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Unique contributions of dynamic versus global measures of parent-child interaction quality in predicting school adjustment.

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Bardack, Sarah; Herbers, Janette E; Obradović, Jelena

2017-09-01

This study investigates the unique contribution of microsocial and global measures of parent-child positive coregulation (PCR) in predicting children's behavioral and social adjustment in school. Using a community sample of 102 children, ages 4-6, and their parents, we conducted nested path analytic models to identify the unique effects of 2 measures of PCR on school outcomes. Microsocial PCR independently predicted fewer externalizing and inattention/impulsive behaviors in school. Global PCR did not uniquely relate to children's behavioral and social adjustment outcomes. Household socioeconomic status was related to both microsocial and global measures of PCR, but not directly associated with school outcomes. Findings illustrate the importance of using dynamic measures of PCR based on microsocial coding to further understand how the quality of parent-child interaction is related to children's self-regulatory and social development during school transition. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Development of METAL-ACTIVE SITE and ZINCCLUSTER tool to predict active site pockets.

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Ajitha, M; Sundar, K; Arul Mugilan, S; Arumugam, S

2018-03-01

The advent of whole genome sequencing leads to increasing number of proteins with known amino acid sequences. Despite many efforts, the number of proteins with resolved three dimensional structures is still low. One of the challenging tasks the structural biologists face is the prediction of the interaction of metal ion with any protein for which the structure is unknown. Based on the information available in Protein Data Bank, a site (METALACTIVE INTERACTION) has been generated which displays information for significant high preferential and low-preferential combination of endogenous ligands for 49 metal ions. User can also gain information about the residues present in the first and second coordination sphere as it plays a major role in maintaining the structure and function of metalloproteins in biological system. In this paper, a novel computational tool (ZINCCLUSTER) is developed, which can predict the zinc metal binding sites of proteins even if only the primary sequence is known. The purpose of this tool is to predict the active site cluster of an uncharacterized protein based on its primary sequence or a 3D structure. The tool can predict amino acids interacting with a metal or vice versa. This tool is based on the occurrence of significant triplets and it is tested to have higher prediction accuracy when compared to that of other available techniques. © 2017 Wiley Periodicals, Inc.

PREDICTION OF SOLAR FLARES USING UNIQUE SIGNATURES OF MAGNETIC FIELD IMAGES

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Raboonik, Abbas; Safari, Hossein; Alipour, Nasibe [Department of Physics, University of Zanjan, P.O. Box 45195-313, Zanjan (Iran, Islamic Republic of); Wheatland, Michael S., E-mail: raboonik@alumni.znu.ac.ir, E-mail: safari@znu.ac.ir [Sydney Institute for Astronomy, School of Physics, The University of Sydney, NSW 2006 (Australia)

2017-01-01

Prediction of solar flares is an important task in solar physics. The occurrence of solar flares is highly dependent on the structure and topology of solar magnetic fields. A new method for predicting large (M- and X-class) flares is presented, which uses machine learning methods applied to the Zernike moments (ZM) of magnetograms observed by the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory for a period of six years from 2010 June 2 to 2016 August 1. Magnetic field images consisting of the radial component of the magnetic field are converted to finite sets of ZMs and fed to the support vector machine classifier. ZMs have the capability to elicit unique features from any 2D image, which may allow more accurate classification. The results indicate whether an arbitrary active region has the potential to produce at least one large flare. We show that the majority of large flares can be predicted within 48 hr before their occurrence, with only 10 false negatives out of 385 flaring active region magnetograms and 21 false positives out of 179 non-flaring active region magnetograms. Our method may provide a useful tool for the prediction of solar flares, which can be employed alongside other forecasting methods.

Transcription factor binding sites prediction based on modified nucleosomes.

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Mohammad Talebzadeh

Full Text Available In computational methods, position weight matrices (PWMs are commonly applied for transcription factor binding site (TFBS prediction. Although these matrices are more accurate than simple consensus sequences to predict actual binding sites, they usually produce a large number of false positive (FP predictions and so are impoverished sources of information. Several studies have employed additional sources of information such as sequence conservation or the vicinity to transcription start sites to distinguish true binding regions from random ones. Recently, the spatial distribution of modified nucleosomes has been shown to be associated with different promoter architectures. These aligned patterns can facilitate DNA accessibility for transcription factors. We hypothesize that using data from these aligned and periodic patterns can improve the performance of binding region prediction. In this study, we propose two effective features, "modified nucleosomes neighboring" and "modified nucleosomes occupancy", to decrease FP in binding site discovery. Based on these features, we designed a logistic regression classifier which estimates the probability of a region as a TFBS. Our model learned each feature based on Sp1 binding sites on Chromosome 1 and was tested on the other chromosomes in human CD4+T cells. In this work, we investigated 21 histone modifications and found that only 8 out of 21 marks are strongly correlated with transcription factor binding regions. To prove that these features are not specific to Sp1, we combined the logistic regression classifier with the PWM, and created a new model to search TFBSs on the genome. We tested the model using transcription factors MAZ, PU.1 and ELF1 and compared the results to those using only the PWM. The results show that our model can predict Transcription factor binding regions more successfully. The relative simplicity of the model and capability of integrating other features make it a superior method

Detection and characterization of 3D-signature phosphorylation site motifs and their contribution towards improved phosphorylation site prediction in proteins

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Selbig Joachim

2009-04-01

Full Text Available Abstract Background Phosphorylation of proteins plays a crucial role in the regulation and activation of metabolic and signaling pathways and constitutes an important target for pharmaceutical intervention. Central to the phosphorylation process is the recognition of specific target sites by protein kinases followed by the covalent attachment of phosphate groups to the amino acids serine, threonine, or tyrosine. The experimental identification as well as computational prediction of phosphorylation sites (P-sites has proved to be a challenging problem. Computational methods have focused primarily on extracting predictive features from the local, one-dimensional sequence information surrounding phosphorylation sites. Results We characterized the spatial context of phosphorylation sites and assessed its usability for improved phosphorylation site predictions. We identified 750 non-redundant, experimentally verified sites with three-dimensional (3D structural information available in the protein data bank (PDB and grouped them according to their respective kinase family. We studied the spatial distribution of amino acids around phosphorserines, phosphothreonines, and phosphotyrosines to extract signature 3D-profiles. Characteristic spatial distributions of amino acid residue types around phosphorylation sites were indeed discernable, especially when kinase-family-specific target sites were analyzed. To test the added value of using spatial information for the computational prediction of phosphorylation sites, Support Vector Machines were applied using both sequence as well as structural information. When compared to sequence-only based prediction methods, a small but consistent performance improvement was obtained when the prediction was informed by 3D-context information. Conclusion While local one-dimensional amino acid sequence information was observed to harbor most of the discriminatory power, spatial context information was identified as

A systems biology approach to transcription factor binding site prediction.

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Xiang Zhou

2010-03-01

Full Text Available The elucidation of mammalian transcriptional regulatory networks holds great promise for both basic and translational research and remains one the greatest challenges to systems biology. Recent reverse engineering methods deduce regulatory interactions from large-scale mRNA expression profiles and cross-species conserved regulatory regions in DNA. Technical challenges faced by these methods include distinguishing between direct and indirect interactions, associating transcription regulators with predicted transcription factor binding sites (TFBSs, identifying non-linearly conserved binding sites across species, and providing realistic accuracy estimates.We address these challenges by closely integrating proven methods for regulatory network reverse engineering from mRNA expression data, linearly and non-linearly conserved regulatory region discovery, and TFBS evaluation and discovery. Using an extensive test set of high-likelihood interactions, which we collected in order to provide realistic prediction-accuracy estimates, we show that a careful integration of these methods leads to significant improvements in prediction accuracy. To verify our methods, we biochemically validated TFBS predictions made for both transcription factors (TFs and co-factors; we validated binding site predictions made using a known E2F1 DNA-binding motif on E2F1 predicted promoter targets, known E2F1 and JUND motifs on JUND predicted promoter targets, and a de novo discovered motif for BCL6 on BCL6 predicted promoter targets. Finally, to demonstrate accuracy of prediction using an external dataset, we showed that sites matching predicted motifs for ZNF263 are significantly enriched in recent ZNF263 ChIP-seq data.Using an integrative framework, we were able to address technical challenges faced by state of the art network reverse engineering methods, leading to significant improvement in direct-interaction detection and TFBS-discovery accuracy. We estimated the accuracy

Fast dynamics perturbation analysis for prediction of protein functional sites

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Cohn Judith D

2008-01-01

Full Text Available Abstract Background We present a fast version of the dynamics perturbation analysis (DPA algorithm to predict functional sites in protein structures. The original DPA algorithm finds regions in proteins where interactions cause a large change in the protein conformational distribution, as measured using the relative entropy Dx. Such regions are associated with functional sites. Results The Fast DPA algorithm, which accelerates DPA calculations, is motivated by an empirical observation that Dx in a normal-modes model is highly correlated with an entropic term that only depends on the eigenvalues of the normal modes. The eigenvalues are accurately estimated using first-order perturbation theory, resulting in a N-fold reduction in the overall computational requirements of the algorithm, where N is the number of residues in the protein. The performance of the original and Fast DPA algorithms was compared using protein structures from a standard small-molecule docking test set. For nominal implementations of each algorithm, top-ranked Fast DPA predictions overlapped the true binding site 94% of the time, compared to 87% of the time for original DPA. In addition, per-protein recall statistics (fraction of binding-site residues that are among predicted residues were slightly better for Fast DPA. On the other hand, per-protein precision statistics (fraction of predicted residues that are among binding-site residues were slightly better using original DPA. Overall, the performance of Fast DPA in predicting ligand-binding-site residues was comparable to that of the original DPA algorithm. Conclusion Compared to the original DPA algorithm, the decreased run time with comparable performance makes Fast DPA well-suited for implementation on a web server and for high-throughput analysis.

Variable context Markov chains for HIV protease cleavage site prediction.

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Oğul, Hasan

2009-06-01

Deciphering the knowledge of HIV protease specificity and developing computational tools for detecting its cleavage sites in protein polypeptide chain are very desirable for designing efficient and specific chemical inhibitors to prevent acquired immunodeficiency syndrome. In this study, we developed a generative model based on a generalization of variable order Markov chains (VOMC) for peptide sequences and adapted the model for prediction of their cleavability by certain proteases. The new method, called variable context Markov chains (VCMC), attempts to identify the context equivalence based on the evolutionary similarities between individual amino acids. It was applied for HIV-1 protease cleavage site prediction problem and shown to outperform existing methods in terms of prediction accuracy on a common dataset. In general, the method is a promising tool for prediction of cleavage sites of all proteases and encouraged to be used for any kind of peptide classification problem as well.

PROSPER: an integrated feature-based tool for predicting protease substrate cleavage sites.

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Jiangning Song

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

Exploring the role of water in molecular recognition: predicting protein ligandability using a combinatorial search of surface hydration sites

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Vukovic, Sinisa; Brennan, Paul E.; Huggins, David J.

2016-09-01

The interaction between any two biological molecules must compete with their interaction with water molecules. This makes water the most important molecule in medicine, as it controls the interactions of every therapeutic with its target. A small molecule binding to a protein is able to recognize a unique binding site on a protein by displacing bound water molecules from specific hydration sites. Quantifying the interactions of these water molecules allows us to estimate the potential of the protein to bind a small molecule. This is referred to as ligandability. In the study, we describe a method to predict ligandability by performing a search of all possible combinations of hydration sites on protein surfaces. We predict ligandability as the summed binding free energy for each of the constituent hydration sites, computed using inhomogeneous fluid solvation theory. We compared the predicted ligandability with the maximum observed binding affinity for 20 proteins in the human bromodomain family. Based on this comparison, it was determined that effective inhibitors have been developed for the majority of bromodomains, in the range from 10 to 100 nM. However, we predict that more potent inhibitors can be developed for the bromodomains BPTF and BRD7 with relative ease, but that further efforts to develop inhibitors for ATAD2 will be extremely challenging. We have also made predictions for the 14 bromodomains with no reported small molecule K d values by isothermal titration calorimetry. The calculations predict that PBRM1(1) will be a challenging target, while others such as TAF1L(2), PBRM1(4) and TAF1(2), should be highly ligandable. As an outcome of this work, we assembled a database of experimental maximal K d that can serve as a community resource assisting medicinal chemistry efforts focused on BRDs. Effective prediction of ligandability would be a very useful tool in the drug discovery process.

Exploring the role of water in molecular recognition: predicting protein ligandability using a combinatorial search of surface hydration sites.

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Vukovic, Sinisa; Brennan, Paul E; Huggins, David J

2016-09-01

The interaction between any two biological molecules must compete with their interaction with water molecules. This makes water the most important molecule in medicine, as it controls the interactions of every therapeutic with its target. A small molecule binding to a protein is able to recognize a unique binding site on a protein by displacing bound water molecules from specific hydration sites. Quantifying the interactions of these water molecules allows us to estimate the potential of the protein to bind a small molecule. This is referred to as ligandability. In the study, we describe a method to predict ligandability by performing a search of all possible combinations of hydration sites on protein surfaces. We predict ligandability as the summed binding free energy for each of the constituent hydration sites, computed using inhomogeneous fluid solvation theory. We compared the predicted ligandability with the maximum observed binding affinity for 20 proteins in the human bromodomain family. Based on this comparison, it was determined that effective inhibitors have been developed for the majority of bromodomains, in the range from 10 to 100 nM. However, we predict that more potent inhibitors can be developed for the bromodomains BPTF and BRD7 with relative ease, but that further efforts to develop inhibitors for ATAD2 will be extremely challenging. We have also made predictions for the 14 bromodomains with no reported small molecule K d values by isothermal titration calorimetry. The calculations predict that PBRM1(1) will be a challenging target, while others such as TAF1L(2), PBRM1(4) and TAF1(2), should be highly ligandable. As an outcome of this work, we assembled a database of experimental maximal K d that can serve as a community resource assisting medicinal chemistry efforts focused on BRDs. Effective prediction of ligandability would be a very useful tool in the drug discovery process.

MetWAMer: eukaryotic translation initiation site prediction

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Brendel Volker

2008-09-01

Full Text Available Abstract Background Translation initiation site (TIS identification is an important aspect of the gene annotation process, requisite for the accurate delineation of protein sequences from transcript data. We have developed the MetWAMer package for TIS prediction in eukaryotic open reading frames of non-viral origin. MetWAMer can be used as a stand-alone, third-party tool for post-processing gene structure annotations generated by external computational programs and/or pipelines, or directly integrated into gene structure prediction software implementations. Results MetWAMer currently implements five distinct methods for TIS prediction, the most accurate of which is a routine that combines weighted, signal-based translation initiation site scores and the contrast in coding potential of sequences flanking TISs using a perceptron. Also, our program implements clustering capabilities through use of the k-medoids algorithm, thereby enabling cluster-specific TIS parameter utilization. In practice, our static weight array matrix-based indexing method for parameter set lookup can be used with good results in data sets exhibiting moderate levels of 5'-complete coverage. Conclusion We demonstrate that improvements in statistically-based models for TIS prediction can be achieved by taking the class of each potential start-methionine into account pending certain testing conditions, and that our perceptron-based model is suitable for the TIS identification task. MetWAMer represents a well-documented, extensible, and freely available software system that can be readily re-trained for differing target applications and/or extended with existing and novel TIS prediction methods, to support further research efforts in this area.

Predictive Temperature Equations for Three Sites at the Grand Canyon

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McLaughlin, Katrina Marie Neitzel

Climate data collected at a number of automated weather stations were used to create a series of predictive equations spanning from December 2009 to May 2010 in order to better predict the temperatures along hiking trails within the Grand Canyon. The central focus of this project is how atmospheric variables interact and can be combined to predict the weather in the Grand Canyon at the Indian Gardens, Phantom Ranch, and Bright Angel sites. Through the use of statistical analysis software and data regression, predictive equations were determined. The predictive equations are simple or multivariable best fits that reflect the curvilinear nature of the data. With data analysis software curves resulting from the predictive equations were plotted along with the observed data. Each equation's reduced chi2 was determined to aid the visual examination of the predictive equations' ability to reproduce the observed data. From this information an equation or pair of equations was determined to be the best of the predictive equations. Although a best predictive equation for each month and season was determined for each site, future work may refine equations to result in a more accurate predictive equation.

Exploiting protein flexibility to predict the location of allosteric sites

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Panjkovich Alejandro

2012-10-01

Full Text Available Abstract Background Allostery is one of the most powerful and common ways of regulation of protein activity. However, for most allosteric proteins identified to date the mechanistic details of allosteric modulation are not yet well understood. Uncovering common mechanistic patterns underlying allostery would allow not only a better academic understanding of the phenomena, but it would also streamline the design of novel therapeutic solutions. This relatively unexplored therapeutic potential and the putative advantages of allosteric drugs over classical active-site inhibitors fuel the attention allosteric-drug research is receiving at present. A first step to harness the regulatory potential and versatility of allosteric sites, in the context of drug-discovery and design, would be to detect or predict their presence and location. In this article, we describe a simple computational approach, based on the effect allosteric ligands exert on protein flexibility upon binding, to predict the existence and position of allosteric sites on a given protein structure. Results By querying the literature and a recently available database of allosteric sites, we gathered 213 allosteric proteins with structural information that we further filtered into a non-redundant set of 91 proteins. We performed normal-mode analysis and observed significant changes in protein flexibility upon allosteric-ligand binding in 70% of the cases. These results agree with the current view that allosteric mechanisms are in many cases governed by changes in protein dynamics caused by ligand binding. Furthermore, we implemented an approach that achieves 65% positive predictive value in identifying allosteric sites within the set of predicted cavities of a protein (stricter parameters set, 0.22 sensitivity, by combining the current analysis on dynamics with previous results on structural conservation of allosteric sites. We also analyzed four biological examples in detail, revealing

Predicting Greater Prairie-Chicken Lek Site Suitability to Inform Conservation Actions.

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Torre J Hovick

Full Text Available The demands of a growing human population dictates that expansion of energy infrastructure, roads, and other development frequently takes place in native rangelands. Particularly, transmission lines and roads commonly divide rural landscapes and increase fragmentation. This has direct and indirect consequences on native wildlife that can be mitigated through thoughtful planning and proactive approaches to identifying areas of high conservation priority. We used nine years (2003-2011 of Greater Prairie-Chicken (Tympanuchus cupido lek locations totaling 870 unique leks sites in Kansas and seven geographic information system (GIS layers describing land cover, topography, and anthropogenic structures to model habitat suitability across the state. The models obtained had low omission rates (0.81, indicating high model performance and reliability of predicted habitat suitability for Greater Prairie-Chickens. We found that elevation was the most influential in predicting lek locations, contributing three times more predictive power than any other variable. However, models were improved by the addition of land cover and anthropogenic features (transmission lines, roads, and oil and gas structures. Overall, our analysis provides a hierarchal understanding of Greater Prairie-Chicken habitat suitability that is broadly based on geomorphological features followed by land cover suitability. We found that when land features and vegetation cover are suitable for Greater Prairie-Chickens, fragmentation by anthropogenic sources such as roadways and transmission lines are a concern. Therefore, it is our recommendation that future human development in Kansas avoid areas that our models identified as highly suitable for Greater Prairie-Chickens and focus development on land cover types that are of lower conservation concern.

Better estimation of protein-DNA interaction parameters improve prediction of functional sites

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O'Flanagan Ruadhan A

2008-12-01

Full Text Available Abstract Background Characterizing transcription factor binding motifs is a common bioinformatics task. For transcription factors with variable binding sites, we need to get many suboptimal binding sites in our training dataset to get accurate estimates of free energy penalties for deviating from the consensus DNA sequence. One procedure to do that involves a modified SELEX (Systematic Evolution of Ligands by Exponential Enrichment method designed to produce many such sequences. Results We analyzed low stringency SELEX data for E. coli Catabolic Activator Protein (CAP, and we show here that appropriate quantitative analysis improves our ability to predict in vitro affinity. To obtain large number of sequences required for this analysis we used a SELEX SAGE protocol developed by Roulet et al. The sequences obtained from here were subjected to bioinformatic analysis. The resulting bioinformatic model characterizes the sequence specificity of the protein more accurately than those sequence specificities predicted from previous analysis just by using a few known binding sites available in the literature. The consequences of this increase in accuracy for prediction of in vivo binding sites (and especially functional ones in the E. coli genome are also discussed. We measured the dissociation constants of several putative CAP binding sites by EMSA (Electrophoretic Mobility Shift Assay and compared the affinities to the bioinformatics scores provided by methods like the weight matrix method and QPMEME (Quadratic Programming Method of Energy Matrix Estimation trained on known binding sites as well as on the new sites from SELEX SAGE data. We also checked predicted genome sites for conservation in the related species S. typhimurium. We found that bioinformatics scores based on SELEX SAGE data does better in terms of prediction of physical binding energies as well as in detecting functional sites. Conclusion We think that training binding site detection

A GIS approach for predicting prehistoric site locations.

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Kuiper, J. A.; Wescott, K. L.

1999-08-04

Use of geographic information system (GIS)-based predictive mapping to locate areas of high potential for prehistoric archaeological sites is becoming increasingly popular among archaeologists. Knowledge of the environmental variables influencing activities of original inhabitants is used to produce GIS layers representing the spatial distribution of those variables. The GIS layers are then analyzed to identify locations where combinations of environmental variables match patterns observed at known prehistoric sites. Presented are the results of a study to locate high-potential areas for prehistoric sites in a largely unsurveyed area of 39,000 acres in the Upper Chesapeake Bay region, including details of the analysis process. The project used environmental data from over 500 known sites in other parts of the region and the results corresponded well with known sites in the study area.

POLYAR, a new computer program for prediction of poly(A sites in human sequences

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Qamar Raheel

2010-11-01

Full Text Available Abstract Background mRNA polyadenylation is an essential step of pre-mRNA processing in eukaryotes. Accurate prediction of the pre-mRNA 3'-end cleavage/polyadenylation sites is important for defining the gene boundaries and understanding gene expression mechanisms. Results 28761 human mapped poly(A sites have been classified into three classes containing different known forms of polyadenylation signal (PAS or none of them (PAS-strong, PAS-weak and PAS-less, respectively and a new computer program POLYAR for the prediction of poly(A sites of each class was developed. In comparison with polya_svm (till date the most accurate computer program for prediction of poly(A sites while searching for PAS-strong poly(A sites in human sequences, POLYAR had a significantly higher prediction sensitivity (80.8% versus 65.7% and specificity (66.4% versus 51.7% However, when a similar sort of search was conducted for PAS-weak and PAS-less poly(A sites, both programs had a very low prediction accuracy, which indicates that our knowledge about factors involved in the determination of the poly(A sites is not sufficient to identify such polyadenylation regions. Conclusions We present a new classification of polyadenylation sites into three classes and a novel computer program POLYAR for prediction of poly(A sites/regions of each of the class. In tests, POLYAR shows high accuracy of prediction of the PAS-strong poly(A sites, though this program's efficiency in searching for PAS-weak and PAS-less poly(A sites is not very high but is comparable to other available programs. These findings suggest that additional characteristics of such poly(A sites remain to be elucidated. POLYAR program with a stand-alone version for downloading is available at http://cub.comsats.edu.pk/polyapredict.htm.

Predicting protein amidation sites by orchestrating amino acid sequence features

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Zhao, Shuqiu; Yu, Hua; Gong, Xiujun

2017-08-01

Amidation is the fourth major category of post-translational modifications, which plays an important role in physiological and pathological processes. Identifying amidation sites can help us understanding the amidation and recognizing the original reason of many kinds of diseases. But the traditional experimental methods for predicting amidation sites are often time-consuming and expensive. In this study, we propose a computational method for predicting amidation sites by orchestrating amino acid sequence features. Three kinds of feature extraction methods are used to build a feature vector enabling to capture not only the physicochemical properties but also position related information of the amino acids. An extremely randomized trees algorithm is applied to choose the optimal features to remove redundancy and dependence among components of the feature vector by a supervised fashion. Finally the support vector machine classifier is used to label the amidation sites. When tested on an independent data set, it shows that the proposed method performs better than all the previous ones with the prediction accuracy of 0.962 at the Matthew's correlation coefficient of 0.89 and area under curve of 0.964.

CaMELS: In silico prediction of calmodulin binding proteins and their binding sites.

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Abbasi, Wajid Arshad; Asif, Amina; Andleeb, Saiqa; Minhas, Fayyaz Ul Amir Afsar

2017-09-01

Due to Ca 2+ -dependent binding and the sequence diversity of Calmodulin (CaM) binding proteins, identifying CaM interactions and binding sites in the wet-lab is tedious and costly. Therefore, computational methods for this purpose are crucial to the design of such wet-lab experiments. We present an algorithm suite called CaMELS (CalModulin intEraction Learning System) for predicting proteins that interact with CaM as well as their binding sites using sequence information alone. CaMELS offers state of the art accuracy for both CaM interaction and binding site prediction and can aid biologists in studying CaM binding proteins. For CaM interaction prediction, CaMELS uses protein sequence features coupled with a large-margin classifier. CaMELS models the binding site prediction problem using multiple instance machine learning with a custom optimization algorithm which allows more effective learning over imprecisely annotated CaM-binding sites during training. CaMELS has been extensively benchmarked using a variety of data sets, mutagenic studies, proteome-wide Gene Ontology enrichment analyses and protein structures. Our experiments indicate that CaMELS outperforms simple motif-based search and other existing methods for interaction and binding site prediction. We have also found that the whole sequence of a protein, rather than just its binding site, is important for predicting its interaction with CaM. Using the machine learning model in CaMELS, we have identified important features of protein sequences for CaM interaction prediction as well as characteristic amino acid sub-sequences and their relative position for identifying CaM binding sites. Python code for training and evaluating CaMELS together with a webserver implementation is available at the URL: http://faculty.pieas.edu.pk/fayyaz/software.html#camels. © 2017 Wiley Periodicals, Inc.

Establishing a predictive maintenance (PdM) program at the Hanford Site

International Nuclear Information System (INIS)

Murray, W.A.; Winslow, R.G.

1994-02-01

The production reactors have been shut down for some time. But for the rest of the site, there is currently about 16,000 people engaged in a multi-billion dollar effort to safely process wastes which have been stored at the site since the 1940's. This effort also includes demolition of some older facilities and environmental restoration of much of the site. This is expected to take approximately 30 to 40 years. The concept of a site-wide predictive maintenance (PdM) program began to form in early 1993. Several informal studies showed that the stand alone predictive maintenance groups which had prevailed on site to date were less than 15% effective at trending equipment conditions and predicting failures. To improve the effectiveness of PdM within the company, an engineering analysis by Rick Winslow confirmed that utilization of software networking technology which was now available would significantly overcome many of these built in handicaps. A site-wide predictive maintenance network would make PdM technology accessible to all of the areas and facilities at the site regardless of geographical distances and company division lines. Site resident vibration experts can easily be located and provide consultations on the network. However, it was recognized that strong leadership and management skills would be required within each of the two organizations for effective implementation. To start this process, a letter of understanding and agreement between the facilities and Tank Farm divisions was drafted and endorsed by company management. The agreement assigned the primary responsibility of acquiring the network software and licensee to the Tank Farms division. The acquisition and installation of the network server would be the responsibility of the facilities division. This paper describes the rest of the network development and implementation process

Novel immunohistochemistry-based signatures to predict metastatic site of triple-negative breast cancers.

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Klimov, Sergey; Rida, Padmashree Cg; Aleskandarany, Mohammed A; Green, Andrew R; Ellis, Ian O; Janssen, Emiel Am; Rakha, Emad A; Aneja, Ritu

2017-09-05

Although distant metastasis (DM) in breast cancer (BC) is the most lethal form of recurrence and the most common underlying cause of cancer related deaths, the outcome following the development of DM is related to the site of metastasis. Triple negative BC (TNBC) is an aggressive form of BC characterised by early recurrences and high mortality. Athough multiple variables can be used to predict the risk of metastasis, few markers can predict the specific site of metastasis. This study aimed at identifying a biomarker signature to predict particular sites of DM in TNBC. A clinically annotated series of 322 TNBC were immunohistochemically stained with 133 biomarkers relevant to BC, to develop multibiomarker models for predicting metastasis to the bone, liver, lung and brain. Patients who experienced metastasis to each site were compared with those who did not, by gradually filtering the biomarker set via a two-tailed t-test and Cox univariate analyses. Biomarker combinations were finally ranked based on statistical significance, and evaluated in multivariable analyses. Our final models were able to stratify TNBC patients into high risk groups that showed over 5, 6, 7 and 8 times higher risk of developing metastasis to the bone, liver, lung and brain, respectively, than low-risk subgroups. These models for predicting site-specific metastasis retained significance following adjustment for tumour size, patient age and chemotherapy status. Our novel IHC-based biomarkers signatures, when assessed in primary TNBC tumours, enable prediction of specific sites of metastasis, and potentially unravel biomarkers previously unknown in site tropism.

Using TESS to predict transcription factor binding sites in DNA sequence.

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Schug, Jonathan

2008-03-01

This unit describes how to use the Transcription Element Search System (TESS). This Web site predicts transcription factor binding sites (TFBS) in DNA sequence using two different kinds of models of sites, strings and positional weight matrices. The binding of transcription factors to DNA is a major part of the control of gene expression. Transcription factors exhibit sequence-specific binding; they form stronger bonds to some DNA sequences than to others. Identification of a good binding site in the promoter for a gene suggests the possibility that the corresponding factor may play a role in the regulation of that gene. However, the sequences transcription factors recognize are typically short and allow for some amount of mismatch. Because of this, binding sites for a factor can typically be found at random every few hundred to a thousand base pairs. TESS has features to help sort through and evaluate the significance of predicted sites.

AutoSite: an automated approach for pseudo-ligands prediction—from ligand-binding sites identification to predicting key ligand atoms

Science.gov (United States)

Ravindranath, Pradeep Anand; Sanner, Michel F.

2016-01-01

Motivation: The identification of ligand-binding sites from a protein structure facilitates computational drug design and optimization, and protein function assignment. We introduce AutoSite: an efficient software tool for identifying ligand-binding sites and predicting pseudo ligand corresponding to each binding site identified. Binding sites are reported as clusters of 3D points called fills in which every point is labelled as hydrophobic or as hydrogen bond donor or acceptor. From these fills AutoSite derives feature points: a set of putative positions of hydrophobic-, and hydrogen-bond forming ligand atoms. Results: We show that AutoSite identifies ligand-binding sites with higher accuracy than other leading methods, and produces fills that better matches the ligand shape and properties, than the fills obtained with a software program with similar capabilities, AutoLigand. In addition, we demonstrate that for the Astex Diverse Set, the feature points identify 79% of hydrophobic ligand atoms, and 81% and 62% of the hydrogen acceptor and donor hydrogen ligand atoms interacting with the receptor, and predict 81.2% of water molecules mediating interactions between ligand and receptor. Finally, we illustrate potential uses of the predicted feature points in the context of lead optimization in drug discovery projects. Availability and Implementation: http://adfr.scripps.edu/AutoDockFR/autosite.html Contact: sanner@scripps.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27354702

Predicted effectiveness of in-situ activated carbon amendment for field sediment sites with variable site- and compound-specific characteristics

Energy Technology Data Exchange (ETDEWEB)

Choi, Yongju, E-mail: ychoi81@snu.ac.kr [Department of Civil and Environmental Engineering, Seoul National University, Seoul 151-744 (Korea, Republic of); Cho, Yeo-Myoung; Luthy, Richard G. [Department of Civil and Environmental Engineering, Stanford University, Stanford, CA 94305-4020 (United States); Werner, David [School of Civil Engineering and Geosciences, Newcastle University, Newcastle upon Tyne NE1 7RU (United Kingdom)

2016-01-15

Highlights: • The model accounts for the heterogeneity of AC distribution in field applications. • AC amendment effectiveness is predicted for ten sediment sites. • An HOC mass transfer model and calibrated parameters provide reliable predictions. • AC amendment is predicted to be effective for most sites. • K{sub ow}, K{sub d}, and equilibrium-based calculations are useful indicators. - Abstract: A growing body of evidence shows that the effectiveness of in-situ activated carbon (AC) amendment to treat hydrophobic organic contaminants (HOCs) in sediments can be reliably predicted using a mass transfer modeling approach. This study analyzes available field data for characterizing AC-sediment distribution after mechanical mixing of AC into sediment. Those distributions are used to develop an HOC mass transfer model that accounts for plausible heterogeneities resulting from mixing of AC into sediment. The model is applied to ten field sites in the U.S. and Europe with 2–3 representative HOCs from each site using site- and HOC-specific model parameters collected from the literature. The model predicts that the AC amendment reduces the pore-water HOC concentrations by more than 95% fifteen years after AC deployment for 18 of the 25 total simulated cases when the AC is applied at doses of 1.5 times sediment total organic carbon content with an upper limit of 5 dry wt%. The predicted effectiveness shows negative correlation with the HOC octanol–water partitioning coefficients and the sediment-water distribution coefficients, and positive correlation with the effectiveness calculated based on equilibrium coefficients of sediment and AC, suggesting the possibility for use of the values for screening-level assessments.

Predicted effectiveness of in-situ activated carbon amendment for field sediment sites with variable site- and compound-specific characteristics

International Nuclear Information System (INIS)

Choi, Yongju; Cho, Yeo-Myoung; Luthy, Richard G.; Werner, David

2016-01-01

Highlights: • The model accounts for the heterogeneity of AC distribution in field applications. • AC amendment effectiveness is predicted for ten sediment sites. • An HOC mass transfer model and calibrated parameters provide reliable predictions. • AC amendment is predicted to be effective for most sites. • K ow , K d , and equilibrium-based calculations are useful indicators. - Abstract: A growing body of evidence shows that the effectiveness of in-situ activated carbon (AC) amendment to treat hydrophobic organic contaminants (HOCs) in sediments can be reliably predicted using a mass transfer modeling approach. This study analyzes available field data for characterizing AC-sediment distribution after mechanical mixing of AC into sediment. Those distributions are used to develop an HOC mass transfer model that accounts for plausible heterogeneities resulting from mixing of AC into sediment. The model is applied to ten field sites in the U.S. and Europe with 2–3 representative HOCs from each site using site- and HOC-specific model parameters collected from the literature. The model predicts that the AC amendment reduces the pore-water HOC concentrations by more than 95% fifteen years after AC deployment for 18 of the 25 total simulated cases when the AC is applied at doses of 1.5 times sediment total organic carbon content with an upper limit of 5 dry wt%. The predicted effectiveness shows negative correlation with the HOC octanol–water partitioning coefficients and the sediment-water distribution coefficients, and positive correlation with the effectiveness calculated based on equilibrium coefficients of sediment and AC, suggesting the possibility for use of the values for screening-level assessments.

Site and stand analysis for growth prediction of Eucalyptus grandis ...

African Journals Online (AJOL)

The integration of site information with that of tree growth is of special importance in Zululand, where sustainable supply of timber is essential for local processing and export commitments. Site prediction growth models need to be based on easily attainable input variables that are suitable for operational implementation by ...

Site-specific data confirm arsenic exposure predicted by the U.S. Environmental Protection Agency.

Science.gov (United States)

Walker, S; Griffin, S

1998-03-01

The EPA uses an exposure assessment model to estimate daily intake to chemicals of potential concern. At the Anaconda Superfund site in Montana, the EPA exposure assessment model was used to predict total and speciated urinary arsenic concentrations. Predicted concentrations were then compared to concentrations measured in children living near the site. When site-specific information on concentrations of arsenic in soil, interior dust, and diet, site-specific ingestion rates, and arsenic absorption rates were used, measured and predicted urinary arsenic concentrations were in reasonable agreement. The central tendency exposure assessment model successfully described the measured urinary arsenic concentration for the majority of children at the site. The reasonable maximum exposure assessment model successfully identified the uppermost exposed population. While the agreement between measured and predicted urinary arsenic is good, it is not exact. The variables that were identified which influenced agreement included soil and dust sample collection methodology, daily urinary volume, soil ingestion rate, and the ability to define the exposure unit. The concentration of arsenic in food affected agreement between measured and predicted total urinary arsenic, but was not considered when comparing measured and predicted speciated urinary arsenic. Speciated urinary arsenic is the recommended biomarker for recent inorganic arsenic exposure. By using site-specific data in the exposure assessment model, predicted risks from exposure to arsenic were less than predicted risks would have been if the EPA's default values had been used in the exposure assessment model. This difference resulted in reduced magnitude and cost of remediation while still protecting human health.

Protein-protein interaction site predictions with minimum covariance determinant and Mahalanobis distance.

Science.gov (United States)

Qiu, Zhijun; Zhou, Bo; Yuan, Jiangfeng

2017-11-21

Protein-protein interaction site (PPIS) prediction must deal with the diversity of interaction sites that limits their prediction accuracy. Use of proteins with unknown or unidentified interactions can also lead to missing interfaces. Such data errors are often brought into the training dataset. In response to these two problems, we used the minimum covariance determinant (MCD) method to refine the training data to build a predictor with better performance, utilizing its ability of removing outliers. In order to predict test data in practice, a method based on Mahalanobis distance was devised to select proper test data as input for the predictor. With leave-one-validation and independent test, after the Mahalanobis distance screening, our method achieved higher performance according to Matthews correlation coefficient (MCC), although only a part of test data could be predicted. These results indicate that data refinement is an efficient approach to improve protein-protein interaction site prediction. By further optimizing our method, it is hopeful to develop predictors of better performance and wide range of application. Copyright © 2017 Elsevier Ltd. All rights reserved.

Predictability of bone density at posterior mandibular implant sites using cone-beam computed tomography intensity values.

Science.gov (United States)

Alkhader, Mustafa; Hudieb, Malik; Khader, Yousef

2017-01-01

The aim of this study was to investigate the predictability of bone density at posterior mandibular implant sites using cone-beam computed tomography (CBCT) intensity values. CBCT cross-sectional images for 436 posterior mandibular implant sites were selected for the study. Using Invivo software (Anatomage, San Jose, California, USA), two observers classified the bone density into three categories: low, intermediate, and high, and CBCT intensity values were generated. Based on the consensus of the two observers, 15.6% of sites were of low bone density, 47.9% were of intermediate density, and 36.5% were of high density. Receiver-operating characteristic analysis showed that CBCT intensity values had a high predictive power for predicting high density sites (area under the curve [AUC] =0.94, P < 0.005) and intermediate density sites (AUC = 0.81, P < 0.005). The best cut-off value for intensity to predict intermediate density sites was 218 (sensitivity = 0.77 and specificity = 0.76) and the best cut-off value for intensity to predict high density sites was 403 (sensitivity = 0.93 and specificity = 0.77). CBCT intensity values are considered useful for predicting bone density at posterior mandibular implant sites.

A review of influenza detection and prediction through social networking sites.

Science.gov (United States)

Alessa, Ali; Faezipour, Miad

2018-02-01

Early prediction of seasonal epidemics such as influenza may reduce their impact in daily lives. Nowadays, the web can be used for surveillance of diseases. Search engines and social networking sites can be used to track trends of different diseases seven to ten days faster than government agencies such as Center of Disease Control and Prevention (CDC). CDC uses the Illness-Like Influenza Surveillance Network (ILINet), which is a program used to monitor Influenza-Like Illness (ILI) sent by thousands of health care providers in order to detect influenza outbreaks. It is a reliable tool, however, it is slow and expensive. For that reason, many studies aim to develop methods that do real time analysis to track ILI using social networking sites. Social media data such as Twitter can be used to predict the spread of flu in the population and can help in getting early warnings. Today, social networking sites (SNS) are used widely by many people to share thoughts and even health status. Therefore, SNS provides an efficient resource for disease surveillance and a good way to communicate to prevent disease outbreaks. The goal of this study is to review existing alternative solutions that track flu outbreak in real time using social networking sites and web blogs. Many studies have shown that social networking sites can be used to conduct real time analysis for better predictions.

Site-specific data confirm arsenic exposure predicted by the U.S. Environmental Protection Agency.

OpenAIRE

Walker, S; Griffin, S

1998-01-01

The EPA uses an exposure assessment model to estimate daily intake to chemicals of potential concern. At the Anaconda Superfund site in Montana, the EPA exposure assessment model was used to predict total and speciated urinary arsenic concentrations. Predicted concentrations were then compared to concentrations measured in children living near the site. When site-specific information on concentrations of arsenic in soil, interior dust, and diet, site-specific ingestion rates, and arsenic abso...

Prediction of protein-protein interaction sites in sequences and 3D structures by random forests.

Directory of Open Access Journals (Sweden)

Mile Sikić

2009-01-01

Full Text Available Identifying interaction sites in proteins provides important clues to the function of a protein and is becoming increasingly relevant in topics such as systems biology and drug discovery. Although there are numerous papers on the prediction of interaction sites using information derived from structure, there are only a few case reports on the prediction of interaction residues based solely on protein sequence. Here, a sliding window approach is combined with the Random Forests method to predict protein interaction sites using (i a combination of sequence- and structure-derived parameters and (ii sequence information alone. For sequence-based prediction we achieved a precision of 84% with a 26% recall and an F-measure of 40%. When combined with structural information, the prediction performance increases to a precision of 76% and a recall of 38% with an F-measure of 51%. We also present an attempt to rationalize the sliding window size and demonstrate that a nine-residue window is the most suitable for predictor construction. Finally, we demonstrate the applicability of our prediction methods by modeling the Ras-Raf complex using predicted interaction sites as target binding interfaces. Our results suggest that it is possible to predict protein interaction sites with quite a high accuracy using only sequence information.

Event segmentation ability uniquely predicts event memory.

Science.gov (United States)

Sargent, Jesse Q; Zacks, Jeffrey M; Hambrick, David Z; Zacks, Rose T; Kurby, Christopher A; Bailey, Heather R; Eisenberg, Michelle L; Beck, Taylor M

2013-11-01

Memory for everyday events plays a central role in tasks of daily living, autobiographical memory, and planning. Event memory depends in part on segmenting ongoing activity into meaningful units. This study examined the relationship between event segmentation and memory in a lifespan sample to answer the following question: Is the ability to segment activity into meaningful events a unique predictor of subsequent memory, or is the relationship between event perception and memory accounted for by general cognitive abilities? Two hundred and eight adults ranging from 20 to 79years old segmented movies of everyday events and attempted to remember the events afterwards. They also completed psychometric ability tests and tests measuring script knowledge for everyday events. Event segmentation and script knowledge both explained unique variance in event memory above and beyond the psychometric measures, and did so as strongly in older as in younger adults. These results suggest that event segmentation is a basic cognitive mechanism, important for memory across the lifespan. Copyright © 2013 Elsevier B.V. All rights reserved.

A web server for analysis, comparison and prediction of protein ligand binding sites.

Science.gov (United States)

Singh, Harinder; Srivastava, Hemant Kumar; Raghava, Gajendra P S

2016-03-25

One of the major challenges in the field of system biology is to understand the interaction between a wide range of proteins and ligands. In the past, methods have been developed for predicting binding sites in a protein for a limited number of ligands. In order to address this problem, we developed a web server named 'LPIcom' to facilitate users in understanding protein-ligand interaction. Analysis, comparison and prediction modules are available in the "LPIcom' server to predict protein-ligand interacting residues for 824 ligands. Each ligand must have at least 30 protein binding sites in PDB. Analysis module of the server can identify residues preferred in interaction and binding motif for a given ligand; for example residues glycine, lysine and arginine are preferred in ATP binding sites. Comparison module of the server allows comparing protein-binding sites of multiple ligands to understand the similarity between ligands based on their binding site. This module indicates that ATP, ADP and GTP ligands are in the same cluster and thus their binding sites or interacting residues exhibit a high level of similarity. Propensity-based prediction module has been developed for predicting ligand-interacting residues in a protein for more than 800 ligands. In addition, a number of web-based tools have been integrated to facilitate users in creating web logo and two-sample between ligand interacting and non-interacting residues. In summary, this manuscript presents a web-server for analysis of ligand interacting residue. This server is available for public use from URL http://crdd.osdd.net/raghava/lpicom .

Assessment of Mars Exploration Rover Landing Site Predictions

Science.gov (United States)

Golombek, M. P.

2005-05-01

Comprehensive analyses of remote sensing data during the 3-year effort to select the Mars Exploration Rover landing sites at Gusev crater and Meridiani Planum correctly predicted the safe and trafficable surfaces explored by the two rovers. Gusev crater was predicted to be a relatively low relief surface that was comparably dusty, but less rocky than the Viking landing sites. Available data for Meridiani Planum indicated a very flat plain composed of basaltic sand to granules and hematite that would look completely unlike any of the existing landing sites with a dark, low albedo surface, little dust and very few rocks. Orbital thermal inertia measurements of 315 J m-2 s-0.5 K-1 at Gusev suggested surfaces dominated by duricrust to cemented soil-like materials or cohesionless sand or granules, which is consistent with observed soil characteristics and measured thermal inertias from the surface. THEMIS thermal inertias along the traverse at Gusev vary from 285 at the landing site to 330 around Bonneville rim and show systematic variations that can be related to the observed increase in rock abundance (5-30%). Meridiani has an orbital bulk inertia of ~200, similar to measured surface inertias that correspond to observed surfaces dominated by 0.2 mm sand size particles. Rock abundance derived from orbital thermal differencing techniques suggested that Meridiani Planum would have very low rock abundance, consistent with the rock free plain traversed by Opportunity. Spirit landed in an 8% orbital rock abundance pixel, consistent with the measured 7% of the surface covered by rocks >0.04 m diameter at the landing site, which is representative of the plains away from craters. The orbital albedo of the Spirit traverse varies from 0.19 to 0.30, consistent with surface measurements in and out of dust devil tracks. Opportunity is the first landing in a low albedo portion of Mars as seen from orbit, which is consistent with the dark, dust-free surface and measured albedos. The

[Uniqueness seeking behavior as a self-verification: an alternative approach to the study of uniqueness].

Science.gov (United States)

Yamaoka, S

1995-06-01

Uniqueness theory explains that extremely high perceived similarity between self and others evokes negative emotional reactions and causes uniqueness seeking behavior. However, the theory conceptualizes similarity so ambiguously that it appears to suffer from low predictive validity. The purpose of the current article is to propose an alternative explanation of uniqueness seeking behavior. It posits that perceived uniqueness deprivation is a threat to self-concepts, and therefore causes self-verification behavior. Two levels of self verification are conceived: one based on personal categorization and the other on social categorization. The present approach regards uniqueness seeking behavior as the personal-level self verification. To test these propositions, a 2 (very high or moderate similarity information) x 2 (with or without outgroup information) x 2 (high or low need for uniqueness) between-subject factorial-design experiment was conducted with 95 university students. Results supported the self-verification approach, and were discussed in terms of effects of uniqueness deprivation, levels of self-categorization, and individual differences in need for uniqueness.

Combining specificity determining and conserved residues improves functional site prediction

Directory of Open Access Journals (Sweden)

Gelfand Mikhail S

2009-06-01

Full Text Available Abstract Background Predicting the location of functionally important sites from protein sequence and/or structure is a long-standing problem in computational biology. Most current approaches make use of sequence conservation, assuming that amino acid residues conserved within a protein family are most likely to be functionally important. Most often these approaches do not consider many residues that act to define specific sub-functions within a family, or they make no distinction between residues important for function and those more relevant for maintaining structure (e.g. in the hydrophobic core. Many protein families bind and/or act on a variety of ligands, meaning that conserved residues often only bind a common ligand sub-structure or perform general catalytic activities. Results Here we present a novel method for functional site prediction based on identification of conserved positions, as well as those responsible for determining ligand specificity. We define Specificity-Determining Positions (SDPs, as those occupied by conserved residues within sub-groups of proteins in a family having a common specificity, but differ between groups, and are thus likely to account for specific recognition events. We benchmark the approach on enzyme families of known 3D structure with bound substrates, and find that in nearly all families residues predicted by SDPsite are in contact with the bound substrate, and that the addition of SDPs significantly improves functional site prediction accuracy. We apply SDPsite to various families of proteins containing known three-dimensional structures, but lacking clear functional annotations, and discusse several illustrative examples. Conclusion The results suggest a better means to predict functional details for the thousands of protein structures determined prior to a clear understanding of molecular function.

Predicting sumoylation sites using support vector machines based on various sequence features, conformational flexibility and disorder.

Science.gov (United States)

Yavuz, Ahmet Sinan; Sezerman, Osman Ugur

2014-01-01

Sumoylation, which is a reversible and dynamic post-translational modification, is one of the vital processes in a cell. Before a protein matures to perform its function, sumoylation may alter its localization, interactions, and possibly structural conformation. Abberations in protein sumoylation has been linked with a variety of disorders and developmental anomalies. Experimental approaches to identification of sumoylation sites may not be effective due to the dynamic nature of sumoylation, laborsome experiments and their cost. Therefore, computational approaches may guide experimental identification of sumoylation sites and provide insights for further understanding sumoylation mechanism. In this paper, the effectiveness of using various sequence properties in predicting sumoylation sites was investigated with statistical analyses and machine learning approach employing support vector machines. These sequence properties were derived from windows of size 7 including position-specific amino acid composition, hydrophobicity, estimated sub-window volumes, predicted disorder, and conformational flexibility. 5-fold cross-validation results on experimentally identified sumoylation sites revealed that our method successfully predicts sumoylation sites with a Matthew's correlation coefficient, sensitivity, specificity, and accuracy equal to 0.66, 73%, 98%, and 97%, respectively. Additionally, we have showed that our method compares favorably to the existing prediction methods and basic regular expressions scanner. By using support vector machines, a new, robust method for sumoylation site prediction was introduced. Besides, the possible effects of predicted conformational flexibility and disorder on sumoylation site recognition were explored computationally for the first time to our knowledge as an additional parameter that could aid in sumoylation site prediction.

Analysis and prediction of gene splice sites in four Aspergillus genomes

DEFF Research Database (Denmark)

Wang, Kai; Ussery, David; Brunak, Søren

2009-01-01

Several Aspergillus fungal genomic sequences have been published, with many more in progress. Obviously, it is essential to have high-quality, consistently annotated sets of proteins from each of the genomes, in order to make meaningful comparisons. We have developed a dedicated, publicly available......, splice site prediction program called NetAspGene, for the genus Aspergillus. Gene sequences from Aspergillus fumigatus, the most common mould pathogen, were used to build and test our model. Compared to many animals and plants, Aspergillus contains smaller introns; thus we have applied a larger window...... better splice site prediction than other available tools. NetAspGene will be very helpful for the study in Aspergillus splice sites and especially in alternative splicing. A webpage for NetAspGene is publicly available at http://www.cbs.dtu.dk/services/NetAspGene....

Polyadenylation site prediction using PolyA-iEP method.

Science.gov (United States)

Kavakiotis, Ioannis; Tzanis, George; Vlahavas, Ioannis

2014-01-01

This chapter presents a method called PolyA-iEP that has been developed for the prediction of polyadenylation sites. More precisely, PolyA-iEP is a method that recognizes mRNA 3'ends which contain polyadenylation sites. It is a modular system which consists of two main components. The first exploits the advantages of emerging patterns and the second is a distance-based scoring method. The outputs of the two components are finally combined by a classifier. The final results reach very high scores of sensitivity and specificity.

Splice site prediction in Arabidopsis thaliana pre-mRNA by combining local and global sequence information

DEFF Research Database (Denmark)

Hebsgaard, Stefan M.; Korning, Peter G.; Tolstrup, Niels

1996-01-01

Artificial neural networks have been combined with a rule based system to predict intron splice sites in the dicot plant Arabidopsis thaliana. A two step prediction scheme, where a global prediction of the coding potential regulates a cutoff level for a local predicition of splice sites, is refin...

Ensemble approach combining multiple methods improves human transcription start site prediction.

LENUS (Irish Health Repository)

Dineen, David G

2010-01-01

The computational prediction of transcription start sites is an important unsolved problem. Some recent progress has been made, but many promoters, particularly those not associated with CpG islands, are still difficult to locate using current methods. These methods use different features and training sets, along with a variety of machine learning techniques and result in different prediction sets.

Prediction of protein hydration sites from sequence by modular neural networks

DEFF Research Database (Denmark)

Ehrlich, L.; Reczko, M.; Bohr, Henrik

1998-01-01

The hydration properties of a protein are important determinants of its structure and function. Here, modular neural networks are employed to predict ordered hydration sites using protein sequence information. First, secondary structure and solvent accessibility are predicted from sequence with two...... separate neural networks. These predictions are used as input together with protein sequences for networks predicting hydration of residues, backbone atoms and sidechains. These networks are teined with protein crystal structures. The prediction of hydration is improved by adding information on secondary...... structure and solvent accessibility and, using actual values of these properties, redidue hydration can be predicted to 77% accuracy with a Metthews coefficient of 0.43. However, predicted property data with an accuracy of 60-70% result in less than half the improvement in predictive performance observed...

Prediction of P53 mutants (multiple sites transcriptional activity based on structural (2D&3D properties.

Directory of Open Access Journals (Sweden)

R Geetha Ramani

Full Text Available Prediction of secondary site mutations that reinstate mutated p53 to normalcy has been the focus of intense research in the recent past owing to the fact that p53 mutants have been implicated in more than half of all human cancers and restoration of p53 causes tumor regression. However laboratory investigations are more often laborious and resource intensive but computational techniques could well surmount these drawbacks. In view of this, we formulated a novel approach utilizing computational techniques to predict the transcriptional activity of multiple site (one-site to five-site p53 mutants. The optimal MCC obtained by the proposed approach on prediction of one-site, two-site, three-site, four-site and five-site mutants were 0.775,0.341,0.784,0.916 and 0.655 respectively, the highest reported thus far in literature. We have also demonstrated that 2D and 3D features generate higher prediction accuracy of p53 activity and our findings revealed the optimal results for prediction of p53 status, reported till date. We believe detection of the secondary site mutations that suppress tumor growth may facilitate better understanding of the relationship between p53 structure and function and further knowledge on the molecular mechanisms and biological activity of p53, a targeted source for cancer therapy. We expect that our prediction methods and reported results may provide useful insights on p53 functional mechanisms and generate more avenues for utilizing computational techniques in biological data analysis.

Computational prediction of muon stopping sites using ab initio random structure searching (AIRSS)

Science.gov (United States)

Liborio, Leandro; Sturniolo, Simone; Jochym, Dominik

2018-04-01

The stopping site of the muon in a muon-spin relaxation experiment is in general unknown. There are some techniques that can be used to guess the muon stopping site, but they often rely on approximations and are not generally applicable to all cases. In this work, we propose a purely theoretical method to predict muon stopping sites in crystalline materials from first principles. The method is based on a combination of ab initio calculations, random structure searching, and machine learning, and it has successfully predicted the MuT and MuBC stopping sites of muonium in Si, diamond, and Ge, as well as the muonium stopping site in LiF, without any recourse to experimental results. The method makes use of Soprano, a Python library developed to aid ab initio computational crystallography, that was publicly released and contains all the software tools necessary to reproduce our analysis.

Probabilistic Assessment of Above Zone Pressure Predictions at a Geologic Carbon Storage Site

Energy Technology Data Exchange (ETDEWEB)

Namhata, Argha; Oladyshkin, Sergey; Dilmore, Robert M.; Zhang, Liwei; Nakles, David V.

2016-12-01

Carbon dioxide (CO2) storage into geological formations is regarded as an important mitigation strategy for anthropogenic CO2 emissions to the atmosphere. This study first simulates the leakage of CO2 and brine from a storage reservoir through the caprock. Then, we estimate the resulting pressure changes at the zone overlying the caprock also known as Above Zone Monitoring Interval (AZMI). A data-driven approach of arbitrary Polynomial Chaos (aPC) Expansion is then used to quantify the uncertainty in the above zone pressure prediction based on the uncertainties in different geologic parameters. Finally, a global sensitivity analysis is performed with Sobol indices based on the aPC technique to determine the relative importance of different parameters on pressure prediction. The results indicate that there can be uncertainty in pressure prediction locally around the leakage zones. The degree of such uncertainty in prediction depends on the quality of site specific information available for analysis. The scientific results from this study provide substantial insight that there is a need for site-specific data for efficient predictions of risks associated with storage activities. The presented approach can provide a basis of optimized pressure based monitoring network design at carbon storage sites.

Cross-prediction of the groundwater chemistry at the SKB sites in Sweden. Pilot study

International Nuclear Information System (INIS)

Skaarman, C.; Laaksoharju, M.

1997-08-01

The possibility to perform a large scale prediction throughout Sweden was tested. The aim of the work was: to collect data and create a groundwater database for current and future use; to see if there is any correlation between data at different sites; to perform a modelling where the groundwater composition at different regions in Sweden is predicted. The outcome of the predictions were compared with the measured data at different sites. The results show that it is possible but more work needs to be done to improve the prediction models. More measurements at depth are needed to enable the use of 3D models. It is also important to include hydrogeological parameters in the groundwater chemical prediction models that are used

Seismic Hazard Assessment in Site Evaluation for Nuclear Installations: Ground Motion Prediction Equations and Site Response

International Nuclear Information System (INIS)

2016-07-01

The objective of this publication is to provide the state-of-the-art practice and detailed technical elements related to ground motion evaluation by ground motion prediction equations (GMPEs) and site response in the context of seismic hazard assessments as recommended in IAEA Safety Standards Series No. SSG-9, Seismic Hazards in Site Evaluation for Nuclear Installations. The publication includes the basics of GMPEs, ground motion simulation, selection and adjustment of GMPEs, site characterization, and modelling of site response in order to improve seismic hazard assessment. The text aims at delineating the most important aspects of these topics (including current practices, criticalities and open problems) within a coherent framework. In particular, attention has been devoted to filling conceptual gaps. It is written as a reference text for trained users who are responsible for planning preparatory seismic hazard analyses for siting of all nuclear installations and/or providing constraints for anti-seismic design and retrofitting of existing structures

Using sequence-specific chemical and structural properties of DNA to predict transcription factor binding sites.

