hand hold the work piece in its place. A successful design of support structures can help to achievea building process fast and inexpensive with high quality. Aimof this study was to characterize the usability of two types of support structures: web and tube supports. Purpose of this studywas also to analyze how suitable they are in two industrial application cases: case for dental application and case for jewelry application. It was concluded that the removability of web supports was much better than tube supports. It was noticed that support structures are an important part of LAM process and they strongly affect the manufacturability and the end quality of the part.

Categorical Structure among Shared Features in Networks of Early-Learned Nouns

ERIC Educational Resources Information Center

Hills, Thomas T.; Maouene, Mounir; Maouene, Josita; Sheya, Adam; Smith, Linda

2009-01-01

The shared features that characterize the noun categories that young children learn first are a formative basis of the human category system. To investigate the potential categorical information contained in the features of early-learned nouns, we examine the graph-theoretic properties of noun-feature networks. The networks are built from the…

Using cuttlefish ink as an additive to produce -non-iridescent structural colors of high color visibility.

PubMed

Zhang, Yafeng; Dong, Biqin; Chen, Ang; Liu, Xiaohan; Shi, Lei; Zi, Jian

2015-08-26

Non-iridescent structural colors of high color visibility are produced by amorphous photonic structures, in which -natural cuttlefish ink is used as an additive to break down the long-range order of the structures. The color hue and its spectral purity can be tuned by adjusting the diameter of the polystyrene (PS) spheres and the proportion of ink particles. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Clavulanic acid production estimation based on color and structural features of Streptomyces clavuligerus bacteria using self-organizing map and genetic algorithm.

PubMed

Nurmohamadi, Maryam; Pourghassem, Hossein

2014-05-01

The utilization of antibiotics produced by Clavulanic acid (CA) is an increasing need in medicine and industry. Usually, the CA is created from the fermentation of Streptomycen Clavuligerus (SC) bacteria. Analysis of visual and morphological features of SC bacteria is an appropriate measure to estimate the growth of CA. In this paper, an automatic and fast CA production level estimation algorithm based on visual and structural features of SC bacteria instead of statistical methods and experimental evaluation by microbiologist is proposed. In this algorithm, structural features such as the number of newborn branches, thickness of hyphal and bacterial density and also color features such as acceptance color levels are extracted from the SC bacteria. Moreover, PH and biomass of the medium provided by microbiologists are considered as specified features. The level of CA production is estimated by using a new application of Self-Organizing Map (SOM), and a hybrid model of genetic algorithm with back propagation network (GA-BPN). The proposed algorithm is evaluated on four carbonic resources including malt, starch, wheat flour and glycerol that had used as different mediums of bacterial growth. Then, the obtained results are compared and evaluated with observation of specialist. Finally, the Relative Error (RE) for the SOM and GA-BPN are achieved 14.97% and 16.63%, respectively. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

How Structure Defines Affinity in Protein-Protein Interactions

PubMed Central

Erijman, Ariel; Rosenthal, Eran; Shifman, Julia M.

2014-01-01

Protein-protein interactions (PPI) in nature are conveyed by a multitude of binding modes involving various surfaces, secondary structure elements and intermolecular interactions. This diversity results in PPI binding affinities that span more than nine orders of magnitude. Several early studies attempted to correlate PPI binding affinities to various structure-derived features with limited success. The growing number of high-resolution structures, the appearance of more precise methods for measuring binding affinities and the development of new computational algorithms enable more thorough investigations in this direction. Here, we use a large dataset of PPI structures with the documented binding affinities to calculate a number of structure-based features that could potentially define binding energetics. We explore how well each calculated biophysical feature alone correlates with binding affinity and determine the features that could be used to distinguish between high-, medium- and low- affinity PPIs. Furthermore, we test how various combinations of features could be applied to predict binding affinity and observe a slow improvement in correlation as more features are incorporated into the equation. In addition, we observe a considerable improvement in predictions if we exclude from our analysis low-resolution and NMR structures, revealing the importance of capturing exact intermolecular interactions in our calculations. Our analysis should facilitate prediction of new interactions on the genome scale, better characterization of signaling networks and design of novel binding partners for various target proteins. PMID:25329579

Image ratio features for facial expression recognition application.

PubMed

Song, Mingli; Tao, Dacheng; Liu, Zicheng; Li, Xuelong; Zhou, Mengchu

2010-06-01

Video-based facial expression recognition is a challenging problem in computer vision and human-computer interaction. To target this problem, texture features have been extracted and widely used, because they can capture image intensity changes raised by skin deformation. However, existing texture features encounter problems with albedo and lighting variations. To solve both problems, we propose a new texture feature called image ratio features. Compared with previously proposed texture features, e.g., high gradient component features, image ratio features are more robust to albedo and lighting variations. In addition, to further improve facial expression recognition accuracy based on image ratio features, we combine image ratio features with facial animation parameters (FAPs), which describe the geometric motions of facial feature points. The performance evaluation is based on the Carnegie Mellon University Cohn-Kanade database, our own database, and the Japanese Female Facial Expression database. Experimental results show that the proposed image ratio feature is more robust to albedo and lighting variations, and the combination of image ratio features and FAPs outperforms each feature alone. In addition, we study asymmetric facial expressions based on our own facial expression database and demonstrate the superior performance of our combined expression recognition system.

Differences in the structural features of atypical adenomatous hyperplasia and low-grade prostatic adenocarcinoma.

PubMed

Midi, Ahmet; Tecimer, Tülay; Bozkurt, Süheyla; Ozkan, Naziye

2008-04-01

Atypical adenomatous hyperplasia (AAH) is a small glandular proliferation that has histological similarities with Gleason grade 1 and 2 prostatic adenocarcinoma (PACG1,2). There are no distinct histomorphological criteria distinguishing these two lesions from each other and other small glandular proliferations. Because treatment approaches are different for these lesions, it is necessary to determine histological criteria. The aim of this study is to review the histological features of these two lesions and to define new histological criteria distinguishing AAH from PACG1,2. We, therefore, assessed 18 anatomical and structural parameters. We found 11 AAH (22 foci) and 15 PACG1,2 (22 foci) cases in 105 radical prostatectomy specimens. Basal cell-specific antikeratin was applied to these lesions. We assumed that PACG1,2 lesions did have not basal cells and we grouped the lesions as AAH and PACG1,2 based on this assumption. We found differences between AAH and PACG1,2 lesions for some parameters including the number of glands, structures such as the main ductus and basal cells. We found similar properties in the two lesions for the following parameters: localization, multiplicity, diameter of the lesion, focus asymmetry, distance between glands, inflammatory cells in and out of the lesions, secretory cell shape on the luminal side, papillary projection towards the luminal side of gland, the shape of the outer gland, the infiltrative pattern of the gland, glandular pleomorphism, biggest gland diameter and median gland diameter. We determined that concurrent evaluation of histomorphological features was important to differentiate between AAH and PACG1,2.

Additional adjoint Monte Carlo studies of the shielding of concrete structures against initial gamma radiation. Final report

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

Beer, M.; Cohen, M.O.

1975-02-01

The adjoint Monte Carlo method previously developed by MAGI has been applied to the calculation of initial radiation dose due to air secondary gamma rays and fission product gamma rays at detector points within buildings for a wide variety of problems. These provide an in-depth survey of structure shielding effects as well as many new benchmark problems for matching by simplified models. Specifically, elevated ring source results were obtained in the following areas: doses at on-and off-centerline detectors in four concrete blockhouse structures; doses at detector positions along the centerline of a high-rise structure without walls; dose mapping at basementmore » detector positions in the high-rise structure; doses at detector points within a complex concrete structure containing exterior windows and walls and interior partitions; modeling of the complex structure by replacing interior partitions by additional material at exterior walls; effects of elevation angle changes; effects on the dose of changes in fission product ambient spectra; and modeling of mutual shielding due to external structures. In addition, point source results yielding dose extremes about the ring source average were obtained. (auth)« less

MEVTV Workshop on Tectonic Features on Mars

NASA Technical Reports Server (NTRS)

Watters, Thomas R. (Editor); Golombek, Matthew P. (Editor)

1989-01-01

The state of knowledge of tectonic features on Mars was determined and kinematic and mechanical models were assessed for their origin. Three sessions were held: wrinkle ridges and compressional structure; strike-slip faults; and extensional structures. Each session began with an overview of the features under discussion. In the case of wrinkle ridges and extensional structures, the overview was followed by keynote addresses by specialists working on similar structures on the Earth. The first session of the workshop focused on the controversy over the relative importance of folding, faulting, and intrusive volcanism in the origin of wrinkle ridges. The session ended with discussions of the origin of compressional flank structures associated with Martian volcanoes and the relationship between the volcanic complexes and the inferred regional stress field. The second day of the workshop began with the presentation and discussion of evidence for strike-slip faults on Mars at various scales. In the last session, the discussion of extensional structures ranged from the origin of grabens, tension cracks, and pit-crater chains to the origin of Valles Marineris canyons. Shear and tensile modes of brittle failure in the formation of extensional features and the role of these failure modes in the formation of pit-crater chains and the canyons of Valles Marineris were debated. The relationship of extensional features to other surface processes, such as carbonate dissolution (karst) were also discussed.

Bio-inspired device: a novel smart MR spring featuring tendril structure

NASA Astrophysics Data System (ADS)

Kaluvan, Suresh; Park, Chun-Yong; Choi, Seung-Bok

2016-01-01

Smart materials such as piezoelectric patches, shape memory alloy, electro and magneto rheological fluid, magnetostrictive materials, etc are involved by far to design intelligent and high performance smart devices like injectors, dental braces, dampers, actuators and sensors. In this paper, an interesting smart device is proposed by inspiring on the structure of the bio climber plant. The key enabling concept of this proposed work is to design the smart spring damper as a helical shaped tendril structure using magneto-rheological (MR) fluid. The proposed smart spring consists of a hollow helical structure filled with MR fluid. The viscosity of the MR fluid decides the damping force of helical shaped smart spring, while the fluid intensity in the vine decides the strength of the tendril in the climber plant. Thus, the proposed smart spring can provide a new concept design of the damper which can be applicable to various damping system industries with tuneable damping force. The proposed smart spring damper has several advantageous such as cost effective, easy implementation compared with the conventional damper. In addition, the proposed spring damper can be easily designed to adapt different damping force levels without any alteration.

Coding of visual object features and feature conjunctions in the human brain.

PubMed

Martinovic, Jasna; Gruber, Thomas; Müller, Matthias M

2008-01-01

Object recognition is achieved through neural mechanisms reliant on the activity of distributed coordinated neural assemblies. In the initial steps of this process, an object's features are thought to be coded very rapidly in distinct neural assemblies. These features play different functional roles in the recognition process--while colour facilitates recognition, additional contours and edges delay it. Here, we selectively varied the amount and role of object features in an entry-level categorization paradigm and related them to the electrical activity of the human brain. We found that early synchronizations (approx. 100 ms) increased quantitatively when more image features had to be coded, without reflecting their qualitative contribution to the recognition process. Later activity (approx. 200-400 ms) was modulated by the representational role of object features. These findings demonstrate that although early synchronizations may be sufficient for relatively crude discrimination of objects in visual scenes, they cannot support entry-level categorization. This was subserved by later processes of object model selection, which utilized the representational value of object features such as colour or edges to select the appropriate model and achieve identification.

Unique Structural Features of Influenza Virus H15 Hemagglutinin

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

Tzarum, Netanel; McBride, Ryan; Nycholat, Corwin M.

Influenza A H15 viruses are members of a subgroup (H7-H10-H15) of group 2 hemagglutinin (HA) subtypes that include H7N9 and H10N8 viruses that were isolated from humans during 2013. The isolation of avian H15 viruses is, however, quite rare and, until recently, geographically restricted to wild shorebirds and waterfowl in Australia. The HAs of H15 viruses contain an insertion in the 150-loop (loop beginning at position 150) of the receptor-binding site common to this subgroup and a unique insertion in the 260-loop compared to any other subtype. Here, we show that the H15 HA has a high preference for avianmore » receptor analogs by glycan array analyses. The H15 HA crystal structure reveals that it is structurally closest to H7N9 HA, but the head domain of the H15 trimer is wider than all other HAs due to a tilt and opening of the HA1 subunits of the head domain. The extended 150-loop of the H15 HA retains the conserved conformation as in H7 and H10 HAs. Furthermore, the elongated 260-loop increases the exposed HA surface and can contribute to antigenic variation in H15 HAs. Since avian-origin H15 HA viruses have been shown to cause enhanced disease in mammalian models, further characterization and immune surveillance of H15 viruses are warranted. IMPORTANCEIn the last 2 decades, an apparent increase has been reported for cases of human infection by emerging avian influenza A virus subtypes, including H7N9 and H10N8 viruses isolated during 2013. H15 is the other member of the subgroup of influenza A virus group 2 hemagglutinins (HAs) that also include H7 and H10. H15 viruses have been restricted to Australia, but recent isolation of H15 viruses in western Siberia suggests that they could be spread more globally via the avian flyways that converge and emanate from this region. Here we report on characterization of the three-dimensional structure and receptor specificity of the H15 hemagglutinin, revealing distinct features and specificities that can aid in global

Interactive effects between N addition and disturbance on boreal forest ecosystem structure and function

NASA Astrophysics Data System (ADS)

Nordin, Annika; Strengbom, Joachim; From, Fredrik

2014-05-01

In management of boreal forests, nitrogen (N) enrichment from atmospheric deposition or from forest fertilization can appear in combination with land-use related disturbances, i.e. tree harvesting by clear-felling. Long-term interactive effects between N enrichment and disturbance on boreal forest ecosystem structure and function are, however, poorly known. We investigated effects of N enrichment by forest fertilization done > 25 years ago on forest understory species composition in old-growth (undisturbed) forests, and in forests clear-felled 10 years ago (disturbed). In clear-felled forests we also investigated effects of the previous N addition on growth of tree saplings. The results show that the N enrichment effect on the understory species composition was strongly dependent on the disturbance caused by clear-felling. In undisturbed forests, there were small or no effects on understory species composition from N addition. In contrast, effects were large in forests first exposed to N addition and subsequently disturbed by clear-felling. Effects of N addition differed among functional groups of plants. Abundance of graminoids increased (+232%) and abundance of dwarf shrubs decreased (-44%) following disturbance in N fertilized forests. For vascular plants, the two perturbations had contrasting effects on α-(within forests) and β-diversity (among forests): in disturbed forests, N addition reduced, or had no effect on α-diversity, while β-diversity increased. For bryophytes, negative effects of disturbance on α-diversity were smaller in N fertilized forests than in forests not fertilized, while neither N addition nor disturbance had any effects on β-diversity. Moreover, sapling growth in forests clear-felled 10 years ago was significantly higher in previously N fertilized forests than in forests not fertilized. Our study show that effects of N addition on plant communities may appear small, short-lived, or even absent until exposed to a disturbance. This

High-resolution AFM structure of DNA G-wires in aqueous solution.

