Hierarchical learning architecture with automatic feature selection for multiclass protein fold classification.

PubMed

Huang, Chuen-Der; Lin, Chin-Teng; Pal, Nikhil Ranjan

2003-12-01

The structure classification of proteins plays a very important role in bioinformatics, since the relationships and characteristics among those known proteins can be exploited to predict the structure of new proteins. The success of a classification system depends heavily on two things: the tools being used and the features considered. For the bioinformatics applications, the role of appropriate features has not been paid adequate importance. In this investigation we use three novel ideas for multiclass protein fold classification. First, we use the gating neural network, where each input node is associated with a gate. This network can select important features in an online manner when the learning goes on. At the beginning of the training, all gates are almost closed, i.e., no feature is allowed to enter the network. Through the training, gates corresponding to good features are completely opened while gates corresponding to bad features are closed more tightly, and some gates may be partially open. The second novel idea is to use a hierarchical learning architecture (HLA). The classifier in the first level of HLA classifies the protein features into four major classes: all alpha, all beta, alpha + beta, and alpha/beta. And in the next level we have another set of classifiers, which further classifies the protein features into 27 folds. The third novel idea is to induce the indirect coding features from the amino-acid composition sequence of proteins based on the N-gram concept. This provides us with more representative and discriminative new local features of protein sequences for multiclass protein fold classification. The proposed HLA with new indirect coding features increases the protein fold classification accuracy by about 12%. Moreover, the gating neural network is found to reduce the number of features drastically. Using only half of the original features selected by the gating neural network can reach comparable test accuracy as that using all the original features. The gating mechanism also helps us to get a better insight into the folding process of proteins. For example, tracking the evolution of different gates we can find which characteristics (features) of the data are more important for the folding process. And, of course, it also reduces the computation time.

Semantic Feature Distinctiveness and Frequency

ERIC Educational Resources Information Center

Lamb, Katherine M.

2012-01-01

Lexical access is the process in which basic components of meaning in language, the lexical entries (words) are activated. This activation is based on the organization and representational structure of the lexical entries. Semantic features of words, which are the prominent semantic characteristics of a word concept, provide important information…

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.

Effects of system size and cooling rate on the structure and properties of sodium borosilicate glasses from molecular dynamics simulations.

PubMed

Deng, Lu; Du, Jincheng

2018-01-14

Borosilicate glasses form an important glass forming system in both glass science and technologies. The structure and property changes of borosilicate glasses as a function of thermal history in terms of cooling rate during glass formation and simulation system sizes used in classical molecular dynamics (MD) simulation were investigated with recently developed composition dependent partial charge potentials. Short and medium range structural features such as boron coordination, Si and B Q n distributions, and ring size distributions were analyzed to elucidate the effects of cooling rate and simulation system size on these structure features and selected glass properties such as glass transition temperature, vibration density of states, and mechanical properties. Neutron structure factors, neutron broadened pair distribution functions, and vibrational density of states were calculated and compared with results from experiments as well as ab initio calculations to validate the structure models. The results clearly indicate that both cooling rate and system size play an important role on the structures of these glasses, mainly by affecting the 3 B and 4 B distributions and consequently properties of the glasses. It was also found that different structure features and properties converge at different sizes or cooling rates; thus convergence tests are needed in simulations of the borosilicate glasses depending on the targeted properties. The results also shed light on the complex thermal history dependence on structure and properties in borosilicate glasses and the protocols in MD simulations of these and other glass materials.

Effects of system size and cooling rate on the structure and properties of sodium borosilicate glasses from molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Deng, Lu; Du, Jincheng

2018-01-01

Borosilicate glasses form an important glass forming system in both glass science and technologies. The structure and property changes of borosilicate glasses as a function of thermal history in terms of cooling rate during glass formation and simulation system sizes used in classical molecular dynamics (MD) simulation were investigated with recently developed composition dependent partial charge potentials. Short and medium range structural features such as boron coordination, Si and B Qn distributions, and ring size distributions were analyzed to elucidate the effects of cooling rate and simulation system size on these structure features and selected glass properties such as glass transition temperature, vibration density of states, and mechanical properties. Neutron structure factors, neutron broadened pair distribution functions, and vibrational density of states were calculated and compared with results from experiments as well as ab initio calculations to validate the structure models. The results clearly indicate that both cooling rate and system size play an important role on the structures of these glasses, mainly by affecting the 3B and 4B distributions and consequently properties of the glasses. It was also found that different structure features and properties converge at different sizes or cooling rates; thus convergence tests are needed in simulations of the borosilicate glasses depending on the targeted properties. The results also shed light on the complex thermal history dependence on structure and properties in borosilicate glasses and the protocols in MD simulations of these and other glass materials.

Two Crystallographic Laboratory and Computational Exercises for Undergraduates.

ERIC Educational Resources Information Center

Lessinger, Leslie

1988-01-01

Describes two introductory exercises designed to teach the fundamental ideas and methods of crystallography, and to convey some important features of inorganic and organic crystal structures to students in an advanced laboratory course. Exercises include "The Crystal Structure of NiO" and "The Crystal Structure of Beta-Fumaric Acid." (CW)

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

Comprehensive comparative analysis and identification of RNA-binding protein domains: multi-class classification and feature selection.

PubMed

Jahandideh, Samad; Srinivasasainagendra, Vinodh; Zhi, Degui

2012-11-07

RNA-protein interaction plays an important role in various cellular processes, such as protein synthesis, gene regulation, post-transcriptional gene regulation, alternative splicing, and infections by RNA viruses. In this study, using Gene Ontology Annotated (GOA) and Structural Classification of Proteins (SCOP) databases an automatic procedure was designed to capture structurally solved RNA-binding protein domains in different subclasses. Subsequently, we applied tuned multi-class SVM (TMCSVM), Random Forest (RF), and multi-class ℓ1/ℓq-regularized logistic regression (MCRLR) for analysis and classifying RNA-binding protein domains based on a comprehensive set of sequence and structural features. In this study, we compared prediction accuracy of three different state-of-the-art predictor methods. From our results, TMCSVM outperforms the other methods and suggests the potential of TMCSVM as a useful tool for facilitating the multi-class prediction of RNA-binding protein domains. On the other hand, MCRLR by elucidating importance of features for their contribution in predictive accuracy of RNA-binding protein domains subclasses, helps us to provide some biological insights into the roles of sequences and structures in protein-RNA interactions.

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 unchanged inner structure. Poor roundness of gold particles and preservation of their primary inner structures indicate close proximity of primary source.

Universities' Access to Research Funds: Do Institutional Features and Strategies Matter?

ERIC Educational Resources Information Center

Rossi, Federica

2009-01-01

Competitively allocated research funds, from both public and private sources, constitute an increasing share of university revenues. The article investigates empirically, using data on the Italian university system, whether structural and strategic features of universities--such as size, age and especially the importance that they assign to their…

Conserved and variable domains of RNase MRP RNA.

PubMed

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

2009-01-01

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

Crystal structures of native and xylosaccharide-bound alkali thermostable xylanase from an alkalophilic Bacillus sp. NG-27: Structural insights into alkalophilicity and implications for adaptation to polyextreme conditions

PubMed Central

Manikandan, Karuppasamy; Bhardwaj, Amit; Gupta, Naveen; Lokanath, Neratur K.; Ghosh, Amit; Reddy, Vanga Siva; Ramakumar, Suryanarayanarao

2006-01-01

Crystal structures are known for several glycosyl hydrolase family 10 (GH10) xylanases. However, none of them is from an alkalophilic organism that can grow in alkaline conditions. We have determined the crystal structures at 2.2 Å of a GH10 extracellular endoxylanase (BSX) from an alkalophilic Bacillus sp. NG-27, for the native and the complex enzyme with xylosaccharides. The industrially important enzyme is optimally active and stable at 343 K and at a pH of 8.4. Comparison of the structure of BSX with those of other thermostable GH10 xylanases optimally active at acidic or close to neutral pH showed that the solvent-exposed acidic amino acids, Asp and Glu, are markedly enhanced in BSX, while solvent-exposed Asn was noticeably depleted. The BSX crystal structure when compared with putative three-dimensional homology models of other extracellular alkalophilic GH10 xylanases from alkalophilic organisms suggests that a protein surface rich in acidic residues may be an important feature common to these alkali thermostable enzymes. A comparison of the surface features of BSX and of halophilic proteins allowed us to predict the activity of BSX at high salt concentrations, which we verified through experiments. This offered us important lessons in the polyextremophilicity of proteins, where understanding the structural features of a protein stable in one set of extreme conditions provided clues about the activity of the protein in other extreme conditions. The work brings to the fore the role of the nature and composition of solvent-exposed residues in the adaptation of enzymes to polyextreme conditions, as in BSX. PMID:16823036

Bioinspired Single-Walled Carbon Nanotubes as a Spider Silk Structure for Ultrahigh Mechanical Property.

PubMed

Luo, Chengzhi; Li, Fangying; Li, Delong; Fu, Qiang; Pan, Chunxu

2016-11-16

Due to its unique hierarchical structure, natural spider silk features exceptional mechanical properties such as high tensile strength and great extensibility, making it one of the toughest materials. Herein, we design bioinspired spider silk single-walled carbon nanotubes (BISS-SWCNTs) that combine the hierarchical structure of spider silk and the high strength and conductivity of SWCNTs. To imitate the hierarchical structure, Fe nanoparticles are embedded on the surface of directly synthesized SWCNTs skeleton followed by coating an amorphous carbon layer. The carbon layer forms the spider silk-featured skin-core structure with SWCNTs, thus making the tube junction tougher. The embedded Fe nanoparticles act as glue spots for preventing interfacial slippages between the BISS-SWCNTs and the reinforced matrix. With only 2.1 wt % BISS-SWCNTs added, the tensile strength and Young's modulus of the BISS-SWCNTs/PMMA composites can be improved by 300%. More importantly, the BISS-SWCNTs also retain the high conductivity and transmittance of the pristine SWCNTs film. This unique bioinspired material will be of great importance in applications of multifunctional composite materials and has important implications for the future of biomimetic materials.

Chimaeric sounds reveal dichotomies in auditory perception

PubMed Central

Smith, Zachary M.; Delgutte, Bertrand; Oxenham, Andrew J.

2008-01-01

By Fourier's theorem1, signals can be decomposed into a sum of sinusoids of different frequencies. This is especially relevant for hearing, because the inner ear performs a form of mechanical Fourier transform by mapping frequencies along the length of the cochlear partition. An alternative signal decomposition, originated by Hilbert2, is to factor a signal into the product of a slowly varying envelope and a rapidly varying fine time structure. Neurons in the auditory brainstem3–6 sensitive to these features have been found in mammalian physiological studies. To investigate the relative perceptual importance of envelope and fine structure, we synthesized stimuli that we call ‘auditory chimaeras’, which have the envelope of one sound and the fine structure of another. Here we show that the envelope is most important for speech reception, and the fine structure is most important for pitch perception and sound localization. When the two features are in conflict, the sound of speech is heard at a location determined by the fine structure, but the words are identified according to the envelope. This finding reveals a possible acoustic basis for the hypothesized ‘what’ and ‘where’ pathways in the auditory cortex7–10. PMID:11882898

Evolution of volcanic and tectonic features in caldera settings and their importance in the localization of ore deposits

USGS Publications Warehouse

Rytuba, J.J.

1994-01-01

Many calderas are located along regionally important fault zones that are intermittently active before and after the caldera cycle. In mineralized calderas, the ore deposits are controlled by structures developed during caldera formation and by regional faults which intersect and reactivate the caldera-related structures. The paper discusses the importance of the different stages of caldera formation in connection with the localization of ore deposits. -from Author

Molecular-Scale Features that Govern the Effects of O-Glycosylation on a Carbohydrate-Binding Module

DOE PAGES

Guan, Xiaoyang; Chaffey, Patrick K.; Zeng, Chen; ...

2015-09-21

The protein glycosylation is a ubiquitous post-translational modification in all kingdoms of life. Despite its importance in molecular and cellular biology, the molecular-level ramifications of O-glycosylation on biomolecular structure and function remain elusive. Here, we took a small model glycoprotein and changed the glycan structure and size, amino acid residues near the glycosylation site, and glycosidic linkage while monitoring any corresponding changes to physical stability and cellulose binding affinity. The results of this study reveal the collective importance of all the studied features in controlling the most pronounced effects of O-glycosylation in this system. This study suggests the possibility ofmore » designing proteins with multiple improved properties by simultaneously varying the structures of O-glycans and amino acids local to the glycosylation site.« less

Individual MRI and radiographic features of knee OA in subjects with unilateral knee pain: Health ABC study

PubMed Central

Javaid, MK; Kiran, A; Guermazi, A; Kwoh, K; Zaim, S; Carbone, L; Harris, T.; McCulloch, C.E.; Arden, NK; Lane, NE; Felson, D; Nevitt, M

2012-01-01

Strong associations between radiographic features of knee OA and pain have been demonstrated in persons with unilateral knee symptoms. Our objectives were to compare radiographic with MRI features of knee OA and assess the discrimination between painful and non-painful knees in persons with unilateral symptoms. 283 individuals with unilateral knee pain aged 71 to 80 years from Health ABC, a study of weight-related diseases and mobility, had bilateral knee radiographs, read for KL grade and individual radiographic features, and 1.5T MRIs, read using WORMS. The association of structural features with pain was assessed using a within-person case/control design and conditional logistic regression. Receiver operator characteristics (ROC) were then used to test the discriminatory performance of structural features. In conditional logistic analyses, knee pain was significantly associated with both radiographic (any JSN grade >=1: OR 3.20 (1.79 – 5.71) and MRI (any cartilage defect:>=2: OR 3.67 (1.49 – 9.04)) features. However, most subjects had MR detected osteophytes, cartilage and bone marrow lesions in both knees and no individual structural feature discriminated well between painful and non-painful knees using ROC. The best performing MRI feature (synovitis/effusion) was not significantly more informative than KL grade >=2 (p=0.42). In persons with unilateral knee pain, MR and radiographic features were associated with knee pain confirming an important role in the etiology of pain. However, no single MRI or radiographic finding performed well in discriminating painful from non-painful knees. Further work is needed to examine how structural and non-structural factors influence knee pain. PMID:22736267

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

PubMed

Jiao, Xiong; Ranganathan, Shoba

2017-11-07

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

A practical modification of horizontal line sampling for snag and cavity tree inventory

Treesearch

M. J. Ducey; G. J. Jordan; J. H. Gove; H. T. Valentine

2002-01-01

Snags and cavity trees are important structural features in forests, but they are often sparsely distributed, making efficient inventories problematic. We present a straightforward modification of horizontal line sampling designed to facilitate inventory of these features while remaining compatible with commonly employed sampling methods for the living overstory. The...

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

PubMed

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

2016-08-24

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

Sentiment analysis of feature ranking methods for classification accuracy

NASA Astrophysics Data System (ADS)

Joseph, Shashank; Mugauri, Calvin; Sumathy, S.

2017-11-01

Text pre-processing and feature selection are important and critical steps in text mining. Text pre-processing of large volumes of datasets is a difficult task as unstructured raw data is converted into structured format. Traditional methods of processing and weighing took much time and were less accurate. To overcome this challenge, feature ranking techniques have been devised. A feature set from text preprocessing is fed as input for feature selection. Feature selection helps improve text classification accuracy. Of the three feature selection categories available, the filter category will be the focus. Five feature ranking methods namely: document frequency, standard deviation information gain, CHI-SQUARE, and weighted-log likelihood -ratio is analyzed.

Differential role of molten globule and protein folding in distinguishing unique features of botulinum neurotoxin.

PubMed

Kumar, Raj; Kukreja, Roshan V; Cai, Shuowei; Singh, Bal R

2014-06-01

Botulinum neurotoxins (BoNTs) are proteins of great interest not only because of their extreme toxicity but also paradoxically for their therapeutic applications. All the known serotypes (A-G) have varying degrees of longevity and potency inside the neuronal cell. Differential chemical modifications such as phosphorylation and ubiquitination have been suggested as possible mechanisms for their longevity, but the molecular basis of the longevity remains unclear. Since the endopeptidase domain (light chain; LC) of toxin apparently survives inside the neuronal cells for months, it is important to examine the structural features of this domain to understand its resistance to intracellular degradation. Published crystal structures (both botulinum neurotoxins and endopeptidase domain) have not provided adequate explanation for the intracellular longevity of the domain. Structural features obtained from spectroscopic analysis of LCA and LCB were similar, and a PRIME (PReImminent Molten Globule Enzyme) conformation appears to be responsible for their optimal enzymatic activity at 37°C. LCE, on the other hand, was although optimally active at 37°C, but its active conformation differed from the PRIME conformation of LCA and LCB. This study establishes and confirms our earlier finding that an optimally active conformation of these proteins in the form of PRIME exists for the most poisonous poison, botulinum neurotoxin. There are substantial variations in the structural and functional characteristics of these active molten globule related structures among the three BoNT endopeptidases examined. These differential conformations of LCs are important in understanding the fundamental structural features of proteins, and their possible connection to intracellular longevity could provide significant clues for devising new countermeasures and effective therapeutics. Copyright © 2014 Elsevier B.V. All rights reserved.

Ion Spectral Structures Observed by the Van Allen Probes and Cluster

NASA Astrophysics Data System (ADS)

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

2014-12-01

During the last decades several missions have recorded the presence of dynamic spectral features of energetic ions in the inner magnetosphere. Previous studies have revealed single "nose-like" structures occurring alone and simultaneous nose-like structures (up to three). In this study we also include signatures of new types of ion structure, namely "trunk-like" and "tusk-like" structures. All the ion structures are named after the characteristic shapes of energy bands or gaps in the energy-time spectrograms of in situ measured ion fluxes. They constitute the observational signatures of ion acceleration, transport, and loss in the global magnetosphere. Multi-spacecraft analysis of these structures is important to understand their spatial distribution and temporal evolution. Mass spectrometers onboard Cluster (in a polar orbit) and the Van Allen Probes (in an equatorial orbit) measure energetic hydrogen, helium, and oxygen ions near the inner edge of the plasma sheet, where these ion structures are observed. We present a statistical study of the ion structures, using >1-year measurements from the two missions during the Van Allen Probes era. The results provide important details about the spatial distribution (dependence on geocentric distance and magnetic local time), spectral features of the structures (e.g., characteristic energy and differences among species), and geomagnetic and solar wind conditions under which these structures occur.

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.

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

PubMed

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

2009-05-01

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

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.

Cognitive Structures in Vocational Information Processing and Decision Making.

ERIC Educational Resources Information Center

Nevill, Dorothy D.; And Others

1986-01-01

Tested the assumptions that the structural features of vocational schemas affect vocational information processing and career self-efficacy. Results indicated that effective vocational information processing was facilitated by well-integrated systems that processed information along fewer dimensions. The importance of schematic organization on the…

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

Wu, Huixian; Wacker, Daniel; Mileni, Mauro

Opioid receptors mediate the actions of endogenous and exogenous opioids on many physiological processes, including the regulation of pain, respiratory drive, mood, and - in the case of {kappa}-opioid receptor ({kappa}-OR) - dysphoria and psychotomimesis. Here we report the crystal structure of the human {kappa}-OR in complex with the selective antagonist JDTic, arranged in parallel dimers, at 2.9 {angstrom} resolution. The structure reveals important features of the ligand-binding pocket that contribute to the high affinity and subtype selectivity of JDTic for the human {kappa}-OR. Modelling of other important {kappa}-OR-selective ligands, including the morphinan-derived antagonists norbinaltorphimine and 5'-guanidinonaltrindole, and the diterpenemore » agonist salvinorin A analogue RB-64, reveals both common and distinct features for binding these diverse chemotypes. Analysis of site-directed mutagenesis and ligand structure-activity relationships confirms the interactions observed in the crystal structure, thereby providing a molecular explanation for {kappa}-OR subtype selectivity, and essential insights for the design of compounds with new pharmacological properties targeting the human {kappa}-OR.« less

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.

On the importance of cotranscriptional RNA structure formation

PubMed Central

Lai, Daniel; Proctor, Jeff R.; Meyer, Irmtraud M.

2013-01-01

The expression of genes, both coding and noncoding, can be significantly influenced by RNA structural features of their corresponding transcripts. There is by now mounting experimental and some theoretical evidence that structure formation in vivo starts during transcription and that this cotranscriptional folding determines the functional RNA structural features that are being formed. Several decades of research in bioinformatics have resulted in a wide range of computational methods for predicting RNA secondary structures. Almost all state-of-the-art methods in terms of prediction accuracy, however, completely ignore the process of structure formation and focus exclusively on the final RNA structure. This review hopes to bridge this gap. We summarize the existing evidence for cotranscriptional folding and then review the different, currently used strategies for RNA secondary-structure prediction. Finally, we propose a range of ideas on how state-of-the-art methods could be potentially improved by explicitly capturing the process of cotranscriptional structure formation. PMID:24131802

The Thematic Structure of the Sentence in English and Polish.

ERIC Educational Resources Information Center

Szwedek, Aleksander

An important feature of the sentence in any language is its thematic structure, new/given information organization. It has been found that in English, where word order is grammatically determined, the thematic structure is signalled by the place of the sentence stress. If an indefinite noun (new information) is present in the sentence, it bears…

Spatio-temporal Event Classification using Time-series Kernel based Structured Sparsity

PubMed Central

Jeni, László A.; Lőrincz, András; Szabó, Zoltán; Cohn, Jeffrey F.; Kanade, Takeo

2016-01-01

In many behavioral domains, such as facial expression and gesture, sparse structure is prevalent. This sparsity would be well suited for event detection but for one problem. Features typically are confounded by alignment error in space and time. As a consequence, high-dimensional representations such as SIFT and Gabor features have been favored despite their much greater computational cost and potential loss of information. We propose a Kernel Structured Sparsity (KSS) method that can handle both the temporal alignment problem and the structured sparse reconstruction within a common framework, and it can rely on simple features. We characterize spatio-temporal events as time-series of motion patterns and by utilizing time-series kernels we apply standard structured-sparse coding techniques to tackle this important problem. We evaluated the KSS method using both gesture and facial expression datasets that include spontaneous behavior and differ in degree of difficulty and type of ground truth coding. KSS outperformed both sparse and non-sparse methods that utilize complex image features and their temporal extensions. In the case of early facial event classification KSS had 10% higher accuracy as measured by F1 score over kernel SVM methods1. PMID:27830214

Contrasting Patterns in Solitary and Eusocial Bees While Responding to Landscape Features in the Brazilian Cerrado: a Multiscaled Perspective.

PubMed

Silva, D P; Nogueira, D S; De Marco, P

2017-06-01

Landscape structure is an important determinant of biological fluxes and species composition, but species do not respond equally to landscape features or spatial extents. Evaluating "multi-scale" responses of species to landscape structure is an important framework to be considered, allowing insights about habitat requirements for different groups. We evaluated the response of Brazilian Cerrado's bees (eusocial vs. solitary ones) to both the amount and isolation of remnant vegetation in eight nested multiple-local scales. Response variables included abundance, observed, and estimated species richness, and beta diversity (split into nestedness and turnover resultant dissimilarities). Eusocial species' abundance responded to landscape structure at narrow scales of fragment isolation (250 m of radius from sampling sites), while solitary species' abundance responded to broader scales to fragment area (2000 m). Eusocial species nestedness also responded to landscape features in broader scales (1500 m), especially to increasing fragment isolation. However, all the remaining response variables did not respond to any other landscape variables in any spatial scale considered. Such contrasting responses of the abundances of eusocial vs. solitary species are related to the inherent life-history traits of each group. Important attributes in this context are different requirements on food resources, population features, and flight abilities. Species-specific dispersal abilities may be the main determinants of the nested patterns found for eusocial species at 1500 m. Considering these results, we suggest that different bee groups are considered separately in further landscape analyses, especially in other Brazilian biomes, for a better understanding of landscape effects on these organisms.

Ab initio calculation of the ion feature in x-ray Thomson scattering.

PubMed

Plagemann, Kai-Uwe; Rüter, Hannes R; Bornath, Thomas; Shihab, Mohammed; Desjarlais, Michael P; Fortmann, Carsten; Glenzer, Siegfried H; Redmer, Ronald

2015-07-01

The spectrum of x-ray Thomson scattering is proportional to the dynamic structure factor. An important contribution is the ion feature which describes elastic scattering of x rays off electrons. We apply an ab initio method for the calculation of the form factor of bound electrons, the slope of the screening cloud of free electrons, and the ion-ion structure factor in warm dense beryllium. With the presented method we can calculate the ion feature from first principles. These results will facilitate a better understanding of x-ray scattering in warm dense matter and an accurate measurement of ion temperatures which would allow determining nonequilibrium conditions, e.g., along shock propagation.

Use of the Primitive Unit Cell in Understanding Subtle Features of the Cubic Closest-Packed Structure

ERIC Educational Resources Information Center

Hawkins, John A.; Rittenhouse, Jeffrey L.; Soper, Linda M.; Rittenhouse, Robert C.

2008-01-01

One of the most important crystal structures adopted by metals is characterized by the "abcabc"...stacking of close-packed layers. This structure is commonly referred to in textbooks as the cubic close-packed (ccp) or face-centered cubic (fcc) structure, since the entire lattice can be generated by replication of a face-centered cubic unit cell…

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

Ion spectral structures observed by the Van Allen Probes

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.

2015-12-01

During the last decades several missions have recorded the presence of dynamic spectral features of energetic ions in the inner magnetosphere. Previous studies have reported single "nose-like" structures occurring alone and simultaneous nose-like structures (up to three). These ion structures are named after the characteristic shapes of energy bands or gaps in the energy-time spectrograms of in situ measured ion fluxes. They constitute the observational signatures of ion acceleration, transport, and loss in the global magnetosphere. The HOPE mass spectrometer onboard the Van Allen Probes measures energetic hydrogen, helium, and oxygen ions near the inner edge of the plasma sheet, where these ion structures are observed. We present a statistical study of nose-like structures, using 2-years measurements from the HOPE instrument. The results provide important details about the spatial distribution (dependence on geocentric distance), spectral features of the structures (differences among species), and geomagnetic conditions under which these structures occur.

The future of primordial features with large-scale structure surveys

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

The future of primordial features with large-scale structure surveys

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

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

2016-11-01

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

A novel Multi-Agent Ada-Boost algorithm for predicting protein structural class with the information of protein secondary structure.

PubMed

Fan, Ming; Zheng, Bin; Li, Lihua

2015-10-01

Knowledge of the structural class of a given protein is important for understanding its folding patterns. Although a lot of efforts have been made, it still remains a challenging problem for prediction of protein structural class solely from protein sequences. The feature extraction and classification of proteins are the main problems in prediction. In this research, we extended our earlier work regarding these two aspects. In protein feature extraction, we proposed a scheme by calculating the word frequency and word position from sequences of amino acid, reduced amino acid, and secondary structure. For an accurate classification of the structural class of protein, we developed a novel Multi-Agent Ada-Boost (MA-Ada) method by integrating the features of Multi-Agent system into Ada-Boost algorithm. Extensive experiments were taken to test and compare the proposed method using four benchmark datasets in low homology. The results showed classification accuracies of 88.5%, 96.0%, 88.4%, and 85.5%, respectively, which are much better compared with the existing methods. The source code and dataset are available on request.

Structure-Based Design of Highly Selective Inhibitors of the CREB Binding Protein Bromodomain.

PubMed

Denny, R Aldrin; Flick, Andrew C; Coe, Jotham; Langille, Jonathan; Basak, Arindrajit; Liu, Shenping; Stock, Ingrid; Sahasrabudhe, Parag; Bonin, Paul; Hay, Duncan A; Brennan, Paul E; Pletcher, Mathew; Jones, Lyn H; Chekler, Eugene L Piatnitski

2017-07-13

Chemical probes are required for preclinical target validation to interrogate novel biological targets and pathways. Selective inhibitors of the CREB binding protein (CREBBP)/EP300 bromodomains are required to facilitate the elucidation of biology associated with these important epigenetic targets. Medicinal chemistry optimization that paid particular attention to physiochemical properties delivered chemical probes with desirable potency, selectivity, and permeability attributes. An important feature of the optimization process was the successful application of rational structure-based drug design to address bromodomain selectivity issues (particularly against the structurally related BRD4 protein).

The track structure in condensed matter

NASA Astrophysics Data System (ADS)

Kaplan, I. G.

1995-11-01

The physical stage of track formation in a condensed phase is discussed. For interaction of charged particles with condensed molecular media its most important specific features are: (a) the continuous oscillator strength distribution with the broak peak in the energy range 21-22 eV attributed to the collective plasmon-type state; (b) the lowering of ionization potential compared to a gas phase. These specific features must be taken into account for simulation of track structures. The great difference in mass and charge for a electron and heavy ions cause a qualitative difference in their track structures. We analyse the structure of heavy ion tracks and prove the impossibility to use the LET as a universal characteristic for the radiation action of different ions.

Abnormal semantic knowledge in a case of developmental amnesia.

PubMed

Blumenthal, Anna; Duke, Devin; Bowles, Ben; Gilboa, Asaf; Rosenbaum, R Shayna; Köhler, Stefan; McRae, Ken

2017-07-28

An important theory holds that semantic knowledge can develop independently of episodic memory. One strong source of evidence supporting this independence comes from the observation that individuals with early hippocampal damage leading to developmental amnesia generally perform normally on standard tests of semantic memory, despite their profound impairment in episodic memory. However, one aspect of semantic memory that has not been explored is conceptual structure. We built on the theoretically important distinction between intrinsic features of object concepts (e.g., shape, colour, parts) and extrinsic features (e.g., how something is used, where it is typically located). The accrual of extrinsic feature knowledge that is important for concepts such as chair or spoon may depend on binding mechanisms in the hippocampus. We tested HC, an individual with developmental amnesia due to a well-characterized lesion of the hippocampus, on her ability to generate semantic features for object concepts. HC generated fewer extrinsic features than controls, but a similar number of intrinsic features than controls. We also tested her on typicality ratings. Her typicality ratings were abnormal for nonliving things (which more strongly depend on extrinsic features), but normal for living things (which more strongly depend on intrinsic features). In contrast, NB, who has MTL but not hippocampal damage due to surgery, showed no impairments in either task. These results suggest that episodic and semantic memory are not entirely independent, and that the hippocampus is important for learning some aspects of conceptual knowledge. Copyright © 2017 Elsevier Ltd. All rights reserved.

Linguistic feature analysis for protein interaction extraction

PubMed Central

2009-01-01

Background The rapid growth of the amount of publicly available reports on biomedical experimental results has recently caused a boost of text mining approaches for protein interaction extraction. Most approaches rely implicitly or explicitly on linguistic, i.e., lexical and syntactic, data extracted from text. However, only few attempts have been made to evaluate the contribution of the different feature types. In this work, we contribute to this evaluation by studying the relative importance of deep syntactic features, i.e., grammatical relations, shallow syntactic features (part-of-speech information) and lexical features. For this purpose, we use a recently proposed approach that uses support vector machines with structured kernels. Results Our results reveal that the contribution of the different feature types varies for the different data sets on which the experiments were conducted. The smaller the training corpus compared to the test data, the more important the role of grammatical relations becomes. Moreover, deep syntactic information based classifiers prove to be more robust on heterogeneous texts where no or only limited common vocabulary is shared. Conclusion Our findings suggest that grammatical relations play an important role in the interaction extraction task. Moreover, the net advantage of adding lexical and shallow syntactic features is small related to the number of added features. This implies that efficient classifiers can be built by using only a small fraction of the features that are typically being used in recent approaches. PMID:19909518

Modulation of a Pore in the Capsid of JC Polyomavirus Reduces Infectivity and Prevents Exposure of the Minor Capsid Proteins

PubMed Central

Nelson, Christian D. S.; Ströh, Luisa J.; Gee, Gretchen V.; O'Hara, Bethany A.; Stehle, Thilo

2015-01-01

ABSTRACT JC polyomavirus (JCPyV) infection of immunocompromised individuals results in the fatal demyelinating disease progressive multifocal leukoencephalopathy (PML). The viral capsid of JCPyV is composed primarily of the major capsid protein virus protein 1 (VP1), and pentameric arrangement of VP1 monomers results in the formation of a pore at the 5-fold axis of symmetry. While the presence of this pore is conserved among polyomaviruses, its functional role in infection or assembly is unknown. Here, we investigate the role of the 5-fold pore in assembly and infection of JCPyV by generating a panel of mutant viruses containing amino acid substitutions of the residues lining this pore. Multicycle growth assays demonstrated that the fitness of all mutants was reduced compared to that of the wild-type virus. Bacterial expression of VP1 pentamers containing substitutions to residues lining the 5-fold pore did not affect pentamer assembly or prevent association with the VP2 minor capsid protein. The X-ray crystal structures of selected pore mutants contained subtle changes to the 5-fold pore, and no other changes to VP1 were observed. Pore mutant pseudoviruses were not deficient in assembly, packaging of the minor capsid proteins, or binding to cells or in transport to the host cell endoplasmic reticulum. Instead, these mutant viruses were unable to expose VP2 upon arrival to the endoplasmic reticulum, a step that is critical for infection. This study demonstrated that the 5-fold pore is an important structural feature of JCPyV and that minor modifications to this structure have significant impacts on infectious entry. IMPORTANCE JCPyV is an important human pathogen that causes a severe neurological disease in immunocompromised individuals. While the high-resolution X-ray structure of the major capsid protein of JCPyV has been solved, the importance of a major structural feature of the capsid, the 5-fold pore, remains poorly understood. This pore is conserved across polyomaviruses and suggests either that these viruses have limited structural plasticity in this region or that this pore is important in infection or assembly. Using a structure-guided mutational approach, we showed that modulation of this pore severely inhibits JCPyV infection. These mutants do not appear deficient in assembly or early steps in infectious entry and are instead reduced in their ability to expose a minor capsid protein in the host cell endoplasmic reticulum. Our work demonstrates that the 5-fold pore is an important structural feature for JCPyV. PMID:25609820

Bubble structure evaluation method of sponge cake by using image morphology

NASA Astrophysics Data System (ADS)

Kato, Kunihito; Yamamoto, Kazuhiko; Nonaka, Masahiko; Katsuta, Yukiyo; Kasamatsu, Chinatsu

2007-01-01

Nowadays, many evaluation methods for food industry by using image processing are proposed. These methods are becoming new evaluation method besides the sensory test and the solid-state measurement that have been used for the quality evaluation recently. The goal of our research is structure evaluation of sponge cake by using the image processing. In this paper, we propose a feature extraction method of the bobble structure in the sponge cake. Analysis of the bubble structure is one of the important properties to understand characteristics of the cake from the image. In order to take the cake image, first we cut cakes and measured that's surface by using the CIS scanner, because the depth of field of this type scanner is very shallow. Therefore the bubble region of the surface has low gray scale value, and it has a feature that is blur. We extracted bubble regions from the surface images based on these features. The input image is binarized, and the feature of bubble is extracted by the morphology analysis. In order to evaluate the result of feature extraction, we compared correlation with "Size of the bubble" of the sensory test result. From a result, the bubble extraction by using morphology analysis gives good correlation. It is shown that our method is as well as the subjectivity evaluation.

Complex, multi-scale small intestinal topography replicated in cellular growth substrates fabricated via chemical vapor deposition of Parylene C.

PubMed

Koppes, Abigail N; Kamath, Megha; Pfluger, Courtney A; Burkey, Daniel D; Dokmeci, Mehmet; Wang, Lin; Carrier, Rebecca L

2016-08-22

Native small intestine possesses distinct multi-scale structures (e.g., crypts, villi) not included in traditional 2D intestinal culture models for drug delivery and regenerative medicine. The known impact of structure on cell function motivates exploration of the influence of intestinal topography on the phenotype of cultured epithelial cells, but the irregular, macro- to submicron-scale features of native intestine are challenging to precisely replicate in cellular growth substrates. Herein, we utilized chemical vapor deposition of Parylene C on decellularized porcine small intestine to create polymeric intestinal replicas containing biomimetic irregular, multi-scale structures. These replicas were used as molds for polydimethylsiloxane (PDMS) growth substrates with macro to submicron intestinal topographical features. Resultant PDMS replicas exhibit multiscale resolution including macro- to micro-scale folds, crypt and villus structures, and submicron-scale features of the underlying basement membrane. After 10 d of human epithelial colorectal cell culture on PDMS substrates, the inclusion of biomimetic topographical features enhanced alkaline phosphatase expression 2.3-fold compared to flat controls, suggesting biomimetic topography is important in induced epithelial differentiation. This work presents a facile, inexpensive method for precisely replicating complex hierarchal features of native tissue, towards a new model for regenerative medicine and drug delivery for intestinal disorders and diseases.

Controlling the intermediate structure of an ionic liquid for f-block element separations

DOE PAGES

Abney, Carter W.; Do, Changwoo; Luo, Huimin; ...

2017-04-19

Recent research has revealed molecular structure beyond the inner coordination sphere is essential in defining the performance of separations processes, but nevertheless remains largely unexplored. Here we apply small angle neutron scattering (SANS) and x-ray absorption fine structure (XAFS) spectroscopy to investigate the structure of an ionic liquid system studied for f-block element separations. SANS data reveal dramatic changes in the ionic liquid microstructure (~150 Å) which we demonstrate can be controlled by judicious selection of counter ion. Mesoscale structural features (> 500 Å) are also observed as a function of metal concentration. XAFS analysis supports formation of extended aggregatemore » structures, similar to those observed in traditional solvent extraction processes, and suggest additional parallels may be drawn from further study. As a result, achieving precise tunability over the intermediate features is an important development in controlling mesoscale structure and realizing advanced new forms of soft matter.« less

Parity violation in electron scattering

DOE PAGES

Souder, P.; Paschke, K. D.

2015-12-22

By comparing the cross sections for left- and right-handed electrons scattered from various unpolarized nuclear targets, the small parity-violating asymmetry can be measured. These asymmetry data probe a wide variety of important topics, including searches for new fundamental interactions and important features of nuclear structure that cannot be studied with other probes. A special feature of these experiments is that the results are interpreted with remarkably few theoretical uncertainties, which justifies pushing the experiments to the highest possible precision. To measure the small asymmetries accurately, a number of novel experimental techniques have been developed.

The Significance of Interfacial Water Structure in Soluble Salt Flotation Systems.

PubMed

Hancer, M.; Celik, M. S.; Miller, J. D.

2001-03-01

Flotation of soluble salts with dodecyl amine hydrochloride (DAH) and sodium dodecyl sulfate (SDS) collectors has demonstrated that the interfacial water structure and hydration states of soluble salt surfaces together with the precipitation tendency of the corresponding collector salts are of considerable importance in explaining their flotation behavior. In particular, the high concentration of ions in these soluble salt brines and their hydration appear to modify the bulk and interfacial structure of water as revealed by contact angle measurements and this effect is shown to be an important feature in the flotation chemistry of soluble salt minerals including alkali halide and alkali oxyanion salts. Depending on characteristic chemical features (salt type), the salt can serve either as a structure maker, in which intermolecular hydrogen bonding between water molecules is facilitated, or as a structure breaker, in which intermolecular hydrogen bonding between water molecules is disrupted. For structure making salts the brine completely wets the salt surface and no contact angle can be measured. For structure breaking salts the brine does not completely wet the salt surface and a finite contact angle is measured. In this regard it has been found that soluble salt flotation either with the cationic DAH or anionic SDS collector is possible only if the salt is a structure breaker. Copyright 2001 Academic Press.

Fungal prion HET-s as a model for structural complexity and self-propagation in prions.

PubMed

Wan, William; Stubbs, Gerald

2014-04-08

The highly ordered and reproducible structure of the fungal prion HET-s makes it an excellent model system for studying the inherent properties of prions, self-propagating infectious proteins that have been implicated in a number of fatal diseases. In particular, the HET-s prion-forming domain readily folds into a relatively complex two-rung β-solenoid amyloid. The faithful self-propagation of this fold involves a diverse array of inter- and intramolecular structural features. These features include a long flexible loop connecting the two rungs, buried polar residues, salt bridges, and asparagine ladders. We have used site-directed mutagenesis and X-ray fiber diffraction to probe the relative importance of these features for the formation of β-solenoid structure, as well as the cumulative effects of multiple mutations. Using fibrillization kinetics and chemical stability assays, we have determined the biophysical effects of our mutations on the assembly and stability of the prion-forming domain. We have found that a diversity of structural features provides a level of redundancy that allows robust folding and stability even in the face of significant sequence alterations and suboptimal environmental conditions. Our findings provide fundamental insights into the structural interactions necessary for self-propagation. Propagation of prion structure seems to require an obligatory level of complexity that may not be reproducible in short peptide models.

Prediction of protein structural classes by Chou's pseudo amino acid composition: approached using continuous wavelet transform and principal component analysis.

PubMed

Li, Zhan-Chao; Zhou, Xi-Bin; Dai, Zong; Zou, Xiao-Yong

2009-07-01

A prior knowledge of protein structural classes can provide useful information about its overall structure, so it is very important for quick and accurate determination of protein structural class with computation method in protein science. One of the key for computation method is accurate protein sample representation. Here, based on the concept of Chou's pseudo-amino acid composition (AAC, Chou, Proteins: structure, function, and genetics, 43:246-255, 2001), a novel method of feature extraction that combined continuous wavelet transform (CWT) with principal component analysis (PCA) was introduced for the prediction of protein structural classes. Firstly, the digital signal was obtained by mapping each amino acid according to various physicochemical properties. Secondly, CWT was utilized to extract new feature vector based on wavelet power spectrum (WPS), which contains more abundant information of sequence order in frequency domain and time domain, and PCA was then used to reorganize the feature vector to decrease information redundancy and computational complexity. Finally, a pseudo-amino acid composition feature vector was further formed to represent primary sequence by coupling AAC vector with a set of new feature vector of WPS in an orthogonal space by PCA. As a showcase, the rigorous jackknife cross-validation test was performed on the working datasets. The results indicated that prediction quality has been improved, and the current approach of protein representation may serve as a useful complementary vehicle in classifying other attributes of proteins, such as enzyme family class, subcellular localization, membrane protein types and protein secondary structure, etc.

Compressive strain in Lunae Planum-shortening across wrinkle ridges

NASA Technical Reports Server (NTRS)

Plescia, J. B.

1991-01-01

Wrinkle ridges have long been considered to be structural or structurally controlled features. Most, but not all, recent studies have converged on a model in which wrinkle ridges are structural features formed under compressive stress; the deformation being accommodated by faulting and folding. Given that wrinkle ridges are compressive tectonic features, an analysis of the associated shortening and strain provides important quantitative information about local and regional deformation. Lunae Planum is dominated by north-south trending ridges extending from Kasei Valles in the north to Valles Marineris in the south. To quantify the morphometric character, a photoclinometric study was undertaken for ridges on Lunae Planum using the Davis and Soderblom. More than 25 ridges were examined between long. 57 and 80 deg, lat. 5 to 25 deg N. For each ridge, several profiles were obtained along its length. Ridge width, total relief, and elevation offset were measured for each ridge. Analyses are given.

Separation of alkylphenols by normal-phase and reversed-phase high-performance liquid chromatography

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

Schabron, J.F.; Hurtubise, R.J.; Silver, H.F.

1978-11-01

Empirical correlation factors were developed which relate log k' values for alkylphenols, the naphthols, and two phenylphenols to structural features. Both normal-phase and reversed-phase chromatographic systems were studied. The stationary phases employed in the normal-phase work were ..mu..-Bondapak CN, ..mu..-Bondapak NH/sub 2/, and ..mu..-Porasil. The structural features which affect retention in the normal-phase chromatographic systems are the number of ortho substituents, the number of aliphatic carbons, and the number of aromatic rings. The stationary phases employed in the reversed-phase work were ..mu..-Bondapak C/sub 18/ and ..mu..-Bondapak CN. The structural features which affect retention in the reversed-phase chromatographic systems are themore » number of aliphatic carbons and the number of aromatic double bonds. On ..mu..-Bondapak C/sub 18/, the presence or absence of a nonaromatic ring is of added importance.« less

Vehicle license plate recognition based on geometry restraints and multi-feature decision

NASA Astrophysics Data System (ADS)

Wu, Jianwei; Wang, Zongyue

2005-10-01

Vehicle license plate (VLP) recognition is of great importance to many traffic applications. Though researchers have paid much attention to VLP recognition there has not been a fully operational VLP recognition system yet for many reasons. This paper discusses a valid and practical method for vehicle license plate recognition based on geometry restraints and multi-feature decision including statistical and structural features. In general, the VLP recognition includes the following steps: the location of VLP, character segmentation, and character recognition. This paper discusses the three steps in detail. The characters of VLP are always declining caused by many factors, which makes it more difficult to recognize the characters of VLP, therefore geometry restraints such as the general ratio of length and width, the adjacent edges being perpendicular are used for incline correction. Image Moment has been proved to be invariant to translation, rotation and scaling therefore image moment is used as one feature for character recognition. Stroke is the basic element for writing and hence taking it as a feature is helpful to character recognition. Finally we take the image moment, the strokes and the numbers of each stroke for each character image and some other structural features and statistical features as the multi-feature to match each character image with sample character images so that each character image can be recognized by BP neural net. The proposed method combines statistical and structural features for VLP recognition, and the result shows its validity and efficiency.

Spectral Regression Based Fault Feature Extraction for Bearing Accelerometer Sensor Signals

PubMed Central

Xia, Zhanguo; Xia, Shixiong; Wan, Ling; Cai, Shiyu

2012-01-01

Bearings are not only the most important element but also a common source of failures in rotary machinery. Bearing fault prognosis technology has been receiving more and more attention recently, in particular because it plays an increasingly important role in avoiding the occurrence of accidents. Therein, fault feature extraction (FFE) of bearing accelerometer sensor signals is essential to highlight representative features of bearing conditions for machinery fault diagnosis and prognosis. This paper proposes a spectral regression (SR)-based approach for fault feature extraction from original features including time, frequency and time-frequency domain features of bearing accelerometer sensor signals. SR is a novel regression framework for efficient regularized subspace learning and feature extraction technology, and it uses the least squares method to obtain the best projection direction, rather than computing the density matrix of features, so it also has the advantage in dimensionality reduction. The effectiveness of the SR-based method is validated experimentally by applying the acquired vibration signals data to bearings. The experimental results indicate that SR can reduce the computation cost and preserve more structure information about different bearing faults and severities, and it is demonstrated that the proposed feature extraction scheme has an advantage over other similar approaches. PMID:23202017

LINKING LUNG AIRWAY STRUCTURE TO PULMONARY FUNCTION VIA COMPOSITE BRIDGE REGRESSION

PubMed Central

Chen, Kun; Hoffman, Eric A.; Seetharaman, Indu; Jiao, Feiran; Lin, Ching-Long; Chan, Kung-Sik

2017-01-01

The human lung airway is a complex inverted tree-like structure. Detailed airway measurements can be extracted from MDCT-scanned lung images, such as segmental wall thickness, airway diameter, parent-child branch angles, etc. The wealth of lung airway data provides a unique opportunity for advancing our understanding of the fundamental structure-function relationships within the lung. An important problem is to construct and identify important lung airway features in normal subjects and connect these to standardized pulmonary function test results such as FEV1%. Among other things, the problem is complicated by the fact that a particular airway feature may be an important (relevant) predictor only when it pertains to segments of certain generations. Thus, the key is an efficient, consistent method for simultaneously conducting group selection (lung airway feature types) and within-group variable selection (airway generations), i.e., bi-level selection. Here we streamline a comprehensive procedure to process the lung airway data via imputation, normalization, transformation and groupwise principal component analysis, and then adopt a new composite penalized regression approach for conducting bi-level feature selection. As a prototype of composite penalization, the proposed composite bridge regression method is shown to admit an efficient algorithm, enjoy bi-level oracle properties, and outperform several existing methods. We analyze the MDCT lung image data from a cohort of 132 subjects with normal lung function. Our results show that, lung function in terms of FEV1% is promoted by having a less dense and more homogeneous lung comprising an airway whose segments enjoy more heterogeneity in wall thicknesses, larger mean diameters, lumen areas and branch angles. These data hold the potential of defining more accurately the “normal” subject population with borderline atypical lung functions that are clearly influenced by many genetic and environmental factors. PMID:28280520

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.

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

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

PubMed

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

2018-06-25

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

Asymmetric bagging and feature selection for activities prediction of drug molecules.

PubMed

Li, Guo-Zheng; Meng, Hao-Hua; Lu, Wen-Cong; Yang, Jack Y; Yang, Mary Qu

2008-05-28

Activities of drug molecules can be predicted by QSAR (quantitative structure activity relationship) models, which overcomes the disadvantages of high cost and long cycle by employing the traditional experimental method. With the fact that the number of drug molecules with positive activity is rather fewer than that of negatives, it is important to predict molecular activities considering such an unbalanced situation. Here, asymmetric bagging and feature selection are introduced into the problem and asymmetric bagging of support vector machines (asBagging) is proposed on predicting drug activities to treat the unbalanced problem. At the same time, the features extracted from the structures of drug molecules affect prediction accuracy of QSAR models. Therefore, a novel algorithm named PRIFEAB is proposed, which applies an embedded feature selection method to remove redundant and irrelevant features for asBagging. Numerical experimental results on a data set of molecular activities show that asBagging improve the AUC and sensitivity values of molecular activities and PRIFEAB with feature selection further helps to improve the prediction ability. Asymmetric bagging can help to improve prediction accuracy of activities of drug molecules, which can be furthermore improved by performing feature selection to select relevant features from the drug molecules data sets.

Structural Peculiarities of Social Mental Abilities of Future Teachers

ERIC Educational Resources Information Center

Yermentayevaa, Ardakh Rizabekovna; Kenzhebayeva, Kundyz Serikovna; Umirbekova, Akerke Nurlanbekovna; Aubakirova, Zhanat Kanashovna; Iskakova, Akmaral Bakytbekovna

2016-01-01

The problem of social intelligence of researchers has attracted attention in recent years. Social intelligence is one of the most important characteristics of teachers. The aim of this research was to study features of structure of social intelligence of future teachers. The respondents in this study were selected 360 students of pedagogical…

Structural vibration-based damage classification of delaminated smart composite laminates

NASA Astrophysics Data System (ADS)

Khan, Asif; Kim, Heung Soo; Sohn, Jung Woo

2018-03-01

Separation along the interfaces of layers (delamination) is a principal mode of failure in laminated composites and its detection is of prime importance for structural integrity of composite materials. In this work, structural vibration response is employed to detect and classify delaminations in piezo-bonded laminated composites. Improved layerwise theory and finite element method are adopted to develop the electromechanically coupled governing equation of a smart composite laminate with and without delaminations. Transient responses of the healthy and damaged structures are obtained through a surface bonded piezoelectric sensor by solving the governing equation in the time domain. Wavelet packet transform (WPT) and linear discriminant analysis (LDA) are employed to extract discriminative features from the structural vibration response of the healthy and delaminated structures. Dendrogram-based support vector machine (DSVM) is used to classify the discriminative features. The confusion matrix of the classification algorithm provided physically consistent results.

Theoretical Methods of Domain Structures in Ultrathin Ferroelectric Films: A Review

PubMed Central

Liu, Jianyi; Chen, Weijin; Wang, Biao; Zheng, Yue

2014-01-01

This review covers methods and recent developments of the theoretical study of domain structures in ultrathin ferroelectric films. The review begins with an introduction to some basic concepts and theories (e.g., polarization and its modern theory, ferroelectric phase transition, domain formation, and finite size effects, etc.) that are relevant to the study of domain structures in ultrathin ferroelectric films. Basic techniques and recent progress of a variety of important approaches for domain structure simulation, including first-principles calculation, molecular dynamics, Monte Carlo simulation, effective Hamiltonian approach and phase field modeling, as well as multiscale simulation are then elaborated. For each approach, its important features and relative merits over other approaches for modeling domain structures in ultrathin ferroelectric films are discussed. Finally, we review recent theoretical studies on some important issues of domain structures in ultrathin ferroelectric films, with an emphasis on the effects of interfacial electrostatics, boundary conditions and external loads. PMID:28788198

Quantifying the Hierarchical Order in Self-Aligned Carbon Nanotubes from Atomic to Micrometer Scale.

PubMed

Meshot, Eric R; Zwissler, Darwin W; Bui, Ngoc; Kuykendall, Tevye R; Wang, Cheng; Hexemer, Alexander; Wu, Kuang Jen J; Fornasiero, Francesco

2017-06-27

Fundamental understanding of structure-property relationships in hierarchically organized nanostructures is crucial for the development of new functionality, yet quantifying structure across multiple length scales is challenging. In this work, we used nondestructive X-ray scattering to quantitatively map the multiscale structure of hierarchically self-organized carbon nanotube (CNT) "forests" across 4 orders of magnitude in length scale, from 2.0 Å to 1.5 μm. Fully resolved structural features include the graphitic honeycomb lattice and interlayer walls (atomic), CNT diameter (nano), as well as the greater CNT ensemble (meso) and large corrugations (micro). Correlating orientational order across hierarchical levels revealed a cascading decrease as we probed finer structural feature sizes with enhanced sensitivity to small-scale disorder. Furthermore, we established qualitative relationships for single-, few-, and multiwall CNT forest characteristics, showing that multiscale orientational order is directly correlated with number density spanning 10 9 -10 12 cm -2 , yet order is inversely proportional to CNT diameter, number of walls, and atomic defects. Lastly, we captured and quantified ultralow-q meridional scattering features and built a phenomenological model of the large-scale CNT forest morphology, which predicted and confirmed that these features arise due to microscale corrugations along the vertical forest direction. Providing detailed structural information at multiple length scales is important for design and synthesis of CNT materials as well as other hierarchically organized nanostructures.

CCProf: exploring conformational change profile of proteins

PubMed Central

Chang, Che-Wei; Chou, Chai-Wei; Chang, Darby Tien-Hao

2016-01-01

In many biological processes, proteins have important interactions with various molecules such as proteins, ions or ligands. Many proteins undergo conformational changes upon these interactions, where regions with large conformational changes are critical to the interactions. This work presents the CCProf platform, which provides conformational changes of entire proteins, named conformational change profile (CCP) in the context. CCProf aims to be a platform where users can study potential causes of novel conformational changes. It provides 10 biological features, including conformational change, potential binding target site, secondary structure, conservation, disorder propensity, hydropathy propensity, sequence domain, structural domain, phosphorylation site and catalytic site. All these information are integrated into a well-aligned view, so that researchers can capture important relevance between different biological features visually. The CCProf contains 986 187 protein structure pairs for 3123 proteins. In addition, CCProf provides a 3D view in which users can see the protein structures before and after conformational changes as well as binding targets that induce conformational changes. All information (e.g. CCP, binding targets and protein structures) shown in CCProf, including intermediate data are available for download to expedite further analyses. Database URL: http://zoro.ee.ncku.edu.tw/ccprof/ PMID:27016699

PolySac3DB: an annotated data base of 3 dimensional structures of polysaccharides.

PubMed

Sarkar, Anita; Pérez, Serge

2012-11-14

Polysaccharides are ubiquitously present in the living world. Their structural versatility makes them important and interesting components in numerous biological and technological processes ranging from structural stabilization to a variety of immunologically important molecular recognition events. The knowledge of polysaccharide three-dimensional (3D) structure is important in studying carbohydrate-mediated host-pathogen interactions, interactions with other bio-macromolecules, drug design and vaccine development as well as material science applications or production of bio-ethanol. PolySac3DB is an annotated database that contains the 3D structural information of 157 polysaccharide entries that have been collected from an extensive screening of scientific literature. They have been systematically organized using standard names in the field of carbohydrate research into 18 categories representing polysaccharide families. Structure-related information includes the saccharides making up the repeat unit(s) and their glycosidic linkages, the expanded 3D representation of the repeat unit, unit cell dimensions and space group, helix type, diffraction diagram(s) (when applicable), experimental and/or simulation methods used for structure description, link to the abstract of the publication, reference and the atomic coordinate files for visualization and download. The database is accompanied by a user-friendly graphical user interface (GUI). It features interactive displays of polysaccharide structures and customized search options for beginners and experts, respectively. The site also serves as an information portal for polysaccharide structure determination techniques. The web-interface also references external links where other carbohydrate-related resources are available. PolySac3DB is established to maintain information on the detailed 3D structures of polysaccharides. All the data and features are available via the web-interface utilizing the search engine and can be accessed at http://polysac3db.cermav.cnrs.fr.

A distance constrained synaptic plasticity model of C. elegans neuronal network

NASA Astrophysics Data System (ADS)

Badhwar, Rahul; Bagler, Ganesh

2017-03-01

Brain research has been driven by enquiry for principles of brain structure organization and its control mechanisms. The neuronal wiring map of C. elegans, the only complete connectome available till date, presents an incredible opportunity to learn basic governing principles that drive structure and function of its neuronal architecture. Despite its apparently simple nervous system, C. elegans is known to possess complex functions. The nervous system forms an important underlying framework which specifies phenotypic features associated to sensation, movement, conditioning and memory. In this study, with the help of graph theoretical models, we investigated the C. elegans neuronal network to identify network features that are critical for its control. The 'driver neurons' are associated with important biological functions such as reproduction, signalling processes and anatomical structural development. We created 1D and 2D network models of C. elegans neuronal system to probe the role of features that confer controllability and small world nature. The simple 1D ring model is critically poised for the number of feed forward motifs, neuronal clustering and characteristic path-length in response to synaptic rewiring, indicating optimal rewiring. Using empirically observed distance constraint in the neuronal network as a guiding principle, we created a distance constrained synaptic plasticity model that simultaneously explains small world nature, saturation of feed forward motifs as well as observed number of driver neurons. The distance constrained model suggests optimum long distance synaptic connections as a key feature specifying control of the network.