Directory of Open Access Journals (Sweden)

Amy L Bauer

2010-11-01

Full Text Available An important step in understanding gene regulation is to identify the DNA binding sites recognized by each transcription factor (TF. Conventional approaches to prediction of TF binding sites involve the definition of consensus sequences or position-specific weight matrices and rely on statistical analysis of DNA sequences of known binding sites. Here, we present a method called SiteSleuth in which DNA structure prediction, computational chemistry, and machine learning are applied to develop models for TF binding sites. In this approach, binary classifiers are trained to discriminate between true and false binding sites based on the sequence-specific chemical and structural features of DNA. These features are determined via molecular dynamics calculations in which we consider each base in different local neighborhoods. For each of 54 TFs in Escherichia coli, for which at least five DNA binding sites are documented in RegulonDB, the TF binding sites and portions of the non-coding genome sequence are mapped to feature vectors and used in training. According to cross-validation analysis and a comparison of computational predictions against ChIP-chip data available for the TF Fis, SiteSleuth outperforms three conventional approaches: Match, MATRIX SEARCH, and the method of Berg and von Hippel. SiteSleuth also outperforms QPMEME, a method similar to SiteSleuth in that it involves a learning algorithm. The main advantage of SiteSleuth is a lower false positive rate.

Work characteristics predict the development of multi-site musculoskeletal pain

NARCIS (Netherlands)

Oakman, J.; Wind, A. de; Heuvel, S.G. van den; Beek, A.J. van der

2017-01-01

Purpose. Musculoskeletal pain in more than one body region is common and a barrier to sustaining employment. We aimed to examine whether work characteristics predict the development of multi-site pain (MSP), and to determine differences in work-related predictors between age groups. Methods. This

SITE-94. Discrete-feature modelling of the Aespoe Site: 3. Predictions of hydrogeological parameters for performance assessment

International Nuclear Information System (INIS)

Geier, J.E.

1996-12-01

A 3-dimensional, discrete-feature hydrological model is developed. The model integrates structural and hydrologic data for the Aespoe site, on scales ranging from semi regional fracture zones to individual fractures in the vicinity of the nuclear waste canisters. Predicted parameters for the near field include fracture spacing, fracture aperture, and Darcy velocity at each of forty canister deposition holes. Parameters for the far field include discharge location, Darcy velocity, effective longitudinal dispersion coefficient and head gradient, flow porosity, and flow wetted surface, for each canister source that discharges to the biosphere. Results are presented in the form of statistical summaries for a total of 42 calculation cases, which treat a set of 25 model variants in various combinations. The variants for the SITE-94 Reference Case model address conceptual and parametric uncertainty related to the site-scale hydrogeologic model and its properties, the fracture network within the repository, effective semi regional boundary conditions for the model, and the disturbed-rock zone around the repository tunnels and shafts. Two calculation cases simulate hydrologic conditions that are predicted to occur during future glacial episodes. 30 refs

G-LoSA for Prediction of Protein-Ligand Binding Sites and Structures.

Science.gov (United States)

Lee, Hui Sun; Im, Wonpil

2017-01-01

Recent advances in high-throughput structure determination and computational protein structure prediction have significantly enriched the universe of protein structure. However, there is still a large gap between the number of available protein structures and that of proteins with annotated function in high accuracy. Computational structure-based protein function prediction has emerged to reduce this knowledge gap. The identification of a ligand binding site and its structure is critical to the determination of a protein's molecular function. We present a computational methodology for predicting small molecule ligand binding site and ligand structure using G-LoSA, our protein local structure alignment and similarity measurement tool. All the computational procedures described here can be easily implemented using G-LoSA Toolkit, a package of standalone software programs and preprocessed PDB structure libraries. G-LoSA and G-LoSA Toolkit are freely available to academic users at http://compbio.lehigh.edu/GLoSA . We also illustrate a case study to show the potential of our template-based approach harnessing G-LoSA for protein function prediction.

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

Science.gov (United States)

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

2011-07-01

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

Features generated for computational splice-site prediction correspond to functional elements

Directory of Open Access Journals (Sweden)

Wilbur W John

2007-10-01

Full Text Available Abstract Background Accurate selection of splice sites during the splicing of precursors to messenger RNA requires both relatively well-characterized signals at the splice sites and auxiliary signals in the adjacent exons and introns. We previously described a feature generation algorithm (FGA that is capable of achieving high classification accuracy on human 3' splice sites. In this paper, we extend the splice-site prediction to 5' splice sites and explore the generated features for biologically meaningful splicing signals. Results We present examples from the observed features that correspond to known signals, both core signals (including the branch site and pyrimidine tract and auxiliary signals (including GGG triplets and exon splicing enhancers. We present evidence that features identified by FGA include splicing signals not found by other methods. Conclusion Our generated features capture known biological signals in the expected sequence interval flanking splice sites. The method can be easily applied to other species and to similar classification problems, such as tissue-specific regulatory elements, polyadenylation sites, promoters, etc.

Prediction of protein modification sites of pyrrolidone carboxylic acid using mRMR feature selection and analysis.

Directory of Open Access Journals (Sweden)

Lu-Lu Zheng

Full Text Available 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.

Analysis and prediction of Multiple-Site Damage (MSD) fatigue crack growth

Science.gov (United States)

Dawicke, D. S.; Newman, J. C., Jr.

1992-08-01

A technique was developed to calculate the stress intensity factor for multiple interacting cracks. The analysis was verified through comparison with accepted methods of calculating stress intensity factors. The technique was incorporated into a fatigue crack growth prediction model and used to predict the fatigue crack growth life for multiple-site damage (MSD). The analysis was verified through comparison with experiments conducted on uniaxially loaded flat panels with multiple cracks. Configuration with nearly equal and unequal crack distribution were examined. The fatigue crack growth predictions agreed within 20 percent of the experimental lives for all crack configurations considered.

Analysis and prediction of Multiple-Site Damage (MSD) fatigue crack growth

Science.gov (United States)

Dawicke, D. S.; Newman, J. C., Jr.

1992-01-01

A technique was developed to calculate the stress intensity factor for multiple interacting cracks. The analysis was verified through comparison with accepted methods of calculating stress intensity factors. The technique was incorporated into a fatigue crack growth prediction model and used to predict the fatigue crack growth life for multiple-site damage (MSD). The analysis was verified through comparison with experiments conducted on uniaxially loaded flat panels with multiple cracks. Configuration with nearly equal and unequal crack distribution were examined. The fatigue crack growth predictions agreed within 20 percent of the experimental lives for all crack configurations considered.

SPEER-SERVER: a web server for prediction of protein specificity determining sites.

Science.gov (United States)

Chakraborty, Abhijit; Mandloi, Sapan; Lanczycki, Christopher J; Panchenko, Anna R; Chakrabarti, Saikat

2012-07-01

Sites that show specific conservation patterns within subsets of proteins in a protein family are likely to be involved in the development of functional specificity. These sites, generally termed specificity determining sites (SDS), might play a crucial role in binding to a specific substrate or proteins. Identification of SDS through experimental techniques is a slow, difficult and tedious job. Hence, it is very important to develop efficient computational methods that can more expediently identify SDS. Herein, we present Specificity prediction using amino acids' Properties, Entropy and Evolution Rate (SPEER)-SERVER, a web server that predicts SDS by analyzing quantitative measures of the conservation patterns of protein sites based on their physico-chemical properties and the heterogeneity of evolutionary changes between and within the protein subfamilies. This web server provides an improved representation of results, adds useful input and output options and integrates a wide range of analysis and data visualization tools when compared with the original standalone version of the SPEER algorithm. Extensive benchmarking finds that SPEER-SERVER exhibits sensitivity and precision performance that, on average, meets or exceeds that of other currently available methods. SPEER-SERVER is available at http://www.hpppi.iicb.res.in/ss/.

Prediction of transcriptional regulatory sites in the complete genome sequence of Escherichia coli K-12.

Science.gov (United States)

Thieffry, D; Salgado, H; Huerta, A M; Collado-Vides, J

1998-06-01

As one of the best-characterized free-living organisms, Escherichia coli and its recently completed genomic sequence offer a special opportunity to exploit systematically the variety of regulatory data available in the literature in order to make a comprehensive set of regulatory predictions in the whole genome. The complete genome sequence of E.coli was analyzed for the binding of transcriptional regulators upstream of coding sequences. The biological information contained in RegulonDB (Huerta, A.M. et al., Nucleic Acids Res.,26,55-60, 1998) for 56 different transcriptional proteins was the support to implement a stringent strategy combining string search and weight matrices. We estimate that our search included representatives of 15-25% of the total number of regulatory binding proteins in E.coli. This search was performed on the set of 4288 putative regulatory regions, each 450 bp long. Within the regions with predicted sites, 89% are regulated by one protein and 81% involve only one site. These numbers are reasonably consistent with the distribution of experimental regulatory sites. Regulatory sites are found in 603 regions corresponding to 16% of operon regions and 10% of intra-operonic regions. Additional evidence gives stronger support to some of these predictions, including the position of the site, biological consistency with the function of the downstream gene, as well as genetic evidence for the regulatory interaction. The predictions described here were incorporated into the map presented in the paper describing the complete E.coli genome (Blattner,F.R. et al., Science, 277, 1453-1461, 1997). The complete set of predictions in GenBank format is available at the url: http://www. cifn.unam.mx/Computational_Biology/E.coli-predictions ecoli-reg@cifn.unam.mx, collado@cifn.unam.mx

Method of predicting Splice Sites based on signal interactions

Directory of Open Access Journals (Sweden)

Deogun Jitender S

2006-04-01

Full Text Available Abstract Background Predicting and proper ranking of canonical splice sites (SSs is a challenging problem in bioinformatics and machine learning communities. Any progress in SSs recognition will lead to better understanding of splicing mechanism. We introduce several new approaches of combining a priori knowledge for improved SS detection. First, we design our new Bayesian SS sensor based on oligonucleotide counting. To further enhance prediction quality, we applied our new de novo motif detection tool MHMMotif to intronic ends and exons. We combine elements found with sensor information using Naive Bayesian Network, as implemented in our new tool SpliceScan. Results According to our tests, the Bayesian sensor outperforms the contemporary Maximum Entropy sensor for 5' SS detection. We report a number of putative Exonic (ESE and Intronic (ISE Splicing Enhancers found by MHMMotif tool. T-test statistics on mouse/rat intronic alignments indicates, that detected elements are on average more conserved as compared to other oligos, which supports our assumption of their functional importance. The tool has been shown to outperform the SpliceView, GeneSplicer, NNSplice, Genio and NetUTR tools for the test set of human genes. SpliceScan outperforms all contemporary ab initio gene structural prediction tools on the set of 5' UTR gene fragments. Conclusion Designed methods have many attractive properties, compared to existing approaches. Bayesian sensor, MHMMotif program and SpliceScan tools are freely available on our web site. Reviewers This article was reviewed by Manyuan Long, Arcady Mushegian and Mikhail Gelfand.

Prediction, conservation analysis, and structural characterization of mammalian mucin-type O-glycosylation sites

DEFF Research Database (Denmark)

Julenius, Karin; Mølgaard, Anne; Gupta, Ramneek

2005-01-01

could be predicted from averaged properties together with the fact that glycosylation sites are not precisely conserved indicates that mucin-type glycosylation in most cases is a bulk property and not a very site-specific one. NetOGlyc 3.1 is made available at www.cbs.dtu.dk/services/netoglyc....

Predicting Ligand Binding Sites on Protein Surfaces by 3-Dimensional Probability Density Distributions of Interacting Atoms

Science.gov (United States)

Jian, Jhih-Wei; Elumalai, Pavadai; Pitti, Thejkiran; Wu, Chih Yuan; Tsai, Keng-Chang; Chang, Jeng-Yih; Peng, Hung-Pin; Yang, An-Suei

2016-01-01

Predicting ligand binding sites (LBSs) on protein structures, which are obtained either from experimental or computational methods, is a useful first step in functional annotation or structure-based drug design for the protein structures. In this work, the structure-based machine learning algorithm ISMBLab-LIG was developed to predict LBSs on protein surfaces with input attributes derived from the three-dimensional probability density maps of interacting atoms, which were reconstructed on the query protein surfaces and were relatively insensitive to local conformational variations of the tentative ligand binding sites. The prediction accuracy of the ISMBLab-LIG predictors is comparable to that of the best LBS predictors benchmarked on several well-established testing datasets. More importantly, the ISMBLab-LIG algorithm has substantial tolerance to the prediction uncertainties of computationally derived protein structure models. As such, the method is particularly useful for predicting LBSs not only on experimental protein structures without known LBS templates in the database but also on computationally predicted model protein structures with structural uncertainties in the tentative ligand binding sites. PMID:27513851

Assessing the model transferability for prediction of transcription factor binding sites based on chromatin accessibility.

Science.gov (United States)

Liu, Sheng; Zibetti, Cristina; Wan, Jun; Wang, Guohua; Blackshaw, Seth; Qian, Jiang

2017-07-27

Computational prediction of transcription factor (TF) binding sites in different cell types is challenging. Recent technology development allows us to determine the genome-wide chromatin accessibility in various cellular and developmental contexts. The chromatin accessibility profiles provide useful information in prediction of TF binding events in various physiological conditions. Furthermore, ChIP-Seq analysis was used to determine genome-wide binding sites for a range of different TFs in multiple cell types. Integration of these two types of genomic information can improve the prediction of TF binding events. We assessed to what extent a model built upon on other TFs and/or other cell types could be used to predict the binding sites of TFs of interest. A random forest model was built using a set of cell type-independent features such as specific sequences recognized by the TFs and evolutionary conservation, as well as cell type-specific features derived from chromatin accessibility data. Our analysis suggested that the models learned from other TFs and/or cell lines performed almost as well as the model learned from the target TF in the cell type of interest. Interestingly, models based on multiple TFs performed better than single-TF models. Finally, we proposed a universal model, BPAC, which was generated using ChIP-Seq data from multiple TFs in various cell types. Integrating chromatin accessibility information with sequence information improves prediction of TF binding.The prediction of TF binding is transferable across TFs and/or cell lines suggesting there are a set of universal "rules". A computational tool was developed to predict TF binding sites based on the universal "rules".

Improvement of AEP Predictions Using Diurnal CFD Modelling with Site-Specific Stability Weightings Provided from Mesoscale Simulation

International Nuclear Information System (INIS)

Hristov, Y; Oxley, G; Žagar, M

2014-01-01

The Bolund measurement campaign, performed by Danish Technical University (DTU) Wind Energy Department (also known as RISØ), provided significant insight into wind flow modeling over complex terrain. In the blind comparison study several modelling solutions were submitted with the vast majority being steady-state Computational Fluid Dynamics (CFD) approaches with two equation k-ε turbulence closure. This approach yielded the most accurate results, and was identified as the state-of-the-art tool for wind turbine generator (WTG) micro-siting. Based on the findings from Bolund, further comparison between CFD and field measurement data has been deemed essential in order to improve simulation accuracy for turbine load and long-term Annual Energy Production (AEP) estimations. Vestas Wind Systems A/S is a major WTG original equipment manufacturer (OEM) with an installed base of over 60GW in over 70 countries accounting for 19% of the global installed base. The Vestas Performance and Diagnostic Centre (VPDC) provides online live data to more than 47GW of these turbines allowing a comprehensive comparison between modelled and real-world energy production data. In previous studies, multiple sites have been simulated with a steady neutral CFD formulation for the atmospheric surface layer (ASL), and wind resource (RSF) files have been generated as a base for long-term AEP predictions showing significant improvement over predictions performed with the industry standard linear WAsP tool. In this study, further improvements to the wind resource file generation with CFD are examined using an unsteady diurnal cycle approach with a full atmospheric boundary layer (ABL) formulation, with the unique stratifications throughout the cycle weighted according to mesoscale simulated sectorwise stability frequencies

A Mechanism-Based Model for the Prediction of the Metabolic Sites of Steroids Mediated by Cytochrome P450 3A4

Directory of Open Access Journals (Sweden)

Zi-Ru Dai

2015-06-01

Full Text Available Early prediction of xenobiotic metabolism is essential for drug discovery and development. As the most important human drug-metabolizing enzyme, cytochrome P450 3A4 has a large active cavity and metabolizes a broad spectrum of substrates. The poor substrate specificity of CYP3A4 makes it a huge challenge to predict the metabolic site(s on its substrates. This study aimed to develop a mechanism-based prediction model based on two key parameters, including the binding conformation and the reaction activity of ligands, which could reveal the process of real metabolic reaction(s and the site(s of modification. The newly established model was applied to predict the metabolic site(s of steroids; a class of CYP3A4-preferred substrates. 38 steroids and 12 non-steroids were randomly divided into training and test sets. Two major metabolic reactions, including aliphatic hydroxylation and N-dealkylation, were involved in this study. At least one of the top three predicted metabolic sites was validated by the experimental data. The overall accuracy for the training and test were 82.14% and 86.36%, respectively. In summary, a mechanism-based prediction model was established for the first time, which could be used to predict the metabolic site(s of CYP3A4 on steroids with high predictive accuracy.

Protein-protein interaction site predictions with three-dimensional probability distributions of interacting atoms on protein surfaces.

Directory of Open Access Journals (Sweden)

Ching-Tai Chen

Full Text Available Protein-protein interactions are key to many biological processes. Computational methodologies devised to predict protein-protein interaction (PPI sites on protein surfaces are important tools in providing insights into the biological functions of proteins and in developing therapeutics targeting the protein-protein interaction sites. One of the general features of PPI sites is that the core regions from the two interacting protein surfaces are complementary to each other, similar to the interior of proteins in packing density and in the physicochemical nature of the amino acid composition. In this work, we simulated the physicochemical complementarities by constructing three-dimensional probability density maps of non-covalent interacting atoms on the protein surfaces. The interacting probabilities were derived from the interior of known structures. Machine learning algorithms were applied to learn the characteristic patterns of the probability density maps specific to the PPI sites. The trained predictors for PPI sites were cross-validated with the training cases (consisting of 432 proteins and were tested on an independent dataset (consisting of 142 proteins. The residue-based Matthews correlation coefficient for the independent test set was 0.423; the accuracy, precision, sensitivity, specificity were 0.753, 0.519, 0.677, and 0.779 respectively. The benchmark results indicate that the optimized machine learning models are among the best predictors in identifying PPI sites on protein surfaces. In particular, the PPI site prediction accuracy increases with increasing size of the PPI site and with increasing hydrophobicity in amino acid composition of the PPI interface; the core interface regions are more likely to be recognized with high prediction confidence. The results indicate that the physicochemical complementarity patterns on protein surfaces are important determinants in PPIs, and a substantial portion of the PPI sites can be predicted

Protein-Protein Interaction Site Predictions with Three-Dimensional Probability Distributions of Interacting Atoms on Protein Surfaces

Science.gov (United States)

Chen, Ching-Tai; Peng, Hung-Pin; Jian, Jhih-Wei; Tsai, Keng-Chang; Chang, Jeng-Yih; Yang, Ei-Wen; Chen, Jun-Bo; Ho, Shinn-Ying; Hsu, Wen-Lian; Yang, An-Suei

2012-01-01

Protein-protein interactions are key to many biological processes. Computational methodologies devised to predict protein-protein interaction (PPI) sites on protein surfaces are important tools in providing insights into the biological functions of proteins and in developing therapeutics targeting the protein-protein interaction sites. One of the general features of PPI sites is that the core regions from the two interacting protein surfaces are complementary to each other, similar to the interior of proteins in packing density and in the physicochemical nature of the amino acid composition. In this work, we simulated the physicochemical complementarities by constructing three-dimensional probability density maps of non-covalent interacting atoms on the protein surfaces. The interacting probabilities were derived from the interior of known structures. Machine learning algorithms were applied to learn the characteristic patterns of the probability density maps specific to the PPI sites. The trained predictors for PPI sites were cross-validated with the training cases (consisting of 432 proteins) and were tested on an independent dataset (consisting of 142 proteins). The residue-based Matthews correlation coefficient for the independent test set was 0.423; the accuracy, precision, sensitivity, specificity were 0.753, 0.519, 0.677, and 0.779 respectively. The benchmark results indicate that the optimized machine learning models are among the best predictors in identifying PPI sites on protein surfaces. In particular, the PPI site prediction accuracy increases with increasing size of the PPI site and with increasing hydrophobicity in amino acid composition of the PPI interface; the core interface regions are more likely to be recognized with high prediction confidence. The results indicate that the physicochemical complementarity patterns on protein surfaces are important determinants in PPIs, and a substantial portion of the PPI sites can be predicted correctly with

Ensemble approach combining multiple methods improves human transcription start site prediction

LENUS (Irish Health Repository)

Dineen, David G

2010-11-30

Abstract Background The computational prediction of transcription start sites is an important unsolved problem. Some recent progress has been made, but many promoters, particularly those not associated with CpG islands, are still difficult to locate using current methods. These methods use different features and training sets, along with a variety of machine learning techniques and result in different prediction sets. Results We demonstrate the heterogeneity of current prediction sets, and take advantage of this heterogeneity to construct a two-level classifier (\\'Profisi Ensemble\\') using predictions from 7 programs, along with 2 other data sources. Support vector machines using \\'full\\' and \\'reduced\\' data sets are combined in an either\\/or approach. We achieve a 14% increase in performance over the current state-of-the-art, as benchmarked by a third-party tool. Conclusions Supervised learning methods are a useful way to combine predictions from diverse sources.

Predicting Risky Sexual Behavior: the Unique and Interactive Roles of Childhood Conduct Disorder Symptoms and Callous-Unemotional Traits.

Science.gov (United States)

Anderson, Sarah L; Zheng, Yao; McMahon, Robert J

2017-08-01

Conduct disorder (CD) symptoms and callous-unemotional (CU) traits have been shown to be uniquely associated with risky sexual behavior (RSB) in adolescence and early adulthood, yet their interactive role in predicting RSB remains largely unknown. This study aimed to investigate the predictive value of CD symptoms and CU traits, as well as their interaction, on several RSB outcomes in adolescence and early adulthood. A total of 683 participants (41.7 % female, 47.4 % African American) were followed annually and self-reported age of first sexual intercourse, frequency of condom use, pregnancy, contraction of sexually transmitted infections, and engagement in sexual solicitation from grade 7 to 2-years post-high school. CD symptoms predicted age of first sexual intercourse, condom use, and sexual solicitation. CU traits predicted age of first sexual intercourse and pregnancy. Their interaction predicted a composite score of these RSBs such that CD symptoms positively predicted the composite score among those with high levels of CU traits but not among those with low levels of CU traits. The current findings provide information regarding the importance of both CD symptoms and CU traits in understanding adolescent and early adulthood RSB, as well as the benefits of examining multiple RSB outcomes during this developmental period. These findings have implications for the development and implementation of preventive efforts to target these risky behaviors among adolescents and young adults.

Prediction of pollution into ore bearing aquifer from ISL-site

International Nuclear Information System (INIS)

Dolgopolov, V.; Kayukov, P.; Vyatchennikova, L.; Shishkov, I.

2002-01-01

Outcomes of present mineralogical investigations explain some phenomena observed in previous sorption experiences. First of all they elucidate cutback of filtration coefficients of sediments exposed under pollution process as granulometric fractions of these permeable sediments decreased in its weight ratio in according to impermeable ones. Then sorption graphics are explained by chemical and mineralogical changes in experienced substance. Explores made diagnoses and estimation about 45 authigenous and technogenous minerals playing the essential role in the process of mass transfer of uranium and polluted components in ISL-sites. They are considered in all basic fractions of studied sediments. Bright peculiarities are noticed for gravel and coarse sands, which went to pieces as a result of dilution or decomposition of its cement. Mineral composition of clayey fraction also significantly changed after pollution process. Steep lost of weight of fraction 0.005-0.001mm consisted with partial decomposition of clayey minerals basically of montmorillonite. These investigations show also that ones of the main minerals playing such the essential role are sorptive such as silica, silica gel, common opal, opal-CT, noble opal, allophane, montmorillonite and zeolite minerals. In conclusion the given work shows some filtration properties of aquifer in an ISL-site and predicts the spread of a possible pollution for ISL-site to environment. The extension of pollution could be more one-two dimension of affected by ISL-process. The prediction would be exact if the previous investigation included the desorptive characteristics and sorptive data depending on temperature and pressure. Current investigations continued pervious ones after which some inexplicable matters of migration of contaminated halo from an ISL-polygon are as follows: Identification and specification of all minerals outside ISL-polygon; Calculation of mineral balance for contaminated sites; Specification of flow

Timing of initial arrival at the breeding site predicts age at first reproduction in a long-lived migratory bird

Science.gov (United States)

Becker, Peter H.; Dittmann, Tobias; Ludwigs, Jan-Dieter; Limmer, Bente; Ludwig, Sonja C.; Bauch, Christina; Braasch, Alexander; Wendeln, Helmut

2008-01-01

In long-lived vertebrates, individuals generally visit potential breeding areas or populations during one or more seasons before reproducing for the first time. During these years of prospecting, they select a future breeding site, colony, or mate and improve various skills and their physical condition to meet the requirements of reproduction. One precondition of successful reproduction is arrival in time on the breeding grounds. Here, we study the intricate links among the date of initial spring arrival, body mass, sex, and the age of first breeding in the common tern Sterna hirundo, a long-lived migratory colonial seabird. The study is based on a unique, individual-based, long-term dataset of sexed birds, marked with transponders, which allow recording their individual arrival, overall attendance, and clutch initiation remotely and automatically year by year over the entire lifetime at the natal colony site. We show that the seasonal date of initial arrival at the breeding grounds predicts the individual age at first reproduction, which mostly occurs years later. Late first-time arrivals remain delayed birds throughout subsequent years. Our findings reveal that timing of arrival at the site of reproduction and timing of reproduction itself are coherent parameters of individual quality, which are linked with the prospects of the breeding career and may have consequences for fitness. PMID:18711134

Investigation of unique hue setting changes with ageing

Institute of Scientific and Technical Information of China (English)

Chenyang Fu; Kaida Xiao; Dimosthenis Karatzas; Sophie Wuerger

2011-01-01

Clromatic sensitivity along the protan, deutan, and tritan lines and the loci of the unique hues (red, green,yellow, blue) for a very large sample (n = 185) of colour-normal observers ranging from 18 to 75 years of age are assessed. Visual judgments are obtained under normal viewing conditions using colour patches on self-luminous display under controlled adaptation conditions. Trivector discrimination thresholds show an increase as a function of age along the protan, deutan, and tritan axes, with the largest increase present along the tritan line, less pronounced shifts in unique hue settings are also observed. Based on the chromatic (protan, deutan, tritan) thresholds and using scaled cone signals, we predict the unique hue changes with ageing. A dependency on age for unique red and unique yellow for predicted hue angle is found. We conclude that the chromatic sensitivity deteriorates significantly with age, whereas the appearance of unique hues is much less affected, remaining almost constant despite the known changes in the ocular media.%@@ Clromatic sensitivity along the protan, deutan, and tritan lines and the loci of the unique hues (red, green,yellow, blue) for a very large sample (n ＝ 185) of colour-normal observers ranging from 18 to 75 years of age are assessed.Visual judgments are obtained under normal viewing conditions using colour patches on self-luminous display under controlled adaptation conditions.Trivector discrimination thresholds show an increase as a function of age along the protan, deutan, and tritan axes, with the largest increase present along the tritan line, less pronounced shifts in unique hue settings are also observed.

Predicting ecological flow regime at ungaged sites: A comparison of methods

Science.gov (United States)

Murphy, Jennifer C.; Knight, Rodney R.; Wolfe, William J.; Gain, W. Scott

2012-01-01

Nineteen ecologically relevant streamflow characteristics were estimated using published rainfall–runoff and regional regression models for six sites with observed daily streamflow records in Kentucky. The regional regression model produced median estimates closer to the observed median for all but two characteristics. The variability of predictions from both models was generally less than the observed variability. The variability of the predictions from the rainfall–runoff model was greater than that from the regional regression model for all but three characteristics. Eight characteristics predicted by the rainfall–runoff model display positive or negative bias across all six sites; biases are not as pronounced for the regional regression model. Results suggest that a rainfall–runoff model calibrated on a single characteristic is less likely to perform well as a predictor of a range of other characteristics (flow regime) when compared with a regional regression model calibrated individually on multiple characteristics used to represent the flow regime. Poor model performance may misrepresent hydrologic conditions, potentially distorting the perceived risk of ecological degradation. Without prior selection of streamflow characteristics, targeted calibration, and error quantification, the widespread application of general hydrologic models to ecological flow studies is problematic. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.

Predicting on-site environmental impacts of municipal engineering works

International Nuclear Information System (INIS)

Gangolells, Marta; Casals, Miquel; Forcada, Núria; Macarulla, Marcel

2014-01-01

The research findings fill a gap in the body of knowledge by presenting an effective way to evaluate the significance of on-site environmental impacts of municipal engineering works prior to the construction stage. First, 42 on-site environmental impacts of municipal engineering works were identified by means of a process-oriented approach. Then, 46 indicators and their corresponding significance limits were determined on the basis of a statistical analysis of 25 new-build and remodelling municipal engineering projects. In order to ensure the objectivity of the assessment process, direct and indirect indicators were always based on quantitative data from the municipal engineering project documents. Finally, two case studies were analysed and found to illustrate the practical use of the proposed model. The model highlights the significant environmental impacts of a particular municipal engineering project prior to the construction stage. Consequently, preventive actions can be planned and implemented during on-site activities. The results of the model also allow a comparison of proposed municipal engineering projects and alternatives with respect to the overall on-site environmental impact and the absolute importance of a particular environmental aspect. These findings are useful within the framework of the environmental impact assessment process, as they help to improve the identification and evaluation of on-site environmental aspects of municipal engineering works. The findings may also be of use to construction companies that are willing to implement an environmental management system or simply wish to improve on-site environmental performance in municipal engineering projects. -- Highlights: • We present a model to predict the environmental impacts of municipal engineering works. • It highlights significant on-site environmental impacts prior to the construction stage. • Findings are useful within the environmental impact assessment process. • They also

Predicting on-site environmental impacts of municipal engineering works

Energy Technology Data Exchange (ETDEWEB)

Gangolells, Marta, E-mail: marta.gangolells@upc.edu; Casals, Miquel, E-mail: miquel.casals@upc.edu; Forcada, Núria, E-mail: nuria.forcada@upc.edu; Macarulla, Marcel, E-mail: marcel.macarulla@upc.edu

2014-01-15

The research findings fill a gap in the body of knowledge by presenting an effective way to evaluate the significance of on-site environmental impacts of municipal engineering works prior to the construction stage. First, 42 on-site environmental impacts of municipal engineering works were identified by means of a process-oriented approach. Then, 46 indicators and their corresponding significance limits were determined on the basis of a statistical analysis of 25 new-build and remodelling municipal engineering projects. In order to ensure the objectivity of the assessment process, direct and indirect indicators were always based on quantitative data from the municipal engineering project documents. Finally, two case studies were analysed and found to illustrate the practical use of the proposed model. The model highlights the significant environmental impacts of a particular municipal engineering project prior to the construction stage. Consequently, preventive actions can be planned and implemented during on-site activities. The results of the model also allow a comparison of proposed municipal engineering projects and alternatives with respect to the overall on-site environmental impact and the absolute importance of a particular environmental aspect. These findings are useful within the framework of the environmental impact assessment process, as they help to improve the identification and evaluation of on-site environmental aspects of municipal engineering works. The findings may also be of use to construction companies that are willing to implement an environmental management system or simply wish to improve on-site environmental performance in municipal engineering projects. -- Highlights: • We present a model to predict the environmental impacts of municipal engineering works. • It highlights significant on-site environmental impacts prior to the construction stage. • Findings are useful within the environmental impact assessment process. • They also

Concentration and mindfulness meditations: unique forms of consciousness?

Science.gov (United States)

Dunn, B R; Hartigan, J A; Mikulas, W L

1999-09-01

Electroencephalographic (EEG) recordings from 19 scalp recording sites were used to differentiate among two posited unique forms of mediation, concentration and mindfulness, and a normal relaxation control condition. Analyzes of all traditional frequency bandwidth data (i.e., delta 1-3 Hz; theta, 4-7 Hz; alpha, 8-12 Hz; beta 1, 13-25 Hz; beta 2, 26-32 Hz) showed strong mean amplitude frequency differences between the two meditation conditions and relaxation over numerous cortical sites. Furthermore, significant differences were obtained between concentration and mindfulness states at all bandwidths. Taken together, our results suggest that concentration and mindfulness "meditations" may be unique forms of consciousness and are not merely degrees of a state of relaxation.

LIGSITEcsc: predicting ligand binding sites using the Connolly surface and degree of conservation

Directory of Open Access Journals (Sweden)

Schroeder Michael

2006-09-01

Full Text Available Abstract Background Identifying pockets on protein surfaces is of great importance for many structure-based drug design applications and protein-ligand docking algorithms. Over the last ten years, many geometric methods for the prediction of ligand-binding sites have been developed. Results We present LIGSITEcsc, an extension and implementation of the LIGSITE algorithm. LIGSITEcsc is based on the notion of surface-solvent-surface events and the degree of conservation of the involved surface residues. We compare our algorithm to four other approaches, LIGSITE, CAST, PASS, and SURFNET, and evaluate all on a dataset of 48 unbound/bound structures and 210 bound-structures. LIGSITEcsc performs slightly better than the other tools and achieves a success rate of 71% and 75%, respectively. Conclusion The use of the Connolly surface leads to slight improvements, the prediction re-ranking by conservation to significant improvements of the binding site predictions. A web server for LIGSITEcsc and its source code is available at scoppi.biotec.tu-dresden.de/pocket.

Social Networking Site Use Predicts Changes in Young Adults’ Psychological Adjustment

Science.gov (United States)

Szwedo, David E.; Mikami, Amori Yee; Allen, Joseph P.

2012-01-01

This study examined youths’ friendships and posted pictures on social networking sites as predictors of changes in their adjustment over time. Observational, self-report, and peer report data were obtained from a community sample of 89 young adults interviewed at age 21 and again at age 22. Findings were consistent with a leveling effect for online friendships, predicting decreases in internalizing symptoms for youth with lower initial levels of social acceptance, but increases in symptoms for youth with higher initial levels over the following year. Across the entire sample, deviant behavior in posted photos predicted increases in young adults’ problematic alcohol use over time. The importance of considering the interplay between online and offline social factors for predicting adjustment is discussed. PMID:23109797

Predicting ambient aerosol thermal-optical reflectance (TOR) measurements from infrared spectra: extending the predictions to different years and different sites

Science.gov (United States)

Reggente, Matteo; Dillner, Ann M.; Takahama, Satoshi

2016-02-01

Organic carbon (OC) and elemental carbon (EC) are major components of atmospheric particulate matter (PM), which has been associated with increased morbidity and mortality, climate change, and reduced visibility. Typically OC and EC concentrations are measured using thermal-optical methods such as thermal-optical reflectance (TOR) from samples collected on quartz filters. In this work, we estimate TOR OC and EC using Fourier transform infrared (FT-IR) absorbance spectra from polytetrafluoroethylene (PTFE Teflon) filters using partial least square regression (PLSR) calibrated to TOR OC and EC measurements for a wide range of samples. The proposed method can be integrated with analysis of routinely collected PTFE filter samples that, in addition to OC and EC concentrations, can concurrently provide information regarding the functional group composition of the organic aerosol. We have used the FT-IR absorbance spectra and TOR OC and EC concentrations collected in the Interagency Monitoring of PROtected Visual Environments (IMPROVE) network (USA). We used 526 samples collected in 2011 at seven sites to calibrate the models, and more than 2000 samples collected in 2013 at 17 sites to test the models. Samples from six sites are present both in the calibration and test sets. The calibrations produce accurate predictions both for samples collected at the same six sites present in the calibration set (R2 = 0.97 and R2 = 0.95 for OC and EC respectively), and for samples from 9 of the 11 sites not included in the calibration set (R2 = 0.96 and R2 = 0.91 for OC and EC respectively). Samples collected at the other two sites require a different calibration model to achieve accurate predictions. We also propose a method to anticipate the prediction error; we calculate the squared Mahalanobis distance in the feature space (scores determined by PLSR) between new spectra and spectra in the calibration set. The squared Mahalanobis distance provides a crude method for assessing the

Prediction of allosteric sites on protein surfaces with an elastic-network-model-based thermodynamic method.

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Su, Ji Guo; Qi, Li Sheng; Li, Chun Hua; Zhu, Yan Ying; Du, Hui Jing; Hou, Yan Xue; Hao, Rui; Wang, Ji Hua

2014-08-01

Allostery is a rapid and efficient way in many biological processes to regulate protein functions, where binding of an effector at the allosteric site alters the activity and function at a distant active site. Allosteric regulation of protein biological functions provides a promising strategy for novel drug design. However, how to effectively identify the allosteric sites remains one of the major challenges for allosteric drug design. In the present work, a thermodynamic method based on the elastic network model was proposed to predict the allosteric sites on the protein surface. In our method, the thermodynamic coupling between the allosteric and active sites was considered, and then the allosteric sites were identified as those where the binding of an effector molecule induces a large change in the binding free energy of the protein with its ligand. Using the proposed method, two proteins, i.e., the 70 kD heat shock protein (Hsp70) and GluA2 alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptor, were studied and the allosteric sites on the protein surface were successfully identified. The predicted results are consistent with the available experimental data, which indicates that our method is a simple yet effective approach for the identification of allosteric sites on proteins.

Microbial Communities and Their Predicted Metabolic Functions in Growth Laminae of a Unique Large Conical Mat from Lake Untersee, East Antarctica

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Hyunmin Koo

2017-08-01

Full Text Available In this study, we report the distribution of microbial taxa and their predicted metabolic functions observed in the top (U1, middle (U2, and inner (U3 decadal growth laminae of a unique large conical microbial mat from perennially ice-covered Lake Untersee of East Antarctica, using NextGen sequencing of the 16S rRNA gene and bioinformatics tools. The results showed that the U1 lamina was dominated by cyanobacteria, specifically Phormidium sp., Leptolyngbya sp., and Pseudanabaena sp. The U2 and U3 laminae had high abundances of Actinobacteria, Verrucomicrobia, Proteobacteria, and Bacteroidetes. Closely related taxa within each abundant bacterial taxon found in each lamina were further differentiated at the highest taxonomic resolution using the oligotyping method. PICRUSt analysis, which determines predicted KEGG functional categories from the gene contents and abundances among microbial communities, revealed a high number of sequences belonging to carbon fixation, energy metabolism, cyanophycin, chlorophyll, and photosynthesis proteins in the U1 lamina. The functional predictions of the microbial communities in U2 and U3 represented signal transduction, membrane transport, zinc transport and amino acid-, carbohydrate-, and arsenic- metabolisms. The Nearest Sequenced Taxon Index (NSTI values processed through PICRUSt were 0.10, 0.13, and 0.11 for U1, U2, and U3 laminae, respectively. These values indicated a close correspondence with the reference microbial genome database, implying high confidence in the predicted metabolic functions of the microbial communities in each lamina. The distribution of microbial taxa observed in each lamina and their predicted metabolic functions provides additional insight into the complex microbial ecosystem at Lake Untersee, and lays the foundation for studies that will enhance our understanding of the mechanisms responsible for the formation of these unique mat structures and their evolutionary significance.

High DNA melting temperature predicts transcription start site location in human and mouse.

LENUS (Irish Health Repository)

Dineen, David G

2009-12-01

The accurate computational prediction of transcription start sites (TSS) in vertebrate genomes is a difficult problem. The physicochemical properties of DNA can be computed in various ways and a many combinations of DNA features have been tested in the past for use as predictors of transcription. We looked in detail at melting temperature, which measures the temperature, at which two strands of DNA separate, considering the cooperative nature of this process. We find that peaks in melting temperature correspond closely to experimentally determined transcription start sites in human and mouse chromosomes. Using melting temperature alone, and with simple thresholding, we can predict TSS with accuracy that is competitive with the most accurate state-of-the-art TSS prediction methods. Accuracy is measured using both experimentally and manually determined TSS. The method works especially well with CpG island containing promoters, but also works when CpG islands are absent. This result is clear evidence of the important role of the physical properties of DNA in the process of transcription. It also points to the importance for TSS prediction methods to include melting temperature as prior information.

Need for Uniqueness Determines Reactions to Web-Based Personalized Advertising.

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Stiglbauer, Barbara; Kovacs, Carrie

2018-01-01

The presented empirical study among a sample of n = 256 participants addressed the relationship between consumers' need for uniqueness and their reactions to web-based personalized advertising. Drawing on regulatory focus theory, we argue that the consumers' need for uniqueness dimensions creative choice and similarity avoidance may relate to promotion and prevention regulatory orientations, respectively. Accordingly, we hypothesized that creative choice and similarity avoidance would differentially predict self-reported approach and avoidance behavior toward personalized advertising. These direct relationships were further expected to be mediated by subjective evaluations of personalized advertising (i.e., perceived value and irritation). In line with these hypotheses, we found that creative choice predicted approach behavior through increased web-based personalized advertising value, whereas similarity avoidance predicted avoidance behavior through increased irritation. Creative choice also predicted decreased irritation, which in turn was related to decreased approach behavior. In sum, the results suggest that the consumers' need for uniqueness dimensions should not be investigated as a composite, as they seem to reflect different regulatory orientations and are therefore likely to evoke different affective, cognitive, and behavioral responses.

Seafloor massive sulfide deposits support unique megafaunal assemblages: Implications for seabed mining and conservation.

Science.gov (United States)

Boschen, Rachel E; Rowden, Ashley A; Clark, Malcolm R; Pallentin, Arne; Gardner, Jonathan P A

2016-04-01

Mining of seafloor massive sulfides (SMS) is imminent, but the ecology of assemblages at SMS deposits is poorly known. Proposed conservation strategies include protected areas to preserve biodiversity at risk from mining impacts. Determining site suitability requires biological characterisation of the mine site and protected area(s). Video survey of a proposed mine site and protected area off New Zealand revealed unique megafaunal assemblages at the mine site. Significant relationships were identified between assemblage structure and environmental conditions, including hydrothermal features. Unique assemblages occurred at both active and inactive chimneys and are particularly at risk from mining-related impacts. The occurrence of unique assemblages at the mine site suggests that the proposed protected area is insufficient alone and should instead form part of a network. These results provide support for including hydrothermally active and inactive features within networks of protected areas and emphasise the need for quantitative survey data of proposed sites. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Position-specific prediction of methylation sites from sequence conservation based on information theory.

Science.gov (United States)

Shi, Yinan; Guo, Yanzhi; Hu, Yayun; Li, Menglong

2015-07-23

Protein methylation plays vital roles in many biological processes and has been implicated in various human diseases. To fully understand the mechanisms underlying methylation for use in drug design and work in methylation-related diseases, an initial but crucial step is to identify methylation sites. The use of high-throughput bioinformatics methods has become imperative to predict methylation sites. In this study, we developed a novel method that is based only on sequence conservation to predict protein methylation sites. Conservation difference profiles between methylated and non-methylated peptides were constructed by the information entropy (IE) in a wider neighbor interval around the methylation sites that fully incorporated all of the environmental information. Then, the distinctive neighbor residues were identified by the importance scores of information gain (IG). The most representative model was constructed by support vector machine (SVM) for Arginine and Lysine methylation, respectively. This model yielded a promising result on both the benchmark dataset and independent test set. The model was used to screen the entire human proteome, and many unknown substrates were identified. These results indicate that our method can serve as a useful supplement to elucidate the mechanism of protein methylation and facilitate hypothesis-driven experimental design and validation.

Site characterization and validation. Stage 2 - Preliminary predictions

International Nuclear Information System (INIS)

Olsson, O.; Black, J.H.; Gale, J.E.; Holmes, D.C.

1989-05-01

The Site Characterization and Validation (SCV) project is designed to assess how well we can characterize a volume of rock prior to using it as a repository. The programme of work focuses on the validation of the techniques used in site characterization. The SCV project contains 5 stages of work arranged in two 'cycles' of data-gathering, prediction, and validation. The first stage of work has included drilling of 6 boreholes (N2, N3, N4, W1, W2 and V3) and measurements of geology, fracture characteristics, stess, single borehole geophysical logging, radar, seismics and hydrogeology. The rock at the SCV site is granite with small lithological variations. Based essentially on radar and seismic results 5 'fracture zones' have been identified, named GA, GB, GC, GH and GI. They all extend acroos the entire SCV site. They aer basically in in two groups (GA, GB, GC and GH, GI). The first group are aligned N40 degree E with a dip of 35 degree to the south. The second group are aligned approximately N10 degree W dipping 60 degree E. From the stochastic analysis of the joint data it was possible to identify three main fracture orientation clusters. The orientation of two of these clusters agree roughly with orientation of the main features. Cluster B has roughly the same orientation as GH and GI, while features GA, GB and GC have an orientation similar to the more loosely defined cluster C. The orientation of the third cluster (A) is northwest with a dip to northeast. It is found that 94% of all measured hydraulic transmissivity is accounted for by 4% of the tested rock, not all of this 'concentrated' transmissivity is with the major features defined by geophysics. When the hydraulic connections across the site are examied they show that there are several welldefined zones which permit rapid transmission of hydraulic signals. These are essentially from the northeast to the southwest. (66 figs., 21 tabs., 33 refs.)

Prediction of Poly(A Sites by Poly(A Read Mapping.

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Thomas Bonfert

Full Text Available RNA-seq reads containing part of the poly(A tail of transcripts (denoted as poly(A reads provide the most direct evidence for the position of poly(A sites in the genome. However, due to reduced coverage of poly(A tails by reads, poly(A reads are not routinely identified during RNA-seq mapping. Nevertheless, recent studies for several herpesviruses successfully employed mapping of poly(A reads to identify herpesvirus poly(A sites using different strategies and customized programs. To more easily allow such analyses without requiring additional programs, we integrated poly(A read mapping and prediction of poly(A sites into our RNA-seq mapping program ContextMap 2. The implemented approach essentially generalizes previously used poly(A read mapping approaches and combines them with the context-based approach of ContextMap 2 to take into account information provided by other reads aligned to the same location. Poly(A read mapping using ContextMap 2 was evaluated on real-life data from the ENCODE project and compared against a competing approach based on transcriptome assembly (KLEAT. This showed high positive predictive value for our approach, evidenced also by the presence of poly(A signals, and considerably lower runtime than KLEAT. Although sensitivity is low for both methods, we show that this is in part due to a high extent of spurious results in the gold standard set derived from RNA-PET data. Sensitivity improves for poly(A sites of known transcripts or determined with a more specific poly(A sequencing protocol and increases with read coverage on transcript ends. Finally, we illustrate the usefulness of the approach in a high read coverage scenario by a re-analysis of published data for herpes simplex virus 1. Thus, with current trends towards increasing sequencing depth and read length, poly(A read mapping will prove to be increasingly useful and can now be performed automatically during RNA-seq mapping with ContextMap 2.

Pharmacological considerations for predicting PK/PD at the site of action for therapeutic proteins.

Science.gov (United States)

Wang, Weirong; Zhou, Honghui

For therapeutic proteins whose sites of action are distal to the systemic circulation, both drug and target concentrations at the tissue sites are not necessarily proportional to those in systemic circulation, highlighting the importance of understanding pharmacokinetic/pharmacodynamic (PK/PD) relationship at the sites of action. This review summarizes the pharmacological considerations for predicting local PK/PD and the importance of measuring PK and PD at site of action. Three case examples are presented to show how mechanistic and physiologically based PK/PD (PBPK/PD) models which incorporated the PK and PD at the tissue site can be used to facilitate understanding the exposure-response relationship for therapeutic proteins. Copyright © 2016. Published by Elsevier Ltd.

A homology-based pipeline for global prediction of post-translational modification sites

Science.gov (United States)

Chen, Xiang; Shi, Shao-Ping; Xu, Hao-Dong; Suo, Sheng-Bao; Qiu, Jian-Ding

2016-05-01

The pathways of protein post-translational modifications (PTMs) have been shown to play particularly important roles for almost any biological process. Identification of PTM substrates along with information on the exact sites is fundamental for fully understanding or controlling biological processes. Alternative computational strategies would help to annotate PTMs in a high-throughput manner. Traditional algorithms are suited for identifying the common organisms and tissues that have a complete PTM atlas or extensive experimental data. While annotation of rare PTMs in most organisms is a clear challenge. In this work, to this end we have developed a novel homology-based pipeline named PTMProber that allows identification of potential modification sites for most of the proteomes lacking PTMs data. Cross-promotion E-value (CPE) as stringent benchmark has been used in our pipeline to evaluate homology to known modification sites. Independent-validation tests show that PTMProber achieves over 58.8% recall with high precision by CPE benchmark. Comparisons with other machine-learning tools show that PTMProber pipeline performs better on general predictions. In addition, we developed a web-based tool to integrate this pipeline at http://bioinfo.ncu.edu.cn/PTMProber/index.aspx. In addition to pre-constructed prediction models of PTM, the website provides an extensional functionality to allow users to customize models.

Prediction of citrullination sites by incorporating k-spaced amino acid pairs into Chou's general pseudo amino acid composition.

Science.gov (United States)

Ju, Zhe; Wang, Shi-Yun

2018-04-22

As one of the most important and common protein post-translational modifications, citrullination plays a key role in regulating various biological processes and is associated with several human diseases. The accurate identification of citrullination sites is crucial for elucidating the underlying molecular mechanisms of citrullination and designing drugs for related human diseases. In this study, a novel bioinformatics tool named CKSAAP_CitrSite is developed for the prediction of citrullination sites. With the assistance of support vector machine algorithm, the highlight of CKSAAP_CitrSite is to adopt the composition of k-spaced amino acid pairs surrounding a query site as input. As illustrated by 10-fold cross-validation, CKSAAP_CitrSite achieves a satisfactory performance with a Sensitivity of 77.59%, a Specificity of 95.26%, an Accuracy of 89.37% and a Matthew's correlation coefficient of 0.7566, which is much better than those of the existing prediction method. Feature analysis shows that the N-terminal space containing pairs may play an important role in the prediction of citrullination sites, and the arginines close to N-terminus tend to be citrullinated. The conclusions derived from this study could offer useful information for elucidating the molecular mechanisms of citrullination and related experimental validations. A user-friendly web-server for CKSAAP_CitrSite is available at 123.206.31.171/CKSAAP_CitrSite/. Copyright © 2017. Published by Elsevier B.V.

Prediction of mucin-type O-glycosylation sites in mammalian proteins using the composition of k-spaced amino acid pairs

Directory of Open Access Journals (Sweden)

Sheng Zhi-Ya

2008-02-01

Full Text Available Abstract Background As one of the most common protein post-translational modifications, glycosylation is involved in a variety of important biological processes. Computational identification of glycosylation sites in protein sequences becomes increasingly important in the post-genomic era. A new encoding scheme was employed to improve the prediction of mucin-type O-glycosylation sites in mammalian proteins. Results A new protein bioinformatics tool, CKSAAP_OGlySite, was developed to predict mucin-type O-glycosylation serine/threonine (S/T sites in mammalian proteins. Using the composition of k-spaced amino acid pairs (CKSAAP based encoding scheme, the proposed method was trained and tested in a new and stringent O-glycosylation dataset with the assistance of Support Vector Machine (SVM. When the ratio of O-glycosylation to non-glycosylation sites in training datasets was set as 1:1, 10-fold cross-validation tests showed that the proposed method yielded a high accuracy of 83.1% and 81.4% in predicting O-glycosylated S and T sites, respectively. Based on the same datasets, CKSAAP_OGlySite resulted in a higher accuracy than the conventional binary encoding based method (about +5.0%. When trained and tested in 1:5 datasets, the CKSAAP encoding showed a more significant improvement than the binary encoding. We also merged the training datasets of S and T sites and integrated the prediction of S and T sites into one single predictor (i.e. S+T predictor. Either in 1:1 or 1:5 datasets, the performance of this S+T predictor was always slightly better than those predictors where S and T sites were independently predicted, suggesting that the molecular recognition of O-glycosylated S/T sites seems to be similar and the increase of the S+T predictor's accuracy may be a result of expanded training datasets. Moreover, CKSAAP_OGlySite was also shown to have better performance when benchmarked against two existing predictors. Conclusion Because of CKSAAP

AthMethPre: a web server for the prediction and query of mRNA m6A sites in Arabidopsis thaliana.

Science.gov (United States)

Xiang, Shunian; Yan, Zhangming; Liu, Ke; Zhang, Yaou; Sun, Zhirong

2016-10-18

N 6 -Methyladenosine (m 6 A) is the most prevalent and abundant modification in mRNA that has been linked to many key biological processes. High-throughput experiments have generated m 6 A-peaks across the transcriptome of A. thaliana, but the specific methylated sites were not assigned, which impedes the understanding of m 6 A functions in plants. Therefore, computational prediction of mRNA m 6 A sites becomes emergently important. Here, we present a method to predict the m 6 A sites for A. thaliana mRNA sequence(s). To predict the m 6 A sites of an mRNA sequence, we employed the support vector machine to build a classifier using the features of the positional flanking nucleotide sequence and position-independent k-mer nucleotide spectrum. Our method achieved good performance and was applied to a web server to provide service for the prediction of A. thaliana m 6 A sites. The server also provides a comprehensive database of predicted transcriptome-wide m 6 A sites and curated m 6 A-seq peaks from the literature for query and visualization. The AthMethPre web server is the first web server that provides a user-friendly tool for the prediction and query of A. thaliana mRNA m 6 A sites, which is freely accessible for public use at .

Modelling for the Stripa site characterization and validation drift inflow: prediction of flow through fractured rock

International Nuclear Information System (INIS)

Herbert, A.; Gale, J.; MacLeod, R.; Lanyon, G.

1991-12-01

We present our approach to predicting flow through a fractured rock site; the site characterization and validation region in the Stripa mine. Our approach is based on discrete fracture network modelling using the NAPSAC computer code. We describe the conceptual models and assumptions that we have used to interpret the geometry and flow properties of the fracture networks, from measurements at the site. These are used to investigate large scale properties of the network and we show that for flows on scales larger than about 10 m, porous medium approximation should be used. The porous medium groundwater flow code CFEST is used to predict the large scale flows through the mine and the SCV region. This, in turn, is used to provide boundary conditions for more detailed models, which predict the details of flow, using a discrete fracture network model, on scales of less than 10 m. We conclude that a fracture network approach is feasible and that it provides a better understanding of details of flow than conventional porous medium approaches and a quantification of the uncertainty associated with predictive flow modelling characterised from field measurement in fractured rock. (au)

ProBiS-ligands: a web server for prediction of ligands by examination of protein binding sites.

Science.gov (United States)

Konc, Janez; Janežič, Dušanka

2014-07-01

The ProBiS-ligands web server predicts binding of ligands to a protein structure. Starting with a protein structure or binding site, ProBiS-ligands first identifies template proteins in the Protein Data Bank that share similar binding sites. Based on the superimpositions of the query protein and the similar binding sites found, the server then transposes the ligand structures from those sites to the query protein. Such ligand prediction supports many activities, e.g. drug repurposing. The ProBiS-ligands web server, an extension of the ProBiS web server, is open and free to all users at http://probis.cmm.ki.si/ligands. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Geospatial Analytics in Retail Site Selection and Sales Prediction.

Science.gov (United States)

Ting, Choo-Yee; Ho, Chiung Ching; Yee, Hui Jia; Matsah, Wan Razali

2018-03-01

Studies have shown that certain features from geography, demography, trade area, and environment can play a vital role in retail site selection, largely due to the impact they asserted on retail performance. Although the relevant features could be elicited by domain experts, determining the optimal feature set can be intractable and labor-intensive exercise. The challenges center around (1) how to determine features that are important to a particular retail business and (2) how to estimate retail sales performance given a new location? The challenges become apparent when the features vary across time. In this light, this study proposed a nonintervening approach by employing feature selection algorithms and subsequently sales prediction through similarity-based methods. The results of prediction were validated by domain experts. In this study, data sets from different sources were transformed and aggregated before an analytics data set that is ready for analysis purpose could be obtained. The data sets included data about feature location, population count, property type, education status, and monthly sales from 96 branches of a telecommunication company in Malaysia. The finding suggested that (1) optimal retail performance can only be achieved through fulfillment of specific location features together with the surrounding trade area characteristics and (2) similarity-based method can provide solution to retail sales prediction.

Prediction of glutathionylation sites in proteins using minimal sequence information and their experimental validation.

Science.gov (United States)

Pal, Debojyoti; Sharma, Deepak; Kumar, Mukesh; Sandur, Santosh K

2016-09-01

S-glutathionylation of proteins plays an important role in various biological processes and is known to be protective modification during oxidative stress. Since, experimental detection of S-glutathionylation is labor intensive and time consuming, bioinformatics based approach is a viable alternative. Available methods require relatively longer sequence information, which may prevent prediction if sequence information is incomplete. Here, we present a model to predict glutathionylation sites from pentapeptide sequences. It is based upon differential association of amino acids with glutathionylated and non-glutathionylated cysteines from a database of experimentally verified sequences. This data was used to calculate position dependent F-scores, which measure how a particular amino acid at a particular position may affect the likelihood of glutathionylation event. Glutathionylation-score (G-score), indicating propensity of a sequence to undergo glutathionylation, was calculated using position-dependent F-scores for each amino-acid. Cut-off values were used for prediction. Our model returned an accuracy of 58% with Matthew's correlation-coefficient (MCC) value of 0.165. On an independent dataset, our model outperformed the currently available model, in spite of needing much less sequence information. Pentapeptide motifs having high abundance among glutathionylated proteins were identified. A list of potential glutathionylation hotspot sequences were obtained by assigning G-scores and subsequent Protein-BLAST analysis revealed a total of 254 putative glutathionable proteins, a number of which were already known to be glutathionylated. Our model predicted glutathionylation sites in 93.93% of experimentally verified glutathionylated proteins. Outcome of this study may assist in discovering novel glutathionylation sites and finding candidate proteins for glutathionylation.

Characterization and Prediction of Protein Phosphorylation Hotspots in Arabidopsis thaliana.

Science.gov (United States)

Christian, Jan-Ole; Braginets, Rostyslav; Schulze, Waltraud X; Walther, Dirk

2012-01-01

The regulation of protein function by modulating the surface charge status via sequence-locally enriched phosphorylation sites (P-sites) in so called phosphorylation "hotspots" has gained increased attention in recent years. We set out to identify P-hotspots in the model plant Arabidopsis thaliana. We analyzed the spacing of experimentally detected P-sites within peptide-covered regions along Arabidopsis protein sequences as available from the PhosPhAt database. Confirming earlier reports (Schweiger and Linial, 2010), we found that, indeed, P-sites tend to cluster and that distributions between serine and threonine P-sites to their respected closest next P-site differ significantly from those for tyrosine P-sites. The ability to predict P-hotspots by applying available computational P-site prediction programs that focus on identifying single P-sites was observed to be severely compromised by the inevitable interference of nearby P-sites. We devised a new approach, named HotSPotter, for the prediction of phosphorylation hotspots. HotSPotter is based primarily on local amino acid compositional preferences rather than sequence position-specific motifs and uses support vector machines as the underlying classification engine. HotSPotter correctly identified experimentally determined phosphorylation hotspots in A. thaliana with high accuracy. Applied to the Arabidopsis proteome, HotSPotter-predicted 13,677 candidate P-hotspots in 9,599 proteins corresponding to 7,847 unique genes. Hotspot containing proteins are involved predominantly in signaling processes confirming the surmised modulating role of hotspots in signaling and interaction events. Our study provides new bioinformatics means to identify phosphorylation hotspots and lays the basis for further investigating novel candidate P-hotspots. All phosphorylation hotspot annotations and predictions have been made available as part of the PhosPhAt database at http://phosphat.mpimp-golm.mpg.de.