PubMed

Bose, Krishnashish; Lech, Christopher J; Heddi, Brahim; Phan, Anh Tuân

2018-05-17

We investigate the self-assembly of short pieces of the Tetrahymena telomeric DNA sequence d[G 4 T 2 G 4 ] in physiologically relevant aqueous solution using atomic force microscopy (AFM). Wire-like structures (G-wires) of 3.0 nm height with well-defined surface periodic features were observed. Analysis of high-resolution AFM images allowed their classification based on the periodicity of these features. A major species is identified with periodic features of 4.3 nm displaying left-handed ridges or zigzag features on the molecular surface. A minor species shows primarily left-handed periodic features of 2.2 nm. In addition to 4.3 and 2.2 nm ridges, background features with periodicity of 0.9 nm are also observed. Using molecular modeling and simulation, we identify a molecular structure that can explain both the periodicity and handedness of the major G-wire species. Our results demonstrate the potential structural diversity of G-wire formation and provide valuable insight into the structure of higher-order intermolecular G-quadruplexes. Our results also demonstrate how AFM can be combined with simulation to gain insight into biomolecular structure.

Domain alternation and active site remodeling are conserved structural features of ubiquitin E1.

PubMed

Lv, Zongyang; Yuan, Lingmin; Atkison, James H; Aldana-Masangkay, Grace; Chen, Yuan; Olsen, Shaun K

2017-07-21

E1 enzymes for ubiquitin (Ub) and Ub-like modifiers (Ubls) harbor two catalytic activities that are required for Ub/Ubl activation: adenylation and thioester bond formation. Structural studies of the E1 for the Ubl s mall u biquitin-like mo difier (SUMO) revealed a single active site that is transformed by a conformational switch that toggles its competency for catalysis of these two distinct chemical reactions. Although the mechanisms of adenylation and thioester bond formation revealed by SUMO E1 structures are thought to be conserved in Ub E1, there is currently a lack of structural data supporting this hypothesis. Here, we present a structure of Schizosaccharomyces pombe Uba1 in which the second catalytic cysteine half-domain (SCCH domain) harboring the catalytic cysteine has undergone a 106° rotation that results in a completely different network of intramolecular interactions between the SCCH and adenylation domains and translocation of the catalytic cysteine 12 Å closer to the Ub C terminus compared with previous Uba1 structures. SCCH domain alternation is accompanied by conformational changes within the Uba1 adenylation domains that effectively disassemble the adenylation active site. Importantly, the structural and biochemical data suggest that domain alternation and remodeling of the adenylation active site are interconnected and are intrinsic structural features of Uba1 and that the overall structural basis for adenylation and thioester bond formation exhibited by SUMO E1 is indeed conserved in Ub E1. Finally, the mechanistic insights provided by the novel conformational snapshot of Uba1 presented in this study may guide efforts to develop small molecule inhibitors of this critically important enzyme that is an active target for anticancer therapeutics. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Special Features of Structure Formation in Pipes from Medium-Carbon Low-Alloy Steel 32G2F Under Heat Treatment

NASA Astrophysics Data System (ADS)

Stepanov, A. I.; Belikov, S. V.; Musikhin, S. A.; Burmasov, S. P.; Popov, A. A.

2017-03-01

Special features of formation of structure and properties of seamless pipes from medium-carbon low-alloy steel for oil and gas applications are considered and associated with chemical inhomogeneity of the metal of the pipes.

Effects of Al addition on atomic structure of Cu-Zr metallic glass

NASA Astrophysics Data System (ADS)

Li, Feng; Zhang, Huajian; Liu, Xiongjun; Dong, Yuecheng; Yu, Chunyan; Lu, Zhaoping

2018-02-01

The atomic structures of Cu52Zr48 and Cu45Zr48Al7 metallic glasses (MGs) have been studied by molecular dynamic simulations. The results reveal that the molar volume of the Cu45Zr48Al7 MG is smaller than that of the Cu52Zr48 MG, although the size of the Al atom is larger than that of the Cu atom, implying an enhanced atomic packing density achieved by introducing Al into the ternary MG. Bond shortening in unlike atomic pairs Zr-Al and Cu-Al is observed in the Cu45Zr48Al7 MG, which is attributed to strong interactions between Al and (Zr, Cu) atoms. Meanwhile, the atomic packing efficiency is enhanced by the minor addition of Al. Compared with the Cu52Zr48 binary MG, the potential energy of the ternary MG decreases and the glass transition temperature increases. Structural analyses indicate that more Cu- and Al-centered full icosahedral clusters emerge in the Cu45Zr48Al7 MG as some Cu atoms are substituted by Al. Furthermore, the addition of Al leads to more icosahedral medium-range orders in the ternary MG. The increase of full icosahedral clusters and the enhancement of the packing density are responsible for the improved glass-forming ability of Cu45Zr48Al7.

Low-Velocity Impact Behavior of Sandwich Structures with Additively Manufactured Polymer Lattice Cores

NASA Astrophysics Data System (ADS)

Turner, Andrew J.; Al Rifaie, Mohammed; Mian, Ahsan; Srinivasan, Raghavan

2018-05-01

Sandwich panel structures are widely used in aerospace, marine, and automotive applications because of their high flexural stiffness, strength-to-weight ratio, good vibration damping, and low through-thickness thermal conductivity. These structures consist of solid face sheets and low-density cellular core structures, which are traditionally based upon honeycomb folded-sheet topologies. The recent advances in additive manufacturing (AM) or 3D printing process allow lattice core configurations to be designed with improved mechanical properties. In this work, the sandwich core is comprised of lattice truss structures (LTS). Two different LTS designs are 3D-printed using acrylonitrile butadiene styrene (ABS) and are tested under low-velocity impact loads. The absorption energy and the failure mechanisms of lattice cells under such loads are investigated. The differences in energy-absorption capabilities are captured by integrating the load-displacement curve found from the impact response. It is observed that selective placement of vertical support struts in the unit-cell results in an increase in the absorption energy of the sandwich panels.

Low-Velocity Impact Behavior of Sandwich Structures with Additively Manufactured Polymer Lattice Cores

NASA Astrophysics Data System (ADS)

Turner, Andrew J.; Al Rifaie, Mohammed; Mian, Ahsan; Srinivasan, Raghavan

2018-04-01

Sandwich panel structures are widely used in aerospace, marine, and automotive applications because of their high flexural stiffness, strength-to-weight ratio, good vibration damping, and low through-thickness thermal conductivity. These structures consist of solid face sheets and low-density cellular core structures, which are traditionally based upon honeycomb folded-sheet topologies. The recent advances in additive manufacturing (AM) or 3D printing process allow lattice core configurations to be designed with improved mechanical properties. In this work, the sandwich core is comprised of lattice truss structures (LTS). Two different LTS designs are 3D-printed using acrylonitrile butadiene styrene (ABS) and are tested under low-velocity impact loads. The absorption energy and the failure mechanisms of lattice cells under such loads are investigated. The differences in energy-absorption capabilities are captured by integrating the load-displacement curve found from the impact response. It is observed that selective placement of vertical support struts in the unit-cell results in an increase in the absorption energy of the sandwich panels.

Shape Adaptive, Robust Iris Feature Extraction from Noisy Iris Images

PubMed Central

Ghodrati, Hamed; Dehghani, Mohammad Javad; Danyali, Habibolah

2013-01-01

In the current iris recognition systems, noise removing step is only used to detect noisy parts of the iris region and features extracted from there will be excluded in matching step. Whereas depending on the filter structure used in feature extraction, the noisy parts may influence relevant features. To the best of our knowledge, the effect of noise factors on feature extraction has not been considered in the previous works. This paper investigates the effect of shape adaptive wavelet transform and shape adaptive Gabor-wavelet for feature extraction on the iris recognition performance. In addition, an effective noise-removing approach is proposed in this paper. The contribution is to detect eyelashes and reflections by calculating appropriate thresholds by a procedure called statistical decision making. The eyelids are segmented by parabolic Hough transform in normalized iris image to decrease computational burden through omitting rotation term. The iris is localized by an accurate and fast algorithm based on coarse-to-fine strategy. The principle of mask code generation is to assign the noisy bits in an iris code in order to exclude them in matching step is presented in details. An experimental result shows that by using the shape adaptive Gabor-wavelet technique there is an improvement on the accuracy of recognition rate. PMID:24696801

Shape adaptive, robust iris feature extraction from noisy iris images.

PubMed

Ghodrati, Hamed; Dehghani, Mohammad Javad; Danyali, Habibolah

2013-10-01

In the current iris recognition systems, noise removing step is only used to detect noisy parts of the iris region and features extracted from there will be excluded in matching step. Whereas depending on the filter structure used in feature extraction, the noisy parts may influence relevant features. To the best of our knowledge, the effect of noise factors on feature extraction has not been considered in the previous works. This paper investigates the effect of shape adaptive wavelet transform and shape adaptive Gabor-wavelet for feature extraction on the iris recognition performance. In addition, an effective noise-removing approach is proposed in this paper. The contribution is to detect eyelashes and reflections by calculating appropriate thresholds by a procedure called statistical decision making. The eyelids are segmented by parabolic Hough transform in normalized iris image to decrease computational burden through omitting rotation term. The iris is localized by an accurate and fast algorithm based on coarse-to-fine strategy. The principle of mask code generation is to assign the noisy bits in an iris code in order to exclude them in matching step is presented in details. An experimental result shows that by using the shape adaptive Gabor-wavelet technique there is an improvement on the accuracy of recognition rate.

Effect of nitrogen addition on the structural, electrical, and optical properties of In-Sn-Zn oxide thin films

NASA Astrophysics Data System (ADS)

Jia, Junjun; Torigoshi, Yoshifumi; Suko, Ayaka; Nakamura, Shin-ichi; Kawashima, Emi; Utsuno, Futoshi; Shigesato, Yuzo

2017-02-01

Indium-tin-zinc oxide (ITZO) films were deposited at various nitrogen flow ratios using magnetron sputtering. At a nitrogen flow ratio of 40%, the structure of ITZO film changed from amorphous, with a short-range-ordered In2O3 phase, to a c-axis oriented InN polycrystalline phase, where InN starts to nucleate from an amorphous In2O3 matrix. Whereas, nitrogen addition had no obvious effect on the structure of indium-gallium-zinc oxide (IGZO) films even at a nitrogen flow ratio of 100%. Nitrogen addition also suppressed the formation of oxygen-related vacancies in ITZO films when the nitrogen flow ratio was less than 20%, and higher nitrogen addition led to an increase in carrier density. Moreover, a red-shift in the optical band edge was observed as the nitrogen flow ratio increased, which could be attributed to the generation of InN crystallites. We anticipate that the present findings demonstrating nitrogen-addition induced structural changes can help to understand the environment-dependent instability in amorphous IGZO or ITZO based thin-film transistors (TFTs).

Flexible feature interface for multimedia sources

DOEpatents

Coffland, Douglas R [Livermore, CA

2009-06-09

A flexible feature interface for multimedia sources system that includes a single interface for the addition of features and functions to multimedia sources and for accessing those features and functions from remote hosts. The interface utilizes the export statement: export "C" D11Export void FunctionName(int argc, char ** argv,char * result, SecureSession *ctrl) or the binary equivalent of the export statement.

Guilt by Association: The 13 micron Dust Feature in Circumstellar Shells and Related Spectral Features

NASA Astrophysics Data System (ADS)

Sloan, G. C.; Kraemer, K. E.; Goebel, J. H.; Price, S. D.

A study of spectra from the SWS on ISO of optically thin oxygen-rich dust shells shows that the strength of the 13 micron dust emission feature is correlated with the CO2 bands (13--17 microns) and dust emission features at 19.8 and 28.1 microns. SRb variables tend to show stronger 13 micron features than Mira variables, suggesting that the presence of the 13 micron and related features depends on pulsation mode and mass-loss rate. The absence of any correlation to dust emission features at 16.8 and 32 microns makes spinel an unlikely carrier. The most plausible carrier of the 13 micron feature remains crystalline alumina, and we suggest that the related dust features may be crystalline silicates. When dust forms in regions of low density, it may condense into crystalline grain structures.

Robust feature tracking for endoscopic pose estimation and structure recovery

NASA Astrophysics Data System (ADS)

Speidel, S.; Krappe, S.; Röhl, S.; Bodenstedt, S.; Müller-Stich, B.; Dillmann, R.

2013-03-01

Minimally invasive surgery is a highly complex medical discipline with several difficulties for the surgeon. To alleviate these difficulties, augmented reality can be used for intraoperative assistance. For visualization, the endoscope pose must be known which can be acquired with a SLAM (Simultaneous Localization and Mapping) approach using the endoscopic images. In this paper we focus on feature tracking for SLAM in minimally invasive surgery. Robust feature tracking and minimization of false correspondences is crucial for localizing the endoscope. As sensory input we use a stereo endoscope and evaluate different feature types in a developed SLAM framework. The accuracy of the endoscope pose estimation is validated with synthetic and ex vivo data. Furthermore we test the approach with in vivo image sequences from da Vinci interventions.