Quantitative evaluation method of the bubble structure of sponge cake by using morphology image processing

NASA Astrophysics Data System (ADS)

Tatebe, Hironobu; Kato, Kunihito; Yamamoto, Kazuhiko; Katsuta, Yukio; Nonaka, Masahiko

2005-12-01

Now a day, many evaluation methods for the food industry by using image processing are proposed. These methods are becoming new evaluation method besides the sensory test and the solid-state measurement that are using for the quality evaluation. An advantage of the image processing is to be able to evaluate objectively. The goal of our research is structure evaluation of sponge cake by using image processing. In this paper, we propose a feature extraction method of the bobble structure in the sponge cake. Analysis of the bubble structure is one of the important properties to understand characteristics of the cake from the image. In order to take the cake image, first we cut cakes and measured that's surface by using the CIS scanner. Because the depth of field of this type scanner is very shallow, the bubble region of the surface has low gray scale values, and it has a feature that is blur. We extracted bubble regions from the surface images based on these features. First, input image is binarized, and the feature of bubble is extracted by the morphology analysis. In order to evaluate the result of feature extraction, we compared correlation with "Size of the bubble" of the sensory test result. From a result, the bubble extraction by using morphology analysis gives good correlation. It is shown that our method is as well as the subjectivity evaluation.

Genome-Wide Analysis of Transposon and Retroviral Insertions Reveals Preferential Integrations in Regions of DNA Flexibility.

PubMed

Vrljicak, Pavle; Tao, Shijie; Varshney, Gaurav K; Quach, Helen Ngoc Bao; Joshi, Adita; LaFave, Matthew C; Burgess, Shawn M; Sampath, Karuna

2016-04-07

DNA transposons and retroviruses are important transgenic tools for genome engineering. An important consideration affecting the choice of transgenic vector is their insertion site preferences. Previous large-scale analyses of Ds transposon integration sites in plants were done on the basis of reporter gene expression or germ-line transmission, making it difficult to discern vertebrate integration preferences. Here, we compare over 1300 Ds transposon integration sites in zebrafish with Tol2 transposon and retroviral integration sites. Genome-wide analysis shows that Ds integration sites in the presence or absence of marker selection are remarkably similar and distributed throughout the genome. No strict motif was found, but a preference for structural features in the target DNA associated with DNA flexibility (Twist, Tilt, Rise, Roll, Shift, and Slide) was observed. Remarkably, this feature is also found in transposon and retroviral integrations in maize and mouse cells. Our findings show that structural features influence the integration of heterologous DNA in genomes, and have implications for targeted genome engineering. Copyright © 2016 Vrljicak et al.

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

PubMed Central

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

2016-01-01

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

Local topography shapes fine-scale spatial genetic structure in the Arkansas Valley evening primrose, Oenothera harringtonii (Onagraceae).

PubMed

Rhodes, Matthew K; Fant, Jeremie B; Skogen, Krissa A

2014-01-01

Identifying factors that shape the spatial distribution of genetic variation is crucial to understanding many population- and landscape-level processes. In this study, we explore fine-scale spatial genetic structure in Oenothera harringtonii (Onagraceae), an insect-pollinated, gravity-dispersed herb endemic to the grasslands of south-central and southeastern Colorado, USA. We genotyped 315 individuals with 11 microsatellite markers and utilized a combination of spatial autocorrelation analyses and landscape genetic models to relate life history traits and landscape features to dispersal processes. Spatial genetic structure was consistent with theoretical expectations of isolation by distance, but this pattern was weak (Sp = 0.00374). Anisotropic analyses indicated that spatial genetic structure was markedly directional, in this case consistent with increased dispersal along prominent slopes. Landscape genetic models subsequently confirmed that spatial genetic variation was significantly influenced by local topographic heterogeneity, specifically that geographic distance, elevation and aspect were important predictors of spatial genetic structure. Among these variables, geographic distance was ~68% more important than elevation in describing spatial genetic variation, and elevation was ~42% more important than aspect after removing the effect of geographic distance. From these results, we infer a mechanism of hydrochorous seed dispersal along major drainages aided by seasonal monsoon rains. Our findings suggest that landscape features may shape microevolutionary processes at much finer spatial scales than typically considered, and stress the importance of considering how particular dispersal vectors are influenced by their environmental context. © The American Genetic Association 2014. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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.

Protein functional features are reflected in the patterns of mRNA translation speed.

PubMed

López, Daniel; Pazos, Florencio

2015-07-09

The degeneracy of the genetic code makes it possible for the same amino acid string to be coded by different messenger RNA (mRNA) sequences. These "synonymous mRNAs" may differ largely in a number of aspects related to their overall translational efficiency, such as secondary structure content and availability of the encoded transfer RNAs (tRNAs). Consequently, they may render different yields of the translated polypeptides. These mRNA features related to translation efficiency are also playing a role locally, resulting in a non-uniform translation speed along the mRNA, which has been previously related to some protein structural features and also used to explain some dramatic effects of "silent" single-nucleotide-polymorphisms (SNPs). In this work we perform the first large scale analysis of the relationship between three experimental proxies of mRNA local translation efficiency and the local features of the corresponding encoded proteins. We found that a number of protein functional and structural features are reflected in the patterns of ribosome occupancy, secondary structure and tRNA availability along the mRNA. One or more of these proxies of translation speed have distinctive patterns around the mRNA regions coding for certain protein local features. In some cases the three patterns follow a similar trend. We also show specific examples where these patterns of translation speed point to the protein's important structural and functional features. This support the idea that the genome not only codes the protein functional features as sequences of amino acids, but also as subtle patterns of mRNA properties which, probably through local effects on the translation speed, have some consequence on the final polypeptide. These results open the possibility of predicting a protein's functional regions based on a single genomic sequence, and have implications for heterologous protein expression and fine-tuning protein function.

Mysticism and schizophrenia: A phenomenological exploration of the structure of consciousness in the schizophrenia spectrum disorders.

PubMed

Parnas, Josef; Henriksen, Mads Gram

2016-07-01

Mysticism and schizophrenia are different categories of human existence and experience. Nonetheless, they exhibit important phenomenological affinities, which, however, remain largely unaddressed. In this study, we explore structural analogies between key features of mysticism and major clinical-phenomenological aspects of the schizophrenia spectrum disorders-i.e. attitudes, the nature of experience, and the 'other', mystical or psychotic reality. Not only do these features gravitate around the issue of the basic dimensions of consciousness, they crucially seem to implicate and presuppose a specific alteration of the very structure of consciousness. This finding has bearings for the understanding of consciousness and its psychopathological distortions. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Best practices for quality management of stormwater pipe construction : [summary].

DOT National Transportation Integrated Search

2014-02-01

Although largely unseen, stormwater pipe : systems are integral and important features : of the transportation network. Stormwater : systems support the safety and integrity of : roadways by directing stormwater away from : roadway structures to disc...

Integrated Optical Design Analysis (IODA): New Test Data and Modeling Features

NASA Technical Reports Server (NTRS)

Moore, Jim; Troy, Ed; Patrick, Brian

2003-01-01

A general overview of the capabilities of the IODA ("Integrated Optical Design Analysis") exchange of data and modeling results between thermal, structures, optical design, and testing engineering disciplines. This presentation focuses on new features added to the software that allow measured test data to be imported into the IODA environment for post processing or comparisons with pretest model predictions. software is presented. IODA promotes efficient

PrAS: Prediction of amidation sites using multiple feature extraction.

PubMed

Wang, Tong; Zheng, Wei; Wuyun, Qiqige; Wu, Zhenfeng; Ruan, Jishou; Hu, Gang; Gao, Jianzhao

2017-02-01

Amidation plays an important role in a variety of pathological processes and serious diseases like neural dysfunction and hypertension. However, identification of protein amidation sites through traditional experimental methods is time consuming and expensive. In this paper, we proposed a novel predictor for Prediction of Amidation Sites (PrAS), which is the first software package for academic users. The method incorporated four representative feature types, which are position-based features, physicochemical and biochemical properties features, predicted structure-based features and evolutionary information features. A novel feature selection method, positive contribution feature selection was proposed to optimize features. PrAS achieved AUC of 0.96, accuracy of 92.1%, sensitivity of 81.2%, specificity of 94.9% and MCC of 0.76 on the independent test set. PrAS is freely available at https://sourceforge.net/p/praspkg. Copyright © 2016 Elsevier Ltd. All rights reserved.

The post-rigor structure of myosin VI and implications for the recovery stroke

PubMed Central

Ménétrey, Julie; Llinas, Paola; Cicolari, Jérome; Squires, Gaëlle; Liu, Xiaoyan; Li, Anna; Sweeney, H Lee; Houdusse, Anne

2008-01-01

Myosin VI has an unexpectedly large swing of its lever arm (powerstroke) that optimizes its unique reverse direction movement. The basis for this is an unprecedented rearrangement of the subdomain to which the lever arm is attached, referred to as the converter. It is unclear at what point(s) in the myosin VI ATPase cycle rearrangements in the converter occur, and how this would effect lever arm position. We solved the structure of myosin VI with an ATP analogue (ADP.BeF3) bound in its nucleotide-binding pocket. The structure reveals that no rearrangement in the converter occur upon ATP binding. Based on previously solved myosin structures, our structure suggests that no reversal of the powerstroke occurs during detachment of myosin VI from actin. The structure also reveals novel features of the myosin VI motor that may be important in maintaining the converter conformation during detachment from actin, and other features that may promote rapid rearrangements in the structure following actin detachment that enable hydrolysis of ATP. PMID:18046460

Prospects and limitations of full-text index structures in genome analysis

PubMed Central

Vyverman, Michaël; De Baets, Bernard; Fack, Veerle; Dawyndt, Peter

2012-01-01

The combination of incessant advances in sequencing technology producing large amounts of data and innovative bioinformatics approaches, designed to cope with this data flood, has led to new interesting results in the life sciences. Given the magnitude of sequence data to be processed, many bioinformatics tools rely on efficient solutions to a variety of complex string problems. These solutions include fast heuristic algorithms and advanced data structures, generally referred to as index structures. Although the importance of index structures is generally known to the bioinformatics community, the design and potency of these data structures, as well as their properties and limitations, are less understood. Moreover, the last decade has seen a boom in the number of variant index structures featuring complex and diverse memory-time trade-offs. This article brings a comprehensive state-of-the-art overview of the most popular index structures and their recently developed variants. Their features, interrelationships, the trade-offs they impose, but also their practical limitations, are explained and compared. PMID:22584621

Real-time skin feature identification in a time-sequential video stream

NASA Astrophysics Data System (ADS)

Kramberger, Iztok

2005-04-01

Skin color can be an important feature when tracking skin-colored objects. Particularly this is the case for computer-vision-based human-computer interfaces (HCI). Humans have a highly developed feeling of space and, therefore, it is reasonable to support this within intelligent HCI, where the importance of augmented reality can be foreseen. Joining human-like interaction techniques within multimodal HCI could, or will, gain a feature for modern mobile telecommunication devices. On the other hand, real-time processing plays an important role in achieving more natural and physically intuitive ways of human-machine interaction. The main scope of this work is the development of a stereoscopic computer-vision hardware-accelerated framework for real-time skin feature identification in the sense of a single-pass image segmentation process. The hardware-accelerated preprocessing stage is presented with the purpose of color and spatial filtering, where the skin color model within the hue-saturation-value (HSV) color space is given with a polyhedron of threshold values representing the basis of the filter model. An adaptive filter management unit is suggested to achieve better segmentation results. This enables the adoption of filter parameters to the current scene conditions in an adaptive way. Implementation of the suggested hardware structure is given at the level of filed programmable system level integrated circuit (FPSLIC) devices using an embedded microcontroller as their main feature. A stereoscopic clue is achieved using a time-sequential video stream, but this shows no difference for real-time processing requirements in terms of hardware complexity. The experimental results for the hardware-accelerated preprocessing stage are given by efficiency estimation of the presented hardware structure using a simple motion-detection algorithm based on a binary function.

Representing nested semantic information in a linear string of text using XML.

PubMed

Krauthammer, Michael; Johnson, Stephen B; Hripcsak, George; Campbell, David A; Friedman, Carol

2002-01-01

XML has been widely adopted as an important data interchange language. The structure of XML enables sharing of data elements with variable degrees of nesting as long as the elements are grouped in a strict tree-like fashion. This requirement potentially restricts the usefulness of XML for marking up written text, which often includes features that do not properly nest within other features. We encountered this problem while marking up medical text with structured semantic information from a Natural Language Processor. Traditional approaches to this problem separate the structured information from the actual text mark up. This paper introduces an alternative solution, which tightly integrates the semantic structure with the text. The resulting XML markup preserves the linearity of the medical texts and can therefore be easily expanded with additional types of information.

Representing nested semantic information in a linear string of text using XML.

PubMed Central

Krauthammer, Michael; Johnson, Stephen B.; Hripcsak, George; Campbell, David A.; Friedman, Carol

2002-01-01

XML has been widely adopted as an important data interchange language. The structure of XML enables sharing of data elements with variable degrees of nesting as long as the elements are grouped in a strict tree-like fashion. This requirement potentially restricts the usefulness of XML for marking up written text, which often includes features that do not properly nest within other features. We encountered this problem while marking up medical text with structured semantic information from a Natural Language Processor. Traditional approaches to this problem separate the structured information from the actual text mark up. This paper introduces an alternative solution, which tightly integrates the semantic structure with the text. The resulting XML markup preserves the linearity of the medical texts and can therefore be easily expanded with additional types of information. PMID:12463856

Implicit Learning of Recursive Context-Free Grammars

PubMed Central

Rohrmeier, Martin; Fu, Qiufang; Dienes, Zoltan

2012-01-01

Context-free grammars are fundamental for the description of linguistic syntax. However, most artificial grammar learning experiments have explored learning of simpler finite-state grammars, while studies exploring context-free grammars have not assessed awareness and implicitness. This paper explores the implicit learning of context-free grammars employing features of hierarchical organization, recursive embedding and long-distance dependencies. The grammars also featured the distinction between left- and right-branching structures, as well as between centre- and tail-embedding, both distinctions found in natural languages. People acquired unconscious knowledge of relations between grammatical classes even for dependencies over long distances, in ways that went beyond learning simpler relations (e.g. n-grams) between individual words. The structural distinctions drawn from linguistics also proved important as performance was greater for tail-embedding than centre-embedding structures. The results suggest the plausibility of implicit learning of complex context-free structures, which model some features of natural languages. They support the relevance of artificial grammar learning for probing mechanisms of language learning and challenge existing theories and computational models of implicit learning. PMID:23094021

Determining the Energetics of the Hydrogen Bond through FTIR: A Hands-On Physical Chemistry Lab Experiment

ERIC Educational Resources Information Center

Guerin, Abby C.; Riley, Kristi; Rupnik, Kresimir; Kuroda, Daniel G.

2016-01-01

Hydrogen bonds are very important chemical structures that are responsible for many unique and important properties of solvents, such as the solvation power of water. These distinctive features are directly related to the stabilization energy conferred by hydrogen bonds to the solvent. Thus, the characterization of hydrogen bond energetics has…

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

PubMed

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

2016-06-07

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

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

PubMed

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

2011-01-01

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

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

Polymer separations by liquid interaction chromatography: principles - prospects - limitations.

PubMed

Radke, Wolfgang

2014-03-28

Most heterogeneities of polymers with respect to different structural features cannot be resolved by only size exclusion chromatography (SEC), the most frequently applied mode of polymer chromatography. Instead, methods of interaction chromatography became increasingly important. However, despite the increasing applications the principles and potential of polymer interaction chromatography are still often unknown to a large number of polymer scientists. The present review will explain the principles of the different modes of polymer chromatography. Based on selected examples it will be shown which separation techniques can be successfully applied for separations with respect to the different structural features of polymers. Copyright © 2013 Elsevier B.V. All rights reserved.

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 of 98Ru in the IBA-2 interacting boson model

NASA Astrophysics Data System (ADS)

Giannatiempo, A.

2017-10-01

The 98Ru structure has been investigated in the framework of the IBA-2 model, extending previous works to exploit the whole set of new spectroscopic data. The occurrence of states of mixed symmetry character in the proton and neutron degrees of freedom is of prominent importance in enlightening the structure of this nucleus, which displays features close to those of the Uπ ,ν(5) limit of the model.

Chinese lexical networks: The structure, function and formation

NASA Astrophysics Data System (ADS)

Li, Jianyu; Zhou, Jie; Luo, Xiaoyue; Yang, Zhanxin

2012-11-01

In this paper Chinese phrases are modeled using complex networks theory. We analyze statistical properties of the networks and find that phrase networks display some important features: not only small world and the power-law distribution, but also hierarchical structure and disassortative mixing. These statistical traits display the global organization of Chinese phrases. The origin and formation of such traits are analyzed from a macroscopic Chinese culture and philosophy perspective. It is interesting to find that Chinese culture and philosophy may shape the formation and structure of Chinese phrases. To uncover the structural design principles of networks, network motif patterns are studied. It is shown that they serve as basic building blocks to form the whole phrase networks, especially triad 38 (feed forward loop) plays a more important role in forming most of the phrases and other motifs. The distinct structure may not only keep the networks stable and robust, but also be helpful for information processing. The results of the paper can give some insight into Chinese language learning and language acquisition. It strengthens the idea that learning the phrases helps to understand Chinese culture. On the other side, understanding Chinese culture and philosophy does help to learn Chinese phrases. The hub nodes in the networks show the close relationship with Chinese culture and philosophy. Learning or teaching the hub characters, hub-linking phrases and phrases which are meaning related based on motif feature should be very useful and important for Chinese learning and acquisition.

Characterizing spatial structure of sediment E. coli populations to inform sampling design.

PubMed

Piorkowski, Gregory S; Jamieson, Rob C; Hansen, Lisbeth Truelstrup; Bezanson, Greg S; Yost, Chris K

2014-01-01

Escherichia coli can persist in streambed sediments and influence water quality monitoring programs through their resuspension into overlying waters. This study examined the spatial patterns in E. coli concentration and population structure within streambed morphological features during baseflow and following stormflow to inform sampling strategies for representative characterization of E. coli populations within a stream reach. E. coli concentrations in bed sediments were significantly different (p = 0.002) among monitoring sites during baseflow, and significant interactive effects (p = 0.002) occurred among monitoring sites and morphological features following stormflow. Least absolute shrinkage and selection operator (LASSO) regression revealed that water velocity and effective particle size (D 10) explained E. coli concentration during baseflow, whereas sediment organic carbon, water velocity and median particle diameter (D 50) were important explanatory variables following stormflow. Principle Coordinate Analysis illustrated the site-scale differences in sediment E. coli populations between disconnected stream segments. Also, E. coli populations were similar among depositional features within a reach, but differed in relation to high velocity features (e.g., riffles). Canonical correspondence analysis resolved that E. coli population structure was primarily explained by spatial (26.9–31.7 %) over environmental variables (9.2–13.1 %). Spatial autocorrelation existed among monitoring sites and morphological features for both sampling events, and gradients in mean particle diameter and water velocity influenced E. coli population structure for the baseflow and stormflow sampling events, respectively. Representative characterization of streambed E. coli requires sampling of depositional and high velocity environments to accommodate strain selectivity among these features owing to sediment and water velocity heterogeneity.

Crystal structure and electronic properties of a thiolate-protected Au24 nanocluster

NASA Astrophysics Data System (ADS)

Das, Anindita; Li, Tao; Li, Gao; Nobusada, Katsuyuki; Zeng, Chenjie; Rosi, Nathaniel L.; Jin, Rongchao

2014-05-01

Solving the total structures of gold nanoclusters is of critical importance for understanding their electronic, optical and catalytic properties. Herein, we report the X-ray structure of a charge-neutral Au24(SCH2Ph-tBu)20 nanocluster. This structure features a bi-tetrahedral Au8 kernel protected by four tetrameric staple-like motifs. Electronic structure analysis is further carried out and the optical absorption spectrum is interpreted. The Au24(SCH2Ph-tBu)20, Au23(S-c-C6H11)16 and Au25(SCH2CH2Ph)18 nanoclusters constitute the first crystallographically characterized ``trio''.Solving the total structures of gold nanoclusters is of critical importance for understanding their electronic, optical and catalytic properties. Herein, we report the X-ray structure of a charge-neutral Au24(SCH2Ph-tBu)20 nanocluster. This structure features a bi-tetrahedral Au8 kernel protected by four tetrameric staple-like motifs. Electronic structure analysis is further carried out and the optical absorption spectrum is interpreted. The Au24(SCH2Ph-tBu)20, Au23(S-c-C6H11)16 and Au25(SCH2CH2Ph)18 nanoclusters constitute the first crystallographically characterized ``trio''. Electronic supplementary information (ESI) available: Experimental and supporting Fig. S1-S3. CCDC NUMBER(1000102). For ESI and crystallographic data in CIF or other electronic format see DOI: 10.1039/c4nr01350f

A general prediction model for the detection of ADHD and Autism using structural and functional MRI.

PubMed

Sen, Bhaskar; Borle, Neil C; Greiner, Russell; Brown, Matthew R G

2018-01-01

This work presents a novel method for learning a model that can diagnose Attention Deficit Hyperactivity Disorder (ADHD), as well as Autism, using structural texture and functional connectivity features obtained from 3-dimensional structural magnetic resonance imaging (MRI) and 4-dimensional resting-state functional magnetic resonance imaging (fMRI) scans of subjects. We explore a series of three learners: (1) The LeFMS learner first extracts features from the structural MRI images using the texture-based filters produced by a sparse autoencoder. These filters are then convolved with the original MRI image using an unsupervised convolutional network. The resulting features are used as input to a linear support vector machine (SVM) classifier. (2) The LeFMF learner produces a diagnostic model by first computing spatial non-stationary independent components of the fMRI scans, which it uses to decompose each subject's fMRI scan into the time courses of these common spatial components. These features can then be used with a learner by themselves or in combination with other features to produce the model. Regardless of which approach is used, the final set of features are input to a linear support vector machine (SVM) classifier. (3) Finally, the overall LeFMSF learner uses the combined features obtained from the two feature extraction processes in (1) and (2) above as input to an SVM classifier, achieving an accuracy of 0.673 on the ADHD-200 holdout data and 0.643 on the ABIDE holdout data. Both of these results, obtained with the same LeFMSF framework, are the best known, over all hold-out accuracies on these datasets when only using imaging data-exceeding previously-published results by 0.012 for ADHD and 0.042 for Autism. Our results show that combining multi-modal features can yield good classification accuracy for diagnosis of ADHD and Autism, which is an important step towards computer-aided diagnosis of these psychiatric diseases and perhaps others as well.

Designing attractive gamification features for collaborative storytelling websites.

PubMed

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

2013-06-01

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

Predictive brain networks for major depression in a semi-multimodal fusion hierarchical feature reduction framework.

PubMed

Yang, Jie; Yin, Yingying; Zhang, Zuping; Long, Jun; Dong, Jian; Zhang, Yuqun; Xu, Zhi; Li, Lei; Liu, Jie; Yuan, Yonggui

2018-02-05

Major depressive disorder (MDD) is characterized by dysregulation of distributed structural and functional networks. It is now recognized that structural and functional networks are related at multiple temporal scales. The recent emergence of multimodal fusion methods has made it possible to comprehensively and systematically investigate brain networks and thereby provide essential information for influencing disease diagnosis and prognosis. However, such investigations are hampered by the inconsistent dimensionality features between structural and functional networks. Thus, a semi-multimodal fusion hierarchical feature reduction framework is proposed. Feature reduction is a vital procedure in classification that can be used to eliminate irrelevant and redundant information and thereby improve the accuracy of disease diagnosis. Our proposed framework primarily consists of two steps. The first step considers the connection distances in both structural and functional networks between MDD and healthy control (HC) groups. By adding a constraint based on sparsity regularization, the second step fully utilizes the inter-relationship between the two modalities. However, in contrast to conventional multi-modality multi-task methods, the structural networks were considered to play only a subsidiary role in feature reduction and were not included in the following classification. The proposed method achieved a classification accuracy, specificity, sensitivity, and area under the curve of 84.91%, 88.6%, 81.29%, and 0.91, respectively. Moreover, the frontal-limbic system contributed the most to disease diagnosis. Importantly, by taking full advantage of the complementary information from multimodal neuroimaging data, the selected consensus connections may be highly reliable biomarkers of MDD. Copyright © 2017 Elsevier B.V. All rights reserved.

Ecological forestry in an uneven-aged, late-successional forest: Simulated effects of contrasting treatments on structure and yield

Treesearch

Jacob J. Hanson; Craig G. Lorimer; Corey R. Halpin; Brian J. Palik

2012-01-01

Ecological forestry practices are designed to retain species and structural features important for maintaining ecosystem function but which may be deficient in conventionally managed stands. We used the spatially-explicit, individual tree model CANOPY to assess tradeoffs in enhanced ecological attributes vs. reductions in timber yield for a wide variety of treatments...

The effects of thinning intensity on snag and cavity tree abundance in an Appalachian hardwood stand

Treesearch

Aaron T. Graves; Mary Ann Fajvan; Gary W. Miller

2000-01-01

Traditional silvicultural practices focus on manipulating forest vegetation structure for commodity production. Structural features important to wildlife, such as snags, trees with decay, and cavity trees are also affected by forest management, but these effects are often not quantified. This study measured the effects of different thinning intensities (45, 60, and 75...

Atomic insights into nanoparticle formation of hydroxyfluorinated anatase featuring titanium vacancies

DOE PAGES

Li, Wei; Body, Monique; Legein, Christophe; ...

2016-06-28

Anatase TiO 2 with exposed highly reactive (001) surface is commonly prepared using solution-based synthesis in the presence of a fluorinating agent acting as a structure directing agent. Here, the solvothermal reaction of titanium tetraisopropoxide in the presence of aqueous HF has resulted in the stabilization of an oxyhydroxyfluorinated anatase phase featuring cationic vacancies. In the present work, we have studied its formation mechanism, revealing a solid-state transformation of a highly defective anatase phase having a hydroxyfluoride composition that subsequently evolves through an oxolation reaction into an oxyhydroxyfluoride phase. Importantly, this work confirms that titanium alkoxide precursors can react withmore » HF via a fluorolysis process yielding fluorinated molecular precursors, which further condense to produce new composition and structural features deviating from a well ordered anatase network.« less

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

PubMed

Schulkind, M D

1999-09-01

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

Structural Determination of Functional Domains in Early B-cell Factor (EBF) Family of Transcription Factors Reveals Similarities to Rel DNA-binding Proteins and a Novel Dimerization Motif*

PubMed Central

Siponen, Marina I.; Wisniewska, Magdalena; Lehtiö, Lari; Johansson, Ida; Svensson, Linda; Raszewski, Grzegorz; Nilsson, Lennart; Sigvardsson, Mikael; Berglund, Helena

2010-01-01

The early B-cell factor (EBF) transcription factors are central regulators of development in several organs and tissues. This protein family shows low sequence similarity to other protein families, which is why structural information for the functional domains of these proteins is crucial to understand their biochemical features. We have used a modular approach to determine the crystal structures of the structured domains in the EBF family. The DNA binding domain reveals a striking resemblance to the DNA binding domains of the Rel homology superfamily of transcription factors but contains a unique zinc binding structure, termed zinc knuckle. Further the EBF proteins contain an IPT/TIG domain and an atypical helix-loop-helix domain with a novel type of dimerization motif. The data presented here provide insights into unique structural features of the EBF proteins and open possibilities for detailed molecular investigations of this important transcription factor family. PMID:20592035

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.

DNAproDB: an interactive tool for structural analysis of DNA–protein complexes

PubMed Central

Sagendorf, Jared M.

2017-01-01

Abstract Many biological processes are mediated by complex interactions between DNA and proteins. Transcription factors, various polymerases, nucleases and histones recognize and bind DNA with different levels of binding specificity. To understand the physical mechanisms that allow proteins to recognize DNA and achieve their biological functions, it is important to analyze structures of DNA–protein complexes in detail. DNAproDB is a web-based interactive tool designed to help researchers study these complexes. DNAproDB provides an automated structure-processing pipeline that extracts structural features from DNA–protein complexes. The extracted features are organized in structured data files, which are easily parsed with any programming language or viewed in a browser. We processed a large number of DNA–protein complexes retrieved from the Protein Data Bank and created the DNAproDB database to store this data. Users can search the database by combining features of the DNA, protein or DNA–protein interactions at the interface. Additionally, users can upload their own structures for processing privately and securely. DNAproDB provides several interactive and customizable tools for creating visualizations of the DNA–protein interface at different levels of abstraction that can be exported as high quality figures. All functionality is documented and freely accessible at http://dnaprodb.usc.edu. PMID:28431131

[The study of M dwarf spectral classification].

PubMed

Yi, Zhen-Ping; Pan, Jing-Chang; Luo, A-Li

2013-08-01

As the most common stars in the galaxy, M dwarfs can be used to trace the structure and evolution of the Milky Way. Besides, investigating M dwarfs is important for searching for habitability of extrasolar planets orbiting M dwarfs. Spectral classification of M dwarfs is a fundamental work. The authors used DR7 M dwarf sample of SLOAN to extract important features from the range of 600-900 nm by random forest method. Compared to the features used in Hammer Code, the authors added three new indices. Our test showed that the improved Hammer with new indices is more accurate. Our method has been applied to classify M dwarf spectra of LAMOST.

A data driven approach for condition monitoring of wind turbine blade using vibration signals through best-first tree algorithm and functional trees algorithm: A comparative study.

PubMed

Joshuva, A; Sugumaran, V

2017-03-01

Wind energy is one of the important renewable energy resources available in nature. It is one of the major resources for production of energy because of its dependability due to the development of the technology and relatively low cost. Wind energy is converted into electrical energy using rotating blades. Due to environmental conditions and large structure, the blades are subjected to various vibration forces that may cause damage to the blades. This leads to a liability in energy production and turbine shutdown. The downtime can be reduced when the blades are diagnosed continuously using structural health condition monitoring. These are considered as a pattern recognition problem which consists of three phases namely, feature extraction, feature selection, and feature classification. In this study, statistical features were extracted from vibration signals, feature selection was carried out using a J48 decision tree algorithm and feature classification was performed using best-first tree algorithm and functional trees algorithm. The better algorithm is suggested for fault diagnosis of wind turbine blade. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Venusian arachnoids revisited

NASA Astrophysics Data System (ADS)

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

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

Crustal structure of the southeastern Brazilian margin, Campos Basin, from aeromagnetic data: New kinematic constraints

NASA Astrophysics Data System (ADS)

Stanton, N.; Schmitt, R.; Galdeano, A.; Maia, M.; Mane, M.

2010-07-01

The continental and adjacent marginal features along southeast Brazil were investigated, focusing on the basement structural relationships between onshore and offshore provinces. Lateral and vertical variations in the magnetic anomalies provided a good correlation with the regional tectonic features. The sin-rift dykes and faults are associated with the magnetic lineaments and lie sub parallel to the Precambrian N45E-S45W basement structure of the Ribeira Belt, but orthogonally to the Cabo Frio Tectonic Domain (CFTD) basement, implying that: (1) the upper portion of the continental crust was widely affected by Mesozoic extensional deformation; and (2) tectonic features related to the process of break up of the Gondwana at the CFTD were form regardless of the preexisting structural basement orientation being controlled by the stress orientation during the rift phase. The deep crustal structure (5 km depth) is characterized by NE-SW magnetic "provinces" related to the Ribeira Belt tectonic units, while deep suture zones are defined by magnetic lows. The offshore Campos structural framework is N30E-S30W oriented and resulted from a main WNW-ESE direction of extension in Early Cretaceous. Transfer zones are represented by NW-SE and E-W oriented discontinuities. A slight difference in orientation between onshore (N45E) and offshore (N30E) structural systems seems to reflect a re-orientation of stress during rifting. We proposed a kinematical model to explain the structural evolution of this portion of the margin, characterized by polyphase rifting, associated with the rotation of the South American plate. The Campos Magnetic High (CMH), an important tectonic feature of the Campos Basin corresponds to a wide area of high crustal magnetization. The CMH wass interpreted as a magmatic feature, mafic to ultramafic in composition that extends down to 14 km depth and constitutes an evidence of intense crustal extension at 60 km from the coast.

Peroxisome protein import: a complex journey.

PubMed

Baker, Alison; Lanyon-Hogg, Thomas; Warriner, Stuart L

2016-06-15

The import of proteins into peroxisomes possesses many unusual features such as the ability to import folded proteins, and a surprising diversity of targeting signals with differing affinities that can be recognized by the same receptor. As understanding of the structure and function of many components of the protein import machinery has grown, an increasingly complex network of factors affecting each step of the import pathway has emerged. Structural studies have revealed the presence of additional interactions between cargo proteins and the PEX5 receptor that affect import potential, with a subtle network of cargo-induced conformational changes in PEX5 being involved in the import process. Biochemical studies have also indicated an interdependence of receptor-cargo import with release of unloaded receptor from the peroxisome. Here, we provide an update on recent literature concerning mechanisms of protein import into peroxisomes. © 2016 The Author(s).

Theoretical and experimental analysis of the structural pattern responsible for the iridescence of Morpho butterflies.

PubMed

Siddique, Radwanul Hasan; Diewald, Silvia; Leuthold, Juerg; Hölscher, Hendrik

2013-06-17

Morpho butterflies are well-known for their iridescence originating from nanostructures in the scales of their wings. These optical active structures integrate three design principles leading to the wide angle reflection: alternating lamellae layers, "Christmas tree" like shape, and offsets between neighboring ridges. We study their individual effects rigorously by 2D FEM simulations of the nanostructures of the Morpho sulkowskyi butterfly and show how the reflection spectrum can be controlled by the design of the nanostructures. The width of the spectrum is broad (≈ 90 nm) for alternating lamellae layers (or "brunches") of the structure while the "Christmas tree" pattern together with a height offset between neighboring ridges reduces the directionality of the reflectance. Furthermore, we fabricated the simulated structures by e-beam lithography. The resulting samples mimicked all important optical features of the original Morpho butterfly scales and feature the intense blue iridescence with a wide angular range of reflection.

Self-assembled ultrathin nanotubes on diamond (100) surface

NASA Astrophysics Data System (ADS)

Lu, Shaohua; Wang, Yanchao; Liu, Hanyu; Miao, Mao-Sheng; Ma, Yanming

2014-04-01

Surfaces of semiconductors are crucially important for electronics, especially when the devices are reduced to the nanoscale. However, surface structures are often elusive, impeding greatly the engineering of devices. Here we develop an efficient method that can automatically explore the surface structures using structure swarm intelligence. Its application to a simple diamond (100) surface reveals an unexpected surface reconstruction featuring self-assembled carbon nanotubes arrays. Such a surface is energetically competitive with the known dimer structure under normal conditions, but it becomes more favourable under a small compressive strain or at high temperatures. The intriguing covalent bonding between neighbouring tubes creates a unique feature of carrier kinetics (that is, one dimensionality of hole states, while two dimensionality of electron states) that could lead to novel design of superior electronics. Our findings highlight that the surface plays vital roles in the fabrication of nanodevices by being a functional part of them.

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

PubMed

Wang, Dong; Wang, Haifeng; Hu, P

2015-01-21

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

Emergence of structural patterns out of synchronization in networks with competitive interactions

NASA Astrophysics Data System (ADS)

Assenza, Salvatore; Gutiérrez, Ricardo; Gómez-Gardeñes, Jesús; Latora, Vito; Boccaletti, Stefano

2011-09-01

Synchronization is a collective phenomenon occurring in systems of interacting units, and is ubiquitous in nature, society and technology. Recent studies have enlightened the important role played by the interaction topology on the emergence of synchronized states. However, most of these studies neglect that real world systems change their interaction patterns in time. Here, we analyze synchronization features in networks in which structural and dynamical features co-evolve. The feedback of the node dynamics on the interaction pattern is ruled by the competition of two mechanisms: homophily (reinforcing those interactions with other correlated units in the graph) and homeostasis (preserving the value of the input strength received by each unit). The competition between these two adaptive principles leads to the emergence of key structural properties observed in real world networks, such as modular and scale-free structures, together with a striking enhancement of local synchronization in systems with no global order.

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

NASA Astrophysics Data System (ADS)

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

2000-04-01

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

What is a 'good' job? Modelling job quality for blue collar workers.

PubMed

Jones, Wendy; Haslam, Roger; Haslam, Cheryl

2017-01-01

This paper proposes a model of job quality, developed from interviews with blue collar workers: bus drivers, manufacturing operatives and cleaners (n  =  80). The model distinguishes between core features, important for almost all workers, and 'job fit' features, important to some but not others, or where individuals might have different preferences. Core job features found important for almost all interviewees included job security, personal safety and having enough pay to meet their needs. 'Job fit' features included autonomy and the opportunity to form close relationships. These showed more variation between participants; priorities were influenced by family commitments, stage of life and personal preference. The resulting theoretical perspective indicates the features necessary for a job to be considered 'good' by the person doing it, whilst not adversely affecting their health. The model should have utility as a basis for measuring and improving job quality and the laudable goal of creating 'good jobs'. Practitioner Summary: Good work can contribute positively to health and well-being, but there is a lack of agreement regarding the concept of a 'good' job. A model of job quality has been constructed based on semi-structured worker interviews (n  =  80). The model emphasises the need to take into account variation between individuals in their preferred work characteristics.

Secondary structure of the 3'-noncoding region of flavivirus genomes: comparative analysis of base pairing probabilities.

PubMed

Rauscher, S; Flamm, C; Mandl, C W; Heinz, F X; Stadler, P F

1997-07-01

The prediction of the complete matrix of base pairing probabilities was applied to the 3' noncoding region (NCR) of flavivirus genomes. This approach identifies not only well-defined secondary structure elements, but also regions of high structural flexibility. Flaviviruses, many of which are important human pathogens, have a common genomic organization, but exhibit a significant degree of RNA sequence diversity in the functionally important 3'-NCR. We demonstrate the presence of secondary structures shared by all flaviviruses, as well as structural features that are characteristic for groups of viruses within the genus reflecting the established classification scheme. The significance of most of the predicted structures is corroborated by compensatory mutations. The availability of infectious clones for several flaviviruses will allow the assessment of these structural elements in processes of the viral life cycle, such as replication and assembly.

Physical habitat structure of the lake shoreline and littoral zone -- How important is it?

EPA Science Inventory

The recent National Lakes Assessment (NLA) included the first national assessment of littoral and lakeshore physical habitat. It quantified water depth, surface characteristics, bank morphology, lake level fluctuations, substrate, fish concealment features, aquatic macrophytes, l...

Mapping landscape corridors

Treesearch

Peter Vogt; Kurt H. Riitters; Marcin Iwanowski; Christine Estreguil; Jacek Kozak; Pierre Soille

2007-01-01

Corridors are important geographic features for biological conservation and biodiversity assessment. The identification and mapping of corridors is usually based on visual interpretations of movement patterns (functional corridors) or habitat maps (structural corridors). We present a method for automated corridor mapping with morphological image processing, and...

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.

CAD scheme for detection of hemorrhages and exudates in ocular fundus images

NASA Astrophysics Data System (ADS)

Hatanaka, Yuji; Nakagawa, Toshiaki; Hayashi, Yoshinori; Mizukusa, Yutaka; Fujita, Akihiro; Kakogawa, Masakatsu; Kawase, Kazuhide; Hara, Takeshi; Fujita, Hiroshi

2007-03-01

This paper describes a method for detecting hemorrhages and exudates in ocular fundus images. The detection of hemorrhages and exudates is important in order to diagnose diabetic retinopathy. Diabetic retinopathy is one of the most significant factors contributing to blindness, and early detection and treatment are important. In this study, hemorrhages and exudates were automatically detected in fundus images without using fluorescein angiograms. Subsequently, the blood vessel regions incorrectly detected as hemorrhages were eliminated by first examining the structure of the blood vessels and then evaluating the length-to-width ratio. Finally, the false positives were eliminated by checking the following features extracted from candidate images: the number of pixels, contrast, 13 features calculated from the co-occurrence matrix, two features based on gray-level difference statistics, and two features calculated from the extrema method. The sensitivity of detecting hemorrhages in the fundus images was 85% and that of detecting exudates was 77%. Our fully automated scheme could accurately detect hemorrhages and exudates.

How the structural architecture of the Eurasian continental margin affects the structure, seismicity, and topography of the south central Taiwan fold-and-thrust belt

NASA Astrophysics Data System (ADS)

Brown, Dennis; Alvarez-Marron, Joaquina; Biete, Cristina; Kuo-Chen, Hao; Camanni, Giovanni; Ho, Chun-Wei

2017-07-01

Studies of mountain belts worldwide show that along-strike changes are common in their foreland fold-and-thrust belts. These are typically caused by processes related to fault reactivation and/or fault focusing along changes in sedimentary sequences. The study of active orogens, like Taiwan, can also provide insights into how these processes influence transient features such as seismicity and topography. In this paper, we trace regional-scale features from the Eurasian continental margin in the Taiwan Strait into the south central Taiwan fold-and-thrust belt. We then present newly mapped surface geology, P wave velocity maps and sections, seismicity, and topography data to test the hypothesis of whether or not these regional-scale features of the margin are contributing to along-strike changes in structural style, and the distribution of seismicity and topography in this part of the Taiwan fold-and-thrust belt. These data show that the most important along-strike change takes place at the eastward prolongation of the upper part of the margin necking zone, where there is a causal link between fault reactivation, involvement of basement in the thrusting, concentration of seismicity, and the formation of high topography. On the area correlated with the necking zone, the strike-slip reactivation of east northeast striking extensional faults is causing sigmoidal offset of structures and topography along two main zones. Here basement is not involved in the thrusting; there is weak focusing of seismicity and localized development of topography. We also show that there are important differences in structure, seismicity, and topography between the margin shelf and its necking zone.

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

PubMed

Hsing, Michael; Cherkasov, Artem

2008-06-25

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

Structure and engineering of celluloses.

PubMed

Pérez, Serge; Samain, Daniel

2010-01-01

This chapter collates the developments and conclusions of many of the extensive studies that have been conducted on cellulose, with particular emphasis on the structural and morphological features while not ignoring the most recent results derived from the elucidation of unique biosynthetic pathways. The presentation of structural and morphological data gathered together in this chapter follows the historical development of our knowledge of the different structural levels of cellulose and its various organizational levels. These levels concern features such as chain conformation, chain polarity, chain association, crystal polarity, and microfibril structure and organization. This chapter provides some historical landmarks related to the evolution of concepts in the field of biopolymer science, which parallel the developments of novel methods for characterization of complex macromolecular structures. The elucidation of the different structural levels of organization opens the way to relating structure to function and properties. The chemical and biochemical methods that have been developed to dissolve and further modify cellulose chains are briefly covered. Particular emphasis is given to the facets of topochemistry and topoenzymology where the morphological features play a key role in determining unique physicochemical properties. A final chapter addresses what might be considered tomorrow's goal in amplifying the economic importance of cellulose in the context of sustainable development. Selected examples illustrate the types of result that can be obtained when cellulose fibers are no longer viewed as inert substrates, and when the polyhydroxyl nature of their surfaces, as well as their entire structural complexity, are taken into account. Copyright © 2010 Elsevier Inc. All rights reserved.

Design and Synthesis of Mannich bases as Benzimidazole Derivatives as Analgesic Agents.

PubMed

Datar, Prasanna A; Limaye, Saleel A

2015-01-01

Mannich bases were selected for 2D QSAR study to derive meaningful relationship between the structural features and analgesic activity. Using the knowledge of important features a novel series was designed to obtain improved analgesic activity. A series of novel Mannich bases 1-(N-substituted amino)methyl]-2-substituted benzimidazole derivatives were synthesized and were screened for analgesic activity. Some of these compounds showed promising analgesic activity when compared with the standard drug diclofenac sodium.

The connectivity structure, giant strong component and centrality of metabolic networks.

PubMed

Ma, Hong-Wu; Zeng, An-Ping

2003-07-22

Structural and functional analysis of genome-based large-scale metabolic networks is important for understanding the design principles and regulation of the metabolism at a system level. The metabolic network is conventionally considered to be highly integrated and very complex. A rational reduction of the metabolic network to its core structure and a deeper understanding of its functional modules are important. In this work, we show that the metabolites in a metabolic network are far from fully connected. A connectivity structure consisting of four major subsets of metabolites and reactions, i.e. a fully connected sub-network, a substrate subset, a product subset and an isolated subset is found to exist in metabolic networks of 65 fully sequenced organisms. The largest fully connected part of a metabolic network, called 'the giant strong component (GSC)', represents the most complicated part and the core of the network and has the feature of scale-free networks. The average path length of the whole network is primarily determined by that of the GSC. For most of the organisms, GSC normally contains less than one-third of the nodes of the network. This connectivity structure is very similar to the 'bow-tie' structure of World Wide Web. Our results indicate that the bow-tie structure may be common for large-scale directed networks. More importantly, the uncovered structure feature makes a structural and functional analysis of large-scale metabolic network more amenable. As shown in this work, comparing the closeness centrality of the nodes in the GSC can identify the most central metabolites of a metabolic network. To quantitatively characterize the overall connection structure of the GSC we introduced the term 'overall closeness centralization index (OCCI)'. OCCI correlates well with the average path length of the GSC and is a useful parameter for a system-level comparison of metabolic networks of different organisms. http://genome.gbf.de/bioinformatics/

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.

Enhancement of the Feature Extraction Capability in Global Damage Detection Using Wavelet Theory

NASA Technical Reports Server (NTRS)

Saleeb, Atef F.; Ponnaluru, Gopi Krishna

2006-01-01

The main objective of this study is to assess the specific capabilities of the defect energy parameter technique for global damage detection developed by Saleeb and coworkers. The feature extraction is the most important capability in any damage-detection technique. Features are any parameters extracted from the processed measurement data in order to enhance damage detection. The damage feature extraction capability was studied extensively by analyzing various simulation results. The practical significance in structural health monitoring is that the detection at early stages of small-size defects is always desirable. The amount of changes in the structure's response due to these small defects was determined to show the needed level of accuracy in the experimental methods. The arrangement of fine/extensive sensor network to measure required data for the detection is an "unlimited" ability, but there is a difficulty to place extensive number of sensors on a structure. Therefore, an investigation was conducted using the measurements of coarse sensor network. The white and the pink noises, which cover most of the frequency ranges that are typically encountered in the many measuring devices used (e.g., accelerometers, strain gauges, etc.) are added to the displacements to investigate the effect of noisy measurements in the detection technique. The noisy displacements and the noisy damage parameter values are used to study the signal feature reconstruction using wavelets. The enhancement of the feature extraction capability was successfully achieved by the wavelet theory.

Associations Between Sibling Relationship Quality and Friendship Quality in Early Adolescence: Looking at the Case of Twins.

PubMed

Bekkhus, Mona; Brendgen, Mara; Czajkowski, Nikolai O; Vitaro, Frank; Dionne, Ginette; Boivin, Michel

2016-04-01

Bidirectional pathways between twin relationship quality and friendship quality were investigated in a large longitudinal twin cohort. We examined negative and positive relationship features in 313 monozygotic (MZ) twins and 238 same-sex dizygotic (DZ) twins from ages 13 to 14 years, using latent structural modeling. Results showed stronger stability of the twin relationship quality compared to friendship quality. Positive features in the sibling relationship were associated with increased positive features in the relationship with the best friend a year later. In contrast, no significant association between negative sibling relationship features and change in negative friendship quality features was found. These findings speak to the important role of the sibling relationship in the development of good quality friendship relations in twins.

Bacterial chemoreceptors: high-performance signaling in networked arrays.

PubMed

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

2008-01-01

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

Bacterial chemoreceptors: high-performance signaling in networked arrays

PubMed Central

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

2010-01-01

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

Contribution of low-temperature single-molecule techniques to structural issues of pigment–protein complexes from photosynthetic purple bacteria

PubMed Central

Löhner, Alexander; Cogdell, Richard

2018-01-01

As the electronic energies of the chromophores in a pigment–protein complex are imposed by the geometrical structure of the protein, this allows the spectral information obtained to be compared with predictions derived from structural models. Thereby, the single-molecule approach is particularly suited for the elucidation of specific, distinctive spectral features that are key for a particular model structure, and that would not be observable in ensemble-averaged spectra due to the heterogeneity of the biological objects. In this concise review, we illustrate with the example of the light-harvesting complexes from photosynthetic purple bacteria how results from low-temperature single-molecule spectroscopy can be used to discriminate between different structural models. Thereby the low-temperature approach provides two advantages: (i) owing to the negligible photobleaching, very long observation times become possible, and more importantly, (ii) at cryogenic temperatures, vibrational degrees of freedom are frozen out, leading to sharper spectral features and in turn to better resolved spectra. PMID:29321265

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.

Structural insights of ZIP4 extracellular domain critical for optimal zinc transport

NASA Astrophysics Data System (ADS)

Zhang, Tuo; Sui, Dexin; Hu, Jian

2016-06-01

The ZIP zinc transporter family is responsible for zinc uptake from the extracellular milieu or intracellular vesicles. The LIV-1 subfamily, containing nine out of the 14 human ZIP proteins, is featured with a large extracellular domain (ECD). The critical role of the ECD is manifested by disease-causing mutations on ZIP4, a representative LIV-1 protein. Here we report the first crystal structure of a mammalian ZIP4-ECD, which reveals two structurally independent subdomains and an unprecedented dimer centred at the signature PAL motif. Structure-guided mutagenesis, cell-based zinc uptake assays and mapping of the disease-causing mutations indicate that the two subdomains play pivotal but distinct roles and that the bridging region connecting them is particularly important for ZIP4 function. These findings lead to working hypotheses on how ZIP4-ECD exerts critical functions in zinc transport. The conserved dimeric architecture in ZIP4-ECD is also demonstrated to be a common structural feature among the LIV-1 proteins.

Spectroscopy and atomic force microscopy of biomass.

PubMed

Tetard, L; Passian, A; Farahi, R H; Kalluri, U C; Davison, B H; Thundat, T

2010-05-01

Scanning probe microscopy has emerged as a powerful approach to a broader understanding of the molecular architecture of cell walls, which may shed light on the challenge of efficient cellulosic ethanol production. We have obtained preliminary images of both Populus and switchgrass samples using atomic force microscopy (AFM). The results show distinctive features that are shared by switchgrass and Populus. These features may be attributable to the lignocellulosic cell wall composition, as the collected images exhibit the characteristic macromolecular globule structures attributable to the lignocellulosic systems. Using both AFM and a single case of mode synthesizing atomic force microscopy (MSAFM) to characterize Populus, we obtained images that clearly show the cell wall structure. The results are of importance in providing a better understanding of the characteristic features of both mature cells as well as developing plant cells. In addition, we present spectroscopic investigation of the same samples.

Automatic Detection of Blue-White Veil and Related Structures in Dermoscopy Images

PubMed Central

Celebi, M. Emre; Iyatomi, Hitoshi; Stoecker, William V.; Moss, Randy H.; Rabinovitz, Harold S.; Argenziano, Giuseppe; Soyer, H. Peter

2011-01-01

Dermoscopy is a non-invasive skin imaging technique, which permits visualization of features of pigmented melanocytic neoplasms that are not discernable by examination with the naked eye. One of the most important features for the diagnosis of melanoma in dermoscopy images is the blue-white veil (irregular, structureless areas of confluent blue pigmentation with an overlying white “ground-glass” film). In this article, we present a machine learning approach to the detection of blue-white veil and related structures in dermoscopy images. The method involves contextual pixel classification using a decision tree classifier. The percentage of blue-white areas detected in a lesion combined with a simple shape descriptor yielded a sensitivity of 69.35% and a specificity of 89.97% on a set of 545 dermoscopy images. The sensitivity rises to 78.20% for detection of blue veil in those cases where it is a primary feature for melanoma recognition. PMID:18804955

Ensemble pharmacophore meets ensemble docking: a novel screening strategy for the identification of RIPK1 inhibitors

NASA Astrophysics Data System (ADS)

Fayaz, S. M.; Rajanikant, G. K.

2014-07-01

Programmed cell death has been a fascinating area of research since it throws new challenges and questions in spite of the tremendous ongoing research in this field. Recently, necroptosis, a programmed form of necrotic cell death, has been implicated in many diseases including neurological disorders. Receptor interacting serine/threonine protein kinase 1 (RIPK1) is an important regulatory protein involved in the necroptosis and inhibition of this protein is essential to stop necroptotic process and eventually cell death. Current structure-based virtual screening methods involve a wide range of strategies and recently, considering the multiple protein structures for pharmacophore extraction has been emphasized as a way to improve the outcome. However, using the pharmacophoric information completely during docking is very important. Further, in such methods, using the appropriate protein structures for docking is desirable. If not, potential compound hits, obtained through pharmacophore-based screening, may not have correct ranks and scores after docking. Therefore, a comprehensive integration of different ensemble methods is essential, which may provide better virtual screening results. In this study, dual ensemble screening, a novel computational strategy was used to identify diverse and potent inhibitors against RIPK1. All the pharmacophore features present in the binding site were captured using both the apo and holo protein structures and an ensemble pharmacophore was built by combining these features. This ensemble pharmacophore was employed in pharmacophore-based screening of ZINC database. The compound hits, thus obtained, were subjected to ensemble docking. The leads acquired through docking were further validated through feature evaluation and molecular dynamics simulation.

Development of multiple source data processing for structural analysis at a regional scale. [digital remote sensing in geology

NASA Technical Reports Server (NTRS)

Carrere, Veronique

1990-01-01

Various image processing techniques developed for enhancement and extraction of linear features, of interest to the structural geologist, from digital remote sensing, geologic, and gravity data, are presented. These techniques include: (1) automatic detection of linear features and construction of rose diagrams from Landsat MSS data; (2) enhancement of principal structural directions using selective filters on Landsat MSS, Spacelab panchromatic, and HCMM NIR data; (3) directional filtering of Spacelab panchromatic data using Fast Fourier Transform; (4) detection of linear/elongated zones of high thermal gradient from thermal infrared data; and (5) extraction of strong gravimetric gradients from digitized Bouguer anomaly maps. Processing results can be compared to each other through the use of a geocoded database to evaluate the structural importance of each lineament according to its depth: superficial structures in the sedimentary cover, or deeper ones affecting the basement. These image processing techniques were successfully applied to achieve a better understanding of the transition between Provence and the Pyrenees structural blocks, in southeastern France, for an improved structural interpretation of the Mediterranean region.

Atomic structures of fibrillar segments of hIAPP suggest tightly mated β-sheets are important for cytotoxicity

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

Krotee, Pascal; Rodriguez, Jose A.; Sawaya, Michael R.

2017-01-03

hIAPP fibrils are associated with Type-II Diabetes, but the link of hIAPP structure to islet cell death remains elusive. Here we observe that hIAPP fibrils are cytotoxic to cultured pancreatic β-cells, leading us to determine the structure and cytotoxicity of protein segments composing the amyloid spine of hIAPP. Using the cryoEM method MicroED, we discover that one segment, 19–29 S20G, forms pairs of β-sheets mated by a dry interface that share structural features with and are similarly cytotoxic to full-length hIAPP fibrils. In contrast, a second segment, 15–25 WT, forms non-toxic labile β-sheets. These segments possess different structures and cytotoxicmore » effects, however, both can seed full-length hIAPP, and cause hIAPP to take on the cytotoxic and structural features of that segment. These results suggest that protein segment structures represent polymorphs of their parent protein and that segment 19–29 S20G may serve as a model for the toxic spine of hIAPP.« less

Very high resolution Earth observation features for monitoring plant and animal community structure across multiple spatial scales in protected areas

NASA Astrophysics Data System (ADS)

Mairota, Paola; Cafarelli, Barbara; Labadessa, Rocco; Lovergine, Francesco; Tarantino, Cristina; Lucas, Richard M.; Nagendra, Harini; Didham, Raphael K.

2015-05-01

Monitoring the status and future trends in biodiversity can be prohibitively expensive using ground-based surveys. Consequently, significant effort is being invested in the use of satellite remote sensing to represent aspects of the proximate mechanisms (e.g., resource availability) that can be related to biodiversity surrogates (BS) such as species community descriptors. We explored the potential of very high resolution (VHR) satellite Earth observation (EO) features as proxies for habitat structural attributes that influence spatial variation in habitat quality and biodiversity change. In a semi-natural grassland mosaic of conservation concern in southern Italy, we employed a hierarchical nested sampling strategy to collect field and VHR-EO data across three spatial extent levels (landscape, patch and plot). Species incidence and abundance data were collected at the plot level for plant, insect and bird functional groups. Spectral and textural VHR-EO image features were derived from a Worldview-2 image. Three window sizes (grains) were tested for analysis and computation of textural features, guided by the perception limits of different organisms. The modelled relationships between VHR-EO features and BS responses differed across scales, suggesting that landscape, patch and plot levels are respectively most appropriate when dealing with birds, plants and insects. This research demonstrates the potential of VHR-EO for biodiversity mapping and habitat modelling, and highlights the importance of identifying the appropriate scale of analysis for specific taxonomic groups of interest. Further, textural features are important in the modelling of functional group-specific indices which represent BS in high conservation value habitat types, and provide a more direct link to species interaction networks and ecosystem functioning, than provided by traditional taxonomic diversity indices.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-07-01

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

Giant geode (subchondrial cyst) in calcium pyrophosphate deposition disease on the curist.

PubMed

Weinberg, S; Scott, R A

1981-09-01

It is important to be aware of the radiographic features of pyrophosphate arthropathy with or without associated chondrocalcinosis. Accordingly, when appropriate structural joint changes are present an extraordinarily large subchondral cyst should not prompt a misdiagnosis of cystic tumor.

Designing an Earthquake-Resistant Building

ERIC Educational Resources Information Center

English, Lyn D.; King, Donna T.