NBA-Palm: prediction of palmitoylation site implemented in Naïve Bayes algorithm.

Science.gov (United States)

Xue, Yu; Chen, Hu; Jin, Changjiang; Sun, Zhirong; Yao, Xuebiao

2006-10-17

Protein palmitoylation, an essential and reversible post-translational modification (PTM), has been implicated in cellular dynamics and plasticity. Although numerous experimental studies have been performed to explore the molecular mechanisms underlying palmitoylation processes, the intrinsic feature of substrate specificity has remained elusive. Thus, computational approaches for palmitoylation prediction are much desirable for further experimental design. In this work, we present NBA-Palm, a novel computational method based on Naïve Bayes algorithm for prediction of palmitoylation site. The training data is curated from scientific literature (PubMed) and includes 245 palmitoylated sites from 105 distinct proteins after redundancy elimination. The proper window length for a potential palmitoylated peptide is optimized as six. To evaluate the prediction performance of NBA-Palm, 3-fold cross-validation, 8-fold cross-validation and Jack-Knife validation have been carried out. Prediction accuracies reach 85.79% for 3-fold cross-validation, 86.72% for 8-fold cross-validation and 86.74% for Jack-Knife validation. Two more algorithms, RBF network and support vector machine (SVM), also have been employed and compared with NBA-Palm. Taken together, our analyses demonstrate that NBA-Palm is a useful computational program that provides insights for further experimentation. The accuracy of NBA-Palm is comparable with our previously described tool CSS-Palm. The NBA-Palm is freely accessible from: http://www.bioinfo.tsinghua.edu.cn/NBA-Palm.

Friends' Alcohol-Related Social Networking Site Activity Predicts Escalations in Adolescent Drinking: Mediation by Peer Norms.

Science.gov (United States)

Nesi, Jacqueline; Rothenberg, W Andrew; Hussong, Andrea M; Jackson, Kristina M

2017-06-01

Adolescents' increased use of social networking sites (SNS) coincides with a developmental period of heightened risk for alcohol use initiation. However, little is known regarding associations between adolescents' SNS use and drinking initiation nor the mechanisms of this association. This study examined longitudinal associations among adolescents' exposure to friends' alcohol-related SNS postings, alcohol-favorable peer injunctive norms, and initiation of drinking behaviors. Participants were 658 high-school students who reported on posting of alcohol-related SNS content by self and friends, alcohol-related injunctive norms, and other developmental risk factors for alcohol use at two time points, 1 year apart. Participants also reported on initiation of three drinking behaviors: consuming a full drink, becoming drunk, and heavy episodic drinking (three or more drinks per occasion). Probit regression analyses were used to predict initiation of drinking behaviors from exposure to alcohol-related SNS content. Path analyses examined mediation of this association by peer injunctive norms. Exposure to friends' alcohol-related SNS content predicted adolescents' initiation of drinking and heavy episodic drinking 1 year later, controlling for demographic and known developmental risk factors for alcohol use (i.e., parental monitoring and peer orientation). In addition, alcohol-favorable peer injunctive norms statistically mediated the relationship between alcohol-related SNS exposure and each drinking milestone. Results suggest that social media plays a unique role in contributing to peer influence processes surrounding alcohol use and highlight the need for future investigative and preventive efforts to account for adolescents' changing social environments. Copyright © 2017 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Computational prediction of cAMP receptor protein (CRP binding sites in cyanobacterial genomes

Directory of Open Access Journals (Sweden)

Su Zhengchang

2009-01-01

Full Text Available Abstract Background Cyclic AMP receptor protein (CRP, also known as catabolite gene activator protein (CAP, is an important transcriptional regulator widely distributed in many bacteria. The biological processes under the regulation of CRP are highly diverse among different groups of bacterial species. Elucidation of CRP regulons in cyanobacteria will further our understanding of the physiology and ecology of this important group of microorganisms. Previously, CRP has been experimentally studied in only two cyanobacterial strains: Synechocystis sp. PCC 6803 and Anabaena sp. PCC 7120; therefore, a systematic genome-scale study of the potential CRP target genes and binding sites in cyanobacterial genomes is urgently needed. Results We have predicted and analyzed the CRP binding sites and regulons in 12 sequenced cyanobacterial genomes using a highly effective cis-regulatory binding site scanning algorithm. Our results show that cyanobacterial CRP binding sites are very similar to those in E. coli; however, the regulons are very different from that of E. coli. Furthermore, CRP regulons in different cyanobacterial species/ecotypes are also highly diversified, ranging from photosynthesis, carbon fixation and nitrogen assimilation, to chemotaxis and signal transduction. In addition, our prediction indicates that crp genes in modern cyanobacteria are likely inherited from a common ancestral gene in their last common ancestor, and have adapted various cellular functions in different environments, while some cyanobacteria lost their crp genes as well as CRP binding sites during the course of evolution. Conclusion The CRP regulons in cyanobacteria are highly diversified, probably as a result of divergent evolution to adapt to various ecological niches. Cyanobacterial CRPs may function as lineage-specific regulators participating in various cellular processes, and are important in some lineages. However, they are dispensable in some other lineages. The

Prediction of suspended-sediment concentrations at selected sites in the Fountain Creek watershed, Colorado, 2008-09

Science.gov (United States)

Stogner, Sr., Robert W.; Nelson, Jonathan M.; McDonald, Richard R.; Kinzel, Paul J.; Mau, David P.

2013-01-01

In 2008, the U.S. Geological Survey (USGS), in cooperation with Pikes Peak Area Council of Governments, Colorado Water Conservation Board, Colorado Springs City Engineering, and the Lower Arkansas Valley Water Conservancy District, began a small-scale pilot study to evaluate the effectiveness of the use of a computational model of streamflow and suspended-sediment transport for predicting suspended-sediment concentrations and loads in the Fountain Creek watershed in Colorado. Increased erosion and sedimentation damage have been identified by the Fountain Creek Watershed Plan as key problems within the watershed. A recommendation in the Fountain Creek Watershed plan for management of the basin is to establish measurable criteria to determine if progress in reducing erosion and sedimentation damage is being made. The major objective of this study was to test a computational method to predict local suspended-sediment loads at two sites with different geomorphic characteristics in order to evaluate the feasibility of using such an approach to predict local suspended-sediment loads throughout the entire watershed. Detailed topographic surveys, particle-size data, and suspended-sediment samples were collected at two gaged sites: Monument Creek above Woodmen Road at Colorado Springs, Colorado (USGS gage 07103970), and Sand Creek above mouth at Colorado Springs, Colorado (USGS gage 07105600). These data were used to construct three-dimensional computational models of relatively short channel reaches at each site. The streamflow component of these models predicted a spatially distributed field of water-surface elevation, water velocity, and bed shear stress for a range of stream discharges. Using the model predictions, along with measured particle sizes, the sediment-transport component of the model predicted the suspended-sediment concentration throughout the reach of interest. These computed concentrations were used with predicted flow patterns and channel morphology to

Mapping the heparin-binding site of the BMP antagonist gremlin by site-directed mutagenesis based on predictive modelling.

Science.gov (United States)

Tatsinkam, Arnold Junior; Mulloy, Barbara; Rider, Christopher C

2015-08-15

Gremlin is a member of the CAN (cerberus and DAN) family of secreted BMP (bone morphogenetic protein) antagonists and also an agonist of VEGF (vascular endothelial growth factor) receptor-2. It is critical in limb skeleton and kidney development and is re-expressed during tissue fibrosis. Gremlin binds strongly to heparin and heparan sulfate and, in the present study, we sought to investigate its heparin-binding site. In order to explore a putative non-contiguous binding site predicted by computational molecular modelling, we substituted a total of 11 key arginines and lysines located in three basic residue sequence clusters with homologous sequences from cerberus and DAN (differential screening selected gene abberative in neuroblastoma), CAN proteins which lack basic residues in these positions. A panel of six Myc-tagged gremlin mutants, MGR-1-MGR-6 (MGR, mutant gremlin), each containing different combinations of targeted substitutions, all showed markedly reduced affinity for heparin as demonstrated by their NaCl elution on heparin affinity chromatography, thus verifying our predictions. Both MGR-5 and MGR-6 retained BMP-4-binding activity comparable to that of wild-type gremlin. Low-molecular-mass heparin neither promoted nor inhibited BMP-4 binding. Finally, glutaraldehyde cross-linking demonstrated that gremlin forms non-covalent dimers, similar behaviour to that of DAN and also PRDC (protein related to cerberus and DAN), another CAN protein. The resulting dimer would possess two heparin-binding sites, each running along an exposed surface on the second β-strand finger loop of one of the monomers. © 2015 Authors; published by Portland Press Limited.

The predictable nature of the Paleozoic sedimentary sequence beneath the Bruce nuclear site in Southern Ontario, Canada

International Nuclear Information System (INIS)

Parmenter, Andrew; Jensen, Mark; Crowe, Richard

2012-01-01

Document available in extended abstract form only. A key aspect of a Deep Geologic Repository (DGR) safety case is the ability to develop and communicate an understanding of the geologic stability and resilience to change at time frames relevant to demonstrating repository performance. As part of an on-going Environmental Assessment, Ontario Power Generation (OPG) recently completed site-specific investigations within an 850 m thick Paleozoic sedimentary sequence beneath the Bruce nuclear site for the proposed development of a DGR for Low and Intermediate Level Waste (L and ILW). As envisioned, the shaft-accessed DGR would be excavated at a nominal depth of 680 m within the low permeability Ordovician argillaceous limestone of the Cobourg Formation, which is overlain by more than 200 m of low permeability Ordovician shale. The geo-scientific investigations revealed a relatively undeformed and laterally continuous architecture within the sedimentary sequence at the repository scale (1.5 km 2 ) and beyond. This paper explores the predictable nature of the sedimentary sequence that has contributed to increasing confidence in an understanding of the spatial distribution of groundwater system properties, deep groundwater system evolution and natural barrier performance. Multi-disciplinary geo-scientific investigations of the Bruce nuclear site were completed in 3 phases between 2006 and 2010. The sub-surface investigations included a deep drilling, coring and in-situ testing program and, the completion of a 19.7 km (9 lines) 2-D seismic reflection survey. The drilling program involved 6 (150 mm dia.) deep boreholes (4-vertical; 2 inclined) that were extended through the sedimentary sequence from 4 drill sites, arranged around the 0.3 km 2 footprint of the proposed repository. The more than 3.8 km of rock core (77 mm dia.) retrieved have provided, in part, a strong basis to understand bedrock lithology and mineralogy, facies assemblages, structure, and oil and gas

A RCRA clean closure of a unique site - Kerr Hollow quarry at the Y-12 Plant

International Nuclear Information System (INIS)

Stone, J.E.; Yemington, C.

1991-01-01

An abandoned rock quarry, Kerr Hollow Quarry (KHQ), near the DOE Oak Ridge Y-12 Plant, Oak Ridge, Tennessee, was used from 1951-1988 as a site to treat RCRA wastes which were reactive, corrosive, or ignitable and which posed major concerns for personnel safety. The wastes were generated from operations at the Y-12 Plant and Oak Ridge National Laboratory and were previously treated by allowing the wastes to react with the water in KHQ. When closure of the site was required by the RCRA regulations, a closure method was selected to allow for clean closure of the quarry without treatment or removal of the water in KHQ. The method proposed to and approved by the Tennessee Department of Health and Environment (TDHE) was one of surveying the containers in the quarry by a submersible Remotely Operated Vehicle (ROV) using sonar and visually inspecting the containers by camera to confirm that all containers are breached and empty. Any container found intact would be breached to allow the contents to react with water and form non-hazardous residue. The progress of this unique type of closure is presented along with a summary of the problems encountered, planning activities, equipment utilized and other information about the closure. All work was done with remotely operated equipment. This work is being performed by Sonsub, Inc. This closure project showed the practicality and cost benefits of telerobotic systems for work on hazardous waste sites. In addition to the intangible benefit of reduced exposure of workers, insurance costs are much lower and efficiency is higher. Daily start-up time is reduced since there is no need to don protective suits or other gear. Productivity is higher since personnel work only in clean areas where they are not hampered by protective gear. Cleanup time at shift end is minimized since the remote equipment does not leave the hazardous area and personnel need not go through decontamination

JASSA: a comprehensive tool for prediction of SUMOylation sites and SIMs.

Science.gov (United States)

Beauclair, Guillaume; Bridier-Nahmias, Antoine; Zagury, Jean-François; Saïb, Ali; Zamborlini, Alessia

2015-11-01

Post-translational modification by the Small Ubiquitin-like Modifier (SUMO) proteins, a process termed SUMOylation, is involved in many fundamental cellular processes. SUMO proteins are conjugated to a protein substrate, creating an interface for the recruitment of cofactors harboring SUMO-interacting motifs (SIMs). Mapping both SUMO-conjugation sites and SIMs is required to study the functional consequence of SUMOylation. To define the best candidate sites for experimental validation we designed JASSA, a Joint Analyzer of SUMOylation site and SIMs. JASSA is a predictor that uses a scoring system based on a Position Frequency Matrix derived from the alignment of experimental SUMOylation sites or SIMs. Compared with existing web-tools, JASSA displays on par or better performances. Novel features were implemented towards a better evaluation of the prediction, including identification of database hits matching the query sequence and representation of candidate sites within the secondary structural elements and/or the 3D fold of the protein of interest, retrievable from deposited PDB files. JASSA is freely accessible at http://www.jassa.fr/. Website is implemented in PHP and MySQL, with all major browsers supported. guillaume.beauclair@inserm.fr Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Prediction of protein binding sites using physical and chemical descriptors and the support vector machine regression method

International Nuclear Information System (INIS)

Sun Zhong-Hua; Jiang Fan

2010-01-01

In this paper a new continuous variable called core-ratio is defined to describe the probability for a residue to be in a binding site, thereby replacing the previous binary description of the interface residue using 0 and 1. So we can use the support vector machine regression method to fit the core-ratio value and predict the protein binding sites. We also design a new group of physical and chemical descriptors to characterize the binding sites. The new descriptors are more effective, with an averaging procedure used. Our test shows that much better prediction results can be obtained by the support vector regression (SVR) method than by the support vector classification method. (rapid communication)

Streamflow prediction using multi-site rainfall obtained from hydroclimatic teleconnection

Science.gov (United States)

Kashid, S. S.; Ghosh, Subimal; Maity, Rajib

2010-12-01

SummarySimultaneous variations in weather and climate over widely separated regions are commonly known as "hydroclimatic teleconnections". Rainfall and runoff patterns, over continents, are found to be significantly teleconnected, with large-scale circulation patterns, through such hydroclimatic teleconnections. Though such teleconnections exist in nature, it is very difficult to model them, due to their inherent complexity. Statistical techniques and Artificial Intelligence (AI) tools gain popularity in modeling hydroclimatic teleconnection, based on their ability, in capturing the complicated relationship between the predictors (e.g. sea surface temperatures) and predictand (e.g., rainfall). Genetic Programming is such an AI tool, which is capable of capturing nonlinear relationship, between predictor and predictand, due to its flexible functional structure. In the present study, gridded multi-site weekly rainfall is predicted from El Niño Southern Oscillation (ENSO) indices, Equatorial Indian Ocean Oscillation (EQUINOO) indices, Outgoing Longwave Radiation (OLR) and lag rainfall at grid points, over the catchment, using Genetic Programming. The predicted rainfall is further used in a Genetic Programming model to predict streamflows. The model is applied for weekly forecasting of streamflow in Mahanadi River, India, and satisfactory performance is observed.

Predicting risk of trace element pollution from municipal roads using site-specific soil samples and remotely sensed data.

Science.gov (United States)

Reeves, Mari Kathryn; Perdue, Margaret; Munk, Lee Ann; Hagedorn, Birgit

2018-07-15

Studies of environmental processes exhibit spatial variation within data sets. The ability to derive predictions of risk from field data is a critical path forward in understanding the data and applying the information to land and resource management. Thanks to recent advances in predictive modeling, open source software, and computing, the power to do this is within grasp. This article provides an example of how we predicted relative trace element pollution risk from roads across a region by combining site specific trace element data in soils with regional land cover and planning information in a predictive model framework. In the Kenai Peninsula of Alaska, we sampled 36 sites (191 soil samples) adjacent to roads for trace elements. We then combined this site specific data with freely-available land cover and urban planning data to derive a predictive model of landscape scale environmental risk. We used six different model algorithms to analyze the dataset, comparing these in terms of their predictive abilities and the variables identified as important. Based on comparable predictive abilities (mean R 2 from 30 to 35% and mean root mean square error from 65 to 68%), we averaged all six model outputs to predict relative levels of trace element deposition in soils-given the road surface, traffic volume, sample distance from the road, land cover category, and impervious surface percentage. Mapped predictions of environmental risk from toxic trace element pollution can show land managers and transportation planners where to prioritize road renewal or maintenance by each road segment's relative environmental and human health risk. Published by Elsevier B.V.

NBA-Palm: prediction of palmitoylation site implemented in Naïve Bayes algorithm

Directory of Open Access Journals (Sweden)

Jin Changjiang

2006-10-01

Full Text Available Abstract Background Protein palmitoylation, an essential and reversible post-translational modification (PTM, has been implicated in cellular dynamics and plasticity. Although numerous experimental studies have been performed to explore the molecular mechanisms underlying palmitoylation processes, the intrinsic feature of substrate specificity has remained elusive. Thus, computational approaches for palmitoylation prediction are much desirable for further experimental design. Results In this work, we present NBA-Palm, a novel computational method based on Naïve Bayes algorithm for prediction of palmitoylation site. The training data is curated from scientific literature (PubMed and includes 245 palmitoylated sites from 105 distinct proteins after redundancy elimination. The proper window length for a potential palmitoylated peptide is optimized as six. To evaluate the prediction performance of NBA-Palm, 3-fold cross-validation, 8-fold cross-validation and Jack-Knife validation have been carried out. Prediction accuracies reach 85.79% for 3-fold cross-validation, 86.72% for 8-fold cross-validation and 86.74% for Jack-Knife validation. Two more algorithms, RBF network and support vector machine (SVM, also have been employed and compared with NBA-Palm. Conclusion Taken together, our analyses demonstrate that NBA-Palm is a useful computational program that provides insights for further experimentation. The accuracy of NBA-Palm is comparable with our previously described tool CSS-Palm. The NBA-Palm is freely accessible from: http://www.bioinfo.tsinghua.edu.cn/NBA-Palm.

On splice site prediction using weight array models: a comparison of smoothing techniques

International Nuclear Information System (INIS)

Taher, Leila; Meinicke, Peter; Morgenstern, Burkhard

2007-01-01

In most eukaryotic genes, protein-coding exons are separated by non-coding introns which are removed from the primary transcript by a process called 'splicing'. The positions where introns are cut and exons are spliced together are called 'splice sites'. Thus, computational prediction of splice sites is crucial for gene finding in eukaryotes. Weight array models are a powerful probabilistic approach to splice site detection. Parameters for these models are usually derived from m-tuple frequencies in trusted training data and subsequently smoothed to avoid zero probabilities. In this study we compare three different ways of parameter estimation for m-tuple frequencies, namely (a) non-smoothed probability estimation, (b) standard pseudo counts and (c) a Gaussian smoothing procedure that we recently developed

Radionuclide migration in groundwater at a low-level waste disposal site: a comparison of predictive performance modeling versus field observations

International Nuclear Information System (INIS)

Robertson, D.E.; Myers, D.A.; Abel, K.H.; Bergeron, M.P.; Champ, D.R.; Killey, R.W.D.; Moltyaner, G.L.; Young, J.L.

1986-01-01

This paper describes a project which is structured to test the concept of modeling a shallow land low-level waste burial site. The project involves a comparison of the actual observed radionuclide migration in groundwaters at a 30-year old well-monitored field site with the results of predictive transport modeling. The comparison is being conducted as a cooperative program with the Atomic Energy of Canada Ltd. (AECL) at the low-level waste management area at the Chalk River Nuclear Laboratories, Ontario, Canada. A joint PNL-AECL field investigation was conducted in 1983 and 1984 to compliment the existing extensive data base on actual radionuclide migration. Predictive transport modeling is currently being conducted for this site; first, as if it were a new location being considered for a low-level waste shallow-land burial site and only minimal information about the site were available, and second, utilizing the extensive data base available for the site. The modeling results will then be compared with the level of effort needed to reasonably predict the spacial and temporal movement of radionuclides in the groundwater environment

Predicted impacts of future water level decline on monitoring wells using a ground-water model of the Hanford Site

International Nuclear Information System (INIS)

Wurstner, S.K.; Freshley, M.D.

1994-12-01

A ground-water flow model was used to predict water level decline in selected wells in the operating areas (100, 200, 300, and 400 Areas) and the 600 Area. To predict future water levels, the unconfined aquifer system was stimulated with the two-dimensional version of a ground-water model of the Hanford Site, which is based on the Coupled Fluid, Energy, and Solute Transport (CFEST) Code in conjunction with the Geographic Information Systems (GIS) software package. The model was developed using the assumption that artificial recharge to the unconfined aquifer system from Site operations was much greater than any natural recharge from precipitation or from the basalt aquifers below. However, artificial recharge is presently decreasing and projected to decrease even more in the future. Wells currently used for monitoring at the Hanford Site are beginning to go dry or are difficult to sample, and as the water table declines over the next 5 to 10 years, a larger number of wells is expected to be impacted. The water levels predicted by the ground-water model were compared with monitoring well completion intervals to determine which wells will become dry in the future. Predictions of wells that will go dry within the next 5 years have less uncertainty than predictions for wells that will become dry within 5 to 10 years. Each prediction is an estimate based on assumed future Hanford Site operating conditions and model assumptions

Prediction of flow and drawdown for the site characterization and validation site in the Stripa Mine

International Nuclear Information System (INIS)

Long, J.C.S.; Mauldon, A.D.; Nelson, K.; Martel, S.; Fuller, P.; and Karasaki, K.

1992-01-01

Geophysical and hydrologic data from a location in the Stripa Mine in Sweden, called the Site Characterization and Validation (SCV) block, has been used to create a series of models for flow through the fracture network. The models can be characterized as ''equivalent discontinuum'' models. Equivalent discontinuum models are derived starting from a specified lattice or 6 ''template''. An inverse analysis called ''Simulated Annealing'' is used to make a random search through the elements of the lattice to find a configuration that can reproduce the measured responses. Evidence at Stripa points to hydrology which is dominated by fracture zones. These have been identified and located through extensive characterization efforts. Lattice templates were arranged to lie on the fracture zones identified by Black and Olsson. The fundamental goal of this project was to build a fracture flow model based an initial data set, and use this model to make predictions of the flow behavior during a new test. Then given data from the new test, predict a second test, etc. The first data set was an interference test called C1-2. Both a two-dimensional and a three-dimensional model were annealed to the C1-2 data and use this model to predict the behavior of the Simulated Drift Experiment (SDE). The SDE measured the flow into, and drawdown due to reducing the pressure in a group of 6 parallel boreholes. Then both the C1-2 and SDE data were used to predict the flow into and drawdown due to an excavation, the Validation Drift (VD), made through the boreholes. Finally, all the data was used to predict the hydrologic response to opening another hole, T1

A novel method for improved accuracy of transcription factor binding site prediction

KAUST Repository

Khamis, Abdullah M.; Motwalli, Olaa Amin; Oliva, Romina; Jankovic, Boris R.; Medvedeva, Yulia; Ashoor, Haitham; Essack, Magbubah; Gao, Xin; Bajic, Vladimir B.

2018-01-01

Identifying transcription factor (TF) binding sites (TFBSs) is important in the computational inference of gene regulation. Widely used computational methods of TFBS prediction based on position weight matrices (PWMs) usually have high false positive rates. Moreover, computational studies of transcription regulation in eukaryotes frequently require numerous PWM models of TFBSs due to a large number of TFs involved. To overcome these problems we developed DRAF, a novel method for TFBS prediction that requires only 14 prediction models for 232 human TFs, while at the same time significantly improves prediction accuracy. DRAF models use more features than PWM models, as they combine information from TFBS sequences and physicochemical properties of TF DNA-binding domains into machine learning models. Evaluation of DRAF on 98 human ChIP-seq datasets shows on average 1.54-, 1.96- and 5.19-fold reduction of false positives at the same sensitivities compared to models from HOCOMOCO, TRANSFAC and DeepBind, respectively. This observation suggests that one can efficiently replace the PWM models for TFBS prediction by a small number of DRAF models that significantly improve prediction accuracy. The DRAF method is implemented in a web tool and in a stand-alone software freely available at http://cbrc.kaust.edu.sa/DRAF.

A novel method for improved accuracy of transcription factor binding site prediction

KAUST Repository

Khamis, Abdullah M.

2018-03-20

Identifying transcription factor (TF) binding sites (TFBSs) is important in the computational inference of gene regulation. Widely used computational methods of TFBS prediction based on position weight matrices (PWMs) usually have high false positive rates. Moreover, computational studies of transcription regulation in eukaryotes frequently require numerous PWM models of TFBSs due to a large number of TFs involved. To overcome these problems we developed DRAF, a novel method for TFBS prediction that requires only 14 prediction models for 232 human TFs, while at the same time significantly improves prediction accuracy. DRAF models use more features than PWM models, as they combine information from TFBS sequences and physicochemical properties of TF DNA-binding domains into machine learning models. Evaluation of DRAF on 98 human ChIP-seq datasets shows on average 1.54-, 1.96- and 5.19-fold reduction of false positives at the same sensitivities compared to models from HOCOMOCO, TRANSFAC and DeepBind, respectively. This observation suggests that one can efficiently replace the PWM models for TFBS prediction by a small number of DRAF models that significantly improve prediction accuracy. The DRAF method is implemented in a web tool and in a stand-alone software freely available at http://cbrc.kaust.edu.sa/DRAF.

Trends of Abutment-Scour Prediction Equations Applied to 144 Field Sites in South Carolina

Science.gov (United States)

Benedict, Stephen T.; Deshpande, Nikhil; Aziz, Nadim M.; Conrads, Paul

2006-01-01

The U.S. Geological Survey conducted a study in cooperation with the Federal Highway Administration in which predicted abutment-scour depths computed with selected predictive equations were compared with field measurements of abutment-scour depth made at 144 bridges in South Carolina. The assessment used five equations published in the Fourth Edition of 'Evaluating Scour at Bridges,' (Hydraulic Engineering Circular 18), including the original Froehlich, the modified Froehlich, the Sturm, the Maryland, and the HIRE equations. An additional unpublished equation also was assessed. Comparisons between predicted and observed scour depths are intended to illustrate general trends and order-of-magnitude differences for the prediction equations. Field measurements were taken during non-flood conditions when the hydraulic conditions that caused the scour generally are unknown. The predicted scour depths are based on hydraulic conditions associated with the 100-year flow at all sites and the flood of record for 35 sites. Comparisons showed that predicted scour depths frequently overpredict observed scour and at times were excessive. The comparison also showed that underprediction occurred, but with less frequency. The performance of these equations indicates that they are poor predictors of abutment-scour depth in South Carolina, and it is probable that poor performance will occur when the equations are applied in other geographic regions. Extensive data and graphs used to compare predicted and observed scour depths in this study were compiled into spreadsheets and are included in digital format with this report. In addition to the equation-comparison data, Water-Surface Profile Model tube-velocity data, soil-boring data, and selected abutment-scour data are included in digital format with this report. The digital database was developed as a resource for future researchers and is especially valuable for evaluating the reasonableness of future equations that may be developed.

Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building.

Science.gov (United States)

Cha, Young-Jin; Trocha, Peter; Büyüköztürk, Oral

2016-07-01

Tall buildings are ubiquitous in major cities and house the homes and workplaces of many individuals. However, relatively few studies have been carried out to study the dynamic characteristics of tall buildings based on field measurements. In this paper, the dynamic behavior of the Green Building, a unique 21-story tall structure located on the campus of the Massachusetts Institute of Technology (MIT, Cambridge, MA, USA), was characterized and modeled as a simplified lumped-mass beam model (SLMM), using data from a network of accelerometers. The accelerometer network was used to record structural responses due to ambient vibrations, blast loading, and the October 16th 2012 earthquake near Hollis Center (ME, USA). Spectral and signal coherence analysis of the collected data was used to identify natural frequencies, modes, foundation rocking behavior, and structural asymmetries. A relation between foundation rocking and structural natural frequencies was also found. Natural frequencies and structural acceleration from the field measurements were compared with those predicted by the SLMM which was updated by inverse solving based on advanced multiobjective optimization methods using the measured structural responses and found to have good agreement.

Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building

Directory of Open Access Journals (Sweden)

Young-Jin Cha

2016-07-01

Full Text Available Tall buildings are ubiquitous in major cities and house the homes and workplaces of many individuals. However, relatively few studies have been carried out to study the dynamic characteristics of tall buildings based on field measurements. In this paper, the dynamic behavior of the Green Building, a unique 21-story tall structure located on the campus of the Massachusetts Institute of Technology (MIT, Cambridge, MA, USA, was characterized and modeled as a simplified lumped-mass beam model (SLMM, using data from a network of accelerometers. The accelerometer network was used to record structural responses due to ambient vibrations, blast loading, and the October 16th 2012 earthquake near Hollis Center (ME, USA. Spectral and signal coherence analysis of the collected data was used to identify natural frequencies, modes, foundation rocking behavior, and structural asymmetries. A relation between foundation rocking and structural natural frequencies was also found. Natural frequencies and structural acceleration from the field measurements were compared with those predicted by the SLMM which was updated by inverse solving based on advanced multiobjective optimization methods using the measured structural responses and found to have good agreement.

Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building

Science.gov (United States)

Cha, Young-Jin; Trocha, Peter; Büyüköztürk, Oral

2016-01-01

Tall buildings are ubiquitous in major cities and house the homes and workplaces of many individuals. However, relatively few studies have been carried out to study the dynamic characteristics of tall buildings based on field measurements. In this paper, the dynamic behavior of the Green Building, a unique 21-story tall structure located on the campus of the Massachusetts Institute of Technology (MIT, Cambridge, MA, USA), was characterized and modeled as a simplified lumped-mass beam model (SLMM), using data from a network of accelerometers. The accelerometer network was used to record structural responses due to ambient vibrations, blast loading, and the October 16th 2012 earthquake near Hollis Center (ME, USA). Spectral and signal coherence analysis of the collected data was used to identify natural frequencies, modes, foundation rocking behavior, and structural asymmetries. A relation between foundation rocking and structural natural frequencies was also found. Natural frequencies and structural acceleration from the field measurements were compared with those predicted by the SLMM which was updated by inverse solving based on advanced multiobjective optimization methods using the measured structural responses and found to have good agreement. PMID:27376303

Using Quantum Confinement to Uniquely Identify Devices

Science.gov (United States)

Roberts, J.; Bagci, I. E.; Zawawi, M. A. M.; Sexton, J.; Hulbert, N.; Noori, Y. J.; Young, M. P.; Woodhead, C. S.; Missous, M.; Migliorato, M. A.; Roedig, U.; Young, R. J.

2015-11-01

Modern technology unintentionally provides resources that enable the trust of everyday interactions to be undermined. Some authentication schemes address this issue using devices that give a unique output in response to a challenge. These signatures are generated by hard-to-predict physical responses derived from structural characteristics, which lend themselves to two different architectures, known as unique objects (UNOs) and physically unclonable functions (PUFs). The classical design of UNOs and PUFs limits their size and, in some cases, their security. Here we show that quantum confinement lends itself to the provision of unique identities at the nanoscale, by using fluctuations in tunnelling measurements through quantum wells in resonant tunnelling diodes (RTDs). This provides an uncomplicated measurement of identity without conventional resource limitations whilst providing robust security. The confined energy levels are highly sensitive to the specific nanostructure within each RTD, resulting in a distinct tunnelling spectrum for every device, as they contain a unique and unpredictable structure that is presently impossible to clone. This new class of authentication device operates with minimal resources in simple electronic structures above room temperature.

Radionuclide migration in groundwater at a low-level waste disposal site: a comparison of predictive performance modeling versus field observations

International Nuclear Information System (INIS)

Robertson, D.E.; Myers, D.A.; Bergeron, M.P.; Champ, D.R.; Killey, R.W.D.; Moltyaner, G.L.; Young, J.L.

1985-08-01

This paper describes a project which is structured to test the concept of modeling a shallow land low-level waste burial site. The project involves a comparison of the actual observed radionuclide migration in groundwaters at a 30-year-old well-monitored field site with the results of predictive transport modeling. The comparison is being conducted as a cooperative program with the Atomic Energy of Canada Ltd. (AECL) at the low-level waste management area at the Chalk River Nuclear Laboratories, Ontario, Canada. A joint PNL-AECL field inviestigation was conducted in 1983 and 1984 to complement the existing extensive data base on actual radionuclide migration. Predictive transport modeling is currently being conducted for this site; first, as if it were a new location being considered for a low-level waste shallow-land burial site and only minimal information about the site were available, and second, utilizing the extensive data base available for the site. The modeling results will then be compared with the empirical observations to provide insight into the level of effort needed to reasonably predict the spacial and temporal movement of radionuclides in the groundwater enviroment. 8 refs., 5 figs.,

Predicting internalizing problems in Chinese children: the unique and interactive effects of parenting and child temperament.

Science.gov (United States)

Muhtadie, Luma; Zhou, Qing; Eisenberg, Nancy; Wang, Yun

2013-08-01

The additive and interactive relations of parenting styles (authoritative and authoritarian parenting) and child temperament (anger/frustration, sadness, and effortful control) to children's internalizing problems were examined in a 3.8-year longitudinal study of 425 Chinese children (aged 6-9 years) from Beijing. At Wave 1, parents self-reported on their parenting styles, and parents and teachers rated child temperament. At Wave 2, parents, teachers, and children rated children's internalizing problems. Structural equation modeling indicated that the main effect of authoritative parenting and the interactions of Authoritarian Parenting × Effortful Control and Authoritative Parenting × Anger/Frustration (parents' reports only) prospectively and uniquely predicted internalizing problems. The above results did not vary by child sex and remained significant after controlling for co-occurring externalizing problems. These findings suggest that (a) children with low effortful control may be particularly susceptible to the adverse effect of authoritarian parenting and (b) the benefit of authoritative parenting may be especially important for children with high anger/frustration.

Bayesian Poisson hierarchical models for crash data analysis: Investigating the impact of model choice on site-specific predictions.

Science.gov (United States)

Khazraee, S Hadi; Johnson, Valen; Lord, Dominique

2018-08-01

The Poisson-gamma (PG) and Poisson-lognormal (PLN) regression models are among the most popular means for motor vehicle crash data analysis. Both models belong to the Poisson-hierarchical family of models. While numerous studies have compared the overall performance of alternative Bayesian Poisson-hierarchical models, little research has addressed the impact of model choice on the expected crash frequency prediction at individual sites. This paper sought to examine whether there are any trends among candidate models predictions e.g., that an alternative model's prediction for sites with certain conditions tends to be higher (or lower) than that from another model. In addition to the PG and PLN models, this research formulated a new member of the Poisson-hierarchical family of models: the Poisson-inverse gamma (PIGam). Three field datasets (from Texas, Michigan and Indiana) covering a wide range of over-dispersion characteristics were selected for analysis. This study demonstrated that the model choice can be critical when the calibrated models are used for prediction at new sites, especially when the data are highly over-dispersed. For all three datasets, the PIGam model would predict higher expected crash frequencies than would the PLN and PG models, in order, indicating a clear link between the models predictions and the shape of their mixing distributions (i.e., gamma, lognormal, and inverse gamma, respectively). The thicker tail of the PIGam and PLN models (in order) may provide an advantage when the data are highly over-dispersed. The analysis results also illustrated a major deficiency of the Deviance Information Criterion (DIC) in comparing the goodness-of-fit of hierarchical models; models with drastically different set of coefficients (and thus predictions for new sites) may yield similar DIC values, because the DIC only accounts for the parameters in the lowest (observation) level of the hierarchy and ignores the higher levels (regression coefficients

Determination of the strain generated in InAs/InP quantum wires: prediction of nucleation sites

International Nuclear Information System (INIS)

Molina, S I; Ben, T; Sales, D L; Pizarro, J; Galindo, P L; Varela, M; Pennycook, S J; Fuster, D; Gonzalez, Y; Gonzalez, L

2006-01-01

The compositional distribution in a self-assembled InAs(P) quantum wire grown by molecular beam epitaxy on an InP(001) substrate has been determined by electron energy loss spectrum imaging. We have determined the strain and stress fields generated in and around this wire capped with a 5 nm InP layer by finite element calculations using as input the compositional map experimentally obtained. Preferential sites for nucleation of wires grown on the surface of this InP capping layer are predicted, based on chemical potential minimization, from the determined strain and stress fields on this surface. The determined preferential sites for wire nucleation agree with their experimentally measured locations. The method used in this paper, which combines electron energy loss spectroscopy, high-resolution Z contrast imaging, and elastic theory finite element calculations, is believed to be a valuable technique of wide applicability for predicting the preferential nucleation sites of epitaxial self-assembled nano-objects

Determination of the strain generated in InAs/InP quantum wires: prediction of nucleation sites

Energy Technology Data Exchange (ETDEWEB)

Molina, S I [Departamento de Ciencia de los Materiales e I.M. y Q.I., Facultad de Ciencias, Universidad de Cadiz, Campus RIo San Pedro, s/n, 11510 Puerto Real, Cadiz (Spain); Ben, T [Departamento de Ciencia de los Materiales e I.M. y Q.I., Facultad de Ciencias, Universidad de Cadiz, Campus RIo San Pedro, s/n, 11510 Puerto Real, Cadiz (Spain); Sales, D L [Departamento de Ciencia de los Materiales e I.M. y Q.I., Facultad de Ciencias, Universidad de Cadiz, Campus RIo San Pedro, s/n, 11510 Puerto Real, Cadiz (Spain); Pizarro, J [Departamento de Lenguajes y Sistemas Informaticos, CASEM, Universidad de Cadiz, Campus RIo San Pedro, s/n, 11510 Puerto Real, Cadiz (Spain); Galindo, P L [Departamento de Lenguajes y Sistemas Informaticos, CASEM, Universidad de Cadiz, Campus RIo San Pedro, s/n, 11510 Puerto Real, Cadiz (Spain); Varela, M [Condensed Matter Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Pennycook, S J [Condensed Matter Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Fuster, D [Instituto de Microelectronica de Madrid (CNM, CSIC), Isaac Newton 8, 28760 Tres Cantos, Madrid (Spain); Gonzalez, Y [Instituto de Microelectronica de Madrid (CNM, CSIC), Isaac Newton 8, 28760 Tres Cantos, Madrid (Spain); Gonzalez, L [Instituto de Microelectronica de Madrid (CNM, CSIC), Isaac Newton 8, 28760 Tres Cantos, Madrid (Spain)

2006-11-28

The compositional distribution in a self-assembled InAs(P) quantum wire grown by molecular beam epitaxy on an InP(001) substrate has been determined by electron energy loss spectrum imaging. We have determined the strain and stress fields generated in and around this wire capped with a 5 nm InP layer by finite element calculations using as input the compositional map experimentally obtained. Preferential sites for nucleation of wires grown on the surface of this InP capping layer are predicted, based on chemical potential minimization, from the determined strain and stress fields on this surface. The determined preferential sites for wire nucleation agree with their experimentally measured locations. The method used in this paper, which combines electron energy loss spectroscopy, high-resolution Z contrast imaging, and elastic theory finite element calculations, is believed to be a valuable technique of wide applicability for predicting the preferential nucleation sites of epitaxial self-assembled nano-objects.

Prediction of the thermohydraulic performance of porous-media reservoirs for compressed-air energy storage

Energy Technology Data Exchange (ETDEWEB)

Wiles, L.E.; McCann, R.A.

1981-09-01

The numerical modeling capability that has been developed at the Pacific Northwest Laboratory (PNL) for the prediction of the thermohydraulic performance of porous media reservoirs for compressed air energy storage (CAES) is described. The capability of the numerical models was demonstrated by application to a variety of parametric analyses and the support analyses for the CAES porous media field demonstration program. The demonstration site analyses include calculations for the displacement of aquifer water to develop the air storage zone, the potential for water coning, thermal development in the reservoir, and the dehydration of the near-wellbore region. Unique features of the demonstration site reservoir that affect the thermohydraulic performance are identified and contrasted against the predicted performance for conditions that would be considered more typical of a commercial CAES site.

Neural network model for the prediction of PM10 daily concentrations in two sites in the Western Mediterranean.

Science.gov (United States)

de Gennaro, Gianluigi; Trizio, Livia; Di Gilio, Alessia; Pey, Jorge; Pérez, Noemi; Cusack, Michael; Alastuey, Andrés; Querol, Xavier

2013-10-01

An artificial neural network (ANN) was developed and tested to forecast PM10 daily concentration in two contrasted environments in NE Spain, a regional background site (Montseny), and an urban background site (Barcelona-CSIC), which was highly influenced by vehicular emissions. In order to predict 24-h average PM10 concentrations, the artificial neural network previously developed by Caselli et al. (2009) was improved by using hourly PM concentrations and deterministic factors such as a Saharan dust alert. In particular, the model input data for prediction were the hourly PM10 concentrations 1-day in advance, local meteorological data and information about air masses origin. The forecasted performance indexes for both sites were calculated and they showed better results for the regional background site in Montseny (R(2)=0.86, SI=0.75) than for urban site in Barcelona (R(2)=0.73, SI=0.58), influenced by local and sometimes unexpected sources. Moreover, a sensitivity analysis conducted to understand the importance of the different variables included among the input data, showed that local meteorology and air masses origin are key factors in the model forecasts. This result explains the reason for the improvement of ANN's forecasting performance at the Montseny site with respect to the Barcelona site. Moreover, the artificial neural network developed in this work could prove useful to predict PM10 concentrations, especially, at regional background sites such as those on the Mediterranean Basin which are primarily affected by long-range transports. Hence, the artificial neural network presented here could be a powerful tool for obtaining real time information on air quality status and could aid stakeholders in their development of cost-effective control strategies. © 2013 Elsevier B.V. All rights reserved.

GPS 2.1: enhanced prediction of kinase-specific phosphorylation sites with an algorithm of motif length selection.

Science.gov (United States)

Xue, Yu; Liu, Zexian; Cao, Jun; Ma, Qian; Gao, Xinjiao; Wang, Qingqi; Jin, Changjiang; Zhou, Yanhong; Wen, Longping; Ren, Jian

2011-03-01

As the most important post-translational modification of proteins, phosphorylation plays essential roles in all aspects of biological processes. Besides experimental approaches, computational prediction of phosphorylated proteins with their kinase-specific phosphorylation sites has also emerged as a popular strategy, for its low-cost, fast-speed and convenience. In this work, we developed a kinase-specific phosphorylation sites predictor of GPS 2.1 (Group-based Prediction System), with a novel but simple approach of motif length selection (MLS). By this approach, the robustness of the prediction system was greatly improved. All algorithms in GPS old versions were also reserved and integrated in GPS 2.1. The online service and local packages of GPS 2.1 were implemented in JAVA 1.5 (J2SE 5.0) and freely available for academic researches at: http://gps.biocuckoo.org.

Computer simulations of rare earth sites in glass: experimental tests and applications to laser materials

International Nuclear Information System (INIS)

Weber, M.J.

1984-11-01

Computer simulations of the microscopic structure of BeF 2 glasses using molecular dynamics are reviewed and compared with x-ray and neutron diffraction, EXAFS, NMR, and optical measurements. Unique information about the site-to-site variations in the local environments of rare earth ions is obtained using optical selective excitation and laser-induced fluorescence line-narrowing techniques. Applications and limitations of computer simulations to the development of laser glasses and to predictions of other static and dynamic properties of glasses are discussed. 35 references, 2 figures, 2 tables

Unique associations among emotion dysregulation dimensions and aggressive tendencies : A multi-site study

NARCIS (Netherlands)

Velotti, Patrizia; Casselman, Robert B.; Garofalo, C.; McKenzie, Melissa D.

2017-01-01

While problems with emotion regulation (ER) have long been associated with internalizing symptoms, only recently has an ER framework been applied to the study of aggression. Therefore, little is known about the unique and independent associations between specific domains of the ER construct and

Implications of next generation attenuation ground motion prediction equations for site coefficients used in earthquake resistant design

Science.gov (United States)

Borcherdt, Roger D.

2014-01-01

Proposals are developed to update Tables 11.4-1 and 11.4-2 of Minimum Design Loads for Buildings and Other Structures published as American Society of Civil Engineers Structural Engineering Institute standard 7-10 (ASCE/SEI 7–10). The updates are mean next generation attenuation (NGA) site coefficients inferred directly from the four NGA ground motion prediction equations used to derive the maximum considered earthquake response maps adopted in ASCE/SEI 7–10. Proposals include the recommendation to use straight-line interpolation to infer site coefficients at intermediate values of (average shear velocity to 30-m depth). The NGA coefficients are shown to agree well with adopted site coefficients at low levels of input motion (0.1 g) and those observed from the Loma Prieta earthquake. For higher levels of input motion, the majority of the adopted values are within the 95% epistemic-uncertainty limits implied by the NGA estimates with the exceptions being the mid-period site coefficient, Fv, for site class D and the short-period coefficient, Fa, for site class C, both of which are slightly less than the corresponding 95% limit. The NGA data base shows that the median value  of 913 m/s for site class B is more typical than 760 m/s as a value to characterize firm to hard rock sites as the uniform ground condition for future maximum considered earthquake response ground motion estimates. Future updates of NGA ground motion prediction equations can be incorporated easily into future adjustments of adopted site coefficients using procedures presented herein. 

Networking for philanthropy: increasing volunteer behavior via social networking sites.

Science.gov (United States)

Kim, Yoojung; Lee, Wei-Na

2014-03-01

Social networking sites (SNSs) provide a unique social venue to engage the young generation in philanthropy through their networking capabilities. An integrated model that incorporates social capital into the Theory of Reasoned Action is developed to explain volunteer behavior through social networks. As expected, volunteer behavior was predicted by volunteer intention, which was influenced by attitudes and subjective norms. In addition, social capital, an outcome of the extensive use of SNSs, was as an important driver of users' attitude and subjective norms toward volunteering via SNSs.

Plutonium uniqueness

International Nuclear Information System (INIS)

Silver, G.L.

1984-01-01

A standard is suggested against which the putative uniqueness of plutonium may be tested. It is common folklore that plutonium is unique among the chemical elements because its four common oxidation states can coexist in the same solution. Whether this putative uniqueness appears only during transit to equilibrium, or only at equilibrium, or all of the time, is not generally made clear. But while the folklore may contain some truth, it cannot be put to test until some measure of 'uniqueness' is agreed upon so that quantitative comparisons are possible. One way of measuring uniqueness is as the magnitude of the product of the mole fractions of the element at equilibrium. A 'coexistence index' is defined and discussed. (author)

Utilizing knowledge base of amino acids structural neighborhoods to predict protein-protein interaction sites.

Science.gov (United States)

Jelínek, Jan; Škoda, Petr; Hoksza, David

2017-12-06

Protein-protein interactions (PPI) play a key role in an investigation of various biochemical processes, and their identification is thus of great importance. Although computational prediction of which amino acids take part in a PPI has been an active field of research for some time, the quality of in-silico methods is still far from perfect. We have developed a novel prediction method called INSPiRE which benefits from a knowledge base built from data available in Protein Data Bank. All proteins involved in PPIs were converted into labeled graphs with nodes corresponding to amino acids and edges to pairs of neighboring amino acids. A structural neighborhood of each node was then encoded into a bit string and stored in the knowledge base. When predicting PPIs, INSPiRE labels amino acids of unknown proteins as interface or non-interface based on how often their structural neighborhood appears as interface or non-interface in the knowledge base. We evaluated INSPiRE's behavior with respect to different types and sizes of the structural neighborhood. Furthermore, we examined the suitability of several different features for labeling the nodes. Our evaluations showed that INSPiRE clearly outperforms existing methods with respect to Matthews correlation coefficient. In this paper we introduce a new knowledge-based method for identification of protein-protein interaction sites called INSPiRE. Its knowledge base utilizes structural patterns of known interaction sites in the Protein Data Bank which are then used for PPI prediction. Extensive experiments on several well-established datasets show that INSPiRE significantly surpasses existing PPI approaches.

Retirement investment theory explains patterns in songbird nest-site choice

Science.gov (United States)

Streby, Henry M.; Refsnider, Jeanine M.; Peterson, Sean M.; Andersen, David E.

2014-01-01

When opposing evolutionary selection pressures act on a behavioural trait, the result is often stabilizing selection for an intermediate optimal phenotype, with deviations from the predicted optimum attributed to tracking a moving target, development of behavioural syndromes or shifts in riskiness over an individual's lifetime. We investigated nest-site choice by female golden-winged warblers, and the selection pressures acting on that choice by two fitness components, nest success and fledgling survival. We observed strong and consistent opposing selection pressures on nest-site choice for maximizing these two fitness components, and an abrupt, within-season switch in the fitness component birds prioritize via nest-site choice, dependent on the time remaining for additional nesting attempts. We found that females consistently deviated from the predicted optimal behaviour when choosing nest sites because they can make multiple attempts at one fitness component, nest success, but only one attempt at the subsequent component, fledgling survival. Our results demonstrate a unique natural strategy for balancing opposing selection pressures to maximize total fitness. This time-dependent switch from high to low risk tolerance in nest-site choice maximizes songbird fitness in the same way a well-timed switch in human investor risk tolerance can maximize one's nest egg at retirement. Our results also provide strong evidence for the adaptive nature of songbird nest-site choice, which we suggest has been elusive primarily due to a lack of consideration for fledgling survival.

Site decontamination

International Nuclear Information System (INIS)

Bicker, A.E.

1981-01-01

Among the several DOE sites that have been radiologically decontaminated under the auspices of the Nevada Operations Office are three whose physical characteristics are unique. These are the Tatum Dome Test Site (TDTS) near Hattiesburg, Mississippi; a location of mountainous terrain (Pahute Mesa) on the Nevada Test Site; and the GNOME site near Carlsbad, New Mexico. In each case the contamination, the terrain, and the climate conditions were different. This presentation includes a brief description of each site, the methods used to perform radiological surveys, the logistics required to support the decontamination (including health physics and sample analysis), and the specific techniques used to reduce or remove the contamination

Conserved Functional Motifs and Homology Modeling to Predict Hidden Moonlighting Functional Sites

KAUST Repository

Wong, Aloysius Tze

2015-06-09

Moonlighting functional centers within proteins can provide them with hitherto unrecognized functions. Here, we review how hidden moonlighting functional centers, which we define as binding sites that have catalytic activity or regulate protein function in a novel manner, can be identified using targeted bioinformatic searches. Functional motifs used in such searches include amino acid residues that are conserved across species and many of which have been assigned functional roles based on experimental evidence. Molecules that were identified in this manner seeking cyclic mononucleotide cyclases in plants are used as examples. The strength of this computational approach is enhanced when good homology models can be developed to test the functionality of the predicted centers in silico, which, in turn, increases confidence in the ability of the identified candidates to perform the predicted functions. Computational characterization of moonlighting functional centers is not diagnostic for catalysis but serves as a rapid screening method, and highlights testable targets from a potentially large pool of candidates for subsequent in vitro and in vivo experiments required to confirm the functionality of the predicted moonlighting centers.

Conserved Functional Motifs and Homology Modeling to Predict Hidden Moonlighting Functional Sites

KAUST Repository

Wong, Aloysius Tze; Gehring, Christoph A; Irving, Helen R.

2015-01-01

Moonlighting functional centers within proteins can provide them with hitherto unrecognized functions. Here, we review how hidden moonlighting functional centers, which we define as binding sites that have catalytic activity or regulate protein function in a novel manner, can be identified using targeted bioinformatic searches. Functional motifs used in such searches include amino acid residues that are conserved across species and many of which have been assigned functional roles based on experimental evidence. Molecules that were identified in this manner seeking cyclic mononucleotide cyclases in plants are used as examples. The strength of this computational approach is enhanced when good homology models can be developed to test the functionality of the predicted centers in silico, which, in turn, increases confidence in the ability of the identified candidates to perform the predicted functions. Computational characterization of moonlighting functional centers is not diagnostic for catalysis but serves as a rapid screening method, and highlights testable targets from a potentially large pool of candidates for subsequent in vitro and in vivo experiments required to confirm the functionality of the predicted moonlighting centers.

Predicting Flavin and Nicotinamide Adenine Dinucleotide-Binding Sites in Proteins Using the Fragment Transformation Method

Directory of Open Access Journals (Sweden)

Chih-Hao Lu

2015-01-01

Full Text Available We developed a computational method to identify NAD- and FAD-binding sites in proteins. First, we extracted from the Protein Data Bank structures of proteins that bind to at least one of these ligands. NAD-/FAD-binding residue templates were then constructed by identifying binding residues through the ligand-binding database BioLiP. The fragment transformation method was used to identify structures within query proteins that resembled the ligand-binding templates. By comparing residue types and their relative spatial positions, potential binding sites were identified and a ligand-binding potential for each residue was calculated. Setting the false positive rate at 5%, our method predicted NAD- and FAD-binding sites at true positive rates of 67.1% and 68.4%, respectively. Our method provides excellent results for identifying FAD- and NAD-binding sites in proteins, and the most important is that the requirement of conservation of residue types and local structures in the FAD- and NAD-binding sites can be verified.

Predictability of bone density at posterior mandibular implant sites using cone-beam computed tomography intensity values

OpenAIRE

Alkhader, Mustafa; Hudieb, Malik; Khader, Yousef

2017-01-01

Objective: The aim of this study was to investigate the predictability of bone density at posterior mandibular implant sites using cone-beam computed tomography (CBCT) intensity values. Materials and Methods: CBCT cross-sectional images for 436 posterior mandibular implant sites were selected for the study. Using Invivo software (Anatomage, San Jose, California, USA), two observers classified the bone density into three categories: low, intermediate, and high, and CBCT intensity values were g...

Predicting Internalizing Problems in Chinese Children: the Unique and Interactive Effects of Parenting and Child Temperament

Science.gov (United States)

Muhtadie, Luma; Zhou, Qing; Eisenberg, Nancy; Wang, Yun

2012-01-01

The additive and interactive relations of parenting styles (authoritative and authoritarian parenting) and child temperament (anger/frustration, sadness, and effortful control) to children’s internalizing problems were examined in a 3.8-year longitudinal study of 425 Chinese children (6 – 9 years) from Beijing. At Wave 1, parents self-reported on their parenting styles, and parents and teachers rated child temperament. At Wave 2, parents, teachers, and children rated children’s internalizing problems. Structural equation modeling indicated that the main effect of authoritative parenting, and the interactions of authoritarian parenting × effortful control and authoritative parenting × anger/frustration (parents’ reports only) prospectively and uniquely predicted internalizing problems. The above results did not vary by child sex and remained significant after controlling for co-occurring externalizing problems. These findings suggest that: a) children with low effortful control may be particularly susceptible to the adverse effect of authoritarian parenting, and b) the benefit of authoritative parenting may be especially important for children with high anger/frustration. PMID:23880383

Work characteristics predict the development of multi-site musculoskeletal pain.

Science.gov (United States)

Oakman, Jodi; de Wind, Astrid; van den Heuvel, Swenne G; van der Beek, Allard J

2017-10-01

Musculoskeletal pain in more than one body region is common and a barrier to sustaining employment. We aimed to examine whether work characteristics predict the development of multi-site pain (MSP), and to determine differences in work-related predictors between age groups. This study is based on 5136 employees from the Study on Transitions in Employment, Ability and Motivation (STREAM) who reported no MSP at baseline. Measures included physical, emotional, mental, and psychological job demands, social support and autonomy. Predictors of MSP were studied by logistic regression analyses. Univariate and multivariate analyses with age stratification (45-49, 50-54, 55-59, and 60-64 years) were done to explore differences between age groups. All work characteristics with the exception of autonomy were predictive of the development of MSP, with odds ratios varying from 1.21 (95% CI 1.04-1.40) for mental job demands to 1.63 (95% CI 1.43-1.86) for physical job demands. No clear pattern of age-related differences in the predictors of MSP emerged, with the exception of social support, which was predictive of MSP developing in all age groups except for the age group 60-64 years. Adverse physical and psychosocial work characteristics are associated with MSP. Organisations need to comprehensively assess work environments to ensure that all relevant workplace hazards, physical and psychosocial, are identified and then controlled for across all age groups.

Prediction of functional sites in proteins using conserved functional group analysis.

Science.gov (United States)

Innis, C Axel; Anand, A Prem; Sowdhamini, R

2004-04-02

A detailed knowledge of a protein's functional site is an absolute prerequisite for understanding its mode of action at the molecular level. However, the rapid pace at which sequence and structural information is being accumulated for proteins greatly exceeds our ability to determine their biochemical roles experimentally. As a result, computational methods are required which allow for the efficient processing of the evolutionary information contained in this wealth of data, in particular that related to the nature and location of functionally important sites and residues. The method presented here, referred to as conserved functional group (CFG) analysis, relies on a simplified representation of the chemical groups found in amino acid side-chains to identify functional sites from a single protein structure and a number of its sequence homologues. We show that CFG analysis can fully or partially predict the location of functional sites in approximately 96% of the 470 cases tested and that, unlike other methods available, it is able to tolerate wide variations in sequence identity. In addition, we discuss its potential in a structural genomics context, where automation, scalability and efficiency are critical, and an increasing number of protein structures are determined with no prior knowledge of function. This is exemplified by our analysis of the hypothetical protein Ydde_Ecoli, whose structure was recently solved by members of the North East Structural Genomics consortium. Although the proposed active site for this protein needs to be validated experimentally, this example illustrates the scope of CFG analysis as a general tool for the identification of residues likely to play an important role in a protein's biochemical function. Thus, our method offers a convenient solution to rapidly and automatically process the vast amounts of data that are beginning to emerge from structural genomics projects.