On The Development of Additive Construction Technologies for Application to Development of Lunar/Martian Surface Structures Using In-Situ Materials

NASA Technical Reports Server (NTRS)

Werkheiser, Niki; Fiske, Michael; Edmunson, Jennifer; Khoshnevis, Behrokh

2015-01-01

For long-duration missions on other planetary bodies, the use of in-situ materials will become increasingly critical. As man's presence on these bodies expands, so must the breadth of the structures required to accommodate them including habitats, laboratories, berms, radiation shielding for natural radiation and surface reactors, garages, solar storm shelters, greenhouses, etc. Planetary surface structure manufacturing and assembly technologies that incorporate in-situ resources provide options for autonomous, affordable, pre-positioned environments with radiation shielding features and protection from micrometeorites, exhaust plume debris, and other hazards. This is important because gamma and particle radiation constitute a serious but reducible threat to long-term survival of human beings, electronics, and other materials in space environments. Also, it is anticipated that surface structures will constitute the primary mass element of lunar or Martian launch requirements. The ability to use in-situ materials to construct these structures will provide a benefit in the reduction of up-mass that would otherwise make long-term Moon or Mars structures cost prohibitive. The ability to fabricate structures in situ brings with it the ability to repair these structures, which allows for self-sufficiency necessary for long-duration habitation. Previously, under the auspices of the MSFC In Situ Fabrication and Repair (ISFR) project and more recently, under the joint MSFC/KSC Additive Construction with Mobile Emplacement (ACME) project, the MSFC Surface Structures Group has been developing materials and construction technologies to support future planetary habitats with in situ resources. One such technology, known as Contour Crafting (additive construction), is shown in Figure 1, along with a typical structure fabricated using this technology. This paper will present the results to date of these efforts, including development of novel nozzle concepts for advanced layer

AQUATOX Features and Tools

EPA Pesticide Factsheets

Numerous features have been included to facilitate the modeling process, from model setup and data input, presentation and analysis of results, to easy export of results to spreadsheet programs for additional analysis.

Differences in the structural features of atypical adenomatous hyperplasia and low-grade prostatic adenocarcinoma

PubMed Central

Midi, Ahmet; Tecimer, Tülay; Bozkurt, Süheyla; Özkan, Naziye

2008-01-01

Aim Atypical adenomatous hyperplasia (AAH) is a small glandular proliferation that has histological similarities with Gleason grade 1 and 2 prostatic adenocarcinoma (PACG1,2). There are no distinct histomorphological criteria distinguishing these two lesions from each other and other small glandular proliferations. Because treatment approaches are different for these lesions, it is necessary to determine histological criteria. The aim of this study is to review the histological features of these two lesions and to define new histological criteria distinguishing AAH from PACG1,2. We, therefore, assessed 18 anatomical and structural parameters. Materials and Methods We found 11 AAH (22 foci) and 15 PACG1,2 (22 foci) cases in 105 radical prostatectomy specimens. Basal cell-specific antikeratin was applied to these lesions. We assumed that PACG1,2 lesions did have not basal cells and we grouped the lesions as AAH and PACG1,2 based on this assumption. Results We found differences between AAH and PACG1,2 lesions for some parameters including the number of glands, structures such as the main ductus and basal cells. We found similar properties in the two lesions for the following parameters: localization, multiplicity, diameter of the lesion, focus asymmetry, distance between glands, inflammatory cells in and out of the lesions, secretory cell shape on the luminal side, papillary projection towards the luminal side of gland, the shape of the outer gland, the infiltrative pattern of the gland, glandular pleomorphism, biggest gland diameter and median gland diameter. Conclusion We determined that concurrent evaluation of histomorphological features was important to differentiate between AAH and PACG1,2. PMID:19468392

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

System Complexity Reduction via Feature Selection

ERIC Educational Resources Information Center

Deng, Houtao

2011-01-01

This dissertation transforms a set of system complexity reduction problems to feature selection problems. Three systems are considered: classification based on association rules, network structure learning, and time series classification. Furthermore, two variable importance measures are proposed to reduce the feature selection bias in tree…

Mechanical characterization of structurally porous biomaterials built via additive manufacturing: experiments, predictive models, and design maps for load-bearing bone replacement implants.

PubMed

Melancon, D; Bagheri, Z S; Johnston, R B; Liu, L; Tanzer, M; Pasini, D

2017-11-01

Porous biomaterials can be additively manufactured with micro-architecture tailored to satisfy the stringent mechano-biological requirements imposed by bone replacement implants. In a previous investigation, we introduced structurally porous biomaterials, featuring strength five times stronger than commercially available porous materials, and confirmed their bone ingrowth capability in an in vivo canine model. While encouraging, the manufactured biomaterials showed geometric mismatches between their internal porous architecture and that of its as-designed counterpart, as well as discrepancies between predicted and tested mechanical properties, issues not fully elucidated. In this work, we propose a systematic approach integrating computed tomography, mechanical testing, and statistical analysis of geometric imperfections to generate statistical based numerical models of high-strength additively manufactured porous biomaterials. The method is used to develop morphology and mechanical maps that illustrate the role played by pore size, porosity, strut thickness, and topology on the relations governing their elastic modulus and compressive yield strength. Overall, there are mismatches between the mechanical properties of ideal-geometry models and as-manufactured porous biomaterials with average errors of 49% and 41% respectively for compressive elastic modulus and yield strength. The proposed methodology gives more accurate predictions for the compressive stiffness and the compressive strength properties with a reduction of the average error to 11% and 7.6%. The implications of the results and the methodology here introduced are discussed in the relevant biomechanical and clinical context, with insight that highlights promises and limitations of additively manufactured porous biomaterials for load-bearing bone replacement implants. In this work, we perform mechanical characterization of load-bearing porous biomaterials for bone replacement over their entire design

Synergistic influence of Al, Ni, Bi and Sn addition to a zinc bath upon growth kinetics and the structure of coatings

NASA Astrophysics Data System (ADS)

Kania, H.; Liberski, P.

2012-05-01

In this article the authors have analysed the current knowledge about the influence of alloy additions used in galvanizing baths. The optimum concentration of Al, Ni, Bi and Sn addition has been established. Some tests have been conducted to determine the synergistic effect of the addition of AlNiBiSn to a zinc bath upon the structure and growth kinetics of coatings. The structure of the coatings obtained on steel with low silicon contents and on Sandelin steel as well as their chemical composition have been revealed. It has been established that the addition of AlNiBiSn helps to reduce excessive growth of coating on Sandelin steel. The chemical composition and the structure of the coating on Sandelin steel are similar to the chemical composition and structure obtained on steel with regular silicon contents.

Features of optical surfaces of multifocal diffractive-refractive eye lenses

NASA Astrophysics Data System (ADS)

Lenkova, G. A.

2017-09-01

This paper considers shape features of the surface structures of multifocal intraocular lenses (IOLs), which, unlike bifocal IOLs, generate additional foci or extends the depth of focus, which not only corrects near and far vision but also provides good vision at intermediate distances. Expansion of the field of clear vision is achieved due to the effects of diffraction, interference, and refraction (change in the radius of curvature of the lens surface). The optical characteristics of the most famous multifocal IOLs (trifocal and quadrafocal lenses and lenses with extended focal area) are given.

Structural Features of the Western Taiwan Foreland Basin in the Eastern Taiwan Strait since Late Miocene

NASA Astrophysics Data System (ADS)

WANG, J. H.; Liu, C. S.; Chang, J. H.; Yang, E. Y.

2017-12-01

The western Taiwan Foreland Basin lies on the eastern part of Taiwan Strait. The structures in this region are dominated by crustal stretch and a series of flexural normal faults have been developed since Late Miocene owing to the flexural of Eurasia Plate. Through deciphering multi-channel seismic data and drilling data, these flexural features are observed in the offshore Changhua coastal area. The flexure normal faults are important features to realize structural activity in the western Taiwan Foreland Basin. Yang et al. (2016) mention that the reactivated normal faults are found north of the Zhushuixi estuary. It should be a significant issue to decipher whether these faults are still active. In this study, we have analyzed all the available seismic reflections profiles in the central part of the Taiwan Strait, and have observed many pre-Pliocene normal faults that are mainly distributed in the middle of the Taiwan Strait to Changyun Rise, and we tentatively suggest that the formation of these faults may be associated with the formation of the foreland basal unconformity. Furthermore, we will map the distribution of these normal faults and examine whether the reactivated normal faults have extended to south of the Zhushuixi estuary. Finally, we discuss the relation between the reactivated normal faults in the Taiwan Strait and those faults onshore. Key words: Multichannel seismic reflection profile, Taiwan Strait, Foreland basin, normal fault.

Dedifferentiated Liposarcoma With Epithelioid/Epithelial Features.

PubMed

Makise, Naohiro; Yoshida, Akihiko; Komiyama, Motokiyo; Nakatani, Fumihiko; Yonemori, Kan; Kawai, Akira; Fukayama, Masashi; Hiraoka, Nobuyoshi

2017-11-01

Dedifferentiated liposarcoma (DDLPS) demonstrates a variety of growth patterns, and their histologic resemblance to other spindle cell mesenchymal tumors has been widely recognized. However, epithelioid morphology in DDLPS has only rarely been documented. Here, we report 6 cases of DDLPS with striking epithelioid/epithelial features. The patients were 5 men and 1 woman with a median age of 61 years. All tumors were located in the internal trunk. During follow-up of 1 to 41 months, local recurrence, distant metastases, and tumor-related death occurred in 4, 2, and 4 patients, respectively. Beside well-differentiated liposarcoma component and conventional high-grade spindle cell morphology, all tumors focally exhibited growth comprising small or large epithelioid cells in diffuse or sheet-like proliferation. Rhabdoid cells were present in 2 cases. All 5 tumors tested harbored MDM2 amplification. Cytokeratin and/or epithelial membrane antigen were at least focally positive in all 5 tumors tested. One case contained a small focus of novel heterologous epithelial differentiation with acinar structures, wherein cytokeratin, MOC31, and claudin-4 were diffusely expressed and H3K27me3 expression was lost. DDLPS with epithelioid/epithelial features may lead to misdiagnosis of carcinoma or mesothelioma, and their diagnosis should be based on correlation with clinicopathologic and molecular findings. The epithelioid morphology in DDLPS may suggest an aggressive behavior based on this small series. In addition, we document 2 cases of MDM2-amplified undifferentiated neoplasm with epithelioid features in the internal trunk that lacked association with well-differentiated liposarcoma histology and showed rapid clinical course. Whether these latter tumors belong to DDLPS with epithelioid features requires further study.

Face recognition algorithm using extended vector quantization histogram features.

PubMed

Yan, Yan; Lee, Feifei; Wu, Xueqian; Chen, Qiu

2018-01-01

In this paper, we propose a face recognition algorithm based on a combination of vector quantization (VQ) and Markov stationary features (MSF). The VQ algorithm has been shown to be an effective method for generating features; it extracts a codevector histogram as a facial feature representation for face recognition. Still, the VQ histogram features are unable to convey spatial structural information, which to some extent limits their usefulness in discrimination. To alleviate this limitation of VQ histograms, we utilize Markov stationary features (MSF) to extend the VQ histogram-based features so as to add spatial structural information. We demonstrate the effectiveness of our proposed algorithm by achieving recognition results superior to those of several state-of-the-art methods on publicly available face databases.

Cathodoluminescence studies of chevron features in semi-polar (11 2 ¯ 2 ) InGaN/GaN multiple quantum well structures

NASA Astrophysics Data System (ADS)

Brasser, C.; Bruckbauer, J.; Gong, Y.; Jiu, L.; Bai, J.; Warzecha, M.; Edwards, P. R.; Wang, T.; Martin, R. W.

2018-05-01

Epitaxial overgrowth of semi-polar III-nitride layers and devices often leads to arrowhead-shaped surface features, referred to as chevrons. We report on a study into the optical, structural, and electrical properties of these features occurring in two very different semi-polar structures, a blue-emitting multiple quantum well structure, and an amber-emitting light-emitting diode. Cathodoluminescence (CL) hyperspectral imaging has highlighted shifts in their emission energy, occurring in the region of the chevron. These variations are due to different semi-polar planes introduced in the chevron arms resulting in a lack of uniformity in the InN incorporation across samples, and the disruption of the structure which could cause a narrowing of the quantum wells (QWs) in this region. Atomic force microscopy has revealed that chevrons can penetrate over 150 nm into the sample and quench light emission from the active layers. The dominance of non-radiative recombination in the chevron region was exposed by simultaneous measurement of CL and the electron beam-induced current. Overall, these results provide an overview of the nature and impact of chevrons on the luminescence of semi-polar devices.

Robust Feature Matching in Terrestrial Image Sequences

NASA Astrophysics Data System (ADS)

Abbas, A.; Ghuffar, S.

2018-04-01

From the last decade, the feature detection, description and matching techniques are most commonly exploited in various photogrammetric and computer vision applications, which includes: 3D reconstruction of scenes, image stitching for panoramic creation, image classification, or object recognition etc. However, in terrestrial imagery of urban scenes contains various issues, which include duplicate and identical structures (i.e. repeated windows and doors) that cause the problem in feature matching phase and ultimately lead to failure of results specially in case of camera pose and scene structure estimation. In this paper, we will address the issue related to ambiguous feature matching in urban environment due to repeating patterns.

Self-Assembling Block Copolymer Resist Mixtures towards Lithographic Resists for Sub-10 nm Features

NASA Astrophysics Data System (ADS)

Chandler, Curran; Daga, Vikram; Watkins, James

2009-03-01

Significant improvements in 193 nm photolithography have enabled the extension of device feature sizes beyond the 45 nm and 32 nm nodes, yet uncertainty lies beyond 22 nm features as no single replacement has emerged. Here we show that low molecular weight, nonionic block copolymer surfactant blends are capable of self-assembling into highly ordered domains with feature sizes on the order of 5 nm. These surfactants, most of which lack the required χN for microphase separation on their own, exhibit strong segregation and long-range order upon addition of a component capable of multi-point hydrogen bonding that is specific for one of the blocks in the copolymer. This has been demonstrated by our SAXS data for several Pluronic (PEO-b-PPO-b-PEO) and Brij (PEO-b-[CH2]nCH3) surfactants of various molecular weights and PEO volume fractions. Furthermore, we employ these highly-ordered systems as thin film, nanolithographic etch masks for the transfer of sub-10 nm patterns into silicon-based substrates. Small molecule, hydrogen bonding additives containing aromatic or silsesquioxane structure are also used to tune etch contrast between the blocks which is important for reducing line edge roughness (LER) of such small features.