2016-01-01

How do cross-bracing, geometry, and base isolation help buildings withstand earthquakes? These important structural design features involve fundamental geometry that elementary school students can readily model and understand. The problem activity, Designing an Earthquake-Resistant Building, was undertaken by several classes of sixth- grade…

Visualization of molecular structures using HoloLens-based augmented reality

PubMed Central

Hoffman, MA; Provance, JB

2017-01-01

Biological molecules and biologically active small molecules are complex three dimensional structures. Current flat screen monitors are limited in their ability to convey the full three dimensional characteristics of these molecules. Augmented reality devices, including the Microsoft HoloLens, offer an immersive platform to change how we interact with molecular visualizations. We describe a process to incorporate the three dimensional structures of small molecules and complex proteins into the Microsoft HoloLens using aspirin and the human leukocyte antigen (HLA) as examples. Small molecular structures can be introduced into the HoloStudio application, which provides native support for rotating, resizing and performing other interactions with these molecules. Larger molecules can be imported through the Unity gaming development platform and then Microsoft Visual Developer. The processes described here can be modified to import a wide variety of molecular structures into augmented reality systems and improve our comprehension of complex structural features. PMID:28815109

Hierarchical Structure of Articular Bone-Cartilage Interface and Its Potential Application for Osteochondral Tissue Engineering

NASA Astrophysics Data System (ADS)

Bian, Weiguo; Qin, Lian; Li, Dichen; Wang, Jin; Jin, Zhongmin

2010-09-01

The artificial biodegradable osteochondral construct is one of mostly promising lifetime substitute in the joint replacement. And the complex hierarchical structure of natural joint is important in developing the osteochondral construct. However, the architecture features of the interface between cartilage and bone, in particular those at the micro-and nano-structural level, remain poorly understood. This paper investigates these structural data of the cartilage-bone interface by micro computerized tomography (μCT) and Scanning Electron Microscope (SEM). The result of μCT shows that important bone parameters and the density of articular cartilage are all related to the position in the hierarchical structure. The conjunctions of bone and cartilage were defined by SEM. All of the study results would be useful for the design of osteochondral construct further manufactured by nano-tech. A three-dimensional model with gradient porous structure is constructed in the environment of Pro/ENGINEERING software.

Complementary aspects of diffusion imaging and fMRI; I: structure and function.

PubMed

Mulkern, Robert V; Davis, Peter E; Haker, Steven J; Estepar, Raul San Jose; Panych, Lawrence P; Maier, Stephan E; Rivkin, Michael J

2006-05-01

Studying the intersection of brain structure and function is an important aspect of modern neuroscience. The development of magnetic resonance imaging (MRI) over the last 25 years has provided new and powerful tools for the study of brain structure and function. Two tools in particular, diffusion imaging and functional MRI (fMRI), are playing increasingly important roles in elucidating the complementary aspects of brain structure and function. In this work, we review basic technical features of diffusion imaging and fMRI for studying the integrity of white matter structural components and for determining the location and extent of cortical activation in gray matter, respectively. We then review a growing body of literature in which the complementary aspects of diffusion imaging and fMRI, applied as separate examinations but analyzed in tandem, have been exploited to enhance our knowledge of brain structure and function.

An in-silico method for identifying aggregation rate enhancer and mitigator mutations in proteins.

PubMed

Rawat, Puneet; Kumar, Sandeep; Michael Gromiha, M

2018-06-24

Newly synthesized polypeptides must pass stringent quality controls in cells to ensure appropriate folding and function. However, mutations, environmental stresses and aging can reduce efficiencies of these controls, leading to accumulation of protein aggregates, amyloid fibrils and plaques. In-vitro experiments have shown that even single amino acid substitutions can drastically enhance or mitigate protein aggregation kinetics. In this work, we have collected a dataset of 220 unique mutations in 25 proteins and classified them as enhancers or mitigators on the basis of their effect on protein aggregation rate. The data were analyzed via machine learning to identify features capable of distinguishing between aggregation rate enhancers and mitigators. Our initial Support Vector Machine (SVM) model separated such mutations with an overall accuracy of 69%. When local secondary structures at the mutation sites were considered, the accuracies further improved by 13-15%. The machine-learnt features are distinct for each secondary structure class at mutation sites. Protein stability and flexibility changes are important features for mutations in α-helices. β-strand propensity, polarity and charge become important when mutations occur in β-strands and ability to form secondary structure, helical tendency and aggregation propensity are important for mutations lying in coils. These results have been incorporated into a sequence-based algorithm (available at http://www.iitm.ac.in/bioinfo/aggrerate-disc/) capable of predicting whether a mutation will enhance or mitigate a protein's aggregation rate. This algorithm will find several applications towards understanding protein aggregation in human diseases, enable in-silico optimization of biopharmaceuticals and enzymes for improved biophysical attributes and de novo design of bio-nanomaterials. Copyright © 2018. Published by Elsevier B.V.

Exploration of the relationship between topology and designability of conformations

NASA Astrophysics Data System (ADS)

Leelananda, Sumudu P.; Towfic, Fadi; Jernigan, Robert L.; Kloczkowski, Andrzej

2011-06-01

Protein structures are evolutionarily more conserved than sequences, and sequences with very low sequence identity frequently share the same fold. This leads to the concept of protein designability. Some folds are more designable and lots of sequences can assume that fold. Elucidating the relationship between protein sequence and the three-dimensional (3D) structure that the sequence folds into is an important problem in computational structural biology. Lattice models have been utilized in numerous studies to model protein folds and predict the designability of certain folds. In this study, all possible compact conformations within a set of two-dimensional and 3D lattice spaces are explored. Complementary interaction graphs are then generated for each conformation and are described using a set of graph features. The full HP sequence space for each lattice model is generated and contact energies are calculated by threading each sequence onto all the possible conformations. Unique conformation giving minimum energy is identified for each sequence and the number of sequences folding to each conformation (designability) is obtained. Machine learning algorithms are used to predict the designability of each conformation. We find that the highly designable structures can be distinguished from other non-designable conformations based on certain graphical geometric features of the interactions. This finding confirms the fact that the topology of a conformation is an important determinant of the extent of its designability and suggests that the interactions themselves are important for determining the designability.

QSAR and 3D QSAR of inhibitors of the epidermal growth factor receptor

NASA Astrophysics Data System (ADS)

Pinto-Bazurco, Mariano; Tsakovska, Ivanka; Pajeva, Ilza

This article reports quantitative structure-activity relationships (QSAR) and 3D QSAR models of 134 structurally diverse inhibitors of the epidermal growth factor receptor (EGFR) tyrosine kinase. Free-Wilson analysis was used to derive the QSAR model. It identified the substituents in aniline, the polycyclic system, and the substituents at the 6- and 7-positions of the polycyclic system as the most important structural features. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used in the 3D QSAR modeling. The steric and electrostatic interactions proved the most important for the inhibitory effect. Both QSAR and 3D QSAR models led to consistent results. On the basis of the statistically significant models, new structures were proposed and their inhibitory activities were predicted.

Effects of moiré lattice structure on electronic properties of graphene

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

Huang, Lunan; Wu, Yun; Hershberger, M. T.

Here, we study structural and electronic properties of graphene grown on silicone carbide (SiC) substrate using a scanning tunneling microscope, spot-profile-analysis low-energy electron diffraction, and angle-resolved photoemission spectroscopy. We find several new replicas of Dirac cones in the Brillouin zone. Their locations can be understood in terms of a combination of basis vectors linked to SiC 6 × 6 and graphene 6√3×6√3 reconstruction. Therefore, these new features originate from the moiré caused by the lattice mismatch between SiC and graphene. More specifically, Dirac cone replicas are caused by underlying weak modulation of the ionic potential by the substrate that ismore » then experienced by the electrons in the graphene. We also demonstrate that this effect is equally strong in single- and trilayer graphene; therefore, the additional Dirac cones are intrinsic features rather than the result of photoelectron diffraction. These new features in the electronic structure are very important for the interpretation of recent transport measurements and can assist in tuning the properties of graphene for practical applications.« less

Effects of moiré lattice structure on electronic properties of graphene

NASA Astrophysics Data System (ADS)

Huang, Lunan; Wu, Yun; Hershberger, M. T.; Mou, Daixiang; Schrunk, Benjamin; Tringides, Michael C.; Hupalo, Myron; Kaminski, Adam

2017-07-01

We study structural and electronic properties of graphene grown on silicone carbide (SiC) substrate using a scanning tunneling microscope, spot-profile-analysis low-energy electron diffraction, and angle-resolved photoemission spectroscopy. We find several new replicas of Dirac cones in the Brillouin zone. Their locations can be understood in terms of a combination of basis vectors linked to SiC 6 × 6 and graphene 6 √{3 }×6 √{3 } reconstruction. Therefore, these new features originate from the moiré caused by the lattice mismatch between SiC and graphene. More specifically, Dirac cone replicas are caused by underlying weak modulation of the ionic potential by the substrate that is then experienced by the electrons in the graphene. We also demonstrate that this effect is equally strong in single- and trilayer graphene; therefore, the additional Dirac cones are intrinsic features rather than the result of photoelectron diffraction. These new features in the electronic structure are very important for the interpretation of recent transport measurements and can assist in tuning the properties of graphene for practical applications.

Effects of moiré lattice structure on electronic properties of graphene

DOE PAGES

Huang, Lunan; Wu, Yun; Hershberger, M. T.; ...

2017-07-10

Here, we study structural and electronic properties of graphene grown on silicone carbide (SiC) substrate using a scanning tunneling microscope, spot-profile-analysis low-energy electron diffraction, and angle-resolved photoemission spectroscopy. We find several new replicas of Dirac cones in the Brillouin zone. Their locations can be understood in terms of a combination of basis vectors linked to SiC 6 × 6 and graphene 6√3×6√3 reconstruction. Therefore, these new features originate from the moiré caused by the lattice mismatch between SiC and graphene. More specifically, Dirac cone replicas are caused by underlying weak modulation of the ionic potential by the substrate that ismore » then experienced by the electrons in the graphene. We also demonstrate that this effect is equally strong in single- and trilayer graphene; therefore, the additional Dirac cones are intrinsic features rather than the result of photoelectron diffraction. These new features in the electronic structure are very important for the interpretation of recent transport measurements and can assist in tuning the properties of graphene for practical applications.« less

Self-organization in precipitation reactions far from the equilibrium

PubMed Central

Nakouzi, Elias; Steinbock, Oliver

2016-01-01

Far from the thermodynamic equilibrium, many precipitation reactions create complex product structures with fascinating features caused by their unusual origins. Unlike the dissipative patterns in other self-organizing reactions, these features can be permanent, suggesting potential applications in materials science and engineering. We review four distinct classes of precipitation reactions, describe similarities and differences, and discuss related challenges for theoretical studies. These classes are hollow micro- and macrotubes in chemical gardens, polycrystalline silica carbonate aggregates (biomorphs), Liesegang bands, and propagating precipitation-dissolution fronts. In many cases, these systems show intricate structural hierarchies that span from the nanometer scale into the macroscopic world. We summarize recent experimental progress that often involves growth under tightly regulated conditions by means of wet stamping, holographic heating, and controlled electric, magnetic, or pH perturbations. In this research field, progress requires mechanistic insights that cannot be derived from experiments alone. We discuss how mesoscopic aspects of the product structures can be modeled by reaction-transport equations and suggest important targets for future studies that should also include materials features at the nanoscale. PMID:27551688

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

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

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

2012-07-01

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

PredPPCrys: accurate prediction of sequence cloning, protein production, purification and crystallization propensity from protein sequences using multi-step heterogeneous feature fusion and selection.

PubMed

Wang, Huilin; Wang, Mingjun; Tan, Hao; Li, Yuan; Zhang, Ziding; Song, Jiangning

2014-01-01

X-ray crystallography is the primary approach to solve the three-dimensional structure of a protein. However, a major bottleneck of this method is the failure of multi-step experimental procedures to yield diffraction-quality crystals, including sequence cloning, protein material production, purification, crystallization and ultimately, structural determination. Accordingly, prediction of the propensity of a protein to successfully undergo these experimental procedures based on the protein sequence may help narrow down laborious experimental efforts and facilitate target selection. A number of bioinformatics methods based on protein sequence information have been developed for this purpose. However, our knowledge on the important determinants of propensity for a protein sequence to produce high diffraction-quality crystals remains largely incomplete. In practice, most of the existing methods display poorer performance when evaluated on larger and updated datasets. To address this problem, we constructed an up-to-date dataset as the benchmark, and subsequently developed a new approach termed 'PredPPCrys' using the support vector machine (SVM). Using a comprehensive set of multifaceted sequence-derived features in combination with a novel multi-step feature selection strategy, we identified and characterized the relative importance and contribution of each feature type to the prediction performance of five individual experimental steps required for successful crystallization. The resulting optimal candidate features were used as inputs to build the first-level SVM predictor (PredPPCrys I). Next, prediction outputs of PredPPCrys I were used as the input to build second-level SVM classifiers (PredPPCrys II), which led to significantly enhanced prediction performance. Benchmarking experiments indicated that our PredPPCrys method outperforms most existing procedures on both up-to-date and previous datasets. In addition, the predicted crystallization targets of currently non-crystallizable proteins were provided as compendium data, which are anticipated to facilitate target selection and design for the worldwide structural genomics consortium. PredPPCrys is freely available at http://www.structbioinfor.org/PredPPCrys.

On the structure of Bayesian network for Indonesian text document paraphrase identification

NASA Astrophysics Data System (ADS)

Prayogo, Ario Harry; Syahrul Mubarok, Mohamad; Adiwijaya

2018-03-01

Paraphrase identification is an important process within natural language processing. The idea is to automatically recognize phrases that have different forms but contain same meanings. For examples if we input query “causing fire hazard”, then the computer has to recognize this query that this query has same meaning as “the cause of fire hazard. Paraphrasing is an activity that reveals the meaning of an expression, writing, or speech using different words or forms, especially to achieve greater clarity. In this research we will focus on classifying two Indonesian sentences whether it is a paraphrase to each other or not. There are four steps in this research, first is preprocessing, second is feature extraction, third is classifier building, and the last is performance evaluation. Preprocessing consists of tokenization, non-alphanumerical removal, and stemming. After preprocessing we will conduct feature extraction in order to build new features from given dataset. There are two kinds of features in the research, syntactic features and semantic features. Syntactic features consist of normalized levenshtein distance feature, term-frequency based cosine similarity feature, and LCS (Longest Common Subsequence) feature. Semantic features consist of Wu and Palmer feature and Shortest Path Feature. We use Bayesian Networks as the method of training the classifier. Parameter estimation that we use is called MAP (Maximum A Posteriori). For structure learning of Bayesian Networks DAG (Directed Acyclic Graph), we use BDeu (Bayesian Dirichlet equivalent uniform) scoring function and for finding DAG with the best BDeu score, we use K2 algorithm. In evaluation step we perform cross-validation. The average result that we get from testing the classifier as follows: Precision 75.2%, Recall 76.5%, F1-Measure 75.8% and Accuracy 75.6%.

Biological and functional relevance of CASP predictions

PubMed Central

Liu, Tianyun; Ish‐Shalom, Shirbi; Torng, Wen; Lafita, Aleix; Bock, Christian; Mort, Matthew; Cooper, David N; Bliven, Spencer; Capitani, Guido; Mooney, Sean D.

2017-01-01

Abstract Our goal is to answer the question: compared with experimental structures, how useful are predicted models for functional annotation? We assessed the functional utility of predicted models by comparing the performances of a suite of methods for functional characterization on the predictions and the experimental structures. We identified 28 sites in 25 protein targets to perform functional assessment. These 28 sites included nine sites with known ligand binding (holo‐sites), nine sites that are expected or suggested by experimental authors for small molecule binding (apo‐sites), and Ten sites containing important motifs, loops, or key residues with important disease‐associated mutations. We evaluated the utility of the predictions by comparing their microenvironments to the experimental structures. Overall structural quality correlates with functional utility. However, the best‐ranked predictions (global) may not have the best functional quality (local). Our assessment provides an ability to discriminate between predictions with high structural quality. When assessing ligand‐binding sites, most prediction methods have higher performance on apo‐sites than holo‐sites. Some servers show consistently high performance for certain types of functional sites. Finally, many functional sites are associated with protein‐protein interaction. We also analyzed biologically relevant features from the protein assemblies of two targets where the active site spanned the protein‐protein interface. For the assembly targets, we find that the features in the models are mainly determined by the choice of template. PMID:28975675

Multimedia Classifier

NASA Astrophysics Data System (ADS)

Costache, G. N.; Gavat, I.

2004-09-01

Along with the aggressive growing of the amount of digital data available (text, audio samples, digital photos and digital movies joined all in the multimedia domain) the need for classification, recognition and retrieval of this kind of data became very important. In this paper will be presented a system structure to handle multimedia data based on a recognition perspective. The main processing steps realized for the interesting multimedia objects are: first, the parameterization, by analysis, in order to obtain a description based on features, forming the parameter vector; second, a classification, generally with a hierarchical structure to make the necessary decisions. For audio signals, both speech and music, the derived perceptual features are the melcepstral (MFCC) and the perceptual linear predictive (PLP) coefficients. For images, the derived features are the geometric parameters of the speaker mouth. The hierarchical classifier consists generally in a clustering stage, based on the Kohonnen Self-Organizing Maps (SOM) and a final stage, based on a powerful classification algorithm called Support Vector Machines (SVM). The system, in specific variants, is applied with good results in two tasks: the first, is a bimodal speech recognition which uses features obtained from speech signal fused to features obtained from speaker's image and the second is a music retrieval from large music database.

Foot Structure in Boys with Down Syndrome.

PubMed

Puszczałowska-Lizis, Ewa; Nowak, Krzysztof; Omorczyk, Jarosław; Ambroży, Tadeusz; Bujas, Przemysław; Nosiadek, Leszek

2017-01-01

Down syndrome (DS) is associated with numerous developmental abnormalities, some of which cause dysfunctions of the posture and the locomotor system. The analysis of selected features of the foot structure in boys with DS versus their peers without developmental disorders is done. The podoscopic examination was performed on 30 boys with DS aged 14-15 years. A control group consisted of 30 age- and gender-matched peers without DS. The feet of boys with DS are flatter compared to their healthy peers. The hallux valgus angle is not the most important feature differentiating the shape of the foot in the boys with DS and their healthy peers. In terms of the V toe setting, healthy boys had poorer results. Specialized therapeutic treatment in individuals with DS should involve exercises to increase the muscle strength around the foot joints, enhancing the stabilization in the joints and proprioception. Introducing orthotics and proper footwear is also important. It is also necessary to monitor the state of the foot in order to modify undertaken therapies.

Spectral-Spatial Shared Linear Regression for Hyperspectral Image Classification.

PubMed

Haoliang Yuan; Yuan Yan Tang

2017-04-01

Classification of the pixels in hyperspectral image (HSI) is an important task and has been popularly applied in many practical applications. Its major challenge is the high-dimensional small-sized problem. To deal with this problem, lots of subspace learning (SL) methods are developed to reduce the dimension of the pixels while preserving the important discriminant information. Motivated by ridge linear regression (RLR) framework for SL, we propose a spectral-spatial shared linear regression method (SSSLR) for extracting the feature representation. Comparing with RLR, our proposed SSSLR has the following two advantages. First, we utilize a convex set to explore the spatial structure for computing the linear projection matrix. Second, we utilize a shared structure learning model, which is formed by original data space and a hidden feature space, to learn a more discriminant linear projection matrix for classification. To optimize our proposed method, an efficient iterative algorithm is proposed. Experimental results on two popular HSI data sets, i.e., Indian Pines and Salinas demonstrate that our proposed methods outperform many SL methods.

DSSPcont: continuous secondary structure assignments for proteins

PubMed Central

Carter, Phil; Andersen, Claus A. F.; Rost, Burkhard

2003-01-01

The DSSP program automatically assigns the secondary structure for each residue from the three-dimensional co-ordinates of a protein structure to one of eight states. However, discrete assignments are incomplete in that they cannot capture the continuum of thermal fluctuations. Therefore, DSSPcont (http://cubic.bioc.columbia.edu/services/DSSPcont) introduces a continuous assignment of secondary structure that replaces ‘static’ by ‘dynamic’ states. Technically, the continuum results from calculating weighted averages over 10 discrete DSSP assignments with different hydrogen bond thresholds. A DSSPcont assignment for a particular residue is a percentage likelihood of eight secondary structure states, derived from a weighted average of the ten DSSP assignments. The continuous assignments have two important features: (i) they reflect the structural variations due to thermal fluctuations as detected by NMR spectroscopy; and (ii) they reproduce the structural variation between many NMR models from one single model. Therefore, functionally important variation can be extracted from a single X-ray structure using the continuous assignment procedure. PMID:12824310

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

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.

Analysis of sequencing data for probing RNA secondary structures and protein-RNA binding in studying posttranscriptional regulations.

PubMed

Hu, Xihao; Wu, Yang; Lu, Zhi John; Yip, Kevin Y

2016-11-01

High-throughput sequencing has been used to study posttranscriptional regulations, where the identification of protein-RNA binding is a major and fast-developing sub-area, which is in turn benefited by the sequencing methods for whole-transcriptome probing of RNA secondary structures. In the study of RNA secondary structures using high-throughput sequencing, bases are modified or cleaved according to their structural features, which alter the resulting composition of sequencing reads. In the study of protein-RNA binding, methods have been proposed to immuno-precipitate (IP) protein-bound RNA transcripts in vitro or in vivo By sequencing these transcripts, the protein-RNA interactions and the binding locations can be identified. For both types of data, read counts are affected by a combination of confounding factors, including expression levels of transcripts, sequence biases, mapping errors and the probing or IP efficiency of the experimental protocols. Careful processing of the sequencing data and proper extraction of important features are fundamentally important to a successful analysis. Here we review and compare different experimental methods for probing RNA secondary structures and binding sites of RNA-binding proteins (RBPs), and the computational methods proposed for analyzing the corresponding sequencing data. We suggest how these two types of data should be integrated to study the structural properties of RBP binding sites as a systematic way to better understand posttranscriptional regulations. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Biological and functional relevance of CASP predictions.

PubMed

Liu, Tianyun; Ish-Shalom, Shirbi; Torng, Wen; Lafita, Aleix; Bock, Christian; Mort, Matthew; Cooper, David N; Bliven, Spencer; Capitani, Guido; Mooney, Sean D; Altman, Russ B

2018-03-01

Our goal is to answer the question: compared with experimental structures, how useful are predicted models for functional annotation? We assessed the functional utility of predicted models by comparing the performances of a suite of methods for functional characterization on the predictions and the experimental structures. We identified 28 sites in 25 protein targets to perform functional assessment. These 28 sites included nine sites with known ligand binding (holo-sites), nine sites that are expected or suggested by experimental authors for small molecule binding (apo-sites), and Ten sites containing important motifs, loops, or key residues with important disease-associated mutations. We evaluated the utility of the predictions by comparing their microenvironments to the experimental structures. Overall structural quality correlates with functional utility. However, the best-ranked predictions (global) may not have the best functional quality (local). Our assessment provides an ability to discriminate between predictions with high structural quality. When assessing ligand-binding sites, most prediction methods have higher performance on apo-sites than holo-sites. Some servers show consistently high performance for certain types of functional sites. Finally, many functional sites are associated with protein-protein interaction. We also analyzed biologically relevant features from the protein assemblies of two targets where the active site spanned the protein-protein interface. For the assembly targets, we find that the features in the models are mainly determined by the choice of template. © 2017 The Authors Proteins: Structure, Function and Bioinformatics Published by Wiley Periodicals, Inc.

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

PubMed

Li, Quan; Cao, Zanxia; Liu, Haiyan

2010-03-01

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

Importance of conduction electron correlation in a Kondo lattice, Ce₂CoSi₃.

PubMed

Patil, Swapnil; Pandey, Sudhir K; Medicherla, V R R; Singh, R S; Bindu, R; Sampathkumaran, E V; Maiti, Kalobaran

2010-06-30

Kondo systems are usually described by the interaction of the correlation induced local moments with the highly itinerant conduction electrons. Here, we study the role of electron correlations among conduction electrons in the electronic structure of a Kondo lattice compound, Ce₂CoSi₃, using high resolution photoemission spectroscopy and ab initio band structure calculations, where Co 3d electrons contribute in the conduction band. High energy resolution employed in the measurements helped to reveal the signatures of Ce 4f states derived Kondo resonance features at the Fermi level and the dominance of Co 3d contributions at higher binding energies in the conduction band. The lineshape of the experimental Co 3d band is found to be significantly different from that obtained from the band structure calculations within the local density approximations, LDA. Consideration of electron-electron Coulomb repulsion, U, among Co 3d electrons within the LDA + U method leads to a better representation of experimental results. The signature of an electron correlation induced satellite feature is also observed in the Co 2p core level spectrum. These results clearly demonstrate the importance of the electron correlation among conduction electrons in deriving the microscopic description of such Kondo systems.

Network motif frequency vectors reveal evolving metabolic network organisation.

PubMed

Pearcy, Nicole; Crofts, Jonathan J; Chuzhanova, Nadia

2015-01-01

At the systems level many organisms of interest may be described by their patterns of interaction, and as such, are perhaps best characterised via network or graph models. Metabolic networks, in particular, are fundamental to the proper functioning of many important biological processes, and thus, have been widely studied over the past decade or so. Such investigations have revealed a number of shared topological features, such as a short characteristic path-length, large clustering coefficient and hierarchical modular structure. However, the extent to which evolutionary and functional properties of metabolism manifest via this underlying network architecture remains unclear. In this paper, we employ a novel graph embedding technique, based upon low-order network motifs, to compare metabolic network structure for 383 bacterial species categorised according to a number of biological features. In particular, we introduce a new global significance score which enables us to quantify important evolutionary relationships that exist between organisms and their physical environments. Using this new approach, we demonstrate a number of significant correlations between environmental factors, such as growth conditions and habitat variability, and network motif structure, providing evidence that organism adaptability leads to increased complexities in the resultant metabolic networks.

Structural and lithologic study of northern California Coast Range and Sacramento Valley, California

NASA Technical Reports Server (NTRS)

Rich, E. I. (Principal Investigator); Steele, W. C.

1973-01-01

The author has identified the following significant results. Photgeologic examination of repetitive multispectral ERTS-1 imagery of Northern California has disclosed several systems of linear features which may be important for the interpretation of the structural history of California. They are separated from an orthogonal system of linears in the Klamath Mts. by a set of discontinuous southeast-trending linear features (the Mendocino system) which is traceable from the Pacific Coast, at Cape Mendocino, into the eastern foothills of the Sierra Nevada. Within the Sierra Nevada, the Mendocino system separates the north-trending Sierran system from a set of linears characteristic of the Modoc Plateau. With minor exception, little overlap exists among the systems which suggests a decipherable chronology and evolutionary history for the region. The San Andres system of linears appears to truncate or co-exist with most of the other systems in the northern Coast Ranges. The Mendocino system truncates the Klamath, Sierran, and Modoc systems. The Sierran system may represent fundamental and long-persisting pre-late Paleozoic zones of crustal weakness which have been reactivated from time to time. The Mendocino system was possibly developed in early Mesozoic and is important to the structural framework of Northern California.

TLS from fundamentals to practice

PubMed Central

Urzhumtsev, Alexandre; Afonine, Pavel V.; Adams, Paul D.

2014-01-01

The Translation-Libration-Screw-rotation (TLS) model of rigid-body harmonic displacements introduced in crystallography by Schomaker & Trueblood (1968) is now a routine tool in macromolecular studies and is a feature of most modern crystallographic structure refinement packages. In this review we consider a number of simple examples that illustrate important features of the TLS model. Based on these examples simplified formulae are given for several special cases that may occur in structure modeling and refinement. The derivation of general TLS formulae from basic principles is also provided. This manuscript describes the principles of TLS modeling, as well as some select algorithmic details for practical application. An extensive list of applications references as examples of TLS in macromolecular crystallography refinement is provided. PMID:25249713

Gstruct: a system for extracting schemas from GML documents

NASA Astrophysics Data System (ADS)

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

2008-10-01

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

Geophysical surveys and archaeological insights at Fort Pierre Chouteau, a frontier trading post on the Middle Missouri

NASA Astrophysics Data System (ADS)

Patton, Margaret Maurine

Fort Pierre Chouteau in present day South Dakota was the most important fur trading post of the American Fur Company in the 1830s, serving as a regional hub for the fur trade. The Fort was sold to the U.S. Military in 1855 for use as a base in the Sioux Wars but was abandoned in 1856. Geophysical surveys and previous excavations indicate evidence of both occupations. Geophysics is an important tool for determining the extent of archaeological sites, yet the relationships between geophysical anomalies and excavation features may not be readily evident. Initial geophysical surveys (Kvamme 2007) were completed to determine the extent of the fur trading Fort, and additional surveys in August 2012 used magnetometry and electrical resistance to determine if evidence of military structures exists outside of the Fort. This study examines connections between excavation features and geophysical anomalies in order to better interpret anomalies inside the Fort palisade. The palisade builder's trench, adobe pavement, post holes, and unknown structures are characterized through the analysis of the excavations and anomalies. The location of one of the military structures outside of the palisade is also identified. As many sites have histories of excavations prior to any geophysical surveys, combining the two sets of information is important in order to more fully understand site layout and the archaeological causes of geophysical anomalies.

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.

Multi-threshold white matter structural networks fusion for accurate diagnosis of Tourette syndrome children

NASA Astrophysics Data System (ADS)

Wen, Hongwei; Liu, Yue; Wang, Shengpei; Li, Zuoyong; Zhang, Jishui; Peng, Yun; He, Huiguang

2017-03-01

Tourette syndrome (TS) is a childhood-onset neurobehavioral disorder. To date, TS is still misdiagnosed due to its varied presentation and lacking of obvious clinical symptoms. Therefore, studies of objective imaging biomarkers are of great importance for early TS diagnosis. As tic generation has been linked to disturbed structural networks, and many efforts have been made recently to investigate brain functional or structural networks using machine learning methods, for the purpose of disease diagnosis. However, few studies were related to TS and some drawbacks still existed in them. Therefore, we propose a novel classification framework integrating a multi-threshold strategy and a network fusion scheme to address the preexisting drawbacks. Here we used diffusion MRI probabilistic tractography to construct the structural networks of 44 TS children and 48 healthy children. We ameliorated the similarity network fusion algorithm specially to fuse the multi-threshold structural networks. Graph theoretical analysis was then implemented, and nodal degree, nodal efficiency and nodal betweenness centrality were selected as features. Finally, support vector machine recursive feature extraction (SVM-RFE) algorithm was used for feature selection, and then optimal features are fed into SVM to automatically discriminate TS children from controls. We achieved a high accuracy of 89.13% evaluated by a nested cross validation, demonstrated the superior performance of our framework over other comparison methods. The involved discriminative regions for classification primarily located in the basal ganglia and frontal cortico-cortical networks, all highly related to the pathology of TS. Together, our study may provide potential neuroimaging biomarkers for early-stage TS diagnosis.

The Equivalence of Precession Phenomena in Metric Theories of Gravity

NASA Technical Reports Server (NTRS)

Krisher, Timothy P.

1997-01-01

The requirement of general covariance imparts to metric theories of gravity, such as general relavity, important structural features. A precise mathematical form results, ensuring that computation of observable physical effects in the theory gives the same answers independently of the chosen system of coordinates.

Perceptions of Public Relations Education.

ERIC Educational Resources Information Center

Stacks, Don W.; Botan, Carl; Turk, Judy VanSlyke

1999-01-01

Surveys 258 public-relations educators and practitioners, finding they agree that public-relations education is on track; that systematic assessment is an important feature of public-relations education; and that they agreed on how public-relations education should be structured, and demonstrated a high degree of similarity in their preferences…

Hierarchy of low-energy models of the electronic structure of cuprate HTSCs: The role of long-range spin-correlated hops

NASA Astrophysics Data System (ADS)

Val'kov, V. V.; Mitskan, V. A.; Dzebisashvili, D. M.; Barabanov, A. F.

2018-02-01

It is shown that for the three-band Emery p-d-model that reflects the real structure of the CuO2-plane of high-temperature superconductors in the regime of strong electron correlations, it is possible to carry out a sequence of reductions to the effective models reproducing low-energy features of elementary excitation spectrum and revealing the spin-polaron nature of the Fermi quasiparticles. The first reduction leads to the spin-fermion model in which the subsystem of spin moments, coupled by the exchange interaction and localized on copper ions, strongly interacts with oxygen holes. The second reduction deals with the transformation from the spin-fermion model to the φ-d-exchange model. An important feature of this transformation is the large energy of the φ-d-exchange coupling, which leads to the formation of spin polarons. The use of this fact allows us to carry out the third reduction, resulting in the t ˜-J˜ *-I -model. Its distinctive feature is the importance of spin-correlated hops as compared to the role of such processes in the commonly used t-J*-model derived from the Hubbard model. Based on the comparative analysis of the spectrum of Fermi excitations calculated for the obtained effective models of the CuO2-plane of high-temperature superconductors, the important role of the usually ignored long-range spin-correlated hops is determined.

A method of plane geometry primitive presentation

NASA Astrophysics Data System (ADS)

Jiao, Anbo; Luo, Haibo; Chang, Zheng; Hui, Bin

2014-11-01

Point feature and line feature are basic elements in object feature sets, and they play an important role in object matching and recognition. On one hand, point feature is sensitive to noise; on the other hand, there are usually a huge number of point features in an image, which makes it complex for matching. Line feature includes straight line segment and curve. One difficulty in straight line segment matching is the uncertainty of endpoint location, the other is straight line segment fracture problem or short straight line segments joined to form long straight line segment. While for the curve, in addition to the above problems, there is another difficulty in how to quantitatively describe the shape difference between curves. Due to the problems of point feature and line feature, the robustness and accuracy of target description will be affected; in this case, a method of plane geometry primitive presentation is proposed to describe the significant structure of an object. Firstly, two types of primitives are constructed, they are intersecting line primitive and blob primitive. Secondly, a line segment detector (LSD) is applied to detect line segment, and then intersecting line primitive is extracted. Finally, robustness and accuracy of the plane geometry primitive presentation method is studied. This method has a good ability to obtain structural information of the object, even if there is rotation or scale change of the object in the image. Experimental results verify the robustness and accuracy of this method.

'I love my work, but ... ': the 'best' and the 'worst' in nurse educators' working life in Finland.

PubMed

Harri, M

1996-06-01

The aim of this study was to investigate nurse educators' perceptions of the quality of their working life. Questionnaires were sent to 706 Finnish nurse educators and their spouses or other adult living with them. The results concerning the structured part of the questionnaire have been described in detail in an earlier paper (Harri 1995). This paper describes the data collected by means of semi-structured questions from 477 (68%) educators and 409 (58%) spouses) and open-ended questions (309 nurse educators and 167 spouses), analysed using content analysis. The seven categories that were identified as the best features of work were, in descending order of prevalence: students, freedom, challenges, teaching, miscellaneous, colleagues, and physical environment. Among the worst features of work, workload ranked first, followed by inadequacy of personal resources, administrative issues, changes, interpersonal relationships, miscellaneous, and physical environment. In the open-ended comments the nurse educators used 400 expressions to describe positive features of their working life, while they used 597 expressions to describe negative features. The spouses made 90 positive comments about the working life of their teacher spouse, and 425 negative comments. The importance of this kind of study was remarked on quite frequently both by nurse educators (22%) and their spouses (12%). The study provides important clues to understanding the present reality of nurse educators' working life. It is hoped that the findings of the study will help focus attention on ways of developing the quality of nurse educators' working life.

A quasi-Hertzian stress field from an internal source: A possible working model for the Vredefort structure

NASA Technical Reports Server (NTRS)

Antoine, L. A. G.; Reimold, W. U.; Colliston, W. P.

1992-01-01

The Vredefort structure is a large domal feature about 110 km southeast of Johannesburg, South Africa, situated within and almost central to the large intracratonic Witwatersrand Basin. This structure consists of an Archean core of ca. 45 km in diameter, consisting largely of granitic gneiss, surrounded by a collar of metasedimentary and metavolcanic supracrustal rocks of the Dominian Group, Witwatersrand and Ventersdorp Supergroups, and Transvaal Sequence. The interpretation of images of the gravity and magnetic fields over Vredefort has permitted the delineation of several important features of the structure and of its environment. The outline of the collar strata is a prominent feature of both the gravity and the magnetic fields. The Vredefort structure shares this distinctive geometry with other structures (e.g., Manicouagan, Decaturville, Sierra Madera) of debated impact origin. In all these, successively older strata with steep outward dips are encountered while traversing inward to the center of the structure. A further attribute of these structures is the shortening of the outcrop of a particular stratigraphic unit compared to the original perimeter of that unit. To account for the geometric attributes of the Vredefort structure a mechanical scheme is required where there is radial movement of horizontal strata toward, with uplift in, the center of the Vredefort structure. Two models can be proposed: (1) one in which there is a rapid rise and violent disruption of cover rocks in response to expansion of a fluid accumulation; and (2) one in which there is, in contrast, a nonexplosive, quasi-Hertzian stress field resulting from a diapiric process. Both models can accommodate the geometry and structural components of Vredefort.

The effect of alkaline pretreatment methods on cellulose structure and accessibility

DOE PAGES

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

2014-11-24

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

13C NMR spectroscopy of the insoluble carbon of carbonaceous chondrites

NASA Technical Reports Server (NTRS)

Cronin, J. R.; Pizzarello, S.; Frye, J. S.

1987-01-01

13C NMR spectra have been obtained of the insoluble carbon residues resulting from HF-digestion of three carbonaceous chondrites, Orgueil (C1), Murchison (CM2), and Allende (CV3). Spectra obtained using the cross polarization magic-angle spinning technique show two major features attributable respectively to carbon in aliphatic/olefinic structures. The spectrum obtained from the Allende sample was weak, presumably as a consequence of its low hydrogen content. Single pulse excitation spectra, which do not depend on 1H-13C polarization transfer for signal enhancement were also obtained. These spectra, which may be more representative of the total carbon in the meteorite samples, indicate a greater content of carbon in aromatic/olefinic structures. These results suggest that extensive polycyclic aromatic sheets are important structural features of the insoluble carbon of all three meteorites. The Orgueil and Murchison materials contain additional hydrogenated aromatic/olefinic and aliphatic groups.

Brain modularity controls the critical behavior of spontaneous activity.

PubMed

Russo, R; Herrmann, H J; de Arcangelis, L

2014-03-13

The human brain exhibits a complex structure made of scale-free highly connected modules loosely interconnected by weaker links to form a small-world network. These features appear in healthy patients whereas neurological diseases often modify this structure. An important open question concerns the role of brain modularity in sustaining the critical behaviour of spontaneous activity. Here we analyse the neuronal activity of a model, successful in reproducing on non-modular networks the scaling behaviour observed in experimental data, on a modular network implementing the main statistical features measured in human brain. We show that on a modular network, regardless the strength of the synaptic connections or the modular size and number, activity is never fully scale-free. Neuronal avalanches can invade different modules which results in an activity depression, hindering further avalanche propagation. Critical behaviour is solely recovered if inter-module connections are added, modifying the modular into a more random structure.

Abdominal Tumor Characterization and Recognition Using Superior-Order Cooccurrence Matrices, Based on Ultrasound Images

PubMed Central

Mitrea, Delia; Mitrea, Paulina; Nedevschi, Sergiu; Badea, Radu; Lupsor, Monica; Socaciu, Mihai; Golea, Adela; Hagiu, Claudia; Ciobanu, Lidia

2012-01-01

The noninvasive diagnosis of the malignant tumors is an important issue in research nowadays. Our purpose is to elaborate computerized, texture-based methods for performing computer-aided characterization and automatic diagnosis of these tumors, using only the information from ultrasound images. In this paper, we considered some of the most frequent abdominal malignant tumors: the hepatocellular carcinoma and the colonic tumors. We compared these structures with the benign tumors and with other visually similar diseases. Besides the textural features that proved in our previous research to be useful in the characterization and recognition of the malignant tumors, we improved our method by using the grey level cooccurrence matrix and the edge orientation cooccurrence matrix of superior order. As resulted from our experiments, the new textural features increased the malignant tumor classification performance, also revealing visual and physical properties of these structures that emphasized the complex, chaotic structure of the corresponding tissue. PMID:22312411

Age structure is critical to the population dynamics and survival of honeybee colonies.

PubMed

Betti, M I; Wahl, L M; Zamir, M

2016-11-01

Age structure is an important feature of the division of labour within honeybee colonies, but its effects on colony dynamics have rarely been explored. We present a model of a honeybee colony that incorporates this key feature, and use this model to explore the effects of both winter and disease on the fate of the colony. The model offers a novel explanation for the frequently observed phenomenon of 'spring dwindle', which emerges as a natural consequence of the age-structured dynamics. Furthermore, the results indicate that a model taking age structure into account markedly affects the predicted timing and severity of disease within a bee colony. The timing of the onset of disease with respect to the changing seasons may also have a substantial impact on the fate of a honeybee colony. Finally, simulations predict that an infection may persist in a honeybee colony over several years, with effects that compound over time. Thus, the ultimate collapse of the colony may be the result of events several years past.

Optimized Structure of the Traffic Flow Forecasting Model With a Deep Learning Approach.

PubMed

Yang, Hao-Fan; Dillon, Tharam S; Chen, Yi-Ping Phoebe

2017-10-01

Forecasting accuracy is an important issue for successful intelligent traffic management, especially in the domain of traffic efficiency and congestion reduction. The dawning of the big data era brings opportunities to greatly improve prediction accuracy. In this paper, we propose a novel model, stacked autoencoder Levenberg-Marquardt model, which is a type of deep architecture of neural network approach aiming to improve forecasting accuracy. The proposed model is designed using the Taguchi method to develop an optimized structure and to learn traffic flow features through layer-by-layer feature granulation with a greedy layerwise unsupervised learning algorithm. It is applied to real-world data collected from the M6 freeway in the U.K. and is compared with three existing traffic predictors. To the best of our knowledge, this is the first time that an optimized structure of the traffic flow forecasting model with a deep learning approach is presented. The evaluation results demonstrate that the proposed model with an optimized structure has superior performance in traffic flow forecasting.

Simplified and refined finite element approaches for determining stresses and internal forces in geometrically nonlinear structural analysis

NASA Technical Reports Server (NTRS)

Robinson, J. C.

1979-01-01

Two methods for determining stresses and internal forces in geometrically nonlinear structural analysis are presented. The simplified approach uses the mid-deformed structural position to evaluate strains when rigid body rotation is present. The important feature of this approach is that it can easily be used with a general-purpose finite-element computer program. The refined approach uses element intrinsic or corotational coordinates and a geometric transformation to determine element strains from joint displacements. Results are presented which demonstrate the capabilities of these potentially useful approaches for geometrically nonlinear structural analysis.

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.

Structure-preserving model reduction of large-scale logistics networks. Applications for supply chains

NASA Astrophysics Data System (ADS)

Scholz-Reiter, B.; Wirth, F.; Dashkovskiy, S.; Makuschewitz, T.; Schönlein, M.; Kosmykov, M.

2011-12-01

We investigate the problem of model reduction with a view to large-scale logistics networks, specifically supply chains. Such networks are modeled by means of graphs, which describe the structure of material flow. An aim of the proposed model reduction procedure is to preserve important features within the network. As a new methodology we introduce the LogRank as a measure for the importance of locations, which is based on the structure of the flows within the network. We argue that these properties reflect relative importance of locations. Based on the LogRank we identify subgraphs of the network that can be neglected or aggregated. The effect of this is discussed for a few motifs. Using this approach we present a meta algorithm for structure-preserving model reduction that can be adapted to different mathematical modeling frameworks. The capabilities of the approach are demonstrated with a test case, where a logistics network is modeled as a Jackson network, i.e., a particular type of queueing network.

Modeling asthma: Pitfalls, promises, and the road ahead.

PubMed

Rosenberg, Helene F; Druey, Kirk M

2018-02-16

Asthma is a chronic, heterogeneous, and recurring inflammatory disease of the lower airways, with exacerbations that feature airway inflammation and bronchial hyperresponsiveness. Asthma has been modeled extensively via disease induction in both wild-type and genetically manipulated laboratory mice (Mus musculus). Antigen sensitization and challenge strategies have reproduced numerous important features of airway inflammation characteristic of human asthma, notably the critical roles of type 2 T helper cell cytokines. Recent models of disease induction have advanced to include physiologic aeroallergens with prolonged respiratory challenge without systemic sensitization; others incorporate tobacco, respiratory viruses, or bacteria as exacerbants. Nonetheless, differences in lung size, structure, and physiologic responses limit the degree to which airway dynamics measured in mice can be compared to human subjects. Other rodent allergic airways models, including those featuring the guinea pig (Cavia porcellus) might be considered for lung function studies. Finally, domestic cats (Feline catus) and horses (Equus caballus) develop spontaneous obstructive airway disorders with clinical and pathologic features that parallel human asthma. Information on pathogenesis and treatment of these disorders is an important resource. ©2018 Society for Leukocyte Biology.

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

nextPARS: parallel probing of RNA structures in Illumina

PubMed Central

Saus, Ester; Willis, Jesse R.; Pryszcz, Leszek P.; Hafez, Ahmed; Llorens, Carlos; Himmelbauer, Heinz

2018-01-01

RNA molecules play important roles in virtually every cellular process. These functions are often mediated through the adoption of specific structures that enable RNAs to interact with other molecules. Thus, determining the secondary structures of RNAs is central to understanding their function and evolution. In recent years several sequencing-based approaches have been developed that allow probing structural features of thousands of RNA molecules present in a sample. Here, we describe nextPARS, a novel Illumina-based implementation of in vitro parallel probing of RNA structures. Our approach achieves comparable accuracy to previous implementations, while enabling higher throughput and sample multiplexing. PMID:29358234

Biologically active ligands for yersinia outer protein H (YopH): feature based pharmacophore screening, docking and molecular dynamics studies.

PubMed

Tamilvanan, Thangaraju; Hopper, Waheeta

2014-01-01

Yersinia pestis, a Gram negative bacillus, spreads via lymphatic to lymph nodes and to all organs through the bloodstream, causing plague. Yersinia outer protein H (YopH) is one of the important effector proteins, which paralyzes lymphocytes and macrophages by dephosphorylating critical tyrosine kinases and signal transduction molecules. The purpose of the study is to generate a three-dimensional (3D) pharmacophore model by using diverse sets of YopH inhibitors, which would be useful for designing of potential antitoxin. In this study, we have selected 60 biologically active inhibitors of YopH to perform Ligand based pharmacophore study to elucidate the important structural features responsible for biological activity. Pharmacophore model demonstrated the importance of two acceptors, one hydrophobic and two aromatic features toward the biological activity. Based on these features, different databases were screened to identify novel compounds and these ligands were subjected for docking, ADME properties and Binding energy prediction. Post docking validation was performed using molecular dynamics simulation for selected ligands to calculate the Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF). The ligands, ASN03270114, Mol_252138, Mol_31073 and ZINC04237078 may act as inhibitors against YopH of Y. pestis.

Comparing ground-penetrating radar (GPR) techniques in 18th-century yard spaces

NASA Astrophysics Data System (ADS)

Carducci, Christiane M.

Yards surrounding historical homesteads are the liminal space between private houses and public space, and contain artifactural and structural remains that help us understand how the residents interfaced with the world. Comparing different yards means collecting reliable evidence, and what is missing is just as important as what is found. Excavations can rely on randomly placed 50-cm shovel test pits to locate features, but this can miss important features. Shallow geophysics, in particular ground-penetrating radar (GPR), can be used to identify features and reliably and efficiently collect evidence. GPR is becoming more integrated into archaeological investigations due to the potential to quickly and nondestructively identify archaeological features and to recent advancements in processing software that make these methods more user-friendly. The most efficacious GPR surveys must take into consideration what is expected to be below the surface, what features look like in GPR outputs, the best methods for detecting features, and the limitations of GPR surveys. Man-made landscape features are expected to have existed within yard spaces, and the alteration of these features shows how the domestic economy of the residence changed through time. This study creates an inventory of these features. By producing a standardized sampling method for GPR in yard spaces, archaeologists can quickly map subsurface features and carry out broad comparisons between yards. To determine the most effective sampling method, several GPR surveys were conducted at the 18th-century Durant-Kenrick House in Newton, Massachusetts, using varied line spacing, line direction, and bin size. Examples of the GPR signatures of features, obtained using GPR-Slice software, from the Durant-Kenrick House and similar sites were analyzed. The efficacy of each method was determined based on the number of features distinguished, clarity of the results, and the time involved. The survey at Newton showed that ground surface conditions are extremely important when using GPR. Furthermore, GPR and archaeological excavations together provide the most complete interpretation because GPR has the ability to detect large-scale features that might be missed with test units, while excavation provides more detailed information, finds small-scale objects, and can be used to test false negatives seen in GPR surveys.

Rtools: a web server for various secondary structural analyses on single RNA sequences.

PubMed

Hamada, Michiaki; Ono, Yukiteru; Kiryu, Hisanori; Sato, Kengo; Kato, Yuki; Fukunaga, Tsukasa; Mori, Ryota; Asai, Kiyoshi

2016-07-08

The secondary structures, as well as the nucleotide sequences, are the important features of RNA molecules to characterize their functions. According to the thermodynamic model, however, the probability of any secondary structure is very small. As a consequence, any tool to predict the secondary structures of RNAs has limited accuracy. On the other hand, there are a few tools to compensate the imperfect predictions by calculating and visualizing the secondary structural information from RNA sequences. It is desirable to obtain the rich information from those tools through a friendly interface. We implemented a web server of the tools to predict secondary structures and to calculate various structural features based on the energy models of secondary structures. By just giving an RNA sequence to the web server, the user can get the different types of solutions of the secondary structures, the marginal probabilities such as base-paring probabilities, loop probabilities and accessibilities of the local bases, the energy changes by arbitrary base mutations as well as the measures for validations of the predicted secondary structures. The web server is available at http://rtools.cbrc.jp, which integrates software tools, CentroidFold, CentroidHomfold, IPKnot, CapR, Raccess, Rchange and RintD. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

PubMed

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

2009-03-01

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

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.

A Conceptual and Psychometric Framework for Distinguishing Categories and Dimensions

ERIC Educational Resources Information Center

De Boeck, Paul; Wilson, Mark; Acton, G. Scott

2005-01-01

An important, sometimes controversial feature of all psychological phenomena is whether they are categorical or dimensional. A conceptual and psychometric framework is described for distinguishing whether the latent structure behind manifest categories (e.g., psychiatric diagnoses, attitude groups, or stages of development) is category-like or…

Transformation of the Schoolhouse. Annual Report for 1969.

ERIC Educational Resources Information Center

Coughlin, Gaila, Ed.

This report reviews some of the more important educational innovations that have transformed the arrangement of space and design of the schoolhouse environment. Design, structural, and functional features are described for open plan schools (schools without interior walls). Consideration is given to the use of performance specifications in the…

The Relationship between Students' Epistemologies and Model-Based Reasoning.

ERIC Educational Resources Information Center

Gobert, Janice; Discenna, Jennifer

Models and modeling are frequently used as instructional tools in science education to convey important information concerning both the explanatory and structural features of topic areas in science. The efficacy of models as such rests almost entirely upon students' ability to conceptualize them as abstracted "representations" of…

Biomimetic surface structuring using cylindrical vector femtosecond laser beams

NASA Astrophysics Data System (ADS)

Skoulas, Evangelos; Manousaki, Alexandra; Fotakis, Costas; Stratakis, Emmanuel

2017-03-01

We report on a new, single-step and scalable method to fabricate highly ordered, multi-directional and complex surface structures that mimic the unique morphological features of certain species found in nature. Biomimetic surface structuring was realized by exploiting the unique and versatile angular profile and the electric field symmetry of cylindrical vector (CV) femtosecond (fs) laser beams. It is shown that, highly controllable, periodic structures exhibiting sizes at nano-, micro- and dual- micro/nano scales can be directly written on Ni upon line and large area scanning with radial and azimuthal polarization beams. Depending on the irradiation conditions, new complex multi-directional nanostructures, inspired by the Shark’s skin morphology, as well as superhydrophobic dual-scale structures mimicking the Lotus’ leaf water repellent properties can be attained. It is concluded that the versatility and features variations of structures formed is by far superior to those obtained via laser processing with linearly polarized beams. More important, by exploiting the capabilities offered by fs CV fields, the present technique can be further extended to fabricate even more complex and unconventional structures. We believe that our approach provides a new concept in laser materials processing, which can be further exploited for expanding the breadth and novelty of applications.

Thermo-mechanical evaluation of carbon-carbon primary structure for SSTO vehicles

NASA Astrophysics Data System (ADS)

Croop, Harold C.; Lowndes, Holland B.; Hahn, Steven E.; Barthel, Chris A.

1998-01-01

An advanced development program to demonstrate carbon-carbon composite structure for use as primary load carrying structure has entered the experimental validation phase. The component being evaluated is a wing torque box section for a single-stage-to-orbit (SSTO) vehicle. The validation or demonstration component features an advanced carbon-carbon design incorporating 3D woven graphite preforms, integral spars, oxidation inhibited matrix, chemical vapor deposited (CVD) oxidation protection coating, and ceramic matrix composite fasteners. The validation component represents the culmination of a four phase design and fabrication development effort. Extensive developmental testing was performed to verify material properties and integrity of basic design features before committing to fabrication of the full scale box. The wing box component is now being set up for testing in the Air Force Research Laboratory Structural Test Facility at Wright-Patterson Air Force Base, Ohio. One of the important developmental tests performed in support of the design and planned testing of the full scale box was the fabrication and test of a skin/spar trial subcomponent. The trial subcomponent incorporated critical features of the full scale wing box design. This paper discusses the results of the trial subcomponent test which served as a pathfinder for the upcoming full scale box test.

Accounting for epistatic interactions improves the functional analysis of protein structures.

PubMed

Wilkins, Angela D; Venner, Eric; Marciano, David C; Erdin, Serkan; Atri, Benu; Lua, Rhonald C; Lichtarge, Olivier

2013-11-01

The constraints under which sequence, structure and function coevolve are not fully understood. Bringing this mutual relationship to light can reveal the molecular basis of binding, catalysis and allostery, thereby identifying function and rationally guiding protein redesign. Underlying these relationships are the epistatic interactions that occur when the consequences of a mutation to a protein are determined by the genetic background in which it occurs. Based on prior data, we hypothesize that epistatic forces operate most strongly between residues nearby in the structure, resulting in smooth evolutionary importance across the structure. We find that when residue scores of evolutionary importance are distributed smoothly between nearby residues, functional site prediction accuracy improves. Accordingly, we designed a novel measure of evolutionary importance that focuses on the interaction between pairs of structurally neighboring residues. This measure that we term pair-interaction Evolutionary Trace yields greater functional site overlap and better structure-based proteome-wide functional predictions. Our data show that the structural smoothness of evolutionary importance is a fundamental feature of the coevolution of sequence, structure and function. Mutations operate on individual residues, but selective pressure depends in part on the extent to which a mutation perturbs interactions with neighboring residues. In practice, this principle led us to redefine the importance of a residue in terms of the importance of its epistatic interactions with neighbors, yielding better annotation of functional residues, motivating experimental validation of a novel functional site in LexA and refining protein function prediction. lichtarge@bcm.edu. Supplementary data are available at Bioinformatics online.

Accounting for epistatic interactions improves the functional analysis of protein structures

PubMed Central

Wilkins, Angela D.; Venner, Eric; Marciano, David C.; Erdin, Serkan; Atri, Benu; Lua, Rhonald C.; Lichtarge, Olivier

2013-01-01

Motivation: The constraints under which sequence, structure and function coevolve are not fully understood. Bringing this mutual relationship to light can reveal the molecular basis of binding, catalysis and allostery, thereby identifying function and rationally guiding protein redesign. Underlying these relationships are the epistatic interactions that occur when the consequences of a mutation to a protein are determined by the genetic background in which it occurs. Based on prior data, we hypothesize that epistatic forces operate most strongly between residues nearby in the structure, resulting in smooth evolutionary importance across the structure. Methods and Results: We find that when residue scores of evolutionary importance are distributed smoothly between nearby residues, functional site prediction accuracy improves. Accordingly, we designed a novel measure of evolutionary importance that focuses on the interaction between pairs of structurally neighboring residues. This measure that we term pair-interaction Evolutionary Trace yields greater functional site overlap and better structure-based proteome-wide functional predictions. Conclusions: Our data show that the structural smoothness of evolutionary importance is a fundamental feature of the coevolution of sequence, structure and function. Mutations operate on individual residues, but selective pressure depends in part on the extent to which a mutation perturbs interactions with neighboring residues. In practice, this principle led us to redefine the importance of a residue in terms of the importance of its epistatic interactions with neighbors, yielding better annotation of functional residues, motivating experimental validation of a novel functional site in LexA and refining protein function prediction. Contact: lichtarge@bcm.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24021383

Tuning transport properties on graphene multiterminal structures by mechanical deformations

NASA Astrophysics Data System (ADS)

Latge, Andrea; Torres, Vanessa; Faria, Daiara

The realization of mechanical strain on graphene structures is viewed as a promise route to tune electronic and transport properties such as changing energy band-gaps and promoting localization of states. Using continuum models, mechanical deformations are described by effective gauge fields, mirrored as pseudomagnetic fields that may reach quite high values. Interesting symmetry features are developed due to out of plane deformations on graphene; lift sublattice symmetry was predicted and observed in centrosymmetric bumps and strained nanobubbles. Here we discuss the effects of Gaussian-like strain on a hexagonal graphene flake connected to three leads, modeled as perfect graphene nanoribbons. The Green function formalism is used within a tight-binding approximation. For this particular deformation sharp resonant states are achieved depending on the strained structure details. We also study a fold-strained structure in which the three leads are deformed extending up to the very center of the hexagonal flake. We show that conductance suppressions can be controlled by the strain intensity and important transport features are modeled by the electronic band structure of the leads.