An integrative computational framework based on a two-step random forest algorithm improves prediction of zinc-binding sites in proteins.

Directory of Open Access Journals (Sweden)

Cheng Zheng

Full Text Available Zinc-binding proteins are the most abundant metalloproteins in the Protein Data Bank where the zinc ions usually have catalytic, regulatory or structural roles critical for the function of the protein. Accurate prediction of zinc-binding sites is not only useful for the inference of protein function but also important for the prediction of 3D structure. Here, we present a new integrative framework that combines multiple sequence and structural properties and graph-theoretic network features, followed by an efficient feature selection to improve prediction of zinc-binding sites. We investigate what information can be retrieved from the sequence, structure and network levels that is relevant to zinc-binding site prediction. We perform a two-step feature selection using random forest to remove redundant features and quantify the relative importance of the retrieved features. Benchmarking on a high-quality structural dataset containing 1,103 protein chains and 484 zinc-binding residues, our method achieved >80% recall at a precision of 75% for the zinc-binding residues Cys, His, Glu and Asp on 5-fold cross-validation tests, which is a 10%-28% higher recall at the 75% equal precision compared to SitePredict and zincfinder at residue level using the same dataset. The independent test also indicates that our method has achieved recall of 0.790 and 0.759 at residue and protein levels, respectively, which is a performance better than the other two methods. Moreover, AUC (the Area Under the Curve and AURPC (the Area Under the Recall-Precision Curve by our method are also respectively better than those of the other two methods. Our method can not only be applied to large-scale identification of zinc-binding sites when structural information of the target is available, but also give valuable insights into important features arising from different levels that collectively characterize the zinc-binding sites. The scripts and datasets are available at http://protein.cau.edu.cn/zincidentifier/.

[Prediction of 137Cs accumulation in animal products in the territory of Semipalatinsk test site].

Science.gov (United States)

Spiridonov, S I; Gontarenko, I A; Mukusheva, M K; Fesenko, S V; Semioshkina, N A

2005-01-01

The paper describes mathematical models for 137Cs behavior in the organism of horses and sheep pasturing on the bording area to the testing area "Ground Zero" of the Semipalatinsk Test Site. The models are parameterized on the base of the data from an experiment with the breeds of animals now commonly encountered within the Semipalatinsk Test Site. The predictive calculations with the models devised have shown that 137Cs concentrations in milk of horses and sheep pasturingon the testing area to "Ground Zero" can exceed the adopted standards during a long period of time.

Rapid and accurate prediction and scoring of water molecules in protein binding sites.

Directory of Open Access Journals (Sweden)

Gregory A Ross

Full Text Available Water plays a critical role in ligand-protein interactions. However, it is still challenging to predict accurately not only where water molecules prefer to bind, but also which of those water molecules might be displaceable. The latter is often seen as a route to optimizing affinity of potential drug candidates. Using a protocol we call WaterDock, we show that the freely available AutoDock Vina tool can be used to predict accurately the binding sites of water molecules. WaterDock was validated using data from X-ray crystallography, neutron diffraction and molecular dynamics simulations and correctly predicted 97% of the water molecules in the test set. In addition, we combined data-mining, heuristic and machine learning techniques to develop probabilistic water molecule classifiers. When applied to WaterDock predictions in the Astex Diverse Set of protein ligand complexes, we could identify whether a water molecule was conserved or displaced to an accuracy of 75%. A second model predicted whether water molecules were displaced by polar groups or by non-polar groups to an accuracy of 80%. These results should prove useful for anyone wishing to undertake rational design of new compounds where the displacement of water molecules is being considered as a route to improved affinity.

Sequence-based prediction of protein-binding sites in DNA: comparative study of two SVM models.

Science.gov (United States)

Park, Byungkyu; Im, Jinyong; Tuvshinjargal, Narankhuu; Lee, Wook; Han, Kyungsook

2014-11-01

As many structures of protein-DNA complexes have been known in the past years, several computational methods have been developed to predict DNA-binding sites in proteins. However, its inverse problem (i.e., predicting protein-binding sites in DNA) has received much less attention. One of the reasons is that the differences between the interaction propensities of nucleotides are much smaller than those between amino acids. Another reason is that DNA exhibits less diverse sequence patterns than protein. Therefore, predicting protein-binding DNA nucleotides is much harder than predicting DNA-binding amino acids. We computed the interaction propensity (IP) of nucleotide triplets with amino acids using an extensive dataset of protein-DNA complexes, and developed two support vector machine (SVM) models that predict protein-binding nucleotides from sequence data alone. One SVM model predicts protein-binding nucleotides using DNA sequence data alone, and the other SVM model predicts protein-binding nucleotides using both DNA and protein sequences. In a 10-fold cross-validation with 1519 DNA sequences, the SVM model that uses DNA sequence data only predicted protein-binding nucleotides with an accuracy of 67.0%, an F-measure of 67.1%, and a Matthews correlation coefficient (MCC) of 0.340. With an independent dataset of 181 DNAs that were not used in training, it achieved an accuracy of 66.2%, an F-measure 66.3% and a MCC of 0.324. Another SVM model that uses both DNA and protein sequences achieved an accuracy of 69.6%, an F-measure of 69.6%, and a MCC of 0.383 in a 10-fold cross-validation with 1519 DNA sequences and 859 protein sequences. With an independent dataset of 181 DNAs and 143 proteins, it showed an accuracy of 67.3%, an F-measure of 66.5% and a MCC of 0.329. Both in cross-validation and independent testing, the second SVM model that used both DNA and protein sequence data showed better performance than the first model that used DNA sequence data. To the best of

Protein docking prediction using predicted protein-protein interface

Directory of Open Access Journals (Sweden)

Li Bin

2012-01-01

Full Text Available Abstract Background Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations. Results We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm, is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering. Conclusion We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.

Protein docking prediction using predicted protein-protein interface.

Science.gov (United States)

Li, Bin; Kihara, Daisuke

2012-01-10

Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations. We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm), is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering. We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.

Evaluation of the DayCent model to predict carbon fluxes in French crop sites

Science.gov (United States)

Fujisaki, Kenji; Martin, Manuel P.; Zhang, Yao; Bernoux, Martial; Chapuis-Lardy, Lydie

2017-04-01

Croplands in temperate regions are an important component of the carbon balance and can act as a sink or a source of carbon, depending on pedoclimatic conditions and management practices. Therefore the evaluation of carbon fluxes in croplands by modelling approach is relevant in the context of global change. This study was part of the Comete-Global project funded by the multi-Partner call FACCE JPI. Carbon fluxes, net ecosystem exchange (NEE), leaf area index (LAI), biomass, and grain production were simulated at the site level in three French crop experiments from the CarboEurope project. Several crops were studied, like winter wheat, rapeseed, barley, maize, and sunflower. Daily NEE was measured with eddy covariance and could be partitioned between gross primary production (GPP) and total ecosystem respiration (TER). Measurements were compared to DayCent simulations, a process-based model predicting plant production and soil organic matter turnover at daily time step. We compared two versions of the model: the original one with a simplified plant module and a newer version that simulates LAI. Input data for modelling were soil properties, climate, and management practices. Simulations of grain yields and biomass production were acceptable when using optimized crop parameters. Simulation of NEE was also acceptable. GPP predictions were improved with the newer version of the model, eliminating temporal shifts that could be observed with the original model. TER was underestimated by the model. Predicted NEE was more sensitive to soil tillage and nitrogen applications than measured NEE. DayCent was therefore a relevant tool to predict carbon fluxes in French crops at the site level. The introduction of LAI in the model improved its performance.

A Generic Multi-Compartmental CNS Distribution Model Structure for 9 Drugs Allows Prediction of Human Brain Target Site Concentrations

NARCIS (Netherlands)

Yamamoto, Yumi; Valitalo, Pyry A.; van den Berg, Dirk-Jan; Hartman, Robin; van den Brink, Willem; Wong, Yin Cheong; Huntjens, Dymphy R.; Proost, Johannes H.; Vermeulen, An; Krauwinkel, Walter; Bakshi, Suruchi; Aranzana-Climent, Vincent; Marchand, Sandrine; Dahyot-Fizelier, Claire; Couet, William; Danhof, Meindert; van Hasselt, Johan G. C.; de lange, Elizabeth C. M.

Purpose Predicting target site drug concentration in the brain is of key importance for the successful development of drugs acting on the central nervous system. We propose a generic mathematical model to describe the pharmacokinetics in brain compartments, and apply this model to predict human

Imbalanced multi-modal multi-label learning for subcellular localization prediction of human proteins with both single and multiple sites.

Directory of Open Access Journals (Sweden)

Jianjun He

Full Text Available It is well known that an important step toward understanding the functions of a protein is to determine its subcellular location. Although numerous prediction algorithms have been developed, most of them typically focused on the proteins with only one location. In recent years, researchers have begun to pay attention to the subcellular localization prediction of the proteins with multiple sites. However, almost all the existing approaches have failed to take into account the correlations among the locations caused by the proteins with multiple sites, which may be the important information for improving the prediction accuracy of the proteins with multiple sites. In this paper, a new algorithm which can effectively exploit the correlations among the locations is proposed by using gaussian process model. Besides, the algorithm also can realize optimal linear combination of various feature extraction technologies and could be robust to the imbalanced data set. Experimental results on a human protein data set show that the proposed algorithm is valid and can achieve better performance than the existing approaches.

Unique contributions of emotion regulation and executive functions in predicting the quality of parent-child interaction behaviors.

Science.gov (United States)

Shaffer, Anne; Obradović, Jelena

2017-03-01

Parenting is a cognitive, emotional, and behavioral endeavor, yet limited research investigates parents' executive functions and emotion regulation as predictors of how parents interact with their children. The current study is a multimethod investigation of parental self-regulation in relation to the quality of parenting behavior and parent-child interactions in a diverse sample of parents and kindergarten-age children. Using path analyses, we tested how parent executive functions (inhibitory control) and lack of emotion regulation strategies uniquely relate to both sensitive/responsive behaviors and positive/collaborative behaviors during observed interaction tasks. In our analyses, we accounted for parent education, financial stress, and social support as socioeconomic factors that likely relate to parent executive function and emotion regulation skills. In a diverse sample of primary caregivers (N = 102), we found that direct assessment of parent inhibitory control was positively associated with sensitive/responsive behaviors, whereas parent self-reported difficulties in using emotion regulation strategies were associated with lower levels of positive and collaborative dyadic behaviors. Parent education and financial stress predicted inhibitory control, and social support predicted emotion regulation difficulties; parent education was also a significant predictor of sensitive/responsive behaviors. Greater inhibitory control skills and fewer difficulties identifying effective emotion regulation strategies were not significantly related in our final path model. We discuss our findings in the context of current and emerging parenting interventions. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Prediction of Pseudo relative velocity response spectra at Yucca Mountain for underground nuclear explosions conducted in the Pahute Mesa testing area at the Nevada testing site; Yucca Mountain Site Characterization Project

Energy Technology Data Exchange (ETDEWEB)

Phillips, J.S.

1991-12-01

The Yucca Mountain Site Characterization Project (YMP), managed by the Office of Geologic Disposal of the Office of Civilian Radioactive Waste Management of the US Department of Energy, is examining the feasibility of siting a repository for commercial, high-level nuclear wastes at Yucca Mountain on and adjacent to the Nevada Test Site (NTS). This work, intended to extend our understanding of the ground motion at Yucca Mountain resulting from testing of nuclear weapons on the NTS, was funded by the Yucca Mountain project and the Military Applications Weapons Test Program. This report summarizes one aspect of the weapons test seismic investigations conducted in FY88. Pseudo relative velocity response spectra (PSRV) have been calculated for a large body of surface ground motions generated by underground nuclear explosions. These spectra have been analyzed and fit using multiple linear regression techniques to develop a credible prediction technique for surface PSRVs. In addition, a technique for estimating downhole PSRVs at specific stations is included. A data summary, data analysis, prediction development, prediction evaluation, software summary and FORTRAN listing of the prediction technique are included in this report.

Dissociative absorption: An empirically unique, clinically relevant, dissociative factor.

Science.gov (United States)

Soffer-Dudek, Nirit; Lassri, Dana; Soffer-Dudek, Nir; Shahar, Golan

2015-11-01

Research of dissociative absorption has raised two questions: (a) Is absorption a unique dissociative factor within a three-factor structure, or a part of one general dissociative factor? Even when three factors are found, the specificity of the absorption factor is questionable. (b) Is absorption implicated in psychopathology? Although commonly viewed as "non-clinical" dissociation, absorption was recently hypothesized to be specifically associated with obsessive-compulsive symptoms. To address these questions, we conducted exploratory and confirmatory factor analyses on 679 undergraduates. Analyses supported the three-factor model, and a "purified" absorption scale was extracted from the original inclusive absorption factor. The purified scale predicted several psychopathology scales. As hypothesized, absorption was a stronger predictor of obsessive-compulsive symptoms than of general psychopathology. In addition, absorption was the only dissociative scale that longitudinally predicted obsessive-compulsive symptoms. We conclude that absorption is a unique and clinically relevant dissociative tendency that is particularly meaningful to obsessive-compulsive symptoms. Copyright © 2015 Elsevier Inc. All rights reserved.

NetOglyc: prediction of mucin type O-glycosylation sites based on sequence context and surface accessibility

DEFF Research Database (Denmark)

Hansen, Jan Erik; Lund, Ole; Tolstrup, Niels

1998-01-01

-glycosylated serine and threonine residues in independent test sets, thus proving more accurate than matrix statistics and vector projection methods. Predicition of O-glycosylation sites in the envelope glycoprotein gp120 from the primate lentiviruses HIV-1, HIV-2 and SIV are presented. The most conserved O...... structure and surface accessibility. The sequence context of glycosylated threonines was found to differ from that of serine, and the sites were found to cluster. Non-clustered sites had a sequence context different from that of clustered sites. charged residues were disfavoured at postition -1 and +3......-glycosylation signals in these evolutionary-related glycoproteins were found in their first hypervariable loop, V1. However, the strain variation for HIV-1 gp120 was significant. A computer server, available through WWW or E-mail, has been developed for prediction of mucin type O-glycosylation sites in proteins based...

Neural Network Prediction of Translation Initiation Sites in Eukaryotes: Perspectives for EST and Genome analysis

DEFF Research Database (Denmark)

Pedersen, Anders Gorm; Nielsen, Henrik

1997-01-01

Translation in eukaryotes does not always start at the first AUG in an mRNA, implying that context information also plays a role.This makes prediction of translation initiation sites a non-trivial task, especially when analysing EST and genome data where the entire mature mRNA sequence is not known...

RBPmap: a web server for mapping binding sites of RNA-binding proteins.

Science.gov (United States)

Paz, Inbal; Kosti, Idit; Ares, Manuel; Cline, Melissa; Mandel-Gutfreund, Yael

2014-07-01

Regulation of gene expression is executed in many cases by RNA-binding proteins (RBPs) that bind to mRNAs as well as to non-coding RNAs. RBPs recognize their RNA target via specific binding sites on the RNA. Predicting the binding sites of RBPs is known to be a major challenge. We present a new webserver, RBPmap, freely accessible through the website http://rbpmap.technion.ac.il/ for accurate prediction and mapping of RBP binding sites. RBPmap has been developed specifically for mapping RBPs in human, mouse and Drosophila melanogaster genomes, though it supports other organisms too. RBPmap enables the users to select motifs from a large database of experimentally defined motifs. In addition, users can provide any motif of interest, given as either a consensus or a PSSM. The algorithm for mapping the motifs is based on a Weighted-Rank approach, which considers the clustering propensity of the binding sites and the overall tendency of regulatory regions to be conserved. In addition, RBPmap incorporates a position-specific background model, designed uniquely for different genomic regions, such as splice sites, 5' and 3' UTRs, non-coding RNA and intergenic regions. RBPmap was tested on high-throughput RNA-binding experiments and was proved to be highly accurate. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Affective and cognitive meta-bases of attitudes: Unique effects on information interest and persuasion.

Science.gov (United States)

See, Ya Hui Michelle; Petty, Richard E; Fabrigar, Leandre R

2008-06-01

The authors investigated the predictive utility of people's subjective assessments of whether their evaluations are affect- or cognition driven (i.e., meta-cognitive bases) as separate from whether people's attitudes are actually affect- or cognition based (i.e., structural bases). Study 1 demonstrated that meta-bases uniquely predict interest in affective versus cognitive information above and beyond structural bases and other related variables (i.e., need for cognition and need for affect). In Study 2, meta-bases were shown to account for unique variance in attitude change as a function of appeal type. Finally, Study 3 showed that as people became more deliberative in their judgments, meta-bases increased in predictive utility, and structural bases decreased in predictive utility. These findings support the existence of meta-bases of attitudes and demonstrate that meta-bases are distinguishable from structural bases in their predictive utility. (PsycINFO Database Record (c) 2008 APA, all rights reserved).

Risk Factors and Predictive Model Development of Thirty-Day Post-Operative Surgical Site Infection in the Veterans Administration Surgical Population.

Science.gov (United States)

Li, Xinli; Nylander, William; Smith, Tracy; Han, Soonhee; Gunnar, William

2018-04-01

Surgical site infection (SSI) complicates approximately 2% of surgeries in the Veterans Affairs (VA) hospitals. Surgical site infections are responsible for increased morbidity, length of hospital stay, cost, and mortality. Surgical site infection can be minimized by modifying risk factors. In this study, we identified risk factors and developed accurate predictive surgical specialty-specific SSI risk prediction models for the Veterans Health Administration (VHA) surgery population. In a retrospective observation study, surgical patients who underwent surgery from October 2013 to September 2016 from 136 VA hospitals were included. The Veteran Affairs Surgical Quality Improvement Program (VASQIP) database was used for the pre-operative demographic and clinical characteristics, intra-operative characteristics, and 30-day post-operative outcomes. The study population represents 11 surgical specialties: neurosurgery, urology, podiatry, otolaryngology, general, orthopedic, plastic, thoracic, vascular, cardiac coronary artery bypass graft (CABG), and cardiac valve/other surgery. Multivariable logistic regression models were developed for the 30-day post-operative SSIs. Among 354,528 surgical procedures, 6,538 (1.8%) had SSIs within 30 days. Surgical site infection rates varied among surgical specialty (0.7%-3.0%). Surgical site infection rates were higher in emergency procedures, procedures with long operative duration, greater complexity, and higher relative value units. Other factors associated with increased SSI risk were high level of American Society of Anesthesiologists (ASA) classification (level 4 and 5), dyspnea, open wound/infection, wound classification, ascites, bleeding disorder, chemotherapy, smoking, history of severe chronic obstructive pulmonary disease (COPD), radiotherapy, steroid use for chronic conditions, and weight loss. Each surgical specialty had a distinct combination of risk factors. Accurate SSI risk-predictive surgery specialty

A neural network based methodology to predict site-specific spectral acceleration values

Science.gov (United States)

Kamatchi, P.; Rajasankar, J.; Ramana, G. V.; Nagpal, A. K.

2010-12-01

A general neural network based methodology that has the potential to replace the computationally-intensive site-specific seismic analysis of structures is proposed in this paper. The basic framework of the methodology consists of a feed forward back propagation neural network algorithm with one hidden layer to represent the seismic potential of a region and soil amplification effects. The methodology is implemented and verified with parameters corresponding to Delhi city in India. For this purpose, strong ground motions are generated at bedrock level for a chosen site in Delhi due to earthquakes considered to originate from the central seismic gap of the Himalayan belt using necessary geological as well as geotechnical data. Surface level ground motions and corresponding site-specific response spectra are obtained by using a one-dimensional equivalent linear wave propagation model. Spectral acceleration values are considered as a target parameter to verify the performance of the methodology. Numerical studies carried out to validate the proposed methodology show that the errors in predicted spectral acceleration values are within acceptable limits for design purposes. The methodology is general in the sense that it can be applied to other seismically vulnerable regions and also can be updated by including more parameters depending on the state-of-the-art in the subject.

The unique role of lexical accessibility in predicting kindergarten emergent literacy.

Science.gov (United States)

Verhoeven, Ludo; van Leeuwe, Jan; Irausquin, Rosemarie; Segers, Eliane

The goal of this longitudinal study was to examine how lexical quality predicts the emergence of literacy abilities in 169 Dutch kindergarten children before formal reading instruction has started. At the beginning of the school year, a battery of precursor measures associated with lexical quality was related to the emergence of letter knowledge and word decoding. Confirmatory factor analysis evidenced five domains related to lexical quality, i.e., vocabulary, phonological coding, phonological awareness, lexical retrieval and phonological working memory. Structural equation modeling showed that the development of letter knowledge during the year could be predicted from children's phonological awareness and lexical retrieval, and the emergence of word decoding from their phonological awareness and letter knowledge. It is concluded that it is primarily the accessibility of phonological representations in the mental lexicon that predicts the emergence of literacy in kindergarten.

Operational strategy for soil concentration predictions of strontium/yttrium-90 and cesium-137 in surface soil at the West Valley Demonstration Project site

International Nuclear Information System (INIS)

Myers, J.A.

1995-01-01

There are difficulties associated with the assessment of the interpretation of field measurements, determination of guideline protocols and control and disposal of low level radioactive contaminated soil in the environmental health physics field. Questions are raised among scientists and in public forums concerning the necessity and high costs of large area soil remediation versus the risks of low-dose radiation health effects. As a result, accurate soil activity assessments become imperative in decontamination situations. The West Valley Demonstration Project (WVDP), a US Department of Energy facility located in West Valley, New York is managed and operated by West Valley Nuclear Services Co., Inc. (WVNS). WVNS has identified contaminated on-site soil areas with a mixed variety of radionuclides (primarily fission product). Through the use of data obtained from a previous project performed during the summer of 1994 entitled ''Field Survey Correlation and Instrumentation Response for an In Situ Soil Measurement Program'' (Myers), the WVDP offers a unique research opportunity to investigate the possibility of soil concentration predictions based on exposure or count rate responses returned from a survey detector probe. In this study, correlations are developed between laboratory measured soil beta activity and survey probe response for the purposes of determining the optimal detector for field use and using these correlations to establish predictability of soil activity levels

Cell-type specificity of ChIP-predicted transcription factor binding sites

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Håndstad Tony

2012-08-01

Full Text Available Abstract Background Context-dependent transcription factor (TF binding is one reason for differences in gene expression patterns between different cellular states. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq identifies genome-wide TF binding sites for one particular context—the cells used in the experiment. But can such ChIP-seq data predict TF binding in other cellular contexts and is it possible to distinguish context-dependent from ubiquitous TF binding? Results We compared ChIP-seq data on TF binding for multiple TFs in two different cell types and found that on average only a third of ChIP-seq peak regions are common to both cell types. Expectedly, common peaks occur more frequently in certain genomic contexts, such as CpG-rich promoters, whereas chromatin differences characterize cell-type specific TF binding. We also find, however, that genotype differences between the cell types can explain differences in binding. Moreover, ChIP-seq signal intensity and peak clustering are the strongest predictors of common peaks. Compared with strong peaks located in regions containing peaks for multiple transcription factors, weak and isolated peaks are less common between the cell types and are less associated with data that indicate regulatory activity. Conclusions Together, the results suggest that experimental noise is prevalent among weak peaks, whereas strong and clustered peaks represent high-confidence binding events that often occur in other cellular contexts. Nevertheless, 30-40% of the strongest and most clustered peaks show context-dependent regulation. We show that by combining signal intensity with additional data—ranging from context independent information such as binding site conservation and position weight matrix scores to context dependent chromatin structure—we can predict whether a ChIP-seq peak is likely to be present in other cellular contexts.

Application of GIS in prediction and assessment system of off-site accident consequence for NPP

International Nuclear Information System (INIS)

Wang Xingyu; Shi Zhongqi

2002-01-01

The assessment and prediction software system of off-site accident consequence for Guangdong Nuclear Power Plant (GNARD2.0) is a GIS-based software system. The spatial analysis of radioactive materials and doses with geographic information is available in this system. The structure and functions of the GNARD system and the method of applying ArcView GIS are presented

Mapping of the Lassa virus LAMP1 binding site reveals unique determinants not shared by other old world arenaviruses.

Directory of Open Access Journals (Sweden)

Hadar Israeli

2017-04-01

Full Text Available Cell entry of many enveloped viruses occurs by engagement with cellular receptors, followed by internalization into endocytic compartments and pH-induced membrane fusion. A previously unnoticed step of receptor switching was found to be critical during cell entry of two devastating human pathogens: Ebola and Lassa viruses. Our recent studies revealed the functional role of receptor switching to LAMP1 for triggering membrane fusion by Lassa virus and showed the involvement of conserved histidines in this switching, suggesting that other viruses from this family may also switch to LAMP1. However, when we investigated viruses that are genetically close to Lassa virus, we discovered that they cannot bind LAMP1. A crystal structure of the receptor-binding module from Morogoro virus revealed structural differences that allowed mapping of the LAMP1 binding site to a unique set of Lassa residues not shared by other viruses in its family, illustrating a key difference in the cell-entry mechanism of Lassa virus that may contribute to its pathogenicity.

IRESPred: Web Server for Prediction of Cellular and Viral Internal Ribosome Entry Site (IRES)

Science.gov (United States)

Kolekar, Pandurang; Pataskar, Abhijeet; Kulkarni-Kale, Urmila; Pal, Jayanta; Kulkarni, Abhijeet

2016-01-01

Cellular mRNAs are predominantly translated in a cap-dependent manner. However, some viral and a subset of cellular mRNAs initiate their translation in a cap-independent manner. This requires presence of a structured RNA element, known as, Internal Ribosome Entry Site (IRES) in their 5′ untranslated regions (UTRs). Experimental demonstration of IRES in UTR remains a challenging task. Computational prediction of IRES merely based on sequence and structure conservation is also difficult, particularly for cellular IRES. A web server, IRESPred is developed for prediction of both viral and cellular IRES using Support Vector Machine (SVM). The predictive model was built using 35 features that are based on sequence and structural properties of UTRs and the probabilities of interactions between UTR and small subunit ribosomal proteins (SSRPs). The model was found to have 75.51% accuracy, 75.75% sensitivity, 75.25% specificity, 75.75% precision and Matthews Correlation Coefficient (MCC) of 0.51 in blind testing. IRESPred was found to perform better than the only available viral IRES prediction server, VIPS. The IRESPred server is freely available at http://bioinfo.net.in/IRESPred/. PMID:27264539

Predicting Risk-Mitigating Behaviors From Indecisiveness and Trait Anxiety

DEFF Research Database (Denmark)

Mcneill, Ilona M.; Dunlop, Patrick D.; Skinner, Timothy C.

2016-01-01

Past research suggests that indecisiveness and trait anxiety may both decrease the likelihood of performing risk-mitigating preparatory behaviors (e.g., preparing for natural hazards) and suggests two cognitive processes (perceived control and worrying) as potential mediators. However, no single...... control over wildfire-related outcomes. Trait anxiety did not uniquely predict preparedness or perceived control, but it did uniquely predict worry, with higher trait anxiety predicting more worrying. Also, worry trended toward uniquely predicting preparedness, albeit in an unpredicted positive direction...

Radionuclide migration in ground water at a low-level waste disposal site: a comparison of predicted radionuclide transport modeling versus field observations

International Nuclear Information System (INIS)

Bergeron, M.P.; Robertson, D.E.; Champ, D.R.; Killey, R.W.D.; Moltyaner, G.L.

1987-01-01

At the Chalk River Nuclear Laboratories (CRNL), in Ontario, Canada, a number of LLW shallow-land burial facilities have existed for 25-30 years. These facilities are useful for testing the concept of site modelability. In 1984, CRNL and the Pacific Northwest Laboratory (PNL) established a cooperative research program to examine two disposal sites having plumes of slightly contaminated ground water for study. This report addresses the LLW Nitrate Disposal Pit site, which received liquid wastes containing approximately 1000-1500 curies of mixed fission products during 1953-54. The objective of this study is to test the regulatory requirement that a site be modeled and to use the Nitrate Disposal Pit site as a field site for testing the reliability of models in predicting radionuclide movement in ground water. The study plan was to approach this site as though it were to be licensed under the requirements of 10 CFR 61. Under the assumption that little was known about this site, a characterization plan was prepared describing the geologic, hydrologic, and geochemical information needed to assess site performance. After completion of the plan, site data generated by CRNL were selected to fill the plan data requirements. This paper describes the site hydrogeology, modeling of ground water flow, the comparison of observed and predicted radionuclide movement, and summarizes the conclusions and recommendations. 3 references, 10 figures

Multi-site laser Doppler flowmetry for assessing collateral flow in experimental ischemic stroke: Validation of outcome prediction with acute MRI.

Science.gov (United States)

Cuccione, Elisa; Versace, Alessandro; Cho, Tae-Hee; Carone, Davide; Berner, Lise-Prune; Ong, Elodie; Rousseau, David; Cai, Ruiyao; Monza, Laura; Ferrarese, Carlo; Sganzerla, Erik P; Berthezène, Yves; Nighoghossian, Norbert; Wiart, Marlène; Beretta, Simone; Chauveau, Fabien

2017-06-01

High variability in infarct size is common in experimental stroke models and affects statistical power and validity of neuroprotection trials. The aim of this study was to explore cerebral collateral flow as a stratification factor for the prediction of ischemic outcome. Transient intraluminal occlusion of the middle cerebral artery was induced for 90 min in 18 Wistar rats. Cerebral collateral flow was assessed intra-procedurally using multi-site laser Doppler flowmetry monitoring in both the lateral middle cerebral artery territory and the borderzone territory between middle cerebral artery and anterior cerebral artery. Multi-modal magnetic resonance imaging was used to assess acute ischemic lesion (diffusion-weighted imaging, DWI), acute perfusion deficit (time-to-peak, TTP), and final ischemic lesion at 24 h. Infarct volumes and typology at 24 h (large hemispheric versus basal ganglia infarcts) were predicted by both intra-ischemic collateral perfusion and acute DWI lesion volume. Collateral flow assessed by multi-site laser Doppler flowmetry correlated with the corresponding acute perfusion deficit using TTP maps. Multi-site laser Doppler flowmetry monitoring was able to predict ischemic outcome and perfusion deficit in good agreement with acute MRI. Our results support the additional value of cerebral collateral flow monitoring for outcome prediction in experimental ischemic stroke, especially when acute MRI facilities are not available.

Predicting Protein-Protein Interaction Sites with a Novel Membership Based Fuzzy SVM Classifier.

Science.gov (United States)

Sriwastava, Brijesh K; Basu, Subhadip; Maulik, Ujjwal

2015-01-01

Predicting residues that participate in protein-protein interactions (PPI) helps to identify, which amino acids are located at the interface. In this paper, we show that the performance of the classical support vector machine (SVM) algorithm can further be improved with the use of a custom-designed fuzzy membership function, for the partner-specific PPI interface prediction problem. We evaluated the performances of both classical SVM and fuzzy SVM (F-SVM) on the PPI databases of three different model proteomes of Homo sapiens, Escherichia coli and Saccharomyces Cerevisiae and calculated the statistical significance of the developed F-SVM over classical SVM algorithm. We also compared our performance with the available state-of-the-art fuzzy methods in this domain and observed significant performance improvements. To predict interaction sites in protein complexes, local composition of amino acids together with their physico-chemical characteristics are used, where the F-SVM based prediction method exploits the membership function for each pair of sequence fragments. The average F-SVM performance (area under ROC curve) on the test samples in 10-fold cross validation experiment are measured as 77.07, 78.39, and 74.91 percent for the aforementioned organisms respectively. Performances on independent test sets are obtained as 72.09, 73.24 and 82.74 percent respectively. The software is available for free download from http://code.google.com/p/cmater-bioinfo.

Analog site for fractured rock characterization. Annual report FY 1995

International Nuclear Information System (INIS)

Long, J.C.S.; Loughty, C.; Faybishenko, B.

1995-10-01

This report describes the accomplishments of the Analog Site for Fracture Rock Characterization Project during fiscal year 1995. This project is designed to address the problem of characterizing contaminated fractured rock. In order to locate contaminant plumes, develop monitoring schemes, and predict future fate and transport, the project will address the following questions: What parts of the system control flow-geometry of a fracture network? What physical processes control flow and transport? What are the limits on measurements to determine the above? What instrumentation should be used? How should it be designed and implemented? How can field tests be designed to provide information for predicting behavior? What numerical models are good predictors of the behavior of the system? The answers to these question can be used to help plan drilling programs that are likely to intersect plumes and provide effective monitoring of plume movement. The work is done at an open-quotes analogueclose quotes site, i.e., a site that is not contaminated, but has similar geology to sites that are contaminated, in order to develop tools and techniques without the financial, time and legal burdens of a contaminated site. The idea is to develop conceptual models and investigations tools and methodology that will apply to the contaminated sites in the same geologic regimes. The Box Canyon site, chosen for most of this work represents a unique opportunity because the Canyon walls allow us to see a vertical plane through the rock. The work represents a collaboration between the Lawrence Berkeley National Laboratory (LBL), Stanford University (Stanford), Idaho National Engineering Laboratory (INEL) and Parsons Environmental Engineering (Parsons). LBL and Stanford bring extensive experience in research in fractured rock systems. INEL and Parsons bring significant experience with the contamination problem at INEL

Efficacy of GPS cluster analysis for predicting carnivory sites of a wide-ranging omnivore: the American black bear

Science.gov (United States)

Kindschuh, Sarah R.; Cain, James W.; Daniel, David; Peyton, Mark A.

2016-01-01

The capacity to describe and quantify predation by large carnivores expanded considerably with the advent of GPS technology. Analyzing clusters of GPS locations formed by carnivores facilitates the detection of predation events by identifying characteristics which distinguish predation sites. We present a performance assessment of GPS cluster analysis as applied to the predation and scavenging of an omnivore, the American black bear (Ursus americanus), on ungulate prey and carrion. Through field investigations of 6854 GPS locations from 24 individual bears, we identified 54 sites where black bears formed a cluster of locations while predating or scavenging elk (Cervus elaphus), mule deer (Odocoileus hemionus), or cattle (Bos spp.). We developed models for three data sets to predict whether a GPS cluster was formed at a carnivory site vs. a non-carnivory site (e.g., bed sites or non-ungulate foraging sites). Two full-season data sets contained GPS locations logged at either 3-h or 30-min intervals from April to November, and a third data set contained 30-min interval data from April through July corresponding to the calving period for elk. Longer fix intervals resulted in the detection of fewer carnivory sites. Clusters were more likely to be carnivory sites if they occurred in open or edge habitats, if they occurred in the early season, if the mean distance between all pairs of GPS locations within the cluster was less, and if the cluster endured for a longer period of time. Clusters were less likely to be carnivory sites if they were initiated in the morning or night compared to the day. The top models for each data set performed well and successfully predicted 71–96% of field-verified carnivory events, 55–75% of non–carnivory events, and 58–76% of clusters overall. Refinement of this method will benefit from further application across species and ecological systems.

Optimizing Restriction Site Placement for Synthetic Genomes

Science.gov (United States)

Montes, Pablo; Memelli, Heraldo; Ward, Charles; Kim, Joondong; Mitchell, Joseph S. B.; Skiena, Steven

Restriction enzymes are the workhorses of molecular biology. We introduce a new problem that arises in the course of our project to design virus variants to serve as potential vaccines: we wish to modify virus-length genomes to introduce large numbers of unique restriction enzyme recognition sites while preserving wild-type function by substitution of synonymous codons. We show that the resulting problem is NP-Complete, give an exponential-time algorithm, and propose effective heuristics, which we show give excellent results for five sample viral genomes. Our resulting modified genomes have several times more unique restriction sites and reduce the maximum gap between adjacent sites by three to nine-fold.

V S30, slope, H 800 and f 0: performance of various site-condition proxies in reducing ground-motion aleatory variability and predicting nonlinear site response

Science.gov (United States)

Derras, Boumédiène; Bard, Pierre-Yves; Cotton, Fabrice

2017-09-01

The aim of this paper is to investigate the ability of various site-condition proxies (SCPs) to reduce ground-motion aleatory variability and evaluate how SCPs capture nonlinearity site effects. The SCPs used here are time-averaged shear-wave velocity in the top 30 m ( V S30), the topographical slope (slope), the fundamental resonance frequency ( f 0) and the depth beyond which V s exceeds 800 m/s ( H 800). We considered first the performance of each SCP taken alone and then the combined performance of the 6 SCP pairs [ V S30- f 0], [ V S30- H 800], [ f 0-slope], [ H 800-slope], [ V S30-slope] and [ f 0- H 800]. This analysis is performed using a neural network approach including a random effect applied on a KiK-net subset for derivation of ground-motion prediction equations setting the relationship between various ground-motion parameters such as peak ground acceleration, peak ground velocity and pseudo-spectral acceleration PSA ( T), and M w, R JB, focal depth and SCPs. While the choice of SCP is found to have almost no impact on the median ground-motion prediction, it does impact the level of aleatory uncertainty. V S30 is found to perform the best of single proxies at short periods ( T < 0.6 s), while f 0 and H 800 perform better at longer periods; considering SCP pairs leads to significant improvements, with particular emphasis on [ V S30- H 800] and [ f 0-slope] pairs. The results also indicate significant nonlinearity on the site terms for soft sites and that the most relevant loading parameter for characterising nonlinear site response is the "stiff" spectral ordinate at the considered period.[Figure not available: see fulltext.

Archaeology Through Computational Linguistics: Inscription Statistics Predict Excavation Sites of Indus Valley Artifacts.

Science.gov (United States)

Recchia, Gabriel L; Louwerse, Max M

2016-11-01

Computational techniques comparing co-occurrences of city names in texts allow the relative longitudes and latitudes of cities to be estimated algorithmically. However, these techniques have not been applied to estimate the provenance of artifacts with unknown origins. Here, we estimate the geographic origin of artifacts from the Indus Valley Civilization, applying methods commonly used in cognitive science to the Indus script. We show that these methods can accurately predict the relative locations of archeological sites on the basis of artifacts of known provenance, and we further apply these techniques to determine the most probable excavation sites of four sealings of unknown provenance. These findings suggest that inscription statistics reflect historical interactions among locations in the Indus Valley region, and they illustrate how computational methods can help localize inscribed archeological artifacts of unknown origin. The success of this method offers opportunities for the cognitive sciences in general and for computational anthropology specifically. Copyright © 2015 Cognitive Science Society, Inc.

Predicting surgical site infection after spine surgery: a validated model using a prospective surgical registry.

Science.gov (United States)

Lee, Michael J; Cizik, Amy M; Hamilton, Deven; Chapman, Jens R

2014-09-01

The impact of surgical site infection (SSI) is substantial. Although previous study has determined relative risk and odds ratio (OR) values to quantify risk factors, these values may be difficult to translate to the patient during counseling of surgical options. Ideally, a model that predicts absolute risk of SSI, rather than relative risk or OR values, would greatly enhance the discussion of safety of spine surgery. To date, there is no risk stratification model that specifically predicts the risk of medical complication. The purpose of this study was to create and validate a predictive model for the risk of SSI after spine surgery. This study performs a multivariate analysis of SSI after spine surgery using a large prospective surgical registry. Using the results of this analysis, this study will then create and validate a predictive model for SSI after spine surgery. The patient sample is from a high-quality surgical registry from our two institutions with prospectively collected, detailed demographic, comorbidity, and complication data. An SSI that required return to the operating room for surgical debridement. Using a prospectively collected surgical registry of more than 1,532 patients with extensive demographic, comorbidity, surgical, and complication details recorded for 2 years after the surgery, we identified several risk factors for SSI after multivariate analysis. Using the beta coefficients from those regression analyses, we created a model to predict the occurrence of SSI after spine surgery. We split our data into two subsets for internal and cross-validation of our model. We created a predictive model based on our beta coefficients from our multivariate analysis. The final predictive model for SSI had a receiver-operator curve characteristic of 0.72, considered to be a fair measure. The final model has been uploaded for use on SpineSage.com. We present a validated model for predicting SSI after spine surgery. The value in this model is that it gives

Feature selection for splice site prediction: A new method using EDA-based feature ranking

Directory of Open Access Journals (Sweden)

Rouzé Pierre

2004-05-01

Full Text Available Abstract Background The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Other advantages of feature selection include the ability of the classification system to attain good or even better solutions using a restricted subset of features, and a faster classification. Thus, robust methods for fast feature selection are of key importance in extracting knowledge from complex biological data. Results In this paper we present a novel method for feature subset selection applied to splice site prediction, based on estimation of distribution algorithms, a more general framework of genetic algorithms. From the estimated distribution of the algorithm, a feature ranking is derived. Afterwards this ranking is used to iteratively discard features. We apply this technique to the problem of splice site prediction, and show how it can be used to gain insight into the underlying biological process of splicing. Conclusion We show that this technique proves to be more robust than the traditional use of estimation of distribution algorithms for feature selection: instead of returning a single best subset of features (as they normally do this method provides a dynamical view of the feature selection process, like the traditional sequential wrapper methods. However, the method is faster than the traditional techniques, and scales better to datasets described by a large number of features.

Executive Functions Contribute Uniquely to Reading Competence in Minority Youth

Science.gov (United States)

Jacobson, Lisa A.; Koriakin, Taylor; Lipkin, Paul; Boada, Richard; Frijters, Jan; Lovett, Maureen; Hill, Dina; Willcutt, Erik; Gottwald, Stephanie; Wolf, Maryanne; Bosson-Heenan, Joan; Gruen, Jeffrey R.; Mahone, E. Mark

2018-01-01

Competent reading requires various skills beyond those for basic word reading (i.e., core language skills, rapid naming, phonological processing). Contributing “higher-level” or domain-general processes include information processing speed and executive functions (working memory, strategic problem solving, attentional switching). Research in this area has relied on largely Caucasian samples, with limited representation of children from racial or ethnic minority groups. This study examined contributions of executive skills to reading competence in 761 children of minority backgrounds. Hierarchical linear regressions examined unique contributions of executive functions (EF) to word reading, fluency, and comprehension. EF contributed uniquely to reading performance, over and above reading-related language skills; working memory contributed uniquely to all components of reading; while attentional switching, but not problem solving, contributed to isolated and contextual word reading and reading fluency. Problem solving uniquely predicted comprehension, suggesting that this skill may be especially important for reading comprehension in minority youth. Attentional switching may play a unique role in development of reading fluency in minority youth, perhaps as a result of the increased demand for switching between spoken versus written dialects. Findings have implications for educational and clinical practice with regard to reading instruction, remedial reading intervention, and assessment of individuals with reading difficulty. PMID:26755569

SLC9B1 methylation predicts fetal intolerance of labor.

Science.gov (United States)

Knight, Anna K; Conneely, Karen N; Kilaru, Varun; Cobb, Dawayland; Payne, Jennifer L; Meilman, Samantha; Corwin, Elizabeth J; Kaminsky, Zachary A; Dunlop, Anne L; Smith, Alicia K

2018-01-01

Fetal intolerance of labor is a common indication for delivery by Caesarean section. Diagnosis is based on the presence of category III fetal heart rate tracing, which is an abnormal heart tracing associated with increased likelihood of fetal hypoxia and metabolic acidemia. This study analyzed data from 177 unique women who, during their prenatal visits (7-15 weeks and/or 24-32 weeks) to Atlanta area prenatal care clinics, consented to provide blood samples for DNA methylation (HumanMethylation450 BeadChip) and gene expression (Human HT-12 v4 Expression BeadChip) analyses. We focused on 57 women aged 18-36 (mean 25.4), who had DNA methylation data available from their second prenatal visit. DNA methylation patterns at CpG sites across the genome were interrogated for associations with fetal intolerance of labor. Four CpG sites (P value intolerance of labor. DNA methylation and gene expression were negatively associated when examined longitudinally during pregnancy using a linear mixed-effects model. Positive predictive values of methylation of these four sites ranged from 0.80 to 0.89, while negative predictive values ranged from 0.91 to 0.92. The four CpG sites were also associated with fetal intolerance of labor in an independent cohort (the Johns Hopkins Prospective PPD cohort). Therefore, fetal intolerance of labor could be accurately predicted from maternal blood samples obtained between 24-32 weeks gestation. Fetal intolerance of labor may be accurately predicted from maternal blood samples obtained between 24-32 weeks gestation by assessing DNA methylation patterns of SLC9B1. The identification of pregnant women at elevated risk for fetal intolerance of labor may allow for the development of targeted treatments or management plans.

A Predictive Approach to Network Reverse-Engineering

Science.gov (United States)

Wiggins, Chris

2005-03-01

A central challenge of systems biology is the ``reverse engineering" of transcriptional networks: inferring which genes exert regulatory control over which other genes. Attempting such inference at the genomic scale has only recently become feasible, via data-intensive biological innovations such as DNA microrrays (``DNA chips") and the sequencing of whole genomes. In this talk we present a predictive approach to network reverse-engineering, in which we integrate DNA chip data and sequence data to build a model of the transcriptional network of the yeast S. cerevisiae capable of predicting the response of genes in unseen experiments. The technique can also be used to extract ``motifs,'' sequence elements which act as binding sites for regulatory proteins. We validate by a number of approaches and present comparison of theoretical prediction vs. experimental data, along with biological interpretations of the resulting model. En route, we will illustrate some basic notions in statistical learning theory (fitting vs. over-fitting; cross- validation; assessing statistical significance), highlighting ways in which physicists can make a unique contribution in data- driven approaches to reverse engineering.

Prediction of multiphase equilibria in associating fluids by a contact-site quasichemical equation of state

International Nuclear Information System (INIS)

Prikhodko, I.V.; Victorov, A.I.; Loos, Th.W.de

1995-01-01

A contract-site quasichemical equation of state has been used for the modeling of different kinds of fluid phase equilibria (between a gas phase and one or more liquids) over a wide range of conditions. Among the systems of interest are the ternary mixtures water + alkanols + hydrocarbons (alkanes or alkynes), water + alkanols (or acetone) + CO 2 , water + polyoxyethyleneglycol ethers + heavy alkanes. The model has been applied to describing the thermodynamic properties of the binary subsystems and to predict the phase behavior of the ternary systems. For longer-chain alkanols and hydrocarbons a group-contribution approach is implemented, which allows the modeling when no experimental data are available. The model gives reasonable predictions of phase behavior and the correct trends in the calculated phase diagrams in most cases. The concentrations of associates in liquid and gas phases are estimated by the model and compared with some experimental and computer simulation data. The predictive abilities of the model, its limitations, and possible ways of its improvement are discussed

MANAGEING THE RETRIEVAL RISK OF BURIED TRANSURANIC (TRU) WASTE WITH UNIQUE CHARACTERISTICS

International Nuclear Information System (INIS)

WOJTASEK, R.D.; GREENWELL, R.D.

2005-01-01

United States-Department of Energy (DOE) sites that store transuranic (TRU) waste are almost certain to encounter waste packages with characteristics that are so unique as to warrant special precautions for retrieval. At the Hanford Site, a subgroup of stored TRU waste (12 drums) had special considerations due to the radioactive source content of plutonium oxide (PuO 2 ), and the potential for high heat generation, pressurization, criticality, and high radiation. These characteristics bear on the approach to safely retrieve, overpack, vent, store, and transport the waste package. Because of the potential risk to personnel, contingency planning for unexpected conditions played an effective roll in work planning and in preparing workers for the field inspection activity. As a result, the integrity inspections successfully confirmed waste package configuration and waste confinement without experiencing any perturbations due to unanticipated packaging conditions. This paper discusses the engineering and field approach to managing the risk of retrieving TRU waste with unique characteristics

SVM prediction of ligand-binding sites in bacterial lipoproteins employing shape and physio-chemical descriptors.

Science.gov (United States)

Kadam, Kiran; Prabhakar, Prashant; Jayaraman, V K

2012-11-01

Bacterial lipoproteins play critical roles in various physiological processes including the maintenance of pathogenicity and numbers of them are being considered as potential candidates for generating novel vaccines. In this work, we put forth an algorithm to identify and predict ligand-binding sites in bacterial lipoproteins. The method uses three types of pocket descriptors, namely fpocket descriptors, 3D Zernike descriptors and shell descriptors, and combines them with Support Vector Machine (SVM) method for the classification. The three types of descriptors represent shape-based properties of the pocket as well as its local physio-chemical features. All three types of descriptors, along with their hybrid combinations are evaluated with SVM and to improve classification performance, WEKA-InfoGain feature selection is applied. Results obtained in the study show that the classifier successfully differentiates between ligand-binding and non-binding pockets. For the combination of three types of descriptors, 10 fold cross-validation accuracy of 86.83% is obtained for training while the selected model achieved test Matthews Correlation Coefficient (MCC) of 0.534. Individually or in combination with new and existing methods, our model can be a very useful tool for the prediction of potential ligand-binding sites in bacterial lipoproteins.

Does the site of platelet sequestration predict the response to splenectomy in adult patients with immune thrombocytopenic purpura?

Science.gov (United States)

Navez, Julie; Hubert, Catherine; Gigot, Jean-François; Navez, Benoit; Lambert, Catherine; Jamar, François; Danse, Etienne; Lannoy, Valérie; Jabbour, Nicolas

2015-01-01

Splenectomy is the only potentially curative treatment for chronic immune thrombocytopenic purpura (ITP) in adults. However, one-third of the patients relapse without predictive factors identified. We evaluate the predictive value of the site of platelet sequestration on the response to splenectomy in patients with ITP. Eighty-two consecutive patients with ITP treated by splenectomy between 1992 and 2013 were retrospectively reviewed. Platelet sequestration site was studied by (111)Indium-oxinate-labeled platelets in 93% of patients. Response to splenectomy was defined at last follow-up as: complete response (CR) for platelet count (PC) ≥100 × 10(9)/L, response (R) for PC≥30 × 10(9)/L and splenectomy was performed in 81 patients (conversion rate of 16%), and open approach in one patient. Median follow-up was 57 months (range, 1-235). Platelet sequestration study was performed in 93% of patients: 50 patients (61%) exhibited splenic sequestration, 9 (11%) hepatic sequestration and 14 patients (17%) mixed sequestration. CR was obtained in 72% of patients, R in 25% and NR in 4% (two with splenic sequestration, one with hepatic sequestration). Preoperative PC, age at diagnosis, hepatic sequestration and male gender were significant for predicting CR in univariate analysis, but only age (HR = 1.025 by one-year increase, 95% CI [1.004-1.047], p = 0.020) and pre-operative PC (HR = 0.112 for > 100 versus splenectomy was independent of the site of platelet sequestration in patients with ITP. Pre-operative platelet sequestration study in these patients cannot be recommended.

Predicting protein-ATP binding sites from primary sequence through fusing bi-profile sampling of multi-view features

Directory of Open Access Journals (Sweden)

Zhang Ya-Nan

2012-05-01

Full Text Available Abstract Background Adenosine-5′-triphosphate (ATP is one of multifunctional nucleotides and plays an important role in cell biology as a coenzyme interacting with proteins. Revealing the binding sites between protein and ATP is significantly important to understand the functionality of the proteins and the mechanisms of protein-ATP complex. Results In this paper, we propose a novel framework for predicting the proteins’ functional residues, through which they can bind with ATP molecules. The new prediction protocol is achieved by combination of sequence evolutional information and bi-profile sampling of multi-view sequential features and the sequence derived structural features. The hypothesis for this strategy is single-view feature can only represent partial target’s knowledge and multiple sources of descriptors can be complementary. Conclusions Prediction performances evaluated by both 5-fold and leave-one-out jackknife cross-validation tests on two benchmark datasets consisting of 168 and 227 non-homologous ATP binding proteins respectively demonstrate the efficacy of the proposed protocol. Our experimental results also reveal that the residue structural characteristics of real protein-ATP binding sites are significant different from those normal ones, for example the binding residues do not show high solvent accessibility propensities, and the bindings prefer to occur at the conjoint points between different secondary structure segments. Furthermore, results also show that performance is affected by the imbalanced training datasets by testing multiple ratios between positive and negative samples in the experiments. Increasing the dataset scale is also demonstrated useful for improving the prediction performances.

Emotion dysregulation and peer drinking norms uniquely predict alcohol-related problems via motives.

Science.gov (United States)

Simons, Raluca M; Hahn, Austin M; Simons, Jeffrey S; Murase, Hanako

2017-08-01

This study examined the relationships between emotion dysregulation, peer drinking norms, drinking motives, and alcohol-related outcomes among 435 college students. We examined the mediating roles of drinking motives when predicting alcohol consumption and related problems from the subscales of the Difficulties in Emotion Regulation Scale (DERS; Gratz and Roemer, 2004) via negative and positive reinforcement models. First, we hypothesized that individuals who lack in emotion regulation strategies or have difficulties in accepting negative emotions are more likely to drink to cope. Additionally, we hypothesized that individuals who act impulsively or become distracted when upset as well as those with higher peer drinking norms are more likely to drink for social and enhancement motives. The results of the path model indicated that limited access to emotion regulation strategies significantly predicted alcohol-related problems via both depression and anxiety coping motives, but did not predict alcohol consumption. Nonacceptance of emotional responses was not significantly associated with coping motives. Impulsivity had a significant direct relationship with alcohol problems. Difficulty in engaging in goal-directed behaviors predicted both enhancement and social motives, but only enhancement motives in turn predicted consumption. Norms indirectly predicted problems via enhancement motives and consumption. The results indicated that using alcohol to reduce negative or to increase positive emotions increases alcohol consumption and alcohol-related problems. Overall, results advance our understanding of the mechanisms of increased alcohol use and problems among college students. Copyright © 2017 Elsevier B.V. All rights reserved.

Prediction and characterization of novel epitopes of serotype A foot-and-mouth disease viruses circulating in East Africa using site-directed mutagenesis

Science.gov (United States)

Bari, Fufa Dawo; Parida, Satya; Asfor, Amin S.; Haydon, Daniel T.; Reeve, Richard; Paton, David J.

2015-01-01

Epitopes on the surface of the foot-and-mouth disease virus (FMDV) capsid have been identified by monoclonal antibody (mAb) escape mutant studies leading to the designation of four antigenic sites in serotype A FMDV. Previous work focused on viruses isolated mainly from Asia, Europe and Latin America. In this study we report on the prediction of epitopes in African serotype A FMDVs and testing of selected epitopes using reverse genetics. Twenty-four capsid amino acid residues were predicted to be of antigenic significance by analysing the capsid sequences (n = 56) using in silico methods, and six residues by correlating capsid sequence with serum–virus neutralization data. The predicted residues were distributed on the surface-exposed capsid regions, VP1–VP3. The significance of residue changes at eight of the predicted epitopes was tested by site-directed mutagenesis using a cDNA clone resulting in the generation of 12 mutant viruses involving seven sites. The effect of the amino acid substitutions on the antigenic nature of the virus was assessed by virus neutralization (VN) test. Mutations at four different positions, namely VP1-43, VP1-45, VP2-191 and VP3-132, led to significant reduction in VN titre (P value = 0.05, 0.05, 0.001 and 0.05, respectively). This is the first time, to our knowledge, that the antigenic regions encompassing amino acids VP1-43 to -45 (equivalent to antigenic site 3 in serotype O), VP2-191 and VP3-132 have been predicted as epitopes and evaluated serologically for serotype A FMDVs. This identifies novel capsid epitopes of recently circulating serotype A FMDVs in East Africa. PMID:25614587

A neural network method for identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites

DEFF Research Database (Denmark)

Nielsen, Henrik; Engelbrecht, Jacob; Brunak, Søren

1997-01-01

We have developed a new method for the identication of signal peptides and their cleavage sites based on neural networks trained on separate sets of prokaryotic and eukaryotic sequences. The method performs signicantly better than previous prediction schemes, and can easily be applied to genome...

SVM-based prediction of propeptide cleavage sites in spider toxins identifies toxin innovation in an Australian tarantula.

Directory of Open Access Journals (Sweden)

Emily S W Wong

Full Text Available Spider neurotoxins are commonly used as pharmacological tools and are a popular source of novel compounds with therapeutic and agrochemical potential. Since venom peptides are inherently toxic, the host spider must employ strategies to avoid adverse effects prior to venom use. It is partly for this reason that most spider toxins encode a protective proregion that upon enzymatic cleavage is excised from the mature peptide. In order to identify the mature toxin sequence directly from toxin transcripts, without resorting to protein sequencing, the propeptide cleavage site in the toxin precursor must be predicted bioinformatically. We evaluated different machine learning strategies (support vector machines, hidden Markov model and decision tree and developed an algorithm (SpiderP for prediction of propeptide cleavage sites in spider toxins. Our strategy uses a support vector machine (SVM framework that combines both local and global sequence information. Our method is superior or comparable to current tools for prediction of propeptide sequences in spider toxins. Evaluation of the SVM method on an independent test set of known toxin sequences yielded 96% sensitivity and 100% specificity. Furthermore, we sequenced five novel peptides (not used to train the final predictor from the venom of the Australian tarantula Selenotypus plumipes to test the accuracy of the predictor and found 80% sensitivity and 99.6% 8-mer specificity. Finally, we used the predictor together with homology information to predict and characterize seven groups of novel toxins from the deeply sequenced venom gland transcriptome of S. plumipes, which revealed structural complexity and innovations in the evolution of the toxins. The precursor prediction tool (SpiderP is freely available on ArachnoServer (http://www.arachnoserver.org/spiderP.html, a web portal to a comprehensive relational database of spider toxins. All training data, test data, and scripts used are available from

On the Non-Uniqueness of Sediment Yield

Science.gov (United States)

Kim, J.; Ivanov, V. Y.; Fatichi, S.

2014-12-01

There has been ample experimental evidence that soil erosion does not necessarily occur at the same rate, given the same amount of rainfall or runoff. Such a non-unique phenomenon has been often referred to in literature as due to 'natural variability'. Our recent study hypothesized that uncertainties in the distribution and properties of a sediment layer can be a potential clue to one of the reasons of the non-unique sediment yield. Specifically, numerical experimentation with a sophisticated two-dimensional model showed that a deposited layer plays two conflicting roles: it can both increase and decrease soil erosion, given the same magnitude of runoff. The difference in erodibilities of the "original, intact soil layer" and the "deposited, loose soil layer" and the composition of soil particles in the underlying layers give rise to the non-uniqueness of the amount of eroded materials. In continuing efforts, we attempt to investigate this phenomenon using a comprehensive the Universal Soil Loss Erosion (USLE) database, that contains data on paired hillslopes that show a high degree of non-uniqueness in the response, even though the hillslopes exhibit the same topography, soil type, rainfall and meteorological forcings, and landuse. An underlying hypothesis of this study is that uncertainties in the distribution of soil substrate prior to a rainfall event lead to low predictability skill, i.e., a stochastically-varying outcome. A large number of simulation cases demonstrating the proposed hypothesis are conducted using a coupled numerical model, tRIBS-VEGGIE-FEaST (Triangulated irregular network - based Real time Integrated Basin Simulator- VEGetation Generator for Interactive Evolution -Flow Erosion and Sediment Transport).