Vessel Classification in Cosmo-Skymed SAR Data Using Hierarchical Feature Selection

NASA Astrophysics Data System (ADS)

Makedonas, A.; Theoharatos, C.; Tsagaris, V.; Anastasopoulos, V.; Costicoglou, S.

2015-04-01

SAR based ship detection and classification are important elements of maritime monitoring applications. Recently, high-resolution SAR data have opened new possibilities to researchers for achieving improved classification results. In this work, a hierarchical vessel classification procedure is presented based on a robust feature extraction and selection scheme that utilizes scale, shape and texture features in a hierarchical way. Initially, different types of feature extraction algorithms are implemented in order to form the utilized feature pool, able to represent the structure, material, orientation and other vessel type characteristics. A two-stage hierarchical feature selection algorithm is utilized next in order to be able to discriminate effectively civilian vessels into three distinct types, in COSMO-SkyMed SAR images: cargos, small ships and tankers. In our analysis, scale and shape features are utilized in order to discriminate smaller types of vessels present in the available SAR data, or shape specific vessels. Then, the most informative texture and intensity features are incorporated in order to be able to better distinguish the civilian types with high accuracy. A feature selection procedure that utilizes heuristic measures based on features' statistical characteristics, followed by an exhaustive research with feature sets formed by the most qualified features is carried out, in order to discriminate the most appropriate combination of features for the final classification. In our analysis, five COSMO-SkyMed SAR data with 2.2m x 2.2m resolution were used to analyse the detailed characteristics of these types of ships. A total of 111 ships with available AIS data were used in the classification process. The experimental results show that this method has good performance in ship classification, with an overall accuracy reaching 83%. Further investigation of additional features and proper feature selection is currently in progress.

Temporal evolution of ion spectral structures during a geomagnetic storm: Observations and modeling

NASA Astrophysics Data System (ADS)

Ferradas, C.; Zhang, J.; Spence, H. E.; Kistler, L. M.; Larsen, B.; Reeves, G. D.; Skoug, R. M.; Funsten, H. O.

2016-12-01

During the last decades several missions have recorded the presence of dynamic spectral features of energetic ions in the inner magnetosphere. We present a case study of the temporal evolution of H+, He+, and O+ spectral structures throughout the geomagnetic storm of 2 October 2013. We use data from the Helium, Oxygen, Proton, and Electron (HOPE) mass spectrometer onboard Van Allen Probe A to analyze the spectral structures in the energy range of 1- 50 keV. We find that the characteristics of the ion structures follow a cyclic pattern, the observed features changing dramatically as the storm starts and then returning to its initial pre-storm state. Quiet, pre-storm times are characterized by multiple and often complex flux structures at narrow energy bands. During the storm main phase, the observed features become simple, with no nose structures or only one nose structure present in the energy-time spectrograms. As the inner magnetosphere recovers from the storm, more complex structures appear once again. Additionally, the heavy ion spectral features are generally more complex than the H+ features, with multiple noses being observed more often in the heavy ion spectra. We use a model of ion drift and losses due to charge exchange to understand the formation of the spectral features and their species dependence.

Common hydraulic fracturing fluid additives alter the structure and function of anaerobic microbial communities

USGS Publications Warehouse

Mumford, Adam C.; Akob, Denise M.; Klinges, J. Grace; Cozzarelli, Isabelle M.

2018-01-01

The development of unconventional oil and gas (UOG) resources results in the production of large volumes of wastewater containing a complex mixture of hydraulic fracturing chemical additives and components from the formation. The release of these wastewaters into the environment poses potential risks that are poorly understood. Microbial communities in stream sediments form the base of the food chain and may serve as sentinels for changes in stream health. Iron-reducing organisms have been shown to play a role in the biodegradation of a wide range of organic compounds, and so to evaluate their response to UOG wastewater, we enriched anaerobic microbial communities from sediments collected upstream (background) and downstream (impacted) of an UOG wastewater injection disposal facility in the presence of hydraulic fracturing fluid (HFF) additives: guar gum, ethylene glycol, and two biocides, 2,2-dibromo-3-nitrilopropionamide (DBNPA) and bronopol (C3H6BrNO4). Iron reduction was significantly inhibited early in the incubations with the addition of biocides, whereas amendment with guar gum and ethylene glycol stimulated iron reduction relative to levels in the unamended controls. Changes in the microbial community structure were observed across all treatments, indicating the potential for even small amounts of UOG wastewater components to influence natural microbial processes. The microbial community structure differed between enrichments with background and impacted sediments, suggesting that impacted sediments may have been preconditioned by exposure to wastewater. These experiments demonstrated the potential for biocides to significantly decrease iron reduction rates immediately following a spill and demonstrated how microbial communities previously exposed to UOG wastewater may be more resilient to additional spills.

Bayesian structured additive regression modeling of epidemic data: application to cholera

PubMed Central

2012-01-01

Background A significant interest in spatial epidemiology lies in identifying associated risk factors which enhances the risk of infection. Most studies, however, make no, or limited use of the spatial structure of the data, as well as possible nonlinear effects of the risk factors. Methods We develop a Bayesian Structured Additive Regression model for cholera epidemic data. Model estimation and inference is based on fully Bayesian approach via Markov Chain Monte Carlo (MCMC) simulations. The model is applied to cholera epidemic data in the Kumasi Metropolis, Ghana. Proximity to refuse dumps, density of refuse dumps, and proximity to potential cholera reservoirs were modeled as continuous functions; presence of slum settlers and population density were modeled as fixed effects, whereas spatial references to the communities were modeled as structured and unstructured spatial effects. Results We observe that the risk of cholera is associated with slum settlements and high population density. The risk of cholera is equal and lower for communities with fewer refuse dumps, but variable and higher for communities with more refuse dumps. The risk is also lower for communities distant from refuse dumps and potential cholera reservoirs. The results also indicate distinct spatial variation in the risk of cholera infection. Conclusion The study highlights the usefulness of Bayesian semi-parametric regression model analyzing public health data. These findings could serve as novel information to help health planners and policy makers in making effective decisions to control or prevent cholera epidemics. PMID:22866662

Inhalation TTC values: A new integrative grouping approach considering structural, toxicological and mechanistic features.

PubMed

Tluczkiewicz, I; Kühne, R; Ebert, R-U; Batke, M; Schüürmann, G; Mangelsdorf, I; Escher, S E

2016-07-01

The present publication describes an integrative grouping concept to derive threshold values for inhalation exposure. The classification scheme starts with differences in toxicological potency and develops criteria to group compounds into two potency classes, namely toxic (T-group) or low toxic (L-group). The TTC concept for inhalation exposure is based on the TTC RepDose data set, consisting of 296 organic compounds with 608 repeated-dose inhalation studies. Initially, 21 structural features (SFs) were identified as being characteristic for compounds of either high or low NOEC values (Schüürmann et al., 2016). In subsequent analyses these SF groups were further refined by taking into account structural homogeneity, type of toxicological effect observed, differences in absorption, metabolism and mechanism of action (MoA), to better define their structural and toxicological boundaries. Differentiation of a local or systemic mode of action did not improve the classification scheme. Finally, 28 groups were discriminated: 19 T-groups and 9 L-groups. Clearly distinct thresholds were derived for the T- and L-toxicity groups, being 2 × 10(-5) ppm (2 μg/person/day) and 0.05 ppm (4260 μg/person/day), respectively. The derived thresholds and the classification are compared to the initial mainly structure driven grouping (Schüürmann et al., 2016) and to the Cramer classification. Copyright © 2016 Elsevier Inc. All rights reserved.

Automatic segmentation of solitary pulmonary nodules based on local intensity structure analysis and 3D neighborhood features in 3D chest CT images

NASA Astrophysics Data System (ADS)

Chen, Bin; Kitasaka, Takayuki; Honma, Hirotoshi; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi; Mori, Kensaku

2012-03-01

This paper presents a solitary pulmonary nodule (SPN) segmentation method based on local intensity structure analysis and neighborhood feature analysis in chest CT images. Automated segmentation of SPNs is desirable for a chest computer-aided detection/diagnosis (CAS) system since a SPN may indicate early stage of lung cancer. Due to the similar intensities of SPNs and other chest structures such as blood vessels, many false positives (FPs) are generated by nodule detection methods. To reduce such FPs, we introduce two features that analyze the relation between each segmented nodule candidate and it neighborhood region. The proposed method utilizes a blob-like structure enhancement (BSE) filter based on Hessian analysis to augment the blob-like structures as initial nodule candidates. Then a fine segmentation is performed to segment much more accurate region of each nodule candidate. FP reduction is mainly addressed by investigating two neighborhood features based on volume ratio and eigenvector of Hessian that are calculates from the neighborhood region of each nodule candidate. We evaluated the proposed method by using 40 chest CT images, include 20 standard-dose CT images that we randomly chosen from a local database and 20 low-dose CT images that were randomly chosen from a public database: LIDC. The experimental results revealed that the average TP rate of proposed method was 93.6% with 12.3 FPs/case.

Predicting the occurrence of wildfires with binary structured additive regression models.

PubMed

Ríos-Pena, Laura; Kneib, Thomas; Cadarso-Suárez, Carmen; Marey-Pérez, Manuel

2017-02-01

Wildfires are one of the main environmental problems facing societies today, and in the case of Galicia (north-west Spain), they are the main cause of forest destruction. This paper used binary structured additive regression (STAR) for modelling the occurrence of wildfires in Galicia. Binary STAR models are a recent contribution to the classical logistic regression and binary generalized additive models. Their main advantage lies in their flexibility for modelling non-linear effects, while simultaneously incorporating spatial and temporal variables directly, thereby making it possible to reveal possible relationships among the variables considered. The results showed that the occurrence of wildfires depends on many covariates which display variable behaviour across space and time, and which largely determine the likelihood of ignition of a fire. The joint possibility of working on spatial scales with a resolution of 1 × 1 km cells and mapping predictions in a colour range makes STAR models a useful tool for plotting and predicting wildfire occurrence. Lastly, it will facilitate the development of fire behaviour models, which can be invaluable when it comes to drawing up fire-prevention and firefighting plans. Copyright © 2016 Elsevier Ltd. All rights reserved.

Contrasting effects of landscape features on genetic structure in different geographic regions in the ornate dragon lizard, Ctenophorus ornatus.

PubMed

Levy, Esther; Tomkins, Joseph L; Lebas, Natasha R; Kennington, W Jason

2013-08-01

Habitat fragmentation can have profound effects on the distribution of genetic variation within and between populations. Previously, we showed that in the ornate dragon lizard, Ctenophorus ornatus, lizards residing on outcrops that are separated by cleared agricultural land are significantly more isolated and hold less genetic variation than lizards residing on neighbouring outcrops connected by undisturbed native vegetation. Here, we extend the fine-scale study to examine the pattern of genetic variation and population structure across the species' range. Using a landscape genetics approach, we test whether land clearing for agricultural purposes has affected the population structure of the ornate dragon lizard. We found significant genetic differentiation between outcrop populations (FST  = 0.12), as well as isolation by distance within each geographic region. In support of our previous study, land clearing was associated with higher genetic divergences between outcrops and lower genetic variation within outcrops, but only in the region that had been exposed to intense agriculture for the longest period of time. No other landscape features influenced population structure in any geographic region. These results show that the effects of landscape features can vary across species' ranges and suggest there may be a temporal lag in response to contemporary changes in land use. These findings therefore highlight the need for caution when assessing the impact of contemporary land use practices on genetic variation and population structure. © 2013 John Wiley & Sons Ltd.

Recognizing and dating prehistoric liquefaction features: Lessons learned in the New Madrid seismic zone, central United States

USGS Publications Warehouse

Tuttle, M.P.; Schweig, E.S.

1996-01-01

The New Madrid seismic zone (NMSZ), which experienced severe liquefaction during the great New Madrid, Missouri, earthquakes of 1811 and 1812 as well as during several prehistoric earthquakes, is a superb laboratory for the study of world-class, arthquake-induced liquefaction features and their use in paleoseismology. In seismically active regions like the NMSZ, frequent large earthquakes can produce a complex record of liquefaction events that is difficult to interpret. Lessons learned studying liquefaction features in the NMSZ may help to unravel the paleoseismic record in other seismically active regions. Soil characteristics of liquefaction features, as well as their structural and sratigraphic relations to Native American occupation horizons and other cultural features, an help to distinguish prehistoric liquefaction features from historic features. In addition, analyses of artifact assemblages and botanical content of cultural horizons can help to narrow the age ranges of liquefaction features. Future research should focus on methods for defining source areas and estimating magnitudes of prehistoric earthquakes from liquefaction features. Also, new methods for dating liquefaction features are needed.

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.

Insights into structural features determining odorant affinities to honey bee odorant binding protein 14.

PubMed

Schwaighofer, Andreas; Pechlaner, Maria; Oostenbrink, Chris; Kotlowski, Caroline; Araman, Can; Mastrogiacomo, Rosa; Pelosi, Paolo; Knoll, Wolfgang; Nowak, Christoph; Larisika, Melanie

2014-04-18

Molecular interactions between odorants and odorant binding proteins (OBPs) are of major importance for understanding the principles of selectivity of OBPs towards the wide range of semiochemicals. It is largely unknown on a structural basis, how an OBP binds and discriminates between odorant molecules. Here we examine this aspect in greater detail by comparing the C-minus OBP14 of the honey bee (Apis mellifera L.) to a mutant form of the protein that comprises the third disulfide bond lacking in C-minus OBPs. Affinities of structurally analogous odorants featuring an aromatic phenol group with different side chains were assessed based on changes of the thermal stability of the protein upon odorant binding monitored by circular dichroism spectroscopy. Our results indicate a tendency that odorants show higher affinity to the wild-type OBP suggesting that the introduced rigidity in the mutant protein has a negative effect on odorant binding. Furthermore, we show that OBP14 stability is very sensitive to the position and type of functional groups in the odorant. Copyright © 2014 Elsevier Inc. All rights reserved.

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.

Structural Feature Ions for Distinguishing N- and O-Linked Glycan Isomers by LC-ESI-IT MS/MS

NASA Astrophysics Data System (ADS)

Everest-Dass, Arun V.; Abrahams, Jodie L.; Kolarich, Daniel; Packer, Nicolle H.; Campbell, Matthew P.