Crystal Structure of Cockroach Allergen Bla g 2, an Unusual Zinc Binding Aspartic Protease with a Novel Mode of Self-inhibition

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

Gustchina, Alla; Li, Mi; Wunschmann, Sabina

2010-07-19

The crystal structure of Bla g 2 was solved in order to investigate the structural basis for the allergenic properties of this unusual protein. This is the first structure of an aspartic protease in which conserved glycine residues, in two canonical DTG triads, are substituted by different amino acid residues. Another unprecedented feature revealed by the structure is the single phenylalanine residue insertion on the tip of the flap, with the side-chain occupying the S1 binding pocket. This and other important amino acid substitutions in the active site region of Bla g 2 modify the interactions in the vicinity ofmore » the catalytic aspartate residues, increasing the distance between them to {approx}4 {angstrom} and establishing unique direct contacts between the flap and the catalytic residues. We attribute the absence of substantial catalytic activity in Bla g 2 to these unusual features of the active site. Five disulfide bridges and a Zn-binding site confer stability to the protein, which may contribute to sensitization at lower levels of exposure than other allergens.« less

Methods and strategies of object localization

NASA Technical Reports Server (NTRS)

Shao, Lejun; Volz, Richard A.

1989-01-01

An important property of an intelligent robot is to be able to determine the location of an object in 3-D space. A general object localization system structure is proposed, some important issues on localization discussed, and an overview given for current available object localization algorithms and systems. The algorithms reviewed are characterized by their feature extracting and matching strategies; the range finding methods; the types of locatable objects; and the mathematical formulating methods.

X-ray and Neutron Scattering Study of the Formation of Core–Shell-Type Polyoxometalates

DOE PAGES

Yin, Panchao; Wu, Bin; Mamontov, Eugene; ...

2016-02-05

A typical type of core-shell polyoxometalates can be obtained through the Keggin-type polyoxometalate-templated growth of a layer of spherical shell structure of {Mo 72Fe 30}. Small angle X-ray scattering is used to study the structural features and stability of the core-shell structures in aqueous solutions. Time-resolved small angle X-ray scattering is applied to monitor the synthetic reactions and a three-stage formation mechanism is proposed to describe the synthesis of the core-shell polyoxometalates based on the monitoring results. Quasi-elastic and inelastic neutron scattering are used to probe the dynamics of water molecules in the core-shell structures and two different types ofmore » water molecules, the confined and structured water, are observed. These water molecules play an important role in bridging core and shell structures and stabilizing the cluster structures. A typical type of core shell polyoxometalates can be obtained through the Keggin-type polyoxometalate-templated growth of a layer of spherical shell structure of {Mo 72Fe 30}. Small-angle X-ray scattering is used to study the structural features and stability of the core shell structures in aqueous solutions. Time-resolved small-angle X-ray scattering is applied to monitor the synthetic reactions, and a three-stage formation mechanism is proposed to describe the synthesis of the core shell polyoxometalates based on the monitoring results. New protocols have been developed by fitting the X-ray data with custom physical models, which provide more convincing, objective, and completed data interpretation. Quasi-elastic and inelastic neutron scattering are used to probe the dynamics of water molecules in the core shell structures, and two different types of water molecules, the confined and structured water, are observed. These water molecules play an important role in bridging core and shell structures and stabilizing the cluster structures.« less

Dynamical injections as the source of near geostationary quiet time particle spatial boundaries

NASA Technical Reports Server (NTRS)

Mauk, B. H.; Meng, C. I.

1983-01-01

The question whether the noon-dusk feature is a manifestation of the spatial structures that should arise from quasi-stationary convection is examined. The key consideration here is whether the energy dispersion of the feature can be explained. It is shown that the observed energy dispersion cannot be attributed to the standard stationary convection configurations, either perturbed or unperturbed. It is also demonstrated, using a detailed computer simulation, that the nighttime, double-spiral-shaped injection boundary (used previously to reproduce the fast changing nighttime features) is successful at reproducing the noon-dusk feature by allowing the particles to evolve for periods of 12 to 36 hours after the injection. It is stressed that the portion of the injection boundary responsible for the feature looks very different from the standard convection boundaries configuration. Conclusions are offered concerning the importance of quasi-stationary convection as the mechanism by which the near geostationary regions are populated.

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.

Extracting features from protein sequences to improve deep extreme learning machine for protein fold recognition.

PubMed

Ibrahim, Wisam; Abadeh, Mohammad Saniee

2017-05-21

Protein fold recognition is an important problem in bioinformatics to predict three-dimensional structure of a protein. One of the most challenging tasks in protein fold recognition problem is the extraction of efficient features from the amino-acid sequences to obtain better classifiers. In this paper, we have proposed six descriptors to extract features from protein sequences. These descriptors are applied in the first stage of a three-stage framework PCA-DELM-LDA to extract feature vectors from the amino-acid sequences. Principal Component Analysis PCA has been implemented to reduce the number of extracted features. The extracted feature vectors have been used with original features to improve the performance of the Deep Extreme Learning Machine DELM in the second stage. Four new features have been extracted from the second stage and used in the third stage by Linear Discriminant Analysis LDA to classify the instances into 27 folds. The proposed framework is implemented on the independent and combined feature sets in SCOP datasets. The experimental results show that extracted feature vectors in the first stage could improve the performance of DELM in extracting new useful features in second stage. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Martian analog in Kansas: Comparing Martian strata with Permian acid saline lake deposits

NASA Astrophysics Data System (ADS)

Benison, Kathleen C.

2006-05-01

An important result of the Mars Exploration Rover's (MER) mission has been the images of sedimentary structures and diagenetic features in the Burns Formation at Meridiani Planum. Bedding, cross-bedding, ripple marks, mud cracks, displacive evaporite crystal molds, and hematite concretions are contained in these Martian strata. Together, these features are evidence of past saline groundwater and ephemeral shallow surface waters on Mars. Geochemical analyses of these Martian outcrops have established the presence of sulfates, iron oxides, and jarosite, which strongly suggests that these waters were also acidic. The same assemblage of sedimentary structures and diagenetic features is found in the salt-bearing terrestrial red sandstones and shales of the middle Permian (ca. 270 Ma) Nippewalla Group of Kansas, which were deposited in and around acid saline ephemeral lakes. These striking sedimentological and mineralogical similarities make these Permian red beds and evaporites the best-known terrestrial analog for the Martian sedimentary rocks at Meridiani Planum.

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

NASA Astrophysics Data System (ADS)

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

2012-03-01

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

Accurate prediction of personalized olfactory perception from large-scale chemoinformatic features.

PubMed

Li, Hongyang; Panwar, Bharat; Omenn, Gilbert S; Guan, Yuanfang

2018-02-01

The olfactory stimulus-percept problem has been studied for more than a century, yet it is still hard to precisely predict the odor given the large-scale chemoinformatic features of an odorant molecule. A major challenge is that the perceived qualities vary greatly among individuals due to different genetic and cultural backgrounds. Moreover, the combinatorial interactions between multiple odorant receptors and diverse molecules significantly complicate the olfaction prediction. Many attempts have been made to establish structure-odor relationships for intensity and pleasantness, but no models are available to predict the personalized multi-odor attributes of molecules. In this study, we describe our winning algorithm for predicting individual and population perceptual responses to various odorants in the DREAM Olfaction Prediction Challenge. We find that random forest model consisting of multiple decision trees is well suited to this prediction problem, given the large feature spaces and high variability of perceptual ratings among individuals. Integrating both population and individual perceptions into our model effectively reduces the influence of noise and outliers. By analyzing the importance of each chemical feature, we find that a small set of low- and nondegenerative features is sufficient for accurate prediction. Our random forest model successfully predicts personalized odor attributes of structurally diverse molecules. This model together with the top discriminative features has the potential to extend our understanding of olfactory perception mechanisms and provide an alternative for rational odorant design.

Biologically important conformational features of DNA as interpreted by quantum mechanics and molecular mechanics computations of its simple fragments.

PubMed

Poltev, V; Anisimov, V M; Dominguez, V; Gonzalez, E; Deriabina, A; Garcia, D; Rivas, F; Polteva, N A

2018-02-01

Deciphering the mechanism of functioning of DNA as the carrier of genetic information requires identifying inherent factors determining its structure and function. Following this path, our previous DFT studies attributed the origin of unique conformational characteristics of right-handed Watson-Crick duplexes (WCDs) to the conformational profile of deoxydinucleoside monophosphates (dDMPs) serving as the minimal repeating units of DNA strand. According to those findings, the directionality of the sugar-phosphate chain and the characteristic ranges of dihedral angles of energy minima combined with the geometric differences between purines and pyrimidines determine the dependence on base sequence of the three-dimensional (3D) structure of WCDs. This work extends our computational study to complementary deoxydinucleotide-monophosphates (cdDMPs) of non-standard conformation, including those of Z-family, Hoogsteen duplexes, parallel-stranded structures, and duplexes with mispaired bases. For most of these systems, except Z-conformation, computations closely reproduce experimental data within the tolerance of characteristic limits of dihedral parameters for each conformation family. Computation of cdDMPs with Z-conformation reveals that their experimental structures do not correspond to the internal energy minimum. This finding establishes the leading role of external factors in formation of the Z-conformation. Energy minima of cdDMPs of non-Watson-Crick duplexes demonstrate different sequence-dependence features than those known for WCDs. The obtained results provide evidence that the biologically important regularities of 3D structure distinguish WCDs from duplexes having non-Watson-Crick nucleotide pairing.

On the use of INS to improve Feature Matching

NASA Astrophysics Data System (ADS)

Masiero, A.; Guarnieri, A.; Vettore, A.; Pirotti, F.

2014-11-01

The continuous technological improvement of mobile devices opens the frontiers of Mobile Mapping systems to very compact systems, i.e. a smartphone or a tablet. This motivates the development of efficient 3D reconstruction techniques based on the sensors typically embedded in such devices, i.e. imaging sensors, GPS and Inertial Navigation System (INS). Such methods usually exploits photogrammetry techniques (structure from motion) to provide an estimation of the geometry of the scene. Actually, 3D reconstruction techniques (e.g. structure from motion) rely on use of features properly matched in different images to compute the 3D positions of objects by means of triangulation. Hence, correct feature matching is of fundamental importance to ensure good quality 3D reconstructions. Matching methods are based on the appearance of features, that can change as a consequence of variations of camera position and orientation, and environment illumination. For this reason, several methods have been developed in recent years in order to provide feature descriptors robust (ideally invariant) to such variations, e.g. Scale-Invariant Feature Transform (SIFT), Affine SIFT, Hessian affine and Harris affine detectors, Maximally Stable Extremal Regions (MSER). This work deals with the integration of information provided by the INS in the feature matching procedure: a previously developed navigation algorithm is used to constantly estimate the device position and orientation. Then, such information is exploited to estimate the transformation of feature regions between two camera views. This allows to compare regions from different images but associated to the same feature as seen by the same point of view, hence significantly easing the comparison of feature characteristics and, consequently, improving matching. SIFT-like descriptors are used in order to ensure good matching results in presence of illumination variations and to compensate the approximations related to the estimation process.

Chemical and structural indicators for large redox potentials in Fe-based positive electrode materials.

PubMed

Melot, Brent C; Scanlon, David O; Reynaud, Marine; Rousse, Gwenaëlle; Chotard, Jean-Noël; Henry, Marc; Tarascon, Jean-Marie

2014-07-23

Li-ion batteries have enabled a revolution in the way portable consumer-electronics are powered and will play an important role as large-scale electrochemical storage applications like electric vehicles and grid-storage are developed. The ability to identify and design promising new positive insertion electrodes will be vital in continuing to push Li-ion technology to its fullest potential. Utilizing a combination of computational tools and structural analysis, we report new indicators which will facilitate the recognition of phases with the desired redox potential. Most importantly of these, we find there is a strong correlation between the presence of Li ions sitting in close-proximity to the redox center of polyanionic phases and the open circuit voltage in Fe-based cathodes. This common structural feature suggests that the bonding associated with Li may have a secondary inductive effect which increases the ionic character of Fe bonds beyond what is typically expected based purely on arguments of electronegativity associated with the polyanionic group. This correlation is supported by ab initio calculations which show the Bader charge increases (reflecting an increased ionicity) in a nearly linear fashion with the experimental cell potentials. These features are demonstrated to be consistent across a wide variety of compositions and structures and should help to facilitate the design of new, high-potential, and environmentally sustainable insertion electrodes.

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

PubMed

Mourad, Raphaël; Cuvier, Olivier

2016-05-01

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

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

PubMed Central

Mourad, Raphaël; Cuvier, Olivier

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

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

USGS Publications Warehouse

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

2017-01-01

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

Thiabendazole inhibits ubiquinone reduction activity of mitochondrial respiratory complex II via a water molecule mediated binding feature.

PubMed

Zhou, Qiangjun; Zhai, Yujia; Lou, Jizhong; Liu, Man; Pang, Xiaoyun; Sun, Fei

2011-07-01

The mitochondrial respiratory complex II or succinate: ubiquinone oxidoreductase (SQR) is a key membrane complex in both the tricarboxylic acid cycle and aerobic respiration. Five disinfectant compounds were investigated with their potent inhibition effects on the ubiquinone reduction activity of the porcine mitochondrial SQR by enzymatic assay and crystallography. Crystal structure of the SQR bound with thiabendazole (TBZ) reveals a different inhibitor-binding feature at the ubiquinone binding site where a water molecule plays an important role. The obvious inhibitory effect of TBZ based on the biochemical data (IC(50) ~100 μmol/L) and the significant structure-based binding affinity calculation (~94 μmol/L) draw the suspicion of using TBZ as a good disinfectant compound for nematode infections treatment and fruit storage.

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

USGS Publications Warehouse

Ruth, Janet M.; Skagen, Susan K.

2017-01-01

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

Distributed rewiring model for complex networking: The effect of local rewiring rules on final structural properties.

PubMed

López Chavira, Magali Alexander; Marcelín-Jiménez, Ricardo

2017-01-01

The study of complex networks has become an important subject over the last decades. It has been shown that these structures have special features, such as their diameter, or their average path length, which in turn are the explanation of some functional properties in a system such as its fault tolerance, its fragility before attacks, or the ability to support routing procedures. In the present work, we study some of the forces that help a network to evolve to the point where structural properties are settled. Although our work is mainly focused on the possibility of applying our ideas to Information and Communication Technologies systems, we consider that our results may contribute to understanding different scenarios where complex networks have become an important modeling tool. Using a discrete event simulator, we get each node to discover the shortcuts that may connect it with regions away from its local environment. Based on this partial knowledge, each node can rewire some of its links, which allows modifying the topology of the entire underlying graph to achieve new structural properties. We proposed a distributed rewiring model that creates networks with features similar to those found in complex networks. Although each node acts in a distributed way and seeking to reduce only the trajectories of its packets, we observed a decrease of diameter and an increase in clustering coefficient in the global structure compared to the initial graph. Furthermore, we can find different final structures depending on slight changes in the local rewiring rules.

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

Effective Moment Feature Vectors for Protein Domain Structures

PubMed Central

Shi, Jian-Yu; Yiu, Siu-Ming; Zhang, Yan-Ning; Chin, Francis Yuk-Lun

2013-01-01

Imaging processing techniques have been shown to be useful in studying protein domain structures. The idea is to represent the pairwise distances of any two residues of the structure in a 2D distance matrix (DM). Features and/or submatrices are extracted from this DM to represent a domain. Existing approaches, however, may involve a large number of features (100–400) or complicated mathematical operations. Finding fewer but more effective features is always desirable. In this paper, based on some key observations on DMs, we are able to decompose a DM image into four basic binary images, each representing the structural characteristics of a fundamental secondary structure element (SSE) or a motif in the domain. Using the concept of moments in image processing, we further derive 45 structural features based on the four binary images. Together with 4 features extracted from the basic images, we represent the structure of a domain using 49 features. We show that our feature vectors can represent domain structures effectively in terms of the following. (1) We show a higher accuracy for domain classification. (2) We show a clear and consistent distribution of domains using our proposed structural vector space. (3) We are able to cluster the domains according to our moment features and demonstrate a relationship between structural variation and functional diversity. PMID:24391828

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Molecular engineering of phosphole-based conjugated materials

NASA Astrophysics Data System (ADS)

Ren, Yi

The work in this thesis focuses on the molecular engineering of phosphorus-based conjugated materials. In the first part (Chapters Two and Three), new phosphorus-based conjugated systems were designed and synthesized to study the effect of the heteroelement on the electronic properties of the π-conjugated systems. The second part (Chapters Four and Five) deals with the self-assembly features of specifically designed phosphorus-based conjugated systems. In Chapter Two, electron-poor and electron-rich aromatic substituents were introduced to the dithienophosphole core in order to balance the electron-accepting and electron-donating character of the systems. Furthermore, an intriguing intramolecular charge transfer process could be observed between two dithienophosphole cores in a bridged bisphosphole-system. In Chapter Three, a secondary heteroelement (Si, P, S) was incorporated in the phosphorus-based conjugated systems. Extensive structure-property studies revealed that the secondary heteroelement can effectively manipulate the communication in phosphinine-based systems. The study of a heterotetracene system allowed for selectively applying distinct heteroatom (S/P) chemistries, which offers a powerful tool for the modification of the electronic structure of the system. More importantly, the heteroatom-specific electronic nature (S/P) can be utilized to selectively control different photophysical aspects (energy gap and fluorescence quantum yield). Furthermore, additional molecular engineering of the heterotetracene provided access to well-defined 1D microstructures, which opened the door for designing multi-functional self-assembled phosphorus-based materials. In Chapter Four, the self-organizing phosphole-lipid system is introduced, which combines the features of phospholipids with the electronics of phospholes. Its amphiphilic nature induces intriguing self-assembly features - liquid crystal and soft crystal architectures, both exhibiting well-organized lamellar structure at a wide range of temperatures. Importantly, its dynamic structure endows the phosphole-lipid system with intriguing external stimuli-responsive features allowing for the modification of the emission of the system without further chemical modification. Chapter Five describes how further molecular engineering allowed for access to a series of new highly fluorescent phosphole-lipid organogels. Remarkably, the external-stimuli responsive features of the system can be amplified in a donor-acceptor system accessible through changes in long distance fluorescence resonance energy transfer processes. In addition, the first fluorescent liquid phospholes could also be accessed in the context of the work on the new phosphole-lipid system.

Resonances and bound states in the continuum on periodic arrays of slightly noncircular cylinders

NASA Astrophysics Data System (ADS)

Hu, Zhen; Lu, Ya Yan

2018-02-01

Optical bound states in the continuum (BICs), especially those on periodic structures, have interesting properties and potentially important applications. Existing theoretical and numerical studies for optical BICs are mostly for idealized structures with simple and perfect geometric features, such as circular holes, rectangular cylinders and spheres. Since small distortions are always present in actual fabricated structures, we perform a high accuracy numerical study for BICs and resonances on a simple periodic structure with small distortions, i.e., periodic arrays of slightly noncircular cylinders. Our numerical results confirm that symmetries are important not only for the so-called symmetry-protected BICs, but also for the majority of propagating BICs which do not have a symmetry mismatch with the outgoing radiation waves. Typically, the BICs continue to exist if the small distortions keep the relevant symmetries, and they become resonant modes with finite quality factors if the small distortions break a required symmetry.

A computational prediction of structure and function of novel homologue of Arabidopsis thaliana Vps51/Vps67 subunit in Corchorus olitorius.

PubMed

Zaman, Aubhishek; Fancy, Nurun Nahar

2012-12-01

Vps mediated vesicular transport is important for transferring macromolecules trapped inside a vesicle. Although highly abundant, Vps shows tremendous sequence variation among diverse array of species. However, this difference in sequence, which seems to also translate into substantial functional variation, is hardly characterized in Corchorus spp. Here, our computational study investigates structural and functional features of one of the Vps subunit namely Vps51/Vps67 in C. olitorius. Broad scale structural characterization revealed novel information about the overall Vps structure and binding sites. Moreover, functional analyses indicate interaction partners which were unexplored to date. Since membrane trafficking is essentially associated with nutrient uptake and chemical de-toxification, characterization of the Vps subunit can well provide us with better insight into important agronomic traits such as stress response, immune response and phytoremediation capacity.

Development and Application of a Three-Dimensional Finite Element Vapor Intrusion Model

PubMed Central

Pennell, Kelly G.; Bozkurt, Ozgur; Suuberg, Eric M.

2010-01-01

Details of a three-dimensional finite element model of soil vapor intrusion, including the overall modeling process and the stepwise approach, are provided. The model is a quantitative modeling tool that can help guide vapor intrusion characterization efforts. It solves the soil gas continuity equation coupled with the chemical transport equation, allowing for both advective and diffusive transport. Three-dimensional pressure, velocity, and chemical concentration fields are produced from the model. Results from simulations involving common site features, such as impervious surfaces, porous foundation sub-base material, and adjacent structures are summarized herein. The results suggest that site-specific features are important to consider when characterizing vapor intrusion risks. More importantly, the results suggest that soil gas or subslab gas samples taken without proper regard for particular site features may not be suitable for evaluating vapor intrusion risks; rather, careful attention needs to be given to the many factors that affect chemical transport into and around buildings. PMID:19418819

Technical design and system implementation of region-line primitive association framework

NASA Astrophysics Data System (ADS)

Wang, Min; Xing, Jinjin; Wang, Jie; Lv, Guonian

2017-08-01

Apart from regions, image edge lines are an important information source, and they deserve more attention in object-based image analysis (OBIA) than they currently receive. In the region-line primitive association framework (RLPAF), we promote straight-edge lines as line primitives to achieve powerful OBIAs. Along with regions, straight lines become basic units for subsequent extraction and analysis of OBIA features. This study develops a new software system called remote-sensing knowledge finder (RSFinder) to implement RLPAF for engineering application purposes. This paper introduces the extended technical framework, a comprehensively designed feature set, key technology, and software implementation. To our knowledge, RSFinder is the world's first OBIA system based on two types of primitives, namely, regions and lines. It is fundamentally different from other well-known region-only-based OBIA systems, such as eCogntion and ENVI feature extraction module. This paper has important reference values for the development of similarly structured OBIA systems and line-involved extraction algorithms of remote sensing information.

Chemical features of Ganoderma polysaccharides with antioxidant, antitumor and antimicrobial activities.

PubMed

Ferreira, Isabel C F R; Heleno, Sandrina A; Reis, Filipa S; Stojkovic, Dejan; Queiroz, Maria João R P; Vasconcelos, M Helena; Sokovic, Marina

2015-06-01

Ganoderma genus comprises one of the most commonly studied species worldwide, Ganoderma lucidum. However, other Ganoderma species have been also reported as important sources of bioactive compounds. Polysaccharides are important contributors to the medicinal properties reported for Ganoderma species, as demonstrated by the numerous publications, including reviews, on this matter. Yet, what are the chemical features of Ganoderma polysaccharides that have bioactivity? In the present manuscript, the chemical features of Ganoderma polysaccharides with reported antioxidant, antitumor and antimicrobial activities (the most studied worldwide) are analyzed in detail. The composition of sugars (homo- versus hetero-glucans and other polysaccharides), type of glycosidic linkages, branching patterns, and linkage to proteins are discussed. Methods for extraction, isolation and identification are evaluated and, finally, the bioactivity of polysaccharidic extracts and purified compounds are discussed. The integration of data allows deduction of structure-activity relationships and gives clues to the chemical aspects involved in Ganoderma bioactivity. Copyright © 2014 Elsevier Ltd. All rights reserved.

Have personal statements become impersonal? An evaluation of personal statements in anesthesiology residency applications.

PubMed

Max, Bryan A; Gelfand, Brian; Brooks, Meredith R; Beckerly, Rena; Segal, Scott

2010-08-01

To evaluate personal statements submitted to a major academic anesthesiology program to determine the prevalence of common features and overall subjective quality, and to survey anesthesiology program directors as to how they utilized these statements during the resident selection process. Structured analysis of de-identified personal statements and Internet-based survey of program directors. Large academic anesthesiology training program. 670 applicant personal statements and academic anesthesiology program directors. Prevalence of 13 specific essay features and 8 quality ratings were calculated for the essays and correlated with other aspects of the residency application, as abstracted from the Electronic Residency Application Service (ERAS) files. A 6-question survey regarding use of personal statements was collected from program directors. 70 of 131 program directors queried responded to our survey. Interest in physiology and pharmacology, enjoyment of a hands-on specialty, and desire to comfort anxious patients were each mentioned in more than half of the essays. Candidates invited for an interview had essays that received higher quality ratings than essays of those not invited (P = 0.02 to P < 0.0001). Higher quality ratings were also strongly associated with graduation from a U.S. or Canadian medical school, applicant file screening score, female gender, and younger age. Interrater reliability was good (kappa 0.75-0.99 for structural features, and 0.45-0.65 for quality features). More than 90% of program directors found proper use of English to be a somewhat or very important feature of the essay. Only 41% found the personal statement to be very or somewhat important in selecting candidates for interview invitations. However, over 90% stated that they used the statements during actual interviews with invited applicants. The data showed a high prevalence of common features found within personal statements and a general ambivalence amongst those program directors for whom the statements were intended. Copyright 2010 Elsevier Inc. All rights reserved.

Final Report Grant No. DE-FG02-98ER20307 Lipopolysaccharide Structures and Genes Required for Root Nodule Development August 1, 2004 to July 31, 2008

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

Noel, K. Dale

This project dealt with the plant-bacterial symbiosis that gives rise to root nodules on leguminous plants in which the bacteria carry out nitrogen fixation. Nitrogen fixation, like carbon dioxide fixation, is essential for life on planet earth, and this symbiosis is estimated to account for half of all nitrogen fixed on land. Aside from being important for the sustenance of global life, this ability allows legumes to grow without nitrogen fertilizers. Basic studies such as this project are aimed at understanding the symbiosis well enough that eventually it can be engineered into important crop species so that they no longermore » depend on nitrogen fertilizer for growth. The production and distribution of excessive fertilizer needed for optimal crop yields is responsible for a significant portion of the energy costs in agriculture. The specific aims of this work were to further the understanding of a bacterial factor that is essential for the symbiotic infection process. This factor is a bacterial surface molecule, lipopolysaccharide O antigen. In this project we showed that, not only the presence, but the specific structure of this molecule is crucial for infection. Although the success of bacterial infections in many pathogenic and mutualistic interactions have been shown to depend on intact O antigen, it has been very rare to establish that specific features of the structure are important. One of the features in this case is the presence of one additional methyl group on one sugar in the O antigen. It is very surprising that such a minor change should have an observable effect. This work sets the stage for biochemical studies of possible plant receptors that may be involved. During the course of this grant period, we developed a method of testing the importance of this bacterial component at stages of nodule development beyond the step that is blocked by null mutation. The method works adequately for this purpose and is being improved. It has implications for testing the roles of other important bacterial factors at multiple stages of nodule development. The project also investigated the biosynthesis of this bacterial factor. It has a complex structure and the first accomplishment was the determination of the sequences of genetic regions known to be important. Next the discovered genes were mutated to identify the 26 that are required for its synthesis. In addition, six others were discovered that are believed to change its structure under various environmental conditions. By studying mutants affected in specific genes, genes were associated with each of the predicted steps in the biosynthesis. Current work is testing the predicted biosynthetic model with studies conducted in vitro with bacterial extracts. Overall, the work funded by this grant establishes this system as a model for host-bacterial interactions based on specific polysaccharide structure. All areas that are needed for a comprehensive model have been significantly advanced: the biological function, the structural features that are crucial, the complete set of bacterial genes involved, and a model for the biosynthesis.« less

Biased estimation of forest log characteristics using intersect diameters

Treesearch

Lisa J. Bate; Torolf R. Torgersen; Michael J. Wisdom; Edward O. Garton

2009-01-01

Logs are an important structural feature of forest ecosystems, and their abundance affects many resources and forest processes, including fire regimes, soil productivity, silviculture, carbon cycling, and wildlife habitat. Consequently, logs are often sampled to estimate their frequency, percent cover, volume, and weight. The line-intersect method (LIM) is one of the...

Improving TV Program Comprehensibility: Developmental Effects of Visual and Verbal Production Features.

ERIC Educational Resources Information Center

Calvert, Sandra L.; And Others

Preplays (critical material presented before a televised program) were inserted before three sections of a televised story to determine if they would improve children's attention and comprehension by providing overall plot structure for selecting and integrating important story events. The preplays varied on two orthogonal dimensions: presence or…

Peer Victimization and Authoritative School Climate: A Multilevel Approach

ERIC Educational Resources Information Center

Cornell, Dewey; Shukla, Kathan; Konold, Timothy

2015-01-01

School climate is widely recognized as an important influence on peer victimization in schools. The purpose of this study is to examine how authoritative school climate theory provides a framework for conceptualizing 2 key features of school climate--disciplinary structure and student support--that are associated with 3 measures of peer…

Modeling and Measuring the Structure of Professional Vision in Preservice Teachers

ERIC Educational Resources Information Center

Seidel, Tina; Stürmer, Kathleen

2014-01-01

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

The Benefits of Collective Pedagogical Teacher Culture for Diverse Students' Mathematics Achievement by Academic Engagement

ERIC Educational Resources Information Center

Moller, Stephanie; Mickelson, Roslyn Arlin; Stearns, Elizabeth; Bottia, Martha; Banerjee, Neena

2011-01-01

Most studies of educational organizations have focused on structural features of schools, such as size, resources, and infrastructure. Research on schools' organizational culture is more sparse. Yet, these studies have suggested that the organizational culture of schools can have important implications for teaching practices and student outcomes.…

Conclusions and recommendations: Exploration of the Saturn system

NASA Technical Reports Server (NTRS)

Hunten, D. M.

1978-01-01

Saturn missions have the following principal goals, in order of importance: (1) Intensive investigation of the atmosphere of Saturn; (2) determination of regional surface chemistry and properties of the surface features of satellites and properties of ring particles; (3) intensive investigation of Titan; and (4) atmospheric dynamics and structure of Saturn satellites and Saturn rings.

Self-Monitoring during Collegiate Studying: An Invaluable Tool for Academic Self-Regulation.

ERIC Educational Resources Information Center

Zimmerman, Barry J.; Paulsen, Andrew S.

1995-01-01

Self-monitoring is an important part of self-regulated learning. While researchers agree on the overt features of self-monitoring, its psychological dimensions are disputed. Faculty can help college students learn formal, systematic techniques by teaching it in four phases: baseline, structured, independent, and self-regulated self-monitoring. A…

Histogram-based automatic thresholding for bruise detection of apples by structured-illumination reflectance imaging

USDA-ARS?s Scientific Manuscript database

Thresholding is an important step in the segmentation of image features, and the existing methods are not all effective when the image histogram exhibits a unimodal pattern, which is common in defect detection of fruit. This study was aimed at developing a general automatic thresholding methodology ...

Glycosyltransferase-mediated Sweet Modification in Oral Streptococci.

PubMed

Zhu, F; Zhang, H; Wu, H

2015-05-01

Bacterial glycosyltransferases play important roles in bacterial fitness and virulence. Oral streptococci have evolved diverse strategies to survive and thrive in the carbohydrate-rich oral cavity. In this review, we discuss 2 important biological processes mediated by 2 distinct groups of glycosyltransferases in oral streptococci that are important for bacterial colonization and virulence. The first process is the glycosylation of highly conserved serine-rich repeat adhesins by a series of glycosyltransferases. Using Streptococcus parasanguinis as a model, we highlight new features of several glycosyltransferases that sequentially modify the serine-rich glycoprotein Fap1. Distinct features of a novel glycosyltransferase fold from a domain of unknown function 1792 are contrasted with common properties of canonical glycosyltransferases. The second biological process we cover is involved in building sticky glucan matrix to establish cariogenic biofilms by an important opportunistic pathogen Streptococcus mutans through the action of a family of 3 glucosyltransferases. We focus on discussing the structural feature of this family as a glycoside hydrolase family of enzymes. While the 2 processes are distinct, they all produce carbohydrate-coated biomolecules, which enable bacteria to stick better in the complex oral microbiome. Understanding the making of the sweet modification presents a unique opportunity to develop novel antiadhesion and antibiofilm strategies to fight infections by oral streptococci and beyond. © International & American Associations for Dental Research 2015.

Glycosyltransferase-mediated Sweet Modification in Oral Streptococci

PubMed Central

Zhu, F.; Zhang, H.

2015-01-01

Bacterial glycosyltransferases play important roles in bacterial fitness and virulence. Oral streptococci have evolved diverse strategies to survive and thrive in the carbohydrate-rich oral cavity. In this review, we discuss 2 important biological processes mediated by 2 distinct groups of glycosyltransferases in oral streptococci that are important for bacterial colonization and virulence. The first process is the glycosylation of highly conserved serine-rich repeat adhesins by a series of glycosyltransferases. Using Streptococcus parasanguinis as a model, we highlight new features of several glycosyltransferases that sequentially modify the serine-rich glycoprotein Fap1. Distinct features of a novel glycosyltransferase fold from a domain of unknown function 1792 are contrasted with common properties of canonical glycosyltransferases. The second biological process we cover is involved in building sticky glucan matrix to establish cariogenic biofilms by an important opportunistic pathogen Streptococcus mutans through the action of a family of 3 glucosyltransferases. We focus on discussing the structural feature of this family as a glycoside hydrolase family of enzymes. While the 2 processes are distinct, they all produce carbohydrate-coated biomolecules, which enable bacteria to stick better in the complex oral microbiome. Understanding the making of the sweet modification presents a unique opportunity to develop novel antiadhesion and antibiofilm strategies to fight infections by oral streptococci and beyond. PMID:25755271

Anatomy and clinical significance of the uncinate process and uncovertebral joint: A comprehensive review.

PubMed

Hartman, Jeffrey

2014-04-01

The uncinate process and its associated uncovertebral articulation are features unique to the cervical spine. This review examines the morphology of these unique structures with particular emphasis on the regional anatomy, development and clinical significance. Five electronic databases were utilized in the literature search and additional relevant citations were retrieved from the references. A total of 74 citations were included for review. This literature review found that the uncinate processes and uncovertebral articulations are rudimentary at birth and develop and evolve with age. With degeneration they become clinically apparent with compression of related structures; most importantly affecting the spinal nerve root and vertebral artery. The articulations have also been found to precipitate torticollis when edematous and be acutely damaged in severe head and neck injuries. The uncinate processes are also important in providing stability and guiding the motion of the cervical spine. This review is intended to re-examine an often overlooked region of the cervical spine as not only an interesting anatomical feature but also a clinically relevant one. Copyright © 2014 Wiley Periodicals, Inc.

Hierarchical Feedback Modules and Reaction Hubs in Cell Signaling Networks

PubMed Central

Xu, Jianfeng; Lan, Yueheng

2015-01-01

Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks. PMID:25951347

Foot Structure in Boys with Down Syndrome

PubMed Central

Nowak, Krzysztof; Omorczyk, Jarosław; Ambroży, Tadeusz; Nosiadek, Leszek

2017-01-01

Introduction and Aim Down syndrome (DS) is associated with numerous developmental abnormalities, some of which cause dysfunctions of the posture and the locomotor system. The analysis of selected features of the foot structure in boys with DS versus their peers without developmental disorders is done. Materials and Methods The podoscopic examination was performed on 30 boys with DS aged 14-15 years. A control group consisted of 30 age- and gender-matched peers without DS. Results The feet of boys with DS are flatter compared to their healthy peers. The hallux valgus angle is not the most important feature differentiating the shape of the foot in the boys with DS and their healthy peers. In terms of the V toe setting, healthy boys had poorer results. Conclusions Specialized therapeutic treatment in individuals with DS should involve exercises to increase the muscle strength around the foot joints, enhancing the stabilization in the joints and proprioception. Introducing orthotics and proper footwear is also important. It is also necessary to monitor the state of the foot in order to modify undertaken therapies. PMID:28904967

Tuberculosis: finding a new potential antimycobacterium derivative in a aldehyde-arylhydrazone-oxoquinoline series.

PubMed

da C Santos, Fernanda; Castro, Helena C; Lourenço, Maria Cristina S; Abreu, Paula A; Batalha, Pedro N; Cunha, Anna C; Carvalho, Guilherme S L; Rodrigues, Carlos R; Medeiros, Cid A; Souza, Simone D; Ferreira, Vitor F; de Souza, Maria C B V

2012-10-01

Tuberculosis (TB) is a contagious disease caused by Mycobacterium tuberculosis, which remains a serious public health problem. The emergence of resistant bacterial strains has continuously increased and new treatment options are currently in need. In this work, we identified a new potential aldehyde-arylhydrazone-oxoquinoline derivative (4e) with interesting chemical structural features that may be important for designing new anti-TB agents. This 1-ethyl-N'-[(1E)-(5-nitro-2-furyl)methylene]-4-oxo-1,4-dihydroquinoline-3-carbohydrazide (4e) presented an in vitro active profile against M. tuberculosis H37Rv strain (minimum inhibitory concentration, MIC = 6.25 μg/mL) better than other acylhydrazones described in the literature (MIC = 12.5 μg/mL) and close to other antitubercular agents currently on the market. The theoretical analysis showed the importance of several structural features that together with the 5-nitro-2-furyl group generated this active compound (4e). This new compound and the analysis of its molecular properties may be useful for designing new and more efficient antibacterial drugs.

Structural insights into the inactivation of CRISPR-Cas systems by diverse anti-CRISPR proteins.

PubMed

Zhu, Yuwei; Zhang, Fan; Huang, Zhiwei

2018-03-19

A molecular arms race is progressively being unveiled between prokaryotes and viruses. Prokaryotes utilize CRISPR-mediated adaptive immune systems to kill the invading phages and mobile genetic elements, and in turn, the viruses evolve diverse anti-CRISPR proteins to fight back. The structures of several anti-CRISPR proteins have now been reported, and here we discuss their structural features, with a particular emphasis on topology, to discover their similarities and differences. We summarize the CRISPR-Cas inhibition mechanisms of these anti-CRISPR proteins in their structural context. Considering anti-CRISPRs in this way will provide important clues for studying their origin and evolution.

Hamiltonian structure and Darboux theorem for families of generalized Lotka-Volterra systems

NASA Astrophysics Data System (ADS)

Hernández-Bermejo, Benito; Fairén, Víctor

1998-11-01

This work is devoted to the establishment of a Poisson structure for a format of equations known as generalized Lotka-Volterra systems. These equations, which include the classical Lotka-Volterra systems as a particular case, have been deeply studied in the literature. They have been shown to constitute a whole hierarchy of systems, the characterization of which is made in the context of simple algebra. Our main result is to show that this algebraic structure is completely translatable into the Poisson domain. Important Poisson structures features, such as the symplectic foliation and the Darboux canonical representation, rise as a result of rather simple matrix manipulations.

Biological features of hepatitis B virus isolates from patients based on full-length genomic analysis.

PubMed

Wen, Yu-Mei; Wang, Yong-Xiang

2009-01-01

The mechanisms for HBV persistence and the pathogenesis of chronic HB have been shown mainly due to defects in host immune responses. However, HBV isolates with different biological features may also contribute to different clinical outcomes and epidemiological implications in viral hepatitis B (HB). This review presents interesting biological features of HBV isolates based on the structural and functional analysis of full-length HBV isolates from various patients. Among isolates from children after failure of HB vaccination, 129L mutant at the 'a' determinant was found with normal binding efficiency to anti-HBs, but with reduced immunogenicity, which could initiate persistent HBV infections. Isolates from fulminant hepatitis (FH) B patients were not all highly replicative, but differences in capacities of anti-HBs induction could be involved in the pathogenesis of FH. The high replicative competency of isolates from hepatocellular carcinoma (HCC) patients could result in enhanced immune-mediated cytopathic effects against HBV viral proteins, and increased transactivating activity by the X protein. The mechanism of a double-spliced variant in enhancing replication of the wild-type virus is presented. The importance of integrating structural and functional analysis to reveal biological features of HBV isolates in viral pathogenesis is discussed.

Ghost features in Doppler-broadened spectra of rovibrational transitions in trapped HD+ ions

NASA Astrophysics Data System (ADS)

Patra, Sayan; Koelemeij, J. C. J.

2017-02-01

Doppler broadening plays an important role in laser rovibrational spectroscopy of trapped deuterated molecular hydrogen ions (HD+), even at the millikelvin temperatures achieved through sympathetic cooling by laser-cooled beryllium ions. Recently, Biesheuvel et al. (2016) presented a theoretical lineshape model for such transitions which not only considers linestrengths and Doppler broadening, but also the finite sample size and population redistribution by blackbody radiation, which are important in view of the long storage and probe times achievable in ion traps. Here, we employ the rate equation model developed by Biesheuvel et al. to theoretically study the Doppler-broadened hyperfine structure of the (v, L) : (0, 3) → (4, 2) rovibrational transition in HD+ at 1442 nm. We observe prominent yet hitherto unrecognized ghost features in the simulated spectrum, whose positions depend on the Doppler width, transition rates, and saturation levels of the hyperfine components addressed by the laser. We explain the origin and behavior of such features, and we provide a simple quantitative guideline to assess whether ghost features may appear. As such ghost features may be common to saturated Doppler-broadened spectra of rotational and vibrational transitions in trapped ions composed of partly overlapping lines, our work illustrates the necessity to use lineshape models that take into account all the relevant physics.

RiboSketch: Versatile Visualization of Multi-stranded RNA and DNA Secondary Structure.

PubMed

Lu, Jacob S; Bindewald, Eckart; Kasprzak, Wojciech; Shapiro, Bruce A

2018-06-15

Creating clear, visually pleasing 2D depictions of RNA and DNA strands and their interactions is important to facilitate and communicate insights related to nucleic acid structure. Here we present RiboSketch, a secondary structure image production application that enables the visualization of multistranded structures via layout algorithms, comprehensive editing capabilities, and a multitude of simulation modes. These interactive features allow RiboSketch to create publication quality diagrams for structures with a wide range of composition, size, and complexity. The program may be run in any web browser without the need for installation, or as a standalone Java application. https://binkley2.ncifcrf.gov/users/bindewae/ribosketch_web.

Analysis of Physicochemical and Structural Properties Determining HIV-1 Coreceptor Usage

PubMed Central

Bozek, Katarzyna; Lengauer, Thomas; Sierra, Saleta; Kaiser, Rolf; Domingues, Francisco S.

2013-01-01

The relationship of HIV tropism with disease progression and the recent development of CCR5-blocking drugs underscore the importance of monitoring virus coreceptor usage. As an alternative to costly phenotypic assays, computational methods aim at predicting virus tropism based on the sequence and structure of the V3 loop of the virus gp120 protein. Here we present a numerical descriptor of the V3 loop encoding its physicochemical and structural properties. The descriptor allows for structure-based prediction of HIV tropism and identification of properties of the V3 loop that are crucial for coreceptor usage. Use of the proposed descriptor for prediction results in a statistically significant improvement over the prediction based solely on V3 sequence with 3 percentage points improvement in AUC and 7 percentage points in sensitivity at the specificity of the 11/25 rule (95%). We additionally assessed the predictive power of the new method on clinically derived ‘bulk’ sequence data and obtained a statistically significant improvement in AUC of 3 percentage points over sequence-based prediction. Furthermore, we demonstrated the capacity of our method to predict therapy outcome by applying it to 53 samples from patients undergoing Maraviroc therapy. The analysis of structural features of the loop informative of tropism indicates the importance of two loop regions and their physicochemical properties. The regions are located on opposite strands of the loop stem and the respective features are predominantly charge-, hydrophobicity- and structure-related. These regions are in close proximity in the bound conformation of the loop potentially forming a site determinant for the coreceptor binding. The method is available via server under http://structure.bioinf.mpi-inf.mpg.de/. PMID:23555214

SMOQ: a tool for predicting the absolute residue-specific quality of a single protein model with support vector machines

PubMed Central

2014-01-01

Background It is important to predict the quality of a protein structural model before its native structure is known. The method that can predict the absolute local quality of individual residues in a single protein model is rare, yet particularly needed for using, ranking and refining protein models. Results We developed a machine learning tool (SMOQ) that can predict the distance deviation of each residue in a single protein model. SMOQ uses support vector machines (SVM) with protein sequence and structural features (i.e. basic feature set), including amino acid sequence, secondary structures, solvent accessibilities, and residue-residue contacts to make predictions. We also trained a SVM model with two new additional features (profiles and SOV scores) on 20 CASP8 targets and found that including them can only improve the performance when real deviations between native and model are higher than 5Å. The SMOQ tool finally released uses the basic feature set trained on 85 CASP8 targets. Moreover, SMOQ implemented a way to convert predicted local quality scores into a global quality score. SMOQ was tested on the 84 CASP9 single-domain targets. The average difference between the residue-specific distance deviation predicted by our method and the actual distance deviation on the test data is 2.637Å. The global quality prediction accuracy of the tool is comparable to other good tools on the same benchmark. Conclusion SMOQ is a useful tool for protein single model quality assessment. Its source code and executable are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/. PMID:24776231

SMOQ: a tool for predicting the absolute residue-specific quality of a single protein model with support vector machines.

PubMed

Cao, Renzhi; Wang, Zheng; Wang, Yiheng; Cheng, Jianlin

2014-04-28

It is important to predict the quality of a protein structural model before its native structure is known. The method that can predict the absolute local quality of individual residues in a single protein model is rare, yet particularly needed for using, ranking and refining protein models. We developed a machine learning tool (SMOQ) that can predict the distance deviation of each residue in a single protein model. SMOQ uses support vector machines (SVM) with protein sequence and structural features (i.e. basic feature set), including amino acid sequence, secondary structures, solvent accessibilities, and residue-residue contacts to make predictions. We also trained a SVM model with two new additional features (profiles and SOV scores) on 20 CASP8 targets and found that including them can only improve the performance when real deviations between native and model are higher than 5Å. The SMOQ tool finally released uses the basic feature set trained on 85 CASP8 targets. Moreover, SMOQ implemented a way to convert predicted local quality scores into a global quality score. SMOQ was tested on the 84 CASP9 single-domain targets. The average difference between the residue-specific distance deviation predicted by our method and the actual distance deviation on the test data is 2.637Å. The global quality prediction accuracy of the tool is comparable to other good tools on the same benchmark. SMOQ is a useful tool for protein single model quality assessment. Its source code and executable are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/.

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.

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

PubMed Central

2012-01-01

Background Nucleosome distribution along chromatin dictates genomic DNA accessibility and thus profoundly influences gene expression. However, the underlying mechanism of nucleosome formation remains elusive. Here, taking a structural perspective, we systematically explored nucleosome formation potential of genomic sequences and the effect on chromatin organization and gene expression in S. cerevisiae. Results We analyzed twelve structural features related to flexibility, curvature and energy of DNA sequences. The results showed that some structural features such as DNA denaturation, DNA-bending stiffness, Stacking energy, Z-DNA, Propeller twist and free energy, were highly correlated with in vitro and in vivo nucleosome occupancy. Specifically, they can be classified into two classes, one positively and the other negatively correlated with nucleosome occupancy. These two kinds of structural features facilitated nucleosome binding in centromere regions and repressed nucleosome formation in the promoter regions of protein-coding genes to mediate transcriptional regulation. Based on these analyses, we integrated all twelve structural features in a model to predict more accurately nucleosome occupancy in vivo than the existing methods that mainly depend on sequence compositional features. Furthermore, we developed a novel approach, named DLaNe, that located nucleosomes by detecting peaks of structural profiles, and built a meta predictor to integrate information from different structural features. As a comparison, we also constructed a hidden Markov model (HMM) to locate nucleosomes based on the profiles of these structural features. The result showed that the meta DLaNe and HMM-based method performed better than the existing methods, demonstrating the power of these structural features in predicting nucleosome positions. Conclusions Our analysis revealed that DNA structures significantly contribute to nucleosome organization and influence chromatin structure and gene expression regulation. The results indicated that our proposed methods are effective in predicting nucleosome occupancy and positions and that these structural features are highly predictive of nucleosome organization. The implementation of our DLaNe method based on structural features is available online. PMID:22449207

A PLANETARY LENSING FEATURE IN CAUSTIC-CROSSING HIGH-MAGNIFICATION MICROLENSING EVENTS

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

Chung, Sun-Ju; Hwang, Kyu-Ha; Ryu, Yoon-Hyun

Current microlensing follow-up observations focus on high-magnification events because of the high efficiency of planet detection. However, central perturbations of high-magnification events caused by a planet can also be produced by a very close or a very wide binary companion, and the two kinds of central perturbations are not generally distinguished without time consuming detailed modeling (a planet-binary degeneracy). Hence, it is important to resolve the planet-binary degeneracy that occurs in high-magnification events. In this paper, we investigate caustic-crossing high-magnification events caused by a planet and a wide binary companion. From this investigation, we find that because of the differentmore » magnification excess patterns inside the central caustics induced by the planet and the binary companion, the light curves of the caustic-crossing planetary-lensing events exhibit a feature that is discriminated from those of the caustic-crossing binary-lensing events, and the feature can be used to immediately distinguish between the planetary and binary companions. The planetary-lensing feature appears in the interpeak region between the two peaks of the caustic-crossings. The structure of the interpeak region for the planetary-lensing events is smooth and convex or boxy, whereas the structure for the binary-lensing events is smooth and concave. We also investigate the effect of a finite background source star on the planetary-lensing feature in the caustic-crossing high-magnification events. From this, we find that the convex-shaped interpeak structure appears in a certain range that changes with the mass ratio of the planet to the planet-hosting star.« less

Detailed Mapping of the Alu Volcano, Ethiopia

NASA Astrophysics Data System (ADS)

Agrain, Guillaume; Buso, Roxane; Carlier, Jean; van Wyk de Vries, Benjamin

2017-04-01

The Alu volcano in the Danakil Depression is interpreted as a forced-fold related uplift, related to progressive intrusions of sills, or similar tabular intrusions. Alu is in a very isolated and difficult to access area, but Google Earth provides high resolution images that can be used for mapping the structure and volcanic features. We use the imagery to map in as much detail as possible all the morphological features of Alu, which we separate into primary volcanic features and secondary structural features. The mapping has been undertaken by a group undergraduates, graduates and researchers. The group has checked and validated the interpretation of each feature mapped. The data set is available as a kmz, and has been imported into QGIS. The detailed mapping reveals a complex history of multiple lava fields and fissure eruptions, some which pre-date uplift, while others have occurred during uplift, but are subsequently deformed. Similarly, there are cross-cutting structures, and we are able to set up a chronology of events. This shows that uplift grew in an area which was already covered by lavas, that some lava has been probably erupted from Alu's flanks, while most eruptions have been from around the base of Alu. Early in the deformation, thrust faults developed on the lower flanks, similar to those described near the Grosmanaux uplift (van Wyk de Vries et al 2014). These are cut by the larger faults, and by minor fissures. The mapping provides an accessible way of preparing for dedicated fieldwork in preparation of an eventual field expedition to Alu, while extracting the most from remote sensing data.

PredPPCrys: Accurate Prediction of Sequence Cloning, Protein Production, Purification and Crystallization Propensity from Protein Sequences Using Multi-Step Heterogeneous Feature Fusion and Selection

PubMed Central

Wang, Huilin; Wang, Mingjun; Tan, Hao; Li, Yuan; Zhang, Ziding; Song, Jiangning

2014-01-01

X-ray crystallography is the primary approach to solve the three-dimensional structure of a protein. However, a major bottleneck of this method is the failure of multi-step experimental procedures to yield diffraction-quality crystals, including sequence cloning, protein material production, purification, crystallization and ultimately, structural determination. Accordingly, prediction of the propensity of a protein to successfully undergo these experimental procedures based on the protein sequence may help narrow down laborious experimental efforts and facilitate target selection. A number of bioinformatics methods based on protein sequence information have been developed for this purpose. However, our knowledge on the important determinants of propensity for a protein sequence to produce high diffraction-quality crystals remains largely incomplete. In practice, most of the existing methods display poorer performance when evaluated on larger and updated datasets. To address this problem, we constructed an up-to-date dataset as the benchmark, and subsequently developed a new approach termed ‘PredPPCrys’ using the support vector machine (SVM). Using a comprehensive set of multifaceted sequence-derived features in combination with a novel multi-step feature selection strategy, we identified and characterized the relative importance and contribution of each feature type to the prediction performance of five individual experimental steps required for successful crystallization. The resulting optimal candidate features were used as inputs to build the first-level SVM predictor (PredPPCrys I). Next, prediction outputs of PredPPCrys I were used as the input to build second-level SVM classifiers (PredPPCrys II), which led to significantly enhanced prediction performance. Benchmarking experiments indicated that our PredPPCrys method outperforms most existing procedures on both up-to-date and previous datasets. In addition, the predicted crystallization targets of currently non-crystallizable proteins were provided as compendium data, which are anticipated to facilitate target selection and design for the worldwide structural genomics consortium. PredPPCrys is freely available at http://www.structbioinfor.org/PredPPCrys. PMID:25148528

Integrated feature extraction and selection for neuroimage classification

NASA Astrophysics Data System (ADS)

Fan, Yong; Shen, Dinggang

2009-02-01

Feature extraction and selection are of great importance in neuroimage classification for identifying informative features and reducing feature dimensionality, which are generally implemented as two separate steps. This paper presents an integrated feature extraction and selection algorithm with two iterative steps: constrained subspace learning based feature extraction and support vector machine (SVM) based feature selection. The subspace learning based feature extraction focuses on the brain regions with higher possibility of being affected by the disease under study, while the possibility of brain regions being affected by disease is estimated by the SVM based feature selection, in conjunction with SVM classification. This algorithm can not only take into account the inter-correlation among different brain regions, but also overcome the limitation of traditional subspace learning based feature extraction methods. To achieve robust performance and optimal selection of parameters involved in feature extraction, selection, and classification, a bootstrapping strategy is used to generate multiple versions of training and testing sets for parameter optimization, according to the classification performance measured by the area under the ROC (receiver operating characteristic) curve. The integrated feature extraction and selection method is applied to a structural MR image based Alzheimer's disease (AD) study with 98 non-demented and 100 demented subjects. Cross-validation results indicate that the proposed algorithm can improve performance of the traditional subspace learning based classification.

Metal Transport across Biomembranes: Emerging Models for a Distinct Chemistry*

PubMed Central

Argüello, José M.; Raimunda, Daniel; González-Guerrero, Manuel

2012-01-01

Transition metals are essential components of important biomolecules, and their homeostasis is central to many life processes. Transmembrane transporters are key elements controlling the distribution of metals in various compartments. However, due to their chemical properties, transition elements require transporters with different structural-functional characteristics from those of alkali and alkali earth ions. Emerging structural information and functional studies have revealed distinctive features of metal transport. Among these are the relevance of multifaceted events involving metal transfer among participating proteins, the importance of coordination geometry at transmembrane transport sites, and the presence of the largely irreversible steps associated with vectorial transport. Here, we discuss how these characteristics shape novel transition metal ion transport models. PMID:22389499

Metal transport across biomembranes: emerging models for a distinct chemistry.

PubMed

Argüello, José M; Raimunda, Daniel; González-Guerrero, Manuel

2012-04-20

Transition metals are essential components of important biomolecules, and their homeostasis is central to many life processes. Transmembrane transporters are key elements controlling the distribution of metals in various compartments. However, due to their chemical properties, transition elements require transporters with different structural-functional characteristics from those of alkali and alkali earth ions. Emerging structural information and functional studies have revealed distinctive features of metal transport. Among these are the relevance of multifaceted events involving metal transfer among participating proteins, the importance of coordination geometry at transmembrane transport sites, and the presence of the largely irreversible steps associated with vectorial transport. Here, we discuss how these characteristics shape novel transition metal ion transport models.

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.

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.

Line group techniques in description of the structural phase transitions in some superconductors

NASA Technical Reports Server (NTRS)

Meszaros, CS.; Balint, A.; Bankuti, J.

1995-01-01

The main features of the theory of line groups, and their irreducible representations are briefly discussed, as well as the most important applications of them. A new approach in the general symmetry analysis of the modulated systems is presented. It is shown, that the line group formalism could be a very effective tool in the examination of the structural phase transitions in High Temperature SUperconductors. As an example, the material YBa2Cu3O(7-x) is discussed briefly.

First-principles molecular dynamics simulation study on electrolytes for use in redox flow battery

NASA Astrophysics Data System (ADS)

Choe, Yoong-Kee; Tsuchida, Eiji; Tokuda, Kazuya; Ootsuka, Jun; Saito, Yoshihiro; Masuno, Atsunobu; Inoue, Hiroyuki

2017-11-01

Results of first-principles molecular dynamics simulations carried out to investigate structural aspects of electrolytes for use in a redox flow battery are reported. The electrolytes studied here are aqueous sulfuric acid solutions where its property is of importance for dissolving redox couples in redox flow battery. The simulation results indicate that structural features of the acid solutions depend on the concentration of sulfuric acid. Such dependency arises from increase of proton dissociation from sulfuric acid.