Using physicochemical and compositional characteristics of DNA sequence for prediction of genomic signals

KAUST Repository

Mulamba, Pierre Abraham

2014-12-01

The challenge in finding genes in eukaryotic organisms using computational methods is an ongoing problem in the biology. Based on various genomic signals found in eukaryotic genomes, this problem can be divided into many different sub­‐problems such as identification of transcription start sites, translation initiation sites, splice sites, poly (A) signals, etc. Each sub-­problem deals with a particular type of genomic signals and various computational methods are used to solve each sub-­problem. Aggregating information from all these individual sub-­problems can lead to a complete annotation of a gene and its component signals. The fundamental principle of most of these computational methods is the mapping principle – building an input-­output model for the prediction of a particular genomic signal based on a set of known input signals and their corresponding output signal. The type of input signals used to build the model is an essential element in most of these computational methods. The common factor of most of these methods is that they are mainly based on the statistical analysis of the basic nucleotide sequence string composition. 4 Our study is based on a novel approach to predict genomic signals in which uniquely generated structural profiles that combine compressed physicochemical properties with topological and compositional properties of DNA sequences are used to develop machine learning predictive models. The compression of the physicochemical properties is made using principal component analysis transformation. Our ideas are evaluated through prediction models of canonical splice sites using support vector machine models. We demonstrate across several species that the proposed methodology has resulted in the most accurate splice site predictors that are publicly available or described. We believe that the approach in this study is quite general and has various applications in other biological modeling problems.

Path spectra derived from inversion of source and site spectra for earthquakes in Southern California

Science.gov (United States)

Klimasewski, A.; Sahakian, V. J.; Baltay, A.; Boatwright, J.; Fletcher, J. B.; Baker, L. M.

2017-12-01

A large source of epistemic uncertainty in Ground Motion Prediction Equations (GMPEs) is derived from the path term, currently represented as a simple geometric spreading and intrinsic attenuation term. Including additional physical relationships between the path properties and predicted ground motions would produce more accurate and precise, region-specific GMPEs by reclassifying some of the random, aleatory uncertainty as epistemic. This study focuses on regions of Southern California, using data from the Anza network and Southern California Seismic network to create a catalog of events magnitude 2.5 and larger from 1998 to 2016. The catalog encompasses regions of varying geology and therefore varying path and site attenuation. Within this catalog of events, we investigate several collections of event region-to-station pairs, each of which share similar origin locations and stations so that all events have similar paths. Compared with a simple regional GMPE, these paths consistently have high or low residuals. By working with events that have the same path, we can isolate source and site effects, and focus on the remaining residual as path effects. We decompose the recordings into source and site spectra for each unique event and site in our greater Southern California regional database using the inversion method of Andrews (1986). This model represents each natural log record spectra as the sum of its natural log event and site spectra, while constraining each record to a reference site or Brune source spectrum. We estimate a regional, path-specific anelastic attenuation (Q) and site attenuation (t*) from the inversion site spectra and corner frequency from the inversion event spectra. We then compute the residuals between the observed record data, and the inversion model prediction (event*site spectra). This residual is representative of path effects, likely anelastic attenuation along the path that varies from the regional median attenuation. We examine the

Impact of germline and somatic missense variations on drug binding sites.

Science.gov (United States)

Yan, C; Pattabiraman, N; Goecks, J; Lam, P; Nayak, A; Pan, Y; Torcivia-Rodriguez, J; Voskanian, A; Wan, Q; Mazumder, R

2017-03-01

Advancements in next-generation sequencing (NGS) technologies are generating a vast amount of data. This exacerbates the current challenge of translating NGS data into actionable clinical interpretations. We have comprehensively combined germline and somatic nonsynonymous single-nucleotide variations (nsSNVs) that affect drug binding sites in order to investigate their prevalence. The integrated data thus generated in conjunction with exome or whole-genome sequencing can be used to identify patients who may not respond to a specific drug because of alterations in drug binding efficacy due to nsSNVs in the target protein's gene. To identify the nsSNVs that may affect drug binding, protein-drug complex structures were retrieved from Protein Data Bank (PDB) followed by identification of amino acids in the protein-drug binding sites using an occluded surface method. Then, the germline and somatic mutations were mapped to these amino acids to identify which of these alter protein-drug binding sites. Using this method we identified 12 993 amino acid-drug binding sites across 253 unique proteins bound to 235 unique drugs. The integration of amino acid-drug binding sites data with both germline and somatic nsSNVs data sets revealed 3133 nsSNVs affecting amino acid-drug binding sites. In addition, a comprehensive drug target discovery was conducted based on protein structure similarity and conservation of amino acid-drug binding sites. Using this method, 81 paralogs were identified that could serve as alternative drug targets. In addition, non-human mammalian proteins bound to drugs were used to identify 142 homologs in humans that can potentially bind to drugs. In the current protein-drug pairs that contain somatic mutations within their binding site, we identified 85 proteins with significant differential gene expression changes associated with specific cancer types. Information on protein-drug binding predicted drug target proteins and prevalence of both somatic and

Structural and biochemical analysis of a unique phosphatase from Bdellovibrio bacteriovorus reveals its structural and functional relationship with the protein tyrosine phosphatase class of phytase.

Directory of Open Access Journals (Sweden)

Robert J Gruninger

Full Text Available Bdellovibrio bacteriovorus is an unusual δ-proteobacterium that invades and preys on other Gram-negative bacteria and is of potential interest as a whole cell therapeutic against pathogens of man, animals and crops. PTPs (protein tyrosine phosphatases are an important class of enzyme involved in desphosphorylating a variety of substrates, often with implications in cell signaling. The B. bacteriovorus open reading frame Bd1204 is predicted to encode a PTP of unknown function. Bd1204 is both structurally and mechanistically related to the PTP-like phytase (PTPLP class of enzymes and possesses a number of unique properties not observed in any other PTPLPs characterized to date. Bd1204 does not display catalytic activity against some common protein tyrosine phosphatase substrates but is highly specific for hydrolysis of phosphomonoester bonds of inositol hexakisphosphate. The structure reveals that Bd1204 has the smallest and least electropositive active site of all characterized PTPLPs to date yet possesses a unique substrate specificity characterized by a strict preference for inositol hexakisphosphate. These two active site features are believed to be the most significant contributors to the specificity of phytate degrading enzymes. We speculate that Bd1204 may be involved in phosphate acquisition outside of prey.

Predicting local distributions of erosion-corrosion wear sites for the piping in the nuclear power plant using CFD models

International Nuclear Information System (INIS)

Ferng, Y.M.

2008-01-01

The erosion-corrosion (E/C) wear is an essential degradation mechanism for the piping in the nuclear power plant, which results in the oxide mass loss from the inside of piping, the wall thinning, and even the pipe break. The pipe break induced by the E/C wear may cause costly plant repairs and personal injures. The measurement of pipe wall thickness is a useful tool for the power plant to prevent this incident. In this paper, CFD models are proposed to predict the local distributions of E/C wear sites, which include both the two-phase hydrodynamic model and the E/C models. The impacts of centrifugal and gravitational forces on the liquid droplet behaviors within the piping can be reasonably captured by the two-phase model. Coupled with these calculated flow characteristics, the E/C models can predicted the wear site distributions that show satisfactory agreement with the plant measurements. Therefore, the models proposed herein can assist in the pipe wall monitoring program for the nuclear power plant by way of concentrating the measuring point on the possible sites of severe E/C wear for the piping and reducing the measurement labor works

Quantification by qPCR of Pathobionts in Chronic Periodontitis: Development of Predictive Models of Disease Severity at Site-Specific Level

OpenAIRE

Tomás, Inmaculada; Regueira-Iglesias, Alba; López, Maria; Arias-Bujanda, Nora; Novoa, Lourdes; Balsa-Castro, Carlos; Tomás, Maria

2017-01-01

Currently, there is little evidence available on the development of predictive models for the diagnosis or prognosis of chronic periodontitis based on the qPCR quantification of subgingival pathobionts. Our objectives were to: (1) analyze and internally validate pathobiont-based models that could be used to distinguish different periodontal conditions at site-specific level within the same patient with chronic periodontitis; (2) develop nomograms derived from predictive models. Subgingival pl...

Locations of the three primary binding sites for long-chain fatty acids on bovine serum albumin

International Nuclear Information System (INIS)

Hamilton, J.A.; Era, S.; Bhamidipati, S.P.; Reed, R.G.

1991-01-01

Binding of 13 C-enriched oleic acid to bovine serum albumin and to three large proteolytic fragments of albumin - two complementary fragments corresponding to the two halved of albumin and one fragment corresponding to the carboxyl-terminal domain - yielded unique patterns of NMR resonances (chemical shifts and relative intensities) that were used to identify the locations of binding of the first 5 mol of oleic acid to the multidomain albumin molecule. The first 3 mol of oleic acid added to intact albumin generated three distinct NMR resonances as a result of simultaneous binding of oleic acid to three heterogeneous sites (primary sites). This distribution suggests albumin to be a less symmetrical binding molecule than theoretical models predict. This work also demonstrates the power of NMR for the study of microenvironments of individual fatty acid binding sites in specific domain

Unique Path Partitions

DEFF Research Database (Denmark)

Bessenrodt, Christine; Olsson, Jørn Børling; Sellers, James A.

2013-01-01

We give a complete classification of the unique path partitions and study congruence properties of the function which enumerates such partitions.......We give a complete classification of the unique path partitions and study congruence properties of the function which enumerates such partitions....

Hydrologic evaluation methodology for estimating water movement through the unsaturated zone at commercial low-level radioactive waste disposal sites

Energy Technology Data Exchange (ETDEWEB)

Meyer, P.D.; Rockhold, M.L.; Nichols, W.E.; Gee, G.W. [Pacific Northwest Lab., Richland, WA (United States)

1996-01-01

This report identifies key technical issues related to hydrologic assessment of water flow in the unsaturated zone at low-level radioactive waste (LLW) disposal facilities. In addition, a methodology for incorporating these issues in the performance assessment of proposed LLW disposal facilities is identified and evaluated. The issues discussed fall into four areas: estimating the water balance at a site (i.e., infiltration, runoff, water storage, evapotranspiration, and recharge); analyzing the hydrologic performance of engineered components of a facility; evaluating the application of models to the prediction of facility performance; and estimating the uncertainty in predicted facility performance. To illustrate the application of the methodology, two examples are presented. The first example is of a below ground vault located in a humid environment. The second example looks at a shallow land burial facility located in an arid environment. The examples utilize actual site-specific data and realistic facility designs. The two examples illustrate the issues unique to humid and arid sites as well as the issues common to all LLW sites. Strategies for addressing the analytical difficulties arising in any complex hydrologic evaluation of the unsaturated zone are demonstrated.

Hydrologic evaluation methodology for estimating water movement through the unsaturated zone at commercial low-level radioactive waste disposal sites

International Nuclear Information System (INIS)

Meyer, P.D.; Rockhold, M.L.; Nichols, W.E.; Gee, G.W.

1996-01-01

This report identifies key technical issues related to hydrologic assessment of water flow in the unsaturated zone at low-level radioactive waste (LLW) disposal facilities. In addition, a methodology for incorporating these issues in the performance assessment of proposed LLW disposal facilities is identified and evaluated. The issues discussed fall into four areas: estimating the water balance at a site (i.e., infiltration, runoff, water storage, evapotranspiration, and recharge); analyzing the hydrologic performance of engineered components of a facility; evaluating the application of models to the prediction of facility performance; and estimating the uncertainty in predicted facility performance. To illustrate the application of the methodology, two examples are presented. The first example is of a below ground vault located in a humid environment. The second example looks at a shallow land burial facility located in an arid environment. The examples utilize actual site-specific data and realistic facility designs. The two examples illustrate the issues unique to humid and arid sites as well as the issues common to all LLW sites. Strategies for addressing the analytical difficulties arising in any complex hydrologic evaluation of the unsaturated zone are demonstrated

A machine learning approach for predicting CRISPR-Cas9 cleavage efficiencies and patterns underlying its mechanism of action.

Science.gov (United States)

Abadi, Shiran; Yan, Winston X; Amar, David; Mayrose, Itay

2017-10-01

The adaptation of the CRISPR-Cas9 system as a genome editing technique has generated much excitement in recent years owing to its ability to manipulate targeted genes and genomic regions that are complementary to a programmed single guide RNA (sgRNA). However, the efficacy of a specific sgRNA is not uniquely defined by exact sequence homology to the target site, thus unintended off-targets might additionally be cleaved. Current methods for sgRNA design are mainly concerned with predicting off-targets for a given sgRNA using basic sequence features and employ elementary rules for ranking possible sgRNAs. Here, we introduce CRISTA (CRISPR Target Assessment), a novel algorithm within the machine learning framework that determines the propensity of a genomic site to be cleaved by a given sgRNA. We show that the predictions made with CRISTA are more accurate than other available methodologies. We further demonstrate that the occurrence of bulges is not a rare phenomenon and should be accounted for in the prediction process. Beyond predicting cleavage efficiencies, the learning process provides inferences regarding patterns that underlie the mechanism of action of the CRISPR-Cas9 system. We discover that attributes that describe the spatial structure and rigidity of the entire genomic site as well as those surrounding the PAM region are a major component of the prediction capabilities.

A machine learning approach for predicting CRISPR-Cas9 cleavage efficiencies and patterns underlying its mechanism of action.

Directory of Open Access Journals (Sweden)

Shiran Abadi

2017-10-01

Full Text Available The adaptation of the CRISPR-Cas9 system as a genome editing technique has generated much excitement in recent years owing to its ability to manipulate targeted genes and genomic regions that are complementary to a programmed single guide RNA (sgRNA. However, the efficacy of a specific sgRNA is not uniquely defined by exact sequence homology to the target site, thus unintended off-targets might additionally be cleaved. Current methods for sgRNA design are mainly concerned with predicting off-targets for a given sgRNA using basic sequence features and employ elementary rules for ranking possible sgRNAs. Here, we introduce CRISTA (CRISPR Target Assessment, a novel algorithm within the machine learning framework that determines the propensity of a genomic site to be cleaved by a given sgRNA. We show that the predictions made with CRISTA are more accurate than other available methodologies. We further demonstrate that the occurrence of bulges is not a rare phenomenon and should be accounted for in the prediction process. Beyond predicting cleavage efficiencies, the learning process provides inferences regarding patterns that underlie the mechanism of action of the CRISPR-Cas9 system. We discover that attributes that describe the spatial structure and rigidity of the entire genomic site as well as those surrounding the PAM region are a major component of the prediction capabilities.

Explorability and predictability of the paleozoic sedimentary sequence beneath the Bruce nuclear site

International Nuclear Information System (INIS)

Parmenter, A.; Jensen, M.; Crowe, R.; Raven, K.

2011-01-01

Ontario Power Generation (OPG) is proposing to develop a Deep Geologic Repository (DGR) for the long-term management of its Low and Intermediate Level Waste (L&ILW) at the Bruce nuclear site located in the Municipality of Kincardine, Ontario. A 4-year program of geoscientific studies to assess the suitability of the 850 m thick Palaeozoic age sedimentary sequence beneath the site to host the DGR was completed in 2010. The studies provide evidence of a geologic setting in which the DGR concept would be safely implemented at a nominal depth of 680 m within the argillaceous limestone of the Cobourg Formation. This paper describes the geologic framework of the Bruce nuclear site with a focus on illustrating the high degree of stratigraphic continuity and traceability at site-specific and regional scales within the Ordovician sediments proposed to host and enclose the DGR. As part of the site-specific studies, a program of deep drilling/coring (6 boreholes) and in-situ testing through the sedimentary sequence was completed from 4 drill sites situated beyond the DGR footprint, approximately 1 km apart. Core logging reveals that the stratigraphic sequence comprises 34 distinct bedrock formations/members/units consistent with the known regional stratigraphic framework. These layered sedimentary formations dip 0.6 o (~10 m/km) to the southwest with highly uniform thicknesses both at the site- and regional-scale, particularly, the Ordovician sediments, which vary on the order of metres. The occurrence of steeply-dipping faults within the sedimentary sequence is not revealed through surface outcrop fracture mapping, micro-seismic (M ≥ 1) monitoring, inclined borehole coring or intersection of hydrothermal type dolomitized reservoir systems. Potential fault structures, interpreted from a 2-D seismic survey, were targeted by angled boreholes which found no evidence for their existence. Formation specific continuity is also evidence by the lateral traceability of physical rock

A unique Fock quantization for fields in non-stationary spacetimes

International Nuclear Information System (INIS)

Cortez, Jerónimo; Marugán, Guillermo A. Mena; Olmedo, Javier; Velhinho, José M.

2010-01-01

In curved spacetimes, the lack of criteria for the construction of a unique quantization is a fundamental problem undermining the significance of the predictions of quantum field theory. Inequivalent quantizations lead to different physics. Recently, however, some uniqueness results have been obtained for fields in non-stationary settings. In particular, for vacua that are invariant under the background symmetries, a unitary implementation of the classical evolution suffices to pick up a unique Fock quantization in the case of Klein-Gordon fields with time-dependent mass, propagating in a static spacetime whose spatial sections are three-spheres. In fact, the field equation can be reinterpreted as describing the propagation in a Friedmann-Robertson-Walker spacetime after a suitable scaling of the field by a function of time. For this class of fields, we prove here an even stronger result about the Fock quantization: the uniqueness persists when one allows for linear time-dependent transformations of the field in order to account for a scaling by background functions. In total, paying attention to the dynamics, there exists a preferred choice of quantum field, and only one SO(4)-invariant Fock representation for it that respects the standard probabilistic interpretation along the evolution. The result has relevant implications e.g. in cosmology

Current status of the plant phosphorylation site database PhosPhAt and its use as a resource for molecular plant physiology.

Science.gov (United States)

Arsova, Borjana; Schulze, Waltraud X

2012-01-01

As the most studied post-translational modification, protein phosphorylation is analyzed in a growing number of proteomic experiments. These high-throughput approaches generate large datasets, from which specific spectrum-based information can be hard to find. In 2007, the PhosPhAt database was launched to collect and present Arabidopsis phosphorylation sites identified by mass spectrometry from and for the scientific community. At present, PhosPhAt 3.0 consolidates phosphoproteomics data from 19 published proteomic studies. Out of 5460 listed unique phosphoproteins, about 25% have been identified in at least two independent experimental setups. This is especially important when considering issues of false positive and false negative identification rates and data quality (Durek etal., 2010). This valuable data set encompasses over 13205 unique phosphopeptides, with unambiguous mapping to serine (77%), threonine (17%), and tyrosine (6%). Sorting the functional annotations of experimentally found phosphorylated proteins in PhosPhAt using Gene Ontology terms shows an over-representation of proteins in regulatory pathways and signaling processes. A similar distribution is found when the PhosPhAt predictor, trained on experimentally obtained plant phosphorylation sites, is used to predict phosphorylation sites for the Arabidopsis genome. Finally, the possibility to insert a protein sequence into the PhosPhAt predictor allows species independent use of the prediction resource. In practice, PhosPhAt also allows easy exploitation of proteomic data for design of further targeted experiments.

Uniqueness and non-uniqueness of semigroups generated by singular diffusion operators

CERN Document Server

Eberle, Andreas

1999-01-01

This book addresses both probabilists working on diffusion processes and analysts interested in linear parabolic partial differential equations with singular coefficients. The central question discussed is whether a given diffusion operator, i.e., a second order linear differential operator without zeroth order term, which is a priori defined on test functions over some (finite or infinite dimensional) state space only, uniquely determines a strongly continuous semigroup on a corresponding weighted Lp space. Particular emphasis is placed on phenomena causing non-uniqueness, as well as on the relation between different notions of uniqueness appearing in analytic and probabilistic contexts.

Inverse modeling with RZWQM2 to predict water quality

Science.gov (United States)

Nolan, Bernard T.; Malone, Robert W.; Ma, Liwang; Green, Christopher T.; Fienen, Michael N.; Jaynes, Dan B.

2011-01-01

This chapter presents guidelines for autocalibration of the Root Zone Water Quality Model (RZWQM2) by inverse modeling using PEST parameter estimation software (Doherty, 2010). Two sites with diverse climate and management were considered for simulation of N losses by leaching and in drain flow: an almond [Prunus dulcis (Mill.) D.A. Webb] orchard in the San Joaquin Valley, California and the Walnut Creek watershed in central Iowa, which is predominantly in corn (Zea mays L.)–soybean [Glycine max (L.) Merr.] rotation. Inverse modeling provides an objective statistical basis for calibration that involves simultaneous adjustment of model parameters and yields parameter confidence intervals and sensitivities. We describe operation of PEST in both parameter estimation and predictive analysis modes. The goal of parameter estimation is to identify a unique set of parameters that minimize a weighted least squares objective function, and the goal of predictive analysis is to construct a nonlinear confidence interval for a prediction of interest by finding a set of parameters that maximizes or minimizes the prediction while maintaining the model in a calibrated state. We also describe PEST utilities (PAR2PAR, TSPROC) for maintaining ordered relations among model parameters (e.g., soil root growth factor) and for post-processing of RZWQM2 outputs representing different cropping practices at the Iowa site. Inverse modeling provided reasonable fits to observed water and N fluxes and directly benefitted the modeling through: (i) simultaneous adjustment of multiple parameters versus one-at-a-time adjustment in manual approaches; (ii) clear indication by convergence criteria of when calibration is complete; (iii) straightforward detection of nonunique and insensitive parameters, which can affect the stability of PEST and RZWQM2; and (iv) generation of confidence intervals for uncertainty analysis of parameters and model predictions. Composite scaled sensitivities, which

Granulomatous slack skin syndrome: Report of a unique case.

Science.gov (United States)

Maheswari, S Uma; Sampath, V; Ramesh, A

2018-01-01

Granulomatous slack skin syndrome is a rare variant of cutaneous T-cell lymphoma (mycosis fungoides). It is characterized clinically by redundant skin folds, which show a predilection towards flexural areas such as the axilla and the groin. Histologically, it shows a granulomatous T-cell infiltrate and loss of elastic tissue. It has an indolent but progressive course; and is usually refractory to treatment. We report a unique case of slack skin syndrome, sparing the classical sites with rapid and unusual involvement of non-intertriginous areas.

Unique issues concerning ''placement'' vs ''movement'' of contaminated soils at ORNL's CERCLA sites

International Nuclear Information System (INIS)

Greer, J.K. Jr.; Schrof, C.A.

1992-01-01

At Oak Ridge National Laboratory, which is owned and operated by the US Department of Energy (DOE), there are several areas where hazardous wastes and/or radioactive materials have been placed in shallow land burial trenches or ''auger'' holes for disposal. Since Oak Ridge Reservation (ORR) has been placed on the National Priority List (NPL) by the US Environmental Protection Agency (EPA), the Comprehensive Environmental Response, Compensation, and Liability Act of 1980 (CERCLA) applies to waste disposal sites at ORNL. Under CERCLA, the RCRA regulations, pertaining to the LDRs, apply to CERCLA activities if the regulations are deemed ''applicable or relevant and appropriate'' (ARARS) by the lead agency or by the EPA. This report discusses the following issue: Under what conditions will contaminated soil and debris generated at a Superfund site be subject to the Resource Conservation and Recovery Act (RCRA) land disposal restrictions (LDRs) treatment standards?

Examination of the site amplification factor of OBS and their application to magnitude estimation and ground-motion prediction for EEW

Science.gov (United States)

Hayashimoto, N.; Hoshiba, M.

2013-12-01

1. Introduction Ocean bottom seismograph (OBS) is useful for making Earthquake Early Warning (EEW) earlier. However, careful handling of these data is required because the installation environment of OBSs may be different from that of land stations. Site amplification factor is an important factor to estimate the magnitudes, and to predict ground motions (e.g. seismic intensity) in EEW. In this presentation, we discuss the site amplification factor of OBS in the Tonankai area of Japan from these two points of view. 2. Examination of magnitude correction of OBS In the EEW of JMA, the magnitude is estimated from the maximum amplitude of the displacement in real time. To provide the fast magnitude estimation, the magnitude-estimation algorithm switches from the P to S formula (Meew(P) to Meew(S)) depending on the expected S-phase arrival (Kamigaichi,2004). To estimate the magnitude correction for OBS, we determine Meew(P) and Meew(S) at OBSs and compare them with JMA magnitude (Mjma). We find Meew(S) at OBS is generally larger than Mjma by approximately 0.6. The slight differences of spatial distribution of Meew(S) amplification are also found among other OBSs. From the numerical simulations, Nakamura et al. (MGR,submitted) pointed out that the oceanic layer and the low-velocity sediment layers causes the large amplifications in low frequency range (0.1-0.2Hz) at OBSs. We conclude that the site effect of OBS characterized by such a low velocity sediment layers causes those amplification of Magnitude. 3. The frequency-dependent site factor of OBS estimated from Fourier spectrum ratio and their application for prediction of seismic intensity of land station We compare Fourier spectra of S-wave portion on OBSs with those on adjacent land stations. Station pair whose distance is smaller than 50 km is analyzed, and we obtain that spectral ratio of land station (MIEH05 of the KiK-net/NIED) to OBS (KMA01 of the DONET/JAMSTEC) is 5-20 for frequencies 10-20Hz for both

Wind resource modelling for micro-siting - Validation at a 60-MW wind farm site

Energy Technology Data Exchange (ETDEWEB)

Hansen, J C; Gylling Mortensen, N [Risoe National Lab., Wind Energy and Atmospheric Physics Dept., Roskilde (Denmark); Said, U S [New and Renewable Energy Authority, Cairo (Egypt)

1999-03-01

This paper investigates and validates the applicability of the WAsP-model for layout optimization and micro-siting of wind turbines at a given site for a 60-MW wind farm at Zafarana at the Gulf of Suez in Egypt. Previous investigations show large gradients in the wind climate within the area. For the design and optimization of the wind farm it was found necessary to verify the WAsP extrapolation of wind atlas results from 2 existing meteorological masts located 5 and 10 km, respectively, from the wind farm site. On-site measurements at the 3.5 x 3.5 km{sup 2} wind farm site in combination with 7 years of near-site wind atlas measurements offer significant amounts of data for verification of wind conditions for micro-siting. Wind speeds, wind directions, turbulence intensities and guests in 47.5 m a.g.l. have been measured at 9 locations across the site. Additionally, one of the site masts is equipped as a reference mast, measuring both vertical profiles of wind speed and temperature as well as air pressure and temperature. The exercise is further facilitated by the fact that winds are highly uni-directional; the north direction accounting for 80-90% of the wind resource. The paper presents comparisons of 5 months of on-site measurements and modeled predictions from 2 existing meteorological masts located at distances of 5 and 10 km, respectively, from the wind farm site. Predictions based on terrain descriptions of the Wind Atlas for the Gulf of Suez 1991-95 showed over-predictions of wind speeds of 4-10%. With calibrated terrain descriptions, made based on measured data and a re-visit to critical parts of the terrain, the average prediction error of wind speeds was reduced to about 1%. These deviations are smaller than generally expected for such wind resource modeling, clearly documenting the validity of using WAsP modeling for micro-siting and layout optimization of the wind farm. (au)

Hybrid model predictive control of a residential HVAC system with on-site thermal energy generation and storage

International Nuclear Information System (INIS)

Fiorentini, Massimo; Wall, Josh; Ma, Zhenjun; Braslavsky, Julio H.; Cooper, Paul

2017-01-01

Highlights: • A comprehensive approach to managing thermal energy in residential buildings. • Solar-assisted HVAC system with on-site energy generation and storage. • Mixed logic-dynamical building model identified using experimental data. • Design and implementation of a logic-dynamical model predictive control strategy. • MPC applied to the Net-Zero Energy house winner of the Solar Decathlon China 2013. - Abstract: This paper describes the development, implementation and experimental investigation of a Hybrid Model Predictive Control (HMPC) strategy to control solar-assisted heating, ventilation and air-conditioning (HVAC) systems with on-site thermal energy generation and storage. A comprehensive approach to the thermal energy management of a residential building is presented to optimise the scheduling of the available thermal energy resources to meet a comfort objective. The system has a hybrid nature with both continuous variables and discrete, logic-driven operating modes. The proposed control strategy is organized in two hierarchical levels. At the high-level, an HMPC controller with a 24-h prediction horizon and a 1-h control step is used to select the operating mode of the HVAC system. At the low-level, each operating mode is optimised using a 1-h rolling prediction horizon with a 5-min control step. The proposed control strategy has been practically implemented on the Building Management and Control System (BMCS) of a Net Zero-Energy Solar Decathlon house. This house features a sophisticated HVAC system comprising of an air-based photovoltaic thermal (PVT) collector and a phase change material (PCM) thermal storage integrated with the air-handling unit (AHU) of a ducted reverse-cycle heat pump system. The simulation and experimental results demonstrated the high performance achievable using an HMPC approach to optimising complex multimode HVAC systems in residential buildings, illustrating efficient selection of the appropriate operating modes

Site-specific strong ground motion prediction using 2.5-D modelling

Science.gov (United States)

Narayan, J. P.

2001-08-01

An algorithm was developed using the 2.5-D elastodynamic wave equation, based on the displacement-stress relation. One of the most significant advantages of the 2.5-D simulation is that the 3-D radiation pattern can be generated using double-couple point shear-dislocation sources in the 2-D numerical grid. A parsimonious staggered grid scheme was adopted instead of the standard staggered grid scheme, since this is the only scheme suitable for computing the dislocation. This new 2.5-D numerical modelling avoids the extensive computational cost of 3-D modelling. The significance of this exercise is that it makes it possible to simulate the strong ground motion (SGM), taking into account the energy released, 3-D radiation pattern, path effects and local site conditions at any location around the epicentre. The slowness vector (py) was used in the supersonic region for each layer, so that all the components of the inertia coefficient are positive. The double-couple point shear-dislocation source was implemented in the numerical grid using the moment tensor components as the body-force couples. The moment per unit volume was used in both the 3-D and 2.5-D modelling. A good agreement in the 3-D and 2.5-D responses for different grid sizes was obtained when the moment per unit volume was further reduced by a factor equal to the finite-difference grid size in the case of the 2.5-D modelling. The components of the radiation pattern were computed in the xz-plane using 3-D and 2.5-D algorithms for various focal mechanisms, and the results were in good agreement. A comparative study of the amplitude behaviour of the 3-D and 2.5-D wavefronts in a layered medium reveals the spatial and temporal damped nature of the 2.5-D elastodynamic wave equation. 3-D and 2.5-D simulated responses at a site using a different strike direction reveal that strong ground motion (SGM) can be predicted just by rotating the strike of the fault counter-clockwise by the same amount as the azimuth of

Predictors of the long-term retention of a unique experience in young children

NARCIS (Netherlands)

Wessel, Ineke; Jansen, Josephien; Lammertink, Sophie; Nanninga, Eline

2016-01-01

We explored the predictive value of age, language ability and rehearsal for performance on various indices of long-term (episodic) memory in early childhood. Preschoolers engaged in a unique treasure-hunt experience. One year later, we tested recall, pictorial recognition and temporal ordering of

Evaluation of three state-of-the-art metabolite prediction software packages (Meteor, MetaSite, and StarDrop) through independent and synergistic use.

Science.gov (United States)

T'jollyn, H; Boussery, K; Mortishire-Smith, R J; Coe, K; De Boeck, B; Van Bocxlaer, J F; Mannens, G

2011-11-01

The aim of this study was to evaluate three different metabolite prediction software packages (Meteor, MetaSite, and StarDrop) with respect to their ability to predict loci of metabolism and suggest relative proportions of metabolites. A chemically diverse test set of 22 compounds, for which in vivo human mass balance studies and metabolic schemes were available, was used as basis for the evaluation. Each software package was provided with structures of the parent compounds, and predicted metabolites were compared with experimentally determined human metabolites. The evaluation consisted of two parts. First, different settings within each software package were investigated and the software was evaluated using those settings determined to give the best prediction. Second, the three different packages were combined using the optimized settings to see whether a synergistic effect concerning the overall metabolism prediction could be established. The performance of the software was scored for both sensitivity and precision, taking into account the capabilities/limitations of the particular software. Varying results were obtained for the individual packages. Meteor showed a general tendency toward overprediction, and this led to a relatively low precision (∼35%) but high sensitivity (∼70%). MetaSite and StarDrop both exhibited a sensitivity and precision of ∼50%. By combining predictions obtained with the different packages, we found that increased precision can be obtained. We conclude that the state-of-the-art individual metabolite prediction software has many advantageous features but needs refinement to obtain acceptable prediction profiles. Synergistic use of different software packages could prove useful.

OGT (O-GlcNAc Transferase) Selectively Modifies Multiple Residues Unique to Lamin A.

Science.gov (United States)

Simon, Dan N; Wriston, Amanda; Fan, Qiong; Shabanowitz, Jeffrey; Florwick, Alyssa; Dharmaraj, Tejas; Peterson, Sherket B; Gruenbaum, Yosef; Carlson, Cathrine R; Grønning-Wang, Line M; Hunt, Donald F; Wilson, Katherine L

2018-05-17

The LMNA gene encodes lamins A and C with key roles in nuclear structure, signaling, gene regulation, and genome integrity. Mutations in LMNA cause over 12 diseases ('laminopathies'). Lamins A and C are identical for their first 566 residues. However, they form separate filaments in vivo, with apparently distinct roles. We report that lamin A is β- O -linked N -acetylglucosamine- (O -GlcNAc)-modified in human hepatoma (Huh7) cells and in mouse liver. In vitro assays with purified O -GlcNAc transferase (OGT) enzyme showed robust O -GlcNAcylation of recombinant mature lamin A tails (residues 385⁻646), with no detectable modification of lamin B1, lamin C, or 'progerin' (Δ50) tails. Using mass spectrometry, we identified 11 O -GlcNAc sites in a 'sweet spot' unique to lamin A, with up to seven sugars per peptide. Most sites were unpredicted by current algorithms. Double-mutant (S612A/T643A) lamin A tails were still robustly O -GlcNAc-modified at seven sites. By contrast, O -GlcNAcylation was undetectable on tails bearing deletion Δ50, which causes Hutchinson⁻Gilford progeria syndrome, and greatly reduced by deletion Δ35. We conclude that residues deleted in progeria are required for substrate recognition and/or modification by OGT in vitro. Interestingly, deletion Δ35, which does not remove the majority of identified O -GlcNAc sites, does remove potential OGT-association motifs (lamin A residues 622⁻625 and 639⁻645) homologous to that in mouse Tet1. These biochemical results are significant because they identify a novel molecular pathway that may profoundly influence lamin A function. The hypothesis that lamin A is selectively regulated by OGT warrants future testing in vivo, along with two predictions: genetic variants may contribute to disease by perturbing OGT-dependent regulation, and nutrient or other stresses might cause OGT to misregulate wildtype lamin A.

Prediction of evacuation time for emergency planning zone of Uljin nuclear site

International Nuclear Information System (INIS)

Jeon, In Young; Lee, Jai Ki

2002-01-01

The time for evacuation of residents in Emergency Planning Zone (EPZ) of Uljin nuclear site in case of a radiological emergency was estimated with traffic analysis. Evacuees were classified into 4 groups by considering population density, local jurisdictions, and whether they are residents or transients. The survey to investigate the behavioral characteristics of the residents was made for 200 households and included a hypothetical scenario explaining the accident situation and questions such as dwelling place, time demand for evacuation preparation, transportation means for evacuation, sheltering place, and evacuation direction. The microscopic traffic simulation model, CORSIM, was used to simulate the behavior of evacuating vehicles on networks. The results showed that the evacuation time required for total vehicles to move out from EPZ took longer in the daytime than at night in spite that the delay times at intersections were longer at night than in the daytime. This was analyzed due to the differences of the trip generation time distribution. To validate whether the CORSIM model can appropriately simulate the congested traffic phenomena assumable in case of emergency, a benchmark study was conducted at an intersection without an actuated traffic signal near Uljin site during the traffic peak-time in the morning. This study indicated that the predicted output by the CORSIM model was in good agreement with the observed data, satisfying the purpose of this study

Skin sites to predict deep-body temperature while wearing firefighters' personal protective equipment during periodical changes in air temperature.

Science.gov (United States)

Kim, Siyeon; Lee, Joo-Young

2016-04-01

The aim of this study was to investigate stable and valid measurement sites of skin temperatures as a non-invasive variable to predict deep-body temperature while wearing firefighters' personal protective equipment (PPE) during air temperature changes. Eight male firefighters participated in an experiment which consisted of 60-min exercise and 10-min recovery while wearing PPE without self-contained breathing apparatus (7.75 kg in total PPE mass). Air temperature was periodically fluctuated from 29.5 to 35.5 °C with an amplitude of 6 °C. Rectal temperature was chosen as a deep-body temperature, and 12 skin temperatures were recorded. The results showed that the forehead and chest were identified as the most valid sites to predict rectal temperature (R(2) = 0.826 and 0.824, respectively) in an environment with periodically fluctuated air temperatures. This study suggests that particular skin temperatures are valid as a non-invasive variable when predicting rectal temperature of an individual wearing PPE in changing ambient temperatures. Practitioner Summary: This study should offer assistance for developing a more reliable indirect indicating system of individual heat strain for firefighters in real time, which can be used practically as a precaution of firefighters' heat-related illness and utilised along with physiological monitoring.

Structural Fingerprints of Transcription Factor Binding Site Regions

Directory of Open Access Journals (Sweden)

Peter Willett

2009-03-01

Full Text Available Fourier transforms are a powerful tool in the prediction of DNA sequence properties, such as the presence/absence of codons. We have previously compiled a database of the structural properties of all 32,896 unique DNA octamers. In this work we apply Fourier techniques to the analysis of the structural properties of human chromosomes 21 and 22 and also to three sets of transcription factor binding sites within these chromosomes. We find that, for a given structural property, the structural property power spectra of chromosomes 21 and 22 are strikingly similar. We find common peaks in their power spectra for both Sp1 and p53 transcription factor binding sites. We use the power spectra as a structural fingerprint and perform similarity searching in order to find transcription factor binding site regions. This approach provides a new strategy for searching the genome data for information. Although it is difficult to understand the relationship between specific functional properties and the set of structural parameters in our database, our structural fingerprints nevertheless provide a useful tool for searching for function information in sequence data. The power spectrum fingerprints provide a simple, fast method for comparing a set of functional sequences, in this case transcription factor binding site regions, with the sequences of whole chromosomes. On its own, the power spectrum fingerprint does not find all transcription factor binding sites in a chromosome, but the results presented here show that in combination with other approaches, this technique will improve the chances of identifying functional sequences hidden in genomic data.

Predictions of tracer transport in interwell tracer tests at the C-Hole complex. Yucca Mountain site characterization project report milestone 4077

International Nuclear Information System (INIS)

Reimus, P.W.

1996-09-01

This report presents predictions of tracer transport in interwell tracer tests that are to be conducted at the C-Hole complex at the Nevada Test Site on behalf of the Yucca Mountain Site Characterization Project. The predictions are used to make specific recommendations about the manner in which the tracer test should be conducted to best satisfy the needs of the Project. The objective of he tracer tests is to study flow and species transport under saturated conditions in the fractured tuffs near Yucca Mountain, Nevada, the site of a potential high-level nuclear waste repository. The potential repository will be located in the unsaturated zone within Yucca Mountain. The saturated zone beneath and around the mountain represents the final barrier to transport to the accessible environment that radionuclides will encounter if they breach the engineered barriers within the repository and the barriers to flow and transport provided by the unsaturated zone. Background information on the C-Holes is provided in Section 1.1, and the planned tracer testing program is discussed in Section 1.2

KatB, a cyanobacterial Mn-catalase with unique active site configuration: Implications for enzyme function.

Science.gov (United States)

Bihani, Subhash C; Chakravarty, Dhiman; Ballal, Anand

2016-04-01

Manganese catalases (Mn-catalases), a class of H2O2 detoxifying proteins, are structurally and mechanistically distinct from the commonly occurring catalases, which contain heme. Active site of Mn-catalases can serve as template for the synthesis of catalase mimetics for therapeutic intervention in oxidative stress related disorders. However, unlike the heme catalases, structural aspects of Mn-catalases remain inadequately explored. The genome of the ancient cyanobacterium Anabaena PCC7120, shows the presence of two Mn-catalases, KatA and KatB. Here, we report the biochemical and structural characterization of KatB. The KatB protein (with a C-terminal his-tag) was over-expressed in Escherichia coli and purified by affinity chromatography. On the addition of Mn(2+) to the E. coli growth medium, a substantial increase in production of the soluble KatB protein was observed. The purified KatB protein was an efficient catalase, which was relatively insensitive to inhibition by azide. Crystal structure of KatB showed a hexameric assembly with four-helix bundle fold, characteristic of the Ferritin-like superfamily. With canonical Glu4His2 coordination geometry and two terminal water ligands, the KatB active site was distinctly different from that of other Mn-catalases. Interestingly, the KatB active site closely resembled the active sites of ruberythrin/bacterioferritin, bi-iron members of the Ferritin-like superfamily. The KatB crystal structure provided fundamental insights into the evolutionary relationship within the Ferritin-like superfamily and further showed that Mn-catalases can be sub-divided into two groups, each with a distinct active site configuration. Copyright © 2016 Elsevier Inc. All rights reserved.

On multi-site damage identification using single-site training data

Science.gov (United States)

Barthorpe, R. J.; Manson, G.; Worden, K.

2017-11-01

This paper proposes a methodology for developing multi-site damage location systems for engineering structures that can be trained using single-site damaged state data only. The methodology involves training a sequence of binary classifiers based upon single-site damage data and combining the developed classifiers into a robust multi-class damage locator. In this way, the multi-site damage identification problem may be decomposed into a sequence of binary decisions. In this paper Support Vector Classifiers are adopted as the means of making these binary decisions. The proposed methodology represents an advancement on the state of the art in the field of multi-site damage identification which require either: (1) full damaged state data from single- and multi-site damage cases or (2) the development of a physics-based model to make multi-site model predictions. The potential benefit of the proposed methodology is that a significantly reduced number of recorded damage states may be required in order to train a multi-site damage locator without recourse to physics-based model predictions. In this paper it is first demonstrated that Support Vector Classification represents an appropriate approach to the multi-site damage location problem, with methods for combining binary classifiers discussed. Next, the proposed methodology is demonstrated and evaluated through application to a real engineering structure - a Piper Tomahawk trainer aircraft wing - with its performance compared to classifiers trained using the full damaged-state dataset.

The method of selecting an integrated development territory for the high-rise unique constructions

Science.gov (United States)

Sheina, Svetlana; Shevtsova, Elina; Sukhinin, Alexander; Priss, Elena

2018-03-01

On the basis of data provided by the Department of architecture and urban planning of the city of Rostov-on-don, the problem of the choice of the territory for complex development that will be in priority for the construction of high-rise and unique buildings is solved. The objective of the study was the development of a methodology for selection of the area and the implementation of the proposed method on the example of evaluation of four-territories complex development. The developed method along with standard indicators of complex evaluation considers additional indicators that assess the territory from the position of high-rise unique building. The final result of the study is the rankings of the functional priority areas that takes into account the construction of both residential and public and business objects of unique high-rise construction. The use of the developed methodology will allow investors and customers to assess the investment attractiveness of the future unique construction project on the proposed site.

Relationship between water temperature predictability and aquatic ...

African Journals Online (AJOL)

Macroinvertebrate taxonomic turnover across seasons was higher for sites having lower water temperature predictability values than for sites with higher predictability, while temporal partitioning was greater at sites with greater temperature variability. Macroinvertebrate taxa responded in a predictable manner to changes in ...

Use of the Hazard Prediction and Assessment Capability (HPAC) at the Savannah River Site

International Nuclear Information System (INIS)

BUCKLEY, ROBERT

2004-01-01

This report provides background information on the implementation of the Hazard Prediction and Assessment Capability (HPAC) software package at the Savannah River Site for atmospheric modeling. Developed by the Defense Threat Reduction Agency (DTRA), HPAC is actually a suite of models that allows for various modes of release of radiological, chemical and biological agents, generates interpolated meteorological data fields based on inputted meteorology, and transports the material using a tested transport and diffusion model. A discussion of meteorological data availability for direct use by HPAC is given, and is important for applications to emergency response. An evaluation of the data input methodology for a release from SRS is examined, as well as an application to the World Trade Center attacks in New York City in September 2001. Benefits of the newer versions of HPAC now in use are then discussed. These include access to more meteorological data sources and improved graphical cap abilities. The HPAC software package is another tool to help the Atmospheric Technologies Group (ATG) provide atmospheric transport and dispersion predictions in the event of hazardous atmospheric releases

Prediction of Water Binding to Protein Hydration Sites with a Discrete, Semiexplicit Solvent Model.

Science.gov (United States)

Setny, Piotr

2015-12-08

Buried water molecules are ubiquitous in protein structures and are found at the interface of most protein-ligand complexes. Determining their distribution and thermodynamic effect is a challenging yet important task, of great of practical value for the modeling of biomolecular structures and their interactions. In this study, we present a novel method aimed at the prediction of buried water molecules in protein structures and estimation of their binding free energies. It is based on a semiexplicit, discrete solvation model, which we previously introduced in the context of small molecule hydration. The method is applicable to all macromolecular structures described by a standard all-atom force field, and predicts complete solvent distribution within a single run with modest computational cost. We demonstrate that it indicates positions of buried hydration sites, including those filled by more than one water molecule, and accurately differentiates them from sterically accessible to water but void regions. The obtained estimates of water binding free energies are in fair agreement with reference results determined with the double decoupling method.

Cognitive Prediction of Reading, Math, and Attention: Shared and Unique Influences.

Science.gov (United States)

Peterson, Robin L; Boada, Richard; McGrath, Lauren M; Willcutt, Erik G; Olson, Richard K; Pennington, Bruce F

The current study tested a multiple-cognitive predictor model of word reading, math ability, and attention in a community-based sample of twins ages 8 to 16 years ( N = 636). The objective was to identify cognitive predictors unique to each skill domain as well as cognitive predictors shared among skills that could help explain their overlap and thus help illuminate the basis for comorbidity of related disorders (reading disability, math disability, and attention deficit hyperactivity disorder). Results indicated that processing speed contributes to the overlap between reading and attention as well as math and attention, whereas verbal comprehension contributes to the overlap between reading and math. There was no evidence that executive functioning skills help account for covariation among these skill domains. Instead, specific executive functions differentially related to certain outcomes (i.e., working memory to math and inhibition to attention). We explored whether the model varied in younger versus older children and found only minor differences. Results are interpreted within the context of the multiple deficit framework for neurodevelopmental disorders.

Predicting Nitrate Transport under Future Climate Scenarios beneath the Nebraska Management Systems Evaluation Area (MSEA) site

Science.gov (United States)

Li, Y.; Akbariyeh, S.; Gomez Peña, C. A.; Bartlet-Hunt, S.

2017-12-01

Understanding the impacts of future climate change on soil hydrological processes and solute transport is crucial to develop appropriate strategies to minimize adverse impacts of agricultural activities on groundwater quality. The goal of this work is to evaluate the direct effects of climate change on the fate and transport of nitrate beneath a center-pivot irrigated corn field in Nebraska Management Systems Evaluation Area (MSEA) site. Future groundwater recharge rate and actual evapotranspiration rate were predicted based on an inverse modeling approach using climate data generated by Weather Research and Forecasting (WRF) model under the RCP 8.5 scenario, which was downscaled from global CCSM4 model to a resolution of 24 by 24 km2. A groundwater flow model was first calibrated based on historical groundwater table measurement and was then applied to predict future groundwater table in the period 2057-2060. Finally, predicted future groundwater recharge rate, actual evapotranspiration rate, and groundwater level, together with future precipitation data from WRF, were used in a three-dimensional (3D) model, which was validated based on rich historic data set collected from 1993-1996, to predict nitrate concentration in soil and groundwater from the year 2057 to 2060. Future groundwater recharge was found to be decreasing in the study area compared to average groundwater recharge data from the literature. Correspondingly, groundwater elevation was predicted to decrease (1 to 2 ft) over the five years of simulation. Predicted higher transpiration data from climate model resulted in lower infiltration of nitrate concentration in subsurface within the root zone.

Novel structures of oxygen adsorbed on a Zr(0001) surface predicted from first principles

Energy Technology Data Exchange (ETDEWEB)

Gao, Bo [State Key Laboratory of Superhard Materials, Jilin University, Changchun, 130012 (China); Beijing computational science research center, Beijing,100084 (China); Wang, Jianyun [State Key Laboratory of Superhard Materials, Jilin University, Changchun, 130012 (China); Lv, Jian [State Key Laboratory of Superhard Materials, Jilin University, Changchun, 130012 (China); College of Materials Science and Engineering, Jilin University, Changchun, 130012 (China); Gao, Xingyu [Laboratory of Computational Physics, Institute of Applied Physics and Computational Mathematics, Beijing, 100088 (China); CAEP Software Center for High Performance Numerical Simulation, Beijing, 100088 (China); Zhao, Yafan [CAEP Software Center for High Performance Numerical Simulation, Beijing, 100088 (China); Wang, Yanchao, E-mail: wyc@calypso.cn [State Key Laboratory of Superhard Materials, Jilin University, Changchun, 130012 (China); Beijing computational science research center, Beijing,100084 (China); College of Materials Science and Engineering, Jilin University, Changchun, 130012 (China); Song, Haifeng, E-mail: song_haifeng@iapcm.ac.cn [Laboratory of Computational Physics, Institute of Applied Physics and Computational Mathematics, Beijing, 100088 (China); CAEP Software Center for High Performance Numerical Simulation, Beijing, 100088 (China); Ma, Yanming [State Key Laboratory of Superhard Materials, Jilin University, Changchun, 130012 (China); Beijing computational science research center, Beijing,100084 (China)

2017-01-30

Highlights: • Two stable structures of O adsorbed on a Zr(0001) surface are predicted with SLAM. • A stable structure of O adsorbed on a Zr(0001) surface is proposed with MLAM. • The calculated work function change is agreement with experimental value. - Abstract: The structures of O atoms adsorbed on a metal surface influence the metal properties significantly. Thus, studying O chemisorption on a Zr surface is of great interest. We investigated O adsorption on a Zr(0001) surface using our newly developed structure-searching method combined with first-principles calculations. A novel structural prototype with a unique combination of surface face-centered cubic (SFCC) and surface hexagonal close-packed (SHCP) O adsorption sites was predicted using a single-layer adsorption model (SLAM) for a 0.5 and 1.0 monolayer (ML) O coverage. First-principles calculations based on the SLAM revealed that the new predicted structures are energetically favorable compared with the well-known SFCC structures for a low O coverage (0.5 and 1.0 ML). Furthermore, on basis of our predicted SFCC + SHCP structures, a new structure within multi-layer adsorption model (MLAM) was proposed to be more stable at the O coverage of 1.0 ML, in which adsorbed O atoms occupy the SFCC + SHCP sites and the substitutional octahedral sites. The calculated work functions indicate that the SFCC + SHCP configuration has the lowest work function of all known structures at an O coverage of 0.5 ML within the SLAM, which agrees with the experimental trend of work function with variation in O coverage.

The need for unique risk adjustment for surgical site infections at a high-volume, tertiary care center with inherent high-risk colorectal procedures.

Science.gov (United States)

Gorgun, E; Benlice, C; Hammel, J; Hull, T; Stocchi, L

2017-08-01

The aim of the present study was to create a unique risk adjustment model for surgical site infection (SSI) in patients who underwent colorectal surgery (CRS) at the Cleveland Clinic (CC) with inherent high risk factors by using a nationwide database. The American College of Surgeons National Surgical Quality Improvement Program database was queried to identify patients who underwent CRS between 2005 and 2010. Initially, CC cases were identified from all NSQIP data according to case identifier and separated from the other NSQIP centers. Demographics, comorbidities, and outcomes were compared. Logistic regression analyses were used to assess the association between SSI and center-related factors. A total of 70,536 patients met the inclusion criteria and underwent CRS, 1090 patients (1.5%) at the CC and 69,446 patients (98.5%) at other centers. Male gender, work-relative value unit, diagnosis of inflammatory bowel disease, pouch formation, open surgery, steroid use, and preoperative radiotherapy rates were significantly higher in the CC cases. Overall morbidity and individual postoperative complication rates were found to be similar in the CC and other centers except for the following: organ-space SSI and sepsis rates (higher in the CC cases); and pneumonia and ventilator dependency rates (higher in the other centers). After covariate adjustment, the estimated degree of difference between the CC and other institutions with respect to organ-space SSI was reduced (OR 1.38, 95% CI 1.08-1.77). The unique risk adjustment strategy may provide center-specific comprehensive analysis, especially for hospitals that perform inherently high-risk procedures. Higher surgical complexity may be the reason for increased SSI rates in the NSQIP at tertiary care centers.

ARAC: A unique command and control resource

Energy Technology Data Exchange (ETDEWEB)

Bradley, M.M.; Baskett, R.L.; Ellis, J.S. [and others

1996-04-01

The Atmospheric Release Advisory Capability (ARAC) at Lawrence Livermore National Laboratory (LLNL) is a centralized federal facility designed to provide real-time, world-wide support to military and civilian command and control centers by predicting the impacts of inadvertent or intentional releases of nuclear, biological, or chemical materials into the atmosphere. ARAC is a complete response system consisting of highly trained and experienced personnel, continually updated computer models, redundant data collection systems, and centralized and remote computer systems. With over 20 years of experience responding to domestic and international incidents, strong linkages with the Department of Defense, and the ability to conduct classified operations, ARAC is a unique command and control resource.

ARAC: A unique command and control resource

International Nuclear Information System (INIS)

Bradley, M.M.; Baskett, R.L.; Ellis, J.S.

1996-04-01

The Atmospheric Release Advisory Capability (ARAC) at Lawrence Livermore National Laboratory (LLNL) is a centralized federal facility designed to provide real-time, world-wide support to military and civilian command and control centers by predicting the impacts of inadvertent or intentional releases of nuclear, biological, or chemical materials into the atmosphere. ARAC is a complete response system consisting of highly trained and experienced personnel, continually updated computer models, redundant data collection systems, and centralized and remote computer systems. With over 20 years of experience responding to domestic and international incidents, strong linkages with the Department of Defense, and the ability to conduct classified operations, ARAC is a unique command and control resource

Final predictions of ambient conditions along the east-west cross drift using the 3-D UZ site-scale model. Level 4 milestone SP33ABM4

International Nuclear Information System (INIS)

Ritcey, A.C.; Sonnenthal, E.L.; Wu, Y.S.; Haukwa, C.; Bodvarsson, G.S.

1998-01-01

In 1998, the Yucca Mountain Site Characterization Project (YMP) is expected to continue construction of an East-West Cross Drift. The 5-meter diameter drift will extend from the North Ramp of the Exploratory Studies Facility (ESF), near Station 19+92, southwest through the repository block, and over to and through the Solitario Canyon Fault. This drift is part of a program designed to enhance characterization of Yucca Mountain and to complement existing surface-based and ESF testing studies. The objective of this milestone is to use the three-dimensional (3-D) unsaturated zone (UZ) site-scale model to predict ambient conditions along the East-West Cross Drift. These predictions provide scientists and engineers with a priori information that can support design and construction of the East-West Cross Drift and associated testing program. The predictions also provide, when compared with data collected after drift construction, an opportunity to test and verify the calibration of the 3-D UZ site-scale model

Structure of the first representative of Pfam family PF04016 (DUF364) reveals enolase and Rossmann-like folds that combine to form a unique active site with a possible role in heavy-metal chelation

International Nuclear Information System (INIS)

Miller, Mitchell D.; Aravind, L.; Bakolitsa, Constantina; Rife, Christopher L.; Carlton, Dennis; Abdubek, Polat; Astakhova, Tamara; Axelrod, Herbert L.; Chiu, Hsiu-Ju; Clayton, Thomas; Deller, Marc C.; Duan, Lian; Feuerhelm, Julie; Grant, Joanna C.; Han, Gye Won; Jaroszewski, Lukasz; Jin, Kevin K.; Klock, Heath E.; Knuth, Mark W.; Kozbial, Piotr; Krishna, S. Sri; Kumar, Abhinav; Marciano, David; McMullan, Daniel; Morse, Andrew T.; Nigoghossian, Edward; Okach, Linda; Reyes, Ron; Bedem, Henry van den; Weekes, Dana; Xu, Qingping; Hodgson, Keith O.; Wooley, John; Elsliger, Marc-André; Deacon, Ashley M.; Godzik, Adam; Lesley, Scott A.; Wilson, Ian A.

2010-01-01

The crystal structure of the first representative of DUF364 family reveals a combination of enolase N-terminal-like and C-terminal Rossmann-like folds. Analysis of the interdomain cleft combined with sequence and genome context conservation among homologs, suggests a unique catalytic site likely involved in the synthesis of a flavin or pterin derivative. The crystal structure of Dhaf4260 from Desulfitobacterium hafniense DCB-2 was determined by single-wavelength anomalous diffraction (SAD) to a resolution of 2.01 Å using the semi-automated high-throughput pipeline of the Joint Center for Structural Genomics (JCSG) as part of the NIGMS Protein Structure Initiative (PSI). This protein structure is the first representative of the PF04016 (DUF364) Pfam family and reveals a novel combination of two well known domains (an enolase N-terminal-like fold followed by a Rossmann-like domain). Structural and bioinformatic analyses reveal partial similarities to Rossmann-like methyltransferases, with residues from the enolase-like fold combining to form a unique active site that is likely to be involved in the condensation or hydrolysis of molecules implicated in the synthesis of flavins, pterins or other siderophores. The genome context of Dhaf4260 and homologs additionally supports a role in heavy-metal chelation

Prediction of Pseudo relative velocity response spectra at Yucca Mountain for underground nuclear explosions conducted in the Pahute Mesa testing area at the Nevada testing site

International Nuclear Information System (INIS)

Phillips, J.S.