2013-06-01

Glycomics is the comprehensive study of glycan expression in an organism, cell, or tissue that relies on effective analytical technologies to understand glycan structure-function relationships. Owing to the macro- and micro-heterogeneity of oligosaccharides, detailed structure characterization has required an orthogonal approach, such as a combination of specific exoglycosidase digestions, LC-MS/MS, and the development of bioinformatic resources to comprehensively profile a complex biological sample. Liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS/MS) has emerged as a key tool in the structural analysis of oligosaccharides because of its high sensitivity, resolution, and robustness. Here, we present a strategy that uses LC-ESI-MS/MS to characterize over 200 N- and O-glycans from human saliva glycoproteins, complemented by sequential exoglycosidase treatment, to further verify the annotated glycan structures. Fragment-specific substructure diagnostic ions were collated from an extensive screen of the literature available on the detailed structural characterization of oligosaccharides and, together with other specific glycan structure feature ions derived from cross-ring and glycosidic-linkage fragmentation, were used to characterize the glycans and differentiate isomers. The availability of such annotated mass spectrometric fragmentation spectral libraries of glycan structures, together with such substructure diagnostic ions, will be key inputs for the future development of the automated elucidation of oligosaccharide structures from MS/MS data.

Characteristics of circular features on comet 67P/Churyumov-Gerasimenko

NASA Astrophysics Data System (ADS)

Deller, J. F.; Güttler, C.; Tubiana, C.; Hofmann, M.; Sierks, H.

2017-09-01

Comet 67P/Churyumov-Gerasimenko shows a large variety of circular structures such as pits, elevated roundish features in Imhotep, and even a single occurrence of a plausible fresh impact crater. Imaging the pits in the Ma'at region, aiming to understand their structure and origin drove the design of the final descent trajectory of the Rosetta spacecraft. The high-resolution images obtained during the last mission phase allow us to study these pits as exemplary circular features. A complete catalogue of circular features gives us the possibility to compare and classify these structures systematically.

Effect of Co addition on the performance and structure of V/ZrCe catalyst for simultaneous removal of NO and Hg0 in simulated flue gas

NASA Astrophysics Data System (ADS)

Zhao, Lingkui; Li, Caiting; Du, Xueyu; Zeng, Guangming; Gao, Lei; Zhai, Yunbo; Wang, Teng; Zhang, Junyi

2018-04-01

The effect of CoOx addition on the performance and structure of V2O5/ZrO2-CeO2 catalyst for simultaneous removal of NO and Hg0 in simulated flue gas was investigated by various methods including SEM, BET, XRD, XPS, H2-TPR and FT-IR. It was found that the introduction of CoOx not only greatly enhanced the redox properties of catalysts, but also increased the catalytic performance for simultaneous removal of NO and Hg0. The CoOx-modified V2O5/ZrO2-CeO2 catalyst displayed excellent catalytic activity for NO conversion (89.6%) and Hg0 oxidation (88.9%) at 250 °C under SCR atmosphere. The synergistic effect among vanadium, cobalt, and the ZrCe support could induce oxygen vacancies formation and promote oxygen mobility via charge transfer. Besides, CoOx could assist vanadium species in rapidly changing the valence by the redox cycle of V5+ + Co2+ ↔ V4+ + Co3+. All the above features contribute to the excellent catalytic performance through CoOx addition.

Effect of calcium chloride addition on ice cream structure and quality.

PubMed

Costa, F F; Resende, J V; Abreu, L R; Goff, H D

2008-06-01

The influence of calcium fortification by the addition of calcium chloride on quality parameters of ice cream based on physical properties was investigated, as was the effect of kappa-carrageenan at modifying the effects of this calcium fortification. Four ice cream mixes of conventional composition, with added kappa-carrageenan (0 or 0.025%) and added calcium chloride (0 or 4.4 g L(-1) = 40 mM of added Ca(2+)), were prepared. Modulated temperature-differential scanning calorimetry was used to investigate the effect of calcium chloride on the nucleation temperature, enthalpy of melting, and freezing point depression. The protein composition of 15.4% (wt/wt) reconstituted skim milk powder solutions with or without 4.4 g L(-1) added CaCl(2) and in the supernatant after ultracentrifugation was determined. Fat particle size distributions in ice cream were characterized by light scattering. Ice crystal sizes before and after temperature cycling were determined by cold-stage light microscopy. The results demonstrated that the addition of calcium chloride led to a substantial increase in ice crystal sizes and in fat partial coalescence, which were exacerbated by the addition of kappa-carrageenan. These results can be explained by the interaction between Ca(2+) ions and casein micelles, rather than any effects on freezing point depression. The calcium ions led to a more compact micelle, less serum beta-casein, and high fat destabilization, all of which would be expected to reduce macromolecular structure and volume occupancy in the unfrozen phase, which led to increased rates of ice recrystallization.

Pathogenic features and characteristics of food borne pathogens biofilm: Biomass, viability and matrix.

PubMed

Lin, Shiqi; Yang, Ling; Chen, Gu; Li, Bing; Chen, Dingqiang; Li, Lin; Xu, Zhenbo

2017-10-01

Biofilm is a ubiquitous growth pattern of bacterial species survival but is notorious for its threat on public health and food contamination. Extensive studies of the biofilm structure, formation, quantification, quorum sensing system and underlying control strategies have been reported during the past decades. Insightful elucidation of the pathogenic features and characteristic of bacterial biofilm can facilitate in devising appropriate control strategies for biofilm eradication. Therefore, this review mainly summarized the pathogenic features of biofilms from food borne microorganisms, including the biomass (which could be quantified using crystal violet and fluorogenic dye Syto9 assays), viability (which could be determined by tetrazolium salts, fluorescein diacetate, resazurin staining and alamar blue assays) and matrix (which are commonly detected by dimethyl methylene blue and wheat germ agglutinin assays). In addition, three features were further compared with its particular benefits in specific application. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multiscale Feature Analysis of Salivary Gland Branching Morphogenesis

PubMed Central

Baydil, Banu; Daley, William P.; Larsen, Melinda; Yener, Bülent

2012-01-01

Pattern formation in developing tissues involves dynamic spatio-temporal changes in cellular organization and subsequent evolution of functional adult structures. Branching morphogenesis is a developmental mechanism by which patterns are generated in many developing organs, which is controlled by underlying molecular pathways. Understanding the relationship between molecular signaling, cellular behavior and resulting morphological change requires quantification and categorization of the cellular behavior. In this study, tissue-level and cellular changes in developing salivary gland in response to disruption of ROCK-mediated signaling by are modeled by building cell-graphs to compute mathematical features capturing structural properties at multiple scales. These features were used to generate multiscale cell-graph signatures of untreated and ROCK signaling disrupted salivary gland organ explants. From confocal images of mouse submandibular salivary gland organ explants in which epithelial and mesenchymal nuclei were marked, a multiscale feature set capturing global structural properties, local structural properties, spectral, and morphological properties of the tissues was derived. Six feature selection algorithms and multiway modeling of the data was performed to identify distinct subsets of cell graph features that can uniquely classify and differentiate between different cell populations. Multiscale cell-graph analysis was most effective in classification of the tissue state. Cellular and tissue organization, as defined by a multiscale subset of cell-graph features, are both quantitatively distinct in epithelial and mesenchymal cell types both in the presence and absence of ROCK inhibitors. Whereas tensor analysis demonstrate that epithelial tissue was affected the most by inhibition of ROCK signaling, significant multiscale changes in mesenchymal tissue organization were identified with this analysis that were not identified in previous biological studies. We

Predicting Gene Structure Changes Resulting from Genetic Variants via Exon Definition Features.

PubMed

Majoros, William H; Holt, Carson; Campbell, Michael S; Ware, Doreen; Yandell, Mark; Reddy, Timothy E

2018-04-25

Genetic variation that disrupts gene function by altering gene splicing between individuals can substantially influence traits and disease. In those cases, accurately predicting the effects of genetic variation on splicing can be highly valuable for investigating the mechanisms underlying those traits and diseases. While methods have been developed to generate high quality computational predictions of gene structures in reference genomes, the same methods perform poorly when used to predict the potentially deleterious effects of genetic changes that alter gene splicing between individuals. Underlying that discrepancy in predictive ability are the common assumptions by reference gene finding algorithms that genes are conserved, well-formed, and produce functional proteins. We describe a probabilistic approach for predicting recent changes to gene structure that may or may not conserve function. The model is applicable to both coding and noncoding genes, and can be trained on existing gene annotations without requiring curated examples of aberrant splicing. We apply this model to the problem of predicting altered splicing patterns in the genomes of individual humans, and we demonstrate that performing gene-structure prediction without relying on conserved coding features is feasible. The model predicts an unexpected abundance of variants that create de novo splice sites, an observation supported by both simulations and empirical data from RNA-seq experiments. While these de novo splice variants are commonly misinterpreted by other tools as coding or noncoding variants of little or no effect, we find that in some cases they can have large effects on splicing activity and protein products, and we propose that they may commonly act as cryptic factors in disease. The software is available from geneprediction.org/SGRF. bmajoros@duke.edu. Supplementary information is available at Bioinformatics online.

Short-term responses and resistance of soil microbial community structure to elevated CO2 and N addition in grassland mesocosms.

PubMed

Simonin, Marie; Nunan, Naoise; Bloor, Juliette M G; Pouteau, Valérie; Niboyet, Audrey

2017-05-01

Nitrogen (N) addition is known to affect soil microbial communities, but the interactive effects of N addition with other drivers of global change remain unclear. The impacts of multiple global changes on the structure of microbial communities may be mediated by specific microbial groups with different life-history strategies. Here, we investigated the combined effects of elevated CO2 and N addition on soil microbial communities using PLFA profiling in a short-term grassland mesocosm experiment. We also examined the linkages between the relative abundance of r- and K-strategist microorganisms and resistance of the microbial community structure to experimental treatments. N addition had a significant effect on microbial community structure, likely driven by concurrent increases in plant biomass and in soil labile C and N. In contrast, microbial community structure did not change under elevated CO2 or show significant CO2 × N interactions. Resistance of soil microbial community structure decreased with increasing fungal/bacterial ratio, but showed a positive relationship with the Gram-positive/Gram-negative bacterial ratio. Our findings suggest that the Gram-positive/Gram-negative bacteria ratio may be a useful indicator of microbial community resistance and that K-strategist abundance may play a role in the short-term stability of microbial communities under global change. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

ASTROS: A multidisciplinary automated structural design tool

NASA Technical Reports Server (NTRS)

Neill, D. J.

1989-01-01

ASTROS (Automated Structural Optimization System) is a finite-element-based multidisciplinary structural optimization procedure developed under Air Force sponsorship to perform automated preliminary structural design. The design task is the determination of the structural sizes that provide an optimal structure while satisfying numerous constraints from many disciplines. In addition to its automated design features, ASTROS provides a general transient and frequency response capability, as well as a special feature to perform a transient analysis of a vehicle subjected to a nuclear blast. The motivation for the development of a single multidisciplinary design tool is that such a tool can provide improved structural designs in less time than is currently needed. The role of such a tool is even more apparent as modern materials come into widespread use. Balancing conflicting requirements for the structure's strength and stiffness while exploiting the benefits of material anisotropy is perhaps an impossible task without assistance from an automated design tool. Finally, the use of a single tool can bring the design task into better focus among design team members, thereby improving their insight into the overall task.

Small-scale structure and the Lyman-α forest baryon acoustic oscillation feature

NASA Astrophysics Data System (ADS)

Hirata, Christopher M.

2018-02-01

The baryon-acoustic oscillation (BAO) feature in the Lyman-α forest is a key probe of the cosmic expansion rate at redshifts z ˜ 2.5, well before dark energy is believed to have become significant. A key advantage of the BAO as a standard ruler is that it is a sharp feature and hence is more robust against broad-band systematic effects than other cosmological probes. However, if the Lyman-α forest transmission is sensitive to the initial streaming velocity of the baryons relative to the dark matter, then the BAO peak position can be shifted. Here we investigate this sensitivity using a suite of hydrodynamic simulations of small regions of the intergalactic medium with a range of box sizes and physics assumptions; each simulation starts from initial conditions at the kinematic decoupling era (z ˜ 1059), undergoes a discrete change from neutral gas to ionized gas thermal evolution at reionization (z ˜ 8), and is finally processed into a Lyman-α forest transmitted flux cube. Streaming velocities suppress small-scale structure, leading to less violent relaxation after reionization. The changes in the gas distribution and temperature-density relation at low redshift are more subtle, due to the convergent temperature evolution in the ionized phase. The change in the BAO scale is estimated to be of the order of 0.12 per cent at z = 2.5; some of the major uncertainties and avenues for future improvement are discussed. The predicted streaming velocity shift would be a subdominant but not negligible effect (of order 0.26σ) for the upcoming DESI Lyman-α forest survey, and exceeds the cosmic variance floor.

Character feature integration of Chinese calligraphy and font

NASA Astrophysics Data System (ADS)

Shi, Cao; Xiao, Jianguo; Jia, Wenhua; Xu, Canhui

2013-01-01

A framework is proposed in this paper to effectively generate a new hybrid character type by means of integrating local contour feature of Chinese calligraphy with structural feature of font in computer system. To explore traditional art manifestation of calligraphy, multi-directional spatial filter is applied for local contour feature extraction. Then the contour of character image is divided into sub-images. The sub-images in the identical position from various characters are estimated by Gaussian distribution. According to its probability distribution, the dilation operator and erosion operator are designed to adjust the boundary of font image. And then new Chinese character images are generated which possess both contour feature of artistical calligraphy and elaborate structural feature of font. Experimental results demonstrate the new characters are visually acceptable, and the proposed framework is an effective and efficient strategy to automatically generate the new hybrid character of calligraphy and font.

Bio-inspired self-healing structural color hydrogel

PubMed Central

Fu, Fanfan; Chen, Zhuoyue; Zhao, Ze; Wang, Huan; Shang, Luoran; Gu, Zhongze

2017-01-01

Biologically inspired self-healing structural color hydrogels were developed by adding a glucose oxidase (GOX)- and catalase (CAT)-filled glutaraldehyde cross-linked BSA hydrogel into methacrylated gelatin (GelMA) inverse opal scaffolds. The composite hydrogel materials with the polymerized GelMA scaffold could maintain the stability of an inverse opal structure and its resultant structural colors, whereas the protein hydrogel filler could impart self-healing capability through the reversible covalent attachment of glutaraldehyde to lysine residues of BSA and enzyme additives. A series of unprecedented structural color materials could be created by assembling and healing the elements of the composite hydrogel. In addition, as both the GelMA and the protein hydrogels were derived from organisms, the composite materials presented high biocompatibility and plasticity. These features of self-healing structural color hydrogels make them excellent functional materials for different applications. PMID:28533368

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

Sequence, Structural Analysis and Metrics to Define the Unique Dynamic Features of the Flap Regions Among Aspartic Proteases.