A protein coevolution method uncovers critical features of the Hepatitis C Virus fusion mechanism

PubMed Central

Douam, Florian; Mancip, Jimmy; Mailly, Laurent; Montserret, Roland; Ding, Qiang; Verhoeyen, Els; Baumert, Thomas F.; Ploss, Alexander; Carbone, Alessandra

2018-01-01

Amino-acid coevolution can be referred to mutational compensatory patterns preserving the function of a protein. Viral envelope glycoproteins, which mediate entry of enveloped viruses into their host cells, are shaped by coevolution signals that confer to viruses the plasticity to evade neutralizing antibodies without altering viral entry mechanisms. The functions and structures of the two envelope glycoproteins of the Hepatitis C Virus (HCV), E1 and E2, are poorly described. Especially, how these two proteins mediate the HCV fusion process between the viral and the cell membrane remains elusive. Here, as a proof of concept, we aimed to take advantage of an original coevolution method recently developed to shed light on the HCV fusion mechanism. When first applied to the well-characterized Dengue Virus (DENV) envelope glycoproteins, coevolution analysis was able to predict important structural features and rearrangements of these viral protein complexes. When applied to HCV E1E2, computational coevolution analysis predicted that E1 and E2 refold interdependently during fusion through rearrangements of the E2 Back Layer (BL). Consistently, a soluble BL-derived polypeptide inhibited HCV infection of hepatoma cell lines, primary human hepatocytes and humanized liver mice. We showed that this polypeptide specifically inhibited HCV fusogenic rearrangements, hence supporting the critical role of this domain during HCV fusion. By combining coevolution analysis and in vitro assays, we also uncovered functionally-significant coevolving signals between E1 and E2 BL/Stem regions that govern HCV fusion, demonstrating the accuracy of our coevolution predictions. Altogether, our work shed light on important structural features of the HCV fusion mechanism and contributes to advance our functional understanding of this process. This study also provides an important proof of concept that coevolution can be employed to explore viral protein mediated-processes, and can guide the development of innovative translational strategies against challenging human-tropic viruses. PMID:29505618

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

PubMed

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

2004-01-01

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

Effects of landscape features on waterbird use of rice fields

USGS Publications Warehouse

King, S.; Elphick, C.S.; Guadagnin, D.; Taft, O.; Amano, T.

2010-01-01

Literature is reviewed to determine the effects of landscape features on waterbird use of fields in regions where rice (Oryza sativa) is grown. Rice-growing landscapes often consist of diverse land uses and land cover, including rice fields, irrigation ditches, other agricultural fields, grasslands, forests and natural wetlands. Numerous studies indicate that local management practices, such as water depth and timing of flooding and drawdown, can strongly influence waterbird use of a given rice field. However, the effects of size and distribution of rice fields and associated habitats at a landscape scale have received less attention. Even fewer studies have focused on local and landscape effects simultaneously. Habitat connectivity, area of rice, distance to natural wetlands, and presence and distance to unsuitable habitat can be important parameters influencing bird use of rice fields. However, responses to a given landscape vary with landscape structure, scale of analysis, among taxa and within taxa among seasons. A lack of multi-scale studies, particularly those extending beyond simple presence and abundance of a given species, and a lack of direct tests comparing the relative importance of landscape features with in-field management activities limits understanding of the importance of landscape in these systems and hampers waterbird conservation and management.

A possible radiation-resistant solar cell geometry using superlattices

NASA Technical Reports Server (NTRS)

Goradia, C.; Clark, R.; Brinker, D.

1985-01-01

A solar cell structure is proposed which uses a GaAs nipi doping superlattice. An important feature of this structure is that photogenerated minority carriers are very quickly collected in a time shorter than bulk lifetime in the fairly heavily doped n and p layers and these carriers are then transported parallel to the superlattice layers to selective ohmic contacts. Assuming that these already-separated carriers have very long recombination lifetimes, due to their across an indirect bandgap in real space, it is argued that the proposed structure may exhibit superior radiation tolerance along with reasonably high beginning-of-life efficiency.

A continuous scale-space method for the automated placement of spot heights on maps

NASA Astrophysics Data System (ADS)

Rocca, Luigi; Jenny, Bernhard; Puppo, Enrico

2017-12-01

Spot heights and soundings explicitly indicate terrain elevation on cartographic maps. Cartographers have developed design principles for the manual selection, placement, labeling, and generalization of spot height locations, but these processes are work-intensive and expensive. Finding an algorithmic criterion that matches the cartographers' judgment in ranking the significance of features on a terrain is a difficult endeavor. This article proposes a method for the automated selection of spot heights locations representing natural features such as peaks, saddles and depressions. A lifespan of critical points in a continuous scale-space model is employed as the main measure of the importance of features, and an algorithm and a data structure for its computation are described. We also introduce a method for the comparison of algorithmically computed spot height locations with manually produced reference compilations. The new method is compared with two known techniques from the literature. Results show spot height locations that are closer to reference spot heights produced manually by swisstopo cartographers, compared to previous techniques. The introduced method can be applied to elevation models for the creation of topographic and bathymetric maps. It also ranks the importance of extracted spot height locations, which allows for a variation in the size of symbols and labels according to the significance of represented features. The importance ranking could also be useful for adjusting spot height density of zoomable maps in real time.

Structural architecture of prothrombin in solution revealed by single molecule spectroscopy

DOE PAGES

Pozzi, Nicola; Bystranowska, Dominika; Zuo, Xiaobing; ...

2016-07-19

The coagulation factor prothrombin has a complex spatial organization of its modular assembly that comprises the N-terminal Gla domain, kringle-1, kringle-2, and the C-terminal protease domain connected by three intervening linkers. Here we use single molecule Förster resonance energy transfer to access the conformational landscape of prothrombin in solution and uncover structural features of functional significance that extend recent x-ray crystallographic analysis. Prothrombin exists in equilibrium between two alternative conformations, open and closed. The closed conformation predominates (70%) and features an unanticipated intramolecular collapse of Tyr 93 in kringle-1 onto Trp 547 in the protease domain that obliterates access tomore » the active site and protects the zymogen from autoproteolytic conversion to thrombin. The open conformation (30%) is more susceptible to chymotrypsin digestion and autoactivation, and features a shape consistent with recent x-ray crystal structures. Small angle x-ray scattering measurements of prothrombin wild type stabilized 70% in the closed conformation and of the mutant Y93A stabilized 80% in the open conformation directly document two envelopes that differ 50 Å in length. These findings reveal important new details on the conformational plasticity of prothrombin in solution and the drastic structural difference between its alternative conformations. Prothrombin uses the intramolecular collapse of kringle-1 onto the active site in the closed form to prevent autoactivation. As a result, the open-closed equilibrium also defines a new structural framework for the mechanism of activation of prothrombin by prothrombinase.« less

Sampling and Visualizing Creases with Scale-Space Particles

PubMed Central

Kindlmann, Gordon L.; Estépar, Raúl San José; Smith, Stephen M.; Westin, Carl-Fredrik

2010-01-01

Particle systems have gained importance as a methodology for sampling implicit surfaces and segmented objects to improve mesh generation and shape analysis. We propose that particle systems have a significantly more general role in sampling structure from unsegmented data. We describe a particle system that computes samplings of crease features (i.e. ridges and valleys, as lines or surfaces) that effectively represent many anatomical structures in scanned medical data. Because structure naturally exists at a range of sizes relative to the image resolution, computer vision has developed the theory of scale-space, which considers an n-D image as an (n + 1)-D stack of images at different blurring levels. Our scale-space particles move through continuous four-dimensional scale-space according to spatial constraints imposed by the crease features, a particle-image energy that draws particles towards scales of maximal feature strength, and an inter-particle energy that controls sampling density in space and scale. To make scale-space practical for large three-dimensional data, we present a spline-based interpolation across scale from a small number of pre-computed blurrings at optimally selected scales. The configuration of the particle system is visualized with tensor glyphs that display information about the local Hessian of the image, and the scale of the particle. We use scale-space particles to sample the complex three-dimensional branching structure of airways in lung CT, and the major white matter structures in brain DTI. PMID:19834216

Electron Microscopy and Analytical X-ray Characterization of Compositional and Nanoscale Structural Changes in Fossil Bone

NASA Astrophysics Data System (ADS)

Boatman, Elizabeth Marie

The nanoscale structure of compact bone contains several features that are direct indicators of bulk tissue mechanical properties. Fossil bone tissues represent unique opportunities to understand the compact bone structure/property relationships from a deep time perspective, offering a possible array of new insights into bone diseases, biomimicry of composite materials, and basic knowledge of bioapatite composition and nanoscale bone structure. To date, most work with fossil bone has employed microscale techniques and has counter-indicated the survival of bioapatite and other nanoscale structural features. The obvious disconnect between the use of microscale techniques and the discernment of nanoscale structure has prompted this work. The goal of this study was to characterize the nanoscale constituents of fossil compact bone by applying a suite of diffraction, microscopy, and spectrometry techniques, representing the highest levels of spatial and energy resolution available today, and capable of complementary structural and compositional characterization from the micro- to the nanoscale. Fossil dinosaur and crocodile long bone specimens, as well as modern ratite and crocodile femurs, were acquired from the UC Museum of Paleontology. Preserved physiological features of significance were documented with scanning electron microscopy back-scattered imaging. Electron microprobe wavelength-dispersive X-ray spectroscopy (WDS) revealed fossil bone compositions enriched in fluorine with a complementary loss of oxygen. X-ray diffraction analyses demonstrated that all specimens were composed of apatite. Transmission electron microscopy (TEM) imaging revealed preserved nanocrystallinity in the fossil bones and electron diffraction studies further identified these nanocrystallites as apatite. Tomographic analyses of nanoscale elements imaged by TEM and small angle X-ray scattering were performed, with the results of each analysis further indicating that nanoscale structure is highly conserved in these four fossil specimens. Finally, the results of this study indicate that bioapatite can be preserved in even the most ancient vertebrate specimens, further supporting the idea that fossilization is a preservational process. This work also underlines the importance of using appropriately selected characterization and analytical techniques for the study of fossil bone, especially from the perspective of spatial resolution and the scale of the bone structural features in question.

Structural insights into xenobiotic and inhibitor binding to human aldehyde oxidase.

PubMed

Coelho, Catarina; Foti, Alessandro; Hartmann, Tobias; Santos-Silva, Teresa; Leimkühler, Silke; Romão, Maria João

2015-10-01

Aldehyde oxidase (AOX) is a xanthine oxidase (XO)-related enzyme with emerging importance due to its role in the metabolism of drugs and xenobiotics. We report the first crystal structures of human AOX1, substrate free (2.6-Å resolution) and in complex with the substrate phthalazine and the inhibitor thioridazine (2.7-Å resolution). Analysis of the protein active site combined with steady-state kinetic studies highlight the unique features, including binding and substrate orientation at the active site, that characterize human AOX1 as an important drug-metabolizing enzyme. Structural analysis of the complex with the noncompetitive inhibitor thioridazine revealed a new, unexpected and fully occupied inhibitor-binding site that is structurally conserved among mammalian AOXs and XO. The new structural insights into the catalytic and inhibition mechanisms of human AOX that we now report will be of great value for the rational analysis of clinical drug interactions involving inhibition of AOX1 and for the prediction and design of AOX-stable putative drugs.

Novel real-time tumor-contouring method using deep learning to prevent mistracking in X-ray fluoroscopy.

PubMed

Terunuma, Toshiyuki; Tokui, Aoi; Sakae, Takeji

2018-03-01

Robustness to obstacles is the most important factor necessary to achieve accurate tumor tracking without fiducial markers. Some high-density structures, such as bone, are enhanced on X-ray fluoroscopic images, which cause tumor mistracking. Tumor tracking should be performed by controlling "importance recognition": the understanding that soft-tissue is an important tracking feature and bone structure is unimportant. We propose a new real-time tumor-contouring method that uses deep learning with importance recognition control. The novelty of the proposed method is the combination of the devised random overlay method and supervised deep learning to induce the recognition of structures in tumor contouring as important or unimportant. This method can be used for tumor contouring because it uses deep learning to perform image segmentation. Our results from a simulated fluoroscopy model showed accurate tracking of a low-visibility tumor with an error of approximately 1 mm, even if enhanced bone structure acted as an obstacle. A high similarity of approximately 0.95 on the Jaccard index was observed between the segmented and ground truth tumor regions. A short processing time of 25 ms was achieved. The results of this simulated fluoroscopy model support the feasibility of robust real-time tumor contouring with fluoroscopy. Further studies using clinical fluoroscopy are highly anticipated.

Assessment of chronic post-surgical pain after knee replacement: development of a core outcome set.

PubMed

Wylde, V; MacKichan, F; Bruce, J; Gooberman-Hill, R

2015-05-01

Approximately 20% of patients experience chronic post-surgical pain (CPSP) after total knee replacement (TKR). There is scope to improve assessment of CPSP after TKR, and this study aimed to develop a core outcome set. Eighty patients and 43 clinicians were recruited into a three-round modified Delphi study. In Round 1, participants were presented with 56 pain features identified from a systematic review, structured interviews with patients and focus groups with clinicians. Participants assigned importance ratings, using a 1-9 scale, to individual pain features; those features rated as most important were retained in subsequent rounds. Consensus that a pain feature should be included in the core outcome set was defined as the feature having a rating of 7-9 by ≥70% of both panels (patients and clinicians) and 1-3 by ≤15% of both panels or rated as 7-9 by ≥90% of one panel. Round 1 was completed by 71 patients and 39 clinicians, and Round 3 by 62 patients and 33 clinicians. The final consensus was that 33 pain features were important. These were grouped into an 8-item core outcome set comprising: pain intensity, pain interference with daily living, pain and physical functioning, temporal aspects of pain, pain description, emotional aspects of pain, use of pain medication, and improvement and satisfaction with pain relief. This core outcome set serves to guide assessment of CPSP after TKR. Consistency in assessment can promote standardized reporting and facilitate comparability between studies that address a common but understudied type of CPSP. © 2014 The Authors. European Journal of Pain published by John Wiley & Sons Ltd on behalf of European Pain Federation - EFIC®.

Structural Distortions under pressure and doping in superconducting BaFe2As2

NASA Astrophysics Data System (ADS)

Kimber, Simon

2010-03-01

The discovery of a new family of high-TC materials, the iron arsenides, has led to a resurgence of interest in superconductivity. Several important traits of these materials are now apparent: for example, layers of iron tetrahedrally coordinated by arsenic are crucial structural ingredients. The structure and properties of chemically substituted samples are known to be intimately linked; however, until recently (1), remarkably little was known about this relationship when high pressure is used to induce superconductivity in undoped compounds. Here we show that the key structural features in BaFe2As2 show the same behaviour under pressure as found in chemically substituted samples. Using experimentally derived structural data, we show that the electronic structure evolves similarly in both cases. Our results show that, in contrast to the cuprates, structural distortions are more important than charge doping in the iron arsenides. This work was performed at the Helmholtz-Zentrum Berlin in collaboration with Ames Laboratory, Goethe-Universit"at Frankfurt, JCNS J"ulich and the Institute Laue-Langevin. (1) S.A.J. Kimber et al, Nature Materials,

Habitat, topographical, and geographical components structuring shrubsteppe bird communities

USGS Publications Warehouse

Knick, S.T.; Rotenberry, J.T.; Leu, M.

2008-01-01

Landscapes available to birds to select for breeding locations are arrayed along multiple dimensions. Identifying the primary gradients structuring shrubsteppe bird communities in the western United States is important because widespread habitat loss and alteration are shifting the environmental template on which these birds depend. We integrated field habitat surveys, GIS coverages, and bird counts from 61 Breeding Bird Survey routes located in shrubsteppe habitats across a >800 000 km2 region to determine the gradients of habitat, topography, and geography underlying bird communities. A small set of habitat features dominated the primary environmental gradients in a canonical ordination; the 13 species in the shrubsteppe bird community were closely packed along the first two axes. Using hierarchical variance partitioning, we identified habitat as the most important pure (31% explained variation) or shared component. Topography (9%) and geography (4%) were minor components but each shared a larger contribution with habitat (habitat-topography 21%; habitat-geography 22%) in explaining the organization of the bird community. In a second tier partition of habitat structure, pure composition (% land cover) was more important (45%) than configuration (patch size and edge) (7%); the two components shared 27% of the explained variation in the bird community axes. Local (9%), community (14%), and landscape (10%) levels contributed equally. Adjacent organizational levels had a larger shared contribution (local-community 26%; community-landscape 27%) than more separated local-landscape levels (21%). Extensive conversion of shrubsteppe habitats to agriculture, exotic annual grasslands, or pinyon (Pinus spp.)-juniper (Juniperus spp.) woodlands is occurring along the primary axes of habitat structure. Because the shrubsteppe bird community was organized along short gradients dominated by habitat features, relatively small shifts in their available environment will exert a strong influence on these bird populations in the absence of buffering by alternative gradients. ?? 2008 The Authors.

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.

Multimodal emotional state recognition using sequence-dependent deep hierarchical features.

PubMed

Barros, Pablo; Jirak, Doreen; Weber, Cornelius; Wermter, Stefan

2015-12-01

Emotional state recognition has become an important topic for human-robot interaction in the past years. By determining emotion expressions, robots can identify important variables of human behavior and use these to communicate in a more human-like fashion and thereby extend the interaction possibilities. Human emotions are multimodal and spontaneous, which makes them hard to be recognized by robots. Each modality has its own restrictions and constraints which, together with the non-structured behavior of spontaneous expressions, create several difficulties for the approaches present in the literature, which are based on several explicit feature extraction techniques and manual modality fusion. Our model uses a hierarchical feature representation to deal with spontaneous emotions, and learns how to integrate multiple modalities for non-verbal emotion recognition, making it suitable to be used in an HRI scenario. Our experiments show that a significant improvement of recognition accuracy is achieved when we use hierarchical features and multimodal information, and our model improves the accuracy of state-of-the-art approaches from 82.5% reported in the literature to 91.3% for a benchmark dataset on spontaneous emotion expressions. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Age structure is critical to the population dynamics and survival of honeybee colonies

PubMed Central

Betti, M. I.; Wahl, L. M.

2016-01-01

Age structure is an important feature of the division of labour within honeybee colonies, but its effects on colony dynamics have rarely been explored. We present a model of a honeybee colony that incorporates this key feature, and use this model to explore the effects of both winter and disease on the fate of the colony. The model offers a novel explanation for the frequently observed phenomenon of ‘spring dwindle’, which emerges as a natural consequence of the age-structured dynamics. Furthermore, the results indicate that a model taking age structure into account markedly affects the predicted timing and severity of disease within a bee colony. The timing of the onset of disease with respect to the changing seasons may also have a substantial impact on the fate of a honeybee colony. Finally, simulations predict that an infection may persist in a honeybee colony over several years, with effects that compound over time. Thus, the ultimate collapse of the colony may be the result of events several years past. PMID:28018627

Sensory Hair Cells: An Introduction to Structure and Physiology.

PubMed

McPherson, Duane R

2018-06-18

Sensory hair cells are specialized secondary sensory cells that mediate our senses of hearing, balance, linear acceleration, and angular acceleration (head rotation). In addition, hair cells in fish and amphibians mediate sensitivity to water movement through the lateral line system, and closely related electroreceptive cells mediate sensitivity to low-voltage electric fields in the aquatic environment of many fish species and several species of amphibian.Sensory hair cells share many structural and functional features across all vertebrate groups, while at the same time they are specialized for employment in a wide variety of sensory tasks. The complexity of hair cell structure is large, and the diversity of hair cell applications in sensory systems exceeds that seen for most, if not all, sensory cell types. The intent of this review is to summarize the more significant structural features and some of the more interesting and important physiological mechanisms that have been elucidated thus far. Outside vertebrates, hair cells are only known to exist in the coronal organ of tunicates. Electrical resonance, electromotility, and their exquisite mechanical sensitivity all contribute to the attractiveness of hair cells as a research subject.

The triple helix of collagens - an ancient protein structure that enabled animal multicellularity and tissue evolution.

PubMed

Fidler, Aaron L; Boudko, Sergei P; Rokas, Antonis; Hudson, Billy G

2018-04-09

The cellular microenvironment, characterized by an extracellular matrix (ECM), played an essential role in the transition from unicellularity to multicellularity in animals (metazoans), and in the subsequent evolution of diverse animal tissues and organs. A major ECM component are members of the collagen superfamily -comprising 28 types in vertebrates - that exist in diverse supramolecular assemblies ranging from networks to fibrils. Each assembly is characterized by a hallmark feature, a protein structure called a triple helix. A current gap in knowledge is understanding the mechanisms of how the triple helix encodes and utilizes information in building scaffolds on the outside of cells. Type IV collagen, recently revealed as the evolutionarily most ancient member of the collagen superfamily, serves as an archetype for a fresh view of fundamental structural features of a triple helix that underlie the diversity of biological activities of collagens. In this Opinion, we argue that the triple helix is a protein structure of fundamental importance in building the extracellular matrix, which enabled animal multicellularity and tissue evolution. © 2018. Published by The Company of Biologists Ltd.

The Origins of Magnetic Structure in the Corona and Wind

NASA Technical Reports Server (NTRS)

Antiochos, Spiro K.

2010-01-01

One of the most important and most puzzling features of the coronal magnetic field is that it appears to have smooth magnetic structure with little evidence for non-potentiality except at two special locations: photospheric polarity inversions lines. (non-potentiality observed as a filament channel) and coronal hole boundaries, (observed as the slow solar wind). This characteristic feature of the closed-field corona is highly unexpected given that its magnetic field is continuously tangled by photospheric motions. Although reconnection can eliminate some of the injected structure, it cannot destroy the helicity, which should build up to produce observable complexity. I propose that an inverse cascade process transports the injected helicity from the interior of closed flux regions to their boundaries inversion lines and coronal holes, creating both filament channels and the slow wind. We describe how the helicity is injected and transported and calculate the relevant rates. I argue that one process, helicity transport, can explain both the observed lack and presence of structure in the coronal magnetic field. This work has been supported by the NASA HTP, SR&T, and LWS programs.

Anomalous High-Energy Waterfall-Like Electronic Structure in 5 d Transition Metal Oxide Sr2IrO4 with a Strong Spin-Orbit Coupling

NASA Astrophysics Data System (ADS)

Liu, Yan; Yu, Li; Jia, Xiaowen; Zhao, Jianzhou; Weng, Hongming; Peng, Yingying; Chen, Chaoyu; Xie, Zhuojin; Mou, Daixiang; He, Junfeng; Liu, Xu; Feng, Ya; Yi, Hemian; Zhao, Lin; Liu, Guodong; He, Shaolong; Dong, Xiaoli; Zhang, Jun; Xu, Zuyan; Chen, Chuangtian; Cao, Gang; Dai, Xi; Fang, Zhong; Zhou, X. J.

2015-08-01

The low energy electronic structure of Sr2IrO4 has been well studied and understood in terms of an effective Jeff = 1/2 Mott insulator model. However, little work has been done in studying its high energy electronic behaviors. Here we report a new observation of the anomalous high energy electronic structure in Sr2IrO4. By taking high-resolution angle-resolved photoemission measurements on Sr2IrO4 over a wide energy range, we have revealed for the first time that the high energy electronic structures show unusual nearly-vertical bands that extend over a large energy range. Such anomalous high energy behaviors resemble the high energy waterfall features observed in the cuprate superconductors. While strong electron correlation plays an important role in producing high energy waterfall features in the cuprate superconductors, the revelation of the high energy anomalies in Sr2IrO4, which exhibits strong spin-orbit coupling and a moderate electron correlation, points to an unknown and novel route in generating exotic electronic excitations.

Anomalous High-Energy Waterfall-Like Electronic Structure in 5 d Transition Metal Oxide Sr2IrO4 with a Strong Spin-Orbit Coupling.

PubMed

Liu, Yan; Yu, Li; Jia, Xiaowen; Zhao, Jianzhou; Weng, Hongming; Peng, Yingying; Chen, Chaoyu; Xie, Zhuojin; Mou, Daixiang; He, Junfeng; Liu, Xu; Feng, Ya; Yi, Hemian; Zhao, Lin; Liu, Guodong; He, Shaolong; Dong, Xiaoli; Zhang, Jun; Xu, Zuyan; Chen, Chuangtian; Cao, Gang; Dai, Xi; Fang, Zhong; Zhou, X J

2015-08-12

The low energy electronic structure of Sr2IrO4 has been well studied and understood in terms of an effective Jeff = 1/2 Mott insulator model. However, little work has been done in studying its high energy electronic behaviors. Here we report a new observation of the anomalous high energy electronic structure in Sr2IrO4. By taking high-resolution angle-resolved photoemission measurements on Sr2IrO4 over a wide energy range, we have revealed for the first time that the high energy electronic structures show unusual nearly-vertical bands that extend over a large energy range. Such anomalous high energy behaviors resemble the high energy waterfall features observed in the cuprate superconductors. While strong electron correlation plays an important role in producing high energy waterfall features in the cuprate superconductors, the revelation of the high energy anomalies in Sr2IrO4, which exhibits strong spin-orbit coupling and a moderate electron correlation, points to an unknown and novel route in generating exotic electronic excitations.

Effect of incubation temperature on the self-assembly of regenerated silk fibroin: a study using AFM.

PubMed

Zhong, Jian; Liu, Xunwei; Wei, Daixu; Yan, Juan; Wang, Ping; Sun, Gang; He, Dannong

2015-05-01

Understanding effect of temperature on the molecular self-assembly process will be helpful to unravel the structure-function relationship of biomolecule and to provide important information for the bottom-up approach to nanotechnology. In this work, the effect of incubation temperature on the secondary structures and morphological structures of regenerated silk fibroin (RSF) was systematically studied using atomic force microscopy and Fourier Transform infrared spectroscopy. The effect of incubation temperature on RSF self-assembly was dependent on RSF concentration. For the RSF solution with relatively low concentrations (15 μg/mL and 60 μg/mL), the increase of the incubation temperature mainly accelerated the formation and aggregation of antiparallel β-sheet protofibrils and decreased the formation of random coil protofilaments/globule-like molecules. For the RSF solution with relatively high concentrations (300 μg/mL and 1.5mg/mL), the increase of the incubation temperature mainly accelerated the formation and aggregation of antiparallel β-sheet RSF features (protofibrils and globule-like features) and decreased the formation of random coil bead-like features. This work implies that the morphology and conformation of biomacromolecules could be tuned by controlling the incubation temperature. Further, it will be beneficial to basic understanding of the nanoscale structure formation in different silk-based biomaterials. Copyright © 2015 Elsevier B.V. All rights reserved.

Isotropic and Anisotropic Growth of Metal-Organic Framework (MOF) on MOF: Logical Inference on MOF Structure Based on Growth Behavior and Morphological Feature.

PubMed

Choi, Sora; Kim, Taeho; Ji, Hoyeon; Lee, Hee Jung; Oh, Moonhyun

2016-11-02

The growth of one metal-organic framework (MOF) on another MOF for constructing a heterocompositional hybrid MOF is an interesting research topic because of the curiosity regarding the occurrence of this phenomenon and the value of hybrid MOFs as multifunctional materials or routes for fine-tuning MOF properties. In particular, the anisotropic growth of MOF on MOF is fascinating for the development of MOFs possessing atypical shapes and heterostructures or abnormal properties. Herein, we clarify the understanding of growth behavior of a secondary MOF on an initial MOF template, such as isotropic or anisotropic ways associated with their cell parameters. The isotropic growth of MIL-68-Br on the MIL-68 template results in the formation of core-shell-type MIL-68@MIL-68-Br. However, the unique anisotropic growth of a secondary MOF (MOF-NDC) on the MIL-68 template results in semitubular particles, and structural features of this unknown secondary MOF are successfully speculated for the first time on the basis of its unique growth behavior and morphological characteristics. Finally, the validation of this structural speculation is verified by the powder X-ray diffraction and the selected area electron diffraction studies. The results suggests that the growth behavior and morphological features of MOFs should be considered to be important factors for understanding the MOFs' structures.

Biomimetic surface structuring using cylindrical vector femtosecond laser beams

PubMed Central

Skoulas, Evangelos; Manousaki, Alexandra; Fotakis, Costas; Stratakis, Emmanuel

2017-01-01

We report on a new, single-step and scalable method to fabricate highly ordered, multi-directional and complex surface structures that mimic the unique morphological features of certain species found in nature. Biomimetic surface structuring was realized by exploiting the unique and versatile angular profile and the electric field symmetry of cylindrical vector (CV) femtosecond (fs) laser beams. It is shown that, highly controllable, periodic structures exhibiting sizes at nano-, micro- and dual- micro/nano scales can be directly written on Ni upon line and large area scanning with radial and azimuthal polarization beams. Depending on the irradiation conditions, new complex multi-directional nanostructures, inspired by the Shark’s skin morphology, as well as superhydrophobic dual-scale structures mimicking the Lotus’ leaf water repellent properties can be attained. It is concluded that the versatility and features variations of structures formed is by far superior to those obtained via laser processing with linearly polarized beams. More important, by exploiting the capabilities offered by fs CV fields, the present technique can be further extended to fabricate even more complex and unconventional structures. We believe that our approach provides a new concept in laser materials processing, which can be further exploited for expanding the breadth and novelty of applications. PMID:28327611

Prediction of Protein Modification Sites of Pyrrolidone Carboxylic Acid Using mRMR Feature Selection and Analysis

PubMed Central

Zheng, Lu-Lu; Niu, Shen; Hao, Pei; Feng, KaiYan; Cai, Yu-Dong; Li, Yixue

2011-01-01

Pyrrolidone carboxylic acid (PCA) is formed during a common post-translational modification (PTM) of extracellular and multi-pass membrane proteins. In this study, we developed a new predictor to predict the modification sites of PCA based on maximum relevance minimum redundancy (mRMR) and incremental feature selection (IFS). We incorporated 727 features that belonged to 7 kinds of protein properties to predict the modification sites, including sequence conservation, residual disorder, amino acid factor, secondary structure and solvent accessibility, gain/loss of amino acid during evolution, propensity of amino acid to be conserved at protein-protein interface and protein surface, and deviation of side chain carbon atom number. Among these 727 features, 244 features were selected by mRMR and IFS as the optimized features for the prediction, with which the prediction model achieved a maximum of MCC of 0.7812. Feature analysis showed that all feature types contributed to the modification process. Further site-specific feature analysis showed that the features derived from PCA's surrounding sites contributed more to the determination of PCA sites than other sites. The detailed feature analysis in this paper might provide important clues for understanding the mechanism of the PCA formation and guide relevant experimental validations. PMID:22174779

Learning and Improving in Quality Improvement Collaboratives: Which Collaborative Features Do Participants Value Most?

PubMed Central

Nembhard, Ingrid M

2009-01-01

Objective To understand participants' views on the relative helpfulness of various features of collaboratives, why each feature was helpful and which features the most successful participants viewed as most central to their success. Data Sources Primary data collected from 53 teams in four 2004–2005 Institute for Healthcare Improvement (IHI) Breakthrough Series collaboratives; secondary data from IHI and demographic sources. Study Design Cross-sectional analyses were conducted to assess participants' views of 12 features, and the relationship between their views and performance improvement. Data Collection Methods Participants' views on features were obtained via self-administered surveys and semi-structured telephone interviews. Performance improvement data were obtained from IHI and demographic data from secondary sources. Principal Findings Participants viewed six features as most helpful for advancing their improvement efforts overall and knowledge acquisition in particular: collaborative faculty, solicitation of their staff's ideas, change package, Plan-Do-Study-Act cycles, Learning Session interactions, and collaborative extranet. These features also provided participants with motivation, social support, and project management skills. Features enabling interorganizational learning were rated higher by teams whose organizations improved significantly than by other teams. Conclusions Findings identify features of collaborative design and implementation that participants view as most helpful and highlight the importance of interorganizational features, at least for those organizations that most improve. PMID:19040423

An overview on benzylisoquinoline derivatives with dopaminergic and serotonergic activities.

PubMed

Cabedo, N; Berenguer, I; Figadère, B; Cortes, D

2009-01-01

Dopamine and serotonin are important neurotransmitters in the mammalian central nervous system (CNS) involved in numerous physiological and behavioural disorders such as schizophrenia, major depression, anxiety, Parkinson's and Huntington's diseases, and attention deficit hyperactivity disorder. Several natural and synthetic benzylisoquinoline derivatives have displayed affinity for dopamine and serotonin receptors in nanomolar or micromolar ranges. This review covers the last three decades of dopaminergic and serotonergic activities, and especially focuses on structure-activity relationships of natural and synthetic benzylisoquinoline derivatives. We have included aporphines, 1-benzyltetrahydroisoquinolines, bis-benzylisoquinolines, protoberberines, cularines and other structural analogues. Further molecular modelling calculations have been considered as important tools to not only obtain structural information of both neurotransmitter receptors, but to also identify their pharmacophore features. The development of selective potential ligands like benzylisoquinoline derivatives may help in the therapy of diseases related to CNS dysfunction.

Fractal Based Analysis of the Influence of Odorants on Heart Activity

NASA Astrophysics Data System (ADS)

Namazi, Hamidreza; Kulish, Vladimir V.

2016-12-01

An important challenge in heart research is to make the relation between the features of external stimuli and heart activity. Olfactory stimulation is an important type of stimulation that affects the heart activity, which is mapped on Electrocardiogram (ECG) signal. Yet, no one has discovered any relation between the structures of olfactory stimuli and the ECG signal. This study investigates the relation between the structures of heart rate and the olfactory stimulus (odorant). We show that the complexity of the heart rate is coupled with the molecular complexity of the odorant, where more structurally complex odorant causes less fractal heart rate. Also, odorant having higher entropy causes the heart rate having lower approximate entropy. The method discussed here can be applied and investigated in case of patients with heart diseases as the rehabilitation purpose.

A Novel Characterization of Amalgamated Networks in Natural Systems

PubMed Central

Barranca, Victor J.; Zhou, Douglas; Cai, David

2015-01-01

Densely-connected networks are prominent among natural systems, exhibiting structural characteristics often optimized for biological function. To reveal such features in highly-connected networks, we introduce a new network characterization determined by a decomposition of network-connectivity into low-rank and sparse components. Based on these components, we discover a new class of networks we define as amalgamated networks, which exhibit large functional groups and dense connectivity. Analyzing recent experimental findings on cerebral cortex, food-web, and gene regulatory networks, we establish the unique importance of amalgamated networks in fostering biologically advantageous properties, including rapid communication among nodes, structural stability under attacks, and separation of network activity into distinct functional modules. We further observe that our network characterization is scalable with network size and connectivity, thereby identifying robust features significant to diverse physical systems, which are typically undetectable by conventional characterizations of connectivity. We expect that studying the amalgamation properties of biological networks may offer new insights into understanding their structure-function relationships. PMID:26035066

Factors associated with stocked cutthroat trout populations in high-mountain lakes

USGS Publications Warehouse

Bailey, Paul E.; Hubert, W.A.

2003-01-01

High-mountain lakes provide important fisheries in the Rocky Mountains; therefore we sought to gain an understanding of the relationships among environmental factors, accessibility to anglers, stocking rates, and features of stocks of cutthroat trout Oncorhynchus clarki in high-mountain lakes of the Bighorn Mountains, Wyoming. We sampled fish with experimental gill nets, measured lake habitat features, and calculated factors affecting angler access among 19 lakes that lacked sufficient natural reproduction to support salmonid fisheries and that were stocked at 1-, 2-, or 4-year intervals with fingerling cutthroat trout. We found that angler accessibility was probably the primary factor affecting stock structure, whereas stocking rates affected the densities of cutthroat trout among lakes. The maximum number of years survived after stocking appeared to have the greatest affect on biomass and population structure. Our findings suggest that control of harvest and manipulation of stocking densities can affect the density, biomass, and structure of cutthroat trout stocks in high-elevation lakes.

Universal composition-structure-property maps for natural and biomimetic platelet-matrix composites and stacked heterostructures.

PubMed

Sakhavand, Navid; Shahsavari, Rouzbeh

2015-03-16

Many natural and biomimetic platelet-matrix composites--such as nacre, silk, and clay-polymer-exhibit a remarkable balance of strength, toughness and/or stiffness, which call for a universal measure to quantify this outstanding feature given the structure and material characteristics of the constituents. Analogously, there is an urgent need to quantify the mechanics of emerging electronic and photonic systems such as stacked heterostructures. Here we report the development of a unified framework to construct universal composition-structure-property diagrams that decode the interplay between various geometries and inherent material features in both platelet-matrix composites and stacked heterostructures. We study the effects of elastic and elastic-perfectly plastic matrices, overlap offset ratio and the competing mechanisms of platelet versus matrix failures. Validated by several 3D-printed specimens and a wide range of natural and synthetic materials across scales, the proposed universally valid diagrams have important implications for science-based engineering of numerous platelet-matrix composites and stacked heterostructures.

Sequence, Structure, and Context Preferences of Human RNA Binding Proteins.

PubMed

Dominguez, Daniel; Freese, Peter; Alexis, Maria S; Su, Amanda; Hochman, Myles; Palden, Tsultrim; Bazile, Cassandra; Lambert, Nicole J; Van Nostrand, Eric L; Pratt, Gabriel A; Yeo, Gene W; Graveley, Brenton R; Burge, Christopher B

2018-06-07

RNA binding proteins (RBPs) orchestrate the production, processing, and function of mRNAs. Here, we present the affinity landscapes of 78 human RBPs using an unbiased assay that determines the sequence, structure, and context preferences of these proteins in vitro by deep sequencing of bound RNAs. These data enable construction of "RNA maps" of RBP activity without requiring crosslinking-based assays. We found an unexpectedly low diversity of RNA motifs, implying frequent convergence of binding specificity toward a relatively small set of RNA motifs, many with low compositional complexity. Offsetting this trend, however, we observed extensive preferences for contextual features distinct from short linear RNA motifs, including spaced "bipartite" motifs, biased flanking nucleotide composition, and bias away from or toward RNA structure. Our results emphasize the importance of contextual features in RNA recognition, which likely enable targeting of distinct subsets of transcripts by different RBPs that recognize the same linear motif. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Enhanced modeling features within TREETOPS

NASA Technical Reports Server (NTRS)

Vandervoort, R. J.; Kumar, Manoj N.

1989-01-01

The original motivation for TREETOPS was to build a generic multi-body simulation and remove the burden of writing multi-body equations from the engineers. The motivation of the enhancement was twofold: (1) to extend the menu of built-in features (sensors, actuators, constraints, etc.) that did not require user code; and (2) to extend the control system design capabilities by linking with other government funded software (NASTRAN and MATLAB). These enhancements also serve to bridge the gap between structures and control groups. It is common on large space programs for the structures groups to build hi-fidelity models of the structure using NASTRAN and for the controls group to build lower order models because they lack the tools to incorporate the former into their analysis. Now the controls engineers can accept the hi-fidelity NASTRAN models into TREETOPS, add sensors and actuators, perform model reduction and couple the result directly into MATLAB to perform their design. The controller can then be imported directly into TREETOPS for non-linear, time-history simulation.

Vibrations of bioionic liquids by ab initio molecular dynamics and vibrational spectroscopy.

PubMed

Tanzi, Luana; Benassi, Paola; Nardone, Michele; Ramondo, Fabio

2014-12-26

Density functional theory and vibrational spectroscopy are used to investigate a class of bioionic liquids consisting of a choline cation and carboxylate anions. Through quantum mechanical studies of motionless ion pairs and molecular dynamics of small portions of the liquid, we have characterized important structural features of the ionic liquid. Hydrogen bonding produces stable ion pairs in the liquid and induces vibrational features of the carboxylate groups comparable with experimental results. Infrared and Raman spectra of liquids have been measured, and main bands have been assigned on the basis of theoretical spectra.

A survey of decision tree classifier methodology

NASA Technical Reports Server (NTRS)

Safavian, S. R.; Landgrebe, David

1991-01-01

Decision tree classifiers (DTCs) are used successfully in many diverse areas such as radar signal classification, character recognition, remote sensing, medical diagnosis, expert systems, and speech recognition. Perhaps the most important feature of DTCs is their capability to break down a complex decision-making process into a collection of simpler decisions, thus providing a solution which is often easier to interpret. A survey of current methods is presented for DTC designs and the various existing issues. After considering potential advantages of DTCs over single-state classifiers, subjects of tree structure design, feature selection at each internal node, and decision and search strategies are discussed.

A survey of decision tree classifier methodology

NASA Technical Reports Server (NTRS)

Safavian, S. Rasoul; Landgrebe, David

1990-01-01

Decision Tree Classifiers (DTC's) are used successfully in many diverse areas such as radar signal classification, character recognition, remote sensing, medical diagnosis, expert systems, and speech recognition. Perhaps, the most important feature of DTC's is their capability to break down a complex decision-making process into a collection of simpler decisions, thus providing a solution which is often easier to interpret. A survey of current methods is presented for DTC designs and the various existing issue. After considering potential advantages of DTC's over single stage classifiers, subjects of tree structure design, feature selection at each internal node, and decision and search strategies are discussed.

Structural Mapping and Geomorphology of Ireland's Southwest Continental Shelf Using High Resolution Sonar

NASA Astrophysics Data System (ADS)

Bowden, S.; Wireman, R.

2016-02-01

Bathymetric surveys were conducted on the continental shelf off the southwest coast of County Cork, Ireland by the Marine Institute of Ireland, the Geological Survey of Ireland, and the INFOMAR project. Data were collected from July 2006 through September 2014 using a Kongsberg EM2040 multibeam echosounder aboard the R/Vs Celtic Voyager and Keary, and a Kongsberg EM1002 on the R/V Celtic Explorer. Sonar data were post-processed with CARIS HIPS and SIPS 9.0 to create 2D and 3D bathymetric and backscatter intensity surfaces with a resolution of 1 m. The offshore study site is part of the 286 Ma western Variscian orogenic front and has several massive outcrops, exhibiting 5 to 20 m of near-vertical relief. These outcrops were structurally mapped and relatively aged, and exhibit significant folding, rotation, tilting, and joint systems. Google Earth, ArcGIS, and previous terrestrial studies were used to further analyze how geomorphology is controlled by seafloor composition and structural features. Rock type and age were interpreted by comparing fracture analysis of the joints and fold trends to similar onshore outcrops documented previously, to determine an age of 416-299 Ma for the shelf's outcropping strata and associated structural features. The oldest features observed are regional anticlines and synclines containing Upper Devonian Old Red Sandstone and Lower Carboniferous shales. Within the shale layers are NE-SW plunging parasitic chevron folds. Jointing is observed in both sandstone and shale layers and is superimposed on chevron folding, with cross joints appearing to influence shallow current patterns. Rotation of the regional folds is the youngest structural feature, as both the parasitic folds and joint systems are warped. Our study shows that high resolution sonar is an effective tool for offshore structural mapping and is an important resource for understanding the geomorphology and geologic history of submerged outcrops on continental shelf systems.

Metrics for comparing neuronal tree shapes based on persistent homology.

PubMed

Li, Yanjie; Wang, Dingkang; Ascoli, Giorgio A; Mitra, Partha; Wang, Yusu

2017-01-01

As more and more neuroanatomical data are made available through efforts such as NeuroMorpho.Org and FlyCircuit.org, the need to develop computational tools to facilitate automatic knowledge discovery from such large datasets becomes more urgent. One fundamental question is how best to compare neuron structures, for instance to organize and classify large collection of neurons. We aim to develop a flexible yet powerful framework to support comparison and classification of large collection of neuron structures efficiently. Specifically we propose to use a topological persistence-based feature vectorization framework. Existing methods to vectorize a neuron (i.e, convert a neuron to a feature vector so as to support efficient comparison and/or searching) typically rely on statistics or summaries of morphometric information, such as the average or maximum local torque angle or partition asymmetry. These simple summaries have limited power in encoding global tree structures. Based on the concept of topological persistence recently developed in the field of computational topology, we vectorize each neuron structure into a simple yet informative summary. In particular, each type of information of interest can be represented as a descriptor function defined on the neuron tree, which is then mapped to a simple persistence-signature. Our framework can encode both local and global tree structure, as well as other information of interest (electrophysiological or dynamical measures), by considering multiple descriptor functions on the neuron. The resulting persistence-based signature is potentially more informative than simple statistical summaries (such as average/mean/max) of morphometric quantities-Indeed, we show that using a certain descriptor function will give a persistence-based signature containing strictly more information than the classical Sholl analysis. At the same time, our framework retains the efficiency associated with treating neurons as points in a simple Euclidean feature space, which would be important for constructing efficient searching or indexing structures over them. We present preliminary experimental results to demonstrate the effectiveness of our persistence-based neuronal feature vectorization framework.

Metrics for comparing neuronal tree shapes based on persistent homology

PubMed Central

Li, Yanjie; Wang, Dingkang; Ascoli, Giorgio A.; Mitra, Partha

2017-01-01

As more and more neuroanatomical data are made available through efforts such as NeuroMorpho.Org and FlyCircuit.org, the need to develop computational tools to facilitate automatic knowledge discovery from such large datasets becomes more urgent. One fundamental question is how best to compare neuron structures, for instance to organize and classify large collection of neurons. We aim to develop a flexible yet powerful framework to support comparison and classification of large collection of neuron structures efficiently. Specifically we propose to use a topological persistence-based feature vectorization framework. Existing methods to vectorize a neuron (i.e, convert a neuron to a feature vector so as to support efficient comparison and/or searching) typically rely on statistics or summaries of morphometric information, such as the average or maximum local torque angle or partition asymmetry. These simple summaries have limited power in encoding global tree structures. Based on the concept of topological persistence recently developed in the field of computational topology, we vectorize each neuron structure into a simple yet informative summary. In particular, each type of information of interest can be represented as a descriptor function defined on the neuron tree, which is then mapped to a simple persistence-signature. Our framework can encode both local and global tree structure, as well as other information of interest (electrophysiological or dynamical measures), by considering multiple descriptor functions on the neuron. The resulting persistence-based signature is potentially more informative than simple statistical summaries (such as average/mean/max) of morphometric quantities—Indeed, we show that using a certain descriptor function will give a persistence-based signature containing strictly more information than the classical Sholl analysis. At the same time, our framework retains the efficiency associated with treating neurons as points in a simple Euclidean feature space, which would be important for constructing efficient searching or indexing structures over them. We present preliminary experimental results to demonstrate the effectiveness of our persistence-based neuronal feature vectorization framework. PMID:28809960

Undefined freeform surfaces having deterministic structure: issues of their characterization for functionality and manufacture

NASA Astrophysics Data System (ADS)

Whitehouse, David J.

2016-09-01

There is an increasing use of surfaces which have structure, an increase in the use of freeform surfaces, and most importantly an increase in the number of surfaces having both characteristics. These can be called multi-function surfaces, where more than one function is helped by the geometrical features: the structure can help one, the freeform another. Alternatively, they can be complementary to optimize a single function, but in all cases both geometries are involved. This paper examines some of the problems posed by having such disparate geometries on one surface; in particular, the methods of characterization needed to help understand the functionality and also to some extent their manufacture. This involves investigating ways of expressing how local and global geometric features of undefined freeform surfaces might influence function and how surface structure on top of or in series with the freeform affects the nature of the characterization. Some methods have been found of identifying possible strategies for tackling the characterization problem, based in part on the principles of least action and on the way that nature has solved the marriage of flexible freeform geometry and structure on surfaces.

On the relationship between the dynamic behavior and nanoscale staggered structure of the bone

NASA Astrophysics Data System (ADS)

Qwamizadeh, Mahan; Zhang, Zuoqi; Zhou, Kun; Zhang, Yong Wei

2015-05-01

Bone, a typical load-bearing biological material, composed of ordinary base materials such as organic protein and inorganic mineral arranged in a hierarchical architecture, exhibits extraordinary mechanical properties. Up to now, most of previous studies focused on its mechanical properties under static loading. However, failure of the bone occurs often under dynamic loading. An interesting question is: Are the structural sizes and layouts of the bone related or even adapted to the functionalities demanded by its dynamic performance? In the present work, systematic finite element analysis was performed on the dynamic response of nanoscale bone structures under dynamic loading. It was found that for a fixed mineral volume fraction and unit cell area, there exists a nanoscale staggered structure at some specific feature size and layout which exhibits the fastest attenuation of stress waves. Remarkably, these specific feature sizes and layouts are in excellent agreement with those experimentally observed in the bone at the same scale, indicating that the structural size and layout of the bone at the nanoscale are evolutionarily adapted to its dynamic behavior. The present work points out the importance of dynamic effect on the biological evolution of load-bearing biological materials.

Agent-based model with multi-level herding for complex financial systems

NASA Astrophysics Data System (ADS)

Chen, Jun-Jie; Tan, Lei; Zheng, Bo

2015-02-01

In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level.

Agent-based model with multi-level herding for complex financial systems

PubMed Central

Chen, Jun-Jie; Tan, Lei; Zheng, Bo

2015-01-01

In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level. PMID:25669427

Protein single-model quality assessment by feature-based probability density functions.

PubMed

Cao, Renzhi; Cheng, Jianlin

2016-04-04

Protein quality assessment (QA) has played an important role in protein structure prediction. We developed a novel single-model quality assessment method-Qprob. Qprob calculates the absolute error for each protein feature value against the true quality scores (i.e. GDT-TS scores) of protein structural models, and uses them to estimate its probability density distribution for quality assessment. Qprob has been blindly tested on the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) as MULTICOM-NOVEL server. The official CASP result shows that Qprob ranks as one of the top single-model QA methods. In addition, Qprob makes contributions to our protein tertiary structure predictor MULTICOM, which is officially ranked 3rd out of 143 predictors. The good performance shows that Qprob is good at assessing the quality of models of hard targets. These results demonstrate that this new probability density distribution based method is effective for protein single-model quality assessment and is useful for protein structure prediction. The webserver of Qprob is available at: http://calla.rnet.missouri.edu/qprob/. The software is now freely available in the web server of Qprob.

Detection and localization of damage using empirical mode decomposition and multilevel support vector machine

NASA Astrophysics Data System (ADS)

Dushyanth, N. D.; Suma, M. N.; Latte, Mrityanjaya V.

2016-03-01

Damage in the structure may raise a significant amount of maintenance cost and serious safety problems. Hence detection of the damage at its early stage is of prime importance. The main contribution pursued in this investigation is to propose a generic optimal methodology to improve the accuracy of positioning of the flaw in a structure. This novel approach involves a two-step process. The first step essentially aims at extracting the damage-sensitive features from the received signal, and these extracted features are often termed the damage index or damage indices, serving as an indicator to know whether the damage is present or not. In particular, a multilevel SVM (support vector machine) plays a vital role in the distinction of faulty and healthy structures. Formerly, when a structure is unveiled as a damaged structure, in the subsequent step, the position of the damage is identified using Hilbert-Huang transform. The proposed algorithm has been evaluated in both simulation and experimental tests on a 6061 aluminum plate with dimensions 300 mm × 300 mm × 5 mm which accordingly yield considerable improvement in the accuracy of estimating the position of the flaw.

Solution structure of Syrian hamster prion protein rPrP(90-231).

PubMed

Liu, H; Farr-Jones, S; Ulyanov, N B; Llinas, M; Marqusee, S; Groth, D; Cohen, F E; Prusiner, S B; James, T L

1999-04-27

NMR has been used to refine the structure of Syrian hamster (SHa) prion protein rPrP(90-231), which is commensurate with the infectious protease-resistant core of the scrapie prion protein PrPSc. The structure of rPrP(90-231), refolded to resemble the normal cellular isoform PrPC spectroscopically and immunologically, has been studied using multidimensional NMR; initial results were published [James et al. (1997) Proc. Natl. Acad. Sci. U.S.A. 94, 10086-10091]. We now report refinement with better definition revealing important structural and dynamic features which can be related to biological observations pertinent to prion diseases. Structure refinement was based on 2778 unambiguously assigned nuclear Overhauser effect (NOE) connectivities, 297 ambiguous NOE restraints, and 63 scalar coupling constants (3JHNHa). The structure is represented by an ensemble of 25 best-scoring structures from 100 structures calculated using ARIA/X-PLOR and further refined with restrained molecular dynamics using the AMBER 4.1 force field with an explicit shell of water molecules. The rPrP(90-231) structure features a core domain (residues 125-228), with a backbone atomic root-mean-square deviation (RMSD) of 0.67 A, consisting of three alpha-helices (residues 144-154, 172-193, and 200-227) and two short antiparallel beta-strands (residues 129-131 and 161-163). The N-terminus (residues 90-119) is largely unstructured despite some sparse and weak medium-range NOEs implying the existence of bends or turns. The transition region between the core domain and flexible N-terminus, i.e., residues 113-128, consists of hydrophobic residues or glycines and does not adopt any regular secondary structure in aqueous solution. There are about 30 medium- and long-range NOEs within this hydrophobic cluster, so it clearly manifests structure. Multiple discrete conformations are evident, implying the possible existence of one or more metastable states, which may feature in conversion of PrPC to PrPSc. To obtain a more comprehensive picture of rPrP(90-231), dynamics have been studied using amide hydrogen-deuterium exchange and 15N NMR relaxation times (T1 and T2) and 15N{1H} NOE measurements. Comparison of the structure with previous reports suggests sequence-dependent features that may be reflected in a species barrier to prion disease transmission.

A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities.

PubMed

Valizade Hasanloei, Mohammad Amin; Sheikhpour, Razieh; Sarram, Mehdi Agha; Sheikhpour, Elnaz; Sharifi, Hamdollah

2018-02-01

Quantitative structure-activity relationship (QSAR) is an effective computational technique for drug design that relates the chemical structures of compounds to their biological activities. Feature selection is an important step in QSAR based drug design to select the most relevant descriptors. One of the most popular feature selection methods for classification problems is Fisher score which aim is to minimize the within-class distance and maximize the between-class distance. In this study, the properties of Fisher criterion were extended for QSAR models to define the new distance metrics based on the continuous activity values of compounds with known activities. Then, a semi-supervised feature selection method was proposed based on the combination of Fisher and Laplacian criteria which exploits both compounds with known and unknown activities to select the relevant descriptors. To demonstrate the efficiency of the proposed semi-supervised feature selection method in selecting the relevant descriptors, we applied the method and other feature selection methods on three QSAR data sets such as serine/threonine-protein kinase PLK3 inhibitors, ROCK inhibitors and phenol compounds. The results demonstrated that the QSAR models built on the selected descriptors by the proposed semi-supervised method have better performance than other models. This indicates the efficiency of the proposed method in selecting the relevant descriptors using the compounds with known and unknown activities. The results of this study showed that the compounds with known and unknown activities can be helpful to improve the performance of the combined Fisher and Laplacian based feature selection methods.

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.

A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities

NASA Astrophysics Data System (ADS)

Valizade Hasanloei, Mohammad Amin; Sheikhpour, Razieh; Sarram, Mehdi Agha; Sheikhpour, Elnaz; Sharifi, Hamdollah

2018-02-01

Quantitative structure-activity relationship (QSAR) is an effective computational technique for drug design that relates the chemical structures of compounds to their biological activities. Feature selection is an important step in QSAR based drug design to select the most relevant descriptors. One of the most popular feature selection methods for classification problems is Fisher score which aim is to minimize the within-class distance and maximize the between-class distance. In this study, the properties of Fisher criterion were extended for QSAR models to define the new distance metrics based on the continuous activity values of compounds with known activities. Then, a semi-supervised feature selection method was proposed based on the combination of Fisher and Laplacian criteria which exploits both compounds with known and unknown activities to select the relevant descriptors. To demonstrate the efficiency of the proposed semi-supervised feature selection method in selecting the relevant descriptors, we applied the method and other feature selection methods on three QSAR data sets such as serine/threonine-protein kinase PLK3 inhibitors, ROCK inhibitors and phenol compounds. The results demonstrated that the QSAR models built on the selected descriptors by the proposed semi-supervised method have better performance than other models. This indicates the efficiency of the proposed method in selecting the relevant descriptors using the compounds with known and unknown activities. The results of this study showed that the compounds with known and unknown activities can be helpful to improve the performance of the combined Fisher and Laplacian based feature selection methods.

Antimicrobial Polymers: Mimicking Amino Acid Functionali ty, Sequence Control and Three-dimensional Structure of Host-defen se Peptides.

PubMed

Hartlieb, Matthias; Williams, Elizabeth G L; Kuroki, Agnès; Perrier, Sébastien; Locock, Katherine E S

2017-01-01

Peptides and proteins control and direct all aspects of cellular function and communication. Having been honed by nature for millions of years, they also typically display an unsurpassed specificity for their biological targets. This underlies the continued focus on peptides as promising drug candidates. However, the development of peptides into viable drugs is hampered by their lack of chemical and pharmacokinetic stability and the cost of large scale production. One method to overcome such hindrances is to develop polymer systems that are able to retain the important structural features of these biologically active peptides, while being cheaper and easier to produce and manipulate chemically. This review illustrates these principles using examples of polymers designed to mimic antimicrobial host-defence peptides. The host-defence peptides have been identified as some of the most important leads for the next generation of antibiotics as they typically exhibit broad spectrum antimicrobial ability, low toxicity toward human cells and little susceptibility to currently known mechanisms of bacterial resistance. Their movement from the bench to clinic is yet to be realised, however, due to the limitations of these peptides as drugs. The literature provides a number of examples of polymers that have been able to mimic these peptides through all levels of structure, starting from specific amino acid sidechains, through to more global features such as overall charge, molecular weight and threedimensional structure (e.g. α-helical). The resulting optimised polymers are able retain the activity profile of the peptides, but within a synthetic macromolecular construct that may be better suited to the development of a new generation of antimicrobial therapeutics. Such work has not only produced important new leads to combat the growing threat of antibiotic resistance, but may also open up new ways for polymers to mimic other important classes of biologically active peptides. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Mediterranean scrubland and elevation drive gene flow of a Mediterranean carnivore, the Egyptian mongoose Herpestes ichneumon (Herpestidae)

Treesearch

Tania Barros; Samuel A. Cushman; Joao Carvalho; Carlos Fonseca

2016-01-01

Identifying the environmental features affecting gene flow across a species range is of extreme importance for conservation planning. We investigated the genetic structure of the Egyptian mongoose (Herpestes ichneumon) in Western Iberian Peninsula by analyzing the correlations between genetic distances and landscape resistance models. We evaluated several...