1991-12-01

The Yucca Mountain Site Characterization Project (YMP), managed by the Office of Geologic Disposal of the Office of Civilian Radioactive Waste Management of the US Department of Energy, is examining the feasibility of siting a repository for commercial, high-level nuclear wastes at Yucca Mountain on and adjacent to the Nevada Test Site (NTS). This work, intended to extend our understanding of the ground motion at Yucca Mountain resulting from testing of nuclear weapons on the NTS, was funded by the Yucca Mountain project and the Military Applications Weapons Test Program. This report summarizes one aspect of the weapons test seismic investigations conducted in FY88. Pseudo relative velocity response spectra (PSRV) have been calculated for a large body of surface ground motions generated by underground nuclear explosions. These spectra have been analyzed and fit using multiple linear regression techniques to develop a credible prediction technique for surface PSRVs. In addition, a technique for estimating downhole PSRVs at specific stations is included. A data summary, data analysis, prediction development, prediction evaluation, software summary and FORTRAN listing of the prediction technique are included in this report

Uniquely Strongly Clean Group Rings

Institute of Scientific and Technical Information of China (English)

WANG XIU-LAN

2012-01-01

A ring R is called clean if every element is the sum of an idempotent and a unit,and R is called uniquely strongly clean (USC for short) if every element is uniquely the sum of an idempotent and a unit that commute.In this article,some conditions on a ring R and a group G such that RG is clean are given.It is also shown that if G is a locally finite group,then the group ring RG is USC if and only if R is USC,and G is a 2-group.The left uniquely exchange group ring,as a middle ring of the uniquely clean ring and the USC ring,does not possess this property,and so does the uniquely exchange group ring.

Development and Validation of a Preprocedural Risk Score to Predict Access Site Complications After Peripheral Vascular Interventions Based on the Vascular Quality Initiative Database

Directory of Open Access Journals (Sweden)

Daniel Ortiz

2016-01-01

Full Text Available Purpose: Access site complications following peripheral vascular intervention (PVI are associated with prolonged hospitalization and increased mortality. Prediction of access site complication risk may optimize PVI care; however, there is no tool designed for this. We aimed to create a clinical scoring tool to stratify patients according to their risk of developing access site complications after PVI. Methods: The Society for Vascular Surgery’s Vascular Quality Initiative database yielded 27,997 patients who had undergone PVI at 131 North American centers. Clinically and statistically significant preprocedural risk factors associated with in-hospital, post-PVI access site complications were included in a multivariate logistic regression model, with access site complications as the outcome variable. A predictive model was developed with a random sample of 19,683 (70% PVI procedures and validated in 8,314 (30%. Results: Access site complications occurred in 939 (3.4% patients. The risk tool predictors are female gender, age > 70 years, white race, bedridden ambulatory status, insulin-treated diabetes mellitus, prior minor amputation, procedural indication of claudication, and nonfemoral arterial access site (model c-statistic = 0.638. Of these predictors, insulin-treated diabetes mellitus and prior minor amputation were protective of access site complications. The discriminatory power of the risk model was confirmed by the validation dataset (c-statistic = 0.6139. Higher risk scores correlated with increased frequency of access site complications: 1.9% for low risk, 3.4% for moderate risk and 5.1% for high risk. Conclusions: The proposed clinical risk score based on eight preprocedural characteristics is a tool to stratify patients at risk for post-PVI access site complications. The risk score may assist physicians in identifying patients at risk for access site complications and selection of patients who may benefit from bleeding avoidance

NetPhosYeast: prediction of protein phosphorylation sites in yeast

DEFF Research Database (Denmark)

Ingrell, C.R.; Miller, Martin Lee; Jensen, O.N.

2007-01-01

sites compared to those in humans, suggesting the need for an yeast-specific phosphorylation site predictor. NetPhosYeast achieves a correlation coefficient close to 0.75 with a sensitivity of 0.84 and specificity of 0.90 and outperforms existing predictors in the identification of phosphorylation sites...

The method of selecting an integrated development territory for the high-rise unique constructions

Directory of Open Access Journals (Sweden)

Sheina Svetlana

2018-01-01

Full Text Available On the basis of data provided by the Department of architecture and urban planning of the city of Rostov-on-don, the problem of the choice of the territory for complex development that will be in priority for the construction of high-rise and unique buildings is solved. The objective of the study was the development of a methodology for selection of the area and the implementation of the proposed method on the example of evaluation of four-territories complex development. The developed method along with standard indicators of complex evaluation considers additional indicators that assess the territory from the position of high-rise unique building. The final result of the study is the rankings of the functional priority areas that takes into account the construction of both residential and public and business objects of unique high-rise construction. The use of the developed methodology will allow investors and customers to assess the investment attractiveness of the future unique construction project on the proposed site.

[Prediction of 137Cs behaviour in the soil-plant system in the territory of Semipalatinsk test site].

Science.gov (United States)

Spiridonov, S I; Mukusheva, M K; Gontarenko, I A; Fesenko, S V; Baranov, S A

2005-01-01

A mathematical model of 137Cs behaviour in the soil-plant system is presented. The model has been parameterized for the area adjacent to the testing area Ground Zero of the Semipalatinsk Test Site. The model describes the main processes responsible for the changes in 137Cs content in the soil solution and, thereby, dynamics of the radionuclide uptake by vegetation. The results are taken from predictive and retrospective calculations that reflect the dynamics of 137Cs distribution by species in soil after nuclear explosions. The importance of factors governing 137Cs accumulation in plants within the STS area is assessed. The analysis of sensitivity of the output model variable to changes in its parameters revealed that the key soil properties significantly influence the results of prediction of 137Cs content in plants.

'Red Flag' Predictions

DEFF Research Database (Denmark)

Hallin, Carina Antonia; Andersen, Torben Juul; Tveterås, Sigbjørn

-generation prediction markets and outline its unique features as a third-generation prediction market. It is argued that frontline employees gain deep insights when they execute operational activities on an ongoing basis in the organization. The experiential learning from close interaction with internal and external......This conceptual article introduces a new way to predict firm performance based on aggregation of sensing among frontline employees about changes in operational capabilities to update strategic action plans and generate innovations. We frame the approach in the context of first- and second...

Prediction of the flooding process at the Ronneburg site - results of an integrated approach

International Nuclear Information System (INIS)

Paul, M.; Saenger, H.-J.; Snagowski, S.; Maerten, H.; Eckart, M.

1998-01-01

The flooding process of the Ronneburg uranium mine (WISMUT) was initiated at the turn of the year 1997 to 1998. In order to prepare the flooding process and to derive and optimize technological measures an integrated modelling approach was chosen which includes several coupled modules. The most important issues to be answered are: (1) prediction of the flooding time (2) prediction of the groundwater level at the post-flooding stage, assessment of amount, location and quality of flooding waters entering the receiving streams at the final stage (3) water quality prediction within the mine during the flooding process (4) definition of technological measures and assessment of their efficiency A box model which includes the three-dimensional distribution of the cavity volume in the mine represents the model core. The model considers the various types of dewatered cavity volumes for each mine level / mining field and the degree of vertical and horizontal connection between the mining fields. Different types of open mine space as well as the dewatered geological pore and joint volume are considered taking into account the contour of the depression cone prior to flooding and the characteristics of the different rock types. Based on the mine water balance and the flooding technology the model predicts the rise of the water table over time during the flooding process for each mine field separately. In order to predict the mine water quality and the efficiency of in-situ water treatment the box model was linked to a geochemical model (PHREEQC). A three-dimensional flow model is used to evaluate the post-flooding situation at the Ronneburg site. This model is coupled to the box model. The modelling results of various flooding scenarios show that a prediction of the post-flooding geohydraulic situation is possible despite of uncertainties concerning the input parameters which still exist. The post-flooding water table in the central part of the Ronneburg mine will be 270 m

Virtual Screening and Prediction of Site of Metabolism for Cytochrome P450 1A2 Ligands

DEFF Research Database (Denmark)

Vasanthanathan, P.; Hritz, Jozef; Taboureau, Olivier

2009-01-01

questions have been addressed: 1. Binding orientations and conformations were successfully predicted for various substrates. 2. A virtual screen was performed with satisfying enrichment rates. 3. A classification of individual compounds into active and inactive was performed. It was found that while docking...... can be used successfully to address the first two questions, it seems to be more difficult to perform the classification. Different scoring functions were included, and the well-characterized water molecule in the active site was included in various ways. Results are compared to experimental data...

Underground facility for geoenvironmental and geotechnical research at the SSC Site in Texas

International Nuclear Information System (INIS)

Wang, H.F.; Myer, L.R.

1994-01-01

The subsurface environment is an important national resource that is utilized for construction, waste disposal and groundwater supply. Conflicting and unwise use has led to problems of groundwater contamination. Cleanup is often difficult and expensive, and perhaps not even possible in many cases. Construction projects often encounter unanticipated difficulties that increase expenses. Many of the difficulties of predicting mechanical behavior and fluid flow and transport behavior stem from problems in characterizing what cannot be seen. An underground research laboratory, such as can be developed in the nearly 14 miles of tunnel at the Superconducting Super Collider (SSC) site, will provide a unique opportunity to advance scientific investigations of fluid flow, chemical transport, and mechanical behavior in situ in weak and fractured, porous rock on a scale relevant to civil and environmental engineering applications involving the subsurface down to a depth of 100 m. The unique element provided by underground studies at the SSC site is three-dimensional access to a range of fracture conditions in two rock types, chalk and shale. Detailed experimentation can be carried out in small sections of the SSC tunnel where different types of fractures and faults occur and where different rock types or contacts are exposed. The entire length of the tunnel can serve as an observatory for large scale mechanical and fluid flow testing. The most exciting opportunity is to mine back a volume of rock to conduct a post-experiment audit following injection of a number of reactive and conservative tracers. Flow paths and tracer distributions can be examined directly. The scientific goal is to test conceptual models and numerical predictions. In addition, mechanical and hydrological data may be of significant value in developing safe and effective methods for closing the tunnel itself

A study of moult-site fidelity in Egyptian geese, Alopochen ...

African Journals Online (AJOL)

Little is known about moult and moult-site fidelity of African waterfowl. Satellite telemetry and uniquely engraved colour-rings were used to study moult-site fidelity of Egyptian geese marked at two sites in South Africa – Barberspan in the summer-rainfall region and Strandfontein in the winter-rainfall region. Twelve Egyptian ...

Predicting transcription factor binding sites using local over-representation and comparative genomics

Directory of Open Access Journals (Sweden)

Touzet Hélène

2006-08-01

Full Text Available Abstract Background Identifying cis-regulatory elements is crucial to understanding gene expression, which highlights the importance of the computational detection of overrepresented transcription factor binding sites (TFBSs in coexpressed or coregulated genes. However, this is a challenging problem, especially when considering higher eukaryotic organisms. Results We have developed a method, named TFM-Explorer, that searches for locally overrepresented TFBSs in a set of coregulated genes, which are modeled by profiles provided by a database of position weight matrices. The novelty of the method is that it takes advantage of spatial conservation in the sequence and supports multiple species. The efficiency of the underlying algorithm and its robustness to noise allow weak regulatory signals to be detected in large heterogeneous data sets. Conclusion TFM-Explorer provides an efficient way to predict TFBS overrepresentation in related sequences. Promising results were obtained in a variety of examples in human, mouse, and rat genomes. The software is publicly available at http://bioinfo.lifl.fr/TFM-Explorer.

Expedited Site Characterization: A rapid, cost-effective process for preremedial site characterization

International Nuclear Information System (INIS)

Burton, J.C.; Walker, J.L.; Jennings, T.V.; Aggarwal, P.K.; Hastings, B.; Meyer, W.T.; Rose, C.M.; Rosignolo, C.L.

1993-01-01

Argonne National Laboratory has developed a unique, cost- and time-effective, technically innovative process for preremedial site characterization, referred to as Expedited Site Characterization (ESC). The cost of the ESC field sampling process ranges from 1/10 to 1/5 of the cost of traditional site characterization. The time required for this ESC field activity is approximately 1/30 of that for current methods. Argonne's preremedial site investigations based on this approach have been accepted by the appropriate regulatory agencies. The ESC process is flexible and neither site nor contaminant dependent. The process has been successfully tested and applied in site investigations of multiple contaminated landfills in New Mexico (for the US Department of the Interior's Bureau of Land Management [BLM]) and at former grain storage facilities in Nebraska and Kansas, contaminated with carbon tetrachloride (for the Department of Agriculture's Commodity Credit Corporation [CCC/USDA]). A working demonstration of this process was sponsored by the US Department of Energy (DOE) Office of Technology Development as a model of the methodology needed to accelerate site characterizations at DOE facilities. This report describes the application of the process in New Mexico, Nebraska and Kansas

Prediction of DtxR regulon: Identification of binding sites and operons controlled by Diphtheria toxin repressor in Corynebacterium diphtheriae

Directory of Open Access Journals (Sweden)

Hasnain Seyed

2004-09-01

Full Text Available Abstract Background The diphtheria toxin repressor, DtxR, of Corynebacterium diphtheriae has been shown to be an iron-activated transcription regulator that controls not only the expression of diphtheria toxin but also of iron uptake genes. This study aims to identify putative binding sites and operons controlled by DtxR to understand the role of DtxR in patho-physiology of Corynebacterium diphtheriae. Result Positional Shannon relative entropy method was used to build the DtxR-binding site recognition profile and the later was used to identify putative regulatory sites of DtxR within C. diphtheriae genome. In addition, DtxR-regulated operons were also identified taking into account the predicted DtxR regulatory sites and genome annotation. Few of the predicted motifs were experimentally validated by electrophoretic mobility shift assay. The analysis identifies motifs upstream to the novel iron-regulated genes that code for Formamidopyrimidine-DNA glycosylase (FpG, an enzyme involved in DNA-repair and starvation inducible DNA-binding protein (Dps which is involved in iron storage and oxidative stress defense. In addition, we have found the DtxR motifs upstream to the genes that code for sortase which catalyzes anchoring of host-interacting proteins to the cell wall of pathogenic bacteria and the proteins of secretory system which could be involved in translocation of various iron-regulated virulence factors including diphtheria toxin. Conclusions We have used an in silico approach to identify the putative binding sites and genes controlled by DtxR in Corynebacterium diphtheriae. Our analysis shows that DtxR could provide a molecular link between Fe+2-induced Fenton's reaction and protection of DNA from oxidative damage. DtxR-regulated Dps prevents lethal combination of Fe+2 and H2O2 and also protects DNA by nonspecific DNA-binding. In addition DtxR could play an important role in host interaction and virulence by regulating the levels of sortase

Legend and legacy: Fifty years of defense production at the Hanford Site

Energy Technology Data Exchange (ETDEWEB)

Gerber, M.S.

1992-09-01

Today, the Hanford Site is engaged in the largest waste cleanup effort ever undertaken in human history. That in itself makes the endeavor historic and unique. The Hanford Site has been designated the ``flagship`` of Department of Energy (DOE) waste remediation endeavors. And, just as the wartime Hanford Project remains unmatched in history, no counterpart exists for the current waste cleanup enterprise. This report provides a summary of the extensive historical record, however, which does give a partial road map. The science of environmental monitoring pioneered at the Hanford Site, and records of this type are the most complete of any in the world, from private companies or public agencies, for the early years of Site operations. The Hanford Site was unique for establishing a detailed, scientific, and multi-faceted environmental monitoring program.

Legend and legacy: Fifty years of defense production at the Hanford Site

International Nuclear Information System (INIS)

Gerber, M.S.

1992-09-01

Today, the Hanford Site is engaged in the largest waste cleanup effort ever undertaken in human history. That in itself makes the endeavor historic and unique. The Hanford Site has been designated the ''flagship'' of Department of Energy (DOE) waste remediation endeavors. And, just as the wartime Hanford Project remains unmatched in history, no counterpart exists for the current waste cleanup enterprise. This report provides a summary of the extensive historical record, however, which does give a partial road map. The science of environmental monitoring pioneered at the Hanford Site, and records of this type are the most complete of any in the world, from private companies or public agencies, for the early years of Site operations. The Hanford Site was unique for establishing a detailed, scientific, and multi-faceted environmental monitoring program

Performance Art at the Campusphere: Pedagogical Experiments On-Site

Science.gov (United States)

Ben-Shaul, Daphna

2018-01-01

Following a unique practice and research laboratory entitled "Performance: Site/Self" that took place in 2013-2015, this article discusses the implementation of performance art at an academic site--the Tel Aviv University campus. This pedagogical and artistic initiative, characterised by the transgressive pedagogy of performance art…

(/sup 3/H)Spiperone binding sites in brain: autoradiographic localization of multiple receptors

Energy Technology Data Exchange (ETDEWEB)

Palacios, J M; Niehoff, D L; Kuhar, M J [Johns Hopkins Univ., Baltimore, MD (USA). School of Medicine

1981-01-01

(/sup 3/H)Spiperone ((/sup 3/H)SP) binding sites were localized by light microscopic autoradiography, after in vitro labelling. The kinetic and pharmacological characteristics of these binding sites were studied in slide-mounted sections of rat forebrain, and optimal labeling conditions were defined. Autoradiograms were obtained by apposing emulsion-coated coverslips to labeled sections. Differential drug sensitivity allowed the selective displacement of (/sup 3/H)SP from dopamine receptors by ADTN, from serotonin receptors by cinanserin, from both by haloperidol and from unique spiperone sites by unlabeled spiperone. The various sites presented a differential anatomical localization. For example, only dopaminergic sites were found in the glomerular layer of the olfactory bulb; only serotonergic sites were found in lamina IV of the neocortex, and a high concentration of unique spiperone sites were found in parts of the hippocampus.

Groundwater remediation at the Hanford site

International Nuclear Information System (INIS)

Fries, W.

1993-01-01

Ion exchange resin and adsorption technology has been used successfully to treat diversified types of toxic waste water for many years. Even though the Hanford Site presents many unique problems, the author believes these technologies can remediate the groundwater at this site. However, treatment of the sludge in tanks generally is beyond the pale of these technologies except for the possibility of experimental studies being performed at the University of Idaho (Troescher)

Prediction of consensus binding mode geometries for related chemical series of positive allosteric modulators of adenosine and muscarinic acetylcholine receptors.

Science.gov (United States)

Sakkal, Leon A; Rajkowski, Kyle Z; Armen, Roger S

2017-06-05

Following insights from recent crystal structures of the muscarinic acetylcholine receptor, binding modes of Positive Allosteric Modulators (PAMs) were predicted under the assumption that PAMs should bind to the extracellular surface of the active state. A series of well-characterized PAMs for adenosine (A 1 R, A 2A R, A 3 R) and muscarinic acetylcholine (M 1 R, M 5 R) receptors were modeled using both rigid and flexible receptor CHARMM-based molecular docking. Studies of adenosine receptors investigated the molecular basis of the probe-dependence of PAM activity by modeling in complex with specific agonist radioligands. Consensus binding modes map common pharmacophore features of several chemical series to specific binding interactions. These models provide a rationalization of how PAM binding slows agonist radioligand dissociation kinetics. M 1 R PAMs were predicted to bind in the analogous M 2 R PAM LY2119620 binding site. The M 5 R NAM (ML-375) was predicted to bind in the PAM (ML-380) binding site with a unique induced-fit receptor conformation. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Three Millennia of Seemingly Time-Predictable Earthquakes, Tell Ateret

Science.gov (United States)

Agnon, Amotz; Marco, Shmuel; Ellenblum, Ronnie

2014-05-01

Among various idealized recurrence models of large earthquakes, the "time-predictable" model has a straightforward mechanical interpretation, consistent with simple friction laws. On a time-predictable fault, the time interval between an earthquake and its predecessor is proportional to the slip during the predecessor. The alternative "slip-predictable" model states that the slip during earthquake rupture is proportional to the preceding time interval. Verifying these models requires extended records of high precision data for both timing and amount of slip. The precision of paleoearthquake data can rarely confirm or rule out predictability, and recent papers argue for either time- or slip-predictable behavior. The Ateret site, on the trace of the Dead Sea fault at the Jordan Gorge segment, offers unique precision for determining space-time patterns. Five consecutive slip events, each associated with deformed and offset sets of walls, are correlated with historical earthquakes. Two correlations are based on detailed archaeological, historical, and numismatic evidence. The other three are tentative. The offsets of three of the events are determined with high precision; the other two are not as certain. Accepting all five correlations, the fault exhibits a striking time-predictable behavior, with a long term slip rate of 3 mm/yr. However, the 30 October 1759 ~0.5 m rupture predicts a subsequent rupture along the Jordan Gorge toward the end of the last century. We speculate that earthquakres on secondary faults (the 25 November 1759 on the Rachaya branch and the 1 January 1837 on the Roum branch, both M≥7) have disrupted the 3 kyr time-predictable pattern.

Verification of geomechanical integrity and prediction of long-term mineral trapping for the Ketzin CO2 storage pilot site

Science.gov (United States)

Kempka, Thomas; De Lucia, Marco; Kühn, Michael

2014-05-01

Static and dynamic numerical modelling generally accompany the entire CO2 storage site life cycle. Thereto, it is required to match the employed models with field observations on a regular basis in order to predict future site behaviour. We investigated the coupled processes at the Ketzin CO2 storage pilot site [1] using a model coupling concept focusing on the temporal relevance of processes involved (hydraulic, chemical and mechanical) at given time-scales (site operation, abandonment and long-term stabilization). For that purpose, long-term dynamic multi-phase flow simulations [2], [3] established the basis for all simulations discussed in the following. Hereby, pressure changes resulting in geomechanical effects are largest during site operation, whereas geochemical reactions are governed by slow kinetics resulting in a long-term stabilization. To account for mechanical integrity, which may be mainly affected during site operation, we incorporated a regional-scale coupled hydro-mechanical model. Our simulation results show maximum ground surface displacements of about 4 mm, whereas shear and tensile failure are not observed. Consequently, the CO2 storage operation at the Ketzin pilot site does not compromise reservoir, caprock and fault integrity. Chemical processes responsible for mineral trapping are expected to mainly occur during long-term stabilization at the Ketzin pilot site [4]. Hence, our previous assessment [3] was extended by integrating two long-term mineral trapping scenarios. Thereby, mineral trapping contributes to the trapping mechanisms with 11.7 % after 16,000 years of simulation in our conservative and with 30.9 % in our maximum reactivity scenarios. Dynamic flow simulations indicate that only 0.2 % of the CO2 injected (about 67,270 t CO2 in total) is in gaseous state, but structurally trapped after 16,000 years. Depending on the studied long-term scenario, CO2 dissolution is the dominating trapping mechanism with 68.9 % and 88

Tritium monitoring in groundwater and evaluation of model predictions for the Hanford Site 200 Area Effluent Treatment Facility

International Nuclear Information System (INIS)

Barnett, D.B.; Bergeron, M.P.; Cole, C.R.; Freshley, M.D.; Wurstner, S.K.

1997-08-01

The Effluent Treatment Facility (ETF) disposal site, also known as the State-Approved Land Disposal Site (SALDS), receives treated effluent containing tritium, which is allowed to infiltrate through the soil column to the water table. Tritium was first detected in groundwater monitoring wells around the facility in July 1996. The SALDS groundwater monitoring plan requires revision of a predictive groundwater model and reevaluation of the monitoring well network one year from the first detection of tritium in groundwater. This document is written primarily to satisfy these requirements and to report on analytical results for tritium in the SALDS groundwater monitoring network through April 1997. The document also recommends an approach to continued groundwater monitoring for tritium at the SALDS. Comparison of numerical groundwater models applied over the last several years indicate that earlier predictions, which show tritium from the SALDS approaching the Columbia River, were too simplified or overly robust in source assumptions. The most recent modeling indicates that concentrations of tritium above 500 pCi/L will extend, at most, no further than ∼1.5 km from the facility, using the most reasonable projections of ETF operation. This extent encompasses only the wells in the current SALDS tritium-tracking network

Common processes at unique volcanoes – a volcanological conundrum

Directory of Open Access Journals (Sweden)

Katharine eCashman

2014-11-01

Full Text Available An emerging challenge in modern volcanology is the apparent contradiction between the perception that every volcano is unique, and classification systems based on commonalities among volcano morphology and eruptive style. On the one hand, detailed studies of individual volcanoes show that a single volcano often exhibits similar patterns of behaviour over multiple eruptive episodes; this observation has led to the idea that each volcano has its own distinctive pattern of behaviour (or personality. In contrast, volcano classification schemes define eruption styles referenced to type volcanoes (e.g. Plinian, Strombolian, Vulcanian; this approach implicitly assumes that common processes underpin volcanic activity and can be used to predict the nature, extent and ensuing hazards of individual volcanoes. Actual volcanic eruptions, however, often include multiple styles, and type volcanoes may experience atypical eruptions (e.g., violent explosive eruptions of Kilauea, Hawaii1. The volcanological community is thus left with a fundamental conundrum that pits the uniqueness of individual volcanic systems against generalization of common processes. Addressing this challenge represents a major challenge to volcano research.

Using the Theory of Planned Behavior to Identify Predictors of Oral Hygiene: A Collection of Unique Behaviors.

Science.gov (United States)

Brein, Daniel J; Fleenor, Thomas J; Kim, Soo-Woo; Krupat, Edward

2016-03-01

This study aims to identify predictors of performed oral hygiene behaviors (OHBs) based on the Theory of Planned Behavior (TPB), oral health knowledge, and demographic factors. Using a questionnaire, 381 participants in three general dental offices and one hospital dental department in York, Pennsylvania, were surveyed regarding performed OHB, attitudes, subjective norms, perceived behavioral control, oral health knowledge, income, age, and sex. Three unique elements of OHB were identified for analysis: brushing, interdental cleaning, and tongue cleaning. Regression analysis revealed that attitude was the strongest predictor of brushing behavior, followed by oral health knowledge, perceived behavior control, subjective norms, and income. Perceived behavior control was the strongest predictor of interdental cleaning, followed by increased age and attitude. Female sex was the strongest predictor of tongue cleaning, followed by subjective norms, decreased age, and perceived behavior control. Respectively, these three groups of predictive variables explained 22.5% of brushing behavior, 22.7% of interdental cleaning behavior, and 9.5% of tongue cleaning behavior. The present findings highlight the utility of viewing OHB as a set of unique behaviors with unique predictive variables and provide additional support for use of TPB in predicting OHB. Periodontal practitioners should consider the strong associations of attitude and perceived behavioral control with brushing and interdental cleaning behaviors when designing interventional efforts to improve patient home care.

Quantifying and visualizing site performance in clinical trials

Directory of Open Access Journals (Sweden)

Eric Yang

2018-03-01

Conclusions: The use of operational data from Covance Central Laboratories provides a unique perspective into the performance of clinical sites with respect to many important metrics such as patient enrollment and retention. These metrics can, in turn, be used to guide operational planning and site selection for new clinical trials, thereby accelerating recruitment, improving quality, and reducing cost.

Tree mycorrhizal type predicts within-site variability in the storage and distribution of soil organic matter.

Science.gov (United States)

Craig, Matthew E; Turner, Benjamin L; Liang, Chao; Clay, Keith; Johnson, Daniel J; Phillips, Richard P

2018-03-24

Forest soils store large amounts of carbon (C) and nitrogen (N), yet how predicted shifts in forest composition will impact long-term C and N persistence remains poorly understood. A recent hypothesis predicts that soils under trees associated with arbuscular mycorrhizas (AM) store less C than soils dominated by trees associated with ectomycorrhizas (ECM), due to slower decomposition in ECM-dominated forests. However, an incipient hypothesis predicts that systems with rapid decomposition-e.g. most AM-dominated forests-enhance soil organic matter (SOM) stabilization by accelerating the production of microbial residues. To address these contrasting predictions, we quantified soil C and N to 1 m depth across gradients of ECM-dominance in three temperate forests. By focusing on sites where AM- and ECM-plants co-occur, our analysis controls for climatic factors that covary with mycorrhizal dominance across broad scales. We found that while ECM stands contain more SOM in topsoil, AM stands contain more SOM when subsoil to 1 m depth is included. Biomarkers and soil fractionations reveal that these patterns are driven by an accumulation of microbial residues in AM-dominated soils. Collectively, our results support emerging theory on SOM formation, demonstrate the importance of subsurface soils in mediating plant effects on soil C and N, and indicate that shifts in the mycorrhizal composition of temperate forests may alter the stabilization of SOM. © 2018 John Wiley & Sons Ltd.

High latitude plasma convection: Predictions for EISCAT and Sondre Stromfjord

International Nuclear Information System (INIS)

Sojka, J.J.; Raitt, W.J.; Schunk, R.W.

1979-01-01

We have used a plasma convection model to predict diurnal patterns of horizontal drift velocities in the vicinity of the EISCAT incoherent scatter facility at Tromso, Norway and for Sondre Stromfjord, Greenland, a proposed new incoherent scatter facility site. The convection model includes the offset of 11.4 0 between the geographic and geomagnetic poles (northern hemisphere), the tendency of plasma to corotate about the geographic pole, and a magnetospheric electric field mapped to a circle about a center offset by 5 0 in the antisunward direction from the magnetic pole. Four different magnetospheric electric field configurations were considered, including a constant cross-tail electric field, asymmetric electric fields with enhancements on the dawn and dusk sides of the polar cap, and an electric field pattern that is not aligned parallel to the noon-midnight magnetic meridian. The different electric field configurations produce different signatures in the plasma convection pattern which are clearly identified. Both of the high-latitude sites are better suited to study magnetospheric convection effects than either Chatanika, Alaska or Millstone Hill, Massachusetts. Also, each site appears to have unique capabilities with regard to studying certain aspects of the magnetospheric electric field

Meta-Analysis of DNA Tumor-Viral Integration Site Selection Indicates a Role for Repeats, Gene Expression and Epigenetics

Directory of Open Access Journals (Sweden)

Janet M. Doolittle-Hall

2015-11-01

Full Text Available Oncoviruses cause tremendous global cancer burden. For several DNA tumor viruses, human genome integration is consistently associated with cancer development. However, genomic features associated with tumor viral integration are poorly understood. We sought to define genomic determinants for 1897 loci prone to hosting human papillomavirus (HPV, hepatitis B virus (HBV or Merkel cell polyomavirus (MCPyV. These were compared to HIV, whose enzyme-mediated integration is well understood. A comprehensive catalog of integration sites was constructed from the literature and experimentally-determined HPV integration sites. Features were scored in eight categories (genes, expression, open chromatin, histone modifications, methylation, protein binding, chromatin segmentation and repeats and compared to random loci. Random forest models determined loci classification and feature selection. HPV and HBV integrants were not fragile site associated. MCPyV preferred integration near sensory perception genes. Unique signatures of integration-associated predictive genomic features were detected. Importantly, repeats, actively-transcribed regions and histone modifications were common tumor viral integration signatures.

Deep subsurface structure modeling and site amplification factor estimation in Niigata plain for broadband strong motion prediction

International Nuclear Information System (INIS)

Sato, Hiroaki

2009-01-01

This report addresses a methodology of deep subsurface structure modeling in Niigata plain, Japan to estimate site amplification factor in the broadband frequency range for broadband strong motion prediction. In order to investigate deep S-wave velocity structures, we conduct microtremor array measurements at nine sites in Niigata plain, which are important to estimate both long- and short-period ground motion. The estimated depths of the top of the basement layer agree well with those of the Green tuff formation as well as the Bouguer anomaly distribution. Dispersion characteristics derived from the observed long-period ground motion records are well explained by the theoretical dispersion curves of Love wave group velocities calculated from the estimated subsurface structures. These results demonstrate the deep subsurface structures from microtremor array measurements make it possible to estimate long-period ground motions in Niigata plain. Moreover an applicability of microtremor array exploration for inclined basement structure like a folding structure is shown from the two dimensional finite difference numerical simulations. The short-period site amplification factors in Niigata plain are empirically estimated by the spectral inversion analysis from S-wave parts of strong motion data. The resultant characteristics of site amplification are relative large in the frequency range of about 1.5-5 Hz, and decay significantly with the frequency increasing over about 5 Hz. However, these features can't be explained by the calculations from the deep subsurface structures. The estimation of site amplification factors in the frequency range of about 1.5-5 Hz are improved by introducing a shallow detailed structure down to GL-20m depth at a site. We also propose to consider random fluctuation in a modeling of deep S-wave velocity structure for broadband site amplification factor estimation. The Site amplification in the frequency range higher than about 5 Hz are filtered

Participatory role of zinc in structural and functional characterization of bioremediase: a unique thermostable microbial silica leaching protein.

Science.gov (United States)

Chowdhury, Trinath; Sarkar, Manas; Chaudhuri, Biswadeep; Chattopadhyay, Brajadulal; Halder, Umesh Chandra

2015-07-01

A unique protein, bioremediase (UniProt Knowledgebase Accession No.: P86277), isolated from a hot spring bacterium BKH1 (GenBank Accession No.: FJ177512), has shown to exhibit silica leaching activity when incorporated to prepare bio-concrete material. Matrix-assisted laser desorption ionization mass spectrometry analysis suggests that bioremediase is 78% homologous to bovine carbonic anhydrase II though it does not exhibit carbonic anhydrase-like activity. Bioinformatics study is performed for understanding the various physical and chemical parameters of the protein which predicts the involvement of zinc encircled by three histidine residues (His94, His96 and His119) at the active site of the protein. Isothermal titration calorimetric-based thermodynamic study on diethyl pyrocarbonate-modified protein recognizes the presence of Zn(2+) in the enzyme moiety. Exothermic to endothermic transition as observed during titration of the protein with Zn(2+) discloses that there are at least two binding sites for zinc within the protein moiety. Addition of Zn(2+) regains the activity of EDTA chelated bioremediase confirming the presence of extra binding site of Zn(2+) in the protein moiety. Revival of folding pattern of completely unfolded urea-treated protein by Zn(2+) explains the participatory role of zinc in structural stability of the protein. Restoration of the λ max in intrinsic fluorescence emission study of the urea-treated protein by Zn(2+) similarly confirms the involvement of Zn in the refolding of the protein. The utility of bioremediase for silica nanoparticles preparation is observed by field emission scanning electron microscopy.

Olkiluoto site description 2006

International Nuclear Information System (INIS)

Andersson, J.; Ahokas, H.; Hudson, J.A.

2007-03-01

This second version of the Olkiluoto Site Report, produced by the OMTF (Olkiluoto Modelling Task Force), updates the Olkiluoto Site Report 2004 (Posiva 2005) with the data and knowledge obtained up to December 2005. The main product of the modelling has been to develop a descriptive model of the site (the Site Descriptive Model), i.e. a model describing the geometry, properties of the bedrock and the water and the associated interacting processes and mechanisms. For practical reasons, the Site Descriptive Model is divided into five parts: surface system, geology, rock mechanics, hydrogeology and hydrogeochemistry, which are presented in individual chapters. Four separated models are presented: the geological, rock mechanics, hydrogeological and hydrogeochemical models. The consistency between the hydrogeological and hydrogeochemical models is assessed in a joint chapter. Chapter 1 presents an outline of the report, explains the background to its development and sets out its objectives and scope. It is also introduces and explains the integrated modelling methodology, the nomenclature used in the descriptions of the models and the prediction/outcome studies. Chapter 2 provides a brief overview of the data used for producing the Site Description. Chapters 3 to 8 present the descriptive modelling, which involves interpreting data, interpolating or extrapolating between measurement points and calibrating the model against data, based on the various assumptions made about each conceptual model. Chapter 9 presents the results of the prediction/outcome studies performed during 2005 and Chapter 10 the overall consistency and confidence assessment. Overall conclusions are provided in Chapter 11. The main advances since Site Report 2004 are: A new geological model is presented in Chapter 4, representing a significant change from Bedrock Model 2003/1. There has been extensive use of geological data, whereas hydrogeological data have deliberately not been used and more

A regional neural network model for predicting mean daily river water temperature

Science.gov (United States)

Wagner, Tyler; DeWeber, Jefferson Tyrell

2014-01-01

Water temperature is a fundamental property of river habitat and often a key aspect of river resource management, but measurements to characterize thermal regimes are not available for most streams and rivers. As such, we developed an artificial neural network (ANN) ensemble model to predict mean daily water temperature in 197,402 individual stream reaches during the warm season (May–October) throughout the native range of brook trout Salvelinus fontinalis in the eastern U.S. We compared four models with different groups of predictors to determine how well water temperature could be predicted by climatic, landform, and land cover attributes, and used the median prediction from an ensemble of 100 ANNs as our final prediction for each model. The final model included air temperature, landform attributes and forested land cover and predicted mean daily water temperatures with moderate accuracy as determined by root mean squared error (RMSE) at 886 training sites with data from 1980 to 2009 (RMSE = 1.91 °C). Based on validation at 96 sites (RMSE = 1.82) and separately for data from 2010 (RMSE = 1.93), a year with relatively warmer conditions, the model was able to generalize to new stream reaches and years. The most important predictors were mean daily air temperature, prior 7 day mean air temperature, and network catchment area according to sensitivity analyses. Forest land cover at both riparian and catchment extents had relatively weak but clear negative effects. Predicted daily water temperature averaged for the month of July matched expected spatial trends with cooler temperatures in headwaters and at higher elevations and latitudes. Our ANN ensemble is unique in predicting daily temperatures throughout a large region, while other regional efforts have predicted at relatively coarse time steps. The model may prove a useful tool for predicting water temperatures in sampled and unsampled rivers under current conditions and future projections of climate

Ground motion predictions

Energy Technology Data Exchange (ETDEWEB)

Loux, P C [Environmental Research Corporation, Alexandria, VA (United States)

1969-07-01

Nuclear generated ground motion is defined and then related to the physical parameters that cause it. Techniques employed for prediction of ground motion peak amplitude, frequency spectra and response spectra are explored, with initial emphasis on the analysis of data collected at the Nevada Test Site (NTS). NTS postshot measurements are compared with pre-shot predictions. Applicability of these techniques to new areas, for example, Plowshare sites, must be questioned. Fortunately, the Atomic Energy Commission is sponsoring complementary studies to improve prediction capabilities primarily in new locations outside the NTS region. Some of these are discussed in the light of anomalous seismic behavior, and comparisons are given showing theoretical versus experimental results. In conclusion, current ground motion prediction techniques are applied to events off the NTS. Predictions are compared with measurements for the event Faultless and for the Plowshare events, Gasbuggy, Cabriolet, and Buggy I. (author)

Ground motion predictions

International Nuclear Information System (INIS)

Loux, P.C.

1969-01-01

Nuclear generated ground motion is defined and then related to the physical parameters that cause it. Techniques employed for prediction of ground motion peak amplitude, frequency spectra and response spectra are explored, with initial emphasis on the analysis of data collected at the Nevada Test Site (NTS). NTS postshot measurements are compared with pre-shot predictions. Applicability of these techniques to new areas, for example, Plowshare sites, must be questioned. Fortunately, the Atomic Energy Commission is sponsoring complementary studies to improve prediction capabilities primarily in new locations outside the NTS region. Some of these are discussed in the light of anomalous seismic behavior, and comparisons are given showing theoretical versus experimental results. In conclusion, current ground motion prediction techniques are applied to events off the NTS. Predictions are compared with measurements for the event Faultless and for the Plowshare events, Gasbuggy, Cabriolet, and Buggy I. (author)

Site Selection for the Salt Disposition Facility at the Savannah River Site

International Nuclear Information System (INIS)

Gladden, J.B.; Rueter, K.J.; Morin, J.P.

2000-01-01

A site selection study was conducted to identify a suitable location for the construction and operation of a new Salt Disposition Facility (SDF) at the Savannah River Site (SRS). The facility to be sited is a single processing facility and support buildings that could house either of three technology alternatives being developed by the High Level Waste Systems Engineering Team: Small Tank Tetraphenylborate Precipitation, Crystalline Silicotitanate Non-Elutable Ion Exchange or Caustic Side Solvent Extraction. A fourth alternative, Direct Disposal in grout, is not part of the site selection study because a location has been identified that is unique to this technology (i.e., Z-Area). Facility site selection at SRS is a formal, documented process that seeks to optimize siting of new facilities with respect to facility-specific engineering requirements, sensitive environmental resources, and applicable regulatory requirements. In this manner, the prime objectives of cost minimization, environmental protection, and regulatory compliance are achieved. The results from this geotechnical characterization indicated that continued consideration be given to Site B for the proposed SDF. Suitable topography, the lack of surface hydrology and floodplain issues, no significant groundwater contamination, the presence of minor soft zones along the northeast portion of footprint, and no apparent geological structure in the Gordon Aquitard support this recommendation

NetAcet: prediction of N-terminal acetylation sites

DEFF Research Database (Denmark)

Kiemer, Lars; Bendtsen, Jannick Dyrløv; Blom, Nikolaj

2005-01-01

Summary: We present here a neural network based method for prediction of N-terminal acetylation-by far the most abundant post-translational modification in eukaryotes. The method was developed on a yeast dataset for N-acetyltransferase A (NatA) acetylation, which is the type of N-acetylation for ......Summary: We present here a neural network based method for prediction of N-terminal acetylation-by far the most abundant post-translational modification in eukaryotes. The method was developed on a yeast dataset for N-acetyltransferase A (NatA) acetylation, which is the type of N...

Enzyme-like specificity in zeolites: a unique site position in mordenite for selective carbonylation of methanol and dimethyl ether with CO.

Science.gov (United States)

Boronat, Mercedes; Martínez-Sánchez, Cristina; Law, David; Corma, Avelino

2008-12-03

The mechanism of methanol carbonylation at different positions of zeolite MOR is investigated by quantum-chemical methods in order to discover which are the active sites that can selectively catalyze the desired reaction. It is shown that when methanol carbonylation competes with hydrocarbon formation, the first reaction occurs preferentially within 8MR channels. However, the unique selectivity for the carbonylation of methanol and dimethyl ether in mordenite is not only due to the size of the 8MR channel: neither process occurs equally at the two T3-O31 and T3-O33 positions. We show that only the T3-O33 positions are selective and that this selectivity is due to the unusual orientation of the methoxy group in relation to the 8MR channel (parallel to the cylinder axis). Only in this situation does the transition state for the attack of CO fit perfectly in the 8MR channel, while the reaction with methanol or DME is sterically impeded. This result explains why T3-O31, while also located in the 8MR channel of mordenite, is not as selective as the T3-O33 position and why ferrierite, although it contains 8MR channels, is less selective than mordenite. The competing effect of water is explained at the molecular level, and the molecular microkinetic reaction model has been established.

LIGAND-BINDING SITES ON THE MYCOBACTERIUM TUBERCULOSIS UREASE

Directory of Open Access Journals (Sweden)

Lisnyak Yu. V.

2017-10-01

Full Text Available Introduction. Mycobacterium tuberculosis is the causative agent of tuberculosis that remains a serious medical and social health problem. Despite intensive efforts have been made in the past decade, there are no new efficient anti-tuberculosis drugs today, and that need is growing due to the spread of drug-resistant strains of M.tuberculosis. M. tuberculosis urease (MTU, being an important factor of the bacterium viability and virulence, is an attractive target for anti-tuberculosis drugs acting by inhibition of urease activity. However, the commercially available urease inhibitors are toxic and unstable, that prevent their clinical use. Therefore, new more potent anti-tuberculosis drugs inhibiting new targets are urgently needed. A useful tool for the search of novel inhibitors is a computational drug design. The inhibitor design is significantly easier if binding sites on the enzyme are identified in advance. This paper aimed to determine the probable ligand binding sites on the surface of M. tuberculosis urease. Methods. To identify ligand binding sites on MTU surface, сomputational solvent mapping method FTSite was applied by the use of MTU homology model we have built earlier. The method places molecular probes (small organic molecules containing various functional groups on a dense grid defined around the enzyme, and for each probe finds favorable positions. The selected poses are refined by free energy minimization, the low energy conformations are clustered, and the clusters are ranked on the basis of the average free energy. FTSite server outputs the protein residues delineating a binding sites and the probe molecules representing each cluster. To predict allosteric pockets on MTU, AlloPred and AlloSite servers were applied. AlloPred uses the normal mode analysis (NMA and models how the dynamics of a protein would be altered in the presence of a modulator at a specific pocket. Pockets on the enzyme are predicted using the Fpocket

Lourdes: A uniquely Catholic approach to medicine.

Science.gov (United States)

Dichoso, Travis Jon

2015-02-01

As an American medical student, I spent the summer break between my first and second year in Lourdes, France, the site where the Immaculate Conception appeared eighteen times to St. Bernadette in 1858 as proclaimed approved by the Catholic Church and whose water is associated with over seven thousand unexplained cures. During this time I volunteered with St. Joseph's Service and Poste Secour, followed several medical teams taking care of large pilgrim groups, and shadowed Dr. Alessandro de Franciscis the president of Le Bureau des Constations Médicales, the office in Lourdes charged with investigating claims of miracles. Through my experiences, I found the mission of medicine in Lourdes to be twofold: to provide the critical care needed to give sick persons the chance to transform their experience of disease through their faith; and secondly, through the efforts of the Medical Bureau, to be an instrument by which we can comprehend the wonders of the work of God. I conclude that this twofold mission should inform the work of every Catholic in health care or research, and Lourdes provides the venue par excellence to cultivate this mission. Lay Summary: Lourdes is a pilgrimage site in southern France that has been associated with medical miracles for the past 150 years. The site is unique in that throughout its history, physicians, of any or no faith, have been invited to participate in the proceedings of the investigations of each claimed cure. The investigations have formalized into a process handled by the Lourdes Medical Bureau and the Lourdes International Medical Association. Travis Dichoso, an American medical student, writes about his experiences as part of this process.

Screening Mixtures of Small Molecules for Binding to Multiple Sites on the Surface Tetanus Toxin C Fragment by Bioaffinity NMR

International Nuclear Information System (INIS)

Cosman, M; Zeller, L; Lightstone, F C; Krishnan, V V; Balhorn, R

2002-01-01

The clostridial neurotoxins include the closely related tetanus (TeNT) and botulinum (BoNT) toxins. Botulinum toxin is used to treat severe muscle disorders and as a cosmetic wrinkle reducer. Large quantities of botulinum toxin have also been produced by terrorists for use as a biological weapon. Because there are no known antidotes for these toxins, they thus pose a potential threat to human health whether by an accidental overdose or by a hostile deployment. Thus, the discovery of high specificity and affinity compounds that can inhibit their binding to neural cells can be used as antidotes or in the design of chemical detectors. Using the crystal structure of the C fragment of the tetanus toxin (TetC), which is the cell recognition and cell surface binding domain, and the computational program DOCK, sets of small molecules have been predicted to bind to two different sites located on the surface of this protein. While Site-1 is common to the TeNT and BoNTs, Site-2 is unique to TeNT. Pairs of these molecules from each site can then be linked together synthetically to thereby increase the specificity and affinity for this toxin. Electrospray ionization mass spectroscopy was used to experimentally screen each compound for binding. Mixtures containing binders were further screened for activity under biologically relevant conditions using nuclear magnetic resonance (NMR) methods. The screening of mixtures of compounds offers increased efficiency and throughput as compared to testing single compounds and can also evaluate how possible structural changes induced by the binding of one ligand can influence the binding of the second ligand. In addition, competitive binding experiments with mixtures containing ligands predicted to bind the same site could identify the best binder for that site. NMR transfer nuclear Overhauser effect (trNOE) confirm that TetC binds doxorubicin but that this molecule is displaced by N-acetylneuraminic acid (sialic acid) in a mixture that

Evaluation of proposed shallow-land burial sites using the PRESTO-II [Prediction of Radiation Effects from Shallow Trench Operations] methodology and code

International Nuclear Information System (INIS)

Fields, D.E.; Uslu, I.; Yalcintas, M.G.

1987-01-01

PRESTO-II (Prediction of Radiation Effects from Shallow Trench Operations) is a computer code designed to evaluate possible doses and risks (health effects) from shallow-land burial sites. The model is intended to serve as a non-site-specific screening model for assessing radionuclide transport, ensuing exposure, and health impacts to a static local population for a 1000-year period following the end of disposal operations. Human exposure scenarios include normal releases (including leaching and operational spillage), human intrusion, and limited site farming or reclamation. Pathways and processes of transport from the trench to an individual or population include ground-water transport, overland flow, erosion, surface water dilution, suspension, atmospheric transport and deposition, inhalation, external exposure, and ingestion of contaminated beef, milk, crops, and water. The proposed waste disposal area in Koteyli, Balikesir, Turkey, has been evaluated using the PRESTO-II methodology. The results have been compared to those obtained for the Barnwell, South Carolina, site. Dose estimates for both sites are below regulatory limits, for the release and exposure scenarios considered. The doses for the sites are comparable, with slightly higher estimates obtained for the Turkish site. 7 refs., 1 tab

Predicting on-site environmental impacts of municipal engineering works

OpenAIRE

Gangolells Solanellas, Marta; Casals Casanova, Miquel; Forcada Matheu, Núria; Macarulla Martí, Marcel

2014-01-01

The research findings fill a gap in the body of knowledge by presenting an effective way to evaluate the significance of on-site environmental impacts of municipal engineering works prior to the construction stage. First, 42 on-site environmental impacts of municipal engineering works were identified by means of a process-oriented approach. Then, 46 indicators and their corresponding significance limits were determined on the basis of a statistical analysis of 25 new-build and remodelling mun...

Relativistic theory of gravitation and nonuniqueness of the predictions of general relativity theory

International Nuclear Information System (INIS)

Logunov, A.A.; Loskutov, Yu.M.

1986-01-01

It is shown that while the predictions of relativistic theory of gravitation (RTG) for the gravitational effects are unique and consistent with the experimental data available, the relevant predictions of general relativity theory are not unique. Therewith the above nonuniqueness manifests itself in some effects in the first order in the gravitational interaction constant in others in the second one. The absence in GRT of the energy-momentum and angular momentum conservation laws for the matter and gravitational field taken together and its inapplicability to give uniquely determined predictions for the gravitational phenomena compel to reject GRT as a physical theory

Investigation of anatomical anomalies in Hanford Site mule deer

Energy Technology Data Exchange (ETDEWEB)

Tiller, B.L.; Cadwell, L.L.; Poston, T.M. [and others

1997-03-01

Rocky Mountain mule deer (Odocoileus hemionus hemionus), common residents of the Hanford Site, are an important part of the shrub-steppe ecosystem as well as being valued for aesthetics and hunting. Because mule deer have been protected from hunting on the Site for 50 years, the herd has developed unique population characteristics, including a large number of old animals and males with either large or atypically developed antlers, in contrast to other herds in the semi-arid regions of the Northwest. Hanford Site mule deer have been studied since 1991 because of the herd`s unique nature and high degree of public interest. A special study of the mule deer herd was initiated in 1993 after observations were made of a relatively large number of male deer with atypical, velvet-covered antlers. This report specifically describes our analyses of adult male deer found on the Site with atypical antlers. The report includes estimates of population densities and composition; home ranges, habitat uses, and dietary habits; natural and human-induced causes of mortality; and the herd`s overall health and reproductive status.

Investigation of anatomical anomalies in Hanford Site mule deer

International Nuclear Information System (INIS)

Tiller, B.L.; Cadwell, L.L.; Poston, T.M.

1997-03-01

Rocky Mountain mule deer (Odocoileus hemionus hemionus), common residents of the Hanford Site, are an important part of the shrub-steppe ecosystem as well as being valued for aesthetics and hunting. Because mule deer have been protected from hunting on the Site for 50 years, the herd has developed unique population characteristics, including a large number of old animals and males with either large or atypically developed antlers, in contrast to other herds in the semi-arid regions of the Northwest. Hanford Site mule deer have been studied since 1991 because of the herd's unique nature and high degree of public interest. A special study of the mule deer herd was initiated in 1993 after observations were made of a relatively large number of male deer with atypical, velvet-covered antlers. This report specifically describes our analyses of adult male deer found on the Site with atypical antlers. The report includes estimates of population densities and composition; home ranges, habitat uses, and dietary habits; natural and human-induced causes of mortality; and the herd's overall health and reproductive status

Methods for estimating on-site ambient air concentrations at disposal sites

International Nuclear Information System (INIS)

Hwang, S.T.

1987-01-01

Currently, Gaussian type dispersion modeling and point source approximation are combined to estimate the ambient air concentrations of pollutants dispersed downwind of an areawide emission source, using the approach of virtual point source approximation. This Gaussian dispersion modeling becomes less accurate as the receptor comes closer to the source, and becomes inapplicable for the estimation of on-site ambient air concentrations at disposal sites. Partial differential equations are solved with appropriate boundary conditions for use in estimating the on-site concentrations in the ambient air impacted by emissions from an area source such as land disposal sites. Two variations of solution techniques are presented, and their predictions are compared

Domain-based small molecule binding site annotation

Directory of Open Access Journals (Sweden)

Dumontier Michel

2006-03-01

Full Text Available Abstract Background Accurate small molecule binding site information for a protein can facilitate studies in drug docking, drug discovery and function prediction, but small molecule binding site protein sequence annotation is sparse. The Small Molecule Interaction Database (SMID, a database of protein domain-small molecule interactions, was created using structural data from the Protein Data Bank (PDB. More importantly it provides a means to predict small molecule binding sites on proteins with a known or unknown structure and unlike prior approaches, removes large numbers of false positive hits arising from transitive alignment errors, non-biologically significant small molecules and crystallographic conditions that overpredict ion binding sites. Description Using a set of co-crystallized protein-small molecule structures as a starting point, SMID interactions were generated by identifying protein domains that bind to small molecules, using NCBI's Reverse Position Specific BLAST (RPS-BLAST algorithm. SMID records are available for viewing at http://smid.blueprint.org. The SMID-BLAST tool provides accurate transitive annotation of small-molecule binding sites for proteins not found in the PDB. Given a protein sequence, SMID-BLAST identifies domains using RPS-BLAST and then lists potential small molecule ligands based on SMID records, as well as their aligned binding sites. A heuristic ligand score is calculated based on E-value, ligand residue identity and domain entropy to assign a level of confidence to hits found. SMID-BLAST predictions were validated against a set of 793 experimental small molecule interactions from the PDB, of which 472 (60% of predicted interactions identically matched the experimental small molecule and of these, 344 had greater than 80% of the binding site residues correctly identified. Further, we estimate that 45% of predictions which were not observed in the PDB validation set may be true positives. Conclusion By

Testing Pearl Model In Three European Sites

Science.gov (United States)

Bouraoui, F.; Bidoglio, G.

The Plant Protection Product Directive (91/414/EEC) stresses the need of validated models to calculate predicted environmental concentrations. The use of models has become an unavoidable step before pesticide registration. In this context, European Commission, and in particular DGVI, set up a FOrum for the Co-ordination of pes- ticide fate models and their USe (FOCUS). In a complementary effort, DG research supported the APECOP project, with one of its objective being the validation and im- provement of existing pesticide fate models. The main topic of research presented here is the validation of the PEARL model for different sites in Europe. The PEARL model, actually used in the Dutch pesticide registration procedure, was validated in three well- instrumented sites: Vredepeel (the Netherlands), Brimstone (UK), and Lanna (Swe- den). A step-wise procedure was used for the validation of the PEARL model. First the water transport module was calibrated, and then the solute transport module, using tracer measurements keeping unchanged the water transport parameters. The Vrede- peel site is characterised by a sandy soil. Fourteen months of measurements were used for the calibration. Two pesticides were applied on the site: bentazone and etho- prophos. PEARL predictions were very satisfactory for both soil moisture content, and pesticide concentration in the soil profile. The Brimstone site is characterised by a cracking clay soil. The calibration was conducted on a time series measurement of 7 years. The validation consisted in comparing predictions and measurement of soil moisture at different soil depths, and in comparing the predicted and measured con- centration of isoproturon in the drainage water. The results, even if in good agreement with the measuremens, highlighted the limitation of the model when the preferential flow becomes a dominant process. PEARL did not reproduce well soil moisture pro- file during summer months, and also under-predicted the arrival of

A multidisciplinary fractured rock characterization study at Raymond field site, Raymond, California

International Nuclear Information System (INIS)

Karasaki, Kenzi; Freifeld, Barry; Cohen, Andrew; Cook, Paul; Vasco, Don; Grossenbacher, Ken

2001-01-01

A dedicated field site was developed and a suite of experiments were conducted in the Sierra Nevada foothills, near the town of Raymond, California to develop and test a multi-disciplinary approach to the characterization of groundwater flow and transport in fractured rocks. A wealth of geologic, hydrologic and geophysical data was collected at the site using a variety of unique tools. A cluster of nine approximately 90 m deep boreholes were drilled at the site in a V-shaped pattern with an angle of 60 degrees. The boreholes are spaced 7.5, 15, 30, and 60 meters from the central borehole. Various geophysical and hydrologic tests were conducted in and between these boreholes. Integration of cross-hole radar and seismic tomography, borehole flow surveys and images from a new digital borehole scanner indicated that groundwater flow is mainly confined to a few sub-horizontal fracture zones. A unique suite of hydraulic tests were conducted, in which three to four intervals in each of the nine boreholes were isolated using pneumatic packers. Some 130 injection tests were conducted, and more than 4,100 cross-hole transient pressure measurements were obtained. A computer algorithm was developed to analyze such massive interference data systematically. As a result of the analysis, an image of the fracture connections emerged, which is consistent with the geophysical data. High precision tiltmeters were effective in remotely characterizing the preferential flow path. Several radial convergent tracer tests were conducted by injecting a mixture of several conservative tracers and one sorbing tracer: deuterium, fluorescein, lithium bromide and polystyrene micro-spheres. Some differences between the breakthrough curves are observed, which may be due to possible differences among so-called 'conservative' tracers. Some characterization tools were found to be more effective than others in locating flowing fractures. However, no single tool was almighty. Characterization of

Disposal Activities and the Unique Waste Streams at the Nevada National Security Site (NNSS)

International Nuclear Information System (INIS)

Arnold, P.

2012-01-01

This slide show documents waste disposal at the Nevada National Security Site. Topics covered include: radionuclide requirements for waste disposal; approved performance assessment (PA) for depleted uranium disposal; requirements; program approval; the Waste Acceptance Review Panel (WARP); description of the Radioactive Waste Acceptance Program (RWAP); facility evaluation; recent program accomplishments, nuclear facility safety changes; higher-activity waste stream disposal; and, large volume bulk waste streams

History of the Hanford Site: 1943-1990

Energy Technology Data Exchange (ETDEWEB)

D.W. Harvey

2000-09-01

This booklet was developed to highlight the national and international historical events that occurred in association with the development of the Hanford Site. The purpose of the booklet is to increase the awareness Hanford Site employees have of the historical significance of the Site's contributions and missions during the Manhattan Project (1943-1946) and Cold War era (1946-1990). By increasing knowledge and understanding of the Site's unique heritage, it is hoped this publication will help generate an appreciation of the Site's historic buildings and structures, and, thus, instill a sense of ''ownership'' in these buildings. One cannot appreciate the historic significance of a place or building without first knowing its story.