PubMed

McGillewie, Lara; Ramesh, Muthusamy; Soliman, Mahmoud E

2017-10-01

Aspartic proteases are a class of hydrolytic enzymes that have been implicated in a number of diseases such as HIV, malaria, cancer and Alzheimer's. The flap region of aspartic proteases is a characteristic unique structural feature of these enzymes; and found to have a profound impact on protein overall structure, function and dynamics. Flap dynamics also plays a crucial role in drug binding and drug resistance. Therefore, understanding the structure and dynamic behavior of this flap regions is crucial in the design of potent and selective inhibitors against aspartic proteases. Defining metrics that can describe the flap motion/dynamics has been a challenging topic in literature. This review is the first attempt to compile comprehensive information on sequence, structure, motion and metrics used to assess the dynamics of the flap region of different aspartic proteases in "one pot". We believe that this review would be of critical importance to the researchers from different scientific domains.

Common and divergent structural features of a series of corticotropin releasing factor-related peptides.

PubMed

Grace, Christy Rani R; Perrin, Marilyn H; Cantle, Jeffrey P; Vale, Wylie W; Rivier, Jean E; Riek, Roland

2007-12-26

Members of the corticoliberin family include the corticotropin releasing factors (CRFs), sauvagine, the urotensins, and urocortin 1 (Ucn1), which bind to both the CRF receptors CRF-R1 and CRF-R2, and the urocortins 2 (Ucn2) and 3 (Ucn3), which are selective agonists of CRF-R2. Structure activity relationship studies led to several potent and long-acting analogues with selective binding to either one of the receptors. NMR structures of six ligands of this family (the antagonists astressin B and astressin2-B, the agonists stressin1, and the natural ligands human Ucn1, Ucn2, and Ucn3) were determined in DMSO. These six peptides show differences in binding affinities, receptor-selectivity, and NMR structure. Overall, their backbones are alpha-helical, with a small kink or a turn around residues 25-27, resulting in a helix-loop-helix motif. The C-terminal helices are of amphipathic nature, whereas the N-terminal helices vary in their amphipathicity. The C-terminal helices thereby assume a conformation very similar to that of astressin bound to the ECD1 of CRF-R2 recently reported by our group.1 On the basis of an analysis of the observed 3D structures and relative potencies of [Ala]-substituted analogues, it is proposed that both helices could play a crucial role in receptor binding and selectivity. In conclusion, the C-terminal helices may interact along their hydrophobic faces with the ECD1, whereas the entire N-terminal helical surface may be involved in receptor activation. On the basis of the common and divergent features observed in the 3D structures of these ligands, multiple binding models are proposed that may explain their plurality of actions.

Structural integrity of additive materials: Microstructure, fatigue behavior, and surface processing

NASA Astrophysics Data System (ADS)

Book, Todd A.

Although Additive Manufacturing (AM) offers numerous performance advantages over existing methods, AM structures are not being utilized for critical aerospace and mechanical applications due to uncertainties in their structural integrity as a result of the microstructural variations and defects arising from the AM process itself. Two of these uncertainties are the observed scatter in tensile strength and fatigue lives of direct metal laser sintering (DMLS) parts. With strain localization a precursor for material failure, this research seeks to explore the impact of microstructural variations in DMLS produced materials on strain localization. The first part of this research explores the role of the microstructure in strain localization of DMLS produced IN718 and Ti6Al4V specimens (as-built and post-processed) through the characterization of the linkage between microstructural variations, and the accumulation of plastic strain during monotonic and low cycle fatigue loading. The second part of this research explores the feasibility for the application of select surface processing techniques in-situ during the DMLS build process to alter the microstructure in AlSi10Mg to reduce strain localization and improve material cohesion. This study is based on utilizing experimental observations through the employment of advanced material characterization techniques such as digital image correlation to illustrate the impacts of DMLS microstructural variation.

Polymyxins and quinazolines are LSD1/KDM1A inhibitors with unusual structural features.

PubMed

Speranzini, Valentina; Rotili, Dante; Ciossani, Giuseppe; Pilotto, Simona; Marrocco, Biagina; Forgione, Mariantonietta; Lucidi, Alessia; Forneris, Federico; Mehdipour, Parinaz; Velankar, Sameer; Mai, Antonello; Mattevi, Andrea

2016-09-01

Because of its involvement in the progression of several malignant tumors, the histone lysine-specific demethylase 1 (LSD1) has become a prominent drug target in modern medicinal chemistry research. We report on the discovery of two classes of noncovalent inhibitors displaying unique structural features. The antibiotics polymyxins bind at the entrance of the substrate cleft, where their highly charged cyclic moiety interacts with a cluster of positively charged amino acids. The same site is occupied by quinazoline-based compounds, which were found to inhibit the enzyme through a most peculiar mode because they form a pile of five to seven molecules that obstruct access to the active center. These data significantly indicate unpredictable strategies for the development of epigenetic inhibitors.

Upper-Ocean Thermal Structure and the Western North Pacific Category 5 Typhoons. Part 1. Ocean Features and the Category 5 Typhoons’ Intensification

DTIC Science & Technology

2008-09-01

Structure and the Western North Pacific Category 5 Typhoons. Part 1: Ocean Features and the Category 5 Typhoons’ Intensification 5a. CONTRACT NUMBER...intensification of category 5 cyclones. Based on 13 yr of satellite altimetry data, in situ &climatological upper-ocean thermal structure data, best-track...Form 298 (Rev. 8/98) Prescribed by ANSI Std. Z39.18 3288 MONTHLY WEATHER REVIEW VOLUME 136 Upper-Ocean Thermal Structure and the Western North

Incidental and Context-Responsive Activation of Structure- and Function-Based Action Features during Object Identification

ERIC Educational Resources Information Center

Lee, Chia-lin; Middleton, Erica; Mirman, Daniel; Kalenine, Solene; Buxbaum, Laurel J.

2013-01-01

Previous studies suggest that action representations are activated during object processing, even when task-irrelevant. In addition, there is evidence that lexical-semantic context may affect such activation during object processing. Finally, prior work from our laboratory and others indicates that function-based ("use") and structure-based…

Structural Coherence and Temporal Stability of Psychopathic Personality Features During Emerging Adulthood

PubMed Central

Hawes, Samuel W.; Mulvey, Edward P.; Schubert, Carol A.; Pardini, Dustin A.

2015-01-01

Psychopathy is a complex personality disorder characterized by affective, interpersonal, and behavioral dimensions. Although features of psychopathy have been extended downwardly to earlier developmental periods, there is a discerning lack of studies that have focused on critically important issues such as longitudinal invariance and stability/change in these features across time. The current study examines these issues using a large sample of male adolescent offenders (N = 1,170) assessed across 7 annual time points during the transition into emerging adulthood (ages ~ 17 to 24 years). Findings demonstrated that features of psychopathy remained longitudinally invariant across this developmental period, and showed temporally consistent and theoretically coherent associations with other measures of personality, psychopathology, and criminal behaviors. Results also demonstrated that mean levels of psychopathic personality features tended to decrease into emerging adulthood and showed relatively modest rank-order stability across assessments with 7-year lags. These findings suggest that reductions in maladaptive personality features seem to parallel the well-documented decreases in offending that occur during the early 20s. PMID:24978692

Potential applications of ferrocene as a structural feature in antioxidants.

PubMed

Liu, Zai-Qun

2011-04-01

Comparing with the wide usage of ferrocene in novel materials, ferrocene was unusually applied to be a structural feature in designing drugs even though some researchers pointed out that ferrocene and its derivatives possessed potential pharmacological applications. This was due to that low polarity limited bioavailability of ferrocene in vivo. Since ferrocene was inert to the oxidation at atmosphere, it was deduced that synthetic derivatives of ferrocene may be a novel kind of antioxidant, in which other organic groups may enhance the bioavailability of ferrocene, or large conjugated system formed among ferrocenyl and other organic groups may increase the antioxidant effectiveness. Thus, synthetic derivatives of ferrocene were divided into nonconjugated and conjugated ones in this review. For nonconjugated ferrocenyl derivatives, carbon chain or simple group attached one or two cyclopentadienyl rings in ferrocene to form a novel molecule with ferrocenyl group. The aim of synthesis of nonconjugated ferrocenyl compounds was to increase the bioavailability of ferrocene in vivo. On the other hand, the conjugated ferrocenyl derivatives referred to introduce other group to form a conjugated system with the cyclopentadienyl ring in ferrocene. The large conjugated system was beneficial for the single electron to dispense among the whole molecule while forming radicals, and enhanced the antioxidant capacity of the whole molecule. This review summarized the potential usage of ferrocene in antioxidants.

Blurred Palmprint Recognition Based on Stable-Feature Extraction Using a Vese–Osher Decomposition Model

PubMed Central

Hong, Danfeng; Su, Jian; Hong, Qinggen; Pan, Zhenkuan; Wang, Guodong

2014-01-01

As palmprints are captured using non-contact devices, image blur is inevitably generated because of the defocused status. This degrades the recognition performance of the system. To solve this problem, we propose a stable-feature extraction method based on a Vese–Osher (VO) decomposition model to recognize blurred palmprints effectively. A Gaussian defocus degradation model is first established to simulate image blur. With different degrees of blurring, stable features are found to exist in the image which can be investigated by analyzing the blur theoretically. Then, a VO decomposition model is used to obtain structure and texture layers of the blurred palmprint images. The structure layer is stable for different degrees of blurring (this is a theoretical conclusion that needs to be further proved via experiment). Next, an algorithm based on weighted robustness histogram of oriented gradients (WRHOG) is designed to extract the stable features from the structure layer of the blurred palmprint image. Finally, a normalized correlation coefficient is introduced to measure the similarity in the palmprint features. We also designed and performed a series of experiments to show the benefits of the proposed method. The experimental results are used to demonstrate the theoretical conclusion that the structure layer is stable for different blurring scales. The WRHOG method also proves to be an advanced and robust method of distinguishing blurred palmprints. The recognition results obtained using the proposed method and data from two palmprint databases (PolyU and Blurred–PolyU) are stable and superior in comparison to previous high-performance methods (the equal error rate is only 0.132%). In addition, the authentication time is less than 1.3 s, which is fast enough to meet real-time demands. Therefore, the proposed method is a feasible way of implementing blurred palmprint recognition. PMID:24992328

Blurred palmprint recognition based on stable-feature extraction using a Vese-Osher decomposition model.

PubMed

Hong, Danfeng; Su, Jian; Hong, Qinggen; Pan, Zhenkuan; Wang, Guodong

2014-01-01

As palmprints are captured using non-contact devices, image blur is inevitably generated because of the defocused status. This degrades the recognition performance of the system. To solve this problem, we propose a stable-feature extraction method based on a Vese-Osher (VO) decomposition model to recognize blurred palmprints effectively. A Gaussian defocus degradation model is first established to simulate image blur. With different degrees of blurring, stable features are found to exist in the image which can be investigated by analyzing the blur theoretically. Then, a VO decomposition model is used to obtain structure and texture layers of the blurred palmprint images. The structure layer is stable for different degrees of blurring (this is a theoretical conclusion that needs to be further proved via experiment). Next, an algorithm based on weighted robustness histogram of oriented gradients (WRHOG) is designed to extract the stable features from the structure layer of the blurred palmprint image. Finally, a normalized correlation coefficient is introduced to measure the similarity in the palmprint features. We also designed and performed a series of experiments to show the benefits of the proposed method. The experimental results are used to demonstrate the theoretical conclusion that the structure layer is stable for different blurring scales. The WRHOG method also proves to be an advanced and robust method of distinguishing blurred palmprints. The recognition results obtained using the proposed method and data from two palmprint databases (PolyU and Blurred-PolyU) are stable and superior in comparison to previous high-performance methods (the equal error rate is only 0.132%). In addition, the authentication time is less than 1.3 s, which is fast enough to meet real-time demands. Therefore, the proposed method is a feasible way of implementing blurred palmprint recognition.

Experience improves feature extraction in Drosophila.

PubMed

Peng, Yueqing; Xi, Wang; Zhang, Wei; Zhang, Ke; Guo, Aike

2007-05-09

Previous exposure to a pattern in the visual scene can enhance subsequent recognition of that pattern in many species from honeybees to humans. However, whether previous experience with a visual feature of an object, such as color or shape, can also facilitate later recognition of that particular feature from multiple visual features is largely unknown. Visual feature extraction is the ability to select the key component from multiple visual features. Using a visual flight simulator, we designed a novel protocol for visual feature extraction to investigate the effects of previous experience on visual reinforcement learning in Drosophila. We found that, after conditioning with a visual feature of objects among combinatorial shape-color features, wild-type flies exhibited poor ability to extract the correct visual feature. However, the ability for visual feature extraction was greatly enhanced in flies trained previously with that visual feature alone. Moreover, we demonstrated that flies might possess the ability to extract the abstract category of "shape" but not a particular shape. Finally, this experience-dependent feature extraction is absent in flies with defective MBs, one of the central brain structures in Drosophila. Our results indicate that previous experience can enhance visual feature extraction in Drosophila and that MBs are required for this experience-dependent visual cognition.