Innovative Language-Based & Object-Oriented Structured AMR Using Fortran 90 and OpenMP

NASA Technical Reports Server (NTRS)

Norton, C.; Balsara, D.

1999-01-01

Parallel adaptive mesh refinement (AMR) is an important numerical technique that leads to the efficient solution of many physical and engineering problems. In this paper, we describe how AMR programing can be performed in an object-oreinted way using the modern aspects of Fortran 90 combined with the parallelization features of OpenMP.

The Importance of Workplace Learning for Trade Unions: A Study of the Steel Industry

ERIC Educational Resources Information Center

Stroud, Dean; Fairbrother, Peter

2008-01-01

This paper is concerned with the relationship between trade unions and learning in the workplace, particularly in relation to the enhancement of worker employability profiles. With the restructuring and modernising of the European steel industry as its context, this paper argues that the organisational and structural features of a sector have a…

Cross Flow Parameter Calculation for Aerodynamic Analysis

NASA Technical Reports Server (NTRS)

Norman, David, Jr. (Inventor)

2014-01-01

A system and method for determining a cross flow angle for a feature on a structure. A processor unit receives location information identifying a location of the feature on the structure, determines an angle of the feature, identifies flow information for the location, determines a flow angle using the flow information, and determines the cross flow angle for the feature using the flow angle and the angle of the feature. The flow information describes a flow of fluid across the structure. The flow angle comprises an angle of the flow of fluid across the structure for the location of the feature.

Challenging the state-of-the-art in protein structure prediction: Highlights of experimental target structures for the 10th Critical Assessment of Techniques for Protein Structure Prediction Experiment CASP10

PubMed Central

Kryshtafovych, Andriy; Moult, John; Bales, Patrick; Bazan, J. Fernando; Biasini, Marco; Burgin, Alex; Chen, Chen; Cochran, Frank V.; Craig, Timothy K.; Das, Rhiju; Fass, Deborah; Garcia-Doval, Carmela; Herzberg, Osnat; Lorimer, Donald; Luecke, Hartmut; Ma, Xiaolei; Nelson, Daniel C.; van Raaij, Mark J.; Rohwer, Forest; Segall, Anca; Seguritan, Victor; Zeth, Kornelius; Schwede, Torsten

2014-01-01

For the last two decades, CASP has assessed the state of the art in techniques for protein structure prediction and identified areas which required further development. CASP would not have been possible without the prediction targets provided by the experimental structural biology community. In the latest experiment, CASP10, over 100 structures were suggested as prediction targets, some of which appeared to be extraordinarily difficult for modeling. In this paper, authors of some of the most challenging targets discuss which specific scientific question motivated the experimental structure determination of the target protein, which structural features were especially interesting from a structural or functional perspective, and to what extent these features were correctly reproduced in the predictions submitted to CASP10. Specifically, the following targets will be presented: the acid-gated urea channel, a difficult to predict trans-membrane protein from the important human pathogen Helicobacter pylori; the structure of human interleukin IL-34, a recently discovered helical cytokine; the structure of a functionally uncharacterized enzyme OrfY from Thermoproteus tenax formed by a gene duplication and a novel fold; an ORFan domain of mimivirus sulfhydryl oxidase R596; the fibre protein gp17 from bacteriophage T7; the Bacteriophage CBA-120 tailspike protein; a virus coat protein from metagenomic samples of the marine environment; and finally an unprecedented class of structure prediction targets based on engineered disulfide-rich small proteins. PMID:24318984

Comparison between periodic and stochastic parabolic light trapping structures for thin-film microcrystalline Silicon solar cells.

PubMed

Peters, M; Battaglia, C; Forberich, K; Bläsi, B; Sahraei, N; Aberle, A G

2012-12-31

Light trapping is of very high importance for silicon photovoltaics (PV) and especially for thin-film silicon solar cells. In this paper we investigate and compare theoretically the light trapping properties of periodic and stochastic structures having similar geometrical features. The theoretical investigations are based on the actual surface geometry of a scattering structure, characterized by an atomic force microscope. This structure is used for light trapping in thin-film microcrystalline silicon solar cells. Very good agreement is found in a first comparison between simulation and experimental results. The geometrical parameters of the stochastic structure are varied and it is found that the light trapping mainly depends on the aspect ratio (length/height). Furthermore, the maximum possible light trapping with this kind of stochastic structure geometry is investigated. In a second step, the stochastic structure is analysed and typical geometrical features are extracted, which are then arranged in a periodic structure. Investigating the light trapping properties of the periodic structure, we find that it performs very similar to the stochastic structure, in agreement with reports in literature. From the obtained results we conclude that a potential advantage of periodic structures for PV applications will very likely not be found in the absorption enhancement in the solar cell material. However, uniformity and higher definition in production of these structures can lead to potential improvements concerning electrical characteristics and parasitic absorption, e.g. in a back reflector.

A Sieving ANN for Emotion-Based Movie Clip Classification

NASA Astrophysics Data System (ADS)

Watanapa, Saowaluk C.; Thipakorn, Bundit; Charoenkitkarn, Nipon

Effective classification and analysis of semantic contents are very important for the content-based indexing and retrieval of video database. Our research attempts to classify movie clips into three groups of commonly elicited emotions, namely excitement, joy and sadness, based on a set of abstract-level semantic features extracted from the film sequence. In particular, these features consist of six visual and audio measures grounded on the artistic film theories. A unique sieving-structured neural network is proposed to be the classifying model due to its robustness. The performance of the proposed model is tested with 101 movie clips excerpted from 24 award-winning and well-known Hollywood feature films. The experimental result of 97.8% correct classification rate, measured against the collected human-judges, indicates the great potential of using abstract-level semantic features as an engineered tool for the application of video-content retrieval/indexing.

Deep learning of support vector machines with class probability output networks.

PubMed

Kim, Sangwook; Yu, Zhibin; Kil, Rhee Man; Lee, Minho

2015-04-01

Deep learning methods endeavor to learn features automatically at multiple levels and allow systems to learn complex functions mapping from the input space to the output space for the given data. The ability to learn powerful features automatically is increasingly important as the volume of data and range of applications of machine learning methods continues to grow. This paper proposes a new deep architecture that uses support vector machines (SVMs) with class probability output networks (CPONs) to provide better generalization power for pattern classification problems. As a result, deep features are extracted without additional feature engineering steps, using multiple layers of the SVM classifiers with CPONs. The proposed structure closely approaches the ideal Bayes classifier as the number of layers increases. Using a simulation of classification problems, the effectiveness of the proposed method is demonstrated. Copyright © 2014 Elsevier Ltd. All rights reserved.

Spectral-spatial classification of hyperspectral image using three-dimensional convolution network

NASA Astrophysics Data System (ADS)

Liu, Bing; Yu, Xuchu; Zhang, Pengqiang; Tan, Xiong; Wang, Ruirui; Zhi, Lu

2018-01-01

Recently, hyperspectral image (HSI) classification has become a focus of research. However, the complex structure of an HSI makes feature extraction difficult to achieve. Most current methods build classifiers based on complex handcrafted features computed from the raw inputs. The design of an improved 3-D convolutional neural network (3D-CNN) model for HSI classification is described. This model extracts features from both the spectral and spatial dimensions through the application of 3-D convolutions, thereby capturing the important discrimination information encoded in multiple adjacent bands. The designed model views the HSI cube data altogether without relying on any pre- or postprocessing. In addition, the model is trained in an end-to-end fashion without any handcrafted features. The designed model was applied to three widely used HSI datasets. The experimental results demonstrate that the 3D-CNN-based method outperforms conventional methods even with limited labeled training samples.

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

PubMed Central

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

2016-01-01

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

Structural and functional studies of a 50 kDa antigenic protein from Salmonella enterica serovar Typhi.

PubMed

Choong, Yee Siew; Lim, Theam Soon; Chew, Ai Lan; Aziah, Ismail; Ismail, Asma

2011-04-01

The high typhoid incidence rate in developing and under-developed countries emphasizes the need for a rapid, affordable and accessible diagnostic test for effective therapy and disease management. TYPHIDOT®, a rapid dot enzyme immunoassay test for typhoid, was developed from the discovery of a ∼50 kDa protein specific for Salmonella enterica serovar Typhi. However, the structure of this antigen remains unknown till today. Studies on the structure of this antigen are important to elucidate its function, which will in turn increase the efficiency of the development and improvement of the typhoid detection test. This paper described the predictive structure and function of the antigenically specific protein. The homology modeling approach was employed to construct the three-dimensional structure of the antigen. The built structure possesses the features of TolC-like outer membrane protein. Molecular docking simulation was also performed to further probe the functionality of the antigen. Docking results showed that hexamminecobalt, Co(NH(3))(6)(3+), as an inhibitor of TolC protein, formed favorable hydrogen bonds with D368 and D371 of the antigen. The single point (D368A, D371A) and double point (D368A and D371A) mutations of the antigen showed a decrease (single point mutation) and loss (double point mutations) of binding affinity towards hexamminecobalt. The architecture features of the built model and the docking simulation reinforced and supported that this antigen is indeed the variant of outer membrane protein, TolC. As channel proteins are important for the virulence and survival of bacteria, therefore this ∼50 kDa channel protein is a good specific target for typhoid detection test. Copyright © 2011 Elsevier Inc. All rights reserved.

The intriguing nature of dorsal root ganglion neurons: linking structure with polarity and function.

PubMed

Nascimento, Ana Isabel; Mar, Fernando Milhazes; Sousa, Mónica Mendes

2018-05-02

Dorsal root ganglion (DRG) neurons are the first neurons of the sensory pathway. They are activated by a variety of sensory stimuli that are then transmitted to the central nervous system. An important feature of DRG neurons is their unique morphology where a single process -the stem axon- bifurcates into a peripheral and a central axonal branch, with different functions and cellular properties. Distinctive structural aspects of the two DRG neuron branches may have important implications for their function in health and disease. However, the link between DRG axonal branch structure, polarity and function has been largely neglected in the field, and relevant information is rather scattered across the literature. In particular, ultrastructural differences between the two axonal branches are likely to account for the higher transport and regenerative ability of the peripheral DRG neuron axon when compared to the central one. Nevertheless, the cell intrinsic factors contributing to this central-peripheral asymmetry are still unknown. Here we critically review the factors that may underlie the functional asymmetry between the peripheral and central DRG axonal branches. Also, we discuss the hypothesis that DRG neurons may assemble a structure resembling the axon initial segment that may be responsible, at least in part, for their polarity and electrophysiological features. Ultimately, we suggest that the clarification of the axonal ultrastructure of DRG neurons using state-of-the-art techniques will be crucial to understand the physiology of this peculiar cell type. Copyright © 2018. Published by Elsevier Ltd.

Experiments on schistosity and slaty cleavage

USGS Publications Warehouse

Becker, George Ferdinand

1904-01-01

Schistosity as a structure is important, and it is a part of the business of geologists to explain its origin. Slaty cleavage has further and greater importance as a possible tectonic feature. Scarcely a great mountain range exists, or has existed, along the course of which belts of slaty rock are not found, the dip of the cleavage usually approaching verticality. Are these slate belts equivalent to minutely distributed step faults of great total throw, or do they indicate compression perpendicular to the cleavage without attendant relative dislocation? Evidently the answer to this question is of first importance in the interpretation of orogenic phenomena.

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

Beliefs About the Causal Structure of the Self-Concept Determine Which Changes Disrupt Personal Identity.

PubMed

Chen, Stephanie Y; Urminsky, Oleg; Bartels, Daniel M

2016-10-01

Personal identity is an important determinant of behavior, yet how people mentally represent their self-concepts and their concepts of other people is not well understood. In the current studies, we examined the age-old question of what makes people who they are. We propose a novel approach to identity that suggests that the answer lies in people's beliefs about how the features of identity (e.g., memories, moral qualities, personality traits) are causally related to each other. We examined the impact of the causal centrality of a feature, a key determinant of the extent to which a feature defines a concept, on judgments of identity continuity. We found support for this approach in three experiments using both measured and manipulated causal centrality. For judgments both of one's self and of others, we found that some features are perceived to be more causally central than others and that changes in such causally central features are believed to be more disruptive to identity.

Computer ranking of the sequence of appearance of 100 features of the brain and related structures in staged human embryos during the first 5 weeks of development.

PubMed

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

1984-11-01

The sequence of events in the development of the brain in staged human embryos was investigated in much greater detail than in previous studies by listing 100 features in 165 embryos of the first 5 weeks. Using a computerized bubble-sort algorithm, individual embryos were ranked in ascending order of the features present. This procedure made feasible an appreciation of the slight variation found in the developmental features. The vast majority of features appeared during either one or two stages (about 2 or 3 days). In general, the soundness of the Carnegie system of embryonic staging was amply confirmed. The rhombencephalon was found to show increasing complexity around stage 13, and the postoptic portion of the diencephalon underwent considerable differentiation by stage 15. The need for similar investigations of other systems of the body is emphasized, and the importance of such studies in assessing the timing of congenital malformations and in clarifying syndromic clusters is suggested.

Segmentation of neuronal structures using SARSA (λ)-based boundary amendment with reinforced gradient-descent curve shape fitting.

PubMed

Zhu, Fei; Liu, Quan; Fu, Yuchen; Shen, Bairong

2014-01-01

The segmentation of structures in electron microscopy (EM) images is very important for neurobiological research. The low resolution neuronal EM images contain noise and generally few features are available for segmentation, therefore application of the conventional approaches to identify the neuron structure from EM images is not successful. We therefore present a multi-scale fused structure boundary detection algorithm in this study. In the algorithm, we generate an EM image Gaussian pyramid first, then at each level of the pyramid, we utilize Laplacian of Gaussian function (LoG) to attain structure boundary, we finally assemble the detected boundaries by using fusion algorithm to attain a combined neuron structure image. Since the obtained neuron structures usually have gaps, we put forward a reinforcement learning-based boundary amendment method to connect the gaps in the detected boundaries. We use a SARSA (λ)-based curve traveling and amendment approach derived from reinforcement learning to repair the incomplete curves. Using this algorithm, a moving point starts from one end of the incomplete curve and walks through the image where the decisions are supervised by the approximated curve model, with the aim of minimizing the connection cost until the gap is closed. Our approach provided stable and efficient structure segmentation. The test results using 30 EM images from ISBI 2012 indicated that both of our approaches, i.e., with or without boundary amendment, performed better than six conventional boundary detection approaches. In particular, after amendment, the Rand error and warping error, which are the most important performance measurements during structure segmentation, were reduced to very low values. The comparison with the benchmark method of ISBI 2012 and the recent developed methods also indicates that our method performs better for the accurate identification of substructures in EM images and therefore useful for the identification of imaging features related to brain diseases.

Segmentation of Neuronal Structures Using SARSA (λ)-Based Boundary Amendment with Reinforced Gradient-Descent Curve Shape Fitting

PubMed Central

Zhu, Fei; Liu, Quan; Fu, Yuchen; Shen, Bairong

2014-01-01

The segmentation of structures in electron microscopy (EM) images is very important for neurobiological research. The low resolution neuronal EM images contain noise and generally few features are available for segmentation, therefore application of the conventional approaches to identify the neuron structure from EM images is not successful. We therefore present a multi-scale fused structure boundary detection algorithm in this study. In the algorithm, we generate an EM image Gaussian pyramid first, then at each level of the pyramid, we utilize Laplacian of Gaussian function (LoG) to attain structure boundary, we finally assemble the detected boundaries by using fusion algorithm to attain a combined neuron structure image. Since the obtained neuron structures usually have gaps, we put forward a reinforcement learning-based boundary amendment method to connect the gaps in the detected boundaries. We use a SARSA (λ)-based curve traveling and amendment approach derived from reinforcement learning to repair the incomplete curves. Using this algorithm, a moving point starts from one end of the incomplete curve and walks through the image where the decisions are supervised by the approximated curve model, with the aim of minimizing the connection cost until the gap is closed. Our approach provided stable and efficient structure segmentation. The test results using 30 EM images from ISBI 2012 indicated that both of our approaches, i.e., with or without boundary amendment, performed better than six conventional boundary detection approaches. In particular, after amendment, the Rand error and warping error, which are the most important performance measurements during structure segmentation, were reduced to very low values. The comparison with the benchmark method of ISBI 2012 and the recent developed methods also indicates that our method performs better for the accurate identification of substructures in EM images and therefore useful for the identification of imaging features related to brain diseases. PMID:24625699

Structures data collection for The National Map using volunteered geographic information

USGS Publications Warehouse

Poore, Barbara S.; Wolf, Eric B.; Korris, Erin M.; Walter, Jennifer L.; Matthews, Greg D.

2012-01-01

The U.S. Geological Survey (USGS) has historically sponsored volunteered data collection projects to enhance its topographic paper and digital map products. This report describes one phase of an ongoing project to encourage volunteers to contribute data to The National Map using online editing tools. The USGS recruited students studying geographic information systems (GIS) at the University of Colorado Denver and the University of Denver in the spring of 2011 to add data on structures - manmade features such as schools, hospitals, and libraries - to four quadrangles covering metropolitan Denver. The USGS customized a version of the online Potlatch editor created by the OpenStreetMap project and populated it with 30 structure types drawn from the Geographic Names Information System (GNIS), a USGS database of geographic features. The students corrected the location and attributes of these points and added information on structures that were missing. There were two rounds of quality control. Student volunteers reviewed each point, and an in-house review of each point by the USGS followed. Nine-hundred and thirty-eight structure points were initially downloaded from the USGS database. Editing and quality control resulted in 1,214 structure points that were subsequently added to The National Map. A post-project analysis of the data shows that after student edit and peer review, 92 percent of the points contributed by volunteers met National Map Accuracy Standards for horizontal accuracy. Lessons from this project will be applied to later phases. These include: simplifying editing tasks and the user interfaces, stressing to volunteers the importance of adding structures that are missing, and emphasizing the importance of conforming to editorial guidelines for formatting names and addresses of structures. The next phase of the project will encompass the entire State of Colorado and will allow any citizen to contribute structures data. Volunteers will benefit from this project by engaging with their local geography and contributing to a national resource of topographic information that remains in the public domain for anyone to download.

A review of quasi-coherent structures in a numerically simulated turbulent boundary layer

NASA Technical Reports Server (NTRS)

Robinson, S. K.; Kline, S. J.; Spalart, P. R.

1989-01-01

Preliminary results of a comprehensive study of the structural aspects of a numerically simulated number turbulent boundary layer are presented. A direct Navier-Stokes simulation of a flat-plate, zero pressure gradient boundary layer at Re0 = 670 was used. Most of the known nonrandom, coherent features of turbulent boundary layers are confirmed in the simulation, and several new aspects of their spatial character are reported. The spatial relationships between many of the various structures are described, forming the basis for a more complete kinematical picture of boundary layer physics than has been previously known. In particular, the importance of vortex structures of various forms to the generation of Reynolds shear stress is investigated.

Aggregation of p-Sulfonatocalixarene-Based Amphiphiles and Supra-Amphiphiles

PubMed Central

Basilio, Nuno; Francisco, Vitor; Garcia-Rio, Luis

2013-01-01

p-Sulfonatocalixarenes are a special class of water soluble macrocyclic molecules made of 4-hydroxybenzenesulfonate units linked by methylene bridges. One of the main features of these compounds relies on their ability to form inclusion complexes with cationic and neutral species. This feature, together with their water solubility and apparent biological compatibility, had enabled them to emerge as one the most important host receptors in supramolecular chemistry. Attachment of hydrophobic alkyl chains to these compounds leads to the formation of macrocyclic host molecules with amphiphilic properties. Like other oligomeric surfactants, these compounds present improved performance with respect to their monomeric counterparts. In addition, they hold their recognition abilities and present several structural features that depend on the size of the macrocycle and on the length of the alkyl chain, such as preorganization, flexibility and adopted conformations, which make these molecules very interesting to study structure-aggregation relationships. Moreover, the recognition abilities of p-sulfonatocalixarenes enable them to be applied in the design of amphiphiles constructed from non-covalent, rather than covalent, bonds (supramolecular amphiphiles). In this review, we summarize the developments made on the design and synthesis of p-sulfonatocalixarenes-based surfactants, the characterization of their self-assembly properties and on how their structure affects these properties. PMID:23380960

CheS-Mapper - Chemical Space Mapping and Visualization in 3D.

PubMed

Gütlein, Martin; Karwath, Andreas; Kramer, Stefan

2012-03-17

Analyzing chemical datasets is a challenging task for scientific researchers in the field of chemoinformatics. It is important, yet difficult to understand the relationship between the structure of chemical compounds, their physico-chemical properties, and biological or toxic effects. To that respect, visualization tools can help to better comprehend the underlying correlations. Our recently developed 3D molecular viewer CheS-Mapper (Chemical Space Mapper) divides large datasets into clusters of similar compounds and consequently arranges them in 3D space, such that their spatial proximity reflects their similarity. The user can indirectly determine similarity, by selecting which features to employ in the process. The tool can use and calculate different kind of features, like structural fragments as well as quantitative chemical descriptors. These features can be highlighted within CheS-Mapper, which aids the chemist to better understand patterns and regularities and relate the observations to established scientific knowledge. As a final function, the tool can also be used to select and export specific subsets of a given dataset for further analysis.

CheS-Mapper - Chemical Space Mapping and Visualization in 3D

PubMed Central

2012-01-01

Analyzing chemical datasets is a challenging task for scientific researchers in the field of chemoinformatics. It is important, yet difficult to understand the relationship between the structure of chemical compounds, their physico-chemical properties, and biological or toxic effects. To that respect, visualization tools can help to better comprehend the underlying correlations. Our recently developed 3D molecular viewer CheS-Mapper (Chemical Space Mapper) divides large datasets into clusters of similar compounds and consequently arranges them in 3D space, such that their spatial proximity reflects their similarity. The user can indirectly determine similarity, by selecting which features to employ in the process. The tool can use and calculate different kind of features, like structural fragments as well as quantitative chemical descriptors. These features can be highlighted within CheS-Mapper, which aids the chemist to better understand patterns and regularities and relate the observations to established scientific knowledge. As a final function, the tool can also be used to select and export specific subsets of a given dataset for further analysis. PMID:22424447

Hierarchical Recurrent Neural Hashing for Image Retrieval With Hierarchical Convolutional Features.

PubMed

Lu, Xiaoqiang; Chen, Yaxiong; Li, Xuelong

Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features. However, these methods only use semantic features to generate hash codes by shallow projection but ignore texture details. In this paper, we proposed a novel hashing method, namely hierarchical recurrent neural hashing (HRNH), to exploit hierarchical recurrent neural network to generate effective hash codes. There are three contributions of this paper. First, a deep hashing method is proposed to extensively exploit both spatial details and semantic information, in which, we leverage hierarchical convolutional features to construct image pyramid representation. Second, our proposed deep network can exploit directly convolutional feature maps as input to preserve the spatial structure of convolutional feature maps. Finally, we propose a new loss function that considers the quantization error of binarizing the continuous embeddings into the discrete binary codes, and simultaneously maintains the semantic similarity and balanceable property of hash codes. Experimental results on four widely used data sets demonstrate that the proposed HRNH can achieve superior performance over other state-of-the-art hashing methods.Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features. However, these methods only use semantic features to generate hash codes by shallow projection but ignore texture details. In this paper, we proposed a novel hashing method, namely hierarchical recurrent neural hashing (HRNH), to exploit hierarchical recurrent neural network to generate effective hash codes. There are three contributions of this paper. First, a deep hashing method is proposed to extensively exploit both spatial details and semantic information, in which, we leverage hierarchical convolutional features to construct image pyramid representation. Second, our proposed deep network can exploit directly convolutional feature maps as input to preserve the spatial structure of convolutional feature maps. Finally, we propose a new loss function that considers the quantization error of binarizing the continuous embeddings into the discrete binary codes, and simultaneously maintains the semantic similarity and balanceable property of hash codes. Experimental results on four widely used data sets demonstrate that the proposed HRNH can achieve superior performance over other state-of-the-art hashing methods.

Effect of regional slopes on local structure and exploration of tilted paleo-highs

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

Nazarov, D.A.; Chernobrov, B.S.

1986-06-01

Prospects for discovering local highs in old petroleum-producing regions have by now been substantially exhausted. Hence it is of great importance at this stage to seek non-anticlinal accumulations of hydrocarbons, including those in traps genetically associated with tilted paleo-highs, often represented in the modern structural plan by structural noses and terraces. Appropriate exploration for such types of deposits may soon become important in Ciscaucasia and other old petroleum-producing regions. Consequently, problems of the scientific basis for prospecting paleo-highs tilted in the modern structural plan, and developing procedures both for revealing and also for assessing their expression in the structural planmore » during different stages of geological history, and establishing the time and depth of changes in aspect, will become extremely topical. In order to discover possible local highs and to study their features within the margins of the platformal basins and the platformal edges of the marginal troughs, the authors use the method of removing the effect of the regional slope on the local structural plan. This paper describes this method. 13 references.« less

Automatic archaeological feature extraction from satellite VHR images

NASA Astrophysics Data System (ADS)

Jahjah, Munzer; Ulivieri, Carlo

2010-05-01

Archaeological applications need a methodological approach on a variable scale able to satisfy the intra-site (excavation) and the inter-site (survey, environmental research). The increased availability of high resolution and micro-scale data has substantially favoured archaeological applications and the consequent use of GIS platforms for reconstruction of archaeological landscapes based on remotely sensed data. Feature extraction of multispectral remotely sensing image is an important task before any further processing. High resolution remote sensing data, especially panchromatic, is an important input for the analysis of various types of image characteristics; it plays an important role in the visual systems for recognition and interpretation of given data. The methods proposed rely on an object-oriented approach based on a theory for the analysis of spatial structures called mathematical morphology. The term "morphology" stems from the fact that it aims at analysing object shapes and forms. It is mathematical in the sense that the analysis is based on the set theory, integral geometry, and lattice algebra. Mathematical morphology has proven to be a powerful image analysis technique; two-dimensional grey tone images are seen as three-dimensional sets by associating each image pixel with an elevation proportional to its intensity level. An object of known shape and size, called the structuring element, is then used to investigate the morphology of the input set. This is achieved by positioning the origin of the structuring element to every possible position of the space and testing, for each position, whether the structuring element either is included or has a nonempty intersection with the studied set. The shape and size of the structuring element must be selected according to the morphology of the searched image structures. Other two feature extraction techniques were used, eCognition and ENVI module SW, in order to compare the results. These techniques were applied to different archaeological sites in Turkmenistan (Nisa) and in Iraq (Babylon); a further change detection analysis was applied to the Babylon site using two HR images as a pre-post second gulf war. We had different results or outputs, taking into consideration the fact that the operative scale of sensed data determines the final result of the elaboration and the output of the information quality, because each of them was sensitive to specific shapes in each input image, we had mapped linear and nonlinear objects, updating archaeological cartography, automatic change detection analysis for the Babylon site. The discussion of these techniques has the objective to provide the archaeological team with new instruments for the orientation and the planning of a remote sensing application.

NMR studies of protein-nucleic acid interactions.

PubMed

Varani, Gabriele; Chen, Yu; Leeper, Thomas C

2004-01-01

Protein-DNA and protein-RNA complexes play key functional roles in every living organism. Therefore, the elucidation of their structure and dynamics is an important goal of structural and molecular biology. Nuclear magnetic resonance (NMR) studies of protein and nucleic acid complexes have common features with studies of protein-protein complexes: the interaction surfaces between the molecules must be carefully delineated, the relative orientation of the two species needs to be accurately and precisely determined, and close intermolecular contacts defined by nuclear Overhauser effects (NOEs) must be obtained. However, differences in NMR properties (e.g., chemical shifts) and biosynthetic pathways for sample productions generate important differences. Chemical shift differences between the protein and nucleic acid resonances can aid the NMR structure determination process; however, the relatively limited dispersion of the RNA ribose resonances makes the process of assigning intermolecular NOEs more difficult. The analysis of the resulting structures requires computational tools unique to nucleic acid interactions. This chapter summarizes the most important elements of the structure determination by NMR of protein-nucleic acid complexes and their analysis. The main emphasis is on recent developments (e.g., residual dipolar couplings and new Web-based analysis tools) that have facilitated NMR studies of these complexes and expanded the type of biological problems to which NMR techniques of structural elucidation can now be applied.

Spatial Heterogeneity as a Genetic Mixing Mechanism in Highly Philopatric Colonial Seabirds

PubMed Central

Cristofari, Robin; Trucchi, Emiliano; Whittington, Jason D.; Vigetta, Stéphanie; Gachot-Neveu, Hélène; Stenseth, Nils Christian; Le Maho, Yvon; Le Bohec, Céline

2015-01-01

How genetic diversity is maintained in philopatric colonial systems remains unclear, and understanding the dynamic balance of philopatry and dispersal at all spatial scales is essential to the study of the evolution of coloniality. In the King penguin, Aptenodytes patagonicus, return rates of post-fledging chicks to their natal sub-colony are remarkably high. Empirical studies have shown that adults return year after year to their previous breeding territories within a radius of a few meters. Yet, little reliable data are available on intra- and inter-colonial dispersal in this species. Here, we present the first fine-scale study of the genetic structure in a king penguin colony in the Crozet Archipelago. Samples were collected from individual chicks and analysed at 8 microsatellite loci. Precise geolocation data of hatching sites and selective pressures associated with habitat features were recorded for all sampling locations. We found that despite strong natal and breeding site fidelity, king penguins retain a high degree of panmixia and genetic diversity. Yet, genetic structure appears markedly heterogeneous across the colony, with higher-than-expected inbreeding levels, and local inbreeding and relatedness hotspots that overlap predicted higher-quality nesting locations. This points towards heterogeneous population structure at the sub-colony level, in which fine-scale environmental features drive local philopatric behaviour, while lower-quality patches may act as genetic mixing mechanisms at the colony level. These findings show how a lack of global genetic structuring can emerge from small-scale heterogeneity in ecological parameters, as opposed to the classical model of homogeneous dispersal. Our results also emphasize the importance of sampling design for estimation of population parameters in colonial seabirds, as at high spatial resolution, basic genetic features are shown to be location-dependent. Finally, this study stresses the importance of understanding intra-colonial dispersal and genetic mixing mechanisms in order to better estimate species-wide gene flows and population dynamics. PMID:25680103

Spatial heterogeneity as a genetic mixing mechanism in highly philopatric colonial seabirds.

PubMed

Cristofari, Robin; Trucchi, Emiliano; Whittington, Jason D; Vigetta, Stéphanie; Gachot-Neveu, Hélène; Stenseth, Nils Christian; Le Maho, Yvon; Le Bohec, Céline

2015-01-01

How genetic diversity is maintained in philopatric colonial systems remains unclear, and understanding the dynamic balance of philopatry and dispersal at all spatial scales is essential to the study of the evolution of coloniality. In the King penguin, Aptenodytes patagonicus, return rates of post-fledging chicks to their natal sub-colony are remarkably high. Empirical studies have shown that adults return year after year to their previous breeding territories within a radius of a few meters. Yet, little reliable data are available on intra- and inter-colonial dispersal in this species. Here, we present the first fine-scale study of the genetic structure in a king penguin colony in the Crozet Archipelago. Samples were collected from individual chicks and analysed at 8 microsatellite loci. Precise geolocation data of hatching sites and selective pressures associated with habitat features were recorded for all sampling locations. We found that despite strong natal and breeding site fidelity, king penguins retain a high degree of panmixia and genetic diversity. Yet, genetic structure appears markedly heterogeneous across the colony, with higher-than-expected inbreeding levels, and local inbreeding and relatedness hotspots that overlap predicted higher-quality nesting locations. This points towards heterogeneous population structure at the sub-colony level, in which fine-scale environmental features drive local philopatric behaviour, while lower-quality patches may act as genetic mixing mechanisms at the colony level. These findings show how a lack of global genetic structuring can emerge from small-scale heterogeneity in ecological parameters, as opposed to the classical model of homogeneous dispersal. Our results also emphasize the importance of sampling design for estimation of population parameters in colonial seabirds, as at high spatial resolution, basic genetic features are shown to be location-dependent. Finally, this study stresses the importance of understanding intra-colonial dispersal and genetic mixing mechanisms in order to better estimate species-wide gene flows and population dynamics.

The structure of people's hair.

PubMed

Yang, Fei-Chi; Zhang, Yuchen; Rheinstädter, Maikel C

2014-01-01

Hair is a filamentous biomaterial consisting mainly of proteins in particular keratin. The structure of human hair is well known: the medulla is a loosely packed, disordered region near the centre of the hair surrounded by the cortex, which contains the major part of the fibre mass, mainly consisting of keratin proteins and structural lipids. The cortex is surrounded by the cuticle, a layer of dead, overlapping cells forming a protective layer around the hair. The corresponding structures have been studied extensively using a variety of different techniques, such as light, electron and atomic force microscopes, and also X-ray diffraction. We were interested in the question how much the molecular hair structure differs from person to person, between male and female hair, hair of different appearances such as colour and waviness. We included hair from parent and child, identical and fraternal twins in the study to see if genetically similar hair would show similar structural features. The molecular structure of the hair samples was studied using high-resolution X-ray diffraction, which covers length scales from molecules up to the organization of secondary structures. Signals due to the coiled-coil phase of α-helical keratin proteins, intermediate keratin filaments in the cortex and from the lipid layers in the cell membrane complex were observed in the specimen of all individuals, with very small deviations. Despite the relatively small number of individuals (12) included in this study, some conclusions can be drawn. While the general features were observed in all individuals and the corresponding molecular structures were almost identical, additional signals were observed in some specimen and assigned to different types of lipids in the cell membrane complex. Genetics seem to play a role in this composition as identical patterns were observed in hair from father and daughter and identical twins, however, not for fraternal twins. Identification and characterization of these features is an important step towards the detection of abnormalities in the molecular structure of hair as a potential diagnostic tool for certain diseases.

NMRDSP: an accurate prediction of protein shape strings from NMR chemical shifts and sequence data.

PubMed

Mao, Wusong; Cong, Peisheng; Wang, Zhiheng; Lu, Longjian; Zhu, Zhongliang; Li, Tonghua

2013-01-01

Shape string is structural sequence and is an extremely important structure representation of protein backbone conformations. Nuclear magnetic resonance chemical shifts give a strong correlation with the local protein structure, and are exploited to predict protein structures in conjunction with computational approaches. Here we demonstrate a novel approach, NMRDSP, which can accurately predict the protein shape string based on nuclear magnetic resonance chemical shifts and structural profiles obtained from sequence data. The NMRDSP uses six chemical shifts (HA, H, N, CA, CB and C) and eight elements of structure profiles as features, a non-redundant set (1,003 entries) as the training set, and a conditional random field as a classification algorithm. For an independent testing set (203 entries), we achieved an accuracy of 75.8% for S8 (the eight states accuracy) and 87.8% for S3 (the three states accuracy). This is higher than only using chemical shifts or sequence data, and confirms that the chemical shift and the structure profile are significant features for shape string prediction and their combination prominently improves the accuracy of the predictor. We have constructed the NMRDSP web server and believe it could be employed to provide a solid platform to predict other protein structures and functions. The NMRDSP web server is freely available at http://cal.tongji.edu.cn/NMRDSP/index.jsp.

Principles for Predicting RNA Secondary Structure Design Difficulty.

PubMed

Anderson-Lee, Jeff; Fisker, Eli; Kosaraju, Vineet; Wu, Michelle; Kong, Justin; Lee, Jeehyung; Lee, Minjae; Zada, Mathew; Treuille, Adrien; Das, Rhiju

2016-02-27

Designing RNAs that form specific secondary structures is enabling better understanding and control of living systems through RNA-guided silencing, genome editing and protein organization. Little is known, however, about which RNA secondary structures might be tractable for downstream sequence design, increasing the time and expense of design efforts due to inefficient secondary structure choices. Here, we present insights into specific structural features that increase the difficulty of finding sequences that fold into a target RNA secondary structure, summarizing the design efforts of tens of thousands of human participants and three automated algorithms (RNAInverse, INFO-RNA and RNA-SSD) in the Eterna massive open laboratory. Subsequent tests through three independent RNA design algorithms (NUPACK, DSS-Opt and MODENA) confirmed the hypothesized importance of several features in determining design difficulty, including sequence length, mean stem length, symmetry and specific difficult-to-design motifs such as zigzags. Based on these results, we have compiled an Eterna100 benchmark of 100 secondary structure design challenges that span a large range in design difficulty to help test future efforts. Our in silico results suggest new routes for improving computational RNA design methods and for extending these insights to assess "designability" of single RNA structures, as well as of switches for in vitro and in vivo applications. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Structural Biology of Non-Ribosomal Peptide Synthetases

PubMed Central

Miller, Bradley R.; Gulick, Andrew M.

2016-01-01

Summary The non-ribosomal peptide synthetases are modular enzymes that catalyze synthesis of important peptide products from a variety of standard and non-proteinogenic amino acid substrates. Within a single module are multiple catalytic domains that are responsible for incorporation of a single residue. After the amino acid is activated and covalently attached to an integrated carrier protein domain, the substrates and intermediates are delivered to neighboring catalytic domains for peptide bond formation or, in some modules, chemical modification. In the final module, the peptide is delivered to a terminal thioesterase domain that catalyzes release of the peptide product. This multi-domain modular architecture raises questions about the structural features that enable this assembly line synthesis in an efficient manner. The structures of the core component domains have been determined and demonstrate insights into the catalytic activity. More recently, multi-domain structures have been determined and are providing clues to the features of these enzyme systems that govern the functional interaction between multiple domains. This chapter describes the structures of NRPS proteins and the strategies that are being used to assist structural studies of these dynamic proteins, including careful consideration of domain boundaries for generation of truncated proteins and the use of mechanism-based inhibitors that trap interactions between the catalytic and carrier protein domains. PMID:26831698

Morphometric analysis of astrocytes in brainstem respiratory regions.

PubMed

Sheikhbahaei, Shahriar; Morris, Brian; Collina, Jared; Anjum, Sommer; Znati, Sami; Gamarra, Julio; Zhang, Ruli; Gourine, Alexander V; Smith, Jeffrey C

2018-06-11

Astrocytes, the most abundant and structurally complex glial cells of the central nervous system, are proposed to play an important role in modulating the activities of neuronal networks, including respiratory rhythm-generating circuits of the preBötzinger complex (preBötC) located in the ventrolateral medulla of the brainstem. However, structural properties of astrocytes residing within different brainstem regions are unknown. In this study astrocytes in the preBötC, an intermediate reticular formation (IRF) region with respiratory-related function, and a region of the nucleus tractus solitarius (NTS) in adult rats were reconstructed and their morphological features were compared. Detailed morphological analysis revealed that preBötC astrocytes are structurally more complex than those residing within the functionally distinct neighboring IRF region, or the NTS, located at the dorsal aspect of the medulla oblongata. Structural analyses of the brainstem microvasculature indicated no significant regional differences in vascular properties. We hypothesize that high morphological complexity of preBötC astrocytes reflects their functional role in providing structural/metabolic support and modulation of the key neuronal circuits essential for breathing, as well as constraints imposed by arrangements of associated neurons and/or other local structural features of the brainstem parenchyma. This article is protected by copyright. All rights reserved. © 2018 Wiley Periodicals, Inc.

SMOG 2: A Versatile Software Package for Generating Structure-Based Models.

PubMed

Noel, Jeffrey K; Levi, Mariana; Raghunathan, Mohit; Lammert, Heiko; Hayes, Ryan L; Onuchic, José N; Whitford, Paul C

2016-03-01

Molecular dynamics simulations with coarse-grained or simplified Hamiltonians have proven to be an effective means of capturing the functionally important long-time and large-length scale motions of proteins and RNAs. Originally developed in the context of protein folding, structure-based models (SBMs) have since been extended to probe a diverse range of biomolecular processes, spanning from protein and RNA folding to functional transitions in molecular machines. The hallmark feature of a structure-based model is that part, or all, of the potential energy function is defined by a known structure. Within this general class of models, there exist many possible variations in resolution and energetic composition. SMOG 2 is a downloadable software package that reads user-designated structural information and user-defined energy definitions, in order to produce the files necessary to use SBMs with high performance molecular dynamics packages: GROMACS and NAMD. SMOG 2 is bundled with XML-formatted template files that define commonly used SBMs, and it can process template files that are altered according to the needs of each user. This computational infrastructure also allows for experimental or bioinformatics-derived restraints or novel structural features to be included, e.g. novel ligands, prosthetic groups and post-translational/transcriptional modifications. The code and user guide can be downloaded at http://smog-server.org/smog2.

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

PubMed Central

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

2011-01-01

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

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

PubMed

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

2011-01-01

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

Substrate-bound Crystal Structures Reveal Features Unique to Mycobacterium tuberculosis N-Acetyl-glucosamine 1-Phosphate Uridyltransferase and a Catalytic Mechanism for Acetyl Transfer

PubMed Central

Jagtap, Pravin Kumar Ankush; Soni, Vijay; Vithani, Neha; Jhingan, Gagan Deep; Bais, Vaibhav Singh; Nandicoori, Vinay Kumar; Prakash, Balaji

2012-01-01

N-Acetyl-glucosamine-1-phosphate uridyltransferase (GlmU), a bifunctional enzyme involved in bacterial cell wall synthesis is exclusive to prokaryotes. GlmU, now recognized as a promising target to develop new antibacterial drugs, catalyzes two key reactions: acetyl transfer and uridyl transfer at two independent domains. Hitherto, we identified GlmU from Mycobacterium tuberculosis (GlmUMtb) to be unique in possessing a 30-residue extension at the C terminus. Here, we present the crystal structures of GlmUMtb in complex with substrates/products bound at the acetyltransferase active site. Analysis of these and mutational data, allow us to infer a catalytic mechanism operative in GlmUMtb. In this SN2 reaction, His-374 and Asn-397 act as catalytic residues by enhancing the nucleophilicity of the attacking amino group of glucosamine 1-phosphate. Ser-416 and Trp-460 provide important interactions for substrate binding. A short helix at the C-terminal extension uniquely found in mycobacterial GlmU provides the highly conserved Trp-460 for substrate binding. Importantly, the structures reveal an uncommon mode of acetyl-CoA binding in GlmUMtb; we term this the U conformation, which is distinct from the L conformation seen in the available non-mycobacterial GlmU structures. Residues, likely determining U/L conformation, were identified, and their importance was evaluated. In addition, we identified that the primary site for PknB-mediated phosphorylation is Thr-418, near the acetyltransferase active site. Down-regulation of acetyltransferase activity upon Thr-418 phosphorylation is rationalized by the structures presented here. Overall, this work provides an insight into substrate recognition, catalytic mechanism for acetyl transfer, and features unique to GlmUMtb, which may be exploited for the development of inhibitors specific to GlmU. PMID:22969087

Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines

PubMed Central

2010-01-01

Background Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods have motivated the development of computational methods for predicting PPIs. As protein interactions generally occur via domains instead of the whole molecules, predicting domain-domain interaction (DDI) is an important step toward PPI prediction. Computational methods developed so far have utilized information from various sources at different levels, from primary sequences, to molecular structures, to evolutionary profiles. Results In this paper, we propose a computational method to predict DDI using support vector machines (SVMs), based on domains represented as interaction profile hidden Markov models (ipHMM) where interacting residues in domains are explicitly modeled according to the three dimensional structural information available at the Protein Data Bank (PDB). Features about the domains are extracted first as the Fisher scores derived from the ipHMM and then selected using singular value decomposition (SVD). Domain pairs are represented by concatenating their selected feature vectors, and classified by a support vector machine trained on these feature vectors. The method is tested by leave-one-out cross validation experiments with a set of interacting protein pairs adopted from the 3DID database. The prediction accuracy has shown significant improvement as compared to InterPreTS (Interaction Prediction through Tertiary Structure), an existing method for PPI prediction that also uses the sequences and complexes of known 3D structure. Conclusions We show that domain-domain interaction prediction can be significantly enhanced by exploiting information inherent in the domain profiles via feature selection based on Fisher scores, singular value decomposition and supervised learning based on support vector machines. Datasets and source code are freely available on the web at http://liao.cis.udel.edu/pub/svdsvm. Implemented in Matlab and supported on Linux and MS Windows. PMID:21034480

Modeling the future evolution of the virtual water trade network: A combination of network and gravity models

NASA Astrophysics Data System (ADS)

Sartori, Martina; Schiavo, Stefano; Fracasso, Andrea; Riccaboni, Massimo

2017-12-01

The paper investigates how the topological features of the virtual water (VW) network and the size of the associated VW flows are likely to change over time, under different socio-economic and climate scenarios. We combine two alternative models of network formation -a stochastic and a fitness model, used to describe the structure of VW flows- with a gravity model of trade to predict the intensity of each bilateral flow. This combined approach is superior to existing methodologies in its ability to replicate the observed features of VW trade. The insights from the models are used to forecast future VW flows in 2020 and 2050, under different climatic scenarios, and compare them with future water availability. Results suggest that the current trend of VW exports is not sustainable for all countries. Moreover, our approach highlights that some VW importers might be exposed to "imported water stress" as they rely heavily on imports from countries whose water use is unsustainable.

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.

Ultraviolet spectral reflectance of carbonaceous materials

NASA Astrophysics Data System (ADS)

Applin, Daniel M.; Izawa, Matthew R. M.; Cloutis, Edward A.; Gillis-Davis, Jeffrey J.; Pitman, Karly M.; Roush, Ted L.; Hendrix, Amanda R.; Lucey, Paul G.

2018-06-01

A number of planetary spacecraft missions have carried instruments with sensors covering the ultraviolet (UV) wavelength range. However, there exists a general lack of relevant UV reflectance laboratory data to compare against these planetary surface remote sensing observations in order to make confident material identifications. To address this need, we have systematically analyzed reflectance spectra of carbonaceous materials in the 200-500 nm spectral range, and found spectral-compositional-structural relationships that suggest this wavelength region could distinguish between otherwise difficult-to-identify carbon phases. In particular (and by analogy with the infrared spectral region), large changes over short wavelength intervals in the refractive indices associated with the trigonal sp2π-π* transition of carbon can lead to Fresnel peaks and Christiansen-like features in reflectance. Previous studies extending to shorter wavelengths also show that anomalous dispersion caused by the σ-σ* transition associated with both the trigonal sp2 and tetrahedral sp3 sites causes these features below λ = 200 nm. The peak wavelength positions and shapes of π-π* and σ-σ* features contain information on sp3/sp2, structure, crystallinity, and powder grain size. A brief comparison with existing observational data indicates that the carbon fraction of the surface of Mercury is likely amorphous and submicroscopic, as is that on the surface of the martian satellites Phobos and Deimos, and possibly comet 67P/Churyumov-Gerasimenko, while further coordinated observations and laboratory experiments should refine these feature assignments and compositional hypotheses. The new laboratory diffuse reflectance data reported here provide an important new resource for interpreting UV reflectance measurements from planetary surfaces throughout the solar system, and confirm that the UV can be rich in important spectral information.

Experimental validation of a structural damage detection method based on marginal Hilbert spectrum

NASA Astrophysics Data System (ADS)

Banerji, Srishti; Roy, Timir B.; Sabamehr, Ardalan; Bagchi, Ashutosh

2017-04-01

Structural Health Monitoring (SHM) using dynamic characteristics of structures is crucial for early damage detection. Damage detection can be performed by capturing and assessing structural responses. Instrumented structures are monitored by analyzing the responses recorded by deployed sensors in the form of signals. Signal processing is an important tool for the processing of the collected data to diagnose anomalies in structural behavior. The vibration signature of the structure varies with damage. In order to attain effective damage detection, preservation of non-linear and non-stationary features of real structural responses is important. Decomposition of the signals into Intrinsic Mode Functions (IMF) by Empirical Mode Decomposition (EMD) and application of Hilbert-Huang Transform (HHT) addresses the time-varying instantaneous properties of the structural response. The energy distribution among different vibration modes of the intact and damaged structure depicted by Marginal Hilbert Spectrum (MHS) detects location and severity of the damage. The present work investigates damage detection analytically and experimentally by employing MHS. The testing of this methodology for different damage scenarios of a frame structure resulted in its accurate damage identification. The sensitivity of Hilbert Spectral Analysis (HSA) is assessed with varying frequencies and damage locations by means of calculating Damage Indices (DI) from the Hilbert spectrum curves of the undamaged and damaged structures.

Single-particle mapping of nonequilibrium nanocrystal transformations

DOE PAGES

Ye, Xingchen; Jones, Matthew R.; Frechette, Layne B.; ...

2016-11-18

Chemists have developed mechanistic insight into numerous chemical reactions by thoroughly characterizing nonequilibrium species. Although methods to probe these processes are well established for molecules, analogous techniques for understanding intermediate structures in nanomaterials have been lacking. For this study, we monitor the shape evolution of individual anisotropic gold nanostructures as they are oxidatively etched in a graphene liquid cell with a controlled redox environment. Short-lived, nonequilibrium nanocrystals are observed, structurally analyzed, and rationalized through Monte Carlo simulations. Understanding these reaction trajectories provides important fundamental insight connecting high-energy nanocrystal morphologies to the development of kinetically stabilized surface features and demonstrates themore » importance of developing tools capable of probing short-lived nanoscale species at the single-particle level.« less

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

Apte, A; Veeraraghavan, H; Oh, J

Purpose: To present an open source and free platform to facilitate radiomics research — The “Radiomics toolbox” in CERR. Method: There is scarcity of open source tools that support end-to-end modeling of image features to predict patient outcomes. The “Radiomics toolbox” strives to fill the need for such a software platform. The platform supports (1) import of various kinds of image modalities like CT, PET, MR, SPECT, US. (2) Contouring tools to delineate structures of interest. (3) Extraction and storage of image based features like 1st order statistics, gray-scale co-occurrence and zonesize matrix based texture features and shape features andmore » (4) Statistical Analysis. Statistical analysis of the extracted features is supported with basic functionality that includes univariate correlations, Kaplan-Meir curves and advanced functionality that includes feature reduction and multivariate modeling. The graphical user interface and the data management are performed with Matlab for the ease of development and readability of code and features for wide audience. Open-source software developed with other programming languages is integrated to enhance various components of this toolbox. For example: Java-based DCM4CHE for import of DICOM, R for statistical analysis. Results: The Radiomics toolbox will be distributed as an open source, GNU copyrighted software. The toolbox was prototyped for modeling Oropharyngeal PET dataset at MSKCC. The analysis will be presented in a separate paper. Conclusion: The Radiomics Toolbox provides an extensible platform for extracting and modeling image features. To emphasize new uses of CERR for radiomics and image-based research, we have changed the name from the “Computational Environment for Radiotherapy Research” to the “Computational Environment for Radiological Research”.« less

Nanoscale Morphology to Macroscopic Performance in Ultra High Molecular Weight Polyethylene Fibers

NASA Astrophysics Data System (ADS)

McDaniel, Preston B.

Ultra high molecular weight polyethylene (UHMWPE) fibers are increasingly used in high -performance applications where strength, stiffness, and the ability to dissipate energy are of critical importance. Despite their use in a variety of applications, the influence of morphological features at the meso/nanoscale on the macroscopic performance of the fibers has not been well understood. There is particular interest in gaining a better understanding of the nanoscale structure-property relationships in UHMWPE fibers used in ballistics applications. In order to accurately model and predict failure in the fiber, a more complete understanding of the complex load pathways that dictate the ways in which load is transferred through the fiber, across interfaces and length scales is required. The goal of the work discussed herein is to identify key meso/nanostructural features evolved in high performance fibers and determine how these features influence the performance of the fiber through a variety of different loading mechanisms. The important structural features in high-performance UHMWPE fibers are first identified through examination of the meso/nanostructure of a series of fibers with different processing conditions. This is achieved primarily through the use of wide-angle x-ray diffraction (WAXD) and atomic force microscopy (AFM). Analysis of AFM images and WAXD data allows identification and quantifications of important structural features at these length scales. Key meso/nanostructural features are then examined with respect to their influence on the transverse compression behavior of single fibers. Through post-mortem AFM analysis of samples at incremental compressive strains, the evolution of damage is examined and compared with macroscopic fiber mechanical response. It was found that collapse of mesoscale voids, followed by nanoscale fibrillation and reorganization of a fibrillar network has a significant influence on the mechanical response of the fiber. Through this work, the importance of nanoscale fibril adhesive interactions is highlighted. However, very little information exists in the literature as to the nature and magnitude of these interactions. Examination of nanoscale fibrillar adhesive interactions is experimentally difficult, and necessitated the development of an AFM based nanoscale splitting technique to quantify the interactions between fibrils. Through analysis of split geometry and careful partitioning of energies, the adhesive energy between fibrils in UHMWPE fibers are determined. The calculated average adhesive energies are significantly larger than the estimated energy due to van der Waals interactions, suggesting that there are physical connections (e.g., tie chains, tie fibrils, and lamellar crystalline bridges) that influence the interactions between fibrils. The interactions identified through this work are believed to be responsible for the creation of load pathways across fibril interfaces where load may be translated through the fiber in tension, compression, and shear. Finally, the nature of the mesoscale fibrillar network is explored through the development of a variable angle, single fiber peel test. This peel test enables the quantification of Mode I and Mode II peel energies. The modes of deformation observed in the peel test are representative of the mechanisms experienced during tensile and transverse compression loading. The quantification of peel energies in both Mode I and Mode II failure highlight the importance of the fibrillar network as a key mechanism for the translation of load through the fiber. In both modes of failure, the fibril network acts as a framework for the orientation and subsequent failure of nanoscale fibrils.

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.

Statistical molecular design of balanced compound libraries for QSAR modeling.

PubMed

Linusson, A; Elofsson, M; Andersson, I E; Dahlgren, M K

2010-01-01

A fundamental step in preclinical drug development is the computation of quantitative structure-activity relationship (QSAR) models, i.e. models that link chemical features of compounds with activities towards a target macromolecule associated with the initiation or progression of a disease. QSAR models are computed by combining information on the physicochemical and structural features of a library of congeneric compounds, typically assembled from two or more building blocks, and biological data from one or more in vitro assays. Since the models provide information on features affecting the compounds' biological activity they can be used as guides for further optimization. However, in order for a QSAR model to be relevant to the targeted disease, and drug development in general, the compound library used must contain molecules with balanced variation of the features spanning the chemical space believed to be important for interaction with the biological target. In addition, the assays used must be robust and deliver high quality data that are directly related to the function of the biological target and the associated disease state. In this review, we discuss and exemplify the concept of statistical molecular design (SMD) in the selection of building blocks and final synthetic targets (i.e. compounds to synthesize) to generate information-rich, balanced libraries for biological testing and computation of QSAR models.

Statistical universals reveal the structures and functions of human music.

PubMed

Savage, Patrick E; Brown, Steven; Sakai, Emi; Currie, Thomas E

2015-07-21

Music has been called "the universal language of mankind." Although contemporary theories of music evolution often invoke various musical universals, the existence of such universals has been disputed for decades and has never been empirically demonstrated. Here we combine a music-classification scheme with statistical analyses, including phylogenetic comparative methods, to examine a well-sampled global set of 304 music recordings. Our analyses reveal no absolute universals but strong support for many statistical universals that are consistent across all nine geographic regions sampled. These universals include 18 musical features that are common individually as well as a network of 10 features that are commonly associated with one another. They span not only features related to pitch and rhythm that are often cited as putative universals but also rarely cited domains including performance style and social context. These cross-cultural structural regularities of human music may relate to roles in facilitating group coordination and cohesion, as exemplified by the universal tendency to sing, play percussion instruments, and dance to simple, repetitive music in groups. Our findings highlight the need for scientists studying music evolution to expand the range of musical cultures and musical features under consideration. The statistical universals we identified represent important candidates for future investigation.

Statistical universals reveal the structures and functions of human music

PubMed Central

Savage, Patrick E.; Brown, Steven; Sakai, Emi; Currie, Thomas E.

2015-01-01

Music has been called “the universal language of mankind.” Although contemporary theories of music evolution often invoke various musical universals, the existence of such universals has been disputed for decades and has never been empirically demonstrated. Here we combine a music-classification scheme with statistical analyses, including phylogenetic comparative methods, to examine a well-sampled global set of 304 music recordings. Our analyses reveal no absolute universals but strong support for many statistical universals that are consistent across all nine geographic regions sampled. These universals include 18 musical features that are common individually as well as a network of 10 features that are commonly associated with one another. They span not only features related to pitch and rhythm that are often cited as putative universals but also rarely cited domains including performance style and social context. These cross-cultural structural regularities of human music may relate to roles in facilitating group coordination and cohesion, as exemplified by the universal tendency to sing, play percussion instruments, and dance to simple, repetitive music in groups. Our findings highlight the need for scientists studying music evolution to expand the range of musical cultures and musical features under consideration. The statistical universals we identified represent important candidates for future investigation. PMID:26124105

Evaluating Measurement of Dynamic Constructs: Defining a Measurement Model of Derivatives

PubMed Central

Estabrook, Ryne

2015-01-01

While measurement evaluation has been embraced as an important step in psychological research, evaluating measurement structures with longitudinal data is fraught with limitations. This paper defines and tests a measurement model of derivatives (MMOD), which is designed to assess the measurement structure of latent constructs both for analyses of between-person differences and for the analysis of change. Simulation results indicate that MMOD outperforms existing models for multivariate analysis and provides equivalent fit to data generation models. Additional simulations show MMOD capable of detecting differences in between-person and within-person factor structures. Model features, applications and future directions are discussed. PMID:24364383

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 structures of good anti radical and antioxidant phenols and anilines are defined. The obtained good correlations imply that measuring anti DPPH activity can be used as a simple predictive test for the anti hydroxyl and peroxyl radical, and antioxidant activities. Kinetic measurements showed that strong antioxidants with high activity have also high reaction rates indicating that factors stabilizing the phenoxyl radicals lower also the activation energy of the hydrogen transfer process. PMID:23497653

Study of Comets Composition and Structure

NASA Astrophysics Data System (ADS)

Khalaf, S. Z.; Selman, A. A.; Ali, H. S.