Cancer: Unique to Older Adults

Science.gov (United States)

... A to Z › Cancer › Unique to Older Adults Font size A A A Print Share Glossary Unique ... group with other older people with the same type of cancer. Researchers have found that support groups ...

Prediction of Active Site and Distal Residues in E. coli DNA Polymerase III alpha Polymerase Activity.

Science.gov (United States)

Parasuram, Ramya; Coulther, Timothy A; Hollander, Judith M; Keston-Smith, Elise; Ondrechen, Mary Jo; Beuning, Penny J

2018-02-20

The process of DNA replication is carried out with high efficiency and accuracy by DNA polymerases. The replicative polymerase in E. coli is DNA Pol III, which is a complex of 10 different subunits that coordinates simultaneous replication on the leading and lagging strands. The 1160-residue Pol III alpha subunit is responsible for the polymerase activity and copies DNA accurately, making one error per 10 5 nucleotide incorporations. The goal of this research is to determine the residues that contribute to the activity of the polymerase subunit. Homology modeling and the computational methods of THEMATICS and POOL were used to predict functionally important amino acid residues through their computed chemical properties. Site-directed mutagenesis and biochemical assays were used to validate these predictions. Primer extension, steady-state single-nucleotide incorporation kinetics, and thermal denaturation assays were performed to understand the contribution of these residues to the function of the polymerase. This work shows that the top 15 residues predicted by POOL, a set that includes the three previously known catalytic aspartate residues, seven remote residues, plus five previously unexplored first-layer residues, are important for function. Six previously unidentified residues, R362, D405, K553, Y686, E688, and H760, are each essential to Pol III activity; three additional residues, Y340, R390, and K758, play important roles in activity.

Probe for the mutagenic activity of the carcinogen 4-aminobiphenyl: synthesis and characterization of an M13mp10 genome containing the major carcinogen-DNA adduct at a unique site

International Nuclear Information System (INIS)

Lasko, D.D.; Basu, A.K.; Kadlubar, F.F.; Evans, F.E.; Lay, J.O. Jr.; Essigmann, J.M.

1987-01-01

The duplex genome of Escherichia coli virus M13mp10 was modified at a unique site to contain N-(deoxyguanosin-8-yl)-4-aminobiphenyl (dG/sup 8-ABP/), the major carcinogen-DNA adduct of the human bladder carcinogen 4-aminobiphenyl. A tetradeoxynucleotide containing a single dG/sup 8-ABP/ residue was synthesized by reacting 5'-d(TpGpCpA)-3' with N-acetoxy-N-(trifluoroacetyl)-4-aminobiphenyl, followed by high-performance liquid chromatography purification of the principal reaction product 5'-d(TpG/sup 8-ABP/pCpA)-3' (yield 15-30%). Characterization by fast atom bombardment mass spectrometry confirmed the structure as an intact 4-aminobiphenyl-modified tetranucleotide, while 1 H nuclear magnetic resonance spectroscopy established the site of substitution and the existence of ring stacking between the carcinogen residue and DNA bases. Experiments in which the tetranucleotides were 5' end labeled with [ 32 P]phosphate revealed the following: 1)the adducted oligomer, when incubated in a 1000-fold molar excess in the presence of T4 DNA ligase and ATP, was found to be incorporated into the gapped DNA molecules with an efficiency of approximately 30%, as compared to the unadducted d(pTpGpCpA), which was incorporated with 60% ligation efficiency; 2)radioactivity from the 5' end of each tetranucleotide was physically mapped to a restriction fragment that contained the PstI site and represented 0.2% of the genome; 3) the presence of the lesion within the PstI recognition site inhibited the ability of PstI to cleave the genome at this site; 4)in genomes in which ligation occurred, T4 DNA ligase was capable of covalently joining both modified and unmodified tetranucleotides to the gapped structures on both the 5' and the 3' ends with at least 90% efficiency. On the basis of these and other data, the dG/sup 8-ABP/-modified genome was judged to be a useful probe for investigation of site-specific mutagenesis in E. coli

Prediction of resource volumes at untested locations using simple local prediction models

Science.gov (United States)

Attanasi, E.D.; Coburn, T.C.; Freeman, P.A.

2006-01-01

This paper shows how local spatial nonparametric prediction models can be applied to estimate volumes of recoverable gas resources at individual undrilled sites, at multiple sites on a regional scale, and to compute confidence bounds for regional volumes based on the distribution of those estimates. An approach that combines cross-validation, the jackknife, and bootstrap procedures is used to accomplish this task. Simulation experiments show that cross-validation can be applied beneficially to select an appropriate prediction model. The cross-validation procedure worked well for a wide range of different states of nature and levels of information. Jackknife procedures are used to compute individual prediction estimation errors at undrilled locations. The jackknife replicates also are used with a bootstrap resampling procedure to compute confidence bounds for the total volume. The method was applied to data (partitioned into a training set and target set) from the Devonian Antrim Shale continuous-type gas play in the Michigan Basin in Otsego County, Michigan. The analysis showed that the model estimate of total recoverable volumes at prediction sites is within 4 percent of the total observed volume. The model predictions also provide frequency distributions of the cell volumes at the production unit scale. Such distributions are the basis for subsequent economic analyses. ?? Springer Science+Business Media, LLC 2007.

Uniqueness in time measurement

International Nuclear Information System (INIS)

Lorenzen, P.

1981-01-01

According to P. Janich a clock is defined as an apparatus in which a point ( hand ) is moving uniformly on a straight line ( path ). For the definition of uniformly first the scaling (as a constant ratio of velocities) is defined without clocks. Thereafter the uniqueness of the time measurement can be proved using the prove of scaling of all clocks. But the uniqueness can be defined without scaling, as it is pointed out here. (orig.) [de

Genetic and caregiving-based contributions to infant attachment: unique associations with distress reactivity and attachment security.

Science.gov (United States)

Raby, K Lee; Cicchetti, Dante; Carlson, Elizabeth A; Cutuli, J J; Englund, Michelle M; Egeland, Byron

2012-09-01

In the longitudinal study reported here, we examined genetic and caregiving-based contributions to individual differences in infant attachment classifications. For 154 mother-infant pairs, we rated mothers' responsiveness to their 6-month-old infants during naturalistic interactions and classified infants' attachment organization at 12 and 18 months using the Strange Situation procedure. These infants were later genotyped with respect to the serotonin-transporter-linked polymorphic region (5-HTTLPR). Maternal responsiveness uniquely predicted infants' attachment security. Infants' 5-HTTLPR variation uniquely predicted their subtype of attachment security at 12 months and their subtype of attachment insecurity at 12 and 18 months. The short allele for 5-HTTLPR was associated with attachment classifications characterized by higher emotional distress. These findings suggest that 5-HTTLPR variation contributes to infants' emotional reactivity and that the degree to which caregivers are responsive influences how effectively infants use their caregivers for emotion regulation. Theoretical implications for the study of genetic and caregiving influences are discussed.

Summary of ground motion prediction results for Nevada Test Site underground nuclear explosions related to the Yucca Mountain project

International Nuclear Information System (INIS)

Walck, M.C.

1996-10-01

This report summarizes available data on ground motions from underground nuclear explosions recorded on and near the Nevada Test Site, with emphasis on the ground motions recorded at stations on Yucca Mountain, the site of a potential high-level radioactive waste repository. Sandia National Laboratories, through the Weapons Test Seismic Investigations project, collected and analyzed ground motion data from NTS explosions over a 14-year period, from 1977 through 1990. By combining these data with available data from earlier, larger explosions, prediction equations for several ground motion parameters have been developed for the Test Site area for underground nuclear explosion sources. Also presented are available analyses of the relationship between surface and downhole motions and spectra and relevant crustal velocity structure information for Yucca Mountain derived from the explosion data. The data and associated analyses demonstrate that ground motions at Yucca Mountain from nuclear tests have been at levels lower than would be expected from moderate to large earthquakes in the region; thus nuclear explosions, while located relatively close, would not control seismic design criteria for the potential repository

Summary of ground motion prediction results for Nevada Test Site underground nuclear explosions related to the Yucca Mountain project

Energy Technology Data Exchange (ETDEWEB)

Walck, M.C.

1996-10-01

This report summarizes available data on ground motions from underground nuclear explosions recorded on and near the Nevada Test Site, with emphasis on the ground motions recorded at stations on Yucca Mountain, the site of a potential high-level radioactive waste repository. Sandia National Laboratories, through the Weapons Test Seismic Investigations project, collected and analyzed ground motion data from NTS explosions over a 14-year period, from 1977 through 1990. By combining these data with available data from earlier, larger explosions, prediction equations for several ground motion parameters have been developed for the Test Site area for underground nuclear explosion sources. Also presented are available analyses of the relationship between surface and downhole motions and spectra and relevant crustal velocity structure information for Yucca Mountain derived from the explosion data. The data and associated analyses demonstrate that ground motions at Yucca Mountain from nuclear tests have been at levels lower than would be expected from moderate to large earthquakes in the region; thus nuclear explosions, while located relatively close, would not control seismic design criteria for the potential repository.

Establishing a predictive maintenance program at the Hanford Site

International Nuclear Information System (INIS)

Winslow, R.W.

1994-05-01

This document contains information about a new Predictive Maintenance Program being developed and implemented at the Hanford Reservation. Details of the document include: background on persons developing the program, history of predictive maintenance, implementation of new program, engineering task analysis, network development and new software, issues to be resolved, benefits expected, and appendix gives information about the symposium from which this paper is based

The role of sleep in predicting college academic performance: is it a unique predictor?

Science.gov (United States)

Taylor, Daniel J; Vatthauer, Karlyn E; Bramoweth, Adam D; Ruggero, Camilo; Roane, Brandy

2013-01-01

Few studies have looked at the predictability of academic performance (i.e., cumulative grade point average [GPA]) using sleep when common nonsleep predictors of academic performance are included. This project studied psychological, demographic, educational, and sleep risk factors of decreased academic performance in college undergraduates. Participants (N = 867) completed a questionnaire packet and sleep diary. It was hypothesized that low total sleep time (TST), increased sleep onset latency, later bedtimes, later wake times, and TST inconsistency would predict decreased academic performance. The most significant predictors of academic performance were high school GPA, standardized test scores (i.e., SAT/ACT), TST, time awake before arising (TWAK), TST inconsistency, and the quadratic terms of perceived stress (PSS) and TST.

Application of neural networks to waste site screening

International Nuclear Information System (INIS)

Dabiri, A.E.; Garrett, M.; Kraft, T.; Hilton, J.; VanHammersveld, M.

1993-02-01

Waste site screening requires knowledge of the actual concentrations of hazardous materials and rates of flow around and below the site with time. The present approach consists primarily of drilling boreholes near contaminated sites and chemically analyzing the extracted physical samples and processing the data. This is expensive and time consuming. The feasibility of using neural network techniques to reduce the cost of waste site screening was investigated. Two neural network techniques, gradient descent back propagation and fully recurrent back propagation were utilized. The networks were trained with data received from Westinghouse Hanford Corporation. The results indicate that the network trained with the fully recurrent technique shows satisfactory generalization capability. The predicted results are close to the results obtained from a mathematical flow prediction model. It is possible to develop a new tool to predict the waste plume, thus substantially reducing the number of the bore sites and samplings. There are a variety of applications for this technique in environmental site screening and remediation. One of the obvious applications would be for optimum well siting. A neural network trained from the existing sampling data could be utilized to decide where would be the best position for the next bore site. Other applications are discussed in the report

Site transition framework for long-term surveillance and maintenance

International Nuclear Information System (INIS)

2014-01-01

This document provides a framework for all U.S. Department of Energy (DOE) facilities and sites where DOE may have anticipated long-term surveillance and maintenance (LTSM) responsibilities. It is a tool to help facilitate a smooth transition from remediation to LTSM, providing a systematic process for affected parties to utilize in analyzing the baseline to understand and manage the actions from EM mission completion through a site's transition into LTSM. The framework is not meant to provide an exhaustive list of the specific requirement and information that are needed. Sites will have unique considerations that may not be adequately addressed by this tool, and it is anticipated that a team comprised of the transferring and receiving organization will use judgment in utilizing this augmenting with other DOE guidance. However the framework should be followed to the extent possible at each site; and adapted to accommodate unique site-specific requirements, needs, and documents. Since the objective of the tool is facilitate better understanding of the conditions of the site and the actions required for transfer, the transition team utilizing the checklist is expected to consult with management of both the receiving and transferring organization to verify that major concerns are addressed. Ideally, this framework should be used as early in the remediation process as possible. Subsequent applications of the Site Transition Framework (STF) to the site should be conducted periodically and used to verify that all appropriate steps have been or will be taken to close-out the site and that actions by both organization are identified to transfer the site to LTSM. The requirements are provided herein

Universal Access in Heritage Sites: A Case Study on Historic Sites in Jaipur, India.

Science.gov (United States)

Vardia, Shweta; Khare, Rachna; Khare, Ajay

2016-01-01

A nation is recognized by a range of its significant historical, cultural and natural properties. These properties are generally preserved and maintained either by national administration or by private owners and charitable trusts due to higher value of their cultural inheritance and termed globally as heritage or historic sites. Heritage sites are a significant asset, a unique and irreplaceable resource which reflects a rich and diverse expression of past societies and forms an integral part of local, regional and national cultural identity. Today, heritage sites also play an important role in communication and knowledge exchange. Thus the rapidly increasing heritage tourism industry faces several challenges too. One of the challenges is that there is a segment of society who is not yet able to equally enjoy the visit to historic structures/sites and attractions, facilities and services. This paper aims to study the experience and develop understanding regarding the heritage structures/sites approached and interacted by diverse users. This study is an outcome of a hands on workshop conducted with diverse users at various historic sites in the city of Jaipur viz. at The City Palace Complex, Jaipur, Jaigarh Fort and the Haveli at Kanota near to Jaipur India.

Modularity, comparative cognition and human uniqueness.

Science.gov (United States)

Shettleworth, Sara J

2012-10-05

Darwin's claim 'that the difference in mind between man and the higher animals … is certainly one of degree and not of kind' is at the core of the comparative study of cognition. Recent research provides unprecedented support for Darwin's claim as well as new reasons to question it, stimulating new theories of human cognitive uniqueness. This article compares and evaluates approaches to such theories. Some prominent theories propose sweeping domain-general characterizations of the difference in cognitive capabilities and/or mechanisms between adult humans and other animals. Dual-process theories for some cognitive domains propose that adult human cognition shares simple basic processes with that of other animals while additionally including slower-developing and more explicit uniquely human processes. These theories are consistent with a modular account of cognition and the 'core knowledge' account of children's cognitive development. A complementary proposal is that human infants have unique social and/or cognitive adaptations for uniquely human learning. A view of human cognitive architecture as a mosaic of unique and species-general modular and domain-general processes together with a focus on uniquely human developmental mechanisms is consistent with modern evolutionary-developmental biology and suggests new questions for comparative research.

Couple-level Minority Stress: An Examination of Same-sex Couples' Unique Experiences.

Science.gov (United States)

Frost, David M; LeBlanc, Allen J; de Vries, Brian; Alston-Stepnitz, Eli; Stephenson, Rob; Woodyatt, Cory

2017-12-01

Social stress resulting from stigma, prejudice, and discrimination-"minority stress"-negatively impacts sexual minority individuals' health and relational well-being. The present study examined how being in a same-sex couple can result in exposure to unique minority stressors not accounted for at the individual level. Relationship timeline interviews were conducted with 120 same-sex couples equally distributed across two study sites (Atlanta and San Francisco), gender (male and female), and relationship duration (at least six months but less than three years, at least three years but less than seven years, and seven or more years). Directed content analyses identified 17 unique couple-level minority stressors experienced within nine distinct social contexts. Analyses also revealed experiences of dyadic minority stress processes (stress discrepancies and stress contagion). These findings can be useful in future efforts to better understand and address the cumulative impact of minority stress on relational well-being and individual health.

Prediction of FAD binding sites in electron transport proteins according to efficient radial basis function networks and significant amino acid pairs.

Science.gov (United States)

Le, Nguyen-Quoc-Khanh; Ou, Yu-Yen

2016-07-30

Cellular respiration is a catabolic pathway for producing adenosine triphosphate (ATP) and is the most efficient process through which cells harvest energy from consumed food. When cells undergo cellular respiration, they require a pathway to keep and transfer electrons (i.e., the electron transport chain). Due to oxidation-reduction reactions, the electron transport chain produces a transmembrane proton electrochemical gradient. In case protons flow back through this membrane, this mechanical energy is converted into chemical energy by ATP synthase. The convert process is involved in producing ATP which provides energy in a lot of cellular processes. In the electron transport chain process, flavin adenine dinucleotide (FAD) is one of the most vital molecules for carrying and transferring electrons. Therefore, predicting FAD binding sites in the electron transport chain is vital for helping biologists understand the electron transport chain process and energy production in cells. We used an independent data set to evaluate the performance of the proposed method, which had an accuracy of 69.84 %. We compared the performance of the proposed method in analyzing two newly discovered electron transport protein sequences with that of the general FAD binding predictor presented by Mishra and Raghava and determined that the accuracy of the proposed method improved by 9-45 % and its Matthew's correlation coefficient was 0.14-0.5. Furthermore, the proposed method enabled reducing the number of false positives significantly and can provide useful information for biologists. We developed a method that is based on PSSM profiles and SAAPs for identifying FAD binding sites in newly discovered electron transport protein sequences. This approach achieved a significant improvement after we added SAAPs to PSSM features to analyze FAD binding proteins in the electron transport chain. The proposed method can serve as an effective tool for predicting FAD binding sites in electron

Application of combinatorial biocatalysis for a unique ring expansion of dihydroxymethylzearalenone.

Science.gov (United States)

Rich, Joseph O; Budde, Cheryl L; McConeghey, Luke D; Cotterill, Ian C; Mozhaev, Vadim V; Singh, Sheo B; Goetz, Michael A; Zhao, Annie; Michels, Peter C; Khmelnitsky, Yuri L

2009-06-01

Combinatorial biocatalysis was applied to generate a diverse set of dihydroxymethylzearalenone analogs with modified ring structure. In one representative chemoenzymatic reaction sequence, dihydroxymethylzearalenone was first subjected to a unique enzyme-catalyzed oxidative ring opening reaction that creates two new carboxylic groups on the molecule. These groups served as reaction sites for further derivatization involving biocatalytic ring closure reactions with structurally diverse bifunctional reagents, including different diols and diamines. As a result, a library of cyclic bislactones and bislactams was created, with modified ring structures covering chemical space and structure activity relationships unattainable by conventional synthetic means.

Unique Problems of Nuclear Technology and the Need for Humble Inquiry

International Nuclear Information System (INIS)

Schein, E.H.

2016-01-01

The concept of Safety Culture is widely accepted but not very well understood. In this paper I argue that the components of safety culture all hinge on whether the executives in the nuclear plant actually create the climate of trust and openness that the other attributes hinge on. The right kind of executive behaviour is especially important in nuclear plants and sites because of the unique characteristics of nuclear technology. In order to create the climate of trust and openness that is required I explain the concept of Humble Leadership as the essential characteristic needed in nuclear plan executives. (author)

Examining the Presence of Social Media on University Web Sites

Science.gov (United States)

Greenwood, Grant

2012-01-01

Over the past few years, social networking has exploded into a massive medium that has captured the attention of a large portion of the American population. The ever-growing social networking site(s) (SNS) movement has filled a networking gap and thus, has presented higher education institutions with unique opportunities (Reid 2009) to further…

A century of change in Kenya's mammal communities: increased richness and decreased uniqueness in six protected areas.

Directory of Open Access Journals (Sweden)

Anikó B Tóth

Full Text Available The potential for large-scale biodiversity losses as a result of climate change and human impact presents major challenges for ecology and conservation science. Governments around the world have established national parks and wildlife reserves to help protect biodiversity, but there are few studies on the long-term consequences of this strategy. We use Kenya as a case study to investigate species richness and other attributes of mammal communities in 6 protected areas over the past century. Museum records from African expeditions that comprehensively sampled mammals from these same areas in the early 1900's provide a baseline for evaluating changes in species richness and community structure over time. We compare species lists assembled from archived specimens (1896-1950 to those of corresponding modern protected areas (1950-2013. Species richness in Kenya was stable or increased at 5 out of 6 sites from historical to modern times. Beta-diversity, in contrast, decreased across all sites. Potential biases such as variable historical vs. modern collection effort and detection of small-bodied, rare, and low-visibility species do not account for the observed results. We attribute the pattern of decreased beta diversity primarily to increased site occupancy by common species across all body size classes. Despite a decrease in land area available to wildlife, our data do not show the extinctions predicted by species-area relationships. Moreover, the results indicate that species-area curves based solely on protected areas could underestimate diversity because they do not account for mammal species whose ranges extend beyond protected area boundaries. We conclude that the 6 protected areas have been effective in preserving species richness in spite of continuing conversion of wild grasslands to cropland, but the overall decrease in beta diversity indicates a decline in the uniqueness of mammal communities that historically characterized Kenya's varied

Predicting the Metabolic Sites by Flavin-Containing Monooxygenase on Drug Molecules Using SVM Classification on Computed Quantum Mechanics and Circular Fingerprints Molecular Descriptors.

Directory of Open Access Journals (Sweden)

Chien-Wei Fu

Full Text Available As an important enzyme in Phase I drug metabolism, the flavin-containing monooxygenase (FMO also metabolizes some xenobiotics with soft nucleophiles. The site of metabolism (SOM on a molecule is the site where the metabolic reaction is exerted by an enzyme. Accurate prediction of SOMs on drug molecules will assist the search for drug leads during the optimization process. Here, some quantum mechanics features such as the condensed Fukui function and attributes from circular fingerprints (called Molprint2D are computed and classified using the support vector machine (SVM for predicting some potential SOMs on a series of drugs that can be metabolized by FMO enzymes. The condensed Fukui function fA- representing the nucleophilicity of central atom A and the attributes from circular fingerprints accounting the influence of neighbors on the central atom. The total number of FMO substrates and non-substrates collected in the study is 85 and they are equally divided into the training and test sets with each carrying roughly the same number of potential SOMs. However, only N-oxidation and S-oxidation features were considered in the prediction since the available C-oxidation data was scarce. In the training process, the LibSVM package of WEKA package and the option of 10-fold cross validation are employed. The prediction performance on the test set evaluated by accuracy, Matthews correlation coefficient and area under ROC curve computed are 0.829, 0.659, and 0.877 respectively. This work reveals that the SVM model built can accurately predict the potential SOMs for drug molecules that are metabolizable by the FMO enzymes.

Unique differences in applying safety analyses for a graphite moderated, channel reactor

International Nuclear Information System (INIS)

Moffitt, R.L.

1993-06-01

Unlike its predecessors, the N Reactor at the Hanford Site in Washington State was designed to produce electricity for civilian energy use as well as weapons-grade plutonium. This paper describes the major problems associated with applying safety analysis methodologies developed for commercial light water reactors (LWR) to a unique reactor like the N Reactor. The focus of the discussion is on non-applicable LWR safety standards and computer modeling/analytical variances of standards. The approaches used to resolve these problems to develop safety standards and limits for the N Reactor are described

Climate Prediction - NOAA's National Weather Service

Science.gov (United States)

Statistical Models... MOS Prod GFS-LAMP Prod Climate Past Weather Predictions Weather Safety Weather Radio National Weather Service on FaceBook NWS on Facebook NWS Director Home > Climate > Predictions Climate Prediction Long range forecasts across the U.S. Climate Prediction Web Sites Climate Prediction

Unique Associations between Childhood Temperament Characteristics and Subsequent Psychopathology Symptom Trajectories from Childhood to Early Adolescence.

Science.gov (United States)

Forbes, Miriam K; Rapee, Ronald M; Camberis, Anna-Lisa; McMahon, Catherine A

2017-08-01

Existing research suggests that temperamental traits that emerge early in childhood may have utility for early detection and intervention for common mental disorders. The present study examined the unique relationships between the temperament characteristics of reactivity, approach-sociability, and persistence in early childhood and subsequent symptom trajectories of psychopathology (depression, anxiety, conduct disorder, and attention-deficit hyperactivity disorder; ADHD) from childhood to early adolescence. Data were from the first five waves of the older cohort from the Longitudinal Study of Australian Children (n = 4983; 51.2% male), which spanned ages 4-5 to 12-13. Multivariate ordinal and logistic regressions examined whether parent-reported child temperament characteristics at age 4-5 predicted the study child's subsequent symptom trajectories for each domain of psychopathology (derived using latent class growth analyses), after controlling for other presenting symptoms. Temperament characteristics differentially predicted the symptom trajectories for depression, anxiety, conduct disorder, and ADHD: Higher levels of reactivity uniquely predicted higher symptom trajectories for all 4 domains; higher levels of approach-sociability predicted higher trajectories of conduct disorder and ADHD, but lower trajectories of anxiety; and higher levels of persistence were related to lower trajectories of conduct disorder and ADHD. These findings suggest that temperament is an early identifiable risk factor for the development of psychopathology, and that identification and timely interventions for children with highly reactive temperaments in particular could prevent later mental health problems.

Site transition framework for long-term surveillance and maintenance

Energy Technology Data Exchange (ETDEWEB)

None

2014-04-01

This document provides a framework for all U.S. Department of Energy (DOE) facilities and sites where DOE may have anticipated long-term surveillance and maintenance (LTSM) responsibilities. It is a tool to help facilitate a smooth transition from remediation to LTSM, providing a systematic process for affected parties to utilize in analyzing the baseline to understand and manage the actions from EM mission completion through a site’s transition into LTSM. The framework is not meant to provide an exhaustive list of the specific requirement and information that are needed. Sites will have unique considerations that may not be adequately addressed by this tool, and it is anticipated that a team comprised of the transferring and receiving organization will use judgment in utilizing this augmenting with other DOE guidance. However the framework should be followed to the extent possible at each site; and adapted to accommodate unique site-specific requirements, needs, and documents. Since the objective of the tool is facilitate better understanding of the conditions of the site and the actions required for transfer, the transition team utilizing the checklist is expected to consult with management of both the receiving and transferring organization to verify that major concerns are addressed. Ideally, this framework should be used as early in the remediation process as possible. Subsequent applications of the Site Transition Framework (STF) to the site should be conducted periodically and used to verify that all appropriate steps have been or will be taken to close-out the site and that actions by both organization are identified to transfer the site to LTSM. The requirements are provided herein.

Unique properties associated with normal martensitic transition and strain glass transition – A simulation study

International Nuclear Information System (INIS)

Wang, Dong; Ni, Yan; Gao, Jinghui; Zhang, Zhen; Ren, Xiaobing; Wang, Yunzhi

2013-01-01

Highlights: ► We model the unique properties of strain glass which is different from that of normal martensite. ► We describe the importance of point defects in the formation of strain glass and related properties. ► The role of point defect can be attributed to global transition temperature effect (GTTE) and local field effect (LFE). -- Abstract: The transition behavior and unique properties associated with normal martensitic transition and strain glass transition are investigated by computer simulations using the phase field method. The simulations are based on a physical model that assumes that point defects alter the thermodynamic stability of martensite and create local lattice distortion. The simulation results show that strain glass transition exhibits different properties from those found in normal martensitic transformations. These unique properties include diffuse scattering pattern, “smear” elastic modulus peak, disappearance of heat flow peak and non-ergodicity. These simulation predictions agree well with the experimental observations

Artificial neural network approach to predict surgical site infection after free-flap reconstruction in patients receiving surgery for head and neck cancer.

Science.gov (United States)

Kuo, Pao-Jen; Wu, Shao-Chun; Chien, Peng-Chen; Chang, Shu-Shya; Rau, Cheng-Shyuan; Tai, Hsueh-Ling; Peng, Shu-Hui; Lin, Yi-Chun; Chen, Yi-Chun; Hsieh, Hsiao-Yun; Hsieh, Ching-Hua

2018-03-02

The aim of this study was to develop an effective surgical site infection (SSI) prediction model in patients receiving free-flap reconstruction after surgery for head and neck cancer using artificial neural network (ANN), and to compare its predictive power with that of conventional logistic regression (LR). There were 1,836 patients with 1,854 free-flap reconstructions and 438 postoperative SSIs in the dataset for analysis. They were randomly assigned tin ratio of 7:3 into a training set and a test set. Based on comprehensive characteristics of patients and diseases in the absence or presence of operative data, prediction of SSI was performed at two time points (pre-operatively and post-operatively) with a feed-forward ANN and the LR models. In addition to the calculated accuracy, sensitivity, and specificity, the predictive performance of ANN and LR were assessed based on area under the curve (AUC) measures of receiver operator characteristic curves and Brier score. ANN had a significantly higher AUC (0.892) of post-operative prediction and AUC (0.808) of pre-operative prediction than LR (both P <0.0001). In addition, there was significant higher AUC of post-operative prediction than pre-operative prediction by ANN (p<0.0001). With the highest AUC and the lowest Brier score (0.090), the post-operative prediction by ANN had the highest overall predictive performance. The post-operative prediction by ANN had the highest overall performance in predicting SSI after free-flap reconstruction in patients receiving surgery for head and neck cancer.

Low-level radioactive waste disposal at a humid site

International Nuclear Information System (INIS)

Lee, D.W.

1987-03-01

Waste management in humid environments poses a continuing challenge because of the potential contamination of groundwater in the long term. Short-term needs for waste disposal, regulatory uncertainty, and unique site and waste characteristics have led to the development of a site-specific waste classification and management system proposed for the Oak Ridge Reservation. The overlying principle of protection of public health and safety is used to define waste classes compatible with generated waste types, disposal sites and technologies, and treatment technologies. 1 fig., 1 tab

RADIOLYTIC HYDROGEN GENERATION INSAVANNAH RIVER SITE (SRS) HIGH LEVEL WASTETANKS COMPARISON OF SRS AND HANFORDMODELING PREDICTIONS

Energy Technology Data Exchange (ETDEWEB)

Crawford, C; Ned Bibler, N

2009-04-15

In the high level waste tanks at the Savannah River Site (SRS), hydrogen is produced continuously by interaction of the radiation in the tank with water in the waste. Consequently, the vapor spaces of the tanks are purged to prevent the accumulation of H{sub 2} and possible formation of a flammable mixture in a tank. Personnel at SRS have developed an empirical model to predict the rate of H{sub 2} formation in a tank. The basis of this model is the prediction of the G value for H{sub 2} production. This G value is the number of H{sub 2} molecules produced per 100 eV of radiolytic energy absorbed by the waste. Based on experimental studies it was found that the G value for H{sub 2} production from beta radiation and from gamma radiation were essentially equal. The G value for H{sub 2} production from alpha radiation was somewhat higher. Thus, the model has two equations, one for beta/gamma radiation and one for alpha radiation. Experimental studies have also indicated that both G values are decreased by the presence of nitrate and nitrite ions in the waste. These are the main scavengers for the precursors of H{sub 2} in the waste; thus the equations that were developed predict G values for hydrogen production as a function of the concentrations of these two ions in waste. Knowing the beta/gamma and alpha heat loads in the waste allows one to predict the total generation rate for hydrogen in a tank. With this prediction a ventilation rate can be established for each tank to ensure that a flammable mixture is not formed in the vapor space in a tank. Recently personnel at Hanford have developed a slightly different model for predicting hydrogen G values. Their model includes the same precursor for H{sub 2} as the SRS model but also includes an additional precursor not in the SRS model. Including the second precursor for H{sub 2} leads to different empirical equations for predicting the G values for H{sub 2} as a function of the nitrate and nitrite concentrations in

An archaeological predictive model for locating rock shelter sites in Hesse Germany) that contain both Final Palaeolithic archaeology and Laacher See tephra

DEFF Research Database (Denmark)

Sauer, Florian Rudolf; Hoggard, Christian Steven; Zernack, Anke Verena

of foragers and the Late Glacial environment there. In contrast, in the medial zone in Hesse only a small number of surface scatters of lithic artefacts are known. No Late Glacial sites, particularly not rock shelter and cave locations, have been excavated in this region. Yet, it is precisely such locations...... of human impacts following the eruption, a dataset of c. 800 rock shelter locations throughout the state of Hesse was used to generate an archaeological predictive model (APM). The database was compiled in the early 1990 for the purpose of discovering new and well-stratified sites (Hofbauer, 1995......). In the project presented here, a landscape-archaeological approach in GIS was employed to estimate the correspondence of the local topography of rock shelter features with the topographic and cultural framework of known Late Palaeolithic sites. Typical parameters like rock shelter orientation and distance...

Do the big-five personality traits predict empathic listening and assertive communication?

OpenAIRE

Sims, Ceri M.

2016-01-01

As personality traits can influence important social outcomes, the current research investigated whether the Big-Five had predictive influences on communication competences of active-empathic listening (AEL) and assertiveness. A sample of 245 adults of various ages completed the self-report scales. Both Agreeableness and Openness uniquely predicted AEL. Extraversion had the biggest influence onassertiveness but did not uniquely explain AEL variance. Conscientiousness and Neuroticism had small...

Prediction of residential radon exposure of the whole Swiss population: comparison of model-based predictions with measurement-based predictions.

Science.gov (United States)

Hauri, D D; Huss, A; Zimmermann, F; Kuehni, C E; Röösli, M

2013-10-01

Radon plays an important role for human exposure to natural sources of ionizing radiation. The aim of this article is to compare two approaches to estimate mean radon exposure in the Swiss population: model-based predictions at individual level and measurement-based predictions based on measurements aggregated at municipality level. A nationwide model was used to predict radon levels in each household and for each individual based on the corresponding tectonic unit, building age, building type, soil texture, degree of urbanization, and floor. Measurement-based predictions were carried out within a health impact assessment on residential radon and lung cancer. Mean measured radon levels were corrected for the average floor distribution and weighted with population size of each municipality. Model-based predictions yielded a mean radon exposure of the Swiss population of 84.1 Bq/m(3) . Measurement-based predictions yielded an average exposure of 78 Bq/m(3) . This study demonstrates that the model- and the measurement-based predictions provided similar results. The advantage of the measurement-based approach is its simplicity, which is sufficient for assessing exposure distribution in a population. The model-based approach allows predicting radon levels at specific sites, which is needed in an epidemiological study, and the results do not depend on how the measurement sites have been selected. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Anxiety Sensitivity Uniquely Predicts Exercise Behaviors in Young Adults Seeking to Increase Physical Activity.

Science.gov (United States)

Moshier, Samantha J; Szuhany, Kristin L; Hearon, Bridget A; Smits, Jasper A J; Otto, Michael W

2016-01-01

Individuals with elevated levels of anxiety sensitivity (AS) may be motivated to avoid aversive emotional or physical states, and therefore may have greater difficulty achieving healthy behavioral change. This may be particularly true for exercise, which produces many of the somatic sensations within the domain of AS concerns. Cross-sectional studies show a negative association between AS and exercise. However, little is known about how AS may prospectively affect attempts at behavior change in individuals who are motivated to increase their exercise. We recruited 145 young adults who self-identified as having a desire to increase their exercise behavior. Participants completed a web survey assessing AS and additional variables identified as important for behavior change-impulsivity, grit, perceived behavioral control, and action planning-and set a specific goal for exercising in the next week. One week later, a second survey assessed participants' success in meeting their exercise goals. We hypothesized that individuals with higher AS would choose lower exercise goals and would complete less exercise at the second survey. AS was not significantly associated with exercise goal level, but significantly and negatively predicted exercise at Time 2 and was the only variable to offer significant prediction beyond consideration of baseline exercise levels. These results underscore the importance of considering AS in relation to health behavior intentions. This is particularly apt given the absence of prediction offered by other traditional predictors of behavior change. © The Author(s) 2015.

Computational topology and the Unique Games Conjecture

OpenAIRE

Grochow, Joshua A.; Tucker-Foltz, Jamie

2018-01-01

Covering spaces of graphs have long been useful for studying expanders (as "graph lifts") and unique games (as the "label-extended graph"). In this paper we advocate for the thesis that there is a much deeper relationship between computational topology and the Unique Games Conjecture. Our starting point is Linial's 2005 observation that the only known problems whose inapproximability is equivalent to the Unique Games Conjecture - Unique Games and Max-2Lin - are instances of Maximum Section of...

Functional profiles reveal unique ecological roles of various biological soil crust organisms

Science.gov (United States)

Bowker, M.A.; Mau, R.L.; Maestre, F.T.; Escolar, C.; Castillo-Monroy, A. P.

2011-01-01

1. At the heart of the body of research on biodiversity effects on ecosystem function is the debate over whether different species tend to be functionally singular or redundant. When we consider ecosystem multi-function, the provision of multiple ecosystem functions simultaneously, we may find that seemingly redundant species may in fact play unique roles in ecosystems. 2. Over the last few decades, the significance of biological soil crusts (BSCs) as ecological boundaries and ecosystem engineers, and their multi-functional nature, has become increasingly well documented. We compiled 'functional profiles' of the organisms in this understudied community, to determine whether functional singularity emerges when multiple ecosystem functions are considered. 3. In two data sets, one representing multiple sites around the semi-arid regions of Spain (regional scale), and another from a single site in central Spain (local scale), we examined correlations between the abundance or frequency of BSC species in a community, and multiple surrogates of ecosystem functioning. There was a wide array of apparent effects of species on specific functions. 4. Notably, in gypsiferous soils and at regional scale, we found that indicators of carbon (C) and phosphorus cycling were apparently suppressed and promoted by the lichens Diploschistes diacapsis and Squamarina lentigera, respectively. The moss Pleurochaete squarrosa appears to promote C cycling in calcareous soils at this spatial scale. At the local scale in gypsiferous soils, D. diacapsis positively correlated with carbon cycling, but negatively with nitrogen cycling, whereas numerous lichens exhibited the opposite profile. 5. We found a high degree of functional singularity, i.e. that species were highly individualistic in their effects on multiple functions. Many functional attributes were not easily predictable from existing functional grouping systems based primarily on morphology. 6. Our results suggest that maintaining

SeedVicious: Analysis of microRNA target and near-target sites.

Science.gov (United States)

Marco, Antonio

2018-01-01

Here I describe seedVicious, a versatile microRNA target site prediction software that can be easily fitted into annotation pipelines and run over custom datasets. SeedVicious finds microRNA canonical sites plus other, less efficient, target sites. Among other novel features, seedVicious can compute evolutionary gains/losses of target sites using maximum parsimony, and also detect near-target sites, which have one nucleotide different from a canonical site. Near-target sites are important to study population variation in microRNA regulation. Some analyses suggest that near-target sites may also be functional sites, although there is no conclusive evidence for that, and they may actually be target alleles segregating in a population. SeedVicious does not aim to outperform but to complement existing microRNA prediction tools. For instance, the precision of TargetScan is almost doubled (from 11% to ~20%) when we filter predictions by the distance between target sites using this program. Interestingly, two adjacent canonical target sites are more likely to be present in bona fide target transcripts than pairs of target sites at slightly longer distances. The software is written in Perl and runs on 64-bit Unix computers (Linux and MacOS X). Users with no computing experience can also run the program in a dedicated web-server by uploading custom data, or browse pre-computed predictions. SeedVicious and its associated web-server and database (SeedBank) are distributed under the GPL/GNU license.

FACTORS PREDICTING CONSUMERS' ASSESSMENT OF ADVERTISEMENTS ON SOCIAL NETWORKING SITES

OpenAIRE

Hossam Deraz; Gabriel Baffour Awuah; Desalegn Abraha Gebrekidan

2015-01-01

Marketers act on social networking sites (SNSs) in order to be more efficient in merchandising their products and/or services. Even so, the scope of the published studies regarding the assessment of advertisements on social networking sites (SNAs) is limited. Consequently, the present study aimed to consider credibility and interactivity, in addition to information, entertainment and irritation values, as main factors for consumers’ assessment of SNAs, as perceived by SNSs’ users. An analysis...

Why Do We Pin? New Gratifications Explain Unique Activities in Pinterest

Directory of Open Access Journals (Sweden)

Ruoxu Wang

2016-08-01

Full Text Available Pinterest is now the fourth most popular social network site after Facebook, Twitter, and LinkedIn in the United States, offering its own suite of functions. This study investigated why individuals use specific features of Pinterest such as pinning, creating, liking, following, commenting, inviting, sharing, checking, searching, and browsing different categories. An online survey (N = 113 revealed that a brand new set of gratifications (specific to digital media predicted a large number of user behaviors in Pinterest. The results showcased the predictive value of affordance-based gratifications in shaping specific user behaviors on social-media.

Predictive Modelling and Time: An Experiment in Temporal Archaeological Predictive Models

OpenAIRE

David Ebert

2006-01-01

One of the most common criticisms of archaeological predictive modelling is that it fails to account for temporal or functional differences in sites. However, a practical solution to temporal or functional predictive modelling has proven to be elusive. This article discusses temporal predictive modelling, focusing on the difficulties of employing temporal variables, then introduces and tests a simple methodology for the implementation of temporal modelling. The temporal models thus created ar...

Data-Model Assimilation at the FACE and AmeriFlux Sites Toward Predictive Understanding of Carbon Sequestration at Ecosystem and Regional Scales

Energy Technology Data Exchange (ETDEWEB)

Luo, Yiqi [Univ. of Oklahoma, Norman, OK (United States)

2013-01-09

The project was conducted during the period from 9/1/2007 to 8/31/2011 with three major tasks: (1) development of data assimilation (DA) techniques for terrestrial carbon research; (2) applications of DA techniques to analysis of carbon cycle at Duke and other FACE sites; and (3) inverse analysis at AmeriFlux sites. During this period, we have developed a variety of techniques, including (1) ensemble Kalman filter to estimate model parameters or state variables (Gao et al. 2011), (2) Conditional inversion to estimate parameters of a carbon cycle model (Wu et al. 2009), and (3) various methods to quantify uncertainty of estimated parameters and predicted C sinks (e.g., Weng et al. 2011), and (4) information theory to evaluate information content of different model structures and data sets (Weng and Luo 2011). We applied the DA techniques to and did modeling at the Duke FACE and other global change experimental sites. We addressed the following issues: (1) interactive effects of CO₂, warming and precipitation on ecosystem processes (e.g., Luo et al. 2008, Weng and Luo 2008, Zhou et al. 2008), (2) effects of warming on estimated parameters related to photosynthesis and residence times (Zhou et al. 2010); and (3) uncertainty in estimated parameters and predicted C sequestration (Gao et al. 2011, Weng and Luo 2011). In addition, we have done data assimilation to estimate carbon residence and carbon sequestration in US continent (Zhou and Luo 2008) and temperature sensitivity at the global scale (Zhou et al. 2009).

High-level-waste containment for a thousand years: unique technical and research problems

International Nuclear Information System (INIS)

Davis, M.S.

1982-01-01

In the United States the present policy for disposal of high level nuclear wastes is focused on isolation of solidified wastes in a mined geologic repository. Safe isolation is to be achieved by utilizing both natural and man-made barriers which will act in concert to assure the overall conservative performance of the disposal system. The incorporation of predictable man-made barriers into the waste disposal strategy has generated some new and unique problems for the scientific community

Site-selective 13C labeling of proteins using erythrose

International Nuclear Information System (INIS)

Weininger, Ulrich

2017-01-01

NMR-spectroscopy enables unique experimental studies on protein dynamics at atomic resolution. In order to obtain a full atom view on protein dynamics, and to study specific local processes like ring-flips, proton-transfer, or tautomerization, one has to perform studies on amino-acid side chains. A key requirement for these studies is site-selective labeling with 13 C and/or 1 H, which is achieved in the most general way by using site-selectively 13 C-enriched glucose (1- and 2- 13 C) as the carbon source in bacterial expression systems. Using this strategy, multiple sites in side chains, including aromatics, become site-selectively labeled and suitable for relaxation studies. Here we systematically investigate the use of site-selectively 13 C-enriched erythrose (1-, 2-, 3- and 4- 13 C) as a suitable precursor for 13 C labeled aromatic side chains. We quantify 13 C incorporation in nearly all sites in all 20 amino acids and compare the results to glucose based labeling. In general the erythrose approach results in more selective labeling. While there is only a minor gain for phenylalanine and tyrosine side-chains, the 13 C incorporation level for tryptophan is at least doubled. Additionally, the Phe ζ and Trp η2 positions become labeled. In the aliphatic side chains, labeling using erythrose yields isolated 13 C labels for certain positions, like Ile β and His β, making these sites suitable for dynamics studies. Using erythrose instead of glucose as a source for site-selective 13 C labeling enables unique or superior labeling for certain positions and is thereby expanding the toolbox for customized isotope labeling of amino-acid side-chains.

OceanSITES RAMA daily in-situ data

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — OceanSITES daily in-situ data. OceanSITES Global Tropical Moored Buoy Array Research Moored Array for African-Asian-Australian Monsoon Analysis and Prediction (RAMA)...

Unveiling the 'unique bone': a study of the distribution of focal clavicular lesions

International Nuclear Information System (INIS)

Suresh, S.; Saifuddin, A.

2008-01-01

Clavicle is a unique bone for many reasons. There is no study discussing the differential diagnosis of clavicular lesions based on the site of occurrence or age at presentation. This study aims to determine whether the distribution of lesions affecting the clavicle and age at presentation aid in the differential diagnosis of focal clavicular lesions. Clinical notes, imaging and histopathological reports of the clavicular lesions between Jan 1999 and Jan 2006 were reviewed. Virtually, all patients had been referred as suspected neoplasm. Fifty-nine patients were identified. Patients 50 years (n=18) had predominantly malignant lesions. The lesions most commonly affected the medial third (n=35) and were predominantly non-neoplastic or benign. The middle third was affected in 15 patients and showed both benign and malignant lesions. The lateral third was least affected with predominance of malignant lesions. The clavicle is not a primary common site for any particular tumour; hence, diagnosis of the lesions can be challenging. Our study has suggested that few factors like age and site of the lesions may be helpful in diagnosis. (orig.)

Predicting tile drainage discharge

DEFF Research Database (Denmark)

Iversen, Bo Vangsø; Kjærgaard, Charlotte; Petersen, Rasmus Jes

used in the analysis. For the dynamic modelling, a simple linear reservoir model was used where different outlets in the model represented tile drain as well as groundwater discharge outputs. This modelling was based on daily measured tile drain discharge values. The statistical predictive model...... was based on a polynomial regression predicting yearly tile drain discharge values using site specific parameters such as soil type, catchment topography, etc. as predictors. Values of calibrated model parameters from the dynamic modelling were compared to the same site specific parameter as used...

Creativity and technical innovation: spatial ability's unique role.

Science.gov (United States)

Kell, Harrison J; Lubinski, David; Benbow, Camilla P; Steiger, James H

2013-09-01

In the late 1970s, 563 intellectually talented 13-year-olds (identified by the SAT as in the top 0.5% of ability) were assessed on spatial ability. More than 30 years later, the present study evaluated whether spatial ability provided incremental validity (beyond the SAT's mathematical and verbal reasoning subtests) for differentially predicting which of these individuals had patents and three classes of refereed publications. A two-step discriminant-function analysis revealed that the SAT subtests jointly accounted for 10.8% of the variance among these outcomes (p development of creativity, beyond the roles played by the abilities traditionally measured in educational selection, counseling, and industrial-organizational psychology. Spatial ability plays a key and unique role in structuring many important psychological phenomena and should be examined more broadly across the applied and basic psychological sciences.

The lost micro-deserts of the Patuxent River using landscape history, insect and plant specimens, and field work to detect and define a unique community

Science.gov (United States)

Droege, S.; Davis, C.A.; Steiner, W.E.; =Mawdsley, J.

2009-01-01

Historical and recent records of both plants and insects are synthesized for uplands along the eastern edge of Maryland?s Patuxent River from the edge of the Piedmont south to Jug Bay. This strip is characterized by deep sandy soils found in the Evesboro and Galestown sandy loams soil series. Within this narrow strip there exists a unique flora and fauna adapted to open dry sandy soils and occurring in small remnant patches associated with old sand mining operations and scattered protected areas. We illustrate the uniqueness of these sites using four groups, vascular plants, tenebrionid beetles (Coleoptera: Tenebrionidae), tiger beetles (Coleoptera: Cicindelidae), and bees (Hymenoptera: Apoidea: Anthophila). Within each of these groups, rare species were detected whose populations were locally restricted to this soil type and whose nearest known populations were often hundreds of kilometers away. In addition to documenting the direct conservation importance of these small sandy openings along the Patuxent, we contrast the lack of any indication from vertebrate inventories that this region is unique. The combination of plant and insect inventories appears to be a better means of clarifying a site?s importance than does any survey of a single taxonomic group.

The SMARTCyp cytochrome P450 metabolism prediction server

DEFF Research Database (Denmark)

Rydberg, Patrik; Gloriam, David Erik Immanuel; Olsen, Lars

2010-01-01

The SMARTCyp server is the first web application for site of metabolism prediction of cytochrome P450-mediated drug metabolism.......The SMARTCyp server is the first web application for site of metabolism prediction of cytochrome P450-mediated drug metabolism....

Prediction of nucleosome positioning based on transcription factor binding sites.

Directory of Open Access Journals (Sweden)

Xianfu Yi

Full Text Available BACKGROUND: The DNA of all eukaryotic organisms is packaged into nucleosomes, the basic repeating units of chromatin. The nucleosome consists of a histone octamer around which a DNA core is wrapped and the linker histone H1, which is associated with linker DNA. By altering the accessibility of DNA sequences, the nucleosome has profound effects on all DNA-dependent processes. Understanding the factors that influence nucleosome positioning is of great importance for the study of genomic control mechanisms. Transcription factors (TFs have been suggested to play a role in nucleosome positioning in vivo. PRINCIPAL FINDINGS: Here, the minimum redundancy maximum relevance (mRMR feature selection algorithm, the nearest neighbor algorithm (NNA, and the incremental feature selection (IFS method were used to identify the most important TFs that either favor or inhibit nucleosome positioning by analyzing the numbers of transcription factor binding sites (TFBSs in 53,021 nucleosomal DNA sequences and 50,299 linker DNA sequences. A total of nine important families of TFs were extracted from 35 families, and the overall prediction accuracy was 87.4% as evaluated by the jackknife cross-validation test. CONCLUSIONS: Our results are consistent with the notion that TFs are more likely to bind linker DNA sequences than the sequences in the nucleosomes. In addition, our results imply that there may be some TFs that are important for nucleosome positioning but that play an insignificant role in discriminating nucleosome-forming DNA sequences from nucleosome-inhibiting DNA sequences. The hypothesis that TFs play a role in nucleosome positioning is, thus, confirmed by the results of this study.

Heart Failure: Unique to Older Adults

Science.gov (United States)

... to Z › Heart Failure › Unique to Older Adults Font size A A A Print Share Glossary Unique ... will suffer from depression at some point. This type of severe depression is more serious than the ...

Genome-Wide Locations of Potential Epimutations Associated with Environmentally Induced Epigenetic Transgenerational Inheritance of Disease Using a Sequential Machine Learning Prediction Approach.

Directory of Open Access Journals (Sweden)

M Muksitul Haque

Full Text Available Environmentally induced epigenetic transgenerational inheritance of disease and phenotypic variation involves germline transmitted epimutations. The primary epimutations identified involve altered differential DNA methylation regions (DMRs. Different environmental toxicants have been shown to promote exposure (i.e., toxicant specific signatures of germline epimutations. Analysis of genomic features associated with these epimutations identified low-density CpG regions (<3 CpG / 100bp termed CpG deserts and a number of unique DNA sequence motifs. The rat genome was annotated for these and additional relevant features. The objective of the current study was to use a machine learning computational approach to predict all potential epimutations in the genome. A number of previously identified sperm epimutations were used as training sets. A novel machine learning approach using a sequential combination of Active Learning and Imbalance Class Learner analysis was developed. The transgenerational sperm epimutation analysis identified approximately 50K individual sites with a 1 kb mean size and 3,233 regions that had a minimum of three adjacent sites with a mean size of 3.5 kb. A select number of the most relevant genomic features were identified with the low density CpG deserts being a critical genomic feature of the features selected. A similar independent analysis with transgenerational somatic cell epimutation training sets identified a smaller number of 1,503 regions of genome-wide predicted sites and differences in genomic feature contributions. The predicted genome-wide germline (sperm epimutations were found to be distinct from the predicted somatic cell epimutations. Validation of the genome-wide germline predicted sites used two recently identified transgenerational sperm epimutation signature sets from the pesticides dichlorodiphenyltrichloroethane (DDT and methoxychlor (MXC exposure lineage F3 generation. Analysis of this positive validation

Controlling engineering project changes for multi-unit, multi-site standardized nuclear power plants

International Nuclear Information System (INIS)

Randall, E.; Boddeker, G.; McGugin, H.; Strother, E.; Waggoner, G.

1978-01-01

Multibillioin dollar multiple nuclear power plant projects have numerous potential sources of engineering changes. The majority of these are internally generated changes, client generated changes, and changes from construction, procurement, other engineering organizations, and regulatory organizations. For multiunit, multisite projects, the use of a standardized design is cost effective. Engineering changes can then be controlled for a single standardized design, and the unit or site unique changes can be treated as deviations. Once an effective change procedure is established for change control of the standardized design, the same procedures can be used for control of unit or site unique changes

Simultaneous alcohol and cannabis expectancies predict simultaneous use

Directory of Open Access Journals (Sweden)

Earleywine Mitch

2006-10-01

Full Text Available Abstract Background Simultaneous use of alcohol and cannabis predicts increased negative consequences for users beyond individual or even concurrent use of the two drugs. Given the widespread use of the drugs and common simultaneous consumption, problems unique to simultaneous use may bear important implications for many substance users. Cognitive expectancies offer a template for future drug use behavior based on previous drug experiences, accurately predicting future use and problems. Studies reveal similar mechanisms underlying both alcohol and cannabis expectancies, but little research examines simultaneous expectancies for alcohol and cannabis use. Whereas research has demonstrated unique outcomes associated with simultaneous alcohol and cannabis use, this study hypothesized that unique cognitive expectancies may underlie simultaneous alcohol and cannabis use. Results: This study examined a sample of 2600 (66% male; 34% female Internet survey respondents solicited through advertisements with online cannabis-related organizations. The study employed known measures of drug use and expectancies, as well as a new measure of simultaneous drug use expectancies. Expectancies for simultaneous use of alcohol and cannabis predicted simultaneous use over and above expectancies for each drug individually. Discussion Simultaneous expectancies may provide meaningful information not available with individual drug expectancies. These findings bear potential implications on the assessment and treatment of substance abuse problems, as well as researcher conceptualizations of drug expectancies. Policies directing the treatment of substance abuse and its funding ought to give unique consideration to simultaneous drug use and its cognitive underlying factors.

Stimulation site within the MRI-defined STN predicts postoperative motor outcome.

Science.gov (United States)

Wodarg, Fritz; Herzog, Jan; Reese, René; Falk, Daniela; Pinsker, Markus O; Steigerwald, Frank; Jansen, Olav; Deuschl, Günther; Mehdorn, H Maximillian; Volkmann, Jens

2012-06-01

High-frequency stimulation of the subthalamic nucleus (STN-HFS) is highly effective in treating motor symptoms in Parkinson's disease (PD) and medication side effects as well as in improving quality of life. Despite preoperative screening for patients as eligible candidates for this treatment, electrode position may furthermore influence treatment quality. Here, we investigated the relationship between the anatomical site of stimulation within the MRI-defined STN and the outcome of PD patients after STN-HFS. In 30 PD patients with bilateral STN stimulation, we retrospectively defined the boundaries of the STN within the axial target plane of the stereotactic T2-weighted MRI and determined the position of the active electrode contact in relation to the border of the STN. The position of the active contact within the STN was the only variable to predict the outcome of STN stimulation. In contrast, covariates such as age, disease duration, symptom severity, and response to levodopa had no effect. The lateral position of the stimulation contact within the STN led to significantly better clinical improvement, lower stimulation parameters, and less need for postoperative dopaminergic medication. The outcome of patients with stimulation contacts within the medial region of the STN was significantly worse. Precise targeting of the lateral region of the STN is essential for achieving sufficient stimulation efficacy. Preoperative T2-weighted MRI might be a useful component of the targeting procedure to improve the outcome of PD patients. Copyright © 2012 Movement Disorder Society.

Parental Expressivity and Parenting Styles in Chinese Families: Prospective and Unique Relations to Children's Psychological Adjustment.

Science.gov (United States)

Chen, Stephen H; Zhou, Qing; Eisenberg, Nancy; Valiente, Carlos; Wang, Yun

2011-01-01

OBJECTIVES: Parents from different cultures differ in how frequently they express emotions. However, the generalizability of the relations between parental expressivity and child adjustment in non-Western cultures has not been extensively studied. The goal of the present study was to investigate prospective relations between parental expressivity within the family (positive, negative dominant, and negative submissive expressivity) and Chinese children's psychological adjustment, above and beyond parenting styles. DESIGN: The study used two waves (3.8 years apart) of longitudinal data from a sample (n= 425) of children in Beijing (mean ages = 7.7 years at T1 and 11.6 years at T2). Parental expressivity and parenting styles were self-reported. To reduce the potential measurement overlap, items that tap parental expression of emotions toward the child were removed from the parenting style measure. Children's adjustment was measured with parents', teachers', and peers' or children's reports. RESULTS: Consistent with findings with European American samples, parental negative dominant expressivity uniquely and positively predicted Chinese children's externalizing problems controlling for prior externalizing problems, parenting styles, and family SES. Neither parental expressivity nor parenting styles uniquely predicted social competence. CONCLUSIONS: Despite previously reported cultural differences in the mean levels of parental expressivity, some of the socialization functions of parental expressivity found in Western countries can be generalized to Chinese families. Although parental expressivity and parenting styles are related constructs, their unique relations to child's adjustment suggest that they should be examined as distinct processes.