A short feature vector for image matching: The Log-Polar Magnitude feature descriptor

PubMed Central

Hast, Anders; Wählby, Carolina; Sintorn, Ida-Maria

2017-01-01

The choice of an optimal feature detector-descriptor combination for image matching often depends on the application and the image type. In this paper, we propose the Log-Polar Magnitude feature descriptor—a rotation, scale, and illumination invariant descriptor that achieves comparable performance to SIFT on a large variety of image registration problems but with much shorter feature vectors. The descriptor is based on the Log-Polar Transform followed by a Fourier Transform and selection of the magnitude spectrum components. Selecting different frequency components allows optimizing for image patterns specific for a particular application. In addition, by relying only on coordinates of the found features and (optionally) feature sizes our descriptor is completely detector independent. We propose 48- or 56-long feature vectors that potentially can be shortened even further depending on the application. Shorter feature vectors result in better memory usage and faster matching. This combined with the fact that the descriptor does not require a time-consuming feature orientation estimation (the rotation invariance is achieved solely by using the magnitude spectrum of the Log-Polar Transform) makes it particularly attractive to applications with limited hardware capacity. Evaluation is performed on the standard Oxford dataset and two different microscopy datasets; one with fluorescence and one with transmission electron microscopy images. Our method performs better than SURF and comparable to SIFT on the Oxford dataset, and better than SIFT on both microscopy datasets indicating that it is particularly useful in applications with microscopy images. PMID:29190737

Hair Follicle Nevus With Features of Comedo Nevus: An Expanding Spectrum.

PubMed

Nagarajan, Priyadharsini; Bartholomew, Timothy S; Allen, Carl M; Peters, Sara B

2016-06-01

Hair follicle nevus (HFN) is a rare hamartomatous lesion of the folliculosebaceous unit, with or without admixed fibroadipose or muscular tissue. It typically has a congenital presentation in the preauricular area of infants and is frequently confused with an accessory tragus. Acquired tumors with similar histopathologic features have been described infrequently during adolescence and adult life. We report yet another unique presentation of this unusual lesion in a 4-year-old girl who had a long-standing tumor of the nasal columella that started growing rapidly after trauma. Histopathologic examination revealed increased numbers of hair follicles, some of which were associated with diminutive sebaceous glands, with no associated central cystic structure. In addition, the infundibula of the follicles were dilated and filled with keratinous debris. Although these hamartomas are common in the head and neck region, to our knowledge, this is the first report of a HFN at this anatomic location. In addition, this tumor has an overall architecture of a HFN but is accompanied by features of a comedo nevus. We also present a review of the literature and summarize the current diagnostic criteria for HFN.

Process Control and Development for Ultrasonic Additive Manufacturing with Embedded Fibers

NASA Astrophysics Data System (ADS)

Hehr, Adam J.

Ultrasonic additive manufacturing (UAM) is a recent additive manufacturing technology which combines ultrasonic metal welding, CNC machining, and mechanized foil layering to create large gapless near net-shape metallic parts. The process has been attracting much attention lately due to its low formation temperature, the capability to join dissimilar metals, and the ability to create complex design features not possible with traditional subtractive processes alone. These process attributes enable light-weighting of structures and components in an unprecedented way. However, UAM is currently limited to niche areas due to the lack of quality tracking and inadequate scientific understanding of the process. As a result, this thesis work is focused on improving both component quality tracking and process understanding through the use of average electrical power input to the welder. Additionally, the understanding and application space of embedding fibers into metals using UAM is investigated, with particular focus on NiTi shape memory alloy fibers.

Automated Feature Identification and Classification Using Automated Feature Weighted Self Organizing Map (FWSOM)

NASA Astrophysics Data System (ADS)

Starkey, Andrew; Usman Ahmad, Aliyu; Hamdoun, Hassan

2017-10-01

This paper investigates the application of a novel method for classification called Feature Weighted Self Organizing Map (FWSOM) that analyses the topology information of a converged standard Self Organizing Map (SOM) to automatically guide the selection of important inputs during training for improved classification of data with redundant inputs, examined against two traditional approaches namely neural networks and Support Vector Machines (SVM) for the classification of EEG data as presented in previous work. In particular, the novel method looks to identify the features that are important for classification automatically, and in this way the important features can be used to improve the diagnostic ability of any of the above methods. The paper presents the results and shows how the automated identification of the important features successfully identified the important features in the dataset and how this results in an improvement of the classification results for all methods apart from linear discriminatory methods which cannot separate the underlying nonlinear relationship in the data. The FWSOM in addition to achieving higher classification accuracy has given insights into what features are important in the classification of each class (left and right-hand movements), and these are corroborated by already published work in this area.

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.

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

Internal versus external features in triggering the brain waveforms for conjunction and feature faces in recognition.

PubMed

Nie, Aiqing; Jiang, Jingguo; Fu, Qiao

2014-08-20

Previous research has found that conjunction faces (whose internal features, e.g. eyes, nose, and mouth, and external features, e.g. hairstyle and ears, are from separate studied faces) and feature faces (partial features of these are studied) can produce higher false alarms than both old and new faces (i.e. those that are exactly the same as the studied faces and those that have not been previously presented) in recognition. The event-related potentials (ERPs) that relate to conjunction and feature faces at recognition, however, have not been described as yet; in addition, the contributions of different facial features toward ERPs have not been differentiated. To address these issues, the present study compared the ERPs elicited by old faces, conjunction faces (the internal and the external features were from two studied faces), old internal feature faces (whose internal features were studied), and old external feature faces (whose external features were studied) with those of new faces separately. The results showed that old faces not only elicited an early familiarity-related FN400, but a more anterior distributed late old/new effect that reflected recollection. Conjunction faces evoked similar late brain waveforms as old internal feature faces, but not to old external feature faces. These results suggest that, at recognition, old faces hold higher familiarity than compound faces in the profiles of ERPs and internal facial features are more crucial than external ones in triggering the brain waveforms that are characterized as reflecting the result of familiarity.

Insights into peptide nucleic acid (PNA) structural features: The crystal structure of a d-lysine-based chiral PNA–DNA duplex

PubMed Central

Menchise, Valeria; De Simone, Giuseppina; Tedeschi, Tullia; Corradini, Roberto; Sforza, Stefano; Marchelli, Rosangela; Capasso, Domenica; Saviano, Michele; Pedone, Carlo

2003-01-01

Peptide nucleic acids (PNAs) are oligonucleotide analogues in which the sugar-phosphate backbone has been replaced by a pseudopeptide skeleton. They bind DNA and RNA with high specificity and selectivity, leading to PNA–RNA and PNA–DNA hybrids more stable than the corresponding nucleic acid complexes. The binding affinity and selectivity of PNAs for nucleic acids can be modified by the introduction of stereogenic centers (such as d-Lys-based units) into the PNA backbone. To investigate the structural features of chiral PNAs, the structure of a PNA decamer containing three d-Lys-based monomers (namely H-GpnTpnApnGpnAdlTdlCdlApnCpnTpn-NH2, in which pn represents a pseudopeptide link and dl represents a d-Lys analogue) hybridized with its complementary antiparallel DNA has been solved at a 1.66-Å resolution by means of a single-wavelength anomalous diffraction experiment on a brominated derivative. Thed-Lys-based chiral PNA–DNA (LPD) heteroduplex adopts the so-called P-helix conformation. From the substantial similarity between the PNA conformation in LPD and the conformations observed in other PNA structures, it can be concluded that PNAs possess intrinsic conformational preferences for the P-helix, and that their flexibility is rather restricted. The conformational rigidity of PNAs is enhanced by the presence of the chiral centers, limiting the ability of PNA strands to adopt other conformations and, ultimately, increasing the selectivity in molecular recognition. PMID:14512516

Representational Flexibility and Problem-Solving Ability in Fraction and Decimal Number Addition: A Structural Model

ERIC Educational Resources Information Center

Deliyianni, Eleni; Gagatsis, Athanasios; Elia, Iliada; Panaoura, Areti

2016-01-01

The aim of this study was to propose and validate a structural model in fraction and decimal number addition, which is founded primarily on a synthesis of major theoretical approaches in the field of representations in Mathematics and also on previous research on the learning of fractions and decimals. The study was conducted among 1,701 primary…

Splicing-Related Features of Introns Serve to Propel Evolution

PubMed Central

Luo, Yuping; Li, Chun; Gong, Xi; Wang, Yanlu; Zhang, Kunshan; Cui, Yaru; Sun, Yi Eve; Li, Siguang

2013-01-01

The role of spliceosomal intronic structures played in evolution has only begun to be elucidated. Comparative genomic analyses of fungal snoRNA sequences, which are often contained within introns and/or exons, revealed that about one-third of snoRNA-associated introns in three major snoRNA gene clusters manifested polymorphisms, likely resulting from intron loss and gain events during fungi evolution. Genomic deletions can clearly be observed as one mechanism underlying intron and exon loss, as well as generation of complex introns where several introns lie in juxtaposition without intercalating exons. Strikingly, by tracking conserved snoRNAs in introns, we found that some introns had moved from one position to another by excision from donor sites and insertion into target sties elsewhere in the genome without needing transposon structures. This study revealed the origin of many newly gained introns. Moreover, our analyses suggested that intron-containing sequences were more prone to sustainable structural changes than DNA sequences without introns due to intron's ability to jump within the genome via unknown mechanisms. We propose that splicing-related structural features of introns serve as an additional motor to propel evolution. PMID:23516505

Effect of additional elements on compositional modulated atomic layered structure of hexagonal Co{sub 80}Pt{sub 20} alloy films with superlattice diffraction

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

Hinata, Shintaro; Research Fellowship Division Japan Society for the Promotion of Science; Yamane, Akira

2016-05-15

The effect of additional element on compositionally modulated atomic layered structure of hexagonal Co{sub 80}Pt{sub 20} alloy films with superlattice diffraction was investigated. In this study it is found that the addition of Cr or W element to Co{sub 80}Pt{sub 20} alloy film shows less deterioration of hcp stacking structure and compositionally modulated atomic layer stacking structure as compared to Si or Zr or Ti with K{sub u} of around 1.4 or 1.0 × 10{sup 7} erg/cm{sup 3} at 5 at.% addition. Furthermore, for O{sub 2} addition of O{sub 2} ≥ 5.0 × 10{sup −3} Pa to CoPt alloy, compositionallymore » modulated atomic layer stacking structure will be deteriorated with enhancement of formation of hcp stacking structure which leads higher K{sub u} of 1.0 × 10{sup 7} erg/cm{sup 3}.« less

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

Evaluation of feature selection algorithms for classification in temporal lobe epilepsy based on MR images

NASA Astrophysics Data System (ADS)

Lai, Chunren; Guo, Shengwen; Cheng, Lina; Wang, Wensheng; Wu, Kai

2017-02-01

It's very important to differentiate the temporal lobe epilepsy (TLE) patients from healthy people and localize the abnormal brain regions of the TLE patients. The cortical features and changes can reveal the unique anatomical patterns of brain regions from the structural MR images. In this study, structural MR images from 28 normal controls (NC), 18 left TLE (LTLE), and 21 right TLE (RTLE) were acquired, and four types of cortical feature, namely cortical thickness (CTh), cortical surface area (CSA), gray matter volume (GMV), and mean curvature (MCu), were explored for discriminative analysis. Three feature selection methods, the independent sample t-test filtering, the sparse-constrained dimensionality reduction model (SCDRM), and the support vector machine-recursive feature elimination (SVM-RFE), were investigated to extract dominant regions with significant differences among the compared groups for classification using the SVM classifier. The results showed that the SVM-REF achieved the highest performance (most classifications with more than 92% accuracy), followed by the SCDRM, and the t-test. Especially, the surface area and gray volume matter exhibited prominent discriminative ability, and the performance of the SVM was improved significantly when the four cortical features were combined. Additionally, the dominant regions with higher classification weights were mainly located in temporal and frontal lobe, including the inferior temporal, entorhinal cortex, fusiform, parahippocampal cortex, middle frontal and frontal pole. It was demonstrated that the cortical features provided effective information to determine the abnormal anatomical pattern and the proposed method has the potential to improve the clinical diagnosis of the TLE.

New Features for Neuron Classification.

PubMed

Hernández-Pérez, Leonardo A; Delgado-Castillo, Duniel; Martín-Pérez, Rainer; Orozco-Morales, Rubén; Lorenzo-Ginori, Juan V

2018-04-28

This paper addresses the problem of obtaining new neuron features capable of improving results of neuron classification. Most studies on neuron classification using morphological features have been based on Euclidean geometry. Here three one-dimensional (1D) time series are derived from the three-dimensional (3D) structure of neuron instead, and afterwards a spatial time series is finally constructed from which the features are calculated. Digitally reconstructed neurons were separated into control and pathological sets, which are related to three categories of alterations caused by epilepsy, Alzheimer's disease (long and local projections), and ischemia. These neuron sets were then subjected to supervised classification and the results were compared considering three sets of features: morphological, features obtained from the time series and a combination of both. The best results were obtained using features from the time series, which outperformed the classification using only morphological features, showing higher correct classification rates with differences of 5.15, 3.75, 5.33% for epilepsy and Alzheimer's disease (long and local projections) respectively. The morphological features were better for the ischemia set with a difference of 3.05%. Features like variance, Spearman auto-correlation, partial auto-correlation, mutual information, local minima and maxima, all related to the time series, exhibited the best performance. Also we compared different evaluators, among which ReliefF was the best ranked.

Mosaic tetraploidy in a liveborn infant with features of the DiGeorge anomaly.

PubMed

Wullich, B; Henn, W; Groterath, E; Ermis, A; Fuchs, S; Zankl, M

1991-11-01

We report on a liveborn male infant with mosaic tetraploidy who presented with multiple congenital anomalies including features of the DiGeorge anomaly (type I truncus arteriosus with other cardiovascular malformations, thymic hypoplasia, hypocalcemia). No structural chromosome aberrations, namely of chromosome 22, were detected. These findings contribute to the variability of symptoms of the polyploid phenotype. Additionally, the cytogenetic studies in our case emphasize the necessity of investigating fibroblasts in order to evaluate the relevant proportion of aberrant cells in mosaicism.

Structural and Functional Features of a Developmentally Regulated Lipopolysaccharide-Binding Protein

PubMed Central

Krasity, Benjamin C.; Troll, Joshua V.; Lehnert, Erik M.; Hackett, Kathleen T.; Dillard, Joseph P.; Apicella, Michael A.; Goldman, William E.