2008-12-01

The present paper focuses on the nature of the different interactions between cometary nucleus and tail with solar wind. The dynamics of the comet will impose many features that provide unique behavior of the comet when entering the solar system. These features are reviewed in this paper and few investigations are made. The calculations made in this work represent the analysis and interpretation of the different features of the comet, such as perihelion and eccentricity dependence on the gas production rate, and the dependence of the latter on the composition of the comet nucleus. The dependences of the heliocentric, bow shock, contact surface, and stand-off distances with gas production rate for many types of comets that cover linear and non-linear types are studied in this work. Important results are obtained which indicated the different physical interactions between cometary ions and solar wind. Furthermore, the important relation between mean molecular weight and gas production rate are analyzed and studied in this work and a conclusion is made that, as the gas production rate increases, the mean molecular weight will decrease exponentially. A detailed discussion for this unique relation is given.

Positional Accuracy in Optical Trap-Assisted Nanolithography

NASA Astrophysics Data System (ADS)

Arnold, Craig B.; McLeod, Euan

2009-03-01

The ability to directly print patterns on size scales below 100 nm is important for many applications where the production or repair of high resolution and density features are important. Laser-based direct-write methods have the benefit of quickly and easily being able to modify and create structures on existing devices, but feature sizes are conventionally limited by diffraction. In this presentation, we show how to overcome this limit with a new method of probe-based near-field nanopatterning in which we employ a CW laser to optically trap and manipulate dispersed microspheres against a substrate using a 2-d Bessel beam optical trap. A secondary, pulsed nanosecond laser at 355 nm is directed through the bead and used to modify the surface below the microsphere, taking advantage of the near-field enhancement in order to produce materials modification with feature sizes under 100 nm. Here, we analyze the 3-d positioning accuracy of the microsphere through analytic modeling as a function of experimental parameters. The model is verified in all directions for our experimental conditions and is used to predict the conditions required for improved positional accuracy.

Linearized texture of three-dimensional extracellular matrix is mandatory for bladder cancer cell invasion.

PubMed

Alfano, Massimo; Nebuloni, Manuela; Allevi, Raffaele; Zerbi, Pietro; Longhi, Erika; Lucianò, Roberta; Locatelli, Irene; Pecoraro, Angela; Indrieri, Marco; Speziali, Chantal; Doglioni, Claudio; Milani, Paolo; Montorsi, Francesco; Salonia, Andrea

2016-10-25

In the fields of biomaterials and tissue engineering simulating the native microenvironment is of utmost importance. As a major component of the microenvironment, the extracellular matrix (ECM) contributes to tissue homeostasis, whereas modifications of native features are associated with pathological conditions. Furthermore, three-dimensional (3D) geometry is an important feature of synthetic scaffolds favoring cell stemness, maintenance and differentiation. We analyzed the 3D structure, geometrical measurements and anisotropy of the ECM isolated from (i) human bladder mucosa (basal lamina and lamina propria) and muscularis propria; and, (ii) bladder carcinoma (BC). Next, binding and invasion of bladder metastatic cell line was observed on synthetic scaffold recapitulating anisotropy of tumoral ECM, but not on scaffold with disorganized texture typical of non-neoplastic lamina propria. This study provided information regarding the ultrastructure and geometry of healthy human bladder and BC ECMs. Likewise, using synthetic scaffolds we identified linearization of the texture as a mandatory feature for BC cell invasion. Integrating microstructure and geometry with biochemical and mechanical factors could support the development of an innovative synthetic bladder substitute or a tumoral scaffold predictive of chemotherapy outcomes.

The external morphology of adult female Egrasilus labracis as shown using hexamethyldisilazane treated, uncoated specimens for scanning electron microscopy.

PubMed

Murray, Harry M; Hill, Stephen J; Ang, Keng P

2016-07-01

The description and application of a modified Scanning Electron Microscope preparation technique using hexamethyldisilazane for small parasitic copepods was demonstrated though a high resolution depiction of individuals of Ergasilus labracis sampled from three spined stickleback (Gasterosteus aculeatus) in Bay D'Espoir, Newfoundland during summer 2015 and from archival samples retrieved from Atlantic salmon par (Salmo salar) stored at the Atlantic reference centre, St. Andrews, New Brunswick. The specimens were very well preserved showing high quality detail of important features and verifying those previously described using light microscopy by Hogans. Additionally the technique allowed excellent in situ demonstrations of mouth parts, swimming legs, and unusual and previously undescribed features of the second antenna including prominent striations and pore-like structures found to define the claw. It is thought that this technique will become a quick and efficient tool for describing important taxonomic features of small parasitic copepods like E. labracis or other similar small aquatic organisms. Microsc. Res. Tech. 79:657-663, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Optical coherence tomography used for internal biometrics

NASA Astrophysics Data System (ADS)

Chang, Shoude; Sherif, Sherif; Mao, Youxin; Flueraru, Costel

2007-06-01

Traditional biometric technologies used for security and person identification essentially deal with fingerprints, hand geometry and face images. However, because all these technologies use external features of human body, they can be easily fooled and tampered with by distorting, modifying or counterfeiting these features. Nowadays, internal biometrics which detects the internal ID features of an object is becoming increasingly important. Being capable of exploring under-skin structure, optical coherence tomography (OCT) system can be used as a powerful tool for internal biometrics. We have applied fiber-optic and full-field OCT systems to detect the multiple-layer 2D images and 3D profile of the fingerprints, which eventually result in a higher discrimination than the traditional 2D recognition methods. More importantly, the OCT based fingerprint recognition has the ability to easily distinguish artificial fingerprint dummies by analyzing the extracted layered surfaces. Experiments show that our OCT systems successfully detected the dummy, which was made of plasticene and was used to bypass the commercially available fingerprint scanning system with a false accept rate (FAR) of 100%.

Efficient iris recognition by characterizing key local variations.

PubMed

Ma, Li; Tan, Tieniu; Wang, Yunhong; Zhang, Dexin

2004-06-01

Unlike other biometrics such as fingerprints and face, the distinct aspect of iris comes from randomly distributed features. This leads to its high reliability for personal identification, and at the same time, the difficulty in effectively representing such details in an image. This paper describes an efficient algorithm for iris recognition by characterizing key local variations. The basic idea is that local sharp variation points, denoting the appearing or vanishing of an important image structure, are utilized to represent the characteristics of the iris. The whole procedure of feature extraction includes two steps: 1) a set of one-dimensional intensity signals is constructed to effectively characterize the most important information of the original two-dimensional image; 2) using a particular class of wavelets, a position sequence of local sharp variation points in such signals is recorded as features. We also present a fast matching scheme based on exclusive OR operation to compute the similarity between a pair of position sequences. Experimental results on 2255 iris images show that the performance of the proposed method is encouraging and comparable to the best iris recognition algorithm found in the current literature.

Processing technology for high efficiency silicon solar cells

NASA Technical Reports Server (NTRS)

Spitzer, M. B.; Keavney, C. J.

1985-01-01

Recent advances in silicon solar cell processing have led to attainment of conversion efficiency approaching 20%. The basic cell design is investigated and features of greatest importance to achievement of 20% efficiency are indicated. Experiments to separately optimize high efficiency design features in test structures are discussed. The integration of these features in a high efficiency cell is examined. Ion implantation has been used to achieve optimal concentrations of emitter dopant and junction depth. The optimization reflects the trade-off between high sheet conductivity, necessary for high fill factor, and heavy doping effects, which must be minimized for high open circuit voltage. A second important aspect of the design experiments is the development of a passivation process to minimize front surface recombination velocity. The manner in which a thin SiO2 layer may be used for this purpose is indicated without increasing reflection losses, if the antireflection coating is properly designed. Details are presented of processing intended to reduce recombination at the contact/Si interface. Data on cell performance (including CZ and ribbon) and analysis of loss mechanisms are also presented.

System among the corticosteroids: specificity and molecular dynamics

PubMed Central

Brookes, Jennifer C.; Galigniana, Mario D.; Harker, Anthony H.; Stoneham, A. Marshall; Vinson, Gavin P.

2012-01-01

Understanding how structural features determine specific biological activities has often proved elusive. With over 161 000 steroid structures described, an algorithm able to predict activity from structural attributes would provide manifest benefits. Molecular simulations of a range of 35 corticosteroids show striking correlations between conformational mobility and biological specificity. Thus steroid ring A is important for glucocorticoid action, and is rigid in the most specific (and potent) examples, such as dexamethasone. By contrast, ring C conformation is important for the mineralocorticoids, and is rigid in aldosterone. Other steroids that are less specific, or have mixed functions, or none at all, are more flexible. One unexpected example is 11-deoxycorticosterone, which the methods predict (and our activity studies confirm) is not only a specific mineralocorticoid, but also has significant glucocorticoid activity. These methods may guide the design of new corticosteroid agonists and antagonists. They will also have application in other examples of ligand–receptor interactions. PMID:21613285

Aquaporin structure-function relationships: water flow through plant living cells.

PubMed

Zhao, Chang-Xing; Shao, Hong-Bo; Chu, Li-Ye

2008-04-01

Plant aquaporins play an important role in water uptake and movement-an aquaporin that opens and closes a gate that regulates water movement in and out of cells. Some plant aquaporins also play an important role in response to water stress. Since their discovery, advancing knowledge of their structures and properties led to an understanding of the basic features of the water transport mechanism and increased illumination to water relations. Meanwhile, molecular and functional characterization of aquaporins has revealed the significance of their regulation in response to the adverse environments such as salinity and drought. This paper reviews the structure, species diversity, physiology function, regulation of plant aquaporins, and the relations between environmental factors and plant aquaporins. Complete understanding of aquaporin function and regulation is to integrate those mechanisms in time and space and to well regulate the permeation of water across biological membranes under changing environmental and developmental conditions.

Simulations of Scatterometry Down to 22 nm Structure Sizes and Beyond with Special Emphasis on LER

NASA Astrophysics Data System (ADS)

Osten, W.; Ferreras Paz, V.; Frenner, K.; Schuster, T.; Bloess, H.

2009-09-01

In recent years, scatterometry has become one of the most commonly used methods for CD metrology. With decreasing structure size for future technology nodes, the search for optimized scatterometry measurement configurations gets more important to exploit maximum sensitivity. As widespread industrial scatterometry tools mainly still use a pre-set measurement configuration, there are still free parameters to improve sensitivity. Our current work uses a simulation based approach to predict and optimize sensitivity of future technology nodes. Since line edge roughness is getting important for such small structures, these imperfections of the periodic continuation cannot be neglected. Using fourier methods like e.g. rigorous coupled wave approach (RCWA) for diffraction calculus, nonperiodic features are hard to reach. We show that in this field certain types of fieldstitching methods show nice numerical behaviour and lead to useful results.

Ab initio surface properties of Ag-Sn alloys: implications for lead-free soldering.

PubMed

Saleh, Gabriele; Xu, Chen; Sanvito, Stefano

2018-02-07

Ag and Sn are the major components of solder alloys adopted to assemble printed circuit boards. The qualities that make them the alloys of choice for the modern electronic industry are related to their physical and chemical properties. For corrosion resistance and solderability, surface properties are particularly important. Yet, atomic-level information about the surfaces of these alloys is not known. Here we fill this gap by presenting an extensive ab initio investigation of composition, energetics, structure and reactivity of Ag-Sn alloy surfaces. The structure and stability of various surfaces is evaluated, and the main factors determining the energetics of surface formation are uncovered. Oxygen and sulphur chemisorptions are studied and discussed in the framework of corrosion tendency, an important issue for printed circuit boards. Adsorption energy trends are rationalized based on the analysis of structural and electronic features.

On the role of spatial phase and phase correlation in vision, illusion, and cognition

PubMed Central

Gladilin, Evgeny; Eils, Roland

2015-01-01

Numerous findings indicate that spatial phase bears an important cognitive information. Distortion of phase affects topology of edge structures and makes images unrecognizable. In turn, appropriately phase-structured patterns give rise to various illusions of virtual image content and apparent motion. Despite a large body of phenomenological evidence not much is known yet about the role of phase information in neural mechanisms of visual perception and cognition. Here, we are concerned with analysis of the role of spatial phase in computational and biological vision, emergence of visual illusions and pattern recognition. We hypothesize that fundamental importance of phase information for invariant retrieval of structural image features and motion detection promoted development of phase-based mechanisms of neural image processing in course of evolution of biological vision. Using an extension of Fourier phase correlation technique, we show that the core functions of visual system such as motion detection and pattern recognition can be facilitated by the same basic mechanism. Our analysis suggests that emergence of visual illusions can be attributed to presence of coherently phase-shifted repetitive patterns as well as the effects of acuity compensation by saccadic eye movements. We speculate that biological vision relies on perceptual mechanisms effectively similar to phase correlation, and predict neural features of visual pattern (dis)similarity that can be used for experimental validation of our hypothesis of “cognition by phase correlation.” PMID:25954190

On the role of spatial phase and phase correlation in vision, illusion, and cognition.

PubMed

Gladilin, Evgeny; Eils, Roland

2015-01-01

Numerous findings indicate that spatial phase bears an important cognitive information. Distortion of phase affects topology of edge structures and makes images unrecognizable. In turn, appropriately phase-structured patterns give rise to various illusions of virtual image content and apparent motion. Despite a large body of phenomenological evidence not much is known yet about the role of phase information in neural mechanisms of visual perception and cognition. Here, we are concerned with analysis of the role of spatial phase in computational and biological vision, emergence of visual illusions and pattern recognition. We hypothesize that fundamental importance of phase information for invariant retrieval of structural image features and motion detection promoted development of phase-based mechanisms of neural image processing in course of evolution of biological vision. Using an extension of Fourier phase correlation technique, we show that the core functions of visual system such as motion detection and pattern recognition can be facilitated by the same basic mechanism. Our analysis suggests that emergence of visual illusions can be attributed to presence of coherently phase-shifted repetitive patterns as well as the effects of acuity compensation by saccadic eye movements. We speculate that biological vision relies on perceptual mechanisms effectively similar to phase correlation, and predict neural features of visual pattern (dis)similarity that can be used for experimental validation of our hypothesis of "cognition by phase correlation."

Line group techniques in description of the structural phase transitions in some superconductors

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

Meszaros, C.; Bankuti, J.; Balint, A.

1994-12-31

The main features of the theory of line groups, and their irreducible representations are briefly discussed, as well as the most important applications of them. A new approach in the general symmetry analysis of the modulated systems is presented. It is shown, that the line group formalism could be a very effective tool in the examination of the structural phase transitions in High Temperature Superconductors. As an example, the material YBa{sub 2}Cu{sub 3}O{sub 7-x} is discussed briefly.

Raman Spectral Signatures as Conformational Probes of Biomolecules

NASA Astrophysics Data System (ADS)

Golan, Amir; Mayorkas, Nitzan; Rosenwaks, Salman; Bar, Ilana

2009-06-01

A first application of ionization-loss stimulated Raman spectroscopy (ILSRS) for monitoring the spectral features of four conformers of a gas phase neurotransmitter (2-phenylethylamine) is reported. The Raman spectra of the conformers show bands that uniquely identify the conformational structure of the molecule and are well matched by density functional theory calculations. The measurement of spectral signatures by ILSRS in an extended spectral range, with a relatively convenient laser source, is extremely important, allowing enhanced accessibility to intra- and inter-molecular forces, which are significant in biological structure and activity.

Raman Spectral Signatures as Conformational Probes of Biomolecules

NASA Astrophysics Data System (ADS)

Bar, Ilana; Golan, Amir; Mayorkas, Nitzan; Rosenwaks, Salman

2009-03-01

A first application of ionization-loss stimulated Raman spectroscopy (ILSRS) monitoring the spectral features of four conformers of a gas phase neurotransmitter (2-phenylethylamine) is reported. The Raman spectra of the conformers show bands that uniquely identify the conformational structure of the molecule and are well matched by density functional theory calculations. The measurement of spectral signatures by ILSRS in an extended spectral range, with a relatively convenient laser source, is extremely important, allowing enhanced accessibility to intra- and inter-molecular forces, which are significant in biological structure and activity.

Structure and morphology of submarine slab slides: clues to origin and behavior

USGS Publications Warehouse

O'Leary, Dennis W.

1991-01-01

Geologic features suggest that some slab slides probably result from long-term strength degradation of weak layers deep in the homoclinal section. Time-dependent strain in clay-rich layers can create potential slide surfaces of low frictional strength. Competent layers are weak in tension and probably fragment in the first instance of, or even prior to, translation, and the allochthonous mass is readily transformed into a high-momentum debris flow. The structure and geomorphology of slab slides provide important clues to their origin and behavior. -from Author

Spiral Galaxy Lensing: A Model with Twist

NASA Astrophysics Data System (ADS)

Bell, Steven R.; Ernst, Brett; Fancher, Sean; Keeton, Charles R.; Komanduru, Abi; Lundberg, Erik

2014-12-01

We propose a single galaxy gravitational lensing model with a mass density that has a spiral structure. Namely, we extend the arcsine gravitational lens (a truncated singular isothermal elliptical model), adding an additional parameter that controls the amount of spiraling in the structure of the mass density. An important feature of our model is that, even though the mass density is sophisticated, we succeed in integrating the deflection term in closed form using a Gauss hypergeometric function. When the spiraling parameter is set to zero, this reduces to the arcsine lens.

Structural Architecture of Prothrombin in Solution Revealed by Single Molecule Spectroscopy.

PubMed

Pozzi, Nicola; Bystranowska, Dominika; Zuo, Xiaobing; Di Cera, Enrico

2016-08-26

The coagulation factor prothrombin has a complex spatial organization of its modular assembly that comprises the N-terminal Gla domain, kringle-1, kringle-2, and the C-terminal protease domain connected by three intervening linkers. Here we use single molecule Förster resonance energy transfer to access the conformational landscape of prothrombin in solution and uncover structural features of functional significance that extend recent x-ray crystallographic analysis. Prothrombin exists in equilibrium between two alternative conformations, open and closed. The closed conformation predominates (70%) and features an unanticipated intramolecular collapse of Tyr(93) in kringle-1 onto Trp(547) in the protease domain that obliterates access to the active site and protects the zymogen from autoproteolytic conversion to thrombin. The open conformation (30%) is more susceptible to chymotrypsin digestion and autoactivation, and features a shape consistent with recent x-ray crystal structures. Small angle x-ray scattering measurements of prothrombin wild type stabilized 70% in the closed conformation and of the mutant Y93A stabilized 80% in the open conformation directly document two envelopes that differ 50 Å in length. These findings reveal important new details on the conformational plasticity of prothrombin in solution and the drastic structural difference between its alternative conformations. Prothrombin uses the intramolecular collapse of kringle-1 onto the active site in the closed form to prevent autoactivation. The open-closed equilibrium also defines a new structural framework for the mechanism of activation of prothrombin by prothrombinase. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Myosin MyTH4-FERM structures highlight important principles of convergent evolution.

PubMed

Planelles-Herrero, Vicente José; Blanc, Florian; Sirigu, Serena; Sirkia, Helena; Clause, Jeffrey; Sourigues, Yannick; Johnsrud, Daniel O; Amigues, Beatrice; Cecchini, Marco; Gilbert, Susan P; Houdusse, Anne; Titus, Margaret A

2016-05-24

Myosins containing MyTH4-FERM (myosin tail homology 4-band 4.1, ezrin, radixin, moesin, or MF) domains in their tails are found in a wide range of phylogenetically divergent organisms, such as humans and the social amoeba Dictyostelium (Dd). Interestingly, evolutionarily distant MF myosins have similar roles in the extension of actin-filled membrane protrusions such as filopodia and bind to microtubules (MT), suggesting that the core functions of these MF myosins have been highly conserved over evolution. The structures of two DdMyo7 signature MF domains have been determined and comparison with mammalian MF structures reveals that characteristic features of MF domains are conserved. However, across millions of years of evolution conserved class-specific insertions are seen to alter the surfaces and the orientation of subdomains with respect to each other, likely resulting in new sites for binding partners. The MyTH4 domains of Myo10 and DdMyo7 bind to MT with micromolar affinity but, surprisingly, their MT binding sites are on opposite surfaces of the MyTH4 domain. The structural analysis in combination with comparison of diverse MF myosin sequences provides evidence that myosin tail domain features can be maintained without strict conservation of motifs. The results illustrate how tuning of existing features can give rise to new structures while preserving the general properties necessary for myosin tails. Thus, tinkering with the MF domain enables it to serve as a multifunctional platform for cooperative recruitment of various partners, allowing common properties such as autoinhibition of the motor and microtubule binding to arise through convergent evolution.

Atomic force microscopy study of the structure function relationships of the biofilm-forming bacterium Streptococcus mutans

NASA Astrophysics Data System (ADS)

Cross, Sarah E.; Kreth, Jens; Zhu, Lin; Qi, Fengxia; Pelling, Andrew E.; Shi, Wenyuan; Gimzewski, James K.

2006-02-01

Atomic force microscopy (AFM) has garnered much interest in recent years for its ability to probe the structure, function and cellular nanomechanics inherent to specific biological cells. In particular, we have used AFM to probe the important structure-function relationships of the bacterium Streptococcus mutans. S. mutans is the primary aetiological agent in human dental caries (tooth decay), and is of medical importance due to the virulence properties of these cells in biofilm initiation and formation, leading to increased tolerance to antibiotics. We have used AFM to characterize the unique surface structures of distinct mutants of S. mutans. These mutations are located in specific genes that encode surface proteins, thus using AFM we have resolved characteristic surface features for mutant strains compared to the wild type. Ultimately, our characterization of surface morphology has shown distinct differences in the local properties displayed by various S. mutans strains on the nanoscale, which is imperative for understanding the collective properties of these cells in biofilm formation.

Parametric imaging of collagen structural changes in human osteoarthritic cartilage using optical polarization tractography

NASA Astrophysics Data System (ADS)

Ravanfar, Mohammadreza; Pfeiffer, Ferris M.; Bozynski, Chantelle C.; Wang, Yuanbo; Yao, Gang

2017-12-01

Collagen degeneration is an important pathological feature of osteoarthritis. The purpose of this study is to investigate whether the polarization-sensitive optical coherence tomography (PSOCT)-based optical polarization tractography (OPT) can be useful in imaging collagen structural changes in human osteoarthritic cartilage samples. OPT eliminated the banding artifacts in conventional PSOCT by calculating the depth-resolved local birefringence and fiber orientation. A close comparison between OPT and PSOCT showed that OPT provided improved visualization and characterization of the zonal structure in human cartilage. Experimental results obtained in this study also underlined the importance of knowing the collagen fiber orientation in conventional polarized light microscopy assessment. In addition, parametric OPT imaging was achieved by quantifying the surface roughness, birefringence, and fiber dispersion in the superficial zone of the cartilage. These quantitative parametric images provided complementary information on the structural changes in cartilage, which can be useful for a comprehensive evaluation of collagen damage in osteoarthritic cartilage.

Challenges in Scale-Resolving Simulations of turbulent wake flows with coherent structures

NASA Astrophysics Data System (ADS)

Pereira, Filipe S.; Eça, Luís; Vaz, Guilherme; Girimaji, Sharath S.

2018-06-01

The objective of this work is to investigate the challenges encountered in Scale-Resolving Simulations (SRS) of turbulent wake flows driven by spatially-developing coherent structures. SRS of practical interest are expressly intended for efficiently computing such flows by resolving only the most important features of the coherent structures and modelling the remainder as stochastic field. The success of SRS methods depends upon three important factors: i) ability to identify key flow mechanisms responsible for the generation of coherent structures; ii) determine the optimum range of resolution required to adequately capture key elements of coherent structures; and iii) ensure that the modelled part is comprised nearly exclusively of fully-developed stochastic turbulence. This study considers the canonical case of the flow around a circular cylinder to address the aforementioned three key issues. It is first demonstrated using experimental evidence that the vortex-shedding instability and flow-structure development involves four important stages. A series of SRS computations of progressively increasing resolution (decreasing cut-off length) are performed. An a priori basis for locating the origin of the coherent structures development is proposed and examined. The criterion is based on the fact that the coherent structures are generated by the Kelvin-Helmholtz (KH) instability. The most important finding is that the key aspects of coherent structures can be resolved only if the effective computational Reynolds number (based on total viscosity) exceeds the critical value of the KH instability in laminar flows. Finally, a quantitative criterion assessing the nature of the unresolved field based on the strain-rate ratio of mean and unresolved fields is examined. The two proposed conditions and rationale offer a quantitative basis for developing "good practice" guidelines for SRS of complex turbulent wake flows with coherent structures.

VMD-SS: A graphical user interface plug-in to calculate the protein secondary structure in VMD program.

PubMed

Yahyavi, Masoumeh; Falsafi-Zadeh, Sajad; Karimi, Zahra; Kalatarian, Giti; Galehdari, Hamid

2014-01-01

The investigation on the types of secondary structure (SS) of a protein is important. The evolution of secondary structures during molecular dynamics simulations is a useful parameter to analyze protein structures. Therefore, it is of interest to describe VMD-SS (a software program) for the identification of secondary structure elements and its trajectories during simulation for known structures available at the Protein Data Bank (PDB). The program helps to calculate (1) percentage SS, (2) SS occurrence in each residue, (3) percentage SS during simulation, and (4) percentage residues in all SS types during simulation. The VMD-SS plug-in was designed using TCL script and stride to calculate secondary structure features. The database is available for free at http://science.scu.ac.ir/HomePage.aspx?TabID=13755.

Influence of Structural Features on Portuguese Toddler Child Care Quality

ERIC Educational Resources Information Center

Pessanha, Manuela; Aguiar, Cecilia; Bairrao, Joaquim

2007-01-01

Whereas child care quality has been extensively studied in the U.S., there is much less information about the quality of child care in other countries. With one of the highest maternal employment rates in Europe, it is important to examine child care in Portugal. Thirty toddler classrooms in child care centers were observed. The purpose of this…

Parental Socialization and Community Context: A Longitudinal Analysis of the Structural Sources of Low Self-Control

ERIC Educational Resources Information Center

Pratt, Travis C.; Turner, Michael G.; Piquero, Alex R.

2004-01-01

Several empirical studies have attempted to estimate the effect of low self-control on criminal and "analogous" behaviors. Most of these studies have shown that low self-control is an important feature of the cause(s) of crime. Although research is beginning to emerge that targets more specifically the "roots" of self-control via parental…

The Equivalence of Precession Phenomena in Metric Theories of Gravity

NASA Technical Reports Server (NTRS)

Krisher, Timothy P.

1996-01-01

The requirement of general covariance imparts to metric theories of gravity, such as general relativity, important structural features. A precise mathematical form results, ensuring that computation of observable physical effects in the theory gives the same answers independently of the chosen system of coordinates. This coordinate independence property, in turn, can lead to an equivalence of apparently different physical effects.

Higher Education Policy: An International Comparative Perspective. Issues in Higher Education Series.

ERIC Educational Resources Information Center

Goedegebuure, Leo, Ed.; And Others

This book is the result of a research project on the most important principles, structural features, and functionalities of higher education policies in 11 developed nations around the world. Reports on each nation, are based in large part on analysis of responses to a common questionnaire by national experts in each nation. An opening chapter,…

"Structures beneath the Skin": How School Leaders Use Their Power and Authority To Create Institutional Opportunities for Developing Positive Interethnic Communities.

ERIC Educational Resources Information Center

Norte, Edmundo

1999-01-01

Explores key features of processes school leaders employ to create positive interethnic school communities, identifying five elements for effective intervention and applying an analytical model to each to provide a schema for framing elements of central importance. Addresses how school leaders use their power and authority and how they determine…

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

DTIC Science & Technology

2010-09-01

22 Figure 23. Flow Type and the reference empirical model ............................................................ 24 Figure 24. Baseline...Trajectory ...................................................................................................... 25 Figure 25. Flow Features Important...94 viii GLOSSARY ACCTE Advanced Ceramic Composites for Turbine Engines AFRL Air Force Research Laboratory AoA Angle of Attack ASE

Cases for the Net Generation: An Empirical Examination of Students' Attitude toward Multimedia Case Studies

ERIC Educational Resources Information Center

Sheppard, Michael; Vibert, Conor

2016-01-01

Case studies have been an important tool in business, legal, and medical education for generations of students. Traditional text-based cases tend to be self-contained and structured in such a way as to teach a particular concept. The multimedia cases introduced in this study feature unscripted web-hosted video interviews with business owners and…

Substrate Binding and Catalytic Mechanism of Human Choline Acetyltransferase

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

Kim,A.; Rylett, J.; Shilton, B.

2006-01-01

Choline acetyltransferase (ChAT) catalyzes the synthesis of the neurotransmitter acetylcholine from choline and acetyl-CoA, and its presence is a defining feature of cholinergic neurons. We report the structure of human ChAT to a resolution of 2.2 {angstrom} along with structures for binary complexes of ChAT with choline, CoA, and a nonhydrolyzable acetyl-CoA analogue, S-(2-oxopropyl)-CoA. The ChAT-choline complex shows which features of choline are important for binding and explains how modifications of the choline trimethylammonium group can be tolerated by the enzyme. A detailed model of the ternary Michaelis complex fully supports the direct transfer of the acetyl group from acetyl-CoAmore » to choline through a mechanism similar to that seen in the serine hydrolases for the formation of an acyl-enzyme intermediate. Domain movements accompany CoA binding, and a surface loop, which is disordered in the unliganded enzyme, becomes localized and binds directly to the phosphates of CoA, stabilizing the complex. Interactions between this surface loop and CoA may function to lower the K{sub M} for CoA and could be important for phosphorylation-dependent regulation of ChAT activity.« less

Commonalities between Perception and Cognition.

PubMed

Tacca, Michela C

2011-01-01

Perception and cognition are highly interrelated. Given the influence that these systems exert on one another, it is important to explain how perceptual representations and cognitive representations interact. In this paper, I analyze the similarities between visual perceptual representations and cognitive representations in terms of their structural properties and content. Specifically, I argue that the spatial structure underlying visual object representation displays systematicity - a property that is considered to be characteristic of propositional cognitive representations. To this end, I propose a logical characterization of visual feature binding as described by Treisman's Feature Integration Theory and argue that systematicity is not only a property of language-like representations, but also of spatially organized visual representations. Furthermore, I argue that if systematicity is taken to be a criterion to distinguish between conceptual and non-conceptual representations, then visual representations, that display systematicity, might count as an early type of conceptual representations. Showing these analogies between visual perception and cognition is an important step toward understanding the interface between the two systems. The ideas here presented might also set the stage for new empirical studies that directly compare binding (and other relational operations) in visual perception and higher cognition.

Commonalities between Perception and Cognition

PubMed Central

Tacca, Michela C.

2011-01-01

Perception and cognition are highly interrelated. Given the influence that these systems exert on one another, it is important to explain how perceptual representations and cognitive representations interact. In this paper, I analyze the similarities between visual perceptual representations and cognitive representations in terms of their structural properties and content. Specifically, I argue that the spatial structure underlying visual object representation displays systematicity – a property that is considered to be characteristic of propositional cognitive representations. To this end, I propose a logical characterization of visual feature binding as described by Treisman’s Feature Integration Theory and argue that systematicity is not only a property of language-like representations, but also of spatially organized visual representations. Furthermore, I argue that if systematicity is taken to be a criterion to distinguish between conceptual and non-conceptual representations, then visual representations, that display systematicity, might count as an early type of conceptual representations. Showing these analogies between visual perception and cognition is an important step toward understanding the interface between the two systems. The ideas here presented might also set the stage for new empirical studies that directly compare binding (and other relational operations) in visual perception and higher cognition. PMID:22144974

Governance versus government: drug consumption rooms in Australia and the UK.

PubMed

Zampini, Giulia Federica

2014-09-01

To evaluate, through a case study, the extent to which elements of governance and elements of government are influential in determining the implementation or non-implementation of a drugs intervention. Comparative analysis of the case of a drug consumption room in the UK (England) and Australia (New South Wales), including 16 semi-structured interviews with key stakeholders and analysis of relevant documents according to characteristic features of governance and government (power decentralisation, power centralisation, independent self-organising policy networks, use of evidence, top-down steering/directing, legislation). Characteristic features of both governance and government are found in the data. Elements of governance are more prominent in New South Wales, Australia than in England, UK, where government prevails. Government is seen as the most important actor at play in the making, or absence, of drug consumption rooms. Both governance and government are useful frameworks in conceptualising the policy process. The governance narrative risks overlooking the importance of traditional government structures. In the case of drug consumption rooms in the UK and Australia, a focus on government is shown to have been crucial in determining whether the intervention was implemented. Copyright © 2014 Elsevier B.V. All rights reserved.

Statistical analysis of dendritic spine distributions in rat hippocampal cultures

PubMed Central

2013-01-01

Background Dendritic spines serve as key computational structures in brain plasticity. Much remains to be learned about their spatial and temporal distribution among neurons. Our aim in this study was to perform exploratory analyses based on the population distributions of dendritic spines with regard to their morphological characteristics and period of growth in dissociated hippocampal neurons. We fit a log-linear model to the contingency table of spine features such as spine type and distance from the soma to first determine which features were important in modeling the spines, as well as the relationships between such features. A multinomial logistic regression was then used to predict the spine types using the features suggested by the log-linear model, along with neighboring spine information. Finally, an important variant of Ripley’s K-function applicable to linear networks was used to study the spatial distribution of spines along dendrites. Results Our study indicated that in the culture system, (i) dendritic spine densities were "completely spatially random", (ii) spine type and distance from the soma were independent quantities, and most importantly, (iii) spines had a tendency to cluster with other spines of the same type. Conclusions Although these results may vary with other systems, our primary contribution is the set of statistical tools for morphological modeling of spines which can be used to assess neuronal cultures following gene manipulation such as RNAi, and to study induced pluripotent stem cells differentiated to neurons. PMID:24088199

An Efficient Scheme for Crystal Structure Prediction Based on Structural Motifs

DOE PAGES

Zhu, Zizhong; Wu, Ping; Wu, Shunqing; ...

2017-05-15

An efficient scheme based on structural motifs is proposed for the crystal structure prediction of materials. The key advantage of the present method comes in two fold: first, the degrees of freedom of the system are greatly reduced, since each structural motif, regardless of its size, can always be described by a set of parameters (R, θ, φ) with five degrees of freedom; second, the motifs could always appear in the predicted structures when the energies of the structures are relatively low. Both features make the present scheme a very efficient method for predicting desired materials. The method has beenmore » applied to the case of LiFePO 4, an important cathode material for lithium-ion batteries. Numerous new structures of LiFePO 4 have been found, compared to those currently available, available, demonstrating the reliability of the present methodology and illustrating the promise of the concept of structural motifs.« less

An Efficient Scheme for Crystal Structure Prediction Based on Structural Motifs

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

Zhu, Zizhong; Wu, Ping; Wu, Shunqing

An efficient scheme based on structural motifs is proposed for the crystal structure prediction of materials. The key advantage of the present method comes in two fold: first, the degrees of freedom of the system are greatly reduced, since each structural motif, regardless of its size, can always be described by a set of parameters (R, θ, φ) with five degrees of freedom; second, the motifs could always appear in the predicted structures when the energies of the structures are relatively low. Both features make the present scheme a very efficient method for predicting desired materials. The method has beenmore » applied to the case of LiFePO 4, an important cathode material for lithium-ion batteries. Numerous new structures of LiFePO 4 have been found, compared to those currently available, available, demonstrating the reliability of the present methodology and illustrating the promise of the concept of structural motifs.« less

Biopolymers and supramolecular polymers as biomaterials for biomedical applications

PubMed Central

Freeman, Ronit; Boekhoven, Job; Dickerson, Matthew B.; Naik, Rajesh R.

2015-01-01

Protein- and peptide-based structural biopolymers are abundant building blocks of biological systems. Either in their natural forms, such as collagen, silk or fibronectin, or as related synthetic materials they can be used in various technologies. An emerging area is that of biomimetic materials inspired by protein-based biopolymers, which are made up of small molecules rather than macromolecules and can therefore be described as supramolecular polymers. These materials are very useful in biomedical applications because of their ability to imitate the extracellular matrix both in architecture and their capacity to signal cells. This article describes important features of the natural extracellular matrix and highlight how these features are being incorporated into biomaterials composed of biopolymers and supramolecular polymers. We particularly focus on the structures, properties, and functions of collagen, fibronectin, silk, and the supramolecular polymers inspired by them as biomaterials for regenerative medicine. PMID:26989295

The widetilde{A}←widetilde{X} ABSORPTION SPECTRUM OF 2-NITROOXYBUTYL PEROXY RADICAL

NASA Astrophysics Data System (ADS)

Eddingsaas, Nathan; Takematsu, Kana; Okumura, Mitchio

2009-06-01

The nitrate radical is an important atmospheric oxidant in the nighttime sky. Nitrate radicals react by addition to alkenes, and in the presence of oxygen form nitrooxyalkyl peroxy radicals. The peroxy radical formed from the reaction of 2-butene, nitrate radical, and oxygen was detected by cavity ringdown spectroscopy (CRDS) via its widetilde{A}←widetilde{X} electronic absorption spectrum. The widetilde{A}←widetilde{X} electronic transition is a bound-bound transition with enough structure to distinguish between different peroxy radicals as well as different conformers of the same peroxy radical. Two conformers of the nitrooxybutyl peroxy radical have been observed; the absorption features are red shifted from the same absorption features of sec-butyl peroxy radical. Calculations on the structure of nitrooxyalkyl peroxy radicals and general trends of the position of the widetilde{A}←widetilde{X} absorption transitions have also been performed and compared to those of unsubstituted peroxy radicals.

Optimal Design of Experiments by Combining Coarse and Fine Measurements

NASA Astrophysics Data System (ADS)

Lee, Alpha A.; Brenner, Michael P.; Colwell, Lucy J.

2017-11-01

In many contexts, it is extremely costly to perform enough high-quality experimental measurements to accurately parametrize a predictive quantitative model. However, it is often much easier to carry out large numbers of experiments that indicate whether each sample is above or below a given threshold. Can many such categorical or "coarse" measurements be combined with a much smaller number of high-resolution or "fine" measurements to yield accurate models? Here, we demonstrate an intuitive strategy, inspired by statistical physics, wherein the coarse measurements are used to identify the salient features of the data, while the fine measurements determine the relative importance of these features. A linear model is inferred from the fine measurements, augmented by a quadratic term that captures the correlation structure of the coarse data. We illustrate our strategy by considering the problems of predicting the antimalarial potency and aqueous solubility of small organic molecules from their 2D molecular structure.

Overcoming computational uncertainties to reveal chemical sensitivity in single molecule conduction calculations.

PubMed

Solomon, Gemma C; Reimers, Jeffrey R; Hush, Noel S

2005-06-08

In the calculation of conduction through single molecule's approximations about the geometry and electronic structure of the system are usually made in order to simplify the problem. Previously [G. C. Solomon, J. R. Reimers, and N. S. Hush, J. Chem. Phys. 121, 6615 (2004)], we have shown that, in calculations employing cluster models for the electrodes, proper treatment of the open-shell nature of the clusters is the most important computational feature required to make the results sensitive to variations in the structural and chemical features of the system. Here, we expand this and establish a general hierarchy of requirements involving treatment of geometrical approximations. These approximations are categorized into two classes: those associated with finite-dimensional methods for representing the semi-infinite electrodes, and those associated with the chemisorption topology. We show that ca. 100 unique atoms are required in order to properly characterize each electrode: using fewer atoms leads to nonsystematic variations in conductivity that can overwhelm the subtler changes. The choice of binding site is shown to be the next most important feature, while some effects that are difficult to control experimentally concerning the orientations at each binding site are actually shown to be insignificant. Verification of this result provides a general test for the precision of computational procedures for molecular conductivity. Predictions concerning the dependence of conduction on substituent and other effects on the central molecule are found to be meaningful only when they exceed the uncertainties of the effects associated with binding-site variation.

Overcoming computational uncertainties to reveal chemical sensitivity in single molecule conduction calculations

NASA Astrophysics Data System (ADS)

Solomon, Gemma C.; Reimers, Jeffrey R.; Hush, Noel S.

2005-06-01

In the calculation of conduction through single molecule's approximations about the geometry and electronic structure of the system are usually made in order to simplify the problem. Previously [G. C. Solomon, J. R. Reimers, and N. S. Hush, J. Chem. Phys. 121, 6615 (2004)], we have shown that, in calculations employing cluster models for the electrodes, proper treatment of the open-shell nature of the clusters is the most important computational feature required to make the results sensitive to variations in the structural and chemical features of the system. Here, we expand this and establish a general hierarchy of requirements involving treatment of geometrical approximations. These approximations are categorized into two classes: those associated with finite-dimensional methods for representing the semi-infinite electrodes, and those associated with the chemisorption topology. We show that ca. 100 unique atoms are required in order to properly characterize each electrode: using fewer atoms leads to nonsystematic variations in conductivity that can overwhelm the subtler changes. The choice of binding site is shown to be the next most important feature, while some effects that are difficult to control experimentally concerning the orientations at each binding site are actually shown to be insignificant. Verification of this result provides a general test for the precision of computational procedures for molecular conductivity. Predictions concerning the dependence of conduction on substituent and other effects on the central molecule are found to be meaningful only when they exceed the uncertainties of the effects associated with binding-site variation.

Definition, Detection and Generation of Iyashi Expressions

NASA Astrophysics Data System (ADS)

Kitaoka, Tetsuko; Diago, Luis A.; Hagiwara, Ichiro; Kitazaki, Satoshi; Yamane, Shigeru

This paper concerns the engineering analysis of “Iyashi”, a peculiar concept to the Japanese, which affect person's heart and may change their expression and behavior. We have integrated the advocator's view of “Iyashi”, analyzed the social background of “Iyashi” and have defined Iyashi and also the Iyashi expression. As the facial expression is the special and important stimulus for both observers and people who show expressions, we want to prove the existence of expressions that change the observer's emotion with Iyashi. We have developed the system to clarify the combination of facial features important for Iyashi through the psychological experiments and the analysis by Holographic Neural Networks (HNN). HNN analysis gave the structure of the Iyashi expression, that is the important combination of the physical facial parameters contributing to the high degree of Iyashi. Based on the structure of Iyashi we are able to generate the Iyashi expression appropriate for each person.

Reconciling the Structural Attributes of Avian Antibodies*

PubMed Central

Conroy, Paul J.; Law, Ruby H. P.; Gilgunn, Sarah; Hearty, Stephen; Caradoc-Davies, Tom T.; Lloyd, Gordon; O'Kennedy, Richard J.; Whisstock, James C.

2014-01-01

Antibodies are high value therapeutic, diagnostic, biotechnological, and research tools. Combinatorial approaches to antibody discovery have facilitated access to unique antibodies by surpassing the diversity limitations of the natural repertoire, exploitation of immune repertoires from multiple species, and tailoring selections to isolate antibodies with desirable biophysical attributes. The V-gene repertoire of the chicken does not utilize highly diverse sequence and structures, which is in stark contrast to the mechanism employed by humans, mice, and primates. Recent exploitation of the avian immune system has generated high quality, high affinity antibodies to a wide range of antigens for a number of therapeutic, diagnostic and biotechnological applications. Furthermore, extensive examination of the amino acid characteristics of the chicken repertoire has provided significant insight into mechanisms employed by the avian immune system. A paucity of avian antibody crystal structures has limited our understanding of the structural consequences of these uniquely chicken features. This paper presents the crystal structure of two chicken single chain fragment variable (scFv) antibodies generated from large libraries by phage display against important human antigen targets, which capture two unique CDRL1 canonical classes in the presence and absence of a non-canonical disulfide constrained CDRH3. These structures cast light on the unique structural features of chicken antibodies and contribute further to our collective understanding of the unique mechanisms of diversity and biochemical attributes that render the chicken repertoire of particular value for antibody generation. PMID:24737329

Abnormal hubs of white matter networks in the frontal-parieto circuit contribute to depression discrimination via pattern classification.

PubMed

Qin, Jiaolong; Wei, Maobin; Liu, Haiyan; Chen, Jianhuai; Yan, Rui; Hua, Lingling; Zhao, Ke; Yao, Zhijian; Lu, Qing

2014-12-01

Previous studies had explored the diagnostic and prognostic value of the structural neuroimaging data of MDD and treated the whole brain voxels, the fractional anisotropy and the structural connectivity as classification features. To our best knowledge, no study examined the potential diagnostic value of the hubs of anatomical brain networks in MDD. The purpose of the current study was to provide an exploratory examination of the potential diagnostic and prognostic values of hubs of white matter brain networks in MDD discrimination and the corresponding impaired hub pattern via a multi-pattern analysis. We constructed white matter brain networks from 29 depressions and 30 healthy controls based on diffusion tensor imaging data, calculated nodal measures and identified hubs. Using these measures as features, two types of feature architectures were established, one only included hubs (HUB) and the other contained both hubs and non hubs. The support vector machine classifiers with Gaussian radial basis kernel were used after the feature selection. Moreover, the relative contribution of the features was estimated by means of the consensus features. Our results presented that the hubs (including the bilateral dorsolateral part of superior frontal gyrus, the left middle frontal gyrus, the bilateral middle temporal gyrus, and the bilateral inferior temporal gyrus) played an important role in distinguishing the depressions from healthy controls with the best accuracy of 83.05%. Moreover, most of the HUB consensus features located in the frontal-parieto circuit. These findings provided evidence that the hubs could be served as valuable potential diagnostic measure for MDD, and the hub-concentrated lesion distribution of MDD was primarily anchored within the frontal-parieto circuit. Copyright © 2014 Elsevier Inc. All rights reserved.

Assessing future vent opening locations at the Somma-Vesuvio volcanic complex: 1. A new information geodatabase with uncertainty characterizations

NASA Astrophysics Data System (ADS)

Tadini, A.; Bisson, M.; Neri, A.; Cioni, R.; Bevilacqua, A.; Aspinall, W. P.

2017-06-01

This study presents new and revised data sets about the spatial distribution of past volcanic vents, eruptive fissures, and regional/local structures of the Somma-Vesuvio volcanic system (Italy). The innovative features of the study are the identification and quantification of important sources of uncertainty affecting interpretations of the data sets. In this regard, the spatial uncertainty of each feature is modeled by an uncertainty area, i.e., a geometric element typically represented by a polygon drawn around points or lines. The new data sets have been assembled as an updatable geodatabase that integrates and complements existing databases for Somma-Vesuvio. The data are organized into 4 data sets and stored as 11 feature classes (points and lines for feature locations and polygons for the associated uncertainty areas), totaling more than 1700 elements. More specifically, volcanic vent and eruptive fissure elements are subdivided into feature classes according to their associated eruptive styles: (i) Plinian and sub-Plinian eruptions (i.e., large- or medium-scale explosive activity); (ii) violent Strombolian and continuous ash emission eruptions (i.e., small-scale explosive activity); and (iii) effusive eruptions (including eruptions from both parasitic vents and eruptive fissures). Regional and local structures (i.e., deep faults) are represented as linear feature classes. To support interpretation of the eruption data, additional data sets are provided for Somma-Vesuvio geological units and caldera morphological features. In the companion paper, the data presented here, and the associated uncertainties, are used to develop a first vent opening probability map for the Somma-Vesuvio caldera, with specific attention focused on large or medium explosive events.

Study of Some Planetary Atmospheres Features by Probe Entry and Descent Simulations

NASA Technical Reports Server (NTRS)

Gil, P. J. S.; Rosa, P. M. B.

2005-01-01

Characterization of planetary atmospheres is analyzed by its effects in the entry and descent trajectories of probes. Emphasis is on the most important variables that characterize atmospheres e.g. density profile with altitude. Probe trajectories are numerically determined with ENTRAP, a developing multi-purpose computational tool for entry and descent trajectory simulations capable of taking into account many features and perturbations. Real data from Mars Pathfinder mission is used. The goal is to be able to determine more accurately the atmosphere structure by observing real trajectories and what changes are to expect in probe descent trajectories if atmospheres have different properties than the ones assumed initially.

[Analysis of Conformational Features of Watson-Crick Duplex Fragments by Molecular Mechanics and Quantum Mechanics Methods].

PubMed

Poltev, V I; Anisimov, V M; Sanchez, C; Deriabina, A; Gonzalez, E; Garcia, D; Rivas, F; Polteva, N A

2016-01-01

It is generally accepted that the important characteristic features of the Watson-Crick duplex originate from the molecular structure of its subunits. However, it still remains to elucidate what properties of each subunit are responsible for the significant characteristic features of the DNA structure. The computations of desoxydinucleoside monophosphates complexes with Na-ions using density functional theory revealed a pivotal role of DNA conformational properties of single-chain minimal fragments in the development of unique features of the Watson-Crick duplex. We found that directionality of the sugar-phosphate backbone and the preferable ranges of its torsion angles, combined with the difference between purines and pyrimidines. in ring bases, define the dependence of three-dimensional structure of the Watson-Crick duplex on nucleotide base sequence. In this work, we extended these density functional theory computations to the minimal' fragments of DNA duplex, complementary desoxydinucleoside monophosphates complexes with Na-ions. Using several computational methods and various functionals, we performed a search for energy minima of BI-conformation for complementary desoxydinucleoside monophosphates complexes with different nucleoside sequences. Two sequences are optimized using ab initio method at the MP2/6-31++G** level of theory. The analysis of torsion angles, sugar ring puckering and mutual base positions of optimized structures demonstrates that the conformational characteristic features of complementary desoxydinucleoside monophosphates complexes with Na-ions remain within BI ranges and become closer to the corresponding characteristic features of the Watson-Crick duplex crystals. Qualitatively, the main characteristic features of each studied complementary desoxydinucleoside monophosphates complex remain invariant when different computational methods are used, although the quantitative values of some conformational parameters could vary lying within the limits typical for the corresponding family. We observe that popular functionals in density functional theory calculations lead to the overestimated distances between base pairs, while MP2 computations and the newer complex functionals produce the structures that have too close atom-atom contacts. A detailed study of some complementary desoxydinucleoside monophosphate complexes with Na-ions highlights the existence of several energy minima corresponding to BI-conformations, in other words, the complexity of the relief pattern of the potential energy surface of complementary desoxydinucleoside monophosphate complexes. This accounts for variability of conformational parameters of duplex fragments with the same base sequence. Popular molecular mechanics force fields AMBER and CHARMM reproduce most of the conformational characteristics of desoxydinucleoside monophosphates and their complementary complexes with Na-ions but fail to reproduce some details of the dependence of the Watson-Crick duplex conformation on the nucleotide sequence.

Identification of symptom and functional domains that fibromyalgia patients would like to see improved: a cluster analysis.

PubMed

Bennett, Robert M; Russell, Jon; Cappelleri, Joseph C; Bushmakin, Andrew G; Zlateva, Gergana; Sadosky, Alesia

2010-06-28

The purpose of this study was to determine whether some of the clinical features of fibromyalgia (FM) that patients would like to see improved aggregate into definable clusters. Seven hundred and eighty-eight patients with clinically confirmed FM and baseline pain > or =40 mm on a 100 mm visual analogue scale ranked 5 FM clinical features that the subjects would most like to see improved after treatment (one for each priority quintile) from a list of 20 developed during focus groups. For each subject, clinical features were transformed into vectors with rankings assigned values 1-5 (lowest to highest ranking). Logistic analysis was used to create a distance matrix and hierarchical cluster analysis was applied to identify cluster structure. The frequency of cluster selection was determined, and cluster importance was ranked using cluster scores derived from rankings of the clinical features. Multidimensional scaling was used to visualize and conceptualize cluster relationships. Six clinical features clusters were identified and named based on their key characteristics. In order of selection frequency, the clusters were Pain (90%; 4 clinical features), Fatigue (89%; 4 clinical features), Domestic (42%; 4 clinical features), Impairment (29%; 3 functions), Affective (21%; 3 clinical features), and Social (9%; 2 functional). The "Pain Cluster" was ranked of greatest importance by 54% of subjects, followed by Fatigue, which was given the highest ranking by 28% of subjects. Multidimensional scaling mapped these clusters to two dimensions: Status (bounded by Physical and Emotional domains), and Setting (bounded by Individual and Group interactions). Common clinical features of FM could be grouped into 6 clusters (Pain, Fatigue, Domestic, Impairment, Affective, and Social) based on patient perception of relevance to treatment. Furthermore, these 6 clusters could be charted in the 2 dimensions of Status and Setting, thus providing a unique perspective for interpretation of FM symptomatology.

Varied Rates of Implementation of Patient-Centered Medical Home Features and Residents' Perceptions of Their Importance Based on Practice Experience.

PubMed

Eiff, M Patrice; Green, Larry A; Jones, Geoff; Devlaeminck, Alex Verdieck; Waller, Elaine; Dexter, Eve; Marino, Miguel; Carney, Patricia A

2017-03-01

Little is known about how the patient-centered medical home (PCMH) is being implemented in residency practices. We describe both the trends in implementation of PCMH features and the influence that working with PCMH features has on resident attitudes toward their importance in 14 family medicine residencies associated with the P4 Project. We assessed 24 residency continuity clinics annually between 2007-2011 on presence or absence of PCMH features. Annual resident surveys (n=690) assessed perceptions of importance of PCMH features using a 4-point scale (not at all important to very important). We used generalized estimating equations logistic regression to assess trends and ordinal-response proportional odds regression models to determine if resident ratings of importance were associated with working with those features during training. Implementation of electronic health record (EHR) features increased significantly from 2007-2011, such as email communication with patients (33% to 67%), preventive services registries (23% to 64%), chronic disease registries (63% to 82%), and population-based quality assurance (46% to 79%). Team-based care was the only process of care feature to change significantly (54% to 93%). Residents with any exposure to EHR-based features had higher odds of rating the features more important compared to those with no exposure. We observed consistently lower odds of the resident rating process of care features as more important with any exposure compared to no exposure. Residencies engaged in educational transformation were more successful in implementing EHR-based PCMH features, and exposure during training appears to positively influence resident ratings of importance, while exposure to process of care features are slower to implement with less influence on importance ratings.

Infrastructure features outperform environmental variables explaining rabbit abundance around motorways.

PubMed

Planillo, Aimara; Malo, Juan E

2018-01-01

Human disturbance is widespread across landscapes in the form of roads that alter wildlife populations. Knowing which road features are responsible for the species response and their relevance in comparison with environmental variables will provide useful information for effective conservation measures. We sampled relative abundance of European rabbits, a very widespread species, in motorway verges at regional scale, in an area with large variability in environmental and infrastructure conditions. Environmental variables included vegetation structure, plant productivity, distance to water sources, and altitude. Infrastructure characteristics were the type of vegetation in verges, verge width, traffic volume, and the presence of embankments. We performed a variance partitioning analysis to determine the relative importance of two sets of variables on rabbit abundance. Additionally, we identified the most important variables and their effects model averaging after model selection by AICc on hypothesis-based models. As a group, infrastructure features explained four times more variability in rabbit abundance than environmental variables, being the effects of the former critical in motorway stretches located in altered landscapes with no available habitat for rabbits, such as agricultural fields. Model selection and Akaike weights showed that verge width and traffic volume are the most important variables explaining rabbit abundance index, with positive and negative effects, respectively. In the light of these results, the response of species to the infrastructure can be modulated through the modification of motorway features, being some of them manageable in the design phase. The identification of such features leads to suggestions for improvement through low-cost corrective measures and conservation plans. As a general indication, keeping motorway verges less than 10 m wide will prevent high densities of rabbits and avoid the unwanted effects that rabbit populations can generate in some areas.

Enriching science, practice, and policy relevant to school psychology around the globe.

PubMed

Jimerson, Shane R

2016-03-01

This editorial provides a brief synthesis of the past, present, and future of School Psychology Quarterly, highlighting important contributions as an international resource to enrich, invigorate, enhance, and advance science, practice, and policy relevant to school psychology around the globe. Information herein highlights (a) the value of high quality and timely reviews, (b) publishing manuscripts that address a breadth of important topics relevant to school psychology, and (c) the structure and contributions of the special topic sections featured in School Psychology Quarterly. (c) 2016 APA, all rights reserved).

Changes in assembly processes in soil bacterial communities following a wildfire disturbance.

PubMed

Ferrenberg, Scott; O'Neill, Sean P; Knelman, Joseph E; Todd, Bryan; Duggan, Sam; Bradley, Daniel; Robinson, Taylor; Schmidt, Steven K; Townsend, Alan R; Williams, Mark W; Cleveland, Cory C; Melbourne, Brett A; Jiang, Lin; Nemergut, Diana R

2013-06-01

Although recent work has shown that both deterministic and stochastic processes are important in structuring microbial communities, the factors that affect the relative contributions of niche and neutral processes are poorly understood. The macrobiological literature indicates that ecological disturbances can influence assembly processes. Thus, we sampled bacterial communities at 4 and 16 weeks following a wildfire and used null deviation analysis to examine the role that time since disturbance has in community assembly. Fire dramatically altered bacterial community structure and diversity as well as soil chemistry for both time-points. Community structure shifted between 4 and 16 weeks for both burned and unburned communities. Community assembly in burned sites 4 weeks after fire was significantly more stochastic than in unburned sites. After 16 weeks, however, burned communities were significantly less stochastic than unburned communities. Thus, we propose a three-phase model featuring shifts in the relative importance of niche and neutral processes as a function of time since disturbance. Because neutral processes are characterized by a decoupling between environmental parameters and community structure, we hypothesize that a better understanding of community assembly may be important in determining where and when detailed studies of community composition are valuable for predicting ecosystem function.