PhosphoRice: a meta-predictor of rice-specific phosphorylation sites

Directory of Open Access Journals (Sweden)

Que Shufu

2012-02-01

Full Text Available Abstract Background As a result of the growing body of protein phosphorylation sites data, the number of phosphoprotein databases is constantly increasing, and dozens of tools are available for predicting protein phosphorylation sites to achieve fast automatic results. However, none of the existing tools has been developed to predict protein phosphorylation sites in rice. Results In this paper, the phosphorylation site predictors, NetPhos 2.0, NetPhosK, Kinasephos, Scansite, Disphos and Predphosphos, were integrated to construct meta-predictors of rice-specific phosphorylation sites using several methods, including unweighted voting, unreduced weighted voting, reduced unweighted voting and weighted voting strategies. PhosphoRice, the meta-predictor produced by using weighted voting strategy with parameters selected by restricted grid search and conditional random search, performed the best at predicting phosphorylation sites in rice. Its Matthew's Correlation Coefficient (MCC and Accuracy (ACC reached to 0.474 and 73.8%, respectively. Compared to the best individual element predictor (Disphos_default, PhosphoRice archieved a significant increase in MCC of 0.071 (P Conclusions PhosphoRice is a powerful tool for predicting unidentified phosphorylation sites in rice. Compared to the existing methods, we found that our tool showed greater robustness in ACC and MCC. PhosphoRice is available to the public at http://bioinformatics.fafu.edu.cn/PhosphoRice.

Quantum mechanical design of enzyme active sites.

Science.gov (United States)

Zhang, Xiyun; DeChancie, Jason; Gunaydin, Hakan; Chowdry, Arnab B; Clemente, Fernando R; Smith, Adam J T; Handel, T M; Houk, K N

2008-02-01

The design of active sites has been carried out using quantum mechanical calculations to predict the rate-determining transition state of a desired reaction in presence of the optimal arrangement of catalytic functional groups (theozyme). Eleven versatile reaction targets were chosen, including hydrolysis, dehydration, isomerization, aldol, and Diels-Alder reactions. For each of the targets, the predicted mechanism and the rate-determining transition state (TS) of the uncatalyzed reaction in water is presented. For the rate-determining TS, a catalytic site was designed using naturalistic catalytic units followed by an estimation of the rate acceleration provided by a reoptimization of the catalytic site. Finally, the geometries of the sites were compared to the X-ray structures of related natural enzymes. Recent advances in computational algorithms and power, coupled with successes in computational protein design, have provided a powerful context for undertaking such an endeavor. We propose that theozymes are excellent candidates to serve as the active site models for design processes.

Baseline report - tall upland shrubland at the Rocky Flats Environmental Technology Site

International Nuclear Information System (INIS)

1997-03-01

Rocky Flats Environmental Technology Site (Site) is located on the Colorado Piedmont east of the Front Range between Boulder and Golden. At an elevation of approximately 6,000 feet, the Site contains a unique ecotonal mixture of mountain and prairie plant species, resulting from the topography and close proximity to the mountain front. The Buffer Zone surrounding the Industrial Area is one of the largest remaining undeveloped areas of its kind along the Colorado Piedmont. A number of plant communities at the Site have been identified as increasingly rare and unique by Site ecologists and the Colorado Natural Heritage Program (CNHP). These include the xeric tallgrass prairie, tall upland shrubland, wetlands, and Great Plains riparian woodland communities. Many of these communities support populations of increasingly rare animals as well, including the Preble's meadow jumping mouse, grasshopper sparrow, loggerhead shrike, Merriam's shrew, black crowned night heron, and Hops blue and Argos skipper butterflies. One of the more interesting and important plant communities at the Site is the tall upland shrubland community. It has been generally overlooked by previous Site ecological studies, probably due to its relatively small size; only 34 acres total. Although mentioned in a plant community ordination study conducted by Clark et al. and also in the Site baseline ecological study, few data were available on this plant community before the present study

Baseline report - tall upland shrubland at the Rocky Flats Environmental Technology Site

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-03-01

Rocky Flats Environmental Technology Site (Site) is located on the Colorado Piedmont east of the Front Range between Boulder and Golden. At an elevation of approximately 6,000 feet, the Site contains a unique ecotonal mixture of mountain and prairie plant species, resulting from the topography and close proximity to the mountain front. The Buffer Zone surrounding the Industrial Area is one of the largest remaining undeveloped areas of its kind along the Colorado Piedmont. A number of plant communities at the Site have been identified as increasingly rare and unique by Site ecologists and the Colorado Natural Heritage Program (CNHP). These include the xeric tallgrass prairie, tall upland shrubland, wetlands, and Great Plains riparian woodland communities. Many of these communities support populations of increasingly rare animals as well, including the Preble`s meadow jumping mouse, grasshopper sparrow, loggerhead shrike, Merriam`s shrew, black crowned night heron, and Hops blue and Argos skipper butterflies. One of the more interesting and important plant communities at the Site is the tall upland shrubland community. It has been generally overlooked by previous Site ecological studies, probably due to its relatively small size; only 34 acres total. Although mentioned in a plant community ordination study conducted by Clark et al. and also in the Site baseline ecological study, few data were available on this plant community before the present study.

Technical advisory on SSC site criteria and catalog of site information needs

Energy Technology Data Exchange (ETDEWEB)

1985-06-15

The Superconducting Super Collider, or SSC, is a proposed scientific instrument of the study of the fundamental nature of matter. In the SSC two 20-TeV beams of protons will be accelerated and counter circulate on an approximately circular path. The protons will be made to collide at six locations where detectors can be placed to count and measure the products of the collisions. These collisions, twenty times more energetic than in any existing facility, will enable scientists to probe deeper into the heart of matter in the quest for a deeper understanding of the universal forces of nature. The goal of the SSC project is to create a scientific laboratory in high energy physics whose facilities are unique. Ultimately the success of that laboratory will be measured by its scientific discoveries, measurements, interpretations, and innovations. Toward that end the accelerator-collider must be constructed to high standards at minimum cost and maximum effectiveness. Preparations must be made for future operations and a scientific-technical staff attracted and maintained. The chosen site must accommodate all of these factors. This document summarizes siting criteria for the SSC and enumerates site-specific information important to the evaluation of potential sites. This document is not a call for site proposals but a technical report prepared for the information and use of the Department of Energy (DOE).

High-Resolution Profiling of Drosophila Replication Start Sites Reveals a DNA Shape and Chromatin Signature of Metazoan Origins

Directory of Open Access Journals (Sweden)

Federico Comoglio

2015-05-01

Full Text Available At every cell cycle, faithful inheritance of metazoan genomes requires the concerted activation of thousands of DNA replication origins. However, the genetic and chromatin features defining metazoan replication start sites remain largely unknown. Here, we delineate the origin repertoire of the Drosophila genome at high resolution. We address the role of origin-proximal G-quadruplexes and suggest that they transiently stall replication forks in vivo. We dissect the chromatin configuration of replication origins and identify a rich spatial organization of chromatin features at initiation sites. DNA shape and chromatin configurations, not strict sequence motifs, mark and predict origins in higher eukaryotes. We further examine the link between transcription and origin firing and reveal that modulation of origin activity across cell types is intimately linked to cell-type-specific transcriptional programs. Our study unravels conserved origin features and provides unique insights into the relationship among DNA topology, chromatin, transcription, and replication initiation across metazoa.

Automatic generation of bioinformatics tools for predicting protein-ligand binding sites.

Science.gov (United States)

Komiyama, Yusuke; Banno, Masaki; Ueki, Kokoro; Saad, Gul; Shimizu, Kentaro

2016-03-15

Predictive tools that model protein-ligand binding on demand are needed to promote ligand research in an innovative drug-design environment. However, it takes considerable time and effort to develop predictive tools that can be applied to individual ligands. An automated production pipeline that can rapidly and efficiently develop user-friendly protein-ligand binding predictive tools would be useful. We developed a system for automatically generating protein-ligand binding predictions. Implementation of this system in a pipeline of Semantic Web technique-based web tools will allow users to specify a ligand and receive the tool within 0.5-1 day. We demonstrated high prediction accuracy for three machine learning algorithms and eight ligands. The source code and web application are freely available for download at http://utprot.net They are implemented in Python and supported on Linux. shimizu@bi.a.u-tokyo.ac.jp Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Expected brine movement at potential nuclear waste repository salt sites

International Nuclear Information System (INIS)

McCauley, V.S.; Raines, G.E.

1987-08-01

The BRINEMIG brine migration code predicts rates and quantities of brine migration to a waste package emplaced in a high-level nuclear waste repository in salt. The BRINEMIG code is an explicit time-marching finite-difference code that solves a mass balance equation and uses the Jenks equation to predict velocities of brine migration. Predictions were made for the seven potentially acceptable salt sites under consideration as locations for the first US high-level nuclear waste repository. Predicted total quantities of accumulated brine were on the order of 1 m 3 brine per waste package or less. Less brine accumulation is expected at domal salt sites because of the lower initial moisture contents relative to bedded salt sites. Less total accumulation of brine is predicted for spent fuel than for commercial high-level waste because of the lower temperatures generated by spent fuel. 11 refs., 36 figs., 29 tabs

Mapping Sites of O-Glycosylation and Fringe Elongation on Drosophila Notch*

Science.gov (United States)

Harvey, Beth M.; Rana, Nadia A.; Moss, Hillary; Leonardi, Jessica; Jafar-Nejad, Hamed; Haltiwanger, Robert S.

2016-01-01

Glycosylation of the Notch receptor is essential for its activity and serves as an important modulator of signaling. Three major forms of O-glycosylation are predicted to occur at consensus sites within the epidermal growth factor-like repeats in the extracellular domain of the receptor: O-fucosylation, O-glucosylation, and O-GlcNAcylation. We have performed comprehensive mass spectral analyses of these three types of O-glycosylation on Drosophila Notch produced in S2 cells and identified peptides containing all 22 predicted O-fucose sites, all 18 predicted O-glucose sites, and all 18 putative O-GlcNAc sites. Using semiquantitative mass spectral methods, we have evaluated the occupancy and relative amounts of glycans at each site. The majority of the O-fucose sites were modified to high stoichiometries. Upon expression of the β3-N-acetylglucosaminyltransferase Fringe with Notch, we observed varying degrees of elongation beyond O-fucose monosaccharide, indicating that Fringe preferentially modifies certain sites more than others. Rumi modified O-glucose sites to high stoichiometries, although elongation of the O-glucose was site-specific. Although the current putative consensus sequence for O-GlcNAcylation predicts 18 O-GlcNAc sites on Notch, we only observed apparent O-GlcNAc modification at five sites. In addition, we performed mass spectral analysis on endogenous Notch purified from Drosophila embryos and found that the glycosylation states were similar to those found on Notch from S2 cells. These data provide foundational information for future studies investigating the mechanisms of how O-glycosylation regulates Notch activity. PMID:27268051

Site characterization and validation - Final report

International Nuclear Information System (INIS)

Olsson, O.

1992-04-01

The central aims of the Site Characterization and Validation (SCV) project were to develop and apply; * an advanced site characterization methodology and * a methodology to validate the models used to describe groundwater flow and transport in fractured rock. The basic experiment within the SCV project was to predict the distribution of water flow and tracer transport through a volume of rock, before and after excavation of a sub-horizontal drift, and to compare these predictions with actual field measurements. A structured approach was developed to combine site characterization data into a geological and hydrogeological conceptual model of a site. The conceptual model was based on a binary description where the rock mass was divided into 'fracture zones' and 'averagely fractured rock'. This designation into categories was based on a Fracture Zone Index (FZI) derived from principal component analysis of single borehole data. The FZI was used to identify the location of fracture zones in the boreholes and the extent of the zones between the boreholes was obtained form remote sensing data (radar and seismics). The consistency of the geometric model thus defined, and its significance to the flow system, was verified by cross-hole hydraulic testing. The conceptual model of the SCV site contained three major and four minor fractures zones which were the principal hydraulic conduits at the site. The location and extent of the fracture zones were included explicitly in the flow and transport models. Four different numerical modelling approaches were pursued within the project; one porous medium approach, two discrete fracture approaches, and an equivalent discontinuum approach. A series of tracer tests was also included in the prediction-validation exercise. (120 refs.) (au)

The unique role of halogen substituents in the design of modern agrochemicals.

Science.gov (United States)

Jeschke, Peter

2010-01-01

The past 30 years have witnessed a period of significant expansion in the use of halogenated compounds in the field of agrochemical research and development. The introduction of halogens into active ingredients has become an important concept in the quest for a modern agrochemical with optimal efficacy, environmental safety, user friendliness and economic viability. Outstanding progress has been made, especially in synthetic methods for particular halogen-substituted key intermediates that were previously prohibitively expensive. Interestingly, there has been a rise in the number of commercial products containing 'mixed' halogens, e.g. one or more fluorine, chlorine, bromine or iodine atoms in addition to one or more further halogen atoms. Extrapolation of the current trend indicates that a definite growth is to be expected in fluorine-substituted agrochemicals throughout the twenty-first century. A number of these recently developed agrochemical candidates containing halogen substituents represent novel classes of chemical compounds with new modes of action. However, the complex structure-activity relationships associated with biologically active molecules mean that the introduction of halogens can lead to either an increase or a decrease in the efficacy of a compound, depending on its changed mode of action, physicochemical properties, target interaction or metabolic susceptibility and transformation. In spite of modern design concepts, it is still difficult to predict the sites in a molecule at which halogen substitution will result in optimal desired effects. This review describes comprehensively the successful utilisation of halogens and their unique role in the design of modern agrochemicals, exemplified by various commercial products from Bayer CropScience coming from different agrochemical areas.

Agenda Trending: Reciprocity and the Predictive Capacity of Social Networking Sites in Intermedia Agenda Setting across Topics over Time

Directory of Open Access Journals (Sweden)

Jacob Groshek

2013-08-01

Full Text Available In the contemporary converged media environment, agenda setting is being transformed by the dramatic growth of audiences that are simultaneously media users and producers. The study reported here addresses related gaps in the literature by first comparing the topical agendas of two leading traditional media outlets (New York Times and CNN with the most frequently shared stories and trending topics on two widely popular Social Networking Sites (Facebook and Twitter. Time-series analyses of the most prominent topics identify the extent to which traditional media sets the agenda for social media as well as reciprocal agenda-setting effects of social media topics entering traditional media agendas. In addition, this study examines social intermedia agenda setting topically and across time within social networking sites, and in so doing, adds a vital understanding of where traditional media, online uses, and social media content intersect around instances of focusing events, particularly elections. Findings identify core differences between certain traditional and social media agendas, but also within social media agendas that extend from uses examined here. Additional results further suggest important topical and event-oriented limitations upon the predictive capacit of social networking sites to shape traditional media agendas over time.

Unique specification of Yang-Mills solutions

International Nuclear Information System (INIS)

Campbell, W.B.; Joseph, D.W.; Morgan, T.A.

1980-01-01

Screened time-independent cylindrically-symmetric solutions of Yang-Mills equations are given which show that the source does not uniquely determine the field. However, these particular solutions suggest a natural way of uniquely specifying solutions in terms of a physical realization of a symmetry group. (orig.)

Computational predictive methods for fracture and fatigue

Science.gov (United States)

Cordes, J.; Chang, A. T.; Nelson, N.; Kim, Y.

1994-09-01

The damage-tolerant design philosophy as used by aircraft industries enables aircraft components and aircraft structures to operate safely with minor damage, small cracks, and flaws. Maintenance and inspection procedures insure that damages developed during service remain below design values. When damage is found, repairs or design modifications are implemented and flight is resumed. Design and redesign guidelines, such as military specifications MIL-A-83444, have successfully reduced the incidence of damage and cracks. However, fatigue cracks continue to appear in aircraft well before the design life has expired. The F16 airplane, for instance, developed small cracks in the engine mount, wing support, bulk heads, the fuselage upper skin, the fuel shelf joints, and along the upper wings. Some cracks were found after 600 hours of the 8000 hour design service life and design modifications were required. Tests on the F16 plane showed that the design loading conditions were close to the predicted loading conditions. Improvements to analytic methods for predicting fatigue crack growth adjacent to holes, when multiple damage sites are present, and in corrosive environments would result in more cost-effective designs, fewer repairs, and fewer redesigns. The overall objective of the research described in this paper is to develop, verify, and extend the computational efficiency of analysis procedures necessary for damage tolerant design. This paper describes an elastic/plastic fracture method and an associated fatigue analysis method for damage tolerant design. Both methods are unique in that material parameters such as fracture toughness, R-curve data, and fatigue constants are not required. The methods are implemented with a general-purpose finite element package. Several proof-of-concept examples are given. With further development, the methods could be extended for analysis of multi-site damage, creep-fatigue, and corrosion fatigue problems.

2S protein Ara h 7.0201 has unique epitopes compared to other Ara h 7 isoforms and is comparable to 2S proteins Ara h 2 and 6 in basophil degranulation capacity.

Science.gov (United States)

Hayen, S M; Ehlers, A M; den Hartog Jager, C F; Garssen, J; Knol, E F; Knulst, A C; Suer, W; Willemsen, L E M; Otten, H G

2018-07-01

Screening for specific IgE against 2S albumin proteins Ara h 2 and 6 has good positive predictive value in diagnosing peanut allergy. From the third 2S member Ara h 7, 3 isoforms have been identified. Their allergenicity has not been elucidated. This study investigated the allergenicity of Ara h 7 isoforms compared to Ara h 2 and 6. Sensitization of 15 DBPCFC-confirmed peanut-allergic patients to recombinant Ara h 2.0201, Ara h 6.01 and isoforms of recombinant Ara h 7 was determined by IgE immunoblotting strips. A basophil activation test (BAT) was performed in 9 patients to determine IgE-cross-linking capacities of the allergens. Sensitivity to the allergens was tested in 5 patients who were sensitized to at least 1 Ara h 7 isoform, by a concentration range in the BAT. 3D prediction models and sequence alignments were used to visualize differences between isoforms and to predict allergenic epitope regions. Sensitization to Ara h 7.0201 was most frequent (80%) and showed to be equally potent as Ara h 2.0201 and 6.01 in inducing basophil degranulation. Sensitization to Ara h 7.0201 together with Ara h 2.0201 and/or 6.01 was observed, indicating the presence of unique epitopes compared to the other 2 isoforms. Differences between the 3 Ara h 7 isoforms were observed in C-terminal cysteine residues, pepsin and trypsin cleavage sites and 3 single amino acid substitutions. The majority of peanut-allergic patients are sensitized to isoform Ara h 7.0201, which is functionally as active as Ara h 2.0201 and 6.01. Unique epitopes are most likely located in the C-terminus or an allergenic loop region which is a known allergenic epitope region for Ara h 2.0201 and 6.01. Due to its unique epitopes and allergenicity, it is an interesting candidate to improve the diagnostic accuracy for peanut allergy. © 2018 The Authors. Clinical & Experimental Allergy Published by John Wiley & Sons Ltd.

Historical Datasets Support Genomic Selection Models for the Prediction of Cotton Fiber Quality Phenotypes Across Multiple Environments.

Science.gov (United States)

Gapare, Washington; Liu, Shiming; Conaty, Warren; Zhu, Qian-Hao; Gillespie, Vanessa; Llewellyn, Danny; Stiller, Warwick; Wilson, Iain

2018-03-20

Genomic selection (GS) has successfully been used in plant breeding to improve selection efficiency and reduce breeding time and cost. However, there has not been a study to evaluate GS prediction models that may be used for predicting cotton breeding lines across multiple environments. In this study, we evaluated the performance of Bayes Ridge Regression, BayesA, BayesB, BayesC and Reproducing Kernel Hilbert Spaces regression models. We then extended the single-site GS model to accommodate genotype × environment interaction (G×E) in order to assess the merits of multi- over single-environment models in a practical breeding and selection context in cotton, a crop for which this has not previously been evaluated. Our study was based on a population of 215 upland cotton ( Gossypium hirsutum ) breeding lines which were evaluated for fiber length and strength at multiple locations in Australia and genotyped with 13,330 single nucleotide polymorphic (SNP) markers. BayesB, which assumes unique variance for each marker and a proportion of markers to have large effects, while most other markers have zero effect, was the preferred model. GS accuracy for fiber length based on a single-site model varied across sites, ranging from 0.27 to 0.77 (mean = 0.38), while that of fiber strength ranged from 0.19 to 0.58 (mean = 0.35) using randomly selected sub-populations as the training population. Prediction accuracies from the M×E model were higher than those for single-site and across-site models, with an average accuracy of 0.71 and 0.59 for fiber length and strength, respectively. The use of the M×E model could therefore identify which breeding lines have effects that are stable across environments and which ones are responsible for G×E and so reduce the amount of phenotypic screening required in cotton breeding programs to identify adaptable genotypes. Copyright © 2018, G3: Genes, Genomes, Genetics.

Does Early Childhood Callous-Unemotional Behavior Uniquely Predict Behavior Problems or Callous-Unemotional Behavior in Late Childhood?

Science.gov (United States)

Waller, Rebecca; Dishion, Thomas J.; Shaw, Daniel S.; Gardner, Frances; Wilson, Melvin N.; Hyde, Luke W.

2016-01-01

Callous-unemotional (CU) behavior has been linked to behavior problems in children and adolescents. However, few studies have examined whether CU behavior in "early childhood" predicts behavior problems or CU behavior in "late childhood". This study examined whether indicators of CU behavior at ages 2-4 predicted aggression,…

Study of the sorption of actinide analogues on calcite and smectite as a model to predict the evolution of radioactive waste disposal in geological sites

International Nuclear Information System (INIS)

Budiman Sastrowardoyo, Pratomo

1991-01-01

In the framework of the problem of the radioactive waste disposal in deep geological sites, the purpose of this study is to predict the sorption of radionuclides on minerals within the geological barrier, after the rupture of the containers and the release of the radionuclides into underground water. Neodymium labelled by 147 Nd was used as an analogue of trivalent actinides. Calcite and smectite were used as examples of altered minerals of granitic sites. In simple media, neodymium is retained with a high affinity on both minerals. Fast kinetics of fixation, high distribution coefficients and sorption capacities are favorable factors for the slowing down of radionuclide migration in underground water. Fixation on calcite is quasi irreversible. A second kinetic step was observed, leading to an increase of the retention capacity. In the first step, this is probably a superficial sorption, but with a non-homogeneous affinity for sorption sites. An exchange mechanism of Nd 3+ with Na + et Ca 2+ ions of smectite occurs. The Freundlich isotherm observed for both minerals can be used for predicting the retention of radioelements as a function of their concentration and introducing these data in a migration model after comparison with the results of dynamic and field experiments. (author) [fr

Success: evolutionary and structural properties of amino acids prove effective for succinylation site prediction.

Science.gov (United States)

López, Yosvany; Sharma, Alok; Dehzangi, Abdollah; Lal, Sunil Pranit; Taherzadeh, Ghazaleh; Sattar, Abdul; Tsunoda, Tatsuhiko

2018-01-19

Post-translational modification is considered an important biological mechanism with critical impact on the diversification of the proteome. Although a long list of such modifications has been studied, succinylation of lysine residues has recently attracted the interest of the scientific community. The experimental detection of succinylation sites is an expensive process, which consumes a lot of time and resources. Therefore, computational predictors of this covalent modification have emerged as a last resort to tackling lysine succinylation. In this paper, we propose a novel computational predictor called 'Success', which efficiently uses the structural and evolutionary information of amino acids for predicting succinylation sites. To do this, each lysine was described as a vector that combined the above information of surrounding amino acids. We then designed a support vector machine with a radial basis function kernel for discriminating between succinylated and non-succinylated residues. We finally compared the Success predictor with three state-of-the-art predictors in the literature. As a result, our proposed predictor showed a significant improvement over the compared predictors in statistical metrics, such as sensitivity (0.866), accuracy (0.838) and Matthews correlation coefficient (0.677) on a benchmark dataset. The proposed predictor effectively uses the structural and evolutionary information of the amino acids surrounding a lysine. The bigram feature extraction approach, while retaining the same number of features, facilitates a better description of lysines. A support vector machine with a radial basis function kernel was used to discriminate between modified and unmodified lysines. The aforementioned aspects make the Success predictor outperform three state-of-the-art predictors in succinylation detection.

How many molecular subtypes? Implications of the unique tumor principle in personalized medicine.

Science.gov (United States)

Ogino, Shuji; Fuchs, Charles S; Giovannucci, Edward

2012-07-01

Cancers are complex multifactorial diseases. For centuries, conventional organ-based classification system (i.e., breast cancer, lung cancer, colon cancer, colorectal cancer, prostate cancer, lymphoma, leukemia, and so on) has been utilized. Recently, molecular diagnostics has become an essential component in clinical decision-making. However, tumor evolution and behavior cannot accurately be predicted, despite numerous research studies reporting promising tumor biomarkers. To advance molecular diagnostics, a better understanding of intratumor and intertumor heterogeneity is essential. Tumor cells interact with the extracellular matrix and host non-neoplastic cells in the tumor microenvironment, which is influenced by genomic variation, hormones, and dietary, lifestyle and environmental exposures, implicated by molecular pathological epidemiology. Essentially, each tumor possesses its own unique characteristics in terms of molecular make-up, tumor microenvironment and interactomes within and between neoplastic and host cells. Starting from the unique tumor concept and paradigm, we can better classify tumors by molecular methods, and move closer toward personalized cancer medicine and prevention.

Communication: Understanding molecular representations in machine learning: The role of uniqueness and target similarity

Science.gov (United States)

Huang, Bing; von Lilienfeld, O. Anatole

2016-10-01

The predictive accuracy of Machine Learning (ML) models of molecular properties depends on the choice of the molecular representation. Inspired by the postulates of quantum mechanics, we introduce a hierarchy of representations which meet uniqueness and target similarity criteria. To systematically control target similarity, we simply rely on interatomic many body expansions, as implemented in universal force-fields, including Bonding, Angular (BA), and higher order terms. Addition of higher order contributions systematically increases similarity to the true potential energy and predictive accuracy of the resulting ML models. We report numerical evidence for the performance of BAML models trained on molecular properties pre-calculated at electron-correlated and density functional theory level of theory for thousands of small organic molecules. Properties studied include enthalpies and free energies of atomization, heat capacity, zero-point vibrational energies, dipole-moment, polarizability, HOMO/LUMO energies and gap, ionization potential, electron affinity, and electronic excitations. After training, BAML predicts energies or electronic properties of out-of-sample molecules with unprecedented accuracy and speed.

Uniqueness of time-independent electromagnetic fields

DEFF Research Database (Denmark)

Karlsson, Per W.

1974-01-01

As a comment on a recent paper by Steele, a more general uniqueness theorem for time-independent fields is mentioned. ©1974 American Institute of Physics......As a comment on a recent paper by Steele, a more general uniqueness theorem for time-independent fields is mentioned. ©1974 American Institute of Physics...

Changes in unique hues induced by chromatic surrounds.

Science.gov (United States)

Klauke, Susanne; Wachtler, Thomas

2016-03-01

A chromatic surround can have a strong influence on the perceived hue of a stimulus. We investigated whether chromatic induction has similar effects on the perception of colors that appear pure and unmixed (unique red, green, blue, and yellow) as on other colors. Subjects performed unique hue settings of stimuli in isoluminant surrounds of different chromaticities. Compared with the settings in a neutral gray surround, unique hue settings altered systematically with chromatic surrounds. The amount of induced hue shift depended on the difference between stimulus and surround hues, and was similar for unique hue settings as for settings of nonunique hues. Intraindividual variability in unique hue settings was roughly twice as high as for settings obtained in asymmetric matching experiments, which may reflect the presence of a reference stimulus in the matching task. Variabilities were also larger with chromatic surrounds than with neutral gray surrounds, for both unique hue settings and matching of nonunique hues. The results suggest that the neural representations underlying unique hue percepts are influenced by the same neural processing mechanisms as the percepts of other colors.

Canonical Labelling of Site Graphs

Directory of Open Access Journals (Sweden)

Nicolas Oury

2013-06-01

Full Text Available We investigate algorithms for canonical labelling of site graphs, i.e. graphs in which edges bind vertices on sites with locally unique names. We first show that the problem of canonical labelling of site graphs reduces to the problem of canonical labelling of graphs with edge colourings. We then present two canonical labelling algorithms based on edge enumeration, and a third based on an extension of Hopcroft's partition refinement algorithm. All run in quadratic worst case time individually. However, one of the edge enumeration algorithms runs in sub-quadratic time for graphs with "many" automorphisms, and the partition refinement algorithm runs in sub-quadratic time for graphs with "few" bisimulation equivalences. This suite of algorithms was chosen based on the expectation that graphs fall in one of those two categories. If that is the case, a combined algorithm runs in sub-quadratic worst case time. Whether this expectation is reasonable remains an interesting open problem.

Is Life Unique?

Science.gov (United States)

Abel, David L.

2011-01-01

Is life physicochemically unique? No. Is life unique? Yes. Life manifests innumerable formalisms that cannot be generated or explained by physicodynamics alone. Life pursues thousands of biofunctional goals, not the least of which is staying alive. Neither physicodynamics, nor evolution, pursue goals. Life is largely directed by linear digital programming and by the Prescriptive Information (PI) instantiated particularly into physicodynamically indeterminate nucleotide sequencing. Epigenomic controls only compound the sophistication of these formalisms. Life employs representationalism through the use of symbol systems. Life manifests autonomy, homeostasis far from equilibrium in the harshest of environments, positive and negative feedback mechanisms, prevention and correction of its own errors, and organization of its components into Sustained Functional Systems (SFS). Chance and necessity—heat agitation and the cause-and-effect determinism of nature’s orderliness—cannot spawn formalisms such as mathematics, language, symbol systems, coding, decoding, logic, organization (not to be confused with mere self-ordering), integration of circuits, computational success, and the pursuit of functionality. All of these characteristics of life are formal, not physical. PMID:25382119

The liberal illusion of uniqueness.

Science.gov (United States)

Stern, Chadly; West, Tessa V; Schmitt, Peter G

2014-01-01

In two studies, we demonstrated that liberals underestimate their similarity to other liberals (i.e., display truly false uniqueness), whereas moderates and conservatives overestimate their similarity to other moderates and conservatives (i.e., display truly false consensus; Studies 1 and 2). We further demonstrated that a fundamental difference between liberals and conservatives in the motivation to feel unique explains this ideological distinction in the accuracy of estimating similarity (Study 2). Implications of the accuracy of consensus estimates for mobilizing liberal and conservative political movements are discussed.

Quantifying and visualizing site performance in clinical trials.

Science.gov (United States)

Yang, Eric; O'Donovan, Christopher; Phillips, JodiLyn; Atkinson, Leone; Ghosh, Krishnendu; Agrafiotis, Dimitris K

2018-03-01

One of the keys to running a successful clinical trial is the selection of high quality clinical sites, i.e., sites that are able to enroll patients quickly, engage them on an ongoing basis to prevent drop-out, and execute the trial in strict accordance to the clinical protocol. Intuitively, the historical track record of a site is one of the strongest predictors of its future performance; however, issues such as data availability and wide differences in protocol complexity can complicate interpretation. Here, we demonstrate how operational data derived from central laboratory services can provide key insights into the performance of clinical sites and help guide operational planning and site selection for new clinical trials. Our methodology uses the metadata associated with laboratory kit shipments to clinical sites (such as trial and anonymized patient identifiers, investigator names and addresses, sample collection and shipment dates, etc.) to reconstruct the complete schedule of patient visits and derive insights about the operational performance of those sites, including screening, enrollment, and drop-out rates and other quality indicators. This information can be displayed in its raw form or normalized to enable direct comparison of site performance across studies of varied design and complexity. Leveraging Covance's market leadership in central laboratory services, we have assembled a database of operational metrics that spans more than 14,000 protocols, 1400 indications, 230,000 unique investigators, and 23 million patient visits and represents a significant fraction of all clinical trials run globally in the last few years. By analyzing this historical data, we are able to assess and compare the performance of clinical investigators across a wide range of therapeutic areas and study designs. This information can be aggregated across trials and geographies to gain further insights into country and regional trends, sometimes with surprising results. The

The Current and Historical Distribution of Special Status Amphibians at the Livermore Site and Site 300

Energy Technology Data Exchange (ETDEWEB)

Hattem, M V; Paterson, L; Woollett, J

2008-08-20

65 surveys were completed in 2002 to assess the current distribution of special status amphibians at the Lawrence Livermore National Laboratory's (LLNL) Livermore Site and Site 300. Combined with historical information from previous years, the information presented herein illustrates the dynamic and probable risk that amphibian populations face at both sites. The Livermore Site is developed and in stark contrast to the mostly undeveloped Site 300. Yet both sites have significant issues threatening the long-term sustainability of their respective amphibian populations. Livermore Site amphibians are presented with a suite of challenges inherent of urban interfaces, most predictably the bullfrog (Rana catesbeiana), while Site 300's erosion issues and periodic feral pig (Sus scrofa) infestations reduce and threaten populations. The long-term sustainability of LLNL's special status amphibians will require active management and resource commitment to maintain and restore amphibian habitat at both sites.

Unique Association of Rare Cardiovascular Disease in an Athlete With Ventricular Arrhythmias.

Science.gov (United States)

Santomauro, V; Contursi, M; Dellegrottaglie, S; Borsellino, G

2015-01-01

Ventricular arrhythmias are a leading cause of non-elegibility to competitive sport. The failure to detect a significant organic substrate in the initial stage of screening does not preclude the identification of structural pathologies in the follow-up by using advanced imaging techniques. Here we report the case of a senior athlete judged not elegible because an arrhythmia with the morphology consistent with the origin of the left ventricle, in which subsequent execution of a cardiac MR and a thoracic CT scan has allowed the identification of an unique association between an area of myocardial damage, probable site of origine of the arrhythma, and a rare aortic malformation.

30 CFR 46.11 - Site-specific hazard awareness training.

Science.gov (United States)

2010-07-01

... Section 46.11 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR EDUCATION AND... workers; (4) Customers, including commercial over-the-road truck drivers; (5) Construction workers or... procedures. The training must address site-specific health and safety risks, such as unique geologic or...

Mutational analysis of the antagonist-binding site of the histamine H(1) receptor.

Science.gov (United States)

Wieland, K; Laak, A M; Smit, M J; Kühne, R; Timmerman, H; Leurs, R

1999-10-15

We combined in a previously derived three-dimensional model of the histamine H(1) receptor (Ter Laak, A. M., Timmerman, H., Leurs, H., Nederkoorn, P. H. J., Smit, M. J., and Donne-Op den Kelder, G. M. (1995) J. Comp. Aid. Mol. Design. 9, 319-330) a pharmacophore for the H(1) antagonist binding site (Ter Laak, A. M., Venhorst, J., Timmerman, H., and Donné-Op de Kelder, G. M. (1994) J. Med. Chem. 38, 3351-3360) with the known interacting amino acid residue Asp(116) (in transmembrane domain III) of the H(1) receptor and verified the predicted receptor-ligand interactions by site-directed mutagenesis. This resulted in the identification of the aromatic amino acids Trp(167), Phe(433), and Phe(436) in transmembrane domains IV and VI of the H(1) receptor as probable interaction points for the trans-aromatic ring of the H(1) antagonists. Subsequently, a specific interaction of carboxylate moieties of two therapeutically important, zwitterionic H(1) antagonists with Lys(200) in transmembrane domain V was predicted. A Lys(200) --> Ala mutation results in a 50- (acrivastine) to 8-fold (d-cetirizine) loss of affinity of these zwitterionic antagonists. In contrast, the affinities of structural analogs of acrivastine and cetirizine lacking the carboxylate group, triprolidine and meclozine, respectively, are unaffected by the Lys(200) --> Ala mutation. These data strongly suggest that Lys(200), unique for the H(1) receptor, acts as a specific anchor point for these "second generation" H(1) antagonists.

The unique and shared contributions of arithmetic operation understanding and numerical magnitude representation to children's mathematics achievement.

Science.gov (United States)

Wong, Terry Tin-Yau

2017-12-01

The current study examined the unique and shared contributions of arithmetic operation understanding and numerical magnitude representation to children's mathematics achievement. A sample of 124 fourth graders was tested on their arithmetic operation understanding (as reflected by their understanding of arithmetic principles and the knowledge about the application of arithmetic operations) and their precision of rational number magnitude representation. They were also tested on their mathematics achievement and arithmetic computation performance as well as the potential confounding factors. The findings suggested that both arithmetic operation understanding and numerical magnitude representation uniquely predicted children's mathematics achievement. The findings highlight the significance of arithmetic operation understanding in mathematics learning. Copyright © 2017 Elsevier Inc. All rights reserved.

Methodology for predictive modeling of environmental transport and health effects for waste sites at the Savannah River Plant: Environmental information document

International Nuclear Information System (INIS)

Stephensen, D.E.; King, C.M.; Looney, B.B.; Grant, M.W.

1987-03-01

This document provides information on the methods used to predict chemical transport and the associated health risk for various postulated closure activities at waste sites. The document was prepared as background documentation for the Department of Energy's proposed Environmental Impact Statement (EIS) on waste management activities for groundwater protection at the Savannah River Plant (SRP). The various mathematical formulations used in the environmental transport analysis, the exposure assessment, and the health risk assessment used in the analysis of all foreseeable scenarios as defined by the National Environmental Policy Act (CFR, 1986) are presented in this document. The scenarios do not necessarily represent actual environmental conditions for every SRP waste site. This document was prepared in support of the National Environmental Policy Act process, but does not by itself satisfy federal or state regulatory requirements. 29 refs., 11 figs

Nucleos: a web server for the identification of nucleotide-binding sites in protein structures.

Science.gov (United States)

Parca, Luca; Ferré, Fabrizio; Ausiello, Gabriele; Helmer-Citterich, Manuela

2013-07-01

Nucleos is a web server for the identification of nucleotide-binding sites in protein structures. Nucleos compares the structure of a query protein against a set of known template 3D binding sites representing nucleotide modules, namely the nucleobase, carbohydrate and phosphate. Structural features, clustering and conservation are used to filter and score the predictions. The predicted nucleotide modules are then joined to build whole nucleotide-binding sites, which are ranked by their score. The server takes as input either the PDB code of the query protein structure or a user-submitted structure in PDB format. The output of Nucleos is composed of ranked lists of predicted nucleotide-binding sites divided by nucleotide type (e.g. ATP-like). For each ranked prediction, Nucleos provides detailed information about the score, the template structure and the structural match for each nucleotide module composing the nucleotide-binding site. The predictions on the query structure and the template-binding sites can be viewed directly on the web through a graphical applet. In 98% of the cases, the modules composing correct predictions belong to proteins with no homology relationship between each other, meaning that the identification of brand-new nucleotide-binding sites is possible using information from non-homologous proteins. Nucleos is available at http://nucleos.bio.uniroma2.it/nucleos/.

Atlantic Coast Unique Regional Atmospheric Tracer Experiment (ACURATE)

International Nuclear Information System (INIS)

Schubert, J.F.; Heffter, J.L.; Mead, G.A.

1983-05-01

The Atlantic Coast Unique Regional Atmospheric Tracer Experiment (ACURATE) is a program designed to obtain data necessary to evaluate atmospheric transport and diffusion models used to calculate regional population doses caused by nuclear facility emissions to the atmosphere. This experiment will significantly improve the basis for evaluating the cost effectiveness of different methods of managing airborne nuclear wastes. During the period from March 1982 through September 1982, twice daily air samples have been collected at each of five sampling stations located on a radial from the SRP to Murray Hill, NJ (1000 km). Kr-85 emitted from the F and H area chemical separations facilities is being used as a tracer to determine the transport and diffusion of atmospheric releases from the SRP. The Kr-85 concentrations in the air samples will be compared with the calculated concentrations as predicted by the transport and diffusion models. The Kr-85 data and the meteorological data are being archived and will be made available to the modeling community

Human Uniqueness, Cognition by Description, and Procedural Memory

Directory of Open Access Journals (Sweden)

John Bolender

2008-06-01

Full Text Available Evidence will be reviewed suggesting a fairly direct link between the human ability to think about entities which one has never perceived — here called “cognition by description” — and procedural memory. Cognition by description is a uniquely hominid trait which makes religion, science, and history possible. It is hypothesized that cognition by description (in the manner of Bertrand Russell’s “knowledge by description” requires variable binding, which in turn utilizes quantifier raising. Quantifier raising plausibly depends upon the computational core of language, specifically the element of it which Noam Chomsky calls “internal Merge”. Internal Merge produces hierarchical structures by means of a memory of derivational steps, a process plausibly involving procedural memory. The hypothesis is testable, predicting that procedural memory deficits will be accompanied by impairments in cognition by description. We also discuss neural mechanisms plausibly underlying procedural memory and also, by our hypothesis, cognition by description.

Evolutionary genomics of archaeal viruses: unique viral genomes in the third domain of life

DEFF Research Database (Denmark)

Prangishvili, D.; Garrett, R. A.; Koonin, E.

2006-01-01

In terms of virion morphology, the known viruses of archaea fall into two distinct classes: viruses of mesophilic and moderately thermophilic Eueryarchaeota closely resemble head-and-tail bacteriophages whereas viruses of hyperthermophilic Crenarchaeota show a variety of unique morphotypes...... of bacteriophages. The proteins encoded by the genes belonging to this pool include predicted transcription regulators, ATPases implicated in viral DNA replication and packaging, enzymes of DNA precursor metabolism, RNA modification enzymes, and glycosylases. In addition, each of the crenarchaeal viruses encodes...

Addressing Uniqueness and Unison of Reliability and Safety for a Better Integration

Science.gov (United States)

Huang, Zhaofeng; Safie, Fayssal

2016-01-01

Over time, it has been observed that Safety and Reliability have not been clearly differentiated, which leads to confusion, inefficiency, and, sometimes, counter-productive practices in executing each of these two disciplines. It is imperative to address this situation to help Reliability and Safety disciplines improve their effectiveness and efficiency. The paper poses an important question to address, "Safety and Reliability - Are they unique or unisonous?" To answer the question, the paper reviewed several most commonly used analyses from each of the disciplines, namely, FMEA, reliability allocation and prediction, reliability design involvement, system safety hazard analysis, Fault Tree Analysis, and Probabilistic Risk Assessment. The paper pointed out uniqueness and unison of Safety and Reliability in their respective roles, requirements, approaches, and tools, and presented some suggestions for enhancing and improving the individual disciplines, as well as promoting the integration of the two. The paper concludes that Safety and Reliability are unique, but compensating each other in many aspects, and need to be integrated. Particularly, the individual roles of Safety and Reliability need to be differentiated, that is, Safety is to ensure and assure the product meets safety requirements, goals, or desires, and Reliability is to ensure and assure maximum achievability of intended design functions. With the integration of Safety and Reliability, personnel can be shared, tools and analyses have to be integrated, and skill sets can be possessed by the same person with the purpose of providing the best value to a product development.

Coexistence of uniquely ergodic subsystems of interval mapping

International Nuclear Information System (INIS)

Ye Xiangdong.

1991-10-01

The purpose of this paper is to show that uniquely ergodic subsystems of interval mapping also coexist in the same way as minimal sets do. To do this we give some notations in section 2. In section 3 we define D-function of a uniquely ergodic system and show its basic properties. We prove the coexistence of uniquely ergodic subsystems of interval mapping in section 4. Lastly we give the examples of uniquely ergodic systems with given D-functions in section 5. 27 refs

Unique Results and Lessons Learned From the TSS Missions

Science.gov (United States)

Stone, Nobie H.

2016-01-01

The Tethered Satellite System (TSS) Space Shuttle missions, TSS-1 in 1993 and TSS-1R in 1996, were the height of space tether technology development in the U.S. Altogether, the investment made by NASA and the Italian Space Agency (ASI) over the thirteen-year period of the TSS Program totaled approximately $400M-exclusive of the two Space Shuttle flights provided by NASA. Since those two pioneering missions, there have been several smaller tether flight experiments, but interest in this promising technology has waned within NASA as well as the DOD agencies. This is curious in view of the unique capabilities of space tether systems and the fact that they have been flight validated in earth orbit and shown to perform better than the preflight dynamic or electrodynamic theoretical predictions. While it is true that the TSS-1 and TSS-1R missions experienced technical difficulties, the causes of these early developmental problems are now known to have been engineering design flaws, material selection, and procedural issues that (1) are unrelated to the basic viability of space tether technology, and (2) can be readily corrected. The purpose of this paper is to review the dynamic and electrodynamic fundamentals of space tethers and the unique capabilities they afford (that are enabling to certain types of space missions); to elucidate the nature, cause, and solution of the early developmental problems; and to provide an update on progress made in development of the technology.

Prediction of supratidal Zones as turtle nesting sites using remote sensing and geographic information system, a case study in Pacitan, Southern Java Sea

Science.gov (United States)

Darmawan, A.; Saputra, D. K.; Wiadnya, D. G. R.; Gusmida, A. M.

2018-04-01

Turtles, the most threatened coastal-marine fauna, are protected through both national and global regulations. However, many of their nesting sites have been degraded in the past years. Completing natal homing, adult females emerged at night to lay-down eggs in the upper intertidal and supra-tidal zone of sandy beach from where they hatched. This study explained coastal topology of beaches usually used for nesting sites, covering 117 km coastline at Pacitan Regency, Southern Java Sea. The shift in beach morphology through times was figured out based on Landsat 8 and Sentinel 2a satellite imagery and remote sensing (GIS methods). This was combined with in-situ data on current coastline features, slope, and tide variations. Results showed a typical sandy beach, called Taman Ria Beach, a long time identified as nesting site for Lepidochelys olivacea, locally named as Penyu Lekang. Also, there was approximatelly 3.49 ha of supratidal area predicted in Taman Ria Beach according this study

The Role of Sleep in Predicting College Academic Performance: Is It A Unique Predictor?

OpenAIRE

Taylor, Daniel J.; Vatthauer, Karlyn E.; Bramoweth, Adam D.; Ruggero, Camilo; Roane, Brandy

2013-01-01

Few studies have looked at the predictability of academic performance (i.e., cumulative grade point average [GPA]) using sleep when common nonsleep predictors of academic performance are included. The present project studied psychological, demographic, educational, and sleep risk factors of decreased academic performance in college undergraduates. Subjects (N = 867) completed a questionnaire packet and sleep diary. It was hypothesized that low total sleep time (TST), increased sleep onset lat...

Site-selective {sup 13}C labeling of proteins using erythrose

Energy Technology Data Exchange (ETDEWEB)

Weininger, Ulrich, E-mail: ulrich.weininger@physik.uni-halle.de [Lund University, Department of Biophysical Chemistry, Center for Molecular Protein Science (Sweden)

2017-03-15

NMR-spectroscopy enables unique experimental studies on protein dynamics at atomic resolution. In order to obtain a full atom view on protein dynamics, and to study specific local processes like ring-flips, proton-transfer, or tautomerization, one has to perform studies on amino-acid side chains. A key requirement for these studies is site-selective labeling with {sup 13}C and/or {sup 1}H, which is achieved in the most general way by using site-selectively {sup 13}C-enriched glucose (1- and 2-{sup 13}C) as the carbon source in bacterial expression systems. Using this strategy, multiple sites in side chains, including aromatics, become site-selectively labeled and suitable for relaxation studies. Here we systematically investigate the use of site-selectively {sup 13}C-enriched erythrose (1-, 2-, 3- and 4-{sup 13}C) as a suitable precursor for {sup 13}C labeled aromatic side chains. We quantify {sup 13}C incorporation in nearly all sites in all 20 amino acids and compare the results to glucose based labeling. In general the erythrose approach results in more selective labeling. While there is only a minor gain for phenylalanine and tyrosine side-chains, the {sup 13}C incorporation level for tryptophan is at least doubled. Additionally, the Phe ζ and Trp η2 positions become labeled. In the aliphatic side chains, labeling using erythrose yields isolated {sup 13}C labels for certain positions, like Ile β and His β, making these sites suitable for dynamics studies. Using erythrose instead of glucose as a source for site-selective {sup 13}C labeling enables unique or superior labeling for certain positions and is thereby expanding the toolbox for customized isotope labeling of amino-acid side-chains.

Measured and predicted aerosol light scattering enhancement factors at the high alpine site Jungfraujoch

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R. Fierz-Schmidhauser

2010-03-01

Full Text Available Ambient relative humidity (RH determines the water content of atmospheric aerosol particles and thus has an important influence on the amount of visible light scattered by particles. The RH dependence of the particle light scattering coefficient (σ_sp is therefore an important variable for climate forcing calculations. We used a humidification system for a nephelometer which allows for the measurement of σ_sp at a defined RH in the range of 20–95%. In this paper we present measurements of light scattering enhancement factors f(RH=σ_sp(RH/σ_sp(dry from a 1-month campaign (May 2008 at the high alpine site Jungfraujoch (3580 m a.s.l., Switzerland. Measurements at the Jungfraujoch are representative for the lower free troposphere above Central Europe. For this aerosol type hardly any information about the f(RH is available so far. At this site, f(RH=85% varied between 1.2 and 3.3. Measured f(RH agreed well with f(RH calculated with Mie theory using measurements of the size distribution, chemical composition and hygroscopic diameter growth factors as input. Good f(RH predictions at RH<85% were also obtained with a simplified model, which uses the Ångström exponent of σ_sp(dry as input. RH influences further intensive optical aerosol properties. The backscatter fraction decreased by about 30% from 0.128 to 0.089, and the single scattering albedo increased on average by 0.05 at 85% RH compared to dry conditions. These changes in σ_sp, backscatter fraction and single scattering albedo have a distinct impact on the radiative forcing of the Jungfraujoch aerosol.

A consistency-based feature selection method allied with linear SVMs for HIV-1 protease cleavage site prediction.

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Orkun Oztürk

Full Text Available BACKGROUND: Predicting type-1 Human Immunodeficiency Virus (HIV-1 protease cleavage site in protein molecules and determining its specificity is an important task which has attracted considerable attention in the research community. Achievements in this area are expected to result in effective drug design (especially for HIV-1 protease inhibitors against this life-threatening virus. However, some drawbacks (like the shortage of the available training data and the high dimensionality of the feature space turn this task into a difficult classification problem. Thus, various machine learning techniques, and specifically several classification methods have been proposed in order to increase the accuracy of the classification model. In addition, for several classification problems, which are characterized by having few samples and many features, selecting the most relevant features is a major factor for increasing classification accuracy. RESULTS: We propose for HIV-1 data a consistency-based feature selection approach in conjunction with recursive feature elimination of support vector machines (SVMs. We used various classifiers for evaluating the results obtained from the feature selection process. We further demonstrated the effectiveness of our proposed method by comparing it with a state-of-the-art feature selection method applied on HIV-1 data, and we evaluated the reported results based on attributes which have been selected from different combinations. CONCLUSION: Applying feature selection on training data before realizing the classification task seems to be a reasonable data-mining process when working with types of data similar to HIV-1. On HIV-1 data, some feature selection or extraction operations in conjunction with different classifiers have been tested and noteworthy outcomes have been reported. These facts motivate for the work presented in this paper. SOFTWARE AVAILABILITY: The software is available at http

Non-unique Product Groups on Two Generators

OpenAIRE

Carter, William Paul

2007-01-01

The main purpose of this paper is to better understand groups that do not have the unique product property. In particular, the goal is to better understand Promislow's example, G, of such a group. In doing so, we will develop methods for generating examples of other sets that do not have the unique product property. With these methods we can show that there exists other distinct 14 element, square, non-unique product sets in G that are not inversions or translations. Also, this paper answers ...

Consensus models to predict endocrine disruption for all ...

Science.gov (United States)

Humans are potentially exposed to tens of thousands of man-made chemicals in the environment. It is well known that some environmental chemicals mimic natural hormones and thus have the potential to be endocrine disruptors. Most of these environmental chemicals have never been tested for their ability to disrupt the endocrine system, in particular, their ability to interact with the estrogen receptor. EPA needs tools to prioritize thousands of chemicals, for instance in the Endocrine Disruptor Screening Program (EDSP). Collaborative Estrogen Receptor Activity Prediction Project (CERAPP) was intended to be a demonstration of the use of predictive computational models on HTS data including ToxCast and Tox21 assays to prioritize a large chemical universe of 32464 unique structures for one specific molecular target – the estrogen receptor. CERAPP combined multiple computational models for prediction of estrogen receptor activity, and used the predicted results to build a unique consensus model. Models were developed in collaboration between 17 groups in the U.S. and Europe and applied to predict the common set of chemicals. Structure-based techniques such as docking and several QSAR modeling approaches were employed, mostly using a common training set of 1677 compounds provided by U.S. EPA, to build a total of 42 classification models and 8 regression models for binding, agonist and antagonist activity. All predictions were evaluated on ToxCast data and on an exte

Molecular Evolutionary Characterization of a V1R Subfamily Unique to Strepsirrhine Primates

Science.gov (United States)

Yoder, Anne D.; Chan, Lauren M.; dos Reis, Mario; Larsen, Peter A.; Campbell, C. Ryan; Rasoloarison, Rodin; Barrett, Meredith; Roos, Christian; Kappeler, Peter; Bielawski, Joseph; Yang, Ziheng

2014-01-01

Vomeronasal receptor genes have frequently been invoked as integral to the establishment and maintenance of species boundaries among mammals due to the elaborate one-to-one correspondence between semiochemical signals and neuronal sensory inputs. Here, we report the most extensive sample of vomeronasal receptor class 1 (V1R) sequences ever generated for a diverse yet phylogenetically coherent group of mammals, the tooth-combed primates (suborder Strepsirrhini). Phylogenetic analysis confirms our intensive sampling from a single V1R subfamily, apparently unique to the strepsirrhine primates. We designate this subfamily as V1Rstrep. The subfamily retains extensive repertoires of gene copies that descend from an ancestral gene duplication that appears to have occurred prior to the diversification of all lemuriform primates excluding the basal genus Daubentonia (the aye-aye). We refer to the descendent clades as V1Rstrep-α and V1Rstrep-β. Comparison of the two clades reveals different amino acid compositions corresponding to the predicted ligand-binding site and thus potentially to altered functional profiles between the two. In agreement with previous studies of the mouse lemur (genus, Microcebus), the majority of V1Rstrep gene copies appear to be intact and under strong positive selection, particularly within transmembrane regions. Finally, despite the surprisingly high number of gene copies identified in this study, it is nonetheless probable that V1R diversity remains underestimated in these nonmodel primates and that complete characterization will be limited until high-coverage assembled genomes are available. PMID:24398377

Is subjective social status a unique correlate of physical health? A meta-analysis.

Science.gov (United States)

Cundiff, Jenny M; Matthews, Karen A

2017-12-01

Both social stratification (e.g., social rank) as well as economic resources (e.g., income) are thought to contribute to socioeconomic health disparities. It has been proposed that subjective socioeconomic status (an individual's perception of his or her hierarchical rank) provides increased predictive utility for physical health over and above more traditional, well-researched socioeconomic constructs such as education, occupation, and income. PsycINFO and PubMed databases were systematically searched for studies examining the association of subjective socioeconomic status (SES) and physical health adjusting for at least 1 measure of objective SES. The final sample included 31 studies and 99 unique effects. Meta-analyses were performed to: (a) estimate the overlap among subjective and objective indicators of SES and (b) estimate the cumulative association of subjective SES with physical health adjusting for objective SES. Potential moderators such as race and type of health indicator assessed (global self-reports vs. more specific and biologically based indicators) were also examined. Across samples, subjective SES shows moderate overlap with objective indicators of SES, but associations are much stronger in Whites than Blacks. Subjective SES evidenced a unique cumulative association with physical health in adults, above and beyond traditional objective indicators of SES (Z = .07, SE = .01, p Subjective SES may provide unique information relevant to understanding disparities in health, especially self-rated health. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

North Carolina Geological Survey's role in siting a low-level radioactive (LLRW) waste disposal facility in North Carolina

International Nuclear Information System (INIS)

Reid, J.C.; Wooten, R.M.; Farrell, K.M.

1993-01-01

The Southeast Compact Commission in 1986 selected North Carolina to host the Southeast's LLRW disposal facility for the next twenty years. The North Carolina Geological Survey (NCGS) for six years has played a major role in the State's efforts by contributing to legislation and administrative code, policy, technical oversight and surveillance and regulation as a member of the State's regulatory team. Future activities include recommendation of the adequacy of characterization and site performance pursuant to federal code, state general statutes and administrative code, and review of a license application. Staff must be prepared to present testimony and professional conclusions in court. The NCGS provides technical advice to the Division of Radiation Protection (DRP), the regulatory agency which will grant or deny a LLRW license. The NCGS has not participated in screening the state for potential sites to minimize bias. The LLRW Management Authority, a separate state agency siting the LLRW facility, hired a contractor to characterize potential sites and to write a license application. Organizational relationships enable the NCGS to assist the DRP in its regulatory role without conflict of interest. Disposal facilities must be sited to ensure safe disposal of LLRW. By law, the siting of a LLRW disposal facility is primarily a geological, rather than an engineering, effort. Federal and State statutes indicate a site must be licensable on its own merits. Engineered barriers cannot make a site licensable. The project is 3 years behind schedule and millions of dollars over budget. This indicates the uncertainty and complexity inherent in siting such as facility, the outcome of which cannot be predicted until site characterization is complete, the license application reviewed and the performance assessment evaluated. State geological surveys are uniquely qualified to overview siting of LLRW facilities because of technical expertise and experience in the state's geology

Remediation management of complex sites using an adaptive site management approach.

Science.gov (United States)

Price, John; Spreng, Carl; Hawley, Elisabeth L; Deeb, Rula

2017-12-15

Complex sites require a disproportionate amount of resources for environmental remediation and long timeframes to achieve remediation objectives, due to their complex geologic conditions, hydrogeologic conditions, geochemical conditions, contaminant-related conditions, large scale of contamination, and/or non-technical challenges. A recent team of state and federal environmental regulators, federal agency representatives, industry experts, community stakeholders, and academia worked together as an Interstate Technology & Regulatory Council (ITRC) team to compile resources and create new guidance on the remediation management of complex sites. This article summarizes the ITRC team's recommended process for addressing complex sites through an adaptive site management approach. The team provided guidance for site managers and other stakeholders to evaluate site complexities and determine site remediation potential, i.e., whether an adaptive site management approach is warranted. Adaptive site management was described as a comprehensive, flexible approach to iteratively evaluate and adjust the remedial strategy in response to remedy performance. Key aspects of adaptive site management were described, including tools for revising and updating the conceptual site model (CSM), the importance of setting interim objectives to define short-term milestones on the journey to achieving site objectives, establishing a performance model and metrics to evaluate progress towards meeting interim objectives, and comparing actual with predicted progress during scheduled periodic evaluations, and establishing decision criteria for when and how to adapt/modify/revise the remedial strategy in response to remedy performance. Key findings will be published in an ITRC Technical and Regulatory guidance document in 2017 and free training webinars will be conducted. More information is available at www.itrc-web.org. Copyright © 2017 Elsevier Ltd. All rights reserved.