2015-01-01

ABSTRACT Mammalian lipopolysaccharide (LPS) binding proteins (LBPs) occur mainly in extracellular fluids and promote LPS delivery to specific host cell receptors. The function of LBPs has been studied principally in the context of host defense; the possible role of LBPs in nonpathogenic host-microbe interactions has not been well characterized. Using the Euprymna scolopes-Vibrio fischeri model, we analyzed the structure and function of an LBP family protein, E. scolopes LBP1 (EsLBP1), and provide evidence for its role in triggering a symbiont-induced host developmental program. Previous studies showed that, during initial host colonization, the LPS of V. fischeri synergizes with peptidoglycan (PGN) monomer to induce morphogenesis of epithelial tissues of the host animal. Computationally modeled EsLBP1 shares some but not all structural features of mammalian LBPs that are thought important for LPS binding. Similar to human LBP, recombinant EsLBP1 expressed in insect cells bound V. fischeri LPS and Neisseria meningitidis lipooligosaccharide (LOS) with nanomolar or greater affinity but bound Francisella tularensis LPS only weakly and did not bind PGN monomer. Unlike human LBP, EsLBP1 did not bind N. meningitidis LOS:CD14 complexes. The eslbp1 transcript was upregulated ~22-fold by V. fischeri at 24 h postinoculation. Surprisingly, this upregulation was not induced by exposure to LPS but, rather, to the PGN monomer alone. Hybridization chain reaction-fluorescent in situ hybridization (HCR-FISH) and immunocytochemistry (ICC) localized eslbp1 transcript and protein in crypt epithelia, where V. fischeri induces morphogenesis. The data presented here provide a window into the evolution of LBPs and the scope of their roles in animal symbioses. PMID:26463160

Crystal Structure of Human Dual-Specificity Tyrosine-Regulated Kinase 3 Reveals New Structural Features and Insights into its Auto-phosphorylation.

PubMed

Kim, Kuglae; Cha, Jeong Seok; Cho, Yong-Soon; Kim, Hoyoung; Chang, Nienping; Kim, Hye-Jung; Cho, Hyun-Soo

2018-05-11

Dual-specificity tyrosine-regulated kinases (DYRKs) auto-phosphorylate a critical tyrosine residue in their activation loop and phosphorylate their substrate on serine and threonine residues. The auto-phosphorylation occurs intramolecularly and is a one-off event. DYRK3 is selectively expressed at a high level in hematopoietic cells and attenuates erythroblast development, leading to anemia. In the present study, we determined the crystal structure of the mature form of human DYRK3 in complex with harmine, an ATP competitive inhibitor. The crystal structure revealed a phosphorylation site, residue S350, whose phosphorylation increases the stability of DYRK3 and enhances its kinase activity. In addition, our structural and biochemical assays suggest that the N-terminal auto-phosphorylation accessory domain stabilizes the DYRK3 protein, followed by auto-phosphorylation of the tyrosine of the activation loop, which is important for kinase activity. Finally, our docking analysis provides information for the design of novel and potent therapeutics to treat anemia. Copyright © 2018 Elsevier Ltd. All rights reserved.

Feature hashing for fast image retrieval

NASA Astrophysics Data System (ADS)

Yan, Lingyu; Fu, Jiarun; Zhang, Hongxin; Yuan, Lu; Xu, Hui

2018-03-01

Currently, researches on content based image retrieval mainly focus on robust feature extraction. However, due to the exponential growth of online images, it is necessary to consider searching among large scale images, which is very timeconsuming and unscalable. Hence, we need to pay much attention to the efficiency of image retrieval. In this paper, we propose a feature hashing method for image retrieval which not only generates compact fingerprint for image representation, but also prevents huge semantic loss during the process of hashing. To generate the fingerprint, an objective function of semantic loss is constructed and minimized, which combine the influence of both the neighborhood structure of feature data and mapping error. Since the machine learning based hashing effectively preserves neighborhood structure of data, it yields visual words with strong discriminability. Furthermore, the generated binary codes leads image representation building to be of low-complexity, making it efficient and scalable to large scale databases. Experimental results show good performance of our approach.

Characterizing mammographic images by using generic texture features

PubMed Central

2012-01-01

Introduction Although mammographic density is an established risk factor for breast cancer, its use is limited in clinical practice because of a lack of automated and standardized measurement methods. The aims of this study were to evaluate a variety of automated texture features in mammograms as risk factors for breast cancer and to compare them with the percentage mammographic density (PMD) by using a case-control study design. Methods A case-control study including 864 cases and 418 controls was analyzed automatically. Four hundred seventy features were explored as possible risk factors for breast cancer. These included statistical features, moment-based features, spectral-energy features, and form-based features. An elaborate variable selection process using logistic regression analyses was performed to identify those features that were associated with case-control status. In addition, PMD was assessed and included in the regression model. Results Of the 470 image-analysis features explored, 46 remained in the final logistic regression model. An area under the curve of 0.79, with an odds ratio per standard deviation change of 2.88 (95% CI, 2.28 to 3.65), was obtained with validation data. Adding the PMD did not improve the final model. Conclusions Using texture features to predict the risk of breast cancer appears feasible. PMD did not show any additional value in this study. With regard to the features assessed, most of the analysis tools appeared to reflect mammographic density, although some features did not correlate with PMD. It remains to be investigated in larger case-control studies whether these features can contribute to increased prediction accuracy. PMID:22490545

Common Hydraulic Fracturing Fluid Additives Alter the Structure and Function of Anaerobic Microbial Communities.

PubMed

Mumford, Adam C; Akob, Denise M; Klinges, J Grace; Cozzarelli, Isabelle M

2018-04-15

The development of unconventional oil and gas (UOG) resources results in the production of large volumes of wastewater containing a complex mixture of hydraulic fracturing chemical additives and components from the formation. The release of these wastewaters into the environment poses potential risks that are poorly understood. Microbial communities in stream sediments form the base of the food chain and may serve as sentinels for changes in stream health. Iron-reducing organisms have been shown to play a role in the biodegradation of a wide range of organic compounds, and so to evaluate their response to UOG wastewater, we enriched anaerobic microbial communities from sediments collected upstream (background) and downstream (impacted) of an UOG wastewater injection disposal facility in the presence of hydraulic fracturing fluid (HFF) additives: guar gum, ethylene glycol, and two biocides, 2,2-dibromo-3-nitrilopropionamide (DBNPA) and bronopol (C 3 H 6 BrNO 4 ). Iron reduction was significantly inhibited early in the incubations with the addition of biocides, whereas amendment with guar gum and ethylene glycol stimulated iron reduction relative to levels in the unamended controls. Changes in the microbial community structure were observed across all treatments, indicating the potential for even small amounts of UOG wastewater components to influence natural microbial processes. The microbial community structure differed between enrichments with background and impacted sediments, suggesting that impacted sediments may have been preconditioned by exposure to wastewater. These experiments demonstrated the potential for biocides to significantly decrease iron reduction rates immediately following a spill and demonstrated how microbial communities previously exposed to UOG wastewater may be more resilient to additional spills. IMPORTANCE Organic components of UOG wastewater can alter microbial communities and biogeochemical processes, which could alter the rates of

Magnitude differences in agronomic, chemical, nutritional, and structural features among different varieties of forage corn grown on dry land and irrigated land.

PubMed

Xin, Hangshu; Abeysekara, Samen; Zhang, Xuewei; Yu, Peiqiang

2015-03-11

In this study, eight varieties of corn forage grown in semiarid western Canada (including Pioneer P2501, Pioneer P39m26, Pioneer P7443, Hyland HL3085, Hyland HLBaxxos, Hyland HLR219, Hyland HLSR22, and Pickseed Silex BT) were selected to explore the effect of irrigation implementation in comparison with nonirrigation on (1) agronomic characteristics, (2) basic chemical profiles explored by using a near-infrared reflectance (NIR) system, and (3) protein and carbohydrate internal structural parameters revealed by using an attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) system. Also, principal component analysis (PCA) was performed on spectroscopic data for clarification of differences in molecular structural makeup among the varieties. The results showed that irrigation treatment significantly increased (P < 0.05) contents of dry matter (DM) and organic matter (OM) but decreased crude protein (CP) of corn forages. Significant interactions of irrigation treatment and corn variety were observed on most agronomic characteristics (DM yield, T/ha, days to tasseling, days to silking) and crude fiber (CF) and ether extract (EE) contents as well as some spectral data such as cellulosic compounds (CELC) peak intensity, peak ratios of CHO third peak to CELC, α-helix to β-sheet, and CHO third peak to amide I. Additionally, the spectral ratios of chemical functional groups that related to structural and nonstructural carbohydrates and protein polymers in forages did not remain constant over corn varieties cultivated with and without water treatment. Moreover, different cultivars had different growth, structure, and nutrition performances in this study. Although significant differences could be found in peak intensities, PCA results indicated some structural similarities existed between two treated corn forages with the exception of HL3085 and HLBaxxos. In conclusion, irrigation and corn variety had interaction effects on agronomic, chemical

In silico methods for co-transcriptional RNA secondary structure prediction and for investigating alternative RNA structure expression.

PubMed

Meyer, Irmtraud M

2017-05-01

RNA transcripts are the primary products of active genes in any living organism, including many viruses. Their cellular destiny not only depends on primary sequence signals, but can also be determined by RNA structure. Recent experimental evidence shows that many transcripts can be assigned more than a single functional RNA structure throughout their cellular life and that structure formation happens co-transcriptionally, i.e. as the transcript is synthesised in the cell. Moreover, functional RNA structures are not limited to non-coding transcripts, but can also feature in coding transcripts. The picture that now emerges is that RNA structures constitute an additional layer of information that can be encoded in any RNA transcript (and on top of other layers of information such as protein-context) in order to exert a wide range of functional roles. Moreover, different encoded RNA structures can be expressed at different stages of a transcript's life in order to alter the transcript's behaviour depending on its actual cellular context. Similar to the concept of alternative splicing for protein-coding genes, where a single transcript can yield different proteins depending on cellular context, it is thus appropriate to propose the notion of alternative RNA structure expression for any given transcript. This review introduces several computational strategies that my group developed to detect different aspects of RNA structure expression in vivo. Two aspects are of particular interest to us: (1) RNA secondary structure features that emerge during co-transcriptional folding and (2) functional RNA structure features that are expressed at different times of a transcript's life and potentially mutually exclusive. Copyright © 2017. Published by Elsevier Inc.

48 CFR 452.236-70 - Additive or Deductive Items.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 48 Federal Acquisition Regulations System 4 2011-10-01 2011-10-01 false Additive or Deductive... Additive or Deductive Items. As prescribed in 436.205, insert the following provision: Additive or... listed in the schedule) those additive or deductive bid items providing the most features of the work...

48 CFR 452.236-70 - Additive or Deductive Items.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 48 Federal Acquisition Regulations System 4 2013-10-01 2013-10-01 false Additive or Deductive... Additive or Deductive Items. As prescribed in 436.205, insert the following provision: Additive or... listed in the schedule) those additive or deductive bid items providing the most features of the work...

48 CFR 452.236-70 - Additive or Deductive Items.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 48 Federal Acquisition Regulations System 4 2012-10-01 2012-10-01 false Additive or Deductive... Additive or Deductive Items. As prescribed in 436.205, insert the following provision: Additive or... listed in the schedule) those additive or deductive bid items providing the most features of the work...

48 CFR 452.236-70 - Additive or Deductive Items.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 48 Federal Acquisition Regulations System 4 2010-10-01 2010-10-01 false Additive or Deductive... Additive or Deductive Items. As prescribed in 436.205, insert the following provision: Additive or... listed in the schedule) those additive or deductive bid items providing the most features of the work...

48 CFR 452.236-70 - Additive or Deductive Items.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 48 Federal Acquisition Regulations System 4 2014-10-01 2014-10-01 false Additive or Deductive... Additive or Deductive Items. As prescribed in 436.205, insert the following provision: Additive or... listed in the schedule) those additive or deductive bid items providing the most features of the work...

The feature-weighted receptive field: an interpretable encoding model for complex feature spaces.

PubMed

St-Yves, Ghislain; Naselaris, Thomas

2017-06-20

We introduce the feature-weighted receptive field (fwRF), an encoding model designed to balance expressiveness, interpretability and scalability. The fwRF is organized around the notion of a feature map-a transformation of visual stimuli into visual features that preserves the topology of visual space (but not necessarily the native resolution of the stimulus). The key assumption of the fwRF model is that activity in each voxel encodes variation in a spatially localized region across multiple feature maps. This region is fixed for all feature maps; however, the contribution of each feature map to voxel activity is weighted. Thus, the model has two separable sets of parameters: "where" parameters that characterize the location and extent of pooling over visual features, and "what" parameters that characterize tuning to visual features. The "where" parameters are analogous to classical receptive fields, while "what" parameters are analogous to classical tuning functions. By treating these as separable parameters, the fwRF model complexity is independent of the resolution of the underlying feature maps. This makes it possible to estimate models with thousands of high-resolution feature maps from relatively small amounts of data. Once a fwRF model has been estimated from data, spatial pooling and feature tuning can be read-off directly with no (or very little) additional post-processing or in-silico experimentation. We describe an optimization algorithm for estimating fwRF models from data acquired during standard visual neuroimaging experiments. We then demonstrate the model's application to two distinct sets of features: Gabor wavelets and features supplied by a deep convolutional neural network. We show that when Gabor feature maps are used, the fwRF model recovers receptive fields and spatial frequency tuning functions consistent with known organizational principles of the visual cortex. We also show that a fwRF model can be used to regress entire deep

Structured Additive Quantile Regression for Assessing the Determinants of Childhood Anemia in Rwanda.

PubMed

Habyarimana, Faustin; Zewotir, Temesgen; Ramroop, Shaun

2017-06-17

Childhood anemia is among the most significant health problems faced by public health departments in developing countries. This study aims at assessing the determinants and possible spatial effects associated with childhood anemia in Rwanda. The 2014/2015 Rwanda Demographic and Health Survey (RDHS) data was used. The analysis was done using the structured spatial additive quantile regression model. The findings of this study revealed that the child's age; the duration of breastfeeding; gender of the child; the nutritional status of the child (whether underweight and/or wasting); whether the child had a fever; had a cough in the two weeks prior to the survey or not; whether the child received vitamin A supplementation in the six weeks before the survey or not; the household wealth index; literacy of the mother; mother's anemia status; mother's age at the birth are all significant factors associated with childhood anemia in Rwanda. Furthermore, significant structured spatial location effects on childhood anemia was found.

Iris-based medical analysis by geometric deformation features.