Changes in assembly processes in soil bacterial communities following a wildfire disturbance

PubMed Central

Ferrenberg, Scott; O'Neill, Sean P; Knelman, Joseph E; Todd, Bryan; Duggan, Sam; Bradley, Daniel; Robinson, Taylor; Schmidt, Steven K; Townsend, Alan R; Williams, Mark W; Cleveland, Cory C; Melbourne, Brett A; Jiang, Lin; Nemergut, Diana R

2013-01-01

Although recent work has shown that both deterministic and stochastic processes are important in structuring microbial communities, the factors that affect the relative contributions of niche and neutral processes are poorly understood. The macrobiological literature indicates that ecological disturbances can influence assembly processes. Thus, we sampled bacterial communities at 4 and 16 weeks following a wildfire and used null deviation analysis to examine the role that time since disturbance has in community assembly. Fire dramatically altered bacterial community structure and diversity as well as soil chemistry for both time-points. Community structure shifted between 4 and 16 weeks for both burned and unburned communities. Community assembly in burned sites 4 weeks after fire was significantly more stochastic than in unburned sites. After 16 weeks, however, burned communities were significantly less stochastic than unburned communities. Thus, we propose a three-phase model featuring shifts in the relative importance of niche and neutral processes as a function of time since disturbance. Because neutral processes are characterized by a decoupling between environmental parameters and community structure, we hypothesize that a better understanding of community assembly may be important in determining where and when detailed studies of community composition are valuable for predicting ecosystem function. PMID:23407312

Off-axis volcano-tectonic activity during continental rifting: Insights from the transversal Goba-Bonga lineament, Main Ethiopian Rift (East Africa)

NASA Astrophysics Data System (ADS)

Corti, Giacomo; Sani, Federico; Agostini, Samuele; Philippon, Melody; Sokoutis, Dimitrios; Willingshofer, Ernst

2018-03-01

The Main Ethiopian Rift, East Africa, is characterized by the presence of major, enigmatic structures which strike approximately orthogonal to the trend of the rift valley. These structures are marked by important deformation and magmatic activity in an off-axis position in the plateaus surrounding the rift. In this study, we present new structural data based on a remote and field analysis, complemented with analogue modelling experiments, and new geochemical analysis of volcanic rocks sampled in different portions of one of these transversal structures: the Goba-Bonga volcano-tectonic lineament (GBVL). This integrated analysis shows that the GBVL is associated with roughly E-W-trending prominent volcano-tectonic activity affecting the western plateau. Within the rift floor, the approximately E-W alignment of Awasa and Corbetti calderas likely represent expressions of the GBVL. Conversely, no tectonic or volcanic features of similar (E-W) orientation have been recognized on the eastern plateau. Analogue modelling suggests that the volcano-tectonic features of the GBVL have probably been controlled by the presence of a roughly E-W striking pre-existing discontinuity beneath the western plateau, which did not extend beneath the eastern plateau. Geochemical analysis supports this interpretation and indicates that, although magmas have the same sub-lithospheric mantle source, limited differences in magma evolution displayed by products found along the GBVL may be ascribed to the different tectonic framework to the west, to the east, and in the axial zone of the rift. These results support the importance of the heterogeneous nature of the lithosphere and the spatial variations of its structure in controlling the architecture of continental rifts and the distribution of the related volcano-tectonic activity.

Diverse Supramolecular Nanofiber Networks Assembled by Functional Low-Complexity Domains.

PubMed

An, Bolin; Wang, Xinyu; Cui, Mengkui; Gui, Xinrui; Mao, Xiuhai; Liu, Yan; Li, Ke; Chu, Cenfeng; Pu, Jiahua; Ren, Susu; Wang, Yanyi; Zhong, Guisheng; Lu, Timothy K; Liu, Cong; Zhong, Chao

2017-07-25

Self-assembling supramolecular nanofibers, common in the natural world, are of fundamental interest and technical importance to both nanotechnology and materials science. Despite important advances, synthetic nanofibers still lack the structural and functional diversity of biological molecules, and the controlled assembly of one type of molecule into a variety of fibrous structures with wide-ranging functional attributes remains challenging. Here, we harness the low-complexity (LC) sequence domain of fused in sarcoma (FUS) protein, an essential cellular nuclear protein with slow kinetics of amyloid fiber assembly, to construct random copolymer-like, multiblock, and self-sorted supramolecular fibrous networks with distinct structural features and fluorescent functionalities. We demonstrate the utilities of these networks in the templated, spatially controlled assembly of ligand-decorated gold nanoparticles, quantum dots, nanorods, DNA origami, and hybrid structures. Owing to the distinguishable nanoarchitectures of these nanofibers, this assembly is structure-dependent. By coupling a modular genetic strategy with kinetically controlled complex supramolecular self-assembly, we demonstrate that a single type of protein molecule can be used to engineer diverse one-dimensional supramolecular nanostructures with distinct functionalities.

Structural features that predict real-value fluctuations of globular proteins.

PubMed

Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke

2012-05-01

It is crucial to consider dynamics for understanding the biological function of proteins. We used a large number of molecular dynamics (MD) trajectories of nonhomologous proteins as references and examined static structural features of proteins that are most relevant to fluctuations. We examined correlation of individual structural features with fluctuations and further investigated effective combinations of features for predicting the real value of residue fluctuations using the support vector regression (SVR). It was found that some structural features have higher correlation than crystallographic B-factors with fluctuations observed in MD trajectories. Moreover, SVR that uses combinations of static structural features showed accurate prediction of fluctuations with an average Pearson's correlation coefficient of 0.669 and a root mean square error of 1.04 Å. This correlation coefficient is higher than the one observed in predictions by the Gaussian network model (GNM). An advantage of the developed method over the GNMs is that the former predicts the real value of fluctuation. The results help improve our understanding of relationships between protein structure and fluctuation. Furthermore, the developed method provides a convienient practial way to predict fluctuations of proteins using easily computed static structural features of proteins. Copyright © 2012 Wiley Periodicals, Inc.

Structural features that predict real-value fluctuations of globular proteins

PubMed Central

Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke

2012-01-01

It is crucial to consider dynamics for understanding the biological function of proteins. We used a large number of molecular dynamics trajectories of non-homologous proteins as references and examined static structural features of proteins that are most relevant to fluctuations. We examined correlation of individual structural features with fluctuations and further investigated effective combinations of features for predicting the real-value of residue fluctuations using the support vector regression. It was found that some structural features have higher correlation than crystallographic B-factors with fluctuations observed in molecular dynamics trajectories. Moreover, support vector regression that uses combinations of static structural features showed accurate prediction of fluctuations with an average Pearson’s correlation coefficient of 0.669 and a root mean square error of 1.04 Å. This correlation coefficient is higher than the one observed for the prediction by the Gaussian network model. An advantage of the developed method over the Gaussian network models is that the former predicts the real-value of fluctuation. The results help improve our understanding of relationships between protein structure and fluctuation. Furthermore, the developed method provides a convienient practial way to predict fluctuations of proteins using easily computed static structural features of proteins. PMID:22328193

Challenging the state of the art in protein structure prediction: Highlights of experimental target structures for the 10th Critical Assessment of Techniques for Protein Structure Prediction Experiment CASP10.

PubMed

Kryshtafovych, Andriy; Moult, John; Bales, Patrick; Bazan, J Fernando; Biasini, Marco; Burgin, Alex; Chen, Chen; Cochran, Frank V; Craig, Timothy K; Das, Rhiju; Fass, Deborah; Garcia-Doval, Carmela; Herzberg, Osnat; Lorimer, Donald; Luecke, Hartmut; Ma, Xiaolei; Nelson, Daniel C; van Raaij, Mark J; Rohwer, Forest; Segall, Anca; Seguritan, Victor; Zeth, Kornelius; Schwede, Torsten

2014-02-01

For the last two decades, CASP has assessed the state of the art in techniques for protein structure prediction and identified areas which required further development. CASP would not have been possible without the prediction targets provided by the experimental structural biology community. In the latest experiment, CASP10, more than 100 structures were suggested as prediction targets, some of which appeared to be extraordinarily difficult for modeling. In this article, authors of some of the most challenging targets discuss which specific scientific question motivated the experimental structure determination of the target protein, which structural features were especially interesting from a structural or functional perspective, and to what extent these features were correctly reproduced in the predictions submitted to CASP10. Specifically, the following targets will be presented: the acid-gated urea channel, a difficult to predict transmembrane protein from the important human pathogen Helicobacter pylori; the structure of human interleukin (IL)-34, a recently discovered helical cytokine; the structure of a functionally uncharacterized enzyme OrfY from Thermoproteus tenax formed by a gene duplication and a novel fold; an ORFan domain of mimivirus sulfhydryl oxidase R596; the fiber protein gene product 17 from bacteriophage T7; the bacteriophage CBA-120 tailspike protein; a virus coat protein from metagenomic samples of the marine environment; and finally, an unprecedented class of structure prediction targets based on engineered disulfide-rich small proteins. Copyright © 2013 The Authors. Wiley Periodicals, Inc.

Structural studies of G protein-coupled receptors.

PubMed

Lu, Mengjie; Wu, Beili

2016-11-01

G protein-coupled receptors (GPCRs) comprise the largest membrane protein family. These receptors sense a variety of signaling molecules, activate multiple intracellular signal pathways, and act as the targets of over 40% of marketed drugs. Recent progress on GPCR structural studies provides invaluable insights into the structure-function relationship of the GPCR superfamily, deepening our understanding about the molecular mechanisms of GPCR signal transduction. Here, we review recent breakthroughs on GPCR structure determination and the structural features of GPCRs, and take the structures of chemokine receptor CCR5 and purinergic receptors P2Y 1 R and P2Y 12 R as examples to discuss the importance of GPCR structures on functional studies and drug discovery. In addition, we discuss the prospect of GPCR structure-based drug discovery. © 2016 IUBMB Life, 68(11):894-903, 2016. © 2016 International Union of Biochemistry and Molecular Biology.

From Sequence and Forces to Structure, Function and Evolution of Intrinsically Disordered Proteins

PubMed Central

Forman-Kay, Julie D.; Mittag, Tanja

2015-01-01

Intrinsically disordered proteins (IDPs), which lack persistent structure, are a challenge to structural biology due to the inapplicability of standard methods for characterization of folded proteins as well as their deviation from the dominant structure/function paradigm. Their widespread presence and involvement in biological function, however, has spurred the growing acceptance of the importance of IDPs and the development of new tools for studying their structure, dynamics and function. The interplay of folded and disordered domains or regions for function and the existence of a continuum of protein states with respect to conformational energetics, motional timescales and compactness is shaping a unified understanding of structure-dynamics-disorder/function relationships. On the 20th anniversary of this journal, Structure, we provide a historical perspective on the investigation of IDPs and summarize the sequence features and physical forces that underlie their unique structural, functional and evolutionary properties. PMID:24010708

From sequence and forces to structure, function, and evolution of intrinsically disordered proteins.

PubMed

Forman-Kay, Julie D; Mittag, Tanja

2013-09-03

Intrinsically disordered proteins (IDPs), which lack persistent structure, are a challenge to structural biology due to the inapplicability of standard methods for characterization of folded proteins as well as their deviation from the dominant structure/function paradigm. Their widespread presence and involvement in biological function, however, has spurred the growing acceptance of the importance of IDPs and the development of new tools for studying their structure, dynamics, and function. The interplay of folded and disordered domains or regions for function and the existence of a continuum of protein states with respect to conformational energetics, motional timescales, and compactness are shaping a unified understanding of structure-dynamics-disorder/function relationships. In the 20(th) anniversary of Structure, we provide a historical perspective on the investigation of IDPs and summarize the sequence features and physical forces that underlie their unique structural, functional, and evolutionary properties. Copyright © 2013 Elsevier Ltd. All rights reserved.

Understanding regulatory networks requires more than computing a multitude of graph statistics. Comment on "Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function" by O.C. Martin et al.

NASA Astrophysics Data System (ADS)

Tkačik, Gašper

2016-07-01

The article by O. Martin and colleagues provides a much needed systematic review of a body of work that relates the topological structure of genetic regulatory networks to evolutionary selection for function. This connection is very important. Using the current wealth of genomic data, statistical features of regulatory networks (e.g., degree distributions, motif composition, etc.) can be quantified rather easily; it is, however, often unclear how to interpret the results. On a graph theoretic level the statistical significance of the results can be evaluated by comparing observed graphs to ;randomized; ones (bravely ignoring the issue of how precisely to randomize!) and comparing the frequency of appearance of a particular network structure relative to a randomized null expectation. While this is a convenient operational test for statistical significance, its biological meaning is questionable. In contrast, an in-silico genotype-to-phenotype model makes explicit the assumptions about the network function, and thus clearly defines the expected network structures that can be compared to the case of no selection for function and, ultimately, to data.

Geological Structures Mapping of Bukit Bunuh using 2-D Resistivity Imaging Method

NASA Astrophysics Data System (ADS)

Nur Amalina, M. K. A.; Nordiana, M. M.; Rahman, Nazrin; Saidin, Mokhtar; Masnan, S. S. K.

2018-04-01

The geological area of Bukit Bunuh is very complex due to the meteorite impact that has occurred millions years ago at Lenggong, Perak. The lithology of the study area consists of alluvium, tephra dust, and granitic rock. The geological contact, fault and fracture zone were found at the study area may indicate the geological process that undergoes at a place locally or regionally. These important features have led to the further research on 2-D resistivity imaging method (2-D RIM) to study the geological features. This method can provide the subsurface image that will delineate the geological structures. The surveys include three separate lines of different length which depend on the accessibility. The surveys were done by using Pole-Dipole array and 10 m of electrodes spacing. The objectives of this research are to determine the subsurface geological contact and to determine the existence of fault/fracture zones at the contact zone. The results from 2-D inversion profiles have successfully signified the types of geological structural such as fault, contact, and fractures. Hence, the results from 2-D RIM were used to draw the geological lineaments of Bukit Bunuh. The discontinuity of the lineaments may indicate the structures present.

Structural disorder in plant proteins: where plasticity meets sessility.

PubMed

Covarrubias, Alejandra A; Cuevas-Velazquez, Cesar L; Romero-Pérez, Paulette S; Rendón-Luna, David F; Chater, Caspar C C

2017-09-01

Plants are sessile organisms. This intriguing nature provokes the question of how they survive despite the continual perturbations caused by their constantly changing environment. The large amount of knowledge accumulated to date demonstrates the fascinating dynamic and plastic mechanisms, which underpin the diverse strategies selected in plants in response to the fluctuating environment. This phenotypic plasticity requires an efficient integration of external cues to their growth and developmental programs that can only be achieved through the dynamic and interactive coordination of various signaling networks. Given the versatility of intrinsic structural disorder within proteins, this feature appears as one of the leading characters of such complex functional circuits, critical for plant adaptation and survival in their wild habitats. In this review, we present information of those intrinsically disordered proteins (IDPs) from plants for which their high level of predicted structural disorder has been correlated with a particular function, or where there is experimental evidence linking this structural feature with its protein function. Using examples of plant IDPs involved in the control of cell cycle, metabolism, hormonal signaling and regulation of gene expression, development and responses to stress, we demonstrate the critical importance of IDPs throughout the life of the plant.

Introducing improved structural properties and salt dependence into a coarse-grained model of DNA

NASA Astrophysics Data System (ADS)

Snodin, Benedict E. K.; Randisi, Ferdinando; Mosayebi, Majid; Šulc, Petr; Schreck, John S.; Romano, Flavio; Ouldridge, Thomas E.; Tsukanov, Roman; Nir, Eyal; Louis, Ard A.; Doye, Jonathan P. K.

2015-06-01

We introduce an extended version of oxDNA, a coarse-grained model of deoxyribonucleic acid (DNA) designed to capture the thermodynamic, structural, and mechanical properties of single- and double-stranded DNA. By including explicit major and minor grooves and by slightly modifying the coaxial stacking and backbone-backbone interactions, we improve the ability of the model to treat large (kilobase-pair) structures, such as DNA origami, which are sensitive to these geometric features. Further, we extend the model, which was previously parameterised to just one salt concentration ([Na+] = 0.5M), so that it can be used for a range of salt concentrations including those corresponding to physiological conditions. Finally, we use new experimental data to parameterise the oxDNA potential so that consecutive adenine bases stack with a different strength to consecutive thymine bases, a feature which allows a more accurate treatment of systems where the flexibility of single-stranded regions is important. We illustrate the new possibilities opened up by the updated model, oxDNA2, by presenting results from simulations of the structure of large DNA objects and by using the model to investigate some salt-dependent properties of DNA.

Anomalous High-Energy Waterfall-Like Electronic Structure in 5 d Transition Metal Oxide Sr2IrO4 with a Strong Spin-Orbit Coupling

PubMed Central

Liu, Yan; Yu, Li; Jia, Xiaowen; Zhao, Jianzhou; Weng, Hongming; Peng, Yingying; Chen, Chaoyu; Xie, Zhuojin; Mou, Daixiang; He, Junfeng; Liu, Xu; Feng, Ya; Yi, Hemian; Zhao, Lin; Liu, Guodong; He, Shaolong; Dong, Xiaoli; Zhang, Jun; Xu, Zuyan; Chen, Chuangtian; Cao, Gang; Dai, Xi; Fang, Zhong; Zhou, X. J.

2015-01-01

The low energy electronic structure of Sr2IrO4 has been well studied and understood in terms of an effective Jeff = 1/2 Mott insulator model. However, little work has been done in studying its high energy electronic behaviors. Here we report a new observation of the anomalous high energy electronic structure in Sr2IrO4. By taking high-resolution angle-resolved photoemission measurements on Sr2IrO4 over a wide energy range, we have revealed for the first time that the high energy electronic structures show unusual nearly-vertical bands that extend over a large energy range. Such anomalous high energy behaviors resemble the high energy waterfall features observed in the cuprate superconductors. While strong electron correlation plays an important role in producing high energy waterfall features in the cuprate superconductors, the revelation of the high energy anomalies in Sr2IrO4, which exhibits strong spin-orbit coupling and a moderate electron correlation, points to an unknown and novel route in generating exotic electronic excitations. PMID:26267653

Introducing improved structural properties and salt dependence into a coarse-grained model of DNA

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

Snodin, Benedict E. K., E-mail: benedict.snodin@chem.ox.ac.uk; Mosayebi, Majid; Schreck, John S.

2015-06-21

We introduce an extended version of oxDNA, a coarse-grained model of deoxyribonucleic acid (DNA) designed to capture the thermodynamic, structural, and mechanical properties of single- and double-stranded DNA. By including explicit major and minor grooves and by slightly modifying the coaxial stacking and backbone-backbone interactions, we improve the ability of the model to treat large (kilobase-pair) structures, such as DNA origami, which are sensitive to these geometric features. Further, we extend the model, which was previously parameterised to just one salt concentration ([Na{sup +}] = 0.5M), so that it can be used for a range of salt concentrations including thosemore » corresponding to physiological conditions. Finally, we use new experimental data to parameterise the oxDNA potential so that consecutive adenine bases stack with a different strength to consecutive thymine bases, a feature which allows a more accurate treatment of systems where the flexibility of single-stranded regions is important. We illustrate the new possibilities opened up by the updated model, oxDNA2, by presenting results from simulations of the structure of large DNA objects and by using the model to investigate some salt-dependent properties of DNA.« less

Electronic structure of the benzene dimer cation

NASA Astrophysics Data System (ADS)

Pieniazek, Piotr A.; Krylov, Anna I.; Bradforth, Stephen E.

2007-07-01

The benzene and benzene dimer cations are studied using the equation-of-motion coupled-cluster model with single and double substitutions for ionized systems. The ten lowest electronic states of the dimer at t-shaped, sandwich, and displaced sandwich configurations are described and cataloged based on the character of the constituent fragment molecular orbitals. The character of the states, bonding patterns, and important features of the electronic spectrum are explained using qualitative dimer molecular orbital linear combination of fragment molecular orbital framework. Relaxed ground state geometries are obtained for all isomers. Calculations reveal that the lowest energy structure of the cation has a displaced sandwich structure and a binding energy of 20kcal/mol, while the t-shaped isomer is 6kcal/mol higher. The calculated electronic spectra agree well with experimental gas phase action spectra and femtosecond transient absorption in liquid benzene. Both sandwich and t-shaped structures feature intense charge resonance bands, whose location is very sensitive to the interfragment distance. Change in the electronic state ordering was observed between σ and πu states, which correlate to the B˜ and C˜ bands of the monomer, suggesting a reassignment of the local excitation peaks in the gas phase experimental spectrum.

Predicting Chemically Induced Duodenal Ulcer and Adrenal Necrosis with Classification Trees

NASA Astrophysics Data System (ADS)

Giampaolo, Casimiro; Gray, Andrew T.; Olshen, Richard A.; Szabo, Sandor

1991-07-01

Binary tree-structured statistical classification algorithms and properties of 56 model alkyl nucleophiles were brought to bear on two problems of experimental pharmacology and toxicology. Each rat of a learning sample of 745 was administered one compound and autopsied to determine the presence of duodenal ulcer or adrenal hemorrhagic necrosis. The cited statistical classification schemes were then applied to these outcomes and 67 features of the compounds to ascertain those characteristics that are associated with biologic activity. For predicting duodenal ulceration, dipole moment, melting point, and solubility in octanol are particularly important, while for predicting adrenal necrosis, important features include the number of sulfhydryl groups and double bonds. These methods may constitute inexpensive but powerful ways to screen untested compounds for possible organ-specific toxicity. Mechanisms for the etiology and pathogenesis of the duodenal and adrenal lesions are suggested, as are additional avenues for drug design.

Corresponding-states behavior of SPC/E-based modified (bent and hybrid) water models

NASA Astrophysics Data System (ADS)

Weiss, Volker C.

2017-02-01

The remarkable and sometimes anomalous properties of water can be traced back at the molecular level to the tetrahedral coordination of molecules due to the ability of a water molecule to form four hydrogen bonds to its neighbors; this feature allows for the formation of a network that greatly influences the thermodynamic behavior. Computer simulations are becoming increasingly important for our understanding of water. Molecular models of water, such as SPC/E, are needed for this purpose, and they have proved to capture many important features of real water. Modifications of the SPC/E model have been proposed, some changing the H-O-H angle (bent models) and others increasing the importance of dispersion interactions (hybrid models), to study the structural features that set water apart from other polar fluids and from simple fluids such as argon. Here, we focus on the properties at liquid-vapor equilibrium and study the coexistence curve, the interfacial tension, and the vapor pressure in a corresponding-states approach. In particular, we calculate Guggenheim's ratio for the reduced apparent enthalpy of vaporization and Guldberg's ratio for the reduced normal boiling point. This analysis offers additional insight from a more macroscopic, thermodynamic perspective and augments that which has already been learned at the molecular level from simulations. In the hybrid models, the relative importance of dispersion interactions is increased, which turns the modified water into a Lennard-Jones-like fluid. Consequently, in a corresponding-states framework, the typical behavior of simple fluids, such as argon, is seen to be approached asymptotically. For the bent models, decreasing the bond angle turns the model essentially into a polar diatomic fluid in which the particles form linear molecular arrangements; as a consequence, characteristic features of the corresponding-states behavior of hydrogen halides emerge.

Design, fabrication, and testing of three-dimensionally ordered macroporous materials for pseudomorphic transformation and power storage

NASA Astrophysics Data System (ADS)

Lytle, Justin Conrad

This dissertation details my study of three-dimensionally ordered macroporous (3DOM) materials, which were prepared using polymer latex colloidal crystal templates. These solids are composed of close-packed and three-dimensionally interconnected spherical macropores surrounded by nanoscale solid wall skeletons. This unique architecture offers relatively large surface areas that are accessible by interconnected macropores, making these materials important for innovative catalysis, sensing, and separations applications. In addition, the three-dimensionally alternating dielectric structure can establish photonic stop bands that control the flow of light analogously to the restraint of electronic conduction by electronic bandgaps. Many potential applications would benefit from reducing device feature sizes from the bulk into the nanoscale regime. However, some compositions are more easily prepared as nanostructured materials than others. Therefore, it would be immensely important to develop synthetic methods of transforming solids that are more easily formed with nanoarchitectural features into compositions that are not. Pseudomorphic transformation reactions may be one solution to this problem, since they are capable of altering chemical composition while maintaining shape and structural morphology. Several compositions of inverse opal and nanostructured preforms were investigated in this work to study the effects of vapor-phase and solution-phase conversion reactions on materials with feature sizes ranging from a few nm to tens of mum. 3DOM SiO2 and WO3, nanostructured Ni, and colloidal silica sphere performs were studied to investigate the effects of preform chemistries, feature sizes and shapes, processing temperatures, and reagent ratios on overall pseudomorphic structural retention. Power storage and fuel cell devices based on nanostructured electrodes are a major example of how reducing device component feature sizes can greatly benefit applications. Bulk electrode geometries have diffusion-limited kinetics and relatively low energy and power densities. Nanostructured electrodes offer extremely short ion diffusion pathlengths and relatively numerous reaction sites. 3DOM SnO2 thin films, 3DOM Li4Ti 5O12 powders, and 3DOM carbon monoliths have been fabricated and characterized in this work as Li-ion anode materials, with 3DOM carbon exhibiting an enormous rate capability beyond similarly prepared, but non-templated, bulk carbon. Furthermore, a novel battery design that is three-dimensionally interpenetrated on the nanoscale was prepared and evaluated in this research.

Human β-glucuronidase: structure, function, and application in enzyme replacement therapy.

PubMed

Naz, Huma; Islam, Asimul; Waheed, Abdul; Sly, William S; Ahmad, Faizan; Hassan, Imtaiyaz

2013-10-01

Lysosomal storage diseases occur due to incomplete metabolic degradation of macromolecules by various hydrolytic enzymes in the lysosome. Despite structural differences, most of the lysosomal enzymes share many common features including a lysosomal targeting motif and phosphotransferase recognition sites. β-Glucuronidase (GUSB) is an important lysosomal enzyme involved in the degradation of glucuronate-containing glycosaminoglycan. The deficiency of GUSB causes mucopolysaccharidosis type VII (MPSVII), leading to lysosomal storage in the brain. GUSB is a well-studied protein for its expression, sequence, structure, and function. The purpose of this review is to summarize our current understanding of sequence, structure, function, and evolution of GUSB and its lysosomal enzyme targeting. Enzyme replacement therapy reported for this protein is also discussed.

Combining Landform Thematic Layer and Object-Oriented Image Analysis to Map the Surface Features of Mountainous Flood Plain Areas

NASA Astrophysics Data System (ADS)

Chuang, H.-K.; Lin, M.-L.; Huang, W.-C.

2012-04-01

The Typhoon Morakot on August 2009 brought more than 2,000 mm of cumulative rainfall in southern Taiwan, the extreme rainfall event caused serious damage to the Kaoping River basin. The losses were mostly blamed on the landslides along sides of the river, and shifting of the watercourse even led to the failure of roads and bridges, as well as flooding and levees damage happened around the villages on flood bank and terraces. Alluvial fans resulted from debris flow of stream feeders blocked the main watercourse and debris dam was even formed and collapsed. These disasters have highlighted the importance of identification and map the watercourse alteration, surface features of flood plain area and artificial structures soon after the catastrophic typhoon event for natural hazard mitigation. Interpretation of remote sensing images is an efficient approach to acquire spatial information for vast areas, therefore making it suitable for the differentiation of terrain and objects near the vast flood plain areas in a short term. The object-oriented image analysis program (Definiens Developer 7.0) and multi-band high resolution satellite images (QuickBird, DigitalGlobe) was utilized to interpret the flood plain features from Liouguei to Baolai of the the Kaoping River basin after Typhoon Morakot. Object-oriented image interpretation is the process of using homogenized image blocks as elements instead of pixels for different shapes, textures and the mutual relationships of adjacent elements, as well as categorized conditions and rules for semi-artificial interpretation of surface features. Digital terrain models (DTM) are also employed along with the above process to produce layers with specific "landform thematic layers". These layers are especially helpful in differentiating some confusing categories in the spectrum analysis with improved accuracy, such as landslides and riverbeds, as well as terraces, riverbanks, which are of significant engineering importance in disaster mitigation. In this study, an automatic and fast image interpretation process for eight surface features including main channel, secondary channel, sandbar, flood plain, river terrace, alluvial fan, landslide, and the nearby artificial structures in the mountainous flood plain is proposed. Images along timelines can even be compared in order to differentiate historical events such as village inundations, failure of roads, bridges and levees, as well as alternation of watercourse, and therefore can be used as references for safety evaluation of engineering structures near rivers, disaster prevention and mitigation, and even future land-use planning. Keywords: Flood plain area, Remote sensing, Object-oriented, Surface feature interpretation, Terrain analysis, Thematic layer, Typhoon Morakot

Habitat predictors of genetic diversity for two sympatric wetland-breeding amphibian species.

PubMed

McKee, Anna M; Maerz, John C; Smith, Lora L; Glenn, Travis C

2017-08-01

Population genetic diversity is widely accepted as important to the conservation and management of wildlife. However, habitat features may differentially affect evolutionary processes that facilitate population genetic diversity among sympatric species. We measured genetic diversity for two pond-breeding amphibian species (Dwarf salamanders, Eurycea quadridigitata ; and Southern Leopard frogs, Lithobates sphenocephalus ) to understand how habitat characteristics and spatial scale affect genetic diversity across a landscape. Samples were collected from wetlands on a longleaf pine reserve in Georgia. We genotyped microsatellite loci for both species to assess population structures and determine which habitat features were most closely associated with observed heterozygosity and rarefied allelic richness. Both species exhibited significant population genetic structure; however, structure in Southern Leopard frogs was driven primarily by one outlier site. Dwarf salamander allelic richness was greater at sites with less surrounding road area within 0.5 km and more wetland area within 1.0 and 2.5 km, and heterozygosity was greater at sites with more wetland area within 0.5 km. In contrast, neither measure of Southern Leopard frog genetic diversity was associated with any habitat features at any scale we evaluated. Genetic diversity in the Dwarf salamander was strongly associated with land cover variables up to 2.5 km away from breeding wetlands, and/or results suggest that minimizing roads in wetland buffers may be beneficial to the maintenance of population genetic diversity. This study suggests that patterns of genetic differentiation and genetic diversity have associations with different habitat features across different spatial scales for two syntopic pond-breeding amphibian species.

EEG resolutions in detecting and decoding finger movements from spectral analysis

PubMed Central

Xiao, Ran; Ding, Lei

2015-01-01

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

The devil is in the detail: brain dynamics in preparation for a global-local task.

PubMed

Leaver, Echo E; Low, Kathy A; DiVacri, Assunta; Merla, Arcangelo; Fabiani, Monica; Gratton, Gabriele

2015-08-01

When analyzing visual scenes, it is sometimes important to determine the relevant "grain" size. Attention control mechanisms may help direct our processing to the intended grain size. Here we used the event-related optical signal, a method possessing high temporal and spatial resolution, to examine the involvement of brain structures within the dorsal attention network (DAN) and the visual processing network (VPN) in preparation for the appropriate level of analysis. Behavioral data indicate that the small features of a hierarchical stimulus (local condition) are more difficult to process than the large features (global condition). Consistent with this finding, cues predicting a local trial were associated with greater DAN activation. This activity was bilateral but more pronounced in the left hemisphere, where it showed a frontal-to-parietal progression over time. Furthermore, the amount of DAN activation, especially in the left hemisphere and in parietal regions, was predictive of subsequent performance. Although local cues elicited left-lateralized DAN activity, no preponderantly right activity was observed for global cues; however, the data indicated an interaction between level of analysis (local vs. global) and hemisphere in VPN. They further showed that local processing involves structures in the ventral VPN, whereas global processing involves structures in the dorsal VPN. These results indicate that in our study preparation for analyzing different size features is an asymmetric process, in which greater preparation is required to focus on small rather than large features, perhaps because of their lesser salience. This preparation involves the same DAN used for other attention control operations.

Prediction of Protein Structural Classes for Low-Similarity Sequences Based on Consensus Sequence and Segmented PSSM.

PubMed

Liang, Yunyun; Liu, Sanyang; Zhang, Shengli

2015-01-01

Prediction of protein structural classes for low-similarity sequences is useful for understanding fold patterns, regulation, functions, and interactions of proteins. It is well known that feature extraction is significant to prediction of protein structural class and it mainly uses protein primary sequence, predicted secondary structure sequence, and position-specific scoring matrix (PSSM). Currently, prediction solely based on the PSSM has played a key role in improving the prediction accuracy. In this paper, we propose a novel method called CSP-SegPseP-SegACP by fusing consensus sequence (CS), segmented PsePSSM, and segmented autocovariance transformation (ACT) based on PSSM. Three widely used low-similarity datasets (1189, 25PDB, and 640) are adopted in this paper. Then a 700-dimensional (700D) feature vector is constructed and the dimension is decreased to 224D by using principal component analysis (PCA). To verify the performance of our method, rigorous jackknife cross-validation tests are performed on 1189, 25PDB, and 640 datasets. Comparison of our results with the existing PSSM-based methods demonstrates that our method achieves the favorable and competitive performance. This will offer an important complementary to other PSSM-based methods for prediction of protein structural classes for low-similarity sequences.

MUFOLD-SS: New deep inception-inside-inception networks for protein secondary structure prediction.

PubMed

Fang, Chao; Shang, Yi; Xu, Dong

2018-05-01

Protein secondary structure prediction can provide important information for protein 3D structure prediction and protein functions. Deep learning offers a new opportunity to significantly improve prediction accuracy. In this article, a new deep neural network architecture, named the Deep inception-inside-inception (Deep3I) network, is proposed for protein secondary structure prediction and implemented as a software tool MUFOLD-SS. The input to MUFOLD-SS is a carefully designed feature matrix corresponding to the primary amino acid sequence of a protein, which consists of a rich set of information derived from individual amino acid, as well as the context of the protein sequence. Specifically, the feature matrix is a composition of physio-chemical properties of amino acids, PSI-BLAST profile, and HHBlits profile. MUFOLD-SS is composed of a sequence of nested inception modules and maps the input matrix to either eight states or three states of secondary structures. The architecture of MUFOLD-SS enables effective processing of local and global interactions between amino acids in making accurate prediction. In extensive experiments on multiple datasets, MUFOLD-SS outperformed the best existing methods and other deep neural networks significantly. MUFold-SS can be downloaded from http://dslsrv8.cs.missouri.edu/~cf797/MUFoldSS/download.html. © 2018 Wiley Periodicals, Inc.

Predicting hot spots in protein interfaces based on protrusion index, pseudo hydrophobicity and electron-ion interaction pseudopotential features

PubMed Central

Xia, Junfeng; Yue, Zhenyu; Di, Yunqiang; Zhu, Xiaolei; Zheng, Chun-Hou

2016-01-01

The identification of hot spots, a small subset of protein interfaces that accounts for the majority of binding free energy, is becoming more important for the research of drug design and cancer development. Based on our previous methods (APIS and KFC2), here we proposed a novel hot spot prediction method. For each hot spot residue, we firstly constructed a wide variety of 108 sequence, structural, and neighborhood features to characterize potential hot spot residues, including conventional ones and new one (pseudo hydrophobicity) exploited in this study. We then selected 3 top-ranking features that contribute the most in the classification by a two-step feature selection process consisting of minimal-redundancy-maximal-relevance algorithm and an exhaustive search method. We used support vector machines to build our final prediction model. When testing our model on an independent test set, our method showed the highest F1-score of 0.70 and MCC of 0.46 comparing with the existing state-of-the-art hot spot prediction methods. Our results indicate that these features are more effective than the conventional features considered previously, and that the combination of our and traditional features may support the creation of a discriminative feature set for efficient prediction of hot spots in protein interfaces. PMID:26934646

A no-reference bitstream-based perceptual model for video quality estimation of videos affected by coding artifacts and packet losses

NASA Astrophysics Data System (ADS)

Pandremmenou, K.; Shahid, M.; Kondi, L. P.; Lövström, B.

2015-03-01

In this work, we propose a No-Reference (NR) bitstream-based model for predicting the quality of H.264/AVC video sequences, affected by both compression artifacts and transmission impairments. The proposed model is based on a feature extraction procedure, where a large number of features are calculated from the packet-loss impaired bitstream. Many of the features are firstly proposed in this work, and the specific set of the features as a whole is applied for the first time for making NR video quality predictions. All feature observations are taken as input to the Least Absolute Shrinkage and Selection Operator (LASSO) regression method. LASSO indicates the most important features, and using only them, it is possible to estimate the Mean Opinion Score (MOS) with high accuracy. Indicatively, we point out that only 13 features are able to produce a Pearson Correlation Coefficient of 0.92 with the MOS. Interestingly, the performance statistics we computed in order to assess our method for predicting the Structural Similarity Index and the Video Quality Metric are equally good. Thus, the obtained experimental results verified the suitability of the features selected by LASSO as well as the ability of LASSO in making accurate predictions through sparse modeling.

Facial expression identification using 3D geometric features from Microsoft Kinect device

NASA Astrophysics Data System (ADS)

Han, Dongxu; Al Jawad, Naseer; Du, Hongbo

2016-05-01

Facial expression identification is an important part of face recognition and closely related to emotion detection from face images. Various solutions have been proposed in the past using different types of cameras and features. Microsoft Kinect device has been widely used for multimedia interactions. More recently, the device has been increasingly deployed for supporting scientific investigations. This paper explores the effectiveness of using the device in identifying emotional facial expressions such as surprise, smile, sad, etc. and evaluates the usefulness of 3D data points on a face mesh structure obtained from the Kinect device. We present a distance-based geometric feature component that is derived from the distances between points on the face mesh and selected reference points in a single frame. The feature components extracted across a sequence of frames starting and ending by neutral emotion represent a whole expression. The feature vector eliminates the need for complex face orientation correction, simplifying the feature extraction process and making it more efficient. We applied the kNN classifier that exploits a feature component based similarity measure following the principle of dynamic time warping to determine the closest neighbors. Preliminary tests on a small scale database of different facial expressions show promises of the newly developed features and the usefulness of the Kinect device in facial expression identification.

A Wavelet Bicoherence-Based Quadratic Nonlinearity Feature for Translational Axis Condition Monitoring

PubMed Central

Li, Yong; Wang, Xiufeng; Lin, Jing; Shi, Shengyu

2014-01-01

The translational axis is one of the most important subsystems in modern machine tools, as its degradation may result in the loss of the product qualification and lower the control precision. Condition-based maintenance (CBM) has been considered as one of the advanced maintenance schemes to achieve effective, reliable and cost-effective operation of machine systems, however, current vibration-based maintenance schemes cannot be employed directly in the translational axis system, due to its complex structure and the inefficiency of commonly used condition monitoring features. In this paper, a wavelet bicoherence-based quadratic nonlinearity feature is proposed for translational axis condition monitoring by using the torque signature of the drive servomotor. Firstly, the quadratic nonlinearity of the servomotor torque signature is discussed, and then, a biphase randomization wavelet bicoherence is introduced for its quadratic nonlinear detection. On this basis, a quadratic nonlinearity feature is proposed for condition monitoring of the translational axis. The properties of the proposed quadratic nonlinearity feature are investigated by simulations. Subsequently, this feature is applied to the real-world servomotor torque data collected from the X-axis on a high precision vertical machining centre. All the results show that the performance of the proposed feature is much better than that of original condition monitoring features. PMID:24473281

Gold nanocrystals with DNA-directed morphologies.

PubMed

Ma, Xingyi; Huh, June; Park, Wounjhang; Lee, Luke P; Kwon, Young Jik; Sim, Sang Jun

2016-09-16

Precise control over the structure of metal nanomaterials is important for developing advanced nanobiotechnology. Assembly methods of nanoparticles into structured blocks have been widely demonstrated recently. However, synthesis of nanocrystals with controlled, three-dimensional structures remains challenging. Here we show a directed crystallization of gold by a single DNA molecular regulator in a sequence-independent manner and its applications in three-dimensional topological controls of crystalline nanostructures. We anchor DNA onto gold nanoseed with various alignments to form gold nanocrystals with defined topologies. Some topologies are asymmetric including pushpin-, star- and biconcave disk-like structures, as well as more complex jellyfish- and flower-like structures. The approach of employing DNA enables the solution-based synthesis of nanocrystals with controlled, three-dimensional structures in a desired direction, and expands the current tools available for designing and synthesizing feature-rich nanomaterials for future translational biotechnology.

Gold nanocrystals with DNA-directed morphologies

NASA Astrophysics Data System (ADS)

Ma, Xingyi; Huh, June; Park, Wounjhang; Lee, Luke P.; Kwon, Young Jik; Sim, Sang Jun

2016-09-01

Precise control over the structure of metal nanomaterials is important for developing advanced nanobiotechnology. Assembly methods of nanoparticles into structured blocks have been widely demonstrated recently. However, synthesis of nanocrystals with controlled, three-dimensional structures remains challenging. Here we show a directed crystallization of gold by a single DNA molecular regulator in a sequence-independent manner and its applications in three-dimensional topological controls of crystalline nanostructures. We anchor DNA onto gold nanoseed with various alignments to form gold nanocrystals with defined topologies. Some topologies are asymmetric including pushpin-, star- and biconcave disk-like structures, as well as more complex jellyfish- and flower-like structures. The approach of employing DNA enables the solution-based synthesis of nanocrystals with controlled, three-dimensional structures in a desired direction, and expands the current tools available for designing and synthesizing feature-rich nanomaterials for future translational biotechnology.

Some Surprising Implications of NMR-directed Simulations of Substrate Recognition and Binding by Cytochrome P450cam (CYP101A1).

PubMed

Asciutto, Eliana K; Pochapsky, Thomas C

2018-04-27

Cytochrome P450 cam (CYP101A1) catalyzes the stereospecific 5-exo hydroxylation of d-camphor by molecular oxygen. Previously, residual dipolar couplings measured for backbone amide 1 H- 15 N correlations in both substrate-free and bound forms of CYP101A1 were used as restraints in soft annealing molecular dynamic simulations in order to identify average conformations of the enzyme with and without substrate bound. Multiple substrate-dependent conformational changes remote from the enzyme active site were identified, and site-directed mutagenesis and activity assays confirmed the importance of these changes in substrate recognition. The current work makes use of perturbation response scanning (PRS) and umbrella sampling molecular dynamic of the residual dipolar coupling-derived CYP101A1 structures to probe the roles of remote structural features in enforcing the regio- and stereospecific nature of the hydroxylation reaction catalyzed by CYP101A1. An improper dihedral angle Ψ was defined and used to maintain substrate orientation in the CYP101A1 active site, and it was observed that different values of Ψ result in different PRS response maps. Umbrella sampling methods show that the free energy of the system is sensitive to Ψ, and bound substrate forms an important mechanical link in the transmission of mechanical coupling through the enzyme structure. Finally, a qualitative approach to interpreting PRS maps in terms of the roles of secondary structural features is proposed. Copyright © 2018 Elsevier Ltd. All rights reserved.

Occurrence and structure of epipharyngeal pouches in bears (Ursidae)

PubMed Central

WEISSENGRUBER, G. E.; FORSTENPOINTNER, G.; KÜBBER-HEISS, A.; RIEDELBERGER, K.; SCHWAMMER, H.; GANZBERGER, K.

2001-01-01

The infrequent mention of epipharyngeal pouches occurring in some species of bears indicates the scarcity of morphological and functional knowledge about these structures. In order to provide precise morphological data on the structure of these remarkable formations and to verify their taxonomic utility, the pharyngeal regions of 1 spectacled bear and 3 brown bears were examined. All these individuals possessed epipharyngeal pouches, which are tubular, blind-ending outpouchings of the caudodorsal pharyngeal wall equipped with respiratory epithelium and a thick layer of elastic fibres. While the spectacled bear and Ursus arctos syriacus possessed a single pouch on the caudodorsal wall of the nasopharynx, in Ursus arctos and Ursus arctos beringianus 2 unequally sized pouches were present. Two additional sacs of smaller size, representing outpouchings of the lateral pharyngeal wall, occurred in the spectacled bear. These findings prove epipharyngeal pouches to be constant and unique morphological features of the family Ursidae, the anatomical features suggesting involvement in the respiratory system most probably in important aspects of ursid phonation. This is the first description of epipharyngeal pouches in the spectacled bear. PMID:11322723

Mechanical Properties of the Upper Airway

PubMed Central

Strohl, Kingman P.; Butler, James P.; Malhotra, Atul

2013-01-01

The importance of the upper airway (nose, pharynx, and larynx) in health and in the pathogenesis of sleep apnea, asthma, and other airway diseases, discussed elsewhere in the Comprehensive Physiology series, prompts this review of the biomechanical properties and functional aspects of the upper airway. There is a literature based on anatomic or structural descriptions in static circumstances, albeit studied in limited numbers of individuals in both health and disease. As for dynamic features, the literature is limited to studies of pressure and flow through all or parts of the upper airway and to the effects of muscle activation on such features; however, the links between structure and function through airway size, shape, and compliance remain a topic that is completely open for investigation, particularly through analyses using concepts of fluid and structural mechanics. Throughout are included both historically seminal references, as well as those serving as signposts or updated reviews. This article should be considered a resource for concepts needed for the application of biomechanical models of upper airway physiology, applicable to understanding the pathophysiology of disease and anticipated results of treatment interventions. PMID:23723026

Algorithm, applications and evaluation for protein comparison by Ramanujan Fourier transform.

PubMed

Zhao, Jian; Wang, Jiasong; Hua, Wei; Ouyang, Pingkai

2015-12-01

The amino acid sequence of a protein determines its chemical properties, chain conformation and biological functions. Protein sequence comparison is of great importance to identify similarities of protein structures and infer their functions. Many properties of a protein correspond to the low-frequency signals within the sequence. Low frequency modes in protein sequences are linked to the secondary structures, membrane protein types, and sub-cellular localizations of the proteins. In this paper, we present Ramanujan Fourier transform (RFT) with a fast algorithm to analyze the low-frequency signals of protein sequences. The RFT method is applied to similarity analysis of protein sequences with the Resonant Recognition Model (RRM). The results show that the proposed fast RFT method on protein comparison is more efficient than commonly used discrete Fourier transform (DFT). RFT can detect common frequencies as significant feature for specific protein families, and the RFT spectrum heat-map of protein sequences demonstrates the information conservation in the sequence comparison. The proposed method offers a new tool for pattern recognition, feature extraction and structural analysis on protein sequences. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

Anatomic Peculiarities of Pig and Human Liver.

PubMed

Nykonenko, Andriy; Vávra, Petr; Zonča, Pavel

2017-02-01

Many investigations on surgical methods and medical treatment are currently done on pigs. This is possible because the pig is sufficiently close genetically to humans. In recent years, progress in liver surgery has opened new possibilities in surgical treatment of liver diseases. Because the methods are relatively novel, various improvements are still needed, and it is thus helpful to conduct experimental surgeries on pig livers. We reviewed the literature to compare the anatomic and functional features of pig and human livers, information that will be of great importance for improving surgical techniques. During the literature review, we used various sources, such as PubMed, Scopus, and veterinary journals. Our results were summarized in diagrams to facilitate understanding of the vascular structure and biliary systems. We conclude that, although the shapes of the human and pig livers are quite different, the pig liver is divided into the same number of segments as the human liver, which also shows a common structure of the vascular system. Thus, with the anatomic and structural features of the pig liver taken into account, this animal model can be used in experimental hepatic surgery.

Anomalous sea surface structures as an object of statistical topography

NASA Astrophysics Data System (ADS)

Klyatskin, V. I.; Koshel, K. V.

2015-06-01

By exploiting ideas of statistical topography, we analyze the stochastic boundary problem of emergence of anomalous high structures on the sea surface. The kinematic boundary condition on the sea surface is assumed to be a closed stochastic quasilinear equation. Applying the stochastic Liouville equation, and presuming the stochastic nature of a given hydrodynamic velocity field within the diffusion approximation, we derive an equation for a spatially single-point, simultaneous joint probability density of the surface elevation field and its gradient. An important feature of the model is that it accounts for stochastic bottom irregularities as one, but not a single, perturbation. Hence, we address the assumption of the infinitely deep ocean to obtain statistic features of the surface elevation field and the squared elevation gradient field. According to the calculations, we show that clustering in the absolute surface elevation gradient field happens with the unit probability. It results in the emergence of rare events such as anomalous high structures and deep gaps on the sea surface almost in every realization of a stochastic velocity field.

Synthesis, activity and pharmacophore development for isatin-β-thiosemicarbazones with selective activity towards multidrug resistant cellsa

PubMed Central

Hall, Matthew D.; Salam, Noeris K.; Hellawell, Jennifer L.; Fales, Henry M.; Kensler, Caroline B.; Ludwig, Joseph A.; Szakacs, Gergely; Hibbs, David E.; Gottesman, Michael M.

2009-01-01

We have recently identified a new class of compounds that selectively kill cells that express P-glycoprotein (P-gp, MDR1), the ATPase efflux pump that confers multidrug resistance on cancer cells. Several isatin-β-thiosemicarbazones from our initial study have been validated, and a range of analogs synthesized and tested. A number demonstrated improved MDR1-selective activity over the lead, NSC73306 (1). Pharmacophores for cytotoxicity and MDR1-selectivity were generated to delineate the structural features required for activity. The MDR1-selective pharmacophore highlights the importance of aromatic/hydrophobic features at the N4 position of the thiosemicarbazone, and the reliance on the isatin moiety as key bioisosteric contributors. Additionally, a quantitative structure-activity relationship (QSAR) model that yielded a cross-validated correlation coefficient of 0.85 effectively predicts the cytotoxicty of untested thiosemicarbazones. Together, the models serve as effective approaches for predicting structures with MDR1-selective activity, and aid in directing the search for the mechanism of action of 1. PMID:19397322

Ketide Synthase (KS) Domain Prediction and Analysis of Iterative Type II PKS Gene in Marine Sponge-Associated Actinobacteria Producing Biosurfactants and Antimicrobial Agents

PubMed Central

Selvin, Joseph; Sathiyanarayanan, Ganesan; Lipton, Anuj N.; Al-Dhabi, Naif Abdullah; Valan Arasu, Mariadhas; Kiran, George S.

2016-01-01

The important biological macromolecules, such as lipopeptide and glycolipid biosurfactant producing marine actinobacteria were analyzed and their potential linkage between type II polyketide synthase (PKS) genes was explored. A unique feature of type II PKS genes is their high amino acid (AA) sequence homology and conserved gene organization. These enzymes mediate the biosynthesis of polyketide natural products with enormous structural complexity and chemical nature by combinatorial use of various domains. Therefore, deciphering the order of AA sequence encoded by PKS domains tailored the chemical structure of polyketide analogs still remains a great challenge. The present work deals with an in vitro and in silico analysis of PKS type II genes from five actinobacterial species to correlate KS domain architecture and structural features. Our present analysis reveals the unique protein domain organization of iterative type II PKS and KS domain of marine actinobacteria. The findings of this study would have implications in metabolic pathway reconstruction and design of semi-synthetic genomes to achieve rational design of novel natural products. PMID:26903957

Clark's nutcracker spatial memory: the importance of large, structural cues.

PubMed

Bednekoff, Peter A; Balda, Russell P

2014-02-01

Clark's nutcrackers, Nucifraga columbiana, cache and recover stored seeds in high alpine areas including areas where snowfall, wind, and rockslides may frequently obscure or alter cues near the cache site. Previous work in the laboratory has established that Clark's nutcrackers use spatial memory to relocate cached food. Following from aspects of this work, we performed experiments to test the importance of large, structural cues for Clark's nutcracker spatial memory. Birds were no more accurate in recovering caches when more objects were on the floor of a large experimental room nor when this room was subdivided with a set of panels. However, nutcrackers were consistently less accurate in this large room than in a small experimental room. Clark's nutcrackers probably use structural features of experimental rooms as important landmarks during recovery of cached food. This use of large, extremely stable cues may reflect the imperfect reliability of smaller, closer cues in the natural habitat of Clark's nutcrackers. This article is part of a Special Issue entitled: CO3 2013. Copyright © 2013 Elsevier B.V. All rights reserved.

Utilizing a structural meta-ontology for family-based quality assurance of the BioPortal ontologies.

PubMed

Ochs, Christopher; He, Zhe; Zheng, Ling; Geller, James; Perl, Yehoshua; Hripcsak, George; Musen, Mark A

2016-06-01

An Abstraction Network is a compact summary of an ontology's structure and content. In previous research, we showed that Abstraction Networks support quality assurance (QA) of biomedical ontologies. The development of an Abstraction Network and its associated QA methodologies, however, is a labor-intensive process that previously was applicable only to one ontology at a time. To improve the efficiency of the Abstraction-Network-based QA methodology, we introduced a QA framework that uses uniform Abstraction Network derivation techniques and QA methodologies that are applicable to whole families of structurally similar ontologies. For the family-based framework to be successful, it is necessary to develop a method for classifying ontologies into structurally similar families. We now describe a structural meta-ontology that classifies ontologies according to certain structural features that are commonly used in the modeling of ontologies (e.g., object properties) and that are important for Abstraction Network derivation. Each class of the structural meta-ontology represents a family of ontologies with identical structural features, indicating which types of Abstraction Networks and QA methodologies are potentially applicable to all of the ontologies in the family. We derive a collection of 81 families, corresponding to classes of the structural meta-ontology, that enable a flexible, streamlined family-based QA methodology, offering multiple choices for classifying an ontology. The structure of 373 ontologies from the NCBO BioPortal is analyzed and each ontology is classified into multiple families modeled by the structural meta-ontology. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Extraction of prostatic lumina and automated recognition for prostatic calculus image using PCA-SVM.

PubMed

Wang, Zhuocai; Xu, Xiangmin; Ding, Xiaojun; Xiao, Hui; Huang, Yusheng; Liu, Jian; Xing, Xiaofen; Wang, Hua; Liao, D Joshua

2011-01-01

Identification of prostatic calculi is an important basis for determining the tissue origin. Computation-assistant diagnosis of prostatic calculi may have promising potential but is currently still less studied. We studied the extraction of prostatic lumina and automated recognition for calculus images. Extraction of lumina from prostate histology images was based on local entropy and Otsu threshold recognition using PCA-SVM and based on the texture features of prostatic calculus. The SVM classifier showed an average time 0.1432 second, an average training accuracy of 100%, an average test accuracy of 93.12%, a sensitivity of 87.74%, and a specificity of 94.82%. We concluded that the algorithm, based on texture features and PCA-SVM, can recognize the concentric structure and visualized features easily. Therefore, this method is effective for the automated recognition of prostatic calculi.

Distinctiveness of management in a university psychiatric hospital as a public health institution.

PubMed

Koncina, Miroslav

2008-06-01

The distinctiveness of management of a university psychiatric hospital which has the status of a public health institution is manifested in the following ways: * Distinctive features and characteristics of managing service provider organizations compared to those whose operational results involve tangible products; * Distinctive features of management which originate from its role as a regional hospital and a tertiary research and educational institution in the field of psychiatry, with special importance for the Republic of Slovenia as a whole; * Distinctive features of management that are defined by the social and legal framework of operation of public health institutions and their special social mission. This paper therefore discusses the specific theoretical and practical findings regarding management of service provider organizations from the viewpoint of their social mission and significance, as well as their legal organization, internal structure and values.

Administrative records and surveys as basis for statistics on international labour migration.

PubMed

Hoffmann, E

1997-08-01

"This paper discusses possible sources for statistics to be used for describing and analysing the number, structure, situation, development and impact of migrant workers. The discussion is focused on key, intrinsic features of the different sources, important for the understanding of their strengths and weaknesses, and draws the reader's attention to features which may tend to undermine the quality of statistics produced as well as ways in which the impact of such features can be evaluated and, if possible, reduced.... The paper is organized around three key groups of migrant workers: (a) Persons who are arriving in a country to work there, i.e. the inflow of foreign workers; (b) Persons who are leaving their country to find work abroad, i.e. the outflow of migrant workers; [and] (c) Stock of foreign workers in the country." (EXCERPT)

Quasiparticle self-consistent GW study of cuprates: electronic structure, model parameters, and the two-band theory for Tc

PubMed Central

Jang, Seung Woo; Kotani, Takao; Kino, Hiori; Kuroki, Kazuhiko; Han, Myung Joon

2015-01-01

Despite decades of progress, an understanding of unconventional superconductivity still remains elusive. An important open question is about the material dependence of the superconducting properties. Using the quasiparticle self-consistent GW method, we re-examine the electronic structure of copper oxide high-Tc materials. We show that QSGW captures several important features, distinctive from the conventional LDA results. The energy level splitting between and is significantly enlarged and the van Hove singularity point is lowered. The calculated results compare better than LDA with recent experimental results from resonant inelastic xray scattering and angle resolved photoemission experiments. This agreement with the experiments supports the previously suggested two-band theory for the material dependence of the superconducting transition temperature, Tc. PMID:26206417

Crown dynamics and wood production of Douglas-fir trees in an old-growth forest

Treesearch

H. Roaki Ishii; Stephen C. Sillett; Allyson L. Carroll

2017-01-01

Large trees are the most prominent structural features of old-growth forests, which are considered to be globally important carbon sinks. Because of their large size, estimates of biomass and growth of large trees are often based on ground-level measurements (e.g., diameter at breast height, DBH) and little is known about growth dynamics within the crown. As trees...

Interactive Medical Volume Visualization for Surgical Operations

DTIC Science & Technology

2001-10-25

the preprocessing and processing stages, related medical brain tissues, which are skull, white matter, gray matter and pathology ( tumor ), are segmented ...from 12 or 16 bit data depths. NMR segmentation plays an important role in our work, because, classifying brain tissues from NMR slices requires an...performing segmentation of brain structures. Our segmentation process uses Self Organizing Feature Maps (SOFM) [12]. In SOM, on the contrary to Feedback

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

PubMed Central

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

2015-01-01